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Monday, December 10, 2018

Whats Blockchain Good For?

Nothing?  Well at least not what they expected, or were willing to reveal.  Still, negative examples are useful.

Blockchain: What’s it good for? Absolutely nothing, report finds

In a joint report for the Monitoring, Evaluation, Research and Learning (MERL) Technology conference this fall, researchers who studied 43 blockchain use cases came to the conclusion that all underdelivered on claims.

And, when they reached out to several blockchain providers about project results, the silence was deafening. "Not one was willing to share data," the researchers said in their blog post.

Asset Management

Management in context and some forecast of future context is powerful.

" ... Achieving digital alpha in asset management

The ability to generate value through digitization will increasingly separate leaders and followers in North American asset management.

Sent from McKinsey Insights .... ' 

Sunday, December 09, 2018

Asking Questions to Gather Knowledge

The Game of Questions, once again looking at a means of questioning to gather knowledge ... we explored this idea from a game perspective.

Back in 2013, posted about this:



Nielsen and Microsoft Strategic Data Alliance

Making data more intelligently available to analytics.   Integrating data assets.

Nielsen, Microsoft Unveil Strategic Data Alliance

Nielsen and Microsoft have jointly developed an enterprise solution that brings the former’s consumer data set to life through the latter’s intelligent cloud platform.

The strategic alliance seeks to “democratize” the vast Nielsen Connect data set through the global-scale Microsoft Azure platform. The goal is to help consumer packaged goods manufacturers and retail companies find growth and accelerate innovation within an open data environment. 

Already, Nielsen Connect is inspiring companies to glean more value from their data and sparking a movement for the industry to reimagine its approach to data strategy. Through advanced analytics and artificial intelligence services built on Azure, Nielsen Connect is helping companies integrate data assets to more easily spot emerging trends, diagnose performance gaps, and act faster on opportunities to grow. Most notably, this platform enables clients to use their data as an enterprise asset across all parts of their organization.  ...  "

Saturday, December 08, 2018

AINow Publishes Recommendations

Followup with AINow,  promoting regulation and transparency in the AI development space.

After a Year of Tech Scandals, Our 10 Recommendations for AI  (Outline Overview) 

Let’s begin with better regulation, protecting workers, and applying “truth in advertising” rules to AI
Today the AI Now Institute publishes our third annual report on the state of AI in 2018, including 10 recommendations for governments, researchers, and industry practitioners.

It has been a dramatic year in AI. From Facebook potentially inciting ethnic cleansing in Myanmar, to Cambridge Analytica seeking to manipulate elections, to Google building a secret censored search engine for the Chinese, to anger over Microsoft contracts with ICE, to multiple worker uprisings over conditions in Amazon’s algorithmically managed warehouses — the headlines haven’t stopped. And these are just a few examples among hundreds.

At the core of these cascading AI scandals are questions of accountability: who is responsible when AI systems harm us? How do we understand these harms, and how do we remedy them? Where are the points of intervention, and what additional research and regulation is needed to ensure those interventions are effective? Currently there are few answers to these questions, and existing regulatory frameworks fall well short of what’s needed. As the pervasiveness, complexity, and scale of these systems grow, this lack of meaningful accountability and oversight — including basic safeguards of responsibility, liability, and due process — is an increasingly urgent concern.  ... " 

Full report from AINOW.

Opsgenie for Incidents in Process Modeling

In the process of looking at modeling processes that link to and handle incident driven operations, I was pointed to:

Atlassian: Opsgenie

Plan and prepare for incidents
Determine who should respond
Use templates to prepare messaging and communication channels to responders and stakeholders
Predefine collaboration methods including video conferences, and chat channels
Create status pages to communicate proactively to all stakeholders  ... "

Whats Best?

I like the pieces from Think with Google, good to follow.

We often addressed the problem when dealing with the term 'Optimal', which often followed with the question:  In what context?  under what Constraints?    When we use 'best' there are often many implied constraints in our search or request.  Its also common to include in conversation.  Search, Google's language of interaction, is a conversation, and includes common sense interpretations of 'Best'.

