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Thursday, June 21, 2018

Cisco Crosswork IP network

New to me, apparently a new kind of architecture.

Laying the Foundations for Innovation

By Philippe Bralet  in the Cisco Blog

Cisco Crosswork provides the holistic real-time insight needed to transform your network operations

Service providers today are facing big challenges, with fast, flexible services and huge bandwidths expected as standard.

If they want to remain competitive by delivering efficient services, providers need a full understanding of what’s going on within their systems. But obtaining accurate and timely operational information has never been easy. And as networks grow more complex, it’s getting harder.

The nature of modern multivendor networks means that the information service providers have on their operations is often incomplete. And even when they can access it, it’s difficult to get to grips with. It comes from multiple sources, in inconsistent formats, and often when it’s too late to act.

A simpler network view

Is there a better way? We think so. Our experts have been working hard to create Cisco Crosswork, our new holistic networking framework. Crosswork uses developments like machine learning and big data to give service providers a comprehensive understanding of how their networks are functioning.

Combining open APIs with our world-leading telemetry solutions, it enables a single, complete and real time overview. It works across physical and virtual technology from different vendors, as well as third party applications, to lay the foundations for effective automation.

The mass awareness enabled by Cisco Crosswork   provides thousands of times more insight, opening up new opportunities for service providers. They can manage their spending more effectively, developing agile, efficient services to meet their customers’ expectations. ..... "

IEEE Roadmap Reports for Devices and Systems

Am a long time member of IEEE,  a wealth of useful information.  Often reference their publications here.   The newest set of such publications.

IEEE Releases the International Roadmap for Devices and Systems (IRDS)

PISCATAWAY, NEW JERSEY, June 18. 2018 – IEEE, the world’s largest technical professional organization dedicated to advancing technology for humanity, today announced the release of the 2017 edition of the International Roadmap for Devices and Systems (IRDS), building upon 15 years of projecting technology needs for evolving the semiconductor and computer industries. The IRDS is an IEEE Standards Association (IEEE-SA) Industry Connections (IC) Program sponsored by the IEEE Rebooting Computing (IEEE RC) Initiative, which has taken a lead in building a comprehensive view of the devices, components, systems, architecture, and software that comprise the global computing ecosystem. .... " 

Free, downloadable roadmap reports: 
    https://irds.ieee.org/roadmap-2017

Wednesday, June 20, 2018

Microsoft to Acquire Bonsai AI

Had previously looked at this, and looks good on the surface of it.   Will take a closer look.

Microsoft to acquire machine learning startup Bonsai, fueling AI efforts   By Taylor Soper in Geekwire

Microsoft is adding more firepower to its artificial intelligence arm. The tech giant has agreed to acquire Bonsai, a San Francisco-based startup that helps enterprise companies add machine learning and AI capabilities into their existing operations.

Founded in 2014 by former Microsoft engineer Mark Hammond and Keen Browne, Bonsai’s technology allows customers in industries like energy, manufacturing, and automotive build AI into their intelligent systems and processes. Its automated platform lets subject matter experts train autonomous systems, regardless of AI knowledge  .... " 

See more at Bonsai.  Powerful claims:  " ... Teaching is the New Programming  .....   Machine Teaching, one of the key innovations in the Bonsai Platform, infuses your organization's unique subject matter expertise directly into an AI model, resulting in accelerated training and more accurate predictions.   ... " 

See also their report on acquisition:  
Microsoft to acquire Bonsai in move to build ‘brains’ for autonomous systems   By Gurdeep Pall - Corporate Vice President, Business AI ... (This contains considerable detail about what they do and are testing with Microsoft) ....

Blockchain from Berkeley

After teaching an on-campus course about cryptocurrencies, UC Berkeley is planning to launch a two-part, online course aimed at educating students around to globe about cryptocurrencies and business-scale blockchain networks.       .... 
   
 in Computerworld: By Lucas Mearian

China increases Biometric Public Transport Scanning

If does seem that while we fret about the possible misuses of tracking data from such passive biometric scanning, other countries are  seeing the efficiency value.  Note the cautious CYA phrase below 'Perhaps too high tech'.

China speeds up its subway with palm scanners and facial recognition in DigitalTrends

While New York attempts to update its public transportation system to run on time and use mobile tickets, commuters over in Beijing are looking at a range of high tech upgrades. In fact, perhaps too high tech. As per a China Daily report, the Chinese capital of Beijing is now considering the introduction of “bio-recognition technology” to its subway station. This technology would include palm scanners and facial recognition scanners, and would purportedly help increase efficiency and decrease gridlock in key stations during rush hour.  ... " 

Death of Supply Chain Management

The death of? No, but lots of new augmentations popping up.

The Death of Supply Chain Management in 7WData

The supply chain is the heart of a company’s operations. To make the best decisions, managers need access to real-time data about their supply chain, but the limitations of legacy technologies can thwart the goal of end-to-end transparency. However, those days may soon be behind us. New digital technologies that have the potential to take over supply chain management entirely are disrupting traditional ways of working. Within 5-10 years, the supply chain function may be obsolete, replaced by a smoothly running, self-regulating utility that optimally manages end-to-end work flows and requires very little human intervention. With a digital foundation in place, companies can capture, analyze, integrate, easily access, and interpret high quality, real-time data – data that fuels process automation, predictive analytics, artificial intelligence, and robotics, the technologies that will soon take over supply chain management. .... " 

Willingness to Pay vs Like What You Buy

This often took a place in research we did. 

