A classic way to get training data.
Researchers use crowdsourcing to speed up data analysis in corn plants
Iowa State University News Service By Fred Love
Iowa State University researchers used crowdsourcing to train a computer model to identify the tassels of corn plants from a vast number of photographic images. The crowdsourcing effort produced similar results to those of trained plant scientists and yielded an algorithm that the researchers say will greatly reduce the time it takes to derive useful metrics from massive datasets. The researchers used Amazon Mechanical Turk to find participants for the study, who received instructions to identify tassels in dozens of images of corn by drawing a square around them, and then used those labeled images to train a computer to identify tassels in similar corn images. The researchers said this approach could generate similar results for other types of plants. ... "
Friday, August 31, 2018
Uses of AI in Marketing
Some obvious, and some examples not so. Some are well known examples I would call analytics.
9 Applications Of Artificial Intelligence In Digital Marketing That Will Revolutionize Your Business
We’ve already posted articles on this topic before, like The Most Surprising Applications of Artificial Intelligence That You’ve Never Even Thought Of and 10 Artificial Intelligence Technologies That’ll Rule 2018. So now, the question we’re asking marketers is: How will artificial intelligence (AI) affect digital marketing in 2018?
A few years ago, marketers were somewhat reluctant to incorporate artificial intelligence (AI) in their digital marketing strategies. But this year they’ve gained a lot more confidence in using AI since its ambiguity has been reduced with respect to the results it can provide. These intelligent tools keep evolving more and more and are even reaching a point in which they are able to surpass humans in certain aspects like we’re about to see.
In a survey taken by over 1,600 professionals dedicated to marketing, 61% of those surveyed (without considering the size of their company) mentioned that both artificial intelligence and machine learning will be the most important data initiatives next year (source: MeMSQL).
Another survey by Salesforce indicated that 51% of marketers are already using AI, and 27% more are even planning on incorporating this technology in 2019. This represents the highest expected year-after-year growth of all emerging technologies that marketers are considering adopting next year, surpassing even the Internet of Things (IoT) and marketing automatization.
And, while the amount of information on potential consumers grows, computer sciences related to AI (like machine learning, deep learning and natural language processing [NPL]), will be of utmost importance when making data-based decisions.
We’ve carefully analyzed which AI applications are already revolutionizing the digital market, and you’ll definitely see more than one that probably never even crossed your mind… "
9 Applications Of Artificial Intelligence In Digital Marketing That Will Revolutionize Your Business
We’ve already posted articles on this topic before, like The Most Surprising Applications of Artificial Intelligence That You’ve Never Even Thought Of and 10 Artificial Intelligence Technologies That’ll Rule 2018. So now, the question we’re asking marketers is: How will artificial intelligence (AI) affect digital marketing in 2018?
A few years ago, marketers were somewhat reluctant to incorporate artificial intelligence (AI) in their digital marketing strategies. But this year they’ve gained a lot more confidence in using AI since its ambiguity has been reduced with respect to the results it can provide. These intelligent tools keep evolving more and more and are even reaching a point in which they are able to surpass humans in certain aspects like we’re about to see.
In a survey taken by over 1,600 professionals dedicated to marketing, 61% of those surveyed (without considering the size of their company) mentioned that both artificial intelligence and machine learning will be the most important data initiatives next year (source: MeMSQL).
Another survey by Salesforce indicated that 51% of marketers are already using AI, and 27% more are even planning on incorporating this technology in 2019. This represents the highest expected year-after-year growth of all emerging technologies that marketers are considering adopting next year, surpassing even the Internet of Things (IoT) and marketing automatization.
And, while the amount of information on potential consumers grows, computer sciences related to AI (like machine learning, deep learning and natural language processing [NPL]), will be of utmost importance when making data-based decisions.
We’ve carefully analyzed which AI applications are already revolutionizing the digital market, and you’ll definitely see more than one that probably never even crossed your mind… "
Insurance Companies Help Protect the Home
I was asked some time ago by a commercial insurance company if I though it would be useful to offer commonly available assistants that could be linked to home protection. Have been testing that now for several years. More and easy to use infrastructure and specific setup skills are still needed. And clear incentives for its use.
Notion IoT Sensors Let Homeowners Design Their Own Home Intelligence
Travelers Insurance is the latest insurance company to offer home monitoring from the technology startup, at a discounted rate so users can select what they want to monitor when they're away from home. By Claire Swedberg in RFID Journal
Aug 31, 2018—Traveler's Insurance is offering its clients a discount on Internet of Things (IoT) technology that enables them to track conditions within their home, automatically and remotely, at a cost of $50. The home-monitoring system is provided by technology company Notion. Travelers is one of a handful of insurance companies to provide the Notion system, which offers cloud-based wireless sensor data to automate homes.
The Notion Home Monitoring System leverages IoT technology consisting of multiple sensors that transmit data to a single hub that, in turn, uses a home's existing Wi-Fi network to forward the data to a cloud-based server. Users can then access or receive alerts regarding data from the sensors using a Notion app on their Android- or iOS-based devices.... "
Notion IoT Sensors Let Homeowners Design Their Own Home Intelligence
Travelers Insurance is the latest insurance company to offer home monitoring from the technology startup, at a discounted rate so users can select what they want to monitor when they're away from home. By Claire Swedberg in RFID Journal
Aug 31, 2018—Traveler's Insurance is offering its clients a discount on Internet of Things (IoT) technology that enables them to track conditions within their home, automatically and remotely, at a cost of $50. The home-monitoring system is provided by technology company Notion. Travelers is one of a handful of insurance companies to provide the Notion system, which offers cloud-based wireless sensor data to automate homes.
The Notion Home Monitoring System leverages IoT technology consisting of multiple sensors that transmit data to a single hub that, in turn, uses a home's existing Wi-Fi network to forward the data to a cloud-based server. Users can then access or receive alerts regarding data from the sensors using a Notion app on their Android- or iOS-based devices.... "
Shifting Decision Making
Quite a suggestion in the title of this piece, Will it, can it? Augment it in both areas enough to change the nature of decision?
Why AI Will Shift Decision Making from the C-Suite to the Front Line by Alessandro Di Fiore in HBR
Hardly a day goes by without the announcement of an incredible new frontier in Artificial Intelligence (AI). From fintech to edtech, what was once fantastically improbable is now a commercial reality. There is no question that big data and AI will bring about important advances in the realm of management, especially as it relates to being able to make better-informed decisions. But certain types of decisions — particularly those related to strategy, innovation and marketing — will likely continue to require a human being who can take a holistic view and make a qualitative judgment based on a personal consideration of the context and facts. In fact, to date, there is no AI technology that is fully able to factor in the emotional, human, and political context needed to automate decisions. .... "
Why AI Will Shift Decision Making from the C-Suite to the Front Line by Alessandro Di Fiore in HBR
Hardly a day goes by without the announcement of an incredible new frontier in Artificial Intelligence (AI). From fintech to edtech, what was once fantastically improbable is now a commercial reality. There is no question that big data and AI will bring about important advances in the realm of management, especially as it relates to being able to make better-informed decisions. But certain types of decisions — particularly those related to strategy, innovation and marketing — will likely continue to require a human being who can take a holistic view and make a qualitative judgment based on a personal consideration of the context and facts. In fact, to date, there is no AI technology that is fully able to factor in the emotional, human, and political context needed to automate decisions. .... "
Google Home Links with GE, Electrolux Appliances
Not unexpected, assistants interacting with common appliances. Rather than build your own smarts, make you appliances work with others. Back to creating and adding to existing infrastructures in the smart home.
GE and Electrolux kitchen appliances get helpful with Google Assistant support in Digitaltrends.
We could all use an assistant in the kitchen. While an actual helping hand might be a little too much to ask for, appliance makers GE and Electrolux are looking to help keep your hands free with the introduction of voice-command features that will integrate with Google Assistant.
According to GE, the company’s full line of Wi-Fi Connect appliances will welcome Google Assistant support in the future. That will make it easier for you to communicate with your internet-connected devices through Google’s voice-powered assistant service. The new support will simplify the command process, allowing you to say things like, “Hey, Google, preheat the oven to 425 degrees” and trust that the A.I. will take care of the task for you without requiring any additional input. .... "
GE and Electrolux kitchen appliances get helpful with Google Assistant support in Digitaltrends.
We could all use an assistant in the kitchen. While an actual helping hand might be a little too much to ask for, appliance makers GE and Electrolux are looking to help keep your hands free with the introduction of voice-command features that will integrate with Google Assistant.
According to GE, the company’s full line of Wi-Fi Connect appliances will welcome Google Assistant support in the future. That will make it easier for you to communicate with your internet-connected devices through Google’s voice-powered assistant service. The new support will simplify the command process, allowing you to say things like, “Hey, Google, preheat the oven to 425 degrees” and trust that the A.I. will take care of the task for you without requiring any additional input. .... "
Thursday, August 30, 2018
Getting Machines to Learn Like Children
Our own experiments in the area of machine learning, or even recognizing trivial patterns and repeating them when needed, were far more simple. Where does the challenge lie?
Growing a Mind in a Machine By Bennie Mols in CACM
"We are far from having any AI that can model the world as flexibly and as deeply as humans do, but we have at least one route to get there, and that is to reverse-engineer how these abilities work in the human mind and brain," says Massachusetts Institute of Technology cognitive scientist and artificial intelligence researcher Josh Tenenbaum.
A man with a stack of papers in his hands walks towards a closed cupboard. In the corner of the room, an 18-month-old boy is watching the scene from a corner of the room. The man bumps to the cupboard, takes a few steps back, tries again, and bumps against the closed doors a second time. The little boy leaves the corner, walks to the cupboard, and opens both cupboard doors; then he looks up to the man, who again walks towards the cupboard. As the boy gazes at the bookshelves, the man places the stack of papers on one of the shelves.
The video described above, titled "Experiments with altruism in children and chimps," was created during a psychological experiment by Massachusetts Institute of Technology (MIT) cognitive scientist and artificial intelligence researcher Josh Tenenbaum. He showed the video during his invited talk on "Building Machines that Learn and Think Like People" at IJCAI 2018, the 27th International Joint Conference on Artificial Intelligence, held in Stockholm, Sweden, in July. .... "
Growing a Mind in a Machine By Bennie Mols in CACM
"We are far from having any AI that can model the world as flexibly and as deeply as humans do, but we have at least one route to get there, and that is to reverse-engineer how these abilities work in the human mind and brain," says Massachusetts Institute of Technology cognitive scientist and artificial intelligence researcher Josh Tenenbaum.
A man with a stack of papers in his hands walks towards a closed cupboard. In the corner of the room, an 18-month-old boy is watching the scene from a corner of the room. The man bumps to the cupboard, takes a few steps back, tries again, and bumps against the closed doors a second time. The little boy leaves the corner, walks to the cupboard, and opens both cupboard doors; then he looks up to the man, who again walks towards the cupboard. As the boy gazes at the bookshelves, the man places the stack of papers on one of the shelves.
The video described above, titled "Experiments with altruism in children and chimps," was created during a psychological experiment by Massachusetts Institute of Technology (MIT) cognitive scientist and artificial intelligence researcher Josh Tenenbaum. He showed the video during his invited talk on "Building Machines that Learn and Think Like People" at IJCAI 2018, the 27th International Joint Conference on Artificial Intelligence, held in Stockholm, Sweden, in July. .... "
Kroger Creates Partnership with UC for Innovation
Note other partnerships methioned in the last paragraph such as with Centrifuse.
Kroger creates partnership to boost innovation in Winsight Grocery Business
Kroger will work with the University of Cincinnati to launch an innovation hub staffed with engineers and software developers. The hub's goals will be to create systems that improve the customer experience and to nurture tech talent, said Kroger executive ... Chris Hjelm.
Kroger to Open Innovation Center at University of Cincinnati
Restock-fueled initiative will provide creative space for developers to work with faculty, students
The Kroger Co. has revealed its plans to operate an innovation lab out of the University of Cincinnati (UC) in a move that company officials say is fueled by Restock Kroger.
Kroger plans to staff its lab, located in UC's new 1819 Innovation Hub, with research and development engineers and software developers who will work closely with UC faculty as well as student co-op members and interns.
Chris Hjelm, Kroger's EVP and chief information officer, said the effort is another way the company is investing to create the "now and future of retail," and it will provide the Kroger Technology team with a "creative space to partner and develop solutions to redefine the grocery customer experience."
"The 1819 Innovation Hub is a coworking community where we will build and discover the next generation of technology and talent," Hjelm said. "Our vision is to create a talent pipeline that supports our business and positions the region as a place for digital and technology students and professionals."
Additionally, Kroger Technology is partnering with the Cincinnati USA Regional Chamber's "Cincy Is IT" initiative to bring top tech experts into the area and support Cincinnati-based Cintrifuse, a public-private partnership that works to stimulate growth in the Midwest through innovation delivered by startups. .... "
By Rebekah Marcarelli
Kroger creates partnership to boost innovation in Winsight Grocery Business
Kroger will work with the University of Cincinnati to launch an innovation hub staffed with engineers and software developers. The hub's goals will be to create systems that improve the customer experience and to nurture tech talent, said Kroger executive ... Chris Hjelm.
Kroger to Open Innovation Center at University of Cincinnati
Restock-fueled initiative will provide creative space for developers to work with faculty, students
The Kroger Co. has revealed its plans to operate an innovation lab out of the University of Cincinnati (UC) in a move that company officials say is fueled by Restock Kroger.
Kroger plans to staff its lab, located in UC's new 1819 Innovation Hub, with research and development engineers and software developers who will work closely with UC faculty as well as student co-op members and interns.
Chris Hjelm, Kroger's EVP and chief information officer, said the effort is another way the company is investing to create the "now and future of retail," and it will provide the Kroger Technology team with a "creative space to partner and develop solutions to redefine the grocery customer experience."
"The 1819 Innovation Hub is a coworking community where we will build and discover the next generation of technology and talent," Hjelm said. "Our vision is to create a talent pipeline that supports our business and positions the region as a place for digital and technology students and professionals."
Additionally, Kroger Technology is partnering with the Cincinnati USA Regional Chamber's "Cincy Is IT" initiative to bring top tech experts into the area and support Cincinnati-based Cintrifuse, a public-private partnership that works to stimulate growth in the Midwest through innovation delivered by startups. .... "
By Rebekah Marcarelli
Business Process Modeling and Simulation
Been re-visiting a book I used long ago. I only have the first edition, but its still useful as an overview of the methods. Also a good intro to simulation. Not enough about topics like RPA to actually use the modeling results. Have not used later versions of ExtendSim. Too expensive in the second edition, but what else is new on textbooks.
Business Process Modeling, Simulation and Design 2nd Edition
by Manuel Laguna (Author), Johan Marklund
Most textbooks on business process management focus on either the nuts and bolts of computer simulation or the managerial aspects of business processes. Covering both technical and managerial aspects of business process management, Business Process Modeling, Simulation and Design, Second Edition presents the tools to design effective business processes and the management techniques to operate them efficiently.
