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Friday, September 21, 2018

Alexa Presentation Language

 Amazon makes a number of enhancements to the Alexa Skills kit.  Designed to allow for better customization for Alexa devices with screens. Notably this links to a number of new devices being launched this fall.  Quite some interesting ideas, look forward to seeing some powerful things built with it.

Introducing the Alexa Presentation Language

We’re excited to announce a preview of the Alexa Presentation Language (APL), a new design language and tools that make it easy to create visually rich Alexa skills for tens of millions of Alexa devices with screens. With APL, you can build interactive voice experiences that include graphics, images, slideshows, and video. You can also customize the experience for different device types. Apply to participate in the APL developer preview today. .... " 

Also discussed in Tech Crunch.

Thursday, September 20, 2018

Scenarios for Autonomous Trucking

Somewhat unexpected scenarios of process for autonomous trucking and the implications:

In SCDigest

Supply Chain News Bites
Supply Chain Graphic of the Week: The Six Most Likely Scenarios for Autonomous Trucks

Highway Exit-to-Exit Automation Tops the List, though Platooning has Few Barriers

A couple of weeks ago, we reported on new research from Steve Viscelli,with the headline news his estimate that the US will lose almost 300,000 long haul truck driver jobs over 25 years as the result of autonomous trucks - even if some (lower paid) local delivery driver jobs actually ctincrease. (See Will or Will not Autonomous Trucks Eliminate Huge Numbers of Truck Driver Jobs?)... "

Amazon Echo Auto Announced

Been examining the idea for a long time,  the existing systems are operationally touchy.  Claim here is it wil operate when car starts.  Location-aware.  $50.  Not quite ready to ship, later this year. Would like to see the integration between the data in the car and such assistants, but that might only occur when the automobile manufacturers cooperate.   Via IFTTT might be good. 

Amazon's Echo Auto puts Alexa in any car
You won't need a new vehicle to get the voice assistant.
Jon Fingas, @jonfingas in Engadget
(Still in development) 

Waiting for the Echo Truck for the supply chain?

Wal-Mart Push Use of VR for Training

Would lead to one of the largest uses of VR, in this case for training.  Serious effort, making everyone take notice of the possibilities.   What experiments have been done of retail training with VR to show improvements?

Walmart is putting 17,000 VR headsets in its US stores for training
By Adi Robertson   @thedextriarchy in theVerge

Walmart is going to send Oculus Go virtual reality headsets to every US branch of its stores, expanding a VR-based employee training system it announced last year. The company announced today that it will ship four headsets to every Walmart Supercenter and two to every neighborhood market and discount store, meaning around 4,700 US locations (not counting Sam’s Club stores and smaller centers like campus stores) will receive them. They start shipping next month, and Walmart says that over 17,000 headsets will be in stores by the end of the year. .... "

Data Culture

Never heard of the term 'Data Culture', but I do see the point.  We should all be thinking about what the data we have, don't have, where it fits for needed goals.

Why data culture matters   By Alejandro Díaz, Kayvaun Rowshankish, and Tamim Saleh

Organizational culture can accelerate the application of analytics, amplify its power, and steer companies away from risky outcomes. Here are seven principles that underpin a healthy data culture.

Revolutions, it’s been remarked, never go backward. Nor do they advance at a constant rate. Consider the immense transformation unleashed by data analytics. By now, it’s clear the data revolution is changing businesses and industries in profound and unalterable ways.

But the changes are neither uniform nor linear, and companies’ data-analytics efforts are all over the map. McKinsey research suggests that the gap between leaders and laggards in adopting analytics, within and among industry sectors, is growing. We’re seeing the same thing on the ground. Some companies are doing amazing things; some are still struggling with the basics; and some are feeling downright overwhelmed, with executives and members of the rank and file questioning the return on data initiatives.

For leading and lagging companies alike, the emergence of data analytics as an omnipresent reality of modern organizational life means that a healthy data culture is becoming increasingly important. With that in mind, we’ve spent the past few months talking with analytics leaders at companies from a wide range of industries and geographies, drilling down on the organizing principles, motivations, and approaches that undergird their data efforts. We’re struck by themes that recur over and again, including the benefits of data, and the risks; the skepticism from employees before they buy in, and the excitement once they do; the need for flexibility, and the insistence on common frameworks and tools. And, especially: the competitive advantage unleashed by a culture that brings data talent, tools, and decision making together.