Ask a researcher: What does ‘best’ really mean?
Ken Wheaton August 2018 Mobile, Search, Consumer Insights

It seems fairly straightforward. When people set out to shop for an item or service, they hope to end up with the best possible outcome. But it turns out that “the best” isn’t an objective absolute. In fact, finding “the best” isn’t necessarily about finding the best thing that exists, it’s about finding the best thing for your needs.

It was pretty clear to us from consumer search data that people’s quest for the best is still on the rise. Mobile searches for “best” have grown over 80% over the past two years.1 And they’re searching for “best” for even the smallest stuff: We’ve seen strong growth in things like “best toothbrush” over the past couple years. ....  "

Robot Scientist Creates New Materials

Machines doing design, and the creative process.  How do they interact with people?

A Robot Scientist Will Dream Up New Materials 
Technology Review   By Will Knight

Cambridge, MA-based startup Kebotix has created machine learning software that learns material chemistry from three-dimensional models of molecules with known properties in order to design novel compounds. Kebotix feeds the molecular models to a neural network that learns a statistical representation of their properties, which can devise new examples aligned with existing models; a second network screens out undesirable designs, then a robotic system tests the chemical structures of the remaining models. The outcomes are input back into the machine learning channel so it can yield results closer to target properties. MIT's Klavs Jensen said the use of such automation in chemistry "won't replace the expert, but you'll be able to do things a lot faster."  ...

R&D in the Age of Agile

Pharma R&D in the ‘age of agile’  From McKinsey

As innovation reshapes the pharma landscape, pharma companies will need to revisit their R&D operating models to thrive. ... 

Sent from McKinsey Insights, available in the App Store and Play Store.

Friday, December 07, 2018

Report from the Stanford AI100 Study

Initial report from this work:

Stanford:    One Hundred Year Study on Artificial Intelligence (AI100)

Stanford University has invited leading thinkers from several institutions to begin a 100-year effort to study and anticipate how the effects of artificial intelligence will ripple through every aspect of how people work, live and play.

This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.  .... 


Barbara J. Grosz and Peter Stone. A Century Long Commitment to Assessing Artificial Intelligence and Its Impact on Society. December 2018. Communications of the ACM (CACM).Doc: groszstone_cacm2018.pdf

Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David Parkes, William Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, and Astro Teller. "Artificial Intelligence and Life in 2030." One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016. Doc: http://ai100.stanford.edu/2016-report. Accessed: September 6, 2016.   

Wal-Mart Floor Cleaning and Complex Environments

Note the claim of being able to operate ' ... to effectively and safely function in complex, crowded environments, ensuring increased productivity and efficiency across applications .... '  That is,  in the same environments as people.   This will grow as a challenge to get robots cooperating with people, passively or actively ...

Walmart Leads the Way...in Floor Scrubbing Robots? 
in ZDNet    by Greg Nichols, with Video

By the end of next month, Walmart will deploy floor-scrubbing robots programmed to map out pathways via demonstration through the BrainOS operating system (OS) from Brain Corp. Store associates will walk the stores’ floors, guiding the robots along a quick demonstration route. Afterwards, BrainOS will take over to scan the area to be cleaned, while monitoring for people or new obstacles using onboard sensors. Said Brain Corp.'s Eugene Izhikevich, "BrainOS technology allows robots to effectively and safely function in complex, crowded environments, ensuring increased productivity and efficiency across applications." The scrubbing robots are the latest artificial intelligence solution explored by Walmart, as the retailer also uses robots from the Bossa Nova hardware company to scan shelves and aggregate customer activity in select retail outlets. ... "

New IFTTT Functions for Assistants and Home

A number of new and interesting IFTTT  (If This Then That) functionalities for the smart home.  I always explore these offerings.   They are free.   Some new interactions that link things like doorbell pushes and multiple step 'scenes'.   Also many examples of  logging information.     A pointer to a future where there will be many selectable skills aka actions that improve the smart home by using its data.  Everyone who has assistants should explore these possibilities.

 For a number of Smart Home assistants.

 For the Ring Doorbell and connected smarthome systems.

And many more.

Amazon Go Cashierless at Airports?

Overall an excellent, hands-on demonstration of the advance of fast reliable sensors.   Will further open people to the idea of the convenience of 'AI' type solutions.  They have already done it with Alexa.   These developments will make people willing to engage and trust new interfaces, and will lead to yet newer ideas.   An opening to driverless cars, sooner?