New to the Second Edition
Three completely revised chapters that incorporate ExtendSim 8
An introduction to simulation
A chapter on business process analytics
Developed from the authors’ many years of teaching process design and simulation courses, the text provides students with a thorough understanding of numerous analytical tools that can be used to model, analyze, design, manage, and improve business processes. It covers a wide range of approaches, including discrete event simulation, graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, analytical queuing methods, and data mining. Unlike other operations management books, this one emphasizes user-friendly simulation software as well as business processes, rather than only manufacturing processes or general operations management problems.
Taking an analytical modeling approach to process design, this book illustrates the power of simulation modeling as a vehicle for analyzing and designing business processes. It teaches how to apply process simulation and discusses the managerial implications of redesigning processes. The ExtendSim software is available online and ancillaries are available for instructors. ... "
Business Process Modeling, Simulation and Design 2nd Edition
by Manuel Laguna (Author), Johan Marklund
Most textbooks on business process management focus on either the nuts and bolts of computer simulation or the managerial aspects of business processes. Covering both technical and managerial aspects of business process management, Business Process Modeling, Simulation and Design, Second Edition presents the tools to design effective business processes and the management techniques to operate them efficiently.
New to the Second Edition
Three completely revised chapters that incorporate ExtendSim 8
An introduction to simulation
A chapter on business process analytics
Developed from the authors’ many years of teaching process design and simulation courses, the text provides students with a thorough understanding of numerous analytical tools that can be used to model, analyze, design, manage, and improve business processes. It covers a wide range of approaches, including discrete event simulation, graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, analytical queuing methods, and data mining. Unlike other operations management books, this one emphasizes user-friendly simulation software as well as business processes, rather than only manufacturing processes or general operations management problems.
Taking an analytical modeling approach to process design, this book illustrates the power of simulation modeling as a vehicle for analyzing and designing business processes. It teaches how to apply process simulation and discusses the managerial implications of redesigning processes. The ExtendSim software is available online and ancillaries are available for instructors. ... "
Open Source Reinforcement Training
More open source resources here useful for training. The frameworks involved here are likely the most instructive part. And for tests to determine comparisons of speed and accuracy. Note also the criticism of reinforcement learning, while conceptually a very powerful idea, can be hard to calibrate for general problems.
Google releases open source reinforcement learning framework for training AI models
Kyle Wiggers @KYLE_L_WIGGERS in Venture Beat
Reinforcement learning — an artificial intelligence (AI) technique that uses rewards (or punishments) to drive agents in the direction of specific goals — trained the systems that defeated Alpha Go world champions and mastered Valve’s Dota 2. And it’s a core part of Google subsidiary DeepMind’s deep Q-network (DQN), which can distribute learning across multiple workers in the pursuit of, for example, achieving “superhuman” performance in Atari 2600 games. The trouble is, reinforcement learning frameworks take time to master a goal, tend to be inflexible, and aren’t always stable.
That’s why Google is proposing an alternative: an open source reinforcement framework based on TensorFlow, its machine learning library. It’s available from Github starting today. .... "
Google releases open source reinforcement learning framework for training AI models
Kyle Wiggers @KYLE_L_WIGGERS in Venture Beat
Reinforcement learning — an artificial intelligence (AI) technique that uses rewards (or punishments) to drive agents in the direction of specific goals — trained the systems that defeated Alpha Go world champions and mastered Valve’s Dota 2. And it’s a core part of Google subsidiary DeepMind’s deep Q-network (DQN), which can distribute learning across multiple workers in the pursuit of, for example, achieving “superhuman” performance in Atari 2600 games. The trouble is, reinforcement learning frameworks take time to master a goal, tend to be inflexible, and aren’t always stable.
That’s why Google is proposing an alternative: an open source reinforcement framework based on TensorFlow, its machine learning library. It’s available from Github starting today. .... "
Deep Learning for Time Series Forecasting
Like Jason's style of clear motivations and short tutorials. You can get free samples of his writing below.
Jason Brownlee's New Book:
Deep Learning for Time Series Forecasting
Predict the Future with MLPs, CNNs and LSTMs in Python
Deep Learning for Time Series Forecasting
$37 USD
Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality.
In this new Ebook written in the friendly Machine Learning Mastery style that you’re used to, finally cut through the math, research papers and patchwork descriptions about time series forecasting with deep learning algorithms.
With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.
About this Ebook:
Read on all devices: PDF format Ebook, no DRM.
Tons of tutorials: 5 parts, 25 step-by-step lessons, 575 pages.
Real-world projects: 2 large end-to-end tutorial projects.
Many datasets: Univariate, multivariate, multi-step, and more.
Working code: 131 Python (.py) code files included.
Clear, Complete End-to-End Examples.
Convinced? .... "
Jason Brownlee's New Book:
Deep Learning for Time Series Forecasting
Predict the Future with MLPs, CNNs and LSTMs in Python
Deep Learning for Time Series Forecasting
$37 USD
Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality.
In this new Ebook written in the friendly Machine Learning Mastery style that you’re used to, finally cut through the math, research papers and patchwork descriptions about time series forecasting with deep learning algorithms.
With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.
About this Ebook:
Read on all devices: PDF format Ebook, no DRM.
Tons of tutorials: 5 parts, 25 step-by-step lessons, 575 pages.
Real-world projects: 2 large end-to-end tutorial projects.
Many datasets: Univariate, multivariate, multi-step, and more.
Working code: 131 Python (.py) code files included.
Clear, Complete End-to-End Examples.
Convinced? .... "
Rehabilitation Robotics
Likely in combination with humans. Close observation of progress will still be required.
These Friendly Helpful Robots Will Likely Be Your Future Rehabilitation Partners By Interesting Engineering
Physical therapy with a socially assistive robot.
Socially assistive robots will be used increasingly in the future, according to researchers at Germany's Freiburg University.
A study by researchers at Freiburg University in Germany found that socially assistive robots (SARs) will be used increasingly in the future.
In response, the researchers outlined principles of effective SAR design to improve the technology's effectiveness.
SARs today typically are used to assist people with cognitive disabilities, people who require rehabilitation, and aging or elderly patients.
In a previous study, the researchers defined the most important components for effective SAR design as the robot's physical embodiment; personality; empathy; relative engagement with patients; adaptation (learning from an environment and quickly implementing those lessons), and transfer of long-term behavioral changes.
The researchers say those involved in SAR design must continue to discuss ways to improve the patient experience. ... "
These Friendly Helpful Robots Will Likely Be Your Future Rehabilitation Partners By Interesting Engineering
Physical therapy with a socially assistive robot.
Socially assistive robots will be used increasingly in the future, according to researchers at Germany's Freiburg University.
A study by researchers at Freiburg University in Germany found that socially assistive robots (SARs) will be used increasingly in the future.
In response, the researchers outlined principles of effective SAR design to improve the technology's effectiveness.
SARs today typically are used to assist people with cognitive disabilities, people who require rehabilitation, and aging or elderly patients.
In a previous study, the researchers defined the most important components for effective SAR design as the robot's physical embodiment; personality; empathy; relative engagement with patients; adaptation (learning from an environment and quickly implementing those lessons), and transfer of long-term behavioral changes.
The researchers say those involved in SAR design must continue to discuss ways to improve the patient experience. ... "
Wednesday, August 29, 2018
Combinatorial Testing Webinar
Combinatorial Testing
VIP Reminder: Register for September 6 ACM SIGSOFT Talk, "Combinatorial Testing: Progress in Automating Test Design"
Register now: https://event.on24.com/eventRegistration/EventLobbyServlet for the next free ACM SIGSOFT Learning Webinar,"Combinatorial Testing: Progress in Automating Test Design," presented on Thursday, September 6 at 12 PM ET by George Sherwood, founder and CEO of Testcover.com. Robert Dyer, Assistant Professor at Bowling Green State University will moderate the questions and answers session.
(If you'd like to attend but can't make it to the virtual event, you still need to register to receive a recording of the webinar when it becomes available.)
Combinatorial testing (CT) is a way to design software tests so that interactions among configuration settings and input values are covered by the test design. This webinar introduces CT, from its origins in design of experiments to its present role in verifying interactions in complex systems. A persistent CT usability challenge has been constraints among test factor values, which can cause some tests to be valid but others not. Research progress in managing constraints has enabled increased adoption among practicing software engineers, and better coverage of test interactions. Embedded functions technology allows functionally dependent relations among test factors to be defined as functions in a general purpose programming language. These relations enforce constraints among test factor values and insure that all valid combinations of determinant factors are available for the test design. Resulting usability improvements enable automated pairwise test designs to meet novel objectives: Cover equivalence classes of expected results; verify univariate and multivariate equivalence class boundaries; verify corners among intersecting boundaries and edges. ...
More here in the brochure, a good overview: : http://testcover.com/pub/brochure.pdf
VIP Reminder: Register for September 6 ACM SIGSOFT Talk, "Combinatorial Testing: Progress in Automating Test Design"
Register now: https://event.on24.com/eventRegistration/EventLobbyServlet for the next free ACM SIGSOFT Learning Webinar,"Combinatorial Testing: Progress in Automating Test Design," presented on Thursday, September 6 at 12 PM ET by George Sherwood, founder and CEO of Testcover.com. Robert Dyer, Assistant Professor at Bowling Green State University will moderate the questions and answers session.
(If you'd like to attend but can't make it to the virtual event, you still need to register to receive a recording of the webinar when it becomes available.)
Combinatorial testing (CT) is a way to design software tests so that interactions among configuration settings and input values are covered by the test design. This webinar introduces CT, from its origins in design of experiments to its present role in verifying interactions in complex systems. A persistent CT usability challenge has been constraints among test factor values, which can cause some tests to be valid but others not. Research progress in managing constraints has enabled increased adoption among practicing software engineers, and better coverage of test interactions. Embedded functions technology allows functionally dependent relations among test factors to be defined as functions in a general purpose programming language. These relations enforce constraints among test factor values and insure that all valid combinations of determinant factors are available for the test design. Resulting usability improvements enable automated pairwise test designs to meet novel objectives: Cover equivalence classes of expected results; verify univariate and multivariate equivalence class boundaries; verify corners among intersecting boundaries and edges. ...
More here in the brochure, a good overview: : http://testcover.com/pub/brochure.pdf
P&G to buy German Merck's consumer health unit for $4.2 billion
New directions for CPG healthcare. More at Reuters.
P&G to buy German Merck's consumer health unit for $4.2 billion
(Reuters) - Procter & Gamble Co (P&G) has agreed to acquire Merck KGaA’s consumer health unit for 3.4 billion euros ($4.2 billion), giving it vitamin brands such as Seven Seas and greater exposure to Latin American and Asian markets.
The maker of Pampers diapers and Gillette razors said the deal would help it expand its portfolio of consumer healthcare products which includes Vicks cold relief. ... "
P&G to buy German Merck's consumer health unit for $4.2 billion
(Reuters) - Procter & Gamble Co (P&G) has agreed to acquire Merck KGaA’s consumer health unit for 3.4 billion euros ($4.2 billion), giving it vitamin brands such as Seven Seas and greater exposure to Latin American and Asian markets.
The maker of Pampers diapers and Gillette razors said the deal would help it expand its portfolio of consumer healthcare products which includes Vicks cold relief. ... "
Open Spec for Hearing Aids
An Open standard for hearing aid manufacturers, the article says. Makes lots of sense.
Google working on native hearing aid support for an upcoming Android release By Abner Li
Today’s hearing aids increasingly overlap and share the same functionality as Bluetooth headphones. Google is now working to improve the experience on Android with native support through a new direct audio streaming specification coming in a future OS update.
Google announced a partnership with hearing aids manufacturer GN Hearing today to add direct audio streaming from Android to these assistive devices. In addition to their primary purpose of amplifying sounds, hearing aids will be able to essentially act as Bluetooth headphones. Wearers will be able to just use one device to hear the world, listen to music, take phone calls, and more ... "
Google working on native hearing aid support for an upcoming Android release By Abner Li
Today’s hearing aids increasingly overlap and share the same functionality as Bluetooth headphones. Google is now working to improve the experience on Android with native support through a new direct audio streaming specification coming in a future OS update.
Google announced a partnership with hearing aids manufacturer GN Hearing today to add direct audio streaming from Android to these assistive devices. In addition to their primary purpose of amplifying sounds, hearing aids will be able to essentially act as Bluetooth headphones. Wearers will be able to just use one device to hear the world, listen to music, take phone calls, and more ... "
Questions to Guide a Digital Transformation
Simple questions, would like to have more process detail to lead some goals, assume its in the book, but a good start.
What questions should guide a digital transformation? Knowledge@Wharton staff
Presented here for discussion is an excerpt of a current article published with permission from Knowledge@Wharton, the online research and business analysis journal of the Wharton School of the University of Pennsylvania.
A new book from MIT researchers Stephanie Woerner and Peter Weill offers a field-tested framework on how companies can digitally transform, based on a years-long study at the MIT Center for Information Systems Research.
The book, “What’s Your Digital Business Model,” is framed around six questions for companies and business leaders to consider:
What is the digital threat and opportunity?
Which business model is best for your enterprise’s future?
What is your digital competitive advantage?
How will you connect using mobile and IoT?
Do you have the crucial capabilities to reinvent the enterprise?
Do you have the leadership to make the transformation happen? ... "
What questions should guide a digital transformation? Knowledge@Wharton staff
Presented here for discussion is an excerpt of a current article published with permission from Knowledge@Wharton, the online research and business analysis journal of the Wharton School of the University of Pennsylvania.
A new book from MIT researchers Stephanie Woerner and Peter Weill offers a field-tested framework on how companies can digitally transform, based on a years-long study at the MIT Center for Information Systems Research.
The book, “What’s Your Digital Business Model,” is framed around six questions for companies and business leaders to consider:
What is the digital threat and opportunity?
Which business model is best for your enterprise’s future?
What is your digital competitive advantage?
How will you connect using mobile and IoT?
Do you have the crucial capabilities to reinvent the enterprise?
Do you have the leadership to make the transformation happen? ... "
Empowering Multimedia Search
Spent lots of time looking at how corporate files containing multimedia could be stored and effectively searched, and included in other systems. The emergence of AI image pattern recognition has started to enable this. Could produce some very useful systems.
OneDrive leans on A.I. to simplify searches for multimedia files in Digitaltrends
Microsoft is leaning on artificial intelligence to help you manage your files and make its OneDrive cloud storage system smarter. Microsoft 365 customers who use OneDrive and SharePoint will soon have access to a number of A.I.-enabled features making it easier to manage and search for multimedia files stored on Microsoft’s cloud.
“Today, we are announcing upcoming capabilities that, along with our recent investments, combine the power of artificial intelligence (A.I.) and machine learning with content stored in OneDrive and SharePoint to help you be more productive, make more informed decisions, and keep more secure,” Microsoft said in a blog post detailing the updates.