The experience of these leaders, and our own, suggests that you can’t import data culture and you can’t impose it. Most of all, you can’t segregate it. You develop a data culture by moving beyond specialists and skunkworks, with the goal of achieving deep business engagement, creating employee pull, and cultivating a sense of purpose, so that data can support your operations instead of the other way around.  ... "

Bias and Fairness in Machine Learning

From the CSIG talk given today:

An instructive experiment which was released for use and experimentation today by IBM.  The slides instructive by themselves are here.   The complete audio and video of the presentation will be placed here shortly.   The comments on the presentation also point to other work that has been done and other efforts underway.   Based on the complexity of the problem there is some doubt that a universal solution to this problem is easily determined, give also the broad regulatory and even philosophical underpinning .  Also this is about Machine learning trained problems, not necessarily human decision making.    Still it would be useful to detect if some artifact of ML, like sampling is involved.  Also the need for integration of clear explanatory capabilities were mentioned.  The examples shown were still too technically complex for typical decision makers.

Nicely done.   Well worth examining.   I understand anyone can experiment with this, instructions in the talk. 

Talk:  “AI Fairness 360”
Speaker: Kush Varshney, IBM

Talk Description:  
Machine learning models are increasingly used to inform high stakes decisions about people. Although machine learning, by its very nature, is always a form of statistical discrimination, the discrimination becomes objectionable when it places certain privileged groups at systematic advantage and certain unprivileged groups at systematic disadvantage. Biases in training data, due to either prejudice in labels or under-/over-sampling, yields models with unwanted bias.In this presentation, we introduce AI Fairness 360, a new Python package that includes a comprehensive set of metrics for datasets and models to test for biases, explanations for these metrics, and algorithms to mitigate bias in datasets and models. They have developed the package with extensibility in mind.  They encourage the contribution of your metrics, explainers, and debiasing algorithms. Please join the community to get started as a contributor. ... " 

How to Code in Python 3

Passing this along to some friends

Well done,  relatively non-technical,  especially useful if you have coded in previous languages where you had to construct numeric and related algorithms.   lists and structural  ...  There are now many resources on coding in Python, search them out.

The major section uses linux environments, but they also have a section for more typical environments, here for Windows 10.



Wednesday, September 19, 2018

Amazon may open up to 3,000 Cashierless stores by 2021

The data gathered must have produced some interesting results.  Now this would change the retail world:

Amazon May open up to 3,000 Cashierless Stores by 2021  in Adage

Sensors and Computer vision Technology

Amazon is considering a plan to open as many as 3,000 new AmazonGo cashierless stores in the next few years, according to people familiar with matter, an aggressive and costly expansion that would threaten convenience chains like 7-Eleven, quick-service sandwich shops like Subway and Panera Bread, and mom-and-pop pizzerias and taco trucks.

CEO Jeff Bezos sees eliminating meal-time logjams in busy cities as the best way for Amazon to reinvent the brick-and-mortar shopping experience, where most spending still occurs. But he's still experimenting with the best format: a convenience store that sells fresh prepared foods as well as a limited grocery selection similar to 7-Eleven franchises, or a place to simply pick up a quick bite to eat for people in a rush, similar to the U.K.-based chain Pret a Manger, one of the people said.   ... "

Talk: AI Fairness 360: Python Package

How to look at biases when your making AI driven decisions about people.

Invitation to the ISSIP Cognitive Systems Institute Group Webinar

 Slides and Recording: http://cognitive-science.info/community/weekly-update/

Date and Time: September 20, 2018 - 10:30am US Eastern
Talk Title: AI Fairness 360

Speaker: Kush Varshney, IBM
Talk Description:  
Machine learning models are increasingly used to inform high stakes decisions about people. Although machine learning, by its very nature, is always a form of statistical discrimination, the discrimination becomes objectionable when it places certain privileged groups at systematic advantage and certain unprivileged groups at systematic disadvantage. Biases in training data, due to either prejudice in labels or under-/over-sampling, yields models with unwanted bias.In this presentation, we introduce AI Fairness 360, a new Python package that includes a comprehensive set of metrics for datasets and models to test for biases, explanations for these metrics, and algorithms to mitigate bias in datasets and models. They have developed the package with extensibility in mind.  They encourage the contribution of your metrics, explainers, and debiasing algorithms. Please join the community to get started as a contributor.

Kush R. Varshney was born in Syracuse, NY in 1982. He received the B.S. degree (magna cum laude) in electrical and computer engineering with honors from Cornell University, Ithaca, NY, in 2004. He received the S.M. degree in 2006 and the Ph.D. degree in 2010, both in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge.  While at MIT, he was a National Science Foundation Graduate Research Fellow.Dr. Varshney is a principal research staff member and manager with IBM Research AI at the Thomas J. Watson Research Center, Yorktown Heights, NY, where he leads the Learning and Decision Making group.  He is the founding co-director of the IBM Science for Social Good initiative.  He applies data science and predictive analytics to human capital management, healthcare, olfaction, computational creativity, public affairs, international development, and algorithmic fairness, which has led to recognitions such as the 2013 Gerstner Award for Client Excellence for contributions to the WellPoint team and the Extraordinary IBM Research Technical Accomplishment for contributions to workforce innovation and enterprise transformation. He conducts academic research on the theory and methods of statistical signal processing and machine learning. His work has been recognized through best paper awards at the Fusion 2009, SOLI 2013, KDD 2014, and SDM 2015 conferences. He is a senior member of the IEEE and a member of the Partnership on AI's Safety-Critical AI working group.