Amazon's cashierless Go stores may come to an airport near you
It has reportedly requested meetings from several US airport operators.
By Steve Dent, @stevetdentin  in Engadget

Airport shopping is mostly about perfumes, booze and overpriced electronics, but that could soon change. Amazon has reportedly inquired about installing its cashierless Go stores at several US airports, according to Reuters. Emails from a public records request revealed that Amazon asked for meetings with managers at San Jose and Los Angeles international airports and received a positive response. "I am looking forward to moving forward with the Amazon Go technology at the airport," wrote one airport IT manager.  ... " 

Robotic Houseplant Moves to Light

Kind of obvious, but made me think more generally about the robotics of the problem.   And adding other dimensions like nutrients and water.    Plus the sensors needed to do that effectively, and the dependence on the architecture of the 'field'.  Reminds me too of robot weed pulling and zapping solutions.

MIT researchers create a robot houseplant that moves on its own

By Rachel England, @rachel_england in Engadget

Google Labs Announces Image Compression Demos

Had a need for comparing alternate methods of this recently. Technical:

Google Labs Announces Squoosh: Image Compression PWALike  | by Dylan Schiemann 

At the 2018 Google Chrome Developer Summit, Google announced Squoosh, an open source image compression Progressive Web App (PWA) that doubles as a practical demonstration of modern web technologies.

Squoosh provides a quick and easy mechanism for leveraging many image compression formats. Users may browse Squoosh.app, drag and drop an image into a browser tab, and experiment with many image optimization and conversion settings. The app displays before and after views side by side for the selected image compression settings.

Squoosh in its current form is likely not meant as a competitor to the numerous image compression apps, ranging from traditional image editing tools as Photoshop and Sketch.app to web-based services like TinyPNG, ImageResize.org, and Compressor.io, to various desktop apps.

Google Labs' primary objective with Squoosh is to demonstrate how advanced web apps can leverage modern technologies to deliver a high-performance experience in today's web browsers.  ... "

Mars and Marketing

In Gartner:
Mars and Marketing – What We Can Learn From NASA    By Christopher Ross

Thursday, December 06, 2018

Google Wants to be Your AI Edited News Radio

So Google will control editing and presentation of news.  Placement of Ads.  Assembled with AI analysis.  Already being delivered to some assistants.  Right now assistants stream selected radio stations.  More control from mega computing?  What are the implications?

Google wants to replace your radio as an audio news source

Google is getting into AI-curated news playlists
By Shannon Liao@Shannon_Liao  in theVerge

You’ll soon be able to listen to an audio news playlist curated by Google Assistant to inform you on the topics you’re interested in. Google’s latest Assistant feature uses artificial intelligence to help make these custom news bundles, and it’s available today for a limited number of users.  ... "

Alexa Conversationally Constructs Playlists

This is something of interest, playlist conversational construction.  If you think of a playlist as a goal, could this be applied to business efforts?   Was thinking something related for business application, is this far away?  More than just tweaks will be needed, but have already noticed some subtlety in recommendation.    Alexa:  Find a better pricing strategy using the latest data.   A Playlist for Business as a set of choices for a process?

Alexa will pepper you with questions to build better playlists   in Engadget, By Mallory Locklear, @mallorylocklear

Amazon is rolling out a few tweaks to Alexa that will make it easier to find the music you want to hear. By telling Alexa what you like and don't like and by conversing with Amazon's assistant about what you enjoy listening to, Alexa will be able to create more personalized suggestions and playback even when you just say, "Alexa, play music."

If you're looking for Alexa to offer some suggestions for playlists that are tailored to you and what you want, the virtual assistant will now be able to talk to you about what you're looking for. When you say something like, "Alexa, help me find a holiday playlist," or "Alexa, help me find dinner music," Alexa will respond with a few questions to help get a better grasp on what genre, tempo or mood you're hoping to incorporate. Alexa will then customize playback based on how you responded and your past listening history.  ... "

China Takes on Cashierless Tech

Alternative tech idea:

Why China's take on cashierless tech might be the right one in Axios

China's retail giants might be ahead of US innovators, such as Amazon, in creating no-checkout retail locations, Erica Pandey writes. While US companies are focused on a hands-free payment experience, Chinese retailers are letting consumers use QR codes to pay quickly and easily, she writes. ... " 

Assessing Progress in Automation Technologies

Useful coverage of automation.  I like that this is defined broadly.