One of the big smart changes is that audio and video files stored on OneDrive and SharePoint will get automatic transcriptions. Microsoft says that it is using the same intelligence found on Microsoft Stream. With transcriptions, users can easily search through audio and video files and collaborate with others. Microsoft claims that the feature brings greater accessibility to users as well. ... "
OneDrive leans on A.I. to simplify searches for multimedia files in Digitaltrends
Microsoft is leaning on artificial intelligence to help you manage your files and make its OneDrive cloud storage system smarter. Microsoft 365 customers who use OneDrive and SharePoint will soon have access to a number of A.I.-enabled features making it easier to manage and search for multimedia files stored on Microsoft’s cloud.
“Today, we are announcing upcoming capabilities that, along with our recent investments, combine the power of artificial intelligence (A.I.) and machine learning with content stored in OneDrive and SharePoint to help you be more productive, make more informed decisions, and keep more secure,” Microsoft said in a blog post detailing the updates.
One of the big smart changes is that audio and video files stored on OneDrive and SharePoint will get automatic transcriptions. Microsoft says that it is using the same intelligence found on Microsoft Stream. With transcriptions, users can easily search through audio and video files and collaborate with others. Microsoft claims that the feature brings greater accessibility to users as well. ... "
IOT Revolutionizing Manufacturing
From IoTCentral.io
Here's How the IoT Is Revolutionizing Manufacturing
The internet of things (IoT) is much more than the next step in consumer technologies — it also represents a significant leap forward for industries of all kinds.
Manufacturing is already — and will continue to be — a field almost uniquely suited to applying IoT technology. In fact, there's almost no part of the process that won't be touched in some way by this ever-expanding web of smart and interconnected sensors, computers and machines. No matter how large or small your operation is, it's increasingly difficult to understate the potential value of adding intelligence and oversight to your processes using the internet of things.
Here are four ways IoT is revolutionizing the field of manufacturing.
A Greater Degree of Competitiveness
According to a report published by Verizon in 2016, an overwhelming majority of manufacturing managers already consider IoT technology a critical competitive advantage. It's hard to believe that such a sea change happened practically overnight, but not quite so much when you realize what's at stake.
Suffice it to say, the IoT represents a bundle of industrial innovations that have been a long time coming. Most of the competitive advantages cited by the Verizon report have to do with parts of the manufacturing and business processes that required guesswork or drew from incomplete data sets. We're talking things like altering business processes based on current demand and future trends, optimizing longstanding workflows and responding to unforeseen events.
Technology powered by the IoT can make manufacturing companies more competitive by, among other things, granting some autonomy and automation to back-end processes that inform the rest of your employee processes and workflows. This type of automation could, for example, automatically flag product for shipment to another location based on current levels or even trip a slowdown on one production line to pivot to another product if future demand isn't expected to be there.
The result is a leaner business that can run circles around your more flat-footed competition, who might've been slow to adopt modern technologies. ... "
Fill article.
Here's How the IoT Is Revolutionizing Manufacturing
The internet of things (IoT) is much more than the next step in consumer technologies — it also represents a significant leap forward for industries of all kinds.
Manufacturing is already — and will continue to be — a field almost uniquely suited to applying IoT technology. In fact, there's almost no part of the process that won't be touched in some way by this ever-expanding web of smart and interconnected sensors, computers and machines. No matter how large or small your operation is, it's increasingly difficult to understate the potential value of adding intelligence and oversight to your processes using the internet of things.
Here are four ways IoT is revolutionizing the field of manufacturing.
A Greater Degree of Competitiveness
According to a report published by Verizon in 2016, an overwhelming majority of manufacturing managers already consider IoT technology a critical competitive advantage. It's hard to believe that such a sea change happened practically overnight, but not quite so much when you realize what's at stake.
Suffice it to say, the IoT represents a bundle of industrial innovations that have been a long time coming. Most of the competitive advantages cited by the Verizon report have to do with parts of the manufacturing and business processes that required guesswork or drew from incomplete data sets. We're talking things like altering business processes based on current demand and future trends, optimizing longstanding workflows and responding to unforeseen events.
Technology powered by the IoT can make manufacturing companies more competitive by, among other things, granting some autonomy and automation to back-end processes that inform the rest of your employee processes and workflows. This type of automation could, for example, automatically flag product for shipment to another location based on current levels or even trip a slowdown on one production line to pivot to another product if future demand isn't expected to be there.
The result is a leaner business that can run circles around your more flat-footed competition, who might've been slow to adopt modern technologies. ... "
Fill article.
Puls Puts Technology Assistants in Homes
Not a bad idea. Though spanning the breadth of electrician to software may be hard to deal with. Never seen much of Geek squad in the Neighborhood, do they advertise that?
Puls Technologies raises $50 million to do tech support in your home By Dean Takahashi in VB
Puls Technologies has raised $50 million to grow its business that brings on-the-go technicians into
your home to perform tech support. In short, the San Francisco-based company is seeking to out-geek Geek Squad by fixing anything with an “on” switch.
Like retailer Best Buy’s Geek Squad, Puls sends technicians to your home to help you install or fix technology. But Puls isn’t tied to a single brand or type of tech, and it has a network of more than 2,500 vetted professionals operating as contractors in 50 metropolitan areas. They can be summoned to install or repair products such as smartphones, big screen TVs, HD antennas, garage door openers, and smart home devices, including voice-activated speakers, video door bells, keyless locks, AI cameras, smart thermostats, and security systems. The target is to fix 85 percent of problems within the allotted appointment time .... "
Puls Technologies raises $50 million to do tech support in your home By Dean Takahashi in VB
Puls Technologies has raised $50 million to grow its business that brings on-the-go technicians into
your home to perform tech support. In short, the San Francisco-based company is seeking to out-geek Geek Squad by fixing anything with an “on” switch.
Like retailer Best Buy’s Geek Squad, Puls sends technicians to your home to help you install or fix technology. But Puls isn’t tied to a single brand or type of tech, and it has a network of more than 2,500 vetted professionals operating as contractors in 50 metropolitan areas. They can be summoned to install or repair products such as smartphones, big screen TVs, HD antennas, garage door openers, and smart home devices, including voice-activated speakers, video door bells, keyless locks, AI cameras, smart thermostats, and security systems. The target is to fix 85 percent of problems within the allotted appointment time .... "
Tuesday, August 28, 2018
Cognitive Systems Talk: Machine Learning in a Snap
Invitation to the ISSIP Cognitive Systems Institute Group Webinar
Please join us for this call and invite your contacts - e.g., at universities, partners & clients. The call is in a series - and you can see the series here http://cognitive-science.info/community/weekly-update/
Talk Title: Machine Learning in a Snap August 30, 2018 - 10:30am US Eastern
Speaker: Thomas Parnell, IBM
Talk Description:
Generalized linear models, such as logistic regression and support vector machines, remain some of the most widely-used techniques in the machine learning field. Their enduring popularity can be attributed to their desirable theoretical properties, effective training algorithms, and relative ease of interpretability. In this talk we will introduce Snap Machine Learning: a new library for fast training of such models, that is designed to enable new real-time and large-scale applications. The library was designed from the ground up with performance in mind. It exploits parallelism at three different levels: across multiple machines in a network, across heterogeneous compute nodes within a machine (e.g. CPU and GPU), as well as the massive parallelism offered by modern GPUs. In this talk we will review this new architecture and give examples of how the library can be used via the various APIs that are provided (e.g. Python, Apache Spark, MPI). Finally, we will present benchmarking results using the publicly available Terabyte Click Logs dataset (from Criteo Labs) and show that Snap Machine Learning can train a logistic regression classifier in 1.53 minutes, 46x faster than any of the results that have been previously reported using the same dataset.
Bio:
Thomas received his B.Sc. and Ph.D. degrees in mathematics from the University of Warwick. U.K., in 2006 and 2011, respectively. He joined Arithmatica, Warwick, U.K., in 2005, where he was involved in FPGA design and electronic design automation. In 2007, he co-founded Siglead Europe, a U.K.-limited subsidiary of Yokohama-based Siglead Inc., where he was involved in developing signal processing and error-correction algorithms for HDD, flash, and emerging storage technologies. In 2013, he joined IBM Research in Zürich, Switzerland, where he is actively involved in the research and development of machine learning, compression and error-correction algorithms for IBM’s storage and AI products. His research interests include signal processing, information theory, machine learning and recommender systems.
Date and Time : August 30 2018 - 10:30am US Eastern
Zoom meeting Link: https://zoom.us/j/7371462221
Zoom Callin: (415) 762-9988 or (646) 568-7788 Meeting id 7371462221
Zoom International Numbers: https://zoom.us/zoomconference
(Check the website in case the date or time changes: http://cognitive-science.info/community/weekly-update/ )
Please retweet - https://twitter.com/sumalaika/status/1034299766266580992
Join LinkedIn Group https://www.linkedin.com/groups/6729452
Please join us for this call and invite your contacts - e.g., at universities, partners & clients. The call is in a series - and you can see the series here http://cognitive-science.info/community/weekly-update/
Talk Title: Machine Learning in a Snap August 30, 2018 - 10:30am US Eastern
Speaker: Thomas Parnell, IBM
Talk Description:
Generalized linear models, such as logistic regression and support vector machines, remain some of the most widely-used techniques in the machine learning field. Their enduring popularity can be attributed to their desirable theoretical properties, effective training algorithms, and relative ease of interpretability. In this talk we will introduce Snap Machine Learning: a new library for fast training of such models, that is designed to enable new real-time and large-scale applications. The library was designed from the ground up with performance in mind. It exploits parallelism at three different levels: across multiple machines in a network, across heterogeneous compute nodes within a machine (e.g. CPU and GPU), as well as the massive parallelism offered by modern GPUs. In this talk we will review this new architecture and give examples of how the library can be used via the various APIs that are provided (e.g. Python, Apache Spark, MPI). Finally, we will present benchmarking results using the publicly available Terabyte Click Logs dataset (from Criteo Labs) and show that Snap Machine Learning can train a logistic regression classifier in 1.53 minutes, 46x faster than any of the results that have been previously reported using the same dataset.
Bio:
Thomas received his B.Sc. and Ph.D. degrees in mathematics from the University of Warwick. U.K., in 2006 and 2011, respectively. He joined Arithmatica, Warwick, U.K., in 2005, where he was involved in FPGA design and electronic design automation. In 2007, he co-founded Siglead Europe, a U.K.-limited subsidiary of Yokohama-based Siglead Inc., where he was involved in developing signal processing and error-correction algorithms for HDD, flash, and emerging storage technologies. In 2013, he joined IBM Research in Zürich, Switzerland, where he is actively involved in the research and development of machine learning, compression and error-correction algorithms for IBM’s storage and AI products. His research interests include signal processing, information theory, machine learning and recommender systems.
Date and Time : August 30 2018 - 10:30am US Eastern
Zoom meeting Link: https://zoom.us/j/7371462221
Zoom Callin: (415) 762-9988 or (646) 568-7788 Meeting id 7371462221
Zoom International Numbers: https://zoom.us/zoomconference
(Check the website in case the date or time changes: http://cognitive-science.info/community/weekly-update/ )
Please retweet - https://twitter.com/sumalaika/status/1034299766266580992
Join LinkedIn Group https://www.linkedin.com/groups/6729452
Second Cashierless Store in Seattle
More testing of the cashier-less model, would seem to be an indication of success. Most interesting would be to see how shopper behavior differs in such a setting.
Amazon has a second Go at cashierless convenience store in downtown Seattle in Seattle Times
People who have visited the pilot store on the ground floor of an Amazon building will find largely the same experience at the new downtown store, near the Seattle Central Library, that opens Monday.
By Matt Day
The bright orange wrapping is coming off the new Amazon Go store in downtown Seattle, the first expansion of the cashierless convenience store outside Amazon’s corporate campus.... "
Amazon has a second Go at cashierless convenience store in downtown Seattle in Seattle Times
People who have visited the pilot store on the ground floor of an Amazon building will find largely the same experience at the new downtown store, near the Seattle Central Library, that opens Monday.
By Matt Day
The bright orange wrapping is coming off the new Amazon Go store in downtown Seattle, the first expansion of the cashierless convenience store outside Amazon’s corporate campus.... "
Publix Healthcare Kiosks
Worked at Publix in my early days. Later looked at how kiosks interact with consumers in Grocery.
Publix pioneers an easier way to see the doctor by Matthew Stern in Retailwire
Healthcare in the U.S. is changing, and retailers are offering a lot of services that once required a visit to a doctor’s office. As this new kind of healthcare takes shape, Publix has been exploring a new model that is showing signs of success.
As part of a collaboration with BayCare Health System, Publix began piloting healthcare kiosks in 12 Florida locations, according to The Ledger. The kiosks are enclosed in a private room where shoppers can teleconference with board-certified medical professionals to receive on-the-spot, non-urgent medical care. Customers enter their symptoms using a touch screen and then make use of tools provided in the room, such as thermometers, blood pressure cuffs and high-definition cameras, to give the doctor the data needed to make a diagnosis. One-thousand customers have used the service since the December 2017 launch. Publix will add kiosks to 13 stores in response to the success of the program.
Although addressing the inconvenience and high cost of arranging doctor visits for non-urgent concerns, seeing a patient via teleconference might pose some concerns. For instance, an accurate diagnosis could rely on the ability of an untrained patient to use equipment properly — and both the retailer and healthcare provider may face issues of liability. .. ."
Publix pioneers an easier way to see the doctor by Matthew Stern in Retailwire
Healthcare in the U.S. is changing, and retailers are offering a lot of services that once required a visit to a doctor’s office. As this new kind of healthcare takes shape, Publix has been exploring a new model that is showing signs of success.
As part of a collaboration with BayCare Health System, Publix began piloting healthcare kiosks in 12 Florida locations, according to The Ledger. The kiosks are enclosed in a private room where shoppers can teleconference with board-certified medical professionals to receive on-the-spot, non-urgent medical care. Customers enter their symptoms using a touch screen and then make use of tools provided in the room, such as thermometers, blood pressure cuffs and high-definition cameras, to give the doctor the data needed to make a diagnosis. One-thousand customers have used the service since the December 2017 launch. Publix will add kiosks to 13 stores in response to the success of the program.
Although addressing the inconvenience and high cost of arranging doctor visits for non-urgent concerns, seeing a patient via teleconference might pose some concerns. For instance, an accurate diagnosis could rely on the ability of an untrained patient to use equipment properly — and both the retailer and healthcare provider may face issues of liability. .. ."
What HBR Gets Wrong About Algorithms
I linked to the HBR article here, this reply is thoughtful ...
What HBR gets wrong about algorithms and bias in O'Reilly
The Harvard Business Review recently published an article, "Want Less-Biased Decisions? Use Algorithms," focusing on the fact that humans make biased decisions. Absolutely true, says Rachel Thomas, but the article ignores many important issues. Here's Rachel's response to the article. ...."