Date and Time : September 20 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  -

Join LinkedIn Group https://www.linkedin.com/groups/6729452

AI, Mixed Reality and Analytics Announced at Microsoft

Strong push at AI business applications and notably also their 'mixed reality' methods.   I still have not seen enough MR applications for the typical business. 

Announcing new AI and mixed reality business applications for Microsoft Dynamics  Alysa Taylor - Corporate Vice President, Business Applications & Industry

Today, I had the opportunity to speak to press and analysts in San Francisco about our vision for business applications at Microsoft. In addition, I had the privilege to make two very important announcements: the upcoming availability of new Dynamics 365 AI applications, and our very first mixed reality business applications: Dynamics 365 Remote Assist and Dynamics 365 Layout.

Our vision for business applications at Microsoft

We live in a connected world where companies are challenged every day to innovate so they can stay ahead of emerging trends and repivot business models to take advantage of new opportunities to meet growing customer demands.

To innovate, organizations need to reimagine their processes. They need solutions that are modern, enabling new experiences for how they can engage their customers while making their people more productive. They need unified systems that break data silos, so they have a holistic view of their business, customers and employees. They need pervasive intelligence threaded throughout the platform, giving them the ability to reason over data, to predict trends and drive proactive intelligent action. And with adaptable applications, they can be nimble, allowing them to take advantage of the next opportunity that comes their way.

Two years ago, when we introduced Dynamics 365 we started a journey to tear down the traditional silos of customer relationship management (CRM) and enterprise resource planning (ERP). We set out to reimagine business applications as modern, unified, intelligent and adaptable solutions that are integrated with Office 365 and natively built on Microsoft Azure.

With the release of our new AI and mixed reality applications we are taking another step forward on our journey to help empower every organization on the planet to achieve more through the accelerant of business applications. Specifically, today we are making the following announcements:  ... "
(more details here)

Mother of All Demos reprise

Those with interest in the history of modern computing know this event well. The 'Mother of all demos', done by Douglas Engelbart in 1968.   He drove home in a single demo what might be done with computers, without the user knowing any computer language.  Quite a new idea then.  Later we met and worked with Engelbart.  His later ideas dealt with collaborative, augmented problem solving.  Still a useful idea.
See also:  https://en.wikipedia.org/wiki/Douglas_Engelbart  

Watch this amazing demo of the early desktop computer
In 1968, computers got personal: How the “mother of all demos” changed the world.

By Margaret O'Hara in FastCompany

On a crisp California afternoon in early December 1968, a square-jawed, mild-mannered Stanford researcher named Douglas Engelbart took the stage at San Francisco’s Civic Auditorium and proceeded to blow everyone’s mind about what computers could do. Sitting down at a keyboard, this computer-age Clark Kent calmly showed a rapt audience of computer engineers how the devices they built could be utterly different kinds of machines–ones that were “alive for you all day,” as he put it, immediately responsive to your input, and which didn’t require users to know programming languages in order to operate.

Engelbart typed simple commands. He edited a grocery list. As he worked, he skipped the computer cursor across the screen using a strange wooden box that fit snugly under his palm. With small wheels underneath and a cord dangling from its rear, Engelbart dubbed it a “mouse.” .... "

Amazon Announces Gadget Alexa Tools

Been impressed by what Amazon is doing to support Devs.   Still nothing I would call breakthrough intelligence.    Waiting for that.

Amazon's new Alexa Gadgets Toolkit lets Alexa have some toy-friendly fun

Robots that can lip sync Alexa's speech? Disco balls that sparkle whenever you say the wake word? Amazon's new software makes it possible.   By    Ry Crist in CNET

Amazon has already made a point of making it as easy as possible for developers to build their own Alexa devices. Now, the online megaretailer wants to do the same thing for devices that work with Alexa -- and it wants to teach those gadgets some fun new tricks aimed at taking them to the next level.

To do so, Amazon is launching the Alexa Gadgets Toolkit, a new set of software tools designed for third-party gadgets that connect with Amazon's Echo devices via Bluetooth. Developers who put the toolkit to work will be able to take advantage of four new features. Here's how Amazon describes them: ... " 

In-Air Drone Charging

Involved in Drone tech examination and application.  Battery charging is a big issue.  Below article with video.   From IdeaConnection

GET In-Air Drone Charging Station  
The GET charging station for drones could offer unlimited flight time by letting the drones charge in mid-air.