Assessing progress in automation technologies  In O'Reilly by Ben Lorica.
When it comes to automation of existing tasks and workflows, you need not adopt an “all or nothing” attitude.

In this post, I share slides and notes from a keynote Roger Chen and I gave at the Artificial Intelligence conference in London in October 2018. We presented an overview of the state of automation technologies: we tried to highlight the state of the key building block technologies and we described how these tools might evolve in the near future. .... " 

A ChatBot Asset Exchange

Brought to my attention by the talk this morning on Bots integrated with AR/VR . Slides here.  The slides include instructive videos.  IBM Sponsored.  I will extract some additional examples.

Some interesting examples of Bot use, coding and design, and a means to exchange examples:

Bot Asset Exchange
Your community-driven chatbot development hub.  (via Anamita Guha 
 @anamitag of IBM)

Discover, configure, deploy, and be rewarded for bots built with Watson Assistant. Join the revolution--build a chatbot today.   ... "

Echo Devices now Support Skype Calling

In further indication of a link between Microsoft and Amazon,  Voice and Video Skype calls can now be made-hands free on Echo devices.  I frequently use Skype for international communications.  Signed up for this and it worked well.  Another move towards Echo for business scenarios.   Text messaging is not yet available, but is coming.

You can now make Skype calls on Amazon Echo devices   By Bruce Brown in DigitalTrends

Just in time for the holiday season, Microsoft and Amazon announced that you can now ask Alexa to make Skype voice and video calls on Echo devices.

In all, 34 countries will soon be Alexa and Skype-enabled. Skype support for the Alexa platform is available now in the U.S., U.K., Ireland, Canada, India, Australia, and New Zealand. Support for other countries will be coming soon, according to Microsoft.

You can use Alexa-enabled devices such as the Echo Plus or Dot to make hands-free Skype voice calls.  ... "

Wednesday, December 05, 2018

Talk: How Bots Fit into the AR/VR Space

Join us Dec 6,  at 10:30am US Eastern - hear @anamitag at @IBMDeveloper

Talk Title: How Bots Fit in the AR/VR Space 

Speaker: Anamita Guha 

Abstract: This talk will describe the use cases of chatbots in AR/VR that are in existence — and Al's potential within those —  in addition to ways you can develop bots within AR/VR applications and make them intelligent. Anamita will also discuss  current and subsequent trends and why AR/VR accompanied with Al is going to have more of an emerging impact in the enterprise space. 

Bio: Anamita Guha is currently the Lead Product Manger for IBM Watson building developer offerings. Her focus has been  on conversational interfaces like chatbots, voicebots, IOT, and AR/VR, in addition to promoting girls in STEM. She recently  launched the Bot Asset Exchange, a tool of bot developers to use when building their bots. She also helped champion  Chatbots for Good, a free cloud-based learning experience where anyone — even those with no prior bot development  experience — can use Watson Assistant and Tone Analyzer services to design, test, and build a chatbot. She holds a  degree in Cognitive Science from UC Berkeley, and has spent most of her career prior to IBM at early-mid stage startups. 

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 http://cognitive-science.info/community/weekly-update/for recordings & slides, and for any date & time changes 
Join Linkedin Group: https://www.linkedin.com/groups/6729452/ (Cognitive Systems Institute) to receive notifications 
Thu, Dec 6, 10:30am US Eastern https://zoom.us/j/7371462221 
More Details Here : http://cognitive-science.info/community/weekly-update/  (Slides and talk recording will be posted after talk

#CSIGnews #opentechai #issip   @KarolynSchalk @mattganis @ibmcodait #chatbots @rama_akkiraju @yassimoghaddam @hyurko @oniak3

P&G Responds to Changing Customer Preferences

Intriguing directions, especially regarding customization.  How does a big company react to customer preferences,  when it can no longer direct them?