Why Willingness to Pay Doesn’t Mean Consumers Like What They Buy in Knowledge@Wharton

Marketers have long relied on willingness to pay as a way to gauge consumer preference for a product, and rightly so. At the height of the Cabbage Patch Kids doll craze in the 1980s, sales passed the $600 million mark, according to Bloomberg News. Now the toy line has an estimated revenue of $50 million a year, indicating a much lower consumer preference. But new research from Alice Moon, Wharton professor of operations, information and decisions, shows that willingness to pay isn’t always a clear indicator of preference. The paper is titled, “The Uncertain Value of Uncertainty: When Consumers are Unwilling to Pay for What They Like,” and was coauthored with Leif D. Nelson from the University of California, Berkeley. She spoke to Knowledge@Wharton about other factors that should be taken into consideration when marketers are trying to price their products.

An edited transcript of the conversation follows.

Knowledge@Wharton: Tell us about your research.

Alice Moon: One of the most critical issues for marketers is how to forecast consumer product interest and consumer preference. One way they frequently do this is by asking consumers how much they’re willing to pay as a measure of their interest in, or value for, that product. I study when that measure insufficiently captures how much a consumer values that product. I find that willingness to pay is informed by many factors, such as what price they think the market is setting for this product. Sometimes those types of factors overshadow the part of willingness to pay that signals preference. Because of that, when you’re trying to understand people’s preferences by looking at how much people are willing to pay for products, you’ll make the wrong assumption about how much they like it.

“[When] you’re trying to understand people’s preferences by looking at how much people are willing to pay for products, you’ll make the wrong assumption about how much they like it.” .... "

Robots Powered by Water Jets

Clever idea for firefighting, other in water contexts.

Firefighting Robot Snake Flies on Jets of Water
Using steerable jets of water like rockets, this robot snake can fly into burning buildings to extinguish fires   ...  By Evan Ackerman in IEEE Spectrum  With Video

Fires have an unfortunate habit of happening in places that aren’t necessarily easy to reach. Whether the source of the fire is somewhere deep within a building, or up more than a floor or two, or both, firefighters have few good options for tackling them. They can either pour water into windows (which doesn’t always work that well), or they can try and get into the building, which seems like it’s probably super dangerous. .... " 

Retailers Shortchanging National Brands

We spent much time and effort examining private retail label versus retail brands.  Was just in a Kroger today and scanned some categories we had worked with, and the evolution of changes wwas stunning.

Are retailers short-changing national grocery brands?     by Tom Ryan in Retailwire, includes expert comment. 

A study from Acosta finds that shoppers overwhelmingly prefer national brands and that pushes toward private labels might be undermining their effectiveness.

Overall, shoppers agreed that “name brands are better than store brands” in 41 of 53 categories, including pet food, beauty & personal care, carbonated soft drinks, coffee and chocolate.

Name and store brands were found to be “about the same” in 12 out of 53. These were most likely in the perimeter (dairy, produce, fresh meat, bakery, etc.) as well as paper products and bottled water.

For no category did respondents believe that store brands are better than name brands.

Generally, the more personal, innovative and differentiated the category, the more likely a shopper is to choose a national brand over a private label brand.

The top three reasons consumers gave for purchasing national brands while grocery shopping included:

“National brand products are higher quality in taste and/or performance.”
“I can get better deals on national brands (through sales/coupons).”
“I trust national brand products more.”
Cost savings was the primary driver of private label brands, and purchases are often viewed as a compromise, the study found.

An accompanying study of over 100 retailers found:
  .... " 

GE Intelligent Systems and Wise.io

Standards make sense iif you plan to replicate new technologies.

GE’s intelligent systems: Creating an AI, machine learning standard

By Kylie Anderson in SiliconAngle

 The business potential in artificial intelligence technologies has enterprises across industries prioritizing the discovery of machine learning opportunities to leverage their next big innovation. In the surge toward modernization, some companies run the risk of overlooking the fundamentals of operational success, specifically the teams that must work with each other and the technology itself, as traditional production processes rapidly change.

“Even if you have really good data science teams, it’s incredibly hard to go from white board into production,” said Jeff Erhardt, vice president of intelligent systems at General Electric Co. “How do you take concepts and make them work reliably, repeatably, scalably over time?”

Following GE’s acquisition of machine learning company Wise.io, where Erhardt served as chief executive officer, Erhardt has been working to implement his former company’s processes at scale within the multinational conglomerate. .... " 

(Update): Future of Jobs in the Age of Augmented Intelligence

 Future of Jobs in the Age of Augmented Intelligence

Talk Attendance Link: https://zoom.us/j/7371462221   June 21, 10:30 AM EDT

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

Talk Description:
 Jobs, and nature of work as we know it, are  changing rapidly.   As companies become more "digital," employees need to be empowered to become more innovative.  In many industries and countries, the most in-demand occupations, specialties, and skills did not exist 10 or even five years ago, and the pace of change is set to accelerate. This will have a tremendous impact on how the workforce of the future acquires and applies new skills, and how companies organize work to stay nimble and competitive. In this talk, Yassi Moghaddam, ISSIP Executive Director talks about how ISSIP members are working together to map out skills required for the future of work in which AI would enhance and augment, not replace, human capabilities.