The GET (Global Energy Transmission) company has developed an outdoor induction loop that can recharge several drones at one time without the need to land. The system, which resembles a wire frame, can transmit up to 12 kilowatts of power at an 80 percent efficiency to several drones simultaneously. A six-minute visit to the loop will provide 25 additional minutes of flight time, and the system is portable enough to be set up where needed—eliminating the need for human battery changers.   ... " 

Experience is the New Product

Experience Is the New Product; Here's How to Manage It
Organize around customer episodes, improving them through Agile teams.

By Gerard du Toit, Jens Engelhardt, Phil Sager and Karsten Fruechtl in Bain.

More companies now emphasize the entire experience surrounding a product or service. But how do they improve the experience, or fix a broken one?

For many, the key unit of management has become the customer "episode," and the core method is Agile. An episode consists of all the activities involved to successfully fulfill a customer's need.
While most Agile to date has focused on software development, improving an episode requires coordinating every factor that affects it, including product features, policies, processes, channels and technology.

Therefore, the team that owns an individual episode should comprise members from all the relevant functions. ....  "

IIOT Platforms

Interesting thoughts and visuals on the topic.

IIoT platforms: The technology stack as value driver in industrial equipment and machinery

Equipment and machinery companies considering a transformation to embrace the Industrial Internet of Things (IIoT) need to develop a clear perspective to drive impact at scale....

" ... Seeing the limits of hardware-driven growth, industrial equipment and machinery companies are looking to the Industrial Internet of Things (IIoT) to develop new customer-oriented, revenue-boosting business models. On the operations side, IIoT could increase production efficiency. Whether the focus is on revenue from new business models, savings from more efficient production, or both, digital-enabled advances in manufacturing require IIoT transformation. ...  "

In McKinsey

Tuesday, September 18, 2018

Cisco Talks Network Assurance with AI

Specific term was new to me.  But I do like the link to the business, the process, the goals.  Are the intents the same as in a simulation model of the business process?   Risks?  Reading more. 

Machine Learning for Analytics and Assurance
By Duval Yeager in Cisco BlogNetwork operation based in the intent of the business.  Goals?  Intriguing.

We are hearing amazing stories from our Cisco customers as they roll out intelligent analytics and assurance solutions in the form of Cisco DNA Center, Meraki insight, and Network Assurance Engine (NAE). The comments are on the accuracy and complexity of the analytical models that we have built, based on 30 years of Cisco networking leadership. You can read my blog post on how analytics works here. But, the back story to this is the approach of Machine Learning. When we add advanced machine learning algorithms to these products, the intelligence and system flexibility will be even more exciting. Let me explain…

Assurance in IP networking uses an analytics engine to verify that the network is operating based on the intents of the business. These intents are translated based on the network policies that IT configured when the system was set-up. The resulting model drives the decisions that an assurance solution makes to improve the network. This model is very good at network optimization, but every network is different, and network utilization is always changing as we change the way we use it  .... " 

Peter Norvig on the Breadth of AI Application

Links to recent O'Reilly talk.  Nice to hear Peter Norvig speaking on this, we read and used his early works on AI.  See: https://en.wikipedia.org/wiki/Peter_Norvig    AI is not just about neural pattern recognition, it can be much, much more.   Almost none of the companies I have surveyed realize this.  Have to believe his management at Google considerably upgrades their Breadth and Depth in AI.

Talk:  The breadth of AI applications: The ongoing expansion
Peter Norvig says one of the most exciting aspects of AI is the diversity of applications in fields far astray from the original breakthrough areas.

This is a keynote highlight from the Artificial Intelligence Conference in San Francisco 2018. Watch the full version of this keynote on O'Reilly's online learning platform.

You can also see other highlights from the event.  .... 

Peter Norvig
Peter Norvig is the Director of Research at Google Inc, where he has been since 2001. From 2002-2005 he was Director of Search Quality, which means he was the manager of record responsible for answering more queries than anyone else in the history of the world. He is a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery and co-author of Artificial Intelligence: A Modern Approach, the leading textbook in the field (with 94% market share). Previously he was the head of the Computational Sciences Division at NASA Ames Research Center, making him NASA's senior computer scientist. He received the NASA Exceptional Achievement Award in 2001. He has served as an assistant professor at the University of Southern California and a research faculty member at the University of California at Berkeley Computer Science Department, from which he received a Ph.D. in 1986 and the distinguished alumni award in 2006. He has over fifty publications in Computer Science, concentrating on Artificial Intelligence, Natural Language Processing and Software Engineering, including the books Paradigms of AI Programming: Case Studies in Common Lisp, Verbmobil: A Translation System for Face-to-Face Dialog, and Intelligent Help Systems for UNIX. He is also the author of the Gettysburg Powerpoint Presentation and the world's longest palindromic sentence.   ... "

Uninformed Consent

Persistence of Surveillance online.   A non-technical survey of hidden capabilities and implications.