Q&A | How P&G Responds to Changing Customer Preferences   in SupplychainBrain

Phil Ruotolo, associate director of merchandising solutions customization with Procter & Gamble, details the consumer-products giant's strategy for adjusting to ever-shifting consumer preferences.

Q: How is P&G responding to changing customer preferences?

Ruotolo: Several years ago, we embarked on an innovative supply-chain solution. We created what we call mixing centers. It was the first time we had brought a portfolio of different P&G products into one location. The next question was, how do we think about merchandising in a more unique way? So we went to a 14-day order lead time. Previously, there was typically a four- to six-week window, and most of it was on a forecast. What inevitably happens is that you're building inventory of something that a customer might want to order.

In this new model, we differentiate the finished product in our customization locations, and then do all of the forecasting for our materials. Now we're able to react very quickly to what a customer might want, and can fulfill that within 14 days.

Q: So this is execution, not planning?

Ruotolo: Correct. It's taking all your favorite P&G products, and bringing them all together into one facing. As a consumer, you’re drawn to that display. We want to drive trials with consumers as they come across our products. Hopefully, they’ll make multiple purchases.   ..... " 

Better Facial Recognition, Says NIST

Interesting stats.   Our own experience says it depends strongly on the contextual aspects of the image acquisition.  And often out of complete control.    Introduce the metadata of context?  But the improvement continues.

Facial Recognition Algorithms Are Getting a Lot Better, NIST Study Finds   in FedScoop   By Tajha Chappellet-Lanier

The U.S. National Institute of Standards and Technology (NIST) determined facial recognition software has made huge gains in accuracy over the past five years. NIST said the technology has undergone an "industrial revolution," making certain algorithms about 20 times better at searching databases and finding matches. NIST researchers tested 127 algorithms developed by 45 vendors, using a primary database of 26.6 million reasonably well-controlled portrait photos of 12.3 million individuals; when provided with good quality photos, the most accurate algorithm could identify matches with only a 0.2% error rate. The same test found at least a 4% failure rate in 2014, and a 5% failure rate in 2010. NIST said this improvement can be attributed to the widespread adoption of convolutional neural networks, which were not being used in 2014.  ... " 

Protein Folding with Alphabet Deep Mind

A big, big deal we took a look at for industry, even suggested a neural net possibility, but methods were still too primitive at the time. This still not a compete solution,  but looks to be a step forward.

Alphabet's DeepMind AI Algorithm Wins Protein-Folding Contest 
V3.co.uk   By Dev Kundaliya

DeepMind's latest artificial intelligence (AI) software won the Protein Structure Prediction Center's Critical Assessment of Structure Prediction contest by accurately predicting the three-dimensional structures into which proteins can be folded. The AlphaFold algorithm predicted the configurations of 25 out of 43 proteins, making it far more accurate than any other software. AlphaFold was designed and taught to model target shapes from scratch, without using previously solved proteins as templates. The DeepMind team used two distinct neural networks to predict the proteins' structures. DeepMind's Demis Hassabis said, "We've not solved the protein folding problem, this is just a first step. It's a hugely challenging problem, but we have a good system and we have a ton of ideas we haven't implemented yet."    ... " 

AI Will Make You Smarter Through Augmentation

Course that is what we are aiming at,  it augments us.   Conversation is a great start.

Artificial intelligence will make you smarter
People plus machines will surpass the capabilities of either element alone. 

By Terrence Sejnowski

Francis Crick Professor and Director of the Computational Neurobiology Laboratory at Salk Institute for Biological Studies, and Distinguished Professor of Neurobiology, University of California San Diego

MIT Press provides funding as a member of The Conversation US.

University of California provides funding as a founding partner of The Conversation US.
Under Creative Commons license.

The future won’t be made by either humans or machines alone – but by both, working together. Technologies modeled on how human brains work are already augmenting people’s abilities, and will only get more influential as society gets used to these increasingly capable machines.

Technology optimists have envisioned a world with rising human productivity and quality of life as artificial intelligence systems take over life’s drudgery and administrivia, benefiting everyone. Pessimists, on the other hand, have warned that these advances could come at great cost in lost jobs and disrupted lives. And fearmongers worry that AI might eventually make human beings obsolete.