What HBR gets wrong about algorithms and bias in O'Reilly
The Harvard Business Review recently published an article, "Want Less-Biased Decisions? Use Algorithms," focusing on the fact that humans make biased decisions. Absolutely true, says Rachel Thomas, but the article ignores many important issues. Here's Rachel's response to the article. ...."
No Touch Planning: Human Error and Supply Chains
Remember that planning means predicting, forecasting and analyzing risk in context
The route to no-touch planning: Taking the human error out of supply-chain planning
Slow, manual supply-chain planning processes can be a thing of the past, with machines taking on repetitive tasks that aren’t a good use of human capacity.
The route to no-touch planning: Taking the human error out of supply-chain planning
By Ignacio Felix, Christoph Kuntze, Ildefonso Silva, and Eduardo Tobias Benoliel in McKinsey
Slow, manual supply-chain planning processes can be a thing of the past, with machines taking on repetitive tasks that aren’t a good use of human capacity.
Supply-chain planning keeps getting harder and more time-consuming, with the consumer goods sector as one of the most extreme examples. The causes are familiar: Online retailing’s endless shelf encourages consumers to be ever more demanding, yielding product portfolios that are ever more complex and lifecycles that are ever shorter. Retailers continue to increase their service and delivery requirements, with stiff financial penalties for non-compliance. On the flip side, more and more real-time data are becoming available, with automation technology rapidly getting cheaper, more capable, and easier to implement—raising the competitive bar for the entire sector.
Traditional planning processes and tools weren’t designed either to take advantage of technology’s advances or to address the demands it creates. By and large, planning still relies heavily on labor-intensive data aggregation and cleaning, manual analysis, and personal judgment. Worse, with more customer and consumer demand signals now available instantaneously, planners often feel compelled to keep tweaking their plans, despite the weaknesses of existing planning systems and processes. Well-intentioned adjustments end up creating more problems than they solve, introducing even more errors and subconscious bias that can increase costs and exacerbate service disruptions. .... "
Blurring the Lines Between Virtual and Reality
In EPFL News. Could be a way to transfer gaming, and thus gaming engagement to real spaces. Say offices, but perhaps also to industrial spaces. Possible then also for use with data, or analytic solutions to data. We examined some possibilities related to this before tech existed. Note also the real-time aspects of such interactions.
Blurring the Lines Between Virtual and Reality
Swiss Federal Institute of Technology in Lausanne
A next-generation virtual reality (VR) headset created by Hugo Hueber at the Swiss Federal Institute of Technology in Lausanne, Switzerland (EPFL) enables wearers to manipulate both real and virtual objects with tactile sensations, using hand avatars that replicate even the slightest movements. Hueber says an enhanced VR video game he is designing "combines the latest technology with the [three-dimensional] interactive research we're carrying out at the lab. That will let video gamers interact physically with a virtual environment that can be transferred to any location—a living room, office, or even classroom—instantly." Real-world objects are modeled and calibrated in the game, and then players can use them at the same time they physically touch them. In addition, players can see and precisely move virtual versions of fingers, and wear bodily sensors to see themselves move within the game in real time. ... "
Blurring the Lines Between Virtual and Reality
Swiss Federal Institute of Technology in Lausanne
A next-generation virtual reality (VR) headset created by Hugo Hueber at the Swiss Federal Institute of Technology in Lausanne, Switzerland (EPFL) enables wearers to manipulate both real and virtual objects with tactile sensations, using hand avatars that replicate even the slightest movements. Hueber says an enhanced VR video game he is designing "combines the latest technology with the [three-dimensional] interactive research we're carrying out at the lab. That will let video gamers interact physically with a virtual environment that can be transferred to any location—a living room, office, or even classroom—instantly." Real-world objects are modeled and calibrated in the game, and then players can use them at the same time they physically touch them. In addition, players can see and precisely move virtual versions of fingers, and wear bodily sensors to see themselves move within the game in real time. ... "
Monday, August 27, 2018
Enabling Reliable Data science and ML Projects
By my own experience, agreed. Enterprise Data Science is rarely done very carefully, leading it open to error.
Enabling reliable, secure collaboration on data science and machine learning projects A conversation with Paul Taylor, chief architect in Watson Data and AI, and IBM fellow.
By Frank Kane O'Reilly Conference Jupyter
Machine learning researchers often prototype new ideas using Jupyter, Scala, or R Studio notebooks, which is a great way for individuals to experiment and share their results. But in an enterprise setting, individuals cannot work in isolation—many developers, perhaps from different departments, need to collaborate on projects simultaneously, and securely. I recently spoke with IBM’s Paul Taylor to find out how IBM Watson Studio is scaling machine learning to enterprise-level, collaborative projects.
First, a bit of background about Taylor. He has enjoyed a distinguished career at IBM over the past 17 years, where he started off working on Db2 and Informix, and working with big data and unstructured data well before those fields exploded. He has held many titles working in different technology areas as a distinguished engineer, chief architect, master inventor, CTO, and this year was appointed as an IBM Fellow.
Today, Taylor leads the technology of IBM Watson data and AI components, where he is exploring the convergence of data, AI, and public cloud with IBM Watson Studio. Watson Studio provides a suite of tools for data scientists, application developers, and subject matter experts to collaborate and work with data to conduct analytics and data science, and to build, train, and deploy models at scale.
Frank Kane: Why is better collaboration in data science important? What sorts of opportunities do you see it creating for real-world developers and businesses?
Paul Taylor: A lot of times I go in to talk to C-suite folks who are running the data science teams. They're in a real challenge because, traditionally, many of those clients and the scientists are using their own little tools, and they may be very sophisticated tools, or they may be very naïve ones. They're all working in silos, and they're using their own tools in their own way. ... "
Enabling reliable, secure collaboration on data science and machine learning projects A conversation with Paul Taylor, chief architect in Watson Data and AI, and IBM fellow.
By Frank Kane O'Reilly Conference Jupyter
Machine learning researchers often prototype new ideas using Jupyter, Scala, or R Studio notebooks, which is a great way for individuals to experiment and share their results. But in an enterprise setting, individuals cannot work in isolation—many developers, perhaps from different departments, need to collaborate on projects simultaneously, and securely. I recently spoke with IBM’s Paul Taylor to find out how IBM Watson Studio is scaling machine learning to enterprise-level, collaborative projects.
First, a bit of background about Taylor. He has enjoyed a distinguished career at IBM over the past 17 years, where he started off working on Db2 and Informix, and working with big data and unstructured data well before those fields exploded. He has held many titles working in different technology areas as a distinguished engineer, chief architect, master inventor, CTO, and this year was appointed as an IBM Fellow.
Today, Taylor leads the technology of IBM Watson data and AI components, where he is exploring the convergence of data, AI, and public cloud with IBM Watson Studio. Watson Studio provides a suite of tools for data scientists, application developers, and subject matter experts to collaborate and work with data to conduct analytics and data science, and to build, train, and deploy models at scale.
Frank Kane: Why is better collaboration in data science important? What sorts of opportunities do you see it creating for real-world developers and businesses?
Paul Taylor: A lot of times I go in to talk to C-suite folks who are running the data science teams. They're in a real challenge because, traditionally, many of those clients and the scientists are using their own little tools, and they may be very sophisticated tools, or they may be very naïve ones. They're all working in silos, and they're using their own tools in their own way. ... "
A Look at Smart Home Market
New look at the direction of Smart Homes. But it does depend upon how your define a smart home. Mine is still quite simple in what it includes,would it be defined as such?
Smart Home Market Analysis – Expectations vs. Reality
Hagai Shaham
All eyes were on the smart home market in 2017. After all, industry experts such as MarketsandMarkets predicted that the industry would be valued at to$137.91B by 2023, growing at a CAGR of 13.61%. Tech giants are all clamoring to get in on the action with Google Home, Apple HomeKit, Amazon Echo and Samsung SmartThings creating buzz, and new smart devices flooding the market at a dizzying rate.
However, despite these high expectations, smart home adoption has been slower than anticipated. While the connected home market is growing steadily, it certainly has not exploded. In fact, according to PwC’s 2017 consumer study of the IoT and the connected home, while 81% of consumers are aware of smart technology, only 26% actually own a smart device. Moreover, 68% of consumers reported that they are not very excited about the future of smart home tech in their daily life. Worse, the study found that 30% of consumers are not fully satisfied with their device or mobile app supporting their device.
What went wrong in the trajectory of smart home adoption, and why did so many experts miss the mark? .... "
Smart Home Market Analysis – Expectations vs. Reality
Hagai Shaham
All eyes were on the smart home market in 2017. After all, industry experts such as MarketsandMarkets predicted that the industry would be valued at to$137.91B by 2023, growing at a CAGR of 13.61%. Tech giants are all clamoring to get in on the action with Google Home, Apple HomeKit, Amazon Echo and Samsung SmartThings creating buzz, and new smart devices flooding the market at a dizzying rate.
However, despite these high expectations, smart home adoption has been slower than anticipated. While the connected home market is growing steadily, it certainly has not exploded. In fact, according to PwC’s 2017 consumer study of the IoT and the connected home, while 81% of consumers are aware of smart technology, only 26% actually own a smart device. Moreover, 68% of consumers reported that they are not very excited about the future of smart home tech in their daily life. Worse, the study found that 30% of consumers are not fully satisfied with their device or mobile app supporting their device.
What went wrong in the trajectory of smart home adoption, and why did so many experts miss the mark? .... "
Zippin Combines SmartShelves and Cameras
Zippin with another approach to 'no checkout', but with claims of combining shelf and camera sensors to increase accuracy. Note also the SRI connection, who we also talked to about shelf tech.
Can Zippin zip past where Amazon Go is going? by Matthew Stern in Retailwire with expert commentary.
With only two Amazon Go stores live (the second having just opened this morning, according to KIRO news), there’s still plenty of room for the great disruptor to be disrupted. San Francisco-based Zippin hopes to be the checkout-free grocer that just walks in and wins at “just walk out.”
Zippin, founded by industry veterans from Amazon and SRI, opened a “just walk out”-enabled concept store in San Francisco’s SOMA neighborhood. In a statement, Zippin notes that while early approaches to autonomous shopping have relied solely on cameras to track purchases, its technology uses a combination of overhead cameras and smart shelf sensors for a higher level of accuracy.
Zippin said in a statement, “Cameras and smart shelf sensors track when and which products are picked up or put back. Combining these two inputs allows Zippin to place the right items in the right shoppers’ virtual carts.”
The start-up said its approach stands out for its ability to work accurately even in a crowded store.
Zippin is marketing its solution, which integrates its own software with readily available hardware, for other grocers to deploy. ... "
Can Zippin zip past where Amazon Go is going? by Matthew Stern in Retailwire with expert commentary.
With only two Amazon Go stores live (the second having just opened this morning, according to KIRO news), there’s still plenty of room for the great disruptor to be disrupted. San Francisco-based Zippin hopes to be the checkout-free grocer that just walks in and wins at “just walk out.”
Zippin, founded by industry veterans from Amazon and SRI, opened a “just walk out”-enabled concept store in San Francisco’s SOMA neighborhood. In a statement, Zippin notes that while early approaches to autonomous shopping have relied solely on cameras to track purchases, its technology uses a combination of overhead cameras and smart shelf sensors for a higher level of accuracy.
Zippin said in a statement, “Cameras and smart shelf sensors track when and which products are picked up or put back. Combining these two inputs allows Zippin to place the right items in the right shoppers’ virtual carts.”
The start-up said its approach stands out for its ability to work accurately even in a crowded store.
Zippin is marketing its solution, which integrates its own software with readily available hardware, for other grocers to deploy. ... "
Keynote Talk on Democratizing Data
Useful overview of the idea.
Democratizing data Keynote from the O'Reilly conference
Tracy Teal explains how to bring people to data and empower them to address their questions.
Tracy Teal is a co-founder and the Executive Director of Data Carpentry. She received her PhD in Computation and Neural Systems from California Institute of Technology and was an NSF Postdoctoral Researcher in Biological Informatics. She worked at Michigan State University as a Research Specialist with the Institute for Cyber-Enabled Research and then as an Assistant Professor in Microbiology. While an assistant professor, she saw researchers' need for effective data skills to effectively and reproducibly conduct research and co-founded Data Carpentry to scale data training along with data production. She is involved in the open source software and reproducible research communities, including as an Editor at the Journal for Open Source Software. ... "
Democratizing data Keynote from the O'Reilly conference
Tracy Teal explains how to bring people to data and empower them to address their questions.
Tracy Teal is a co-founder and the Executive Director of Data Carpentry. She received her PhD in Computation and Neural Systems from California Institute of Technology and was an NSF Postdoctoral Researcher in Biological Informatics. She worked at Michigan State University as a Research Specialist with the Institute for Cyber-Enabled Research and then as an Assistant Professor in Microbiology. While an assistant professor, she saw researchers' need for effective data skills to effectively and reproducibly conduct research and co-founded Data Carpentry to scale data training along with data production. She is involved in the open source software and reproducible research communities, including as an Editor at the Journal for Open Source Software. ... "
More Background Information on IOTA
Good, short, largely non-technical view of IOTA method vs Blockchain
IOTA - David Sonstebo (IOTA Co-Founder) Interview | Part 1/4 - 4.4
How to install Wallet & buy IOTA: https://iota-support.com
IOTA Guide & FAQ | Step by step Tutorials with pictures!
1.) How to install IOTA wallet: https://bit.ly/2MkJImm
2.) How to create an account & login: https://bit.ly/2BkKwTl
3.) How to buy IOTA: https://bit.ly/2Buy5UK
4.) How to receive a transaction: https://bit.ly/2MvnAoN
5.) How to send a transaction: https://bit.ly/2vV0uyp
-------
Follow IOTA-Support.com on Twitter: https://twitter.com/Iota_Support
IOTA - David Sonstebo (IOTA Co-Founder) Interview | Part 1/4 - 4.4
How to install Wallet & buy IOTA: https://iota-support.com
IOTA Guide & FAQ | Step by step Tutorials with pictures!
1.) How to install IOTA wallet: https://bit.ly/2MkJImm
2.) How to create an account & login: https://bit.ly/2BkKwTl
3.) How to buy IOTA: https://bit.ly/2Buy5UK
4.) How to receive a transaction: https://bit.ly/2MvnAoN
5.) How to send a transaction: https://bit.ly/2vV0uyp
-------
Follow IOTA-Support.com on Twitter: https://twitter.com/Iota_Support
Sunday, August 26, 2018
What and Why are ARCH and GARCH?
When you do time series forecasting you almost always get changes in variance over time. Sometimes enough to invalidate your decisions and conclusions. We used these methods in key ways to produce better results over time. Somehow I rarely hear these methods mentioned recently. Here Jason Brownlee provides a good Python based intro. Fairly non-technical, but coding based.