  Uninformed Consent  in the HBR

Companies want access to more and more of your personal data — from where you are to what’s in your DNA. Can they unlock its value without triggering a privacy backlash?

Three years ago the satirical website The Onion ran an article with the headline “Woman Stalked Across 8 Websites by Obsessed Shoe Advertisement.” Everywhere she went online, this fictional consumer saw the same ad. “The creepiest part,” she says in the story, “is that it even seems to know my shoe size.” The piece poked fun at an increasingly common — if clumsy — digital marketing technique. But today its gentle humor seems almost quaint. Technology has advanced far beyond the browser cookies and retargeting that allow ads to follow us around the internet. Smartphones now track our physical location and proximity to other people — and, as researchers recently discovered, can even do so when we turn off location services. We can disable the tracking on our web browsers, but our digital fingerprints can still be connected across devices, enabling our identities to be sleuthed out. Home assistants like Alexa listen to our conversations and, when activated, record what we’re saying. A growing range of everyday things — from Barbie dolls to medical devices — connect to the internet and transmit information about our movements, our behavior, our preferences, and even our health. A dominant web business model today is to amass as much data on individuals as possible and then use it or sell it — to target or persuade, reward or penalize. The internet has become a surveillance economy.    ... "

Efficiency for Machine Learning Automation

 And more elements of AI automation.  Here from MIT.   The details of the data construction for this is also described,  which is always enlightening.

Machine-learning system tackles speech and object recognition, all at once

Model learns to pick out objects within an image, using spoken descriptions.   By Rob Matheson | MIT News Office

MIT computer scientists have developed a system that learns to identify objects within an image, based on a spoken description of the image. Given an image and an audio caption, the model will highlight in real-time the relevant regions of the image being described.

Unlike current speech-recognition technologies, the model doesn’t require manual transcriptions and annotations of the examples it’s trained on. Instead, it learns words directly from recorded speech clips and objects in raw images, and associates them with one another.

The model can currently recognize only several hundred different words and object types. But the researchers hope that one day their combined speech-object recognition technique could save countless hours of manual labor and open new doors in speech and image recognition.

Speech-recognition systems such as Siri and Google Voice, for instance, require transcriptions of many thousands of hours of speech recordings. Using these data, the systems learn to map speech signals with specific words. Such an approach becomes especially problematic when, say, new terms enter our lexicon, and the systems must be retrained.

“We wanted to do speech recognition in a way that’s more natural, leveraging additional signals and information that humans have the benefit of using, but that machine learning algorithms don’t typically have access to. We got the idea of training a model in a manner similar to walking a child through the world and narrating what you’re seeing,” says David Harwath, a researcher in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Spoken Language Systems Group. Harwath co-authored a paper describing the model that was presented at the recent European Conference on Computer Vision.

In the paper, the researchers demonstrate their model on an image of a young girl with blonde hair and blue eyes, wearing a blue dress, with a white lighthouse with a red roof in the background. The model learned to associate which pixels in the image corresponded with the words “girl,” “blonde hair,” “blue eyes,” “blue dress,” “white light house,” and “red roof.” When an audio caption was narrated, the model then highlighted each of those objects in the image as they were described. .... "

Related article.

DarwinAI to Automate AI Development

Another move towards the automating of AI, from U of Waterloo

DarwinAI launches from stealth to automate artificial intelligence development  By Maria Deutscher in SiliconAngle

 Artificial intelligence projects usually rely on existing code. Engineers sift through the AI models available from sources such as academic publications, pick the one deemed most suitable and then customize it to their requirements.

Canada’s DarwinAI Inc. wants to reduce the amount of work involved in the last two steps. The startup today launched from stealth with $3 million in funding and a specialized development platform that promises to automate AI projects.

DarwinAI’s software is based on research conducted by co-founder Alexander Wong at the University of Waterloo, where he serves as a professor with the systems design engineering department. The platform can customize an existing AI for the requirements of an application using its own built-in neural network.