However, people are not very good at imagining the future. Neither utopia nor doomsday is likely. In my new book, “The Deep Learning Revolution,” my goal was to explain the past, present and future of this rapidly growing area of science and technology. My conclusion is that AI will make you smarter, but in ways that will surprise you.

Recognizing patterns

Deep learning is the part of AI that has made the most progress in solving complex problems like identifying objects in images, recognizing speech from multiple speakers and processing text the way people speak or write it. Deep learning has also proven useful for identifying patterns in the increasingly large data sets that are being generated from sensors, medical devices and scientific instruments.

The goal of this approach is to find ways a computer can represent the complexity of the world and generalize from previous experience – even if what’s happening next isn’t exactly the same as what happened before. Just as a person can identify that a specific animal she has never seen before is in fact a cat, deep learning algorithms can identify aspects of what might be called “cat-ness” and extract those attributes from new images of cats. .... " 

Tuesday, December 04, 2018

Alibaba has a Better Intelligent Assistant than Google's

In particular the claim that it is more conversationally powerful is interesting.  Such advances could lead to deeper interaction with humans and further engagement.

Alibaba already has a voice assistant way better than Google’s
It navigates interruptions and other tricky features of human conversation to field millions of requests a day   by Karen Hao  in Technology Review excerpt: 

In May, Google made quite the splash when it unveiled Duplex, its eerily humanlike voice assistant capable of making restaurant reservations and salon appointments. It seemed to mark a new milestone in speech generation and natural-language understanding, and it pulled back the curtain on what the future of human-AI interaction might look like.  Still only in Chinese. 

But while Google slowly rolls out the feature in a limited public launch, Alibaba’s own voice assistant has already been clocking overtime. On December 2 at the 2018 Neural Information Processing Systems conference, one of the largest annual gatherings for AI research, Alibaba demoed the AI customer service agent for its logistics company Cainiao. Jin Rong, the dean of Alibaba’s Machine Intelligence and Technology Lab, said the agent was already servicing millions of customer requests a day.

The demo call involved the agent asking a customer where he wanted his package delivered. In the back-and-forth exchange, the agent successfully navigated several conversational elements that demonstrated the breadth of its natural-language capabilities.

Take this exchange at the beginning of the call, translated from Mandarin: ... "

Wal-Mart Mobile Out of Stock App

We developed a similar mobile App on a Blackberry , and tested it in multiple retail settings, but before home ordering/shipping was common.   Consider how this could be integrated with predictive sales and pricing analysis. The idea has been frequently covered in this blog.   How similar?

 Walmart gives associates a tool to deal with out-of-stocks
by George Anderson in Retailwire

Walmart is not known for having large numbers of associates on its sales floors, but it may need to add more if a new tech tool for workers becomes popular with customers during the holiday season. A new mobile app feature enables Walmart associates to search walmart.com for items not sold at their location, order the item for customers and have it shipped free to a customer’s home or to the store for free pickup.

The retailer claims that one of the best features of the mobile app tool is that it provides a variety of payment options. Once an item is ordered, customers are given a receipt. They then can go to any checkout in the store and pay with cash, check, credit or debit card as well as Walmart Pay.  ... "

Operations 4.0: Pilots

From McKinsey.  Thoughtful examination of essence and value of pilots

The Operations 4.0 podcast: Productivity and ‘pilot purgatory’
The value from Operations 4.0 comes from how it unleashes productivity gains across a wide range of measurements. But to achieve those results, businesses must do more than launch pilot after pilot. ... "

An Architecture for Intelligence?

Is there an underlying model for intelligence?    Is it a structurally simple enough one that we could readily convert into code, we could create something that thinks like the brain?    Still unknown.  Also looking for that secret part we still don't know.

Could this then lead use for AGI      Artificial General Intelligence, AKA "Strong AI"  or   "the intelligence of a machine that could successfully perform any intellectual task that a human being can"?  We don't know that either,  but we know the brain thinks, and its made of things we can dissect piece by piece  (Technical)

The Genius Neuroscientist who might hold the key to True AI.  By Shaun Raviv in Wired

See also:  Karl Friston   https://en.wikipedia.org/wiki/Karl_J._Friston

And further: https://en.wikipedia.org/wiki/Free_energy_principle

The free energy principle tries to explain how (biological) systems maintain their order (non-equilibrium steady-state) by restricting themselves to a limited number of states.[1] It says that biological systems minimise a free energy functional of their internal states, which entail beliefs about hidden states in their environment. The implicit minimisation of variational free energy is formally related to variational Bayesian methods and was originally introduced by Karl Friston as an explanation for embodied perception in neuroscience,[2] where it is also known as active inference.