How to Model Volatility with ARCH and GARCH for Time Series Forecasting in Python by Jason Brownlee in Time Series
A change in the variance or volatility over time can cause problems when modeling time series with classical methods like ARIMA.
The ARCH or Autoregressive Conditional Heteroskedasticity method provides a way to model a change in variance in a time series that is time dependent, such as increasing or decreasing volatility. An extension of this approach named GARCH or Generalized Autoregressive Conditional Heteroskedasticity allows the method to support changes in the time dependent volatility, such as increasing and decreasing volatility in the same series.
In this tutorial, you will discover the ARCH and GARCH models for predicting the variance of a time series.
After completing this tutorial, you will know:
The problem with variance in a time series and the need for ARCH and GARCH models.
How to configure ARCH and GARCH models.
How to implement ARCH and GARCH models in Python.
Let’s get started. .... "
How to Model Volatility with ARCH and GARCH for Time Series Forecasting in Python by Jason Brownlee in Time Series
A change in the variance or volatility over time can cause problems when modeling time series with classical methods like ARIMA.
The ARCH or Autoregressive Conditional Heteroskedasticity method provides a way to model a change in variance in a time series that is time dependent, such as increasing or decreasing volatility. An extension of this approach named GARCH or Generalized Autoregressive Conditional Heteroskedasticity allows the method to support changes in the time dependent volatility, such as increasing and decreasing volatility in the same series.
In this tutorial, you will discover the ARCH and GARCH models for predicting the variance of a time series.
After completing this tutorial, you will know:
The problem with variance in a time series and the need for ARCH and GARCH models.
How to configure ARCH and GARCH models.
How to implement ARCH and GARCH models in Python.
Let’s get started. .... "
Seeking Stages of Smart
Great piece in DSC about 'creating smart'. What does it mean, anyway? To begin with we are doing lots of misusing of the term, since it includes intention and embedding with context. Here is the prologue, rest at the link:
3 Stages of Creating Smart in DSC Posted by Bill Schmarzo
“Tomorrow’s market winners will win with the smartest products. It’s not enough to just build insanely great products; winners must have the smartest products!” – Bill Schmarzo
Okay, that’s a pretty bold statement on my part (especially to challenge the famous Steve Jobs statement about building insanely great products), but then again I’m an analytics dude and think that analytics should be a part of every product and space – smart cities, smart cars, smart vacuums, smart hospitals, smart Chipotle…
But it’s not just me that thinks this way. Tesla’s forthcoming autonomous cars will be nothing more than an artificial intelligence machine on wheels. Tesla is building its own “AI computer”, complete with Tesla-specific microprocessors (silicon), to power its autonomous vehicles (see “Tesla Earnings Bombshell Reminds Us That Tesla's a Tech Company” for more details). And Google is creating the foundation for smart products with its new Edge TPU; a tiny AI accelerator that will carry out machine learning jobs “at the edge” of IoT (see “Google unveils tiny new AI chips for on-device machine learning” for more details).
The technology is advancing at a pace that should enable any company to create “smart” products, things and spaces. But how does one go about actually creating smart? How does one decide where and how to integrate the growing power of machine learning, deep learning and artificial intelligence capabilities to power these smart products?
Here’s my three step recipe for “Getting Smart” (with images of Maxwell Smart dancing in my head).
Step 1: Identify, Validate, Value and Prioritize the Decisions that Power “Smart”
The first step in “Getting Smart” involves identifying, validating, vetting, valuing and prioritizing the decisions[1](or use cases) that the smart entity or product needs to make in support of its operational goals. For example, a “smart” city initiative would need to optimize decisions around traffic congestion, local events, crime, safety, road maintenance, building permits and more (see Figure 1). ... "
3 Stages of Creating Smart in DSC Posted by Bill Schmarzo
“Tomorrow’s market winners will win with the smartest products. It’s not enough to just build insanely great products; winners must have the smartest products!” – Bill Schmarzo
Okay, that’s a pretty bold statement on my part (especially to challenge the famous Steve Jobs statement about building insanely great products), but then again I’m an analytics dude and think that analytics should be a part of every product and space – smart cities, smart cars, smart vacuums, smart hospitals, smart Chipotle…
But it’s not just me that thinks this way. Tesla’s forthcoming autonomous cars will be nothing more than an artificial intelligence machine on wheels. Tesla is building its own “AI computer”, complete with Tesla-specific microprocessors (silicon), to power its autonomous vehicles (see “Tesla Earnings Bombshell Reminds Us That Tesla's a Tech Company” for more details). And Google is creating the foundation for smart products with its new Edge TPU; a tiny AI accelerator that will carry out machine learning jobs “at the edge” of IoT (see “Google unveils tiny new AI chips for on-device machine learning” for more details).
The technology is advancing at a pace that should enable any company to create “smart” products, things and spaces. But how does one go about actually creating smart? How does one decide where and how to integrate the growing power of machine learning, deep learning and artificial intelligence capabilities to power these smart products?
Here’s my three step recipe for “Getting Smart” (with images of Maxwell Smart dancing in my head).
Step 1: Identify, Validate, Value and Prioritize the Decisions that Power “Smart”
The first step in “Getting Smart” involves identifying, validating, vetting, valuing and prioritizing the decisions[1](or use cases) that the smart entity or product needs to make in support of its operational goals. For example, a “smart” city initiative would need to optimize decisions around traffic congestion, local events, crime, safety, road maintenance, building permits and more (see Figure 1). ... "
LG Innovation in Appliances
Been a while since I monitored appliances, but their continued evolution as part of the smart home remains interesting. Quite a detailed piece with overview of many innovative explorations and with lots of images.
How LG built its Signature appliances to solve problems you didn’t know you had
The task put before LG’s appliance research and design team was as unusual as it was daunting: Create a window for a refrigerator that goes from black to see-through when you knock on it. Make it stylish. Oh, and because it’s going to be placed in a refrigerator, of course it needs to withstand extreme temperatures.
For LG research engineer Youngkwen Kim, that last one was the biggest sticking point: Cold inside, warm outside, and a thin profile meant the first versions of the window would sweat like a cold can of Coke.
“The goal was to maintain overall design, but still, function has to be followed,” Kim explained to Digital Trends through a translator during a recent trip this publication took to South Korea. “The biggest challenge was the condensation of that glass door.”.... '
How LG built its Signature appliances to solve problems you didn’t know you had
The task put before LG’s appliance research and design team was as unusual as it was daunting: Create a window for a refrigerator that goes from black to see-through when you knock on it. Make it stylish. Oh, and because it’s going to be placed in a refrigerator, of course it needs to withstand extreme temperatures.
For LG research engineer Youngkwen Kim, that last one was the biggest sticking point: Cold inside, warm outside, and a thin profile meant the first versions of the window would sweat like a cold can of Coke.
“The goal was to maintain overall design, but still, function has to be followed,” Kim explained to Digital Trends through a translator during a recent trip this publication took to South Korea. “The biggest challenge was the condensation of that glass door.”.... '
Podcast, Book: Applied Empathy
Empathy is always a good idea, with customers, clients and colleagues. But how is it best applied?
Author Michael Ventura talks about his book, 'Applied Empathy. From K@W
Michael Ventura is quick to dismiss the notion that empathy is some touchy-feely emotion that makes leaders seem soft. In business, he argues, empathy is what can help a company vanquish the competition, gain loyal customers, retain innovative employees and elevate itself from good to great. Ventura, founder and CEO of strategy and design studio Sub Rosa, has put the lessons he’s learned from working with major brands into a book titled, Applied Empathy: The New Language of Leadership. He recently joined the Knowledge@Wharton show on SiriusXM to discuss why this particular emotion is becoming paramount in the business world.
An edited transcript of the conversation follows.
Knowledge@Wharton: When did you start to see empathy as an important element in leadership?
Michael Ventura: I think that it really was a slow burn for us. It wasn’t a thunderclap kind of moment. We went back and looked at about five years’ worth of work that we had developed and asked, what made all of this work well? Why was this work landing for our clients in such a way? When we dug into it deeply, we started to see it’s not about sitting in a room and shutting the door and getting high on your own supply. It was when we got out of the building, got into the minds of the people we were trying to reach and really took their perspective, really got into their shoes and saw the world from their standpoint. When we did that and brought that insight back, the work got exponentially better. We latched on to it at that point and started to make a practice and a methodology around it. ... "
Author Michael Ventura talks about his book, 'Applied Empathy. From K@W
Michael Ventura is quick to dismiss the notion that empathy is some touchy-feely emotion that makes leaders seem soft. In business, he argues, empathy is what can help a company vanquish the competition, gain loyal customers, retain innovative employees and elevate itself from good to great. Ventura, founder and CEO of strategy and design studio Sub Rosa, has put the lessons he’s learned from working with major brands into a book titled, Applied Empathy: The New Language of Leadership. He recently joined the Knowledge@Wharton show on SiriusXM to discuss why this particular emotion is becoming paramount in the business world.
An edited transcript of the conversation follows.
Knowledge@Wharton: When did you start to see empathy as an important element in leadership?
Michael Ventura: I think that it really was a slow burn for us. It wasn’t a thunderclap kind of moment. We went back and looked at about five years’ worth of work that we had developed and asked, what made all of this work well? Why was this work landing for our clients in such a way? When we dug into it deeply, we started to see it’s not about sitting in a room and shutting the door and getting high on your own supply. It was when we got out of the building, got into the minds of the people we were trying to reach and really took their perspective, really got into their shoes and saw the world from their standpoint. When we did that and brought that insight back, the work got exponentially better. We latched on to it at that point and started to make a practice and a methodology around it. ... "
Sankey Diagrams, Generation and Code
Quantum Simulation from D-Wave
Been watching D-Wave closely through advances and challenges, since their inception, here another advance, in particular linking to material science.
D-Wave Demonstrates First Large-Scale Quantum Simulation of Topological State of Matter From Inside HPC
D-Wave Systems researchers have demonstrated a topological phase transition using a 2048-quantum bit (qubit) annealing quantum computer, a complex quantum simulation of materials that marks a major step toward reducing the need for time-consuming physical research and development. The team says the techniques used in this work could have far-reaching implications in the development of novel materials. D-Wave's Mohammad Amin says this breakthrough represents the first theoretically predicted state of matter to be realized in quantum simulation before being demonstrated in a real magnetic material. ...
D-Wave Demonstrates First Large-Scale Quantum Simulation of Topological State of Matter From Inside HPC
D-Wave Systems researchers have demonstrated a topological phase transition using a 2048-quantum bit (qubit) annealing quantum computer, a complex quantum simulation of materials that marks a major step toward reducing the need for time-consuming physical research and development. The team says the techniques used in this work could have far-reaching implications in the development of novel materials. D-Wave's Mohammad Amin says this breakthrough represents the first theoretically predicted state of matter to be realized in quantum simulation before being demonstrated in a real magnetic material. ...
Home Robots that Hug You
With some connections to other 'family' home robots, that claim to be family friendly. By taking it further to the tactile level. We examined work going in in Japan that aimed to take this to eldercare applications. With assistant style voice systems we can imagine warmth and friendliness, now can we take that further? On to the hug .. And we note that the Kuri is no longer, and though family friendly made no claim to 'hug'. ...
Home Robots that Hug You in DigitalTrends
Forget Roomba, your most important house robot could be the one that hugs you By Luke Dormehl
Sure, so Alexa can play you the right song at the right time, and Google’s Duplex tech means you never need to phone up and book a restaurant again, but our relationship with machines still has the non-tactile frigidity of an unhappy marriage. However, that could all change thanks to work coming out of the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. Researchers there have been developing a robot that is designed for giving you a hug. And, far from an amusing gimmick, they are convinced that it’s really important.
“A robot hugging a person is a good idea because people may crave the benefits that come from a hug at a time when they can’t get a hug from a person, due to factors such as distance, timing, and health,” Alexis Block, one of the lead researchers on the HuggieBot project, told Digital Trends. “We think a hugging robot could be beneficial in this case because a person can get the support they need without feeling self-conscious.” ... '
Home Robots that Hug You in DigitalTrends
Forget Roomba, your most important house robot could be the one that hugs you By Luke Dormehl
Sure, so Alexa can play you the right song at the right time, and Google’s Duplex tech means you never need to phone up and book a restaurant again, but our relationship with machines still has the non-tactile frigidity of an unhappy marriage. However, that could all change thanks to work coming out of the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. Researchers there have been developing a robot that is designed for giving you a hug. And, far from an amusing gimmick, they are convinced that it’s really important.
“A robot hugging a person is a good idea because people may crave the benefits that come from a hug at a time when they can’t get a hug from a person, due to factors such as distance, timing, and health,” Alexis Block, one of the lead researchers on the HuggieBot project, told Digital Trends. “We think a hugging robot could be beneficial in this case because a person can get the support they need without feeling self-conscious.” ... '
Saturday, August 25, 2018
Tableau Announces Smarter Analytics
Report at the link. We were early users of their systems.
Tableau Advances the Era of Smart Analytics
A look at Tableau's intelligent data prep, discovery, recommendation and upcoming query capabilities. New Constellation Research report: Tableau Advances the Era of Smart Analytics.
Author Doug Henschen, VP and Principal Analyst, explores the evolution of self-service BI and the rise of smart analytics in the market, examining four key areas in which Tableau continues to invest: Data prep, data analysis and discovery, natural language interactions, and predictive analytics. ... "
Tableau Advances the Era of Smart Analytics
A look at Tableau's intelligent data prep, discovery, recommendation and upcoming query capabilities. New Constellation Research report: Tableau Advances the Era of Smart Analytics.
Author Doug Henschen, VP and Principal Analyst, explores the evolution of self-service BI and the rise of smart analytics in the market, examining four key areas in which Tableau continues to invest: Data prep, data analysis and discovery, natural language interactions, and predictive analytics. ... "
Looking at Sorting in Multiple Spaces in a New Way
I did much work in the area of sort algorithms, so this is interesting. Its not quite conveyed why this is useful. We do know how to sort very disparate data very quickly and every time you press a smartphone key you initiate a number of fast sorts. What is new and remarkable is how sort algorithms can interact with broader domains and dimensions of information.
Not very technical, but technical papers on the concept linked to below.
In QuantaMagazine:
Universal Method to Sort Complex Information Found
The nearest neighbor problem asks where a new point fits in to an existing data set. A few researchers set out to prove that there was no universal way to solve it. Instead, they found such a way.
By Kevin Hartnett, Senior Writer Quanta
" ... Now, a team of computer scientists has come up with a radically new way of solving nearest neighbor problems. In a pair of papers, five computer scientists have elaborated the first general-purpose method of solving nearest neighbor questions for complex data.
“This is the first result that captures a rich collection of spaces using a single algorithmic technique,” said Piotr Indyk, a computer scientist at the Massachusetts Institute of Technology and influential figure in the development of nearest neighbor search. ... "
Technica papers background:
https://www.ilyaraz.org/static/papers/spectral_gap.pdf
https://ilyaraz.org/static/papers/daher.pdf
Not very technical, but technical papers on the concept linked to below.