According to DarwinAI, the software works by deriving a series of new models from the original based on user-defined parameters. Engineers can then pick the version with the particular combination of characteristics that best matches their target use case and, if necessary, make further enhancements. The startup said AI models created with its software are not only faster but also considerably more efficient.  ... " 

Monday, September 17, 2018

Facebook Advertising from Advertisemint

Just started to read Brian Meert's book:  'The Complete Guide to Facebook Advertising'   Nicely done.   Am no expert in Facebook advertising, but the book takes you through the process and motivations for using Facebook.    See also their company Avertisemint.    More to follow:

They Write:  " ... Facebook is one of the most popular social media sites to advertise one’s business, and for a good reason: it has more than two billion active users, a wealth of user data, and numerous ad formats. In the age of social media when nine in ten people check their phones an hour after waking up in the morning, Facebook advertising is the perfect complement to your advertising strategy. In The Complete Guide to Facebook Advertising, Brian Meert teaches you how to advertise on Facebook. He walks you through step-by-step guides filled with illustrations and easy-to-understand explanations. Additionally, he provides free resources and tips on how to create the perfect Facebook ad.  ... "   

Sisense to Understand and Visualize Data

Of interest. A challenge for the enterprise.  Will this solve it?  I like the idea of making the results broadly available in the enterprise.  Both for use of the data and understanding what you have available.  Now could it also intelligently suggest which data you need?   Point out the holes in your data, perhaps by industry context?

See also past posts on how Sisense can link with Amazon Echo ...

Sisense hauls in $80M investment as data analytics business matures  In TechCrunch By Ron Miller  @ron_miller

Sisense, a company that helps customers understand and visualize their data across multiple sources, announced an $80 million Series E investment today led by Insight Venture Partners. They also announced that Zack Urlocker, former COO at Duo Security and Zendesk, has joined the organization’s board of directors.

The company has attracted a prestigious list of past investors, who also participated in the round, including Battery Ventures, Bessemer Venture Partners, DFJ Venture Capital, Genesis Partners and Opus Capital. Today’s investment brings the total raised to close to $200 million.

CEO Amir Orad says investors like their mission of simplifying complex data with analytics and business intelligence and delivering it in whatever way makes sense. That could be on screens throughout the company, desktop or smartphone, or via Amazon Alexa. “We found a way to make accessing data extremely simple, mashing it together in a logical way and embedding it in every logical place,” he explained.   ..."

Data Imperative

Good O'Reilly Talk from recent conference:

The Data Imperative

Ben Sharma shares how the best organizations immunize themselves against the plague of static data and rigid process

By Ben Sharma September 13, 2018

BBC on Job Replacement

Jobs will be improved, switched in their nature, include many more cases of working with technology and both physical and cognitive robotics.  Be adaptive.  This will not mean you will have to learn advanced math or programming to be employed.

WEF: Robots 'will create more jobs than they displace'

Millions of jobs are likely to be displaced by automation but we have less to fear from robots than some might think, a report from the World Economic Forum has suggested.

The Swiss think tank predicts that robots will displace 75 million jobs globally by 2022 but create 133 million new ones - a "net positive".

It said advances in computing would free up workers for new tasks.

But others have warned there is no guarantee lost jobs will be replaced.

AI 'poses less risk to jobs than feared'
Bank warns on AI jobs threat
The WEF, which runs the famous Davos networking event, said that robots and algorithms would "vastly improve" the productivity of existing jobs and lead to many new ones in the coming years.  ... "

Customer Service State and Future

Good look at state and future of customer service, including advanced tech being used.   Have noted changes in how I use customer service.   In CustomerThink:

Customer Service: Where We Are and Where We Are Going
By Fara Haron in CustomerThink

Product and service-based businesses need a place to direct customers in need. If they don’t have one, it’s a fast road to an angry audience and a poor reputation. Customer service is a constant need across industries and has been for decades. However, not much light has been shed on the vast progress of this industry over the years. It started out with confused or upset customers picking up their landline for help, but today the average contact center supports an average of nine communication channels among email, web chat, social media and much more. To provide some insight on what’s happening behind the customer inquiry scenes, let’s take a look at the evolution of the contact center. How are customers currently serviced, how can we create the most efficient environment today, and how can customers expect to communicate 20 years from now? Perhaps more importantly, what is the data about customer expectations telling us? ... "

Advertising in the Age of Alexa

A former colleague writes. More at the link.

Advertising in the Age of Alexa or: How to Stop Worrying and Build Your Brand  By Lou Killeffer

Very glad to be returning as an Adjunct Professor in the School of Media and Journalism at the University of North Carolina at Chapel Hill.

When the "Advertising Campaigns" course I taught last year (Chobani & Chapel Hill) became unavailable, Carolina asked me to create a new course of my own, and last week the Curriculum Committee approved it: MEJO 490.5 "Advertising in the Age of Alexa or: How to Stop Worrying and Build Your Brand". 