Bio:
Yassi Moghaddam is the Executive Director of International Society of Service Innovation Professionals (ISSIP), www.issip.org, a non-profit organization that has partnered with industry leaders and many universities to promote Service Innovation (people-centred technology-enabled value co-creation) across the globe.  In this role, she has been spearheading industry-academia collaboration to help close the skills gap between education and employment for the emerging innovative jobs of the 21st century. Yassi is also Managing Director of Stradanet, a boutique Silicon Valley consulting firm where she has been driving innovation initiatives working with leading companies including Cisco, VMware, Wells Fargo, Applied Materials, and a number of startups. She  holds an MBA from Columbia University, an MSc in Electrical Engineering (EE) from Georgia Tech, and a BSc in EE from University of Oklahoma.

Speaker: Yassi Moghaddam,  ISSIP

More on an upcoming ISSIP conference on this topic.

Also on this topic I suggest reading Byron Reese's new book:  The Fourth Age: Smart Robots, Conscious Computers and the Future of Humanity.    Which I am in the midst of reading.  Good section on jobs and AI.

Tuesday, June 19, 2018

Its All About Training Data

Was impressed by Figure Eight (formerly Crowdflower). They get at the crux of the matter.  You have to have the right data. 

" ... 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 our new ebook, The Essential Guide to Training Data, we share some of the lessons we've learned along the way. Download the ebook 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 data sets to bootstrap your model
Download the report today.

Best regards,
     The Figure Eight Team  ..... " 


Microsoft Builds Bots for Productivity

Microsoft looks to bots to make employees more productive.  Recall their now long ago work with the 'Clippy' bot.

Microsoft is continuing its quest to try to make workers more productive via a variety of bots, including SwitchBot and Calendar.help.   By Mary Jo Foley

Information about SwitchBot was made public in the form of a research paper published on April 21 for the 2018 ACM Conference on Human Factors in Computing Systems.

SwitchBot is a Skype bot that aims to help workers detach and then reengage at the start and end of their workdays. It's goal: To make workers more productive by getting workers to better use their time on and off the job. .... " 

Choosing an AI Strategy

Example of a corporate approach, not enough detail to really pin what the strategy is, but shows you the complexity and that few companies are advanced in this area.

The Right Fit: Choosing an AI Strategy

Dun & Bradstreet is transforming its own internal AI and analytics operations, even as it helps customers with their analytics and machine learning transformations.

How does your organization compare to its peers in terms of artificial intelligence implementations today? Do you feel as if you are behind? Rest assured, even if you don't have a program in place today, you are in good company.  .... "

Threat Intelligence

Did some work with Recorded Future, an impressive group.

How to Empower Teams With Threat Intelligence   By Amanda McKeon 

In this episode of the Recorded Future podcast, we examine how threat intelligence applies to a variety of roles within an organization, and how security professionals can integrate it to empower their team to operate with greater speed and efficiency. How does threat intelligence apply to SOCs, to incident response, or vulnerability management? And how do corporate leaders make the case that threat intelligence is a worthwhile investment?

Joining us to address these questions is Chris Pace, technology advocate at Recorded Future.

Marriott Installs Alexa

The hospitality angle is not new, have seen tests underway, started in casinos. Tailored to local and hotel information.  In general you cannot bring your own assistant,  I tried that for a test on a trip, the local Wifi was too restrictive.

Amazon launches Alexa for hotels
'Alexa, send up a bottle of wine.'

By Rachel England, @rachelengland in Engadget

Visitors to Marriott hotels will soon be able to use Amazon Alexa to make their stays more enjoyable. "Alexa for Hospitality" lets guests ask Alexa -- via an in-room Amazon Echo -- for help with hotel information, booking guest services, playing music and managing room controls, such as lighting and temperature.   ... " 

Monday, June 18, 2018

Sentiment Analysis Uses and Comparisons

A look at various sentiment applications and services.    Have used a couple of these.

Machine Learning as a Service: Part 1  from Towards Data Science. By Sebastian Kwiatkowski

Sentiment analysis: 10 applications and 4 services
What is sentiment analysis?

The explosive growth in user-generated content and the digitization of archive material have created massive data sets containing opinions expressed by large numbers of people on just about every single topic.

In some cases, the generation of this data is structured through the user interface. It is, for example, relatively easy to process customer reviews on e-commerce sites, because users are required to post a rating alongside the text of the product review.

Most data, however, is available in an unstructured form. It does not contain a standardized summary saying “This content expresses a positive, negative, mixed or neutral view.”

WordPress.com, for example, reports that bloggers using their platform have published more than 87 million posts just in May of 2018.[1] According to YouTube CEO Susan Wojcicki, more than 400 hours of content are uploaded to the video-sharing site every minute.[2] Meanwhile, the Google Books project has digitized at least 25 million volumes in 400 languages.[3]

Whenever a user types into a free text field or speaks into a microphone, an inference is required to categorize the sentiment.

Sentiment analysis is the field that focuses on exactly this task. It is a branch of natural language processing that studies functions designed to map a text document to a representation of a sentiment.