In QuantaMagazine:
Universal Method to Sort Complex Information Found
The nearest neighbor problem asks where a new point fits in to an existing data set. A few researchers set out to prove that there was no universal way to solve it. Instead, they found such a way.
By Kevin Hartnett, Senior Writer Quanta
" ... Now, a team of computer scientists has come up with a radically new way of solving nearest neighbor problems. In a pair of papers, five computer scientists have elaborated the first general-purpose method of solving nearest neighbor questions for complex data.
“This is the first result that captures a rich collection of spaces using a single algorithmic technique,” said Piotr Indyk, a computer scientist at the Massachusetts Institute of Technology and influential figure in the development of nearest neighbor search. ... "
Technica papers background:
https://www.ilyaraz.org/static/papers/spectral_gap.pdf
https://ilyaraz.org/static/papers/daher.pdf
Friday, August 24, 2018
Jupyter and Data Driven Decision Making
Excerpts from JupyterCon, in O'Reilly.
Jupyter is where humans and data science intersect
Discover how data-driven organizations are using Jupyter to analyze data, share insights, and foster practices for dynamic, reproducible data science. By Paco Nathan
I'm grateful to join Fernando Pérez and Brian Granger as a program co-chair for JupyterCon 2018. Project Jupyter, NumFOCUS, and O'Reilly Media will present the second annual JupyterCon in New York City August 21–25, 2018.
Timing for this event couldn't be better. The human side of data science, machine learning/AI, and scientific computing is more important than ever. This is seen in the broad adoption of data-driven decision-making in human organizations of all kinds, the increasing importance of human centered design in tools for working with data, the urgency for better data insights in the face of complex socioeconomic conditions worldwide, as well as dialogue about the social issues these technologies bring to the fore: collaboration, security, ethics, data privacy, transparency, propaganda, etc.
JupyterCon 2018, New York City, Aug. 21-24, 2018
Jupyter is where humans and data science intersect.
And Fernando Perez: The better the technology, the more important that human judgement becomes.
Consequently, we'll explore three main themes at JupyterCon 2018:
Interactive computing with data at scale: the technical best practices and organizational challenges of supporting interactive computing in companies, universities, research collaborations, etc., (JupyterHub)
Extensible user interfaces for data science, machine learning/AI, and scientific computing (JupyterLab)
Computational communication: taking the artifacts of interactive computing and communicating them to different audiences .... "
Jupyter is where humans and data science intersect
Discover how data-driven organizations are using Jupyter to analyze data, share insights, and foster practices for dynamic, reproducible data science. By Paco Nathan
I'm grateful to join Fernando Pérez and Brian Granger as a program co-chair for JupyterCon 2018. Project Jupyter, NumFOCUS, and O'Reilly Media will present the second annual JupyterCon in New York City August 21–25, 2018.
Timing for this event couldn't be better. The human side of data science, machine learning/AI, and scientific computing is more important than ever. This is seen in the broad adoption of data-driven decision-making in human organizations of all kinds, the increasing importance of human centered design in tools for working with data, the urgency for better data insights in the face of complex socioeconomic conditions worldwide, as well as dialogue about the social issues these technologies bring to the fore: collaboration, security, ethics, data privacy, transparency, propaganda, etc.
JupyterCon 2018, New York City, Aug. 21-24, 2018
Jupyter is where humans and data science intersect.
And Fernando Perez: The better the technology, the more important that human judgement becomes.
Consequently, we'll explore three main themes at JupyterCon 2018:
Interactive computing with data at scale: the technical best practices and organizational challenges of supporting interactive computing in companies, universities, research collaborations, etc., (JupyterHub)
Extensible user interfaces for data science, machine learning/AI, and scientific computing (JupyterLab)
Computational communication: taking the artifacts of interactive computing and communicating them to different audiences .... "
Organization as a Network of Conversations
Can better organized conversations create intelligence?
Organization as a network of conversations.
In MIT Sloan Review
" ... In 2004, when Brad Mills became the CEO of Lonmin, the British mining company operating in South Africa, it faced a depressing future. It was so rife with conflicts among management, labor, the local community, and dysfunctional organizational silos that it was hard to discern any collective vision for the company at all. So, as one of his first acts, Mills brought together 100 leaders from the company, along with unions, tribes, and the local community, to participate in a two-day-long designed conversation. The goal of the engagement? To envision a new, compelling future for Lonmin and its stakeholders.
Mills appealed to what the assembled representatives had in common — their humanity — promoting the idea that people can create something exciting by working together as human beings. During the next two days, conversations turned from initial animosity toward what they could build together. The stakeholders began to see themselves — their interests as well as their potential contributions — in Lonmin’s future.
Mills’ approach relies on a uniquely powerful perspective that is rare among executives: the ability to see an organization as a fundamentally linguistic entity. From this vantage, conversation is the primary organizing principle of organizational management. By “conversation,” we mean any linguistic means of communication, ranging from speaking and listening to writing and images. Put simply, a company is the sum of all corporate dialogues, what we call a “network of conversations.”
Conversation in the Leadership Context
Researchers have noted that compliance-based, command-and-control organizations are less viable in today’s global, pluralistic business networks where commercial success may depend on collaborative value creation with partners and customers. The “network of conversations” framing is a logical extension of this perspective. It points toward a fundamental corporate reality: Conversations, whether acknowledged or not, are going on all the time; unacknowledged conversations, however, are not being managed or led. Managers assume that passing along memos, directives, and policies constitutes “conversation,” but often these become mere “topics” of the real, informal conversations that are already occurring in the larger network. Recognizing and managing conversational networks can enrich and accelerate diverse information flows.
This ubiquity of conversations makes the “network of conversations” perspective not only powerful but also an imperative for managers and leaders. While there are many ways to classify conversations (functional, legal, gossip, etc.), we want to highlight three fundamental conversational dimensions — leadership, managerial, and individual — to show how they can be aligned for greater organizational performance. ... "
Organization as a network of conversations.
In MIT Sloan Review
" ... In 2004, when Brad Mills became the CEO of Lonmin, the British mining company operating in South Africa, it faced a depressing future. It was so rife with conflicts among management, labor, the local community, and dysfunctional organizational silos that it was hard to discern any collective vision for the company at all. So, as one of his first acts, Mills brought together 100 leaders from the company, along with unions, tribes, and the local community, to participate in a two-day-long designed conversation. The goal of the engagement? To envision a new, compelling future for Lonmin and its stakeholders.
Mills appealed to what the assembled representatives had in common — their humanity — promoting the idea that people can create something exciting by working together as human beings. During the next two days, conversations turned from initial animosity toward what they could build together. The stakeholders began to see themselves — their interests as well as their potential contributions — in Lonmin’s future.
Mills’ approach relies on a uniquely powerful perspective that is rare among executives: the ability to see an organization as a fundamentally linguistic entity. From this vantage, conversation is the primary organizing principle of organizational management. By “conversation,” we mean any linguistic means of communication, ranging from speaking and listening to writing and images. Put simply, a company is the sum of all corporate dialogues, what we call a “network of conversations.”
Conversation in the Leadership Context
Researchers have noted that compliance-based, command-and-control organizations are less viable in today’s global, pluralistic business networks where commercial success may depend on collaborative value creation with partners and customers. The “network of conversations” framing is a logical extension of this perspective. It points toward a fundamental corporate reality: Conversations, whether acknowledged or not, are going on all the time; unacknowledged conversations, however, are not being managed or led. Managers assume that passing along memos, directives, and policies constitutes “conversation,” but often these become mere “topics” of the real, informal conversations that are already occurring in the larger network. Recognizing and managing conversational networks can enrich and accelerate diverse information flows.
This ubiquity of conversations makes the “network of conversations” perspective not only powerful but also an imperative for managers and leaders. While there are many ways to classify conversations (functional, legal, gossip, etc.), we want to highlight three fundamental conversational dimensions — leadership, managerial, and individual — to show how they can be aligned for greater organizational performance. ... "
IOTA as Permissionless Distributed Ledger
Bought to my attention, examining:
See also their blog: http://www.tangleblog.com/what-is-iota-what-is-the-tangle/
IOTA: A permissionless distributed ledger for a new economy
An Open-Source Distributed Ledger
The first open-source distributed ledger that is being built to power the future of the Internet of Things with feeless microtransactions and data integrity for machines.
The problem we solve
Anyone with a bank account is familiar with the concept of a ledger, containing records of their debits and credits. Collectively, we have all entrusted financial institutions for generations to safeguard these highly sensitive records and their accuracy. With no ability to verify the data that we receive on the Internet today, and with cybercrime on the rise, this delegated and unverifiable trust has become a major obstacle for an inclusive and permissionless economy.
With the advent of distributed ledger technologies, we are now able to distribute and synchronize ledgers of data and money in secure, distributed, decentralized and permissionless environments. By removing the need for trusted third-parties as the gatekeepers and arbiters of truth, enormous efficiency gains, innovation opportunities and new value propositions emerge.
Blockchain technology promised a compelling vision: decentralized networks allowing open innovation and peer-to-peer transactions without intermediaries or fees. Ultimately, they were never built to execute it in full, due to inherent technical flaws in their design. As blockchain adoption has increased over the last decade, early adopters have been hit with sluggish transaction times and skyrocketing fees. As financial rewards for validating blockchain transactions became increasingly competitive, their networks have also become increasingly centralised around a few powerful actors. But the need for decentralized and permissionless systems remains, and has only increased in recent years.
By solving the inefficiencies of the Blockchain, IOTA, based on the revolutionary distributed ledger technology, the Tangle, is the missing link for the Internet of Everything and Web 3.0. Powering a secure, scalable and feeless transaction settlement layer, IOTA will empower machines and humans to participate in flourishing new permissionless economies - the most important one being the Machine Economy which we are building.
Meet ‘the Tangle’
IOTA’s distributed ledger, by contrast, does not consist of transactions grouped into blocks and stored in sequential chains, but as a stream of individual transactions entangled together.
block chain vs tangle
In order to participate in this network, a participant simply needs to perform a small amount of computational work that verifies two previous transactions. Rather than creating a hierarchy of roles and responsibilities in the network, every actor has the same incentives and rewards. In order to make a transaction in the Tangle, two previous transactions must be validated with the reward for doing so being the validation of your own transaction by some subsequent transaction. With this 'pay-it-forward' system of validations, there is no need to offer financial rewards. Transacting with IOTA is and will always be completely fee-free.
Moreover, without the need for monetary rewards, IOTA is not limited to transactional value settlements. It is possible to securely store information within Tangle transactions, or even spread larger amounts of information across multiple bundled or linked transactions.
This structure also enables high scalability of transactions. The more activity in ‘the Tangle’, the faster transactions can be confirmed. .... "
also see:
https://blog.iota.org/the-tangle-an-illustrated-introduction-4d5eae6fe8d4
and QUBIC
https://qubic.iota.org/ (IOTA plus Smart Contracts...)
See also their blog: http://www.tangleblog.com/what-is-iota-what-is-the-tangle/
IOTA: A permissionless distributed ledger for a new economy
An Open-Source Distributed Ledger
The first open-source distributed ledger that is being built to power the future of the Internet of Things with feeless microtransactions and data integrity for machines.
The problem we solve
Anyone with a bank account is familiar with the concept of a ledger, containing records of their debits and credits. Collectively, we have all entrusted financial institutions for generations to safeguard these highly sensitive records and their accuracy. With no ability to verify the data that we receive on the Internet today, and with cybercrime on the rise, this delegated and unverifiable trust has become a major obstacle for an inclusive and permissionless economy.
With the advent of distributed ledger technologies, we are now able to distribute and synchronize ledgers of data and money in secure, distributed, decentralized and permissionless environments. By removing the need for trusted third-parties as the gatekeepers and arbiters of truth, enormous efficiency gains, innovation opportunities and new value propositions emerge.
Blockchain technology promised a compelling vision: decentralized networks allowing open innovation and peer-to-peer transactions without intermediaries or fees. Ultimately, they were never built to execute it in full, due to inherent technical flaws in their design. As blockchain adoption has increased over the last decade, early adopters have been hit with sluggish transaction times and skyrocketing fees. As financial rewards for validating blockchain transactions became increasingly competitive, their networks have also become increasingly centralised around a few powerful actors. But the need for decentralized and permissionless systems remains, and has only increased in recent years.
By solving the inefficiencies of the Blockchain, IOTA, based on the revolutionary distributed ledger technology, the Tangle, is the missing link for the Internet of Everything and Web 3.0. Powering a secure, scalable and feeless transaction settlement layer, IOTA will empower machines and humans to participate in flourishing new permissionless economies - the most important one being the Machine Economy which we are building.
Meet ‘the Tangle’
IOTA’s distributed ledger, by contrast, does not consist of transactions grouped into blocks and stored in sequential chains, but as a stream of individual transactions entangled together.
block chain vs tangle
In order to participate in this network, a participant simply needs to perform a small amount of computational work that verifies two previous transactions. Rather than creating a hierarchy of roles and responsibilities in the network, every actor has the same incentives and rewards. In order to make a transaction in the Tangle, two previous transactions must be validated with the reward for doing so being the validation of your own transaction by some subsequent transaction. With this 'pay-it-forward' system of validations, there is no need to offer financial rewards. Transacting with IOTA is and will always be completely fee-free.
Moreover, without the need for monetary rewards, IOTA is not limited to transactional value settlements. It is possible to securely store information within Tangle transactions, or even spread larger amounts of information across multiple bundled or linked transactions.
This structure also enables high scalability of transactions. The more activity in ‘the Tangle’, the faster transactions can be confirmed. .... "
also see:
https://blog.iota.org/the-tangle-an-illustrated-introduction-4d5eae6fe8d4
and QUBIC
https://qubic.iota.org/ (IOTA plus Smart Contracts...)
Process Automation at Anthem
I never liked the full term RPA (Robotic Process Automation) since it is not really about robots the way we mostly use the term 'Robot' today. So I am now using the term 'Process Automation'. Here how Anthem is using the method to digitize. This further makes the case that its always useful to do some sort of process model first before digitizing. That ensures everyone agrees you are digitizing the right thing and can agree with the results. Even if you never RPA, you can address your model with other methods as appropriate. Or simply as a means to document your current flow of business. Useful for training too. You should only automate your process if you know what it is.
Anthem taps RPA, AI in digital transformation push
The health insurance company is using robotic process automation to balance data center workloads as part of CIO Tim Skeen’s effort to make IT operations more nimble for stakeholders. By Clint Boulton in CIO
Robotic process automation (RPA) has become a popular go-to technology for insurance companies looking to automate data entry and replace paper shuffling. One insurance provider is embracing RPA in a different fashion: Automating computing infrastructure to free up engineers to focus on more strategic tasks.