My aim is an exploration of established advertising and brand theory and their evolving best practices in response to decades of continuous digital disruption. Through selected readings, engaging discussion, student research, and live interface with some of today’s most enlightened, real-world practitioners, we'll investigate  .... "

Modeling a Simple Organism

The nematode Caenor Elegans makes up about 80% of the animals on earth.  Yet it could be called the  most successful animal on earth.  Lives in most any environment.   We have completely sequenced its DNA.  We have been studying it for decades.  It has just 959 cells in its 'Brain',  302 neurons, each of its neurons are connected to 30 others.  So about 10K synapses.   (Humans have trillions).  So we should understand how a nematode's brain works?   No, not even close.   And we have been trying very hard. (Via Byron Reese in his book: The Fourth Age: Smart Robots, Conscious Computers and the Future of Humanity)  Good book on the direction, challenges and cautions of AI.

OpenWorm is an open source project dedicated to creating the first virtual organism in a computer.

Because modeling a simple nervous system is a first step toward fully understanding complex systems like the human brain.

By rejecting red tape and building a community of engineers, scientists, and other motivated volunteers from around the world. ... " 

Guide to Training Data

Nicely done and worth a look:

The Essential Guide to Training Data

A Guide for Machine Learning from Figure Eight
A machine learning algorithm isn't worth much without great training data to power it.

At Figure Eight, we've been providing that training data for a decade. We understand how to take raw data and annotate it so that it can be used to power the most innovative AI projects.

In The Essential Guide to Training Data, we share some of the lessons we've learned along the way. Download the guide and you'll learn about: 

Why simply using more data is often better than finding the latest cutting edge algorithm
Why just having a lot of big data isn’t the same as having labeled data
Where to find some great open datasets to bootstrap your model
Download the guide today.

Best regards,

The Figure Eight Team

Sunday, September 16, 2018

Intelligent Automation on Pace for Explosive Growth

Links of common processes to automation.   Good place to start before you decide to make all your systems 'intelligent'.    Note in particular coverage of RPA:  Robotic Process Automation.

Intelligent Automation on Pace for Explosive Growth, but Organizational Challenges Prevalent  by Kent Weare in InfoQ

In a recent KPMG study, the professional services organization published a report called Ready, Set, Fail?: Avoiding setbacks in the intelligent automation race which projects rapid growth of the intelligent automation (IA) domain. The report suggests that overall spend will reach $232 billion by 2025 compared to $12.4 billion which is spent today. But, this expected growth comes with many challenges, including tool maturity, skilled labor, organizational change management, governance and a lack of clarity involving return on investment.

Intelligent automation is an emerging set of new technology tools that mimic the actions a user would ordinarily perform to complete a task. Federico Berruti, a partner at McKinsey & Company, defines intelligent automation as: 

A suite of business-process improvements and next-generation tools that assists the knowledge worker by removing repetitive, replicable, and routine tasks. And it can radically improve customer journeys by simplifying interactions and speeding up processes.   ... "

P&G invents unique remedy for the common cold

From an un-expected direction by a  former employer.    It used to be that curing the common cold was an example of fabled innovation.   Does not seem to be that,  but a start?

P&G invents unique remedy for the common cold
BY Barrett J. Brunsman  – Staff reporter, Cincinnati Business Courier

Procter & Gamble Co. has been granted a patent for a liquid cold medication with the unique combination of a decongestant and the flavor of anise, an herb that some people find tastes similar to licorice or fennel.

The Cincinnati-based maker of consumer goods such as Vicks NyQuil cold and flu remedies (NYSE: PG) stated in a filing with the U.S. Patent & Trademark office that flavors are commonly added to liquid medications to mask an unpleasant taste.

Anise flavoring has been widely used in such medications, in particular nighttime multi-symptom relief cold and flu remedies, P&G stated. Many consumers not only enjoy that flavor but also trust and expect it. 

“Some consumers would like an anise flavored multi-symptom relief cold/flu medication that also contains phenylephrine hydrochloride, a decongestant,” P&G stated. “However, this formulation is not currently sold because it has surprisingly been found that anise flavoring (causes phenylephrine hydrochloride) to degrade, which makes the liquid medication less effective and significantly reduces the shelf life of the product.”  .... "

Saturday, September 15, 2018

Forrester Talks Digital Twins

Forrester pitches an expensive report below.   Worth a look.  Algorithms are interesting, but like with the term AI what they mean is usually more limited.  They work well in narrow domains for specific goals.  They do not mean they are intelligent nor are they even close to a 'Twin' of how we behave.  The term, like 'intelligence' can be used as a useful, broad description of a cognitive model of human capabilities.  It can replace some things that people do, but not all of them.  Again, beware the marketing.   Twin as a filter I like, so use the term filter.

The Algorithm Of You    By Fatemeh Khatibloo   Principal Analyst Forrester

Algorithm. It’s a buzzword you hear frequently these days. But does the average consumer understand the impact algorithms have on her life? Absolutely not. Consumers enjoy the illusion of unlimited choice in products, services, and content, but there’s almost always an algorithm behind the curtain, constantly refining and defining what’s presented to her.