With the advent of accurate speech and text recognition, the reach of sentiment analysis extends beyond readily accessible digital text data and covers an increasing number of media. ... "

Google Leveraging Digital Assistants

In FMIdailyLead:
Grocers among those launching ad deals with Google

Several major grocers including Costco and Walmart have formed search alliances with Google that include being featured in results from its digital assistants. Instead of paying for ads, the stores agree to share sales revenue with Google, which coordinates purchases through its shopping cart.

in Cnbc.

Drones Detecting Physical Behavior

Another case of complex pattern recognition.  In live video.  Here the drone is classifying a set of human behaviors and them classify them as a 'brawl'.  In English a violent, multi person fight.  Could be with or without weapons.  Could then be integrated further into a model of a crowd.  And identify individuals.    No indication that the drone would do anything other than alert the authorities.    Will see how accurate this is, and how its integration into police decision making is envisioned.

AI Drone Learns to Detect Brawls      in IEEE Spectrum  by Jeremy Hsu

Researchers at the University of Cambridge in the U.K., working with colleagues at the Indian Institute of Science, Bangalore and India's National Institute of Technology, Warangal, have used deep learning to develop a drone surveillance system that automatically detects small groups of people fighting each other. The system uses computer vision software that runs in real time to detect violent individuals, says the University of Cambridge's Amarjot Singh. The researchers trained deep learning algorithms to recognize violent actions by identifying body and limb poses in staged video footage of interns mimicking violence. Singh replaced some of the neural network layers at the front-end with fixed parameters, and used supervised learning toward the back-end, exchanging some of the deep learning process with human engineering input. This allowed the resulting ScatterNet Hybrid Deep Learning (SHDL) network to learn more quickly with less data and less available computing power. The researchers are securing permission from Indian officials to test the system at two upcoming music festivals, and Singh is working to incorporate crowd modeling into the deep learning models.  ... "

Creativity plus Analytics

This was often our biggest goal, often attempted by linking humans and analytics.  Good view here:

The most perfect union: Unlocking the next wave of growth by unifying creativity and analytics  in McKinsey.  By Brian Gregg, Jason Heller, Jesko Perrey, and Jenny Tsai 

Companies that harness creativity and data in tandem have growth rates twice as high as companies that don’t. Here’s how they do it. ... 

GigaOM Voices of AI

Another great look at the topic.   Currently reading Byron Reese's book, will soon follow with notes on that.

Voices in AI – Episode 50: A Conversation with Steve Pratt  By Byron Reese

Byron Reese: This is Voices in AI, brought to you by GigaOm, and I’m Byron Reese. Today, our guest is Steve Pratt. He is the Chief Executive Officer over at Noodle AI, the enterprise artificial intelligence company. Prior to Noodle, he was responsible for all Watson implementations worldwide, for IBM Global Business Services. He was also the founder and CEO of Infosys Consulting, a Senior Partner at Deloitte Consulting, and a Technology and Strategy Consultant at Booz Allen Hamilton. Consulting Magazine has twice selected him as one of the top 25 consultants in the world. He has a Bachelor’s and a Master’s in Electrical Engineering from Northwestern University and George Washington University. Welcome to the show, Steve.

Steve Pratt: Thank you. Great to be here, Byron.

Let’s start with the basics. What is artificial intelligence, and why is it artificial?

Artificial intelligence is basically any form of learning algorithm; is the way we think of things. We actually think there’s a raging religious debate [about] the differences between artificial intelligence and machine learning, and data science, and cognitive computing, and all of that. But we like to get down to basics, and basically say that they are algorithms that learn from data, and improve over time, and are probabilistic in nature. Basically, it’s anything that learns from data, and improves over time.

So, kind of by definition, the way that you’re thinking of it is it models the future, solely based on the past. Correct?

Yes. Generally, it models the future and sometimes makes recommendations, or it will sometimes just explain things more clearly. It typically uses four categories of data. There is both internal data and external data, and both structured and unstructured data. So, you can think of it kind of as a quadrant. We think the best AI algorithms incorporate all four datasets, because especially in the enterprise, where we’re focused, most of the business value is in the structured data. But usually unstructured data can add a lot of predictive capabilities, and a lot of signal, to come up with better predictions and recommendations. .... "

Google Invests in JD.Com

Google invests heavily in Chinese e-commerce giant JD.com  BY James Farrell In SiliconAngle

Google Inc. will invest $550 million in China’s second largest e-commerce firm JD.com, a move that  will give the company a bigger presence in the Asian market and also bolster its position against competitor Amazon.com Inc.  ... "

If You’re a Facebook User, You're also a Research Subject

We are all Research Subjects ...

If You’re A Facebook User, You’re Also a Research Subject
The social network is careful about academic collaborations, but chooses projects that comport with its business goals.   By Karen Weise  and Sarah Frier in Bloomberg

The professor was incredulous. David Craig had been studying the rise of entertainment on social media for several years when a Facebook Inc. employee he didn’t know emailed him last December, asking about his research. “I thought I was being pumped,” Craig said. The company flew him to Menlo Park and offered him $25,000 to fund his ongoing projects, with no obligation to do anything in return. This was definitely not normal, but after checking with his school, University of Southern California, Craig took the gift. “Hell, yes, it was generous to get an out-off-the-blue offer to support our work, with no strings,” he said. “It’s not all so black and white that they are villains.”  ... " 

Sunday, June 17, 2018

China Infuses the Corner Store with AI

Of interest, a move ahead in China that should be watched.