Anthem has implemented more than 130 RPA "bots" to manage the company's data center infrastructure, says CIO Tim Skeen. The bots are a key part of Anthem's broader digital transformation to make IT more nimble for external stakeholders, including consumers, healthcare providers and employers, says Skeen, who took the reins from Tom Miller four months ago. ... "
Anthem taps RPA, AI in digital transformation push
The health insurance company is using robotic process automation to balance data center workloads as part of CIO Tim Skeen’s effort to make IT operations more nimble for stakeholders. By Clint Boulton in CIO
Robotic process automation (RPA) has become a popular go-to technology for insurance companies looking to automate data entry and replace paper shuffling. One insurance provider is embracing RPA in a different fashion: Automating computing infrastructure to free up engineers to focus on more strategic tasks.
Anthem has implemented more than 130 RPA "bots" to manage the company's data center infrastructure, says CIO Tim Skeen. The bots are a key part of Anthem's broader digital transformation to make IT more nimble for external stakeholders, including consumers, healthcare providers and employers, says Skeen, who took the reins from Tom Miller four months ago. ... "
Chatbots, Assistants and Beyond
Good thoughts, we need to think of the whole problem, not just answering simple questions. Autonomous implies knowing much about context and strategy and process, harder yet.
The next generation of AI assistants in enterprise Via O'Reilly
Chatbots are just the first step in the journey to achieve true AI assistants and autonomous organizations. By Alan Nichol
Chatbots are the first step toward autonomous organizations: companies whose operations are largely run by many different AI assistants. Analogous to autonomous cars, there are five levels of sophistication for AI assistants. Currently, basic level two AI assistants are mainstream, and Google just showed the world what a level three assistant looks like. Achieving true level five capabilities for AI assistants will result in a significant shift for society, with many implications for businesses and their customers.
The recent backlash about chatbots is both absolutely correct and completely misses the point. Yes, most chatbots we’ve seen since F8 2016 are bad. Most have failed to add value to the end user when compared to existing websites or apps.
However, chatbots are not the end game. We know from working with Fortune 500 companies there are powerful examples showing that state of the art chatbots can work and actually do help companies generate additional revenue or save costs. Our mission is to work toward true AI assistants that make it possible for customers to express what they want, in their own terms, without a human on the other end. ... "
The next generation of AI assistants in enterprise Via O'Reilly
Chatbots are just the first step in the journey to achieve true AI assistants and autonomous organizations. By Alan Nichol
Chatbots are the first step toward autonomous organizations: companies whose operations are largely run by many different AI assistants. Analogous to autonomous cars, there are five levels of sophistication for AI assistants. Currently, basic level two AI assistants are mainstream, and Google just showed the world what a level three assistant looks like. Achieving true level five capabilities for AI assistants will result in a significant shift for society, with many implications for businesses and their customers.
The recent backlash about chatbots is both absolutely correct and completely misses the point. Yes, most chatbots we’ve seen since F8 2016 are bad. Most have failed to add value to the end user when compared to existing websites or apps.
However, chatbots are not the end game. We know from working with Fortune 500 companies there are powerful examples showing that state of the art chatbots can work and actually do help companies generate additional revenue or save costs. Our mission is to work toward true AI assistants that make it possible for customers to express what they want, in their own terms, without a human on the other end. ... "
Thursday, August 23, 2018
Auto Tune Model: Automating Machine Learning
Given the way such models are constructed, this is not unexpected. For some time humans will still be needed to guide the process. In particular to understand the link to business process.
How machine learning creates demand for human workers in Techrepublic
Building a slide deck, pitch, or presentation? Here are the big takeaways:
An automated machine learning platform called Auto Tune Models (ATM) from MIT and Michigan State University uses cloud-based, on-demand computing to speed data analysis. -MIT and Michigan State University, 2017
ATM was able to deliver a solution better than the one humans had come up with 30% of the time, and could do this 100x faster. -MIT and Michigan State University, 2017
A new automated machine learning system can analyze data and come up with a solution 100x faster than humans, according to a new paper from MIT and Michigan State University. This could potentially help businesses take advantage of machine learning's capabilities in a faster, easier way, while also filling data science talent gaps.
The system also potentially marks a tipping point in machine learning adoption in the enterprise, which is expected to double in 2018, as TechRepublic's sister site ZDNet reported.
When seeking a solution to a problem, data scientists must wade through huge datasets, and choose the modeling technique they believe will work best. The issue is, there are hundreds of techniques to choose from, including neural networks and support vector machines, and choosing the best one could potentially mean the difference between millions of dollars in ad revenue or none, or catching a flaw in a medical device or not ... "
How machine learning creates demand for human workers in Techrepublic
Building a slide deck, pitch, or presentation? Here are the big takeaways:
An automated machine learning platform called Auto Tune Models (ATM) from MIT and Michigan State University uses cloud-based, on-demand computing to speed data analysis. -MIT and Michigan State University, 2017
ATM was able to deliver a solution better than the one humans had come up with 30% of the time, and could do this 100x faster. -MIT and Michigan State University, 2017
A new automated machine learning system can analyze data and come up with a solution 100x faster than humans, according to a new paper from MIT and Michigan State University. This could potentially help businesses take advantage of machine learning's capabilities in a faster, easier way, while also filling data science talent gaps.
The system also potentially marks a tipping point in machine learning adoption in the enterprise, which is expected to double in 2018, as TechRepublic's sister site ZDNet reported.
When seeking a solution to a problem, data scientists must wade through huge datasets, and choose the modeling technique they believe will work best. The issue is, there are hundreds of techniques to choose from, including neural networks and support vector machines, and choosing the best one could potentially mean the difference between millions of dollars in ad revenue or none, or catching a flaw in a medical device or not ... "
July/August 2018 Analytics Magazine
Preview
Latest Informs Analytics Magazine July/August 2018
Supply Chain and Manufacturing: When Optimization Models Fail, how to avoid Chaos ... "
Latest Informs Analytics Magazine July/August 2018
Supply Chain and Manufacturing: When Optimization Models Fail, how to avoid Chaos ... "
Procter Olay Uses AI for Skin Advisor
Worked previously with a company seeking to determine physical age via AI classification methods. Here another. Note too the long history of P&G with advisory and conversational systems.
In Venturebeat:
AI gave Olay its biggest product launch in 10 years By Jen Larsen
" ... The company partnered with Nara Logics, and Olay Skin Advisor was born in 2016. It’s a web-based tool, rather than an app, that reduces barriers to entry, Putman says. You take a selfie, and the AI-powered engine determines your skin age and then matches you with a raft of Olay products intended to fix your particular issues — from about 2 million unique regimens, all told.
Olay started out with a very limited pool of data, says Damon Frost, director of beauty and CIO at Procter & Gamble, but it continued to shore up that collection by turning Olay.com into a direct-to-consumer website. That way, Olay could see the direct impact of Skin Advisor, from the number of visitors to the basket size and conversion rate. ... "
In Venturebeat:
AI gave Olay its biggest product launch in 10 years By Jen Larsen
" ... The company partnered with Nara Logics, and Olay Skin Advisor was born in 2016. It’s a web-based tool, rather than an app, that reduces barriers to entry, Putman says. You take a selfie, and the AI-powered engine determines your skin age and then matches you with a raft of Olay products intended to fix your particular issues — from about 2 million unique regimens, all told.
Olay started out with a very limited pool of data, says Damon Frost, director of beauty and CIO at Procter & Gamble, but it continued to shore up that collection by turning Olay.com into a direct-to-consumer website. That way, Olay could see the direct impact of Skin Advisor, from the number of visitors to the basket size and conversion rate. ... "
Strategy for the Digital World
Developing a Strategy for the Digital World
NEW BOOK: A new book by Sunil Gupta, "Driving Digital Strategy," explores how traditional businesses can make the leap into the digital age.
Digital transformation is certainly a threat to the old guard—just ask cab drivers, newspaper reporters, and coal miners. In 20 years, all commercial truck drivers could be facing the same fate as autonomous vehicles take over the road.
Sunil Gupta’s message in a new book is more positive: Digital “presents an endless number of opportunities for companies from traditional industries,” he writes in Driving Digital Strategy, published last week. But it starts with reimaging what your business is, who your customers are, and how to engage them using digital technology. Gupta is the Edward W. Carter Professor of Business Administration at Harvard Business School. ... "
NEW BOOK: A new book by Sunil Gupta, "Driving Digital Strategy," explores how traditional businesses can make the leap into the digital age.
Digital transformation is certainly a threat to the old guard—just ask cab drivers, newspaper reporters, and coal miners. In 20 years, all commercial truck drivers could be facing the same fate as autonomous vehicles take over the road.
Sunil Gupta’s message in a new book is more positive: Digital “presents an endless number of opportunities for companies from traditional industries,” he writes in Driving Digital Strategy, published last week. But it starts with reimaging what your business is, who your customers are, and how to engage them using digital technology. Gupta is the Edward W. Carter Professor of Business Administration at Harvard Business School. ... "
Alexa Fund Seeks to Support Conversational AI
Alexa Fund Invests in Student Scientists and Entrepreneurs with Expanded Alexa Fellowship
We're thrilled to announce that we have selected 18 universities from around the world as recipients of the 2018-2019 Amazon Alexa Fellowship, fueling the future of conversational AI research, education, and entrepreneurship. We've been consistently impressed with the ingenuity of university students, and our decision to grow the Alexa Fellowship from four universities in 2017 to 18 universities in 2018 represents our belief in the potential these students have to invent the next big thing.
We Believe Voice Is the Future
Voice is the most natural, convenient interface and we believe it can change the way humans interact with technology. To achieve this reality, we need to solve many hard conversational AI challenges, ranging from automatic speech recognition to natural language understanding to text-to-speech. We must also help entrepreneurs build voice interfaces into their technologies.
We knew we’d need top engineers and scientists at Amazon working to solve these problems. But we also knew we’d need to make it easier and more accessible for smart people outside of the company to get involved with conversational AI. That's why we launched the Alexa Skills Kit (ASK) and Alexa Voice Services (AVS) and allocated $200 million to promising startups innovating with voice via the Alexa Fund.
Expanding Our Collaboration with Academia
Just as we engage developers to build with Alexa, it is important for us to support the academic community that continues to tackle the hardest of challenges that can advance voice technology. That’s why last year, we introduced the Alexa Fund Fellowship as a way to support researchers at top universities focused on speech and language technologies. Based on the success at the four original universities and interest among other universities, we're excited to iterate on and grow the program this year as the Alexa Fellowship.
While graduate students are uniquely positioned to accelerate conversational AI research and education, we've observed students with diverse backgrounds inventing new products and services that can benefit from adding voice interfaces. That's why we're tailoring the Alexa Fellowship to directly support two distinct groups of students with the Alexa Graduate Fellowship and the Alexa Innovation Fellowship. ... "
We're thrilled to announce that we have selected 18 universities from around the world as recipients of the 2018-2019 Amazon Alexa Fellowship, fueling the future of conversational AI research, education, and entrepreneurship. We've been consistently impressed with the ingenuity of university students, and our decision to grow the Alexa Fellowship from four universities in 2017 to 18 universities in 2018 represents our belief in the potential these students have to invent the next big thing.
We Believe Voice Is the Future
Voice is the most natural, convenient interface and we believe it can change the way humans interact with technology. To achieve this reality, we need to solve many hard conversational AI challenges, ranging from automatic speech recognition to natural language understanding to text-to-speech. We must also help entrepreneurs build voice interfaces into their technologies.
We knew we’d need top engineers and scientists at Amazon working to solve these problems. But we also knew we’d need to make it easier and more accessible for smart people outside of the company to get involved with conversational AI. That's why we launched the Alexa Skills Kit (ASK) and Alexa Voice Services (AVS) and allocated $200 million to promising startups innovating with voice via the Alexa Fund.
Expanding Our Collaboration with Academia
Just as we engage developers to build with Alexa, it is important for us to support the academic community that continues to tackle the hardest of challenges that can advance voice technology. That’s why last year, we introduced the Alexa Fund Fellowship as a way to support researchers at top universities focused on speech and language technologies. Based on the success at the four original universities and interest among other universities, we're excited to iterate on and grow the program this year as the Alexa Fellowship.
While graduate students are uniquely positioned to accelerate conversational AI research and education, we've observed students with diverse backgrounds inventing new products and services that can benefit from adding voice interfaces. That's why we're tailoring the Alexa Fellowship to directly support two distinct groups of students with the Alexa Graduate Fellowship and the Alexa Innovation Fellowship. ... "
Google Insights on Voice Technology, Conversation
From the Google Blog. Their take on voice, conversation and expectations.
Five insights on voice technology
By Scott Huffman VP, Engineering, Google Assistant
Over the last couple years something interesting happened—millions of people began having conversations with their speakers, cars, computers and phones. Voice technology is fundamentally changing the way we use we our devices, often in ways we didn’t expect.
We’ve learned a lot about how we can better serve people’s needs with voice, helping them save time and get things done. Here are a few things we’ve learned since we introduced the Google Assistant nearly two years ago.
Voice is about action.
When people talk to their Google Assistant, they’re usually trying to get something done. Assistant queries are 40 times more likely to be action-oriented than Search, with people asking for things like “send a text message,” “turn off the lights,” or “turn on airplane mode.”
Why do we think this is happening? For many tasks, particularly while you’re on the go, it can be much easier to get things done through voice. I can say “turn on the lights and play some music,” without having to worry about which app I need to open. Even for basic things like creating a calendar invite, I don’t have to look down at my phone or interrupt what I’m doing, I can just say “create an appointment for noon on Saturday.” These seem like small things, and they are. But they illustrate what makes voice so unique—the technology allows me to complete a task in a way that feels natural. The more we can build these types of experiences, the closer we get to an ideal Assistant.
People expect conversations.
When people start using voice assistants, we often see very simple commands. But very quickly, expectations go up in terms of complex dialogue. We might see “weather Chicago” typed in Search, whereas with the Assistant we see much longer and more conversational queries like “what’s the weather today in Chicago at 3pm.” On average, Assistant queries are 200 times more conversational than Search.
We’ve seen that even simple commands can take all forms. For example, people ask the Google Assistant to set an alarm in more than 5,000 different ways, which means that we have to build the Assistant to understand this conversational complexity. .... "
Five insights on voice technology
By Scott Huffman VP, Engineering, Google Assistant
Over the last couple years something interesting happened—millions of people began having conversations with their speakers, cars, computers and phones. Voice technology is fundamentally changing the way we use we our devices, often in ways we didn’t expect.
We’ve learned a lot about how we can better serve people’s needs with voice, helping them save time and get things done. Here are a few things we’ve learned since we introduced the Google Assistant nearly two years ago.
Voice is about action.
When people talk to their Google Assistant, they’re usually trying to get something done. Assistant queries are 40 times more likely to be action-oriented than Search, with people asking for things like “send a text message,” “turn off the lights,” or “turn on airplane mode.”