Like it or not, we’re in the age of the algorithm.

Unfortunately, many businesses lost consideration for the human amidst the ceaseless data ingestion and optimization of these algorithms, and that’s led to negative outcomes for real people. While some governments are enacting regulation, we don’t think that solves the technology and ethics problem. Rather, we envision a new approach that puts the tools for data control in the hands of people and turns the tide of the impending “algopocalypse.”

In my latest report, “The Algorithm Of You: Meet Your Personal Digital Twin,” I introduce the concept of a personal digital twin (PDT), which I’ve defined as:

An algorithm owned by an individual, optimized for his or her personal objectives. It filters content that is counterproductive to the individual’s goals and identifies opportunities that support achieving them.

PDTs will eventually function as a digital proxy for each of us — they will learn what we value, what we prefer, and how we make decisions. We’ll be able to optimize them for hyperpersonalization, or serendipity. And as we do, the benefits will abound for the organizations we do business with. They’ll finally be able to:

Reach the right level of customer obsession.
Reduce marketing spending waste.
Optimize customer lifetime value.
Protect their brands from costly privacy and security missteps.
Build relationships with customers who actually want a relationship with them.
I’d love to hear your thoughts and invite you to reach out to me via inquiry or on Twitter!  ... "

AI Overhyped? The Term is.

The problem is the term AI itself.   The assumption that it is far more than it is.   This does not mean you should not think about how smarter capabilities could be inserted into codes to augment our capabilities.  For a while we were using the term 'Cognitive Systems' to indicate methods closer and even mimicking human perception and abilities.  Probably be better to ditch 'AI' and go with Cognitive.  Though even the latter requires too much explanation and can be over emphasized.   Our Cognitive Systems Institute, monitored here,  attempts to emphasize cognitive aspects. Beware over-marketing.

 Artificial intelligence is often overhyped—and here’s why that’s dangerous

AI has huge potential to transform our lives, but the term itself is being abused in very worrying ways, says Zachary Lipton, an assistant professor at Carnegie Mellon University.
by Martin Giles

To those with long memories, the hype surrounding artificial intelligence is becoming ever more reminiscent of the dot-com boom.

Billions of dollars are being invested into AI startups and AI projects at giant companies. The trouble, says Zachary Lipton, is that the opportunity is being overshadowed by opportunists making overblown claims about the technology’s capabilities.

During a talk at MIT Technology Review’s EmTech conference today, Lipton warned that the hype is blinding people to its limitations. “It’s getting harder and harder to distinguish what’s a real advance and what is snake oil,” he said.

AI technology known as deep learning has proved very powerful at performing tasks like image recognition and voice translation, and it’s now helping to power everything from self-driving cars to translation apps on smartphones,

But the technology still has significant limitations. Many deep-learning models only work well when fed vast amounts of data, and they often struggle to adapt to fast-changing real-world conditions.

In his presentation, Lipton also highlighted the tendency of AI boosters to claim human-like capabilities for the technology. The risk is that the AI bubble will lead people to place too much faith in algorithms governing things like autonomous vehicles and clinical diagnoses.

“Policymakers don’t read the scientific literature,” warned Lipton, “but they do read the clickbait that goes around.” The media business, he says, is complicit here because it’s not doing a good enough job of distinguishing between real advances in the field and PR fluff.

Lipton isn’t the only academic sounding the alarm: in a recent blog post, “Artificial Intelligence—The Revolution Hasn’t Happened Yet,” Michael Jordan, a professor at University of California, Berkeley, says that AI is all too often bandied about as “an intellectual wildcard,” and this makes it harder to think critically about the technology’s potential impact. ... " 

Alexa Wants to Simplify the Skill Experience

Some 50K skills, but many of them rather pointless. Now if only they could only work together to create something very useful. The unworldliness of all this will cause it collapse.   Not to say the basics of playing music, managing lights and cameras isn't useful and even fun.   But you can't just continue to chop the basic pieces up into smaller ones. 

Its not much different in Google Home.  There I found I could ask questions of the assistant in German,  but she insisted on answering with snippets in English.    I want things that can talk, converse, do useful things when they work together or with people.  Insightful and coherent, so I come out of the interaction a little smarter.   I would take a few hundred skills, if they were the right ones.  So when are we planning delivery?

Amazon wants Alexa to figure out how to fulfill users’ without help from Skills   By AJ Dellinger in Digitaltrends

Amazon’s wildly popular voice assistant Alexa has managed to make herself invaluable to many people because of the wide range of abilities available through Alexa Skills. Now, Amazon is reportedly getting ready to kill off the feature — well, kind of — in favor of a system that will simplify the experience for users.  ... "