China's AI-infused corner store of the future  in Axios

China’s take-no-prisoners Big Tech war is playing out in An Huang's little family grocery in Hangzhou, a three-hour drive southwest of Shanghai.

What’s going on: A year ago, Huang and his father had a visit from representatives of Alibaba, China's e-commerce giant. What did they think of transforming their dowdy place into a state-of-the-art, digitalized store, with all the bells and whistles, under Alibaba’s Tmall brand? According to Huang, it took him and his father only about five minutes to agree.

Today, as he stocks up on popular beer and snacks for the World Cup rush, he told Axios that revenue is up 30% in his spruced-up shop, equipped with artificial intelligence-backed apps and even a heat sensor to track foot traffic.

Why it matters: Alibaba says that over the last year, it has redone about 1 million mom and pop shops like the Huangs' across China. It has done the same with about a hundred superstores. Big and small, these outlets buy all their goods through Alibaba's platform and pay using its affiliate Alipay app. ... " 

How Businesses Can Get Inside the Minds of Their Competitors

If we could, perhaps we could make a better use of game dynamics.     Or just simulate their behavior under multiple contexts.

How Businesses Can Get Inside the Minds of Their Competitors

Wharton's Anoop Menon and Jaeho Choi discuss their research on using natural language processing to analyze competitive strategy.

Every business would love to know the minds of its competitors, and what they are likely to do next. Strategy analysts have thus far used simple tools that employ mostly financial and other structured data to try and predict competitors’ moves. But new research at Wharton has shown how natural language processing techniques could be used to parse tomes of unstructured data such as text buried in conference calls or annual reports to more accurately anticipate competitor strategies.

The research opens new pathways to measure and test assumptions firms make in their competitive strategies, and to “visualize how firms are positioned with respect to each other, and then map that on to performance consequences,” says Wharton management professor Anoop Menon. His research paper, “What You Say Your Strategy Is and Why It Matters: Natural Language Processing of Unstructured Texts,” is co-authored with Jaeho Choi, a Wharton doctoral student, and Haris Tabakovic, an associate at The Brattle Group, a Boston-based international arbitration services firm.

For their study, the researchers used natural language processing (NLP) techniques to measure “strategic change, positioning, and focus,” across their sample of 50,506 business descriptions of publicly held companies contained in their 10-K annual reports, from 1997 to 2016.

Menon and Choi shared the main takeaways for business strategy analysis from their research with Knowledge@Wharton.

An edited transcript of the conversation follows.

Knowledge@Wharton: Anoop, could you tell us what led you to explore this topic in your research? What was your objective?

Anoop Menon: The notion that there is a lot of information that is buried in unstructured text has been around for a while. We know that strategy is very complicated, but we tend to measure it using very, “simple metrics” like a few financials here and there. But we all agree and understand there is a huge amount of information that is buried in text like conference calls and annual reports that gets at the meat of the strategy, how the strategists are thinking about competition and product market choices.

Sadly, we currently don’t have a really good technique or set of techniques to get at that information. So that was the starting point. About six or seven years ago, my co-author Haris [Tabakovic] and I came across this burgeoning line of research in computer science about using natural language processing techniques to extract text, but in very different fields – not ours. [There were] some applications to political science but not at all to strategy. We said we should be able to take some of those techniques and get at the information that is buried in the text..... "

Drone Swarms Hard to Stop


As one might expect, the additional complexity makes it difficult/

Think One Military Drone is Bad? Drone Swarms Are Terrifyingly Difficult to Stop ... "   By Joel Hruska in Extremetech

Quantum Transmission from ETH

This, from ETH, seems quite the breakthrough.  What will this ultimately mean for computing, encryption,  combinatorial computation?    Beam me up?

Quantum Transfer at the Push of a Button 

ETH Zurich   By Oliver Morsch

Scientists at ETH Zurich in Switzerland have transmitted information between two solid-state quantum bits (qubits) about a meter apart, with high fidelity. The team, led by ETH Zurich's Andreas Wallraff, linked two superconducting qubits with a coaxial cable. The first qubit's quantum state was initially transferred to a microwave photon of a resonator via precisely controlled microwave pulses, before being sent through the cable to a second resonator, where microwave pulses passed its quantum state on to the second qubit. "The transmission of the quantum state is deterministic, which means that it works at the push of a button," says ETH Zurich's Philipp Kurpiers. Wallraff notes the process' transmission rate for quantum states is among the highest ever achieved. The team's next challenge is using two qubits each as transmitter and receiver, to enable entanglement swapping. ... "

Saturday, June 16, 2018

Watson Knowledge Catalog

During our earliest look at Watson, we asked, how do we get our knowledge into the system?  Update it?   Set up maintenance? Obvious question.   Too hard, expensive.  Especially information that was the result of other analytics, and had to be dynamically prepared and extracted for use.    Seems its finally here with the Watson Knowledge Catalog.  See the intro article below,  am examining.