Why do we think this is happening? For many tasks, particularly while you’re on the go, it can be much easier to get things done through voice. I can say “turn on the lights and play some music,” without having to worry about which app I need to open. Even for basic things like creating a calendar invite, I don’t have to look down at my phone or interrupt what I’m doing, I can just say “create an appointment for noon on Saturday.” These seem like small things, and they are. But they illustrate what makes voice so unique—the technology allows me to complete a task in a way that feels natural. The more we can build these types of experiences, the closer we get to an ideal Assistant.
People expect conversations.
When people start using voice assistants, we often see very simple commands. But very quickly, expectations go up in terms of complex dialogue. We might see “weather Chicago” typed in Search, whereas with the Assistant we see much longer and more conversational queries like “what’s the weather today in Chicago at 3pm.” On average, Assistant queries are 200 times more conversational than Search.
We’ve seen that even simple commands can take all forms. For example, people ask the Google Assistant to set an alarm in more than 5,000 different ways, which means that we have to build the Assistant to understand this conversational complexity. .... "
Cristie's to Sell AI Art
Consulted for the Auction industry in past years. Can such art also be profitable for sale?
Is the Art Market Ready to Embrace Work Made by Artificial Intelligence? Christie’s Will Test the Waters This Fall
The auction house is selling an AI-produced work of art for the first time this fall.
By Naomi Rea
Is the Art Market Ready to Embrace Work Made by Artificial Intelligence? Christie’s Will Test the Waters This Fall
The auction house is selling an AI-produced work of art for the first time this fall.
By Naomi Rea
Wednesday, August 22, 2018
On Attributes of Blockchain Value
Quote from: Currnt.com
New post to the Current Theme in the The Future of Blockchain in Retail & CPG Supply Chains Public Panel
A new post was made by Steve Kuh in the The Future of Blockchain in Retail & CPG Supply Chains Public Panel.
Reminder of the current theme:
We've established some interesting attributes of blockchain that lends itself as a more efficient and compact way of achieving secure information sharing to support provenance of assets that move through a supply chain. In this respect, blockchain can leverage conventional technologies by augmenting them with these capabilities.
Let's look at a hypothetical case study, drawn from some of the trials that are currently ongoing. We all know how democratization is fueling new innovative technology and business models (e.g. Uber, Air BnB, etc.), and how retailers are exploring ways to reduce friction in the buying experience (e.g. Amazon Go). Let's say we have a CPG startup that wants to create a provenance application whereby a consumer shopping for a product in a store can scan the product with their phone and immediately obtain an affirmation of the following:
It was sourced responsibly and ethically
The materials used within the product are genuine
It did not undergo any production exceptions or abnormalities
It has passed required inspections
It complies with the necessary regulations
It has not been tampered with
It has not expired
The product has not been recalled or redacted
Complies with all vendor claims
Other
You can probably add other items to the list. One organization is already trying to attempt this using blockchain (see www.provenance.org). So the following questions for the panel are:
What products or product groups are prime areas of application?
What kind of solution architecture would you envision?
How would blockchain be used in the solution?
What existing technologies would be involved? What new technologies would be involved?
What would the implementation process look like for a proof-of-concept?
How would you appraise the application for potential ROI?
Feel free to respond to any of the above. Let the sky be your limit. I know there's a lot here, but conciseness of response would be appreciated.
New post to the Current Theme in the The Future of Blockchain in Retail & CPG Supply Chains Public Panel
A new post was made by Steve Kuh in the The Future of Blockchain in Retail & CPG Supply Chains Public Panel.
Reminder of the current theme:
We've established some interesting attributes of blockchain that lends itself as a more efficient and compact way of achieving secure information sharing to support provenance of assets that move through a supply chain. In this respect, blockchain can leverage conventional technologies by augmenting them with these capabilities.
Let's look at a hypothetical case study, drawn from some of the trials that are currently ongoing. We all know how democratization is fueling new innovative technology and business models (e.g. Uber, Air BnB, etc.), and how retailers are exploring ways to reduce friction in the buying experience (e.g. Amazon Go). Let's say we have a CPG startup that wants to create a provenance application whereby a consumer shopping for a product in a store can scan the product with their phone and immediately obtain an affirmation of the following:
It was sourced responsibly and ethically
The materials used within the product are genuine
It did not undergo any production exceptions or abnormalities
It has passed required inspections
It complies with the necessary regulations
It has not been tampered with
It has not expired
The product has not been recalled or redacted
Complies with all vendor claims
Other
You can probably add other items to the list. One organization is already trying to attempt this using blockchain (see www.provenance.org). So the following questions for the panel are:
What products or product groups are prime areas of application?
What kind of solution architecture would you envision?
How would blockchain be used in the solution?
What existing technologies would be involved? What new technologies would be involved?
What would the implementation process look like for a proof-of-concept?
How would you appraise the application for potential ROI?
Feel free to respond to any of the above. Let the sky be your limit. I know there's a lot here, but conciseness of response would be appreciated.
Contextual Assistants Needed
O'Reilly piece on the challenge of contextual chatbots. And beyond the need to keep track of past conversations and plan future goals.
The next generation of AI assistants in enterprise
Chatbots are just the first step in the journey to achieve true AI assistants and autonomous organizations. ... By Alan Nichol
" ... However, chatbots are not the end game. We know from working with Fortune 500 companies there are powerful examples showing that state of the art chatbots can work and actually do help companies generate additional revenue or save costs. Our mission is to work toward true AI assistants that make it possible for customers to express what they want, in their own terms, without a human on the other end.
AI assistants can be applied both for direct customer service and within the operations of an organization. AI that understands customers, context, and that can be proactive will lead to automation of many repetitive tasks. ... "
The next generation of AI assistants in enterprise
Chatbots are just the first step in the journey to achieve true AI assistants and autonomous organizations. ... By Alan Nichol
" ... However, chatbots are not the end game. We know from working with Fortune 500 companies there are powerful examples showing that state of the art chatbots can work and actually do help companies generate additional revenue or save costs. Our mission is to work toward true AI assistants that make it possible for customers to express what they want, in their own terms, without a human on the other end.
AI assistants can be applied both for direct customer service and within the operations of an organization. AI that understands customers, context, and that can be proactive will lead to automation of many repetitive tasks. ... "
How AI is Changing Sales
Well known examples, but worth reviewing
How AI Is Changing Sales By Victor Antonio in the HBR
Companies are using AI in all kinds of innovative ways to advance their businesses. If you’ve ever searched Netflix to watch a movie, AI (a recommendation algorithm) was no doubt used in your decision about what to watch. If you’ve shopped on Amazon, your decision about what to buy was also influenced by AI (via an association algorithm). If you’ve ever ordered an Uber, AI (a location algorithm) was used to have a car in your vicinity quickly. If you ever had a thought about a product or a vacation, and it seemed to suddenly pop up on your search page or in your email inbox, I can assure you it was based on AI (a classification algorithm) monitoring your online activity.
These same types of AI algorithms can be used to power any company’s decision-making process, helping you make better business predictions. Based on research for my book Sales Ex Machina: How Artificial Intelligence is Changing the World of Selling, here are five specific areas where AI algorithms can be leveraged to help your business grow by helping your sales team sell more: ... "
How AI Is Changing Sales By Victor Antonio in the HBR
Companies are using AI in all kinds of innovative ways to advance their businesses. If you’ve ever searched Netflix to watch a movie, AI (a recommendation algorithm) was no doubt used in your decision about what to watch. If you’ve shopped on Amazon, your decision about what to buy was also influenced by AI (via an association algorithm). If you’ve ever ordered an Uber, AI (a location algorithm) was used to have a car in your vicinity quickly. If you ever had a thought about a product or a vacation, and it seemed to suddenly pop up on your search page or in your email inbox, I can assure you it was based on AI (a classification algorithm) monitoring your online activity.
These same types of AI algorithms can be used to power any company’s decision-making process, helping you make better business predictions. Based on research for my book Sales Ex Machina: How Artificial Intelligence is Changing the World of Selling, here are five specific areas where AI algorithms can be leveraged to help your business grow by helping your sales team sell more: ... "
Conversations with Time Logic and Risk
This kindcof problem has just come up again. How do we make the most out of a conversation? In specific contexts. With defined goals? With people, or combined with intelligent agents? Note here the inclusion of 'safety critical', so also an element of defined risk.
U of T Experts in AI Explore a Classical Problem of Computer Science
U of T News By Nina Haikara
Researchers at the University of Toronto (U of T) in Canada are exploring synergies between fast, effective algorithms in artificial intelligence for automated planning and program synthesis, or generating a computer program automatically from a specification of user intent. U of T's Alberto Camacho says he used linear temporal logic (LTL) to develop a practical tool for synthesis, expressing the user's intent in instructions similar to English-language instructions. "I can say something to you, and if you misunderstand, we can have a conversation back and forth [to clarify]," says U of T's Sheila McIlraith. "But when we care about synthesizing safety-critical systems...it really matters that the system understands what we're asking it to do." Camacho says the team is applying automated planning algorithms to LTL synthesis. The program that is produced is correct by construction, and every run of that program satisfies the LTL statements with which it is provided. ... "
U of T Experts in AI Explore a Classical Problem of Computer Science
U of T News By Nina Haikara
Researchers at the University of Toronto (U of T) in Canada are exploring synergies between fast, effective algorithms in artificial intelligence for automated planning and program synthesis, or generating a computer program automatically from a specification of user intent. U of T's Alberto Camacho says he used linear temporal logic (LTL) to develop a practical tool for synthesis, expressing the user's intent in instructions similar to English-language instructions. "I can say something to you, and if you misunderstand, we can have a conversation back and forth [to clarify]," says U of T's Sheila McIlraith. "But when we care about synthesizing safety-critical systems...it really matters that the system understands what we're asking it to do." Camacho says the team is applying automated planning algorithms to LTL synthesis. The program that is produced is correct by construction, and every run of that program satisfies the LTL statements with which it is provided. ... "
What Marketers are doing Wrong with Data Analytics
Interesting podcast piece in K@W. Some useful cautions. The notorious p-hack is brought up again. Its often used because is so easy to apply. Simplicity Bias It cannot be used alone.
What Marketers Are Doing Wrong in Data Analytics
Podcasts Research North America leveraging-customer-analytics-featured-image
Wharton's Ron Berman explains why most marketers 'p-hack' and why it could lead to wrong results.
(Podcast at the link)
Companies gather and analyze data to fine-tune their operations, whether it’s to help them figure out which webpage design works best for customers or what features to include in their product or service to boost sales. Marketers, in particular, use data analytics to answer questions like this: To put people in a shopping mood, is it better to make the webpage banner blue or yellow? Or do these colors not matter? Getting the answer right could mean the difference between higher sales or losing to the competition.
But new Wharton research shows that 57% of marketers are incorrectly crunching the data and potentially getting the wrong answer — and perhaps costing companies a lot of money. “We expected business experimenters [to make this error], but I was nevertheless surprised that so many of them do so,” said Wharton marketing professor Christophe Van den Bulte, who coauthored the study. Wharton marketing professor Ron Berman, another of the study’s authors, agreed: “This was a pretty common phenomenon that we observed.” (Listen to a podcast interview with Berman about the research at the top of this page.)
Their paper, “p-Hacking and False Discovery in A/B Testing,” which was popularly downloaded and widely cited in social media, looked at the A/B testing practices of marketers who used the online platform Optimizely before the platform added safeguards against potential mistakes. In A/B testing, two or more versions of a webpage are tested to see which one resonates more with users. For example, half of a company’s customers would see webpage version A and the other half version B. “Imagine one version says something about the brand of your product and the other version says something about the technical abilities of your product,” Berman said. “You want to determine which one makes consumers respond better, to buy more of your products.” ... "
What Marketers Are Doing Wrong in Data Analytics
Podcasts Research North America leveraging-customer-analytics-featured-image
Wharton's Ron Berman explains why most marketers 'p-hack' and why it could lead to wrong results.
(Podcast at the link)
Companies gather and analyze data to fine-tune their operations, whether it’s to help them figure out which webpage design works best for customers or what features to include in their product or service to boost sales. Marketers, in particular, use data analytics to answer questions like this: To put people in a shopping mood, is it better to make the webpage banner blue or yellow? Or do these colors not matter? Getting the answer right could mean the difference between higher sales or losing to the competition.
But new Wharton research shows that 57% of marketers are incorrectly crunching the data and potentially getting the wrong answer — and perhaps costing companies a lot of money. “We expected business experimenters [to make this error], but I was nevertheless surprised that so many of them do so,” said Wharton marketing professor Christophe Van den Bulte, who coauthored the study. Wharton marketing professor Ron Berman, another of the study’s authors, agreed: “This was a pretty common phenomenon that we observed.” (Listen to a podcast interview with Berman about the research at the top of this page.)
Their paper, “p-Hacking and False Discovery in A/B Testing,” which was popularly downloaded and widely cited in social media, looked at the A/B testing practices of marketers who used the online platform Optimizely before the platform added safeguards against potential mistakes. In A/B testing, two or more versions of a webpage are tested to see which one resonates more with users. For example, half of a company’s customers would see webpage version A and the other half version B. “Imagine one version says something about the brand of your product and the other version says something about the technical abilities of your product,” Berman said. “You want to determine which one makes consumers respond better, to buy more of your products.” ... "
Google Explores Podcasts
In the past I ran an internal podcast in a large company. Have always been interested in podcasts as an information channel, but also one that that had issues, for example it is a serial channel, and takes time to ingest that way. Just recently have started to explore Podcasts again. Especially through voice interfaces. Below work Google is doing in the space. Note 'discovering' and efficient playing. How can AI be used to analyze some of the content and its interaction with other online knowledge? Captioning a good example. Both challenges in the channel when using Podcasts.
Google is developing an experimental podcast app called Shortwave By Russell Brandom @russellbrandom in TheVerge
An experimental unit within Google has been quietly developing a new app for discovering and playing podcasts. Called Shortwave, the new app was revealed by a trademark filing embedded below, which describes it as “allow[ing] users to search, access, and play digital audio files, and to share links to audio files.”
Nothing in the trademark filing specifies the kind of audio being accessed, but a Google representative said the focus of the app was on spoken word content. There is little public information about the app, although Google has played with smart captioning, translation, and other AI-assisted features in previous podcast products. ... "
Google is developing an experimental podcast app called Shortwave By Russell Brandom @russellbrandom in TheVerge
An experimental unit within Google has been quietly developing a new app for discovering and playing podcasts. Called Shortwave, the new app was revealed by a trademark filing embedded below, which describes it as “allow[ing] users to search, access, and play digital audio files, and to share links to audio files.”
Nothing in the trademark filing specifies the kind of audio being accessed, but a Google representative said the focus of the app was on spoken word content. There is little public information about the app, although Google has played with smart captioning, translation, and other AI-assisted features in previous podcast products. ... "
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