Markov Blanket   https://en.wikipedia.org/wiki/Markov_blanket

Prove Your Algorithms are Fair

See some previous work on this,.   Proofs in specific goals and context.

To Build Trust In Artificial Intelligence, IBM Wants Developers To Prove Their Algorithms Are Fair
by Dan Robitzski in Futurism.com

We trust artificial intelligence algorithms with a lot of really important tasks. But they betray us all the time. Algorithmic bias can lead to over-policing in predominately black areas; the automated filters on social media flag activists while allowing hate groups to keep posting unchecked.

As the problems caused by algorithmic bias have bubbled to the surface, experts have proposed all sorts of solutions on how to make artificial intelligence more fair and transparent so that it works for everyone.

These range from subjecting AI developers to third party audits, in which an expert would evaluate their code and source data to make sure the resulting system doesn’t perpetuate society’s biases and prejudices, to developing tests to make sure that an AI algorithm doesn’t treat people differently based on things like race, gender, or socioeconomic class. ... "

Game Theory and Society

A favorite topic is how game theory can be made practical   We tried that and got little out of it beyond descriptive rather than prescriptive models.   Is this new approach useful beyond that?  Note especially regarding networks and social dynamics.

What game theory tells us about politics and society
Economist Alexander Wolitzky uses game theory to model institutions, networks, and social dynamics.   By Peter Dizikes | MIT News Office

Monday, December 03, 2018

Foundational Barriers for AI

Agree, and real feedback from surveys is interesting ...

 AI adoption advances, but foundational barriers remain, results from surveys.

Survey respondents report the rapid adoption of AI and expect only a minimal effect on head count. Yet few companies have in place the foundational building blocks that enable AI to generate value at scale.

The adoption of artificial intelligence (AI) is rapidly taking hold across global business, according to a new McKinsey Global Survey on the topic.1 AI, typically defined as the ability of a machine to perform cognitive functions associated with human minds (such as perceiving, reasoning, learning, and problem solving), includes a range of capabilities that enable AI to solve business problems. The survey asked about nine in particular,2 and nearly half of respondents say their organizations have embedded at least one into their standard business processes, while another 30 percent report piloting the use of AI. Yet overall, the business world is just beginning to harness these technologies and their benefits. Most respondents whose companies have deployed AI in a specific function report achieving moderate or significant value from that use, but only 21 percent of respondents report embedding AI into multiple business units or functions. Indeed, many organizations still lack the foundational practices to create value from AI at scale—for example, mapping where their AI opportunities lie and having clear strategies for sourcing the data that AI requires.

One critical factor of using AI effectively, the results confirm, is an organization’s progress on transforming the core parts of its business through digitization. At the most digitized firms,3 respondents report higher rates of AI usage in more business functions than their peers, along with greater investment in AI and greater overall value from using AI. Another foundational challenge with AI is finding skilled people to implement it effectively. Many respondents say their organizations are addressing the issue by taking a diversified approach to sourcing talent. On the whole, despite reasonable concerns about AI being used to automate existing work, respondents tend to believe that AI will have only a minor effect on overall company head count in the coming years ... "

Brand Loyalty Changing for Natives

Never liked the term Digital Native.    We are all more like digital tourists now, using the convenience and intelligence of it more or less.   .........

Marketing to Digital Natives: How Brand Loyalty Is Changing

Wharton's Americus Reed and Erik Gordon of the University of Michigan discuss reviving old brands for millennials and Gen Z. ... 

Marketing Content

Brand loyalty used to be something companies could rely on to grow and retain their customer base. It was driven in part by cool commercials on network TV and catchy jingles that consumers couldn’t get out of their heads. But younger people, specifically millennials and the Gen Z cohort, aren’t looking at the same media or ads that their parents did. Companies that were popular in past generations are quickly discovering that they need new strategies if they want their brand to appeal to the next generation of shoppers who can easily click and choose from millions of products from around the globe.