Introducing IBM Watson Knowledge Catalog in Medium
Michael Tucker
Senior Offering Manager at IBM

Buying food hasn’t always been the easiest thing to do. Up until the early 1900s, there was not a one-stop shop to purchase your food and drinks. A person went to their local bakery for bread, a butcher for meat, and milk delivered by the milkman. This made the food-shopping task laborious, often times taking an entire day or more, depending on if a person had to go across town for some items. In 1916, to the applause of many, the concept of a supermarket was introduced. This revolutionized way of grocery shopping reduced the task of buying food from days to minutes or hours, helping people make more efficient use of their time.

Do your analysts, data scientists, and knowledge workers have the same “supermarket experience”with your enterprise data? Introducing IBM’s Watson Knowledge Catalog, an intelligent cataloging service that allows you to bring together and prepare analytic assets, including machine learning models and structured and unstructured data, wherever they live (on-premise or in the cloud), to turbocharge your Data Science, Machine Learning and AI. This enables your teams to quickly find information assets in a self-service manner, pull those assets into Data Science or Data analytic tools, and drive productive use and meaningful outcomes faster than ever before.  ... "

Note the connection to:

Watson Studio
Build, train, deploy and manage AI models, and prepare and analyze data, in a single, integrated environment. .... "

Surveillance Cameras Talking to Smartphones

Interesting, but perhaps spooky application.  Your smart city talking to you individually.  Advertising next?

System Allows Surveillance Cameras to 'Talk' to the Public Through Individual Smartphones 

in Purdue University News

Purdue University researchers have developed a system to enable public surveillance cameras to transmit tailored messages to people while maintaining their privacy. The PHADE (private human addressing) system employs movement patterns as the address code for communication, allowing users' smartphones to decide locally whether to accept the messages. PHADE uses a server to receive video streams from cameras to track users, with the camera building a packet by tying a message to the address code and broadcasting the packet. Once it gets the packet, the smartphone of each target uses sensors to deduce its owner's behavior and follow the same conversion to extract a second address code. Should this code match the address code in the message, the smartphone automatically delivers the message to its owner. PHADE shields privacy by keeping users' personal sensing data within their mobile devices, and transforms the raw features of the data to obscure partial details. ... " 

RFID Tags as Sensors

MIT Engineers Configure RFID Tags to Work as Sensors 
MIT News

By Jennifer Chu

Researchers in the Massachusetts Institute of Technology (MIT) Auto-ID Lab have developed an ultra-high-frequency (UHF) radio-frequency identification (RFID) tag-sensor configuration that senses spikes in glucose and wirelessly transmits that information. Experiments on ways to turn passive RFID tags into sensors that can operate over long stretches of time without the need for batteries or replacement typically focus on manipulating a tag’s antenna, so its electrical properties change in response to specific stimuli in the environment. The MIT group previously designed an RFID tag-antenna that responds to moisture content in the soil, and another that senses signs of anemia in blood flowing across an RFID tag. Said MIT’s Sai Nithin Reddy Kantareddy, “People are looking toward more applications like sensing to get more value out of the existing RFID infrastructure.” .... ' 

On Company Towns

Been a follower of the topic.  Starting with towns built around railroads and their workers.   The technology of past days.

Silicon Valley’s company towns are doomed
Facebook and Google want to build planned communities. A brief spin through history shows why this is a bad idea.

By Grant Bollmer

Willow Village is a community planned for a 59-acre site in California’s Silicon Valley, between Menlo Park and East Palo Alto.

It will have housing, offices, a grocery store, a pharmacy, and its developers say, maybe even its own cultural center.

There’s one notable thing about Willow Village that makes it different from other new communities in America: It is being developed by Facebook.

Willow Village evokes “company towns” of the past, once built by corporations to both house and keep tabs on employees. And projects like Willow Village also follow the legacy of utopian communities in the United States.

American history is filled with towns, conceived and built to realize specific theological worldviews, at times linked with faith in capitalism and the power of technology. Like these utopian communities, Willow Village speaks of its founders’ desire to correct imagined social problems by reinventing social life. .... "

Determining the Cause of War

In my early days at the Pentagon, working for the Joint Chiefs, we built and ran conflict simulations. But we were less interested in causes than we were in outcomes.  At the time we would have said the causes are too many, too complex, too subtle to control even for a simulation.

" ... DARPA, BAE Systems and the Air Force Research Lab are working to pioneer new computer simulations, algorithms and advanced software to provide military decision makers with organized, near real-time information on causes of war and conflict in operational scenarios. .... "

Can DARPA & BAE-Developed Computer Algorithms Determine the True Causes of War?   An emerging computer simulation analyzes multiple factors to determine the cause of war

By Kris Osborn - Warrior Maven

DARPA, BAE Systems and the Air Force Research Lab are working to pioneer new computer simulations, algorithms and advanced software to provide military decision makers with organized, near real-time information on causes of war and conflict in operational scenarios.

Drawing upon a range of otherwise disconnected sources of raw data, the new software program is designed to use reasoning algorithms and simulations to analyze intelligence reports, academic theories, environmental factors and details from operational scenarios and other kinds of user input.

“It is about taking information from disparate sources which would be impossible for a person to consume in a short amount of time,” Jonathan Goldstein, Senior Principal Scientist, Autonomy Controls and Estimation, BAE Systems, told Warrior Maven in an interview.

The Air Force Research Laboratory recently awarded a $4.2 million deal to BAE Systems to develop CONTEXT; DARPA is sponsoring BAE's efforts.

The emerging product, called Causal Exploration of Complex Operational Environments (CONTEXT) models different political, territorial and economic tensions that often cause conflict. These nodes, or variables making up a complex, yet interwoven tapestry of causes, include things like economic tensions, terrorism, tribal or religious conflict and issues about resources or territorial disputes – among other things.

“The technology evaluates causal insertions in different forms and innovates them into a model of interwoven causal relationships present in otherwise disconnected sources. We are building a model that can rapidly be used by an expert, so that when a new conflict flares up, decision-makers can understand the underlying issues,” Goldstein said.

While on the surface, organizing and performing some analytics of large pools of data might bring AI to mind, CONTEXT evaluates material input by users and does not necessarily access massive volumes of historical or stored data. Nonetheless, it does appear to perform some measure of automation and AI like functions, in so far as it organizes and integrates different sources for a human decision maker.

“This shortens the decision cycle. People are not good at maintaining a causal model with complexity in their head. The software creates a large graph of causes, evaluates approaches and examines the potential consequences of a given approach,” Goldstein explained.

Automation and AI, which are of course progressing at near lighting speed these days, are often described in terms of easing the “cognitive burden,” meaning they can quickly perform analytics and a range of procedural functions to present to a human operating in a command control capacity.

At the same time, causes of conflict are often a complex byproduct of a range of more subjectively determined variables – impacted by concepts, personalities, individual psychology, historical nuances and larger sociological phenomena. This naturally raises the question as to how much even the most advanced computer programs could account for these and other somewhat less “tangible” factors.

Leading AI and cybersecurity experts often say that advanced computer algorithms can analyze data and quickly perform procedural functions far more quickly than human cognition – yet there are nonetheless still many things which are known to be unique to human cognition. Humans solve problems, interpret emotions and at times respond to certain variables in a way that the best computer technology cannot.

“War causation is always over determined. Even with advanced statistical regressions on extremely large data sets, it is unlikely that what causes conflict can be determined with accuracy,” Ross Rustici, Senior Director, Intelligence Services, Cybereason – and former DoD Cyber Lead Intrusion Analyst and Technical Lead for DoD, East Asia, told Warrior Maven.  .... "

Rise of the Financial Robo Advisor

Much interested in the dynamics of how systems will dynamically and perceptively give advice.   In this blog have called them 'Assistants'.    How will they disrupt in giving financial advice?

The Rise of the Robo-advisor: How Fintech Is Disrupting Retirement  In Knowledge@Wharton

Artificial intelligence is changing the world of retirement planning. By using improved datasets and algorithms to efficiently deliver solutions tailored to people’s needs, AI can help them save, invest and retire better. One of the hottest trends to emerge in this area in recent years is the use of robo-advisors. These are software programs that use the data supplied by clients to create and automatically manage their investment portfolios. They’re gaining in popularity, but are they better than human advisors?

“Robo-advisors are a potential solution to the complexities of financial decision-making,” particularly in retirement planning, said Jill E. Fisch, law professor at the University of Pennsylvania. “But at the same time, there’s a lot we don’t know about robo-advisors — exactly how they work and how effective a solution they’re going to be.” She and other experts from Wharton and elsewhere spoke at a conference hosted by the Pension Research Council titled “The Disruptive Impact of FinTech on Retirement Systems.”   ... " 

Top 20 Python Data Science Libraries from DSC

Extensive sets with good descriptions. 

Top 20 Python libraries for data science in 2018

Posted by Igor Bobriakov

Python continues to take leading positions in solving data science tasks and challenges. Last year we made a blog post overviewing the Python’s libraries that proved to be the most helpful at that moment. This year, we expanded our list with new libraries and gave a fresh look to the ones we already talked about, focusing on the updates that have been made during the year.

Our selection actually contains more than 20 libraries, as some of them are alternatives to each other and solve the same problem. Therefore we have grouped them as it's difficult to distinguish one particular leader at the moment. .... " 

Friday, June 15, 2018

More on the Autonomous Store

More complete piece by Jon Stine on Amazon Go, and the more general topic of autonomous stores.  In US and China.  In the Intel IT Peer Network:

Lots of comment about the Amazon Go store.  And the ten variants of ever-more autonomic stores in China.

Four thoughts for discussion and debate:

From a shopper’s view: it’s about time.
As I visit the stores (and read reports from the front), I’m reminded of the essential 2006 article (“Retail Store Execution: An Empirical Study,” Fisher, Krishnan, and Netessine, Wharton, December 2006) that identified the four most important determinants of store performance.

Stock position (specifically, in-stock); the speed, accuracy, and security of transactions; the ready availability of human help; and, the ability of that human help to truly help—to solve problems and create solutions.

From an operator’s point of view, it’s a neat and rigorously-researched four-point statement of priority.

But from a shopper’s point of view, it’s a neat listing of what shoppers have preferred ever since the first merchant’s rug was spread in the first bazaar.

Which is what Amazon Go and the Chinese stores are working to deliver.

2. From an industry perspective: thank you. (Gulp.)

When I reflect upon the work of Amazon and its Chinese brethren (Alibaba, JD.com, and Suning, specifically) what impresses me most is not the technology but the damn-the-torpedoes mentality that is determined to break through.