The Knowledge@Wharton radio show on SiriusXM invited two professors to talk about marketing to digital natives and what it means for companies. Americus Reed is a marketing professor at Wharton, and Erik Gordon is a professor at the University of Michigan’s Ross School of Business. The following are five key points from their conversation. (Listen to the full podcast at the top of this page.)   ... "

AI Is Watching Employee Expenses

A classic approach to look anomalies in streams of data.

AI Is Watching Employee Expenses   in Bloomberg  By Olivia Carville

AppZen has developed an artificial intelligence program that can identify dubious work expense claims and educate employees about travel and expense policies. The company, which touts Amazon, IBM, Salesforce.com, and Comcast as users, estimated that it has saved its clients $40 million in fraudulent expenses. AppZen can audit 100% of claims in real time by running receipts through an algorithm that looks for duplication, discrepancies, or inflated expenses. The program reimburses legitimate employee expenses on the same day and kicks back any suspicious claims to human auditors for further investigation. In addition, the algorithm can compare the average cost of a flight from New York to Chicago against the amount expensed, and flag it if the price seems out of line for other similar flights that day.  ... " 

Can Amazon Scale up GO?

Scale up is very likely, what are the implications for in store marketing?

Has Amazon figured out how to scale its Go cashier-free tech to bigger stores?
by George Anderson in Retailwire, with expert comment.  Refers to WS Journal article.

Amazon is known for doing things in a big way. So, it should come as no surprise that the e-tailing giant is reported to be working on a way to put deploy the technology behind its Amazon Go convenience stores in much larger store environments.

The Wall Street Journal reports that Amazon is working at a location in Seattle to test how it needs to adjust the technology based on a bigger footprint. Higher ceilings and more items to track are two of the challenges Amazon is looking to address in the test, which is set up to look like a big box store.

In the current seven Amazon Go stores, customers with the Go app are tracked by a variety of technologies including “computer vision, deep learning algorithms and sensor fusion” as they enter and move around the location. Items are automatically added to a virtual shopping cart when a customer takes them off the shelf. When all done, customers simply walk out with their products and Amazon bills their accounts.  ... " 

Difference Between Business Intelligence and Data Science

Nicely done piece.  Good charts at the links below.   Though in some ways I have to ask if there should be a difference in practice?   Depending on Goals and potential value?   I always say you should start any 'advanced'  analytics/science with a descriptive examination.    Or you should have the experts of that description closely accessible to your team.  Attitude should be the same:  Achieve the business goal.

Updated: Difference Between Business Intelligence and Data Science

Posted by Bill Schmarzo in DSC.

I'm reposting this blog (with updated graphics) because I still get many questions about the difference between Business Intelligence and Data Science. Hope this blog helps.

I recently had a client ask me to explain to his management team the difference between a Business Intelligence (BI) Analyst and a Data Scientist.  I frequently hear this question, and typically resort to showing Figure 1 (BI Analyst vs. Data Scientist Characteristics chart, which shows the different attitudinal approaches for each)...  " 

Morse Code for Acccesibility

Most interesting.  Clever idea that has been developed further. Nice idea Google with GBoard!

Google’s Morse code-powered games aim to serve kids with limited mobility In Digitaltrends

Google is now offering access to five games controlled entirely by Morse code, thanks to a 48 hour “hackathon,” and a partnership with Adaptive Design Association. The games use the Morse code functionality introduced into Gboard in May 2018, and are intended for people with limited mobility who cannot use other control methods, as well as for people who are interested in learning Morse code.

The games were created over a period of two days by five teams of game designers and developers, each working with a child with limited mobility. Each of these children worked as the game’s creative director, and their specific vision helped to shape the games, making them uniquely molded around each child’s interests. For instance, Olivia’s “Alphabet’s Got Talent” is modeled after the talent shows she loves, while Hannah’s game uses Morse code to play musical notes. Players will be able to shoot soccer balls at targets in Matthew’s game, and Ben’s passion for trains is clear in his game that shows YouTube videos on a train once the correct letters are typed. Emmett — whose learning of Morse code through a similar Google-built game inspired this challenge — created a maze solved