Take POS.  We’ve known for years that the in-store transaction process is one of the most painful parts of the decision journey. Yes, we’ve envisioned a world of RFID-tagged SKUs in self-reading carts or rolling through reader-rich tunnels or gates.  And there has been no shortage of efforts to improve accuracy, speed, and security within the existing POS paradigm.

But we’ve rarely thought about blowing the whole thing up.   And designing not point of sale—with emphasis upon “point”—but immediate and easy and secure payment.

Congratulations to those lighting the explosives. You’re forcing us all to improve.

There are three big differences between those tests of yesteryear and the pilot stores of today. The first is the technology. Of course. Today’s is more powerful, ever faster, ever smaller, ever more connected, enabling faster learning and deeper inference.  .... " 

Signals of Disruption

Have been involved in several meetings to determine and evaluate such signals. See below a bare outline from MIT/Sloan.  May sound simplistic but there is much more at the link to flesh it out.   This is more of a risk analysis checklist starting point to consider.  There are a number of good industry and specific examples at the link.

Three Signals Your Industry is About to Be Disrupted
By Megan Beck and Barry Libert in MIT/Sloan

Sign #1: Your Industry Has Significant Regulatory Burdens
Sign #2: Your Customers Have to Work at Managing Their Costs
Sign #3: Your Customers’ Experience Isn’t Positive — or Even Neutral  ... " 

Cisco Guide to Smart Manufacturing

Downloadable at the link:

Manufacturing
How to Evolve your Manufacturing Environment to an Ultimate State

By Eric Ehlers

Cisco Live just wrapped this week, and we had a lot of great conversations with customers who are looking to evolve their manufacturing operations and achieve  an “ultimate state.” Many of these conversations revolved around how to improve their factory network and reduce downtime, taking advantage of wireless in a plant and becoming more secure, and how can IT and OT collaborate better together. For the first time, we have captured all these topics in one place, and we call it the Ultimate Guide to Manufacturing. What does an Ultimate Guide to Manufacturing deliver? More than you expect – here’s why.  ... "

Levels of Customer Engagement with Retail IOT

I see that Intel Director Jon Stine, who we worked with at innovation centers, comments on Amazon Go and IoT in retail.

IoT Is Building Higher Levels Of Customer Engagement

Forbes Insights With Intel IoT Connecting The Unconnected  

 Insights Team Insights Team , Forbes Insights

Bestselling author Shep Hypken—the “Chief Amazement Officer” at Shephard Presentations—makes a rock-solid case for why customer experience has advanced to the level of 21st-century table stakes: “New research proves that consumers are expecting, if not demanding, highly personalized experiences,” Hypken writes in Forbes. “And the good news for those businesses that can deliver is that customers are typically willing to spend more when they receive such custom-tailored service.”
Enter the Internet of Things (IoT), which through interconnected devices and strong data analytics makes an entirely new level of customer surprise, delight and convenience possible. What’s more, the IoT brings relevant experiences and information to consumers, whether to facilitate the operation of smart homes or to provide relevant health and wellness data that can be shared with medical professionals.

Here are three examples of how IoT and advanced high-tech are building unprecedented levels of consumer connection and engagement today.

Checking Out Stores Without Checkout Lines

Amazon is testing a new concept in brick-and-mortar shopping that aims to eradicate the bane of every shopper’s existence: the checkout line. The Amazon Go store in Seattle combines machine vision, IoT sensors and a mobile app swiped at the store entrance to create what it calls “just walk out technology.” The system tallies items as the customer places them in a shopping bag (or subtracts them when returned to the shelves) and charges their linked Amazon account accordingly.

This frees the customer to simply leave the store when done shopping, while Amazon in the process collects data to analyze and leverage for further insights. The potential exists to send out personalized coupons for future shopping runs, or guide shoppers via their mobile device to where they can find their favorite products. Eventually, such systems will also analyze shopping lists and alert customers when items are out of stock or going on sale.

Jon Stine, global director retail sales at Intel, says the Amazon Go stores are true game changers because “these are not pilots built to prove technology’s value. Hardly. Understand them as first deployments—soon to be followed by second, third, fourth and thousandth deployments.”
Computer vision also comes into play where smart retail stores are concerned. Founded as a brick-and-mortar retailer in 1998, JD.com has moved from strength to strength, first as an online merchant and most recently with its stores that employ optimized image processing and computer vision technologies. In an unmanned store in the lobby of JD.com’s Beijing headquarters, customers can look up at a camera and, in that instant, pay for the products they walk out with. The cameras can even identify members of the store’s “Jindong PLUS” loyalty program, while smart shelving offers personalized discounts.   .... " 

Imagine a World Based on a Picture

Applications?  Imagining this.  Maybe a new kind of creativity?

DeepMind’s AI can ‘imagine’ a world based on a single picture

Artificial intelligence can now put itself in someone else’s shoes. DeepMind has developed a neural network that taught itself to ‘imagine’ a scene from different viewpoints, based on just a single image.

Given a 2D picture of a scene – say, a room with a brick wall, and a brightly coloured sphere and cube on the floor – the neural network can generate a 3D view from a different vantage point, rendering the opposite sides of the objects and altering where shadows fall to maintain the same light source.

The system, called the Generative Query Network (GQN), can tease out details from the static images to guess at spatial relationships, including the camera’s position.  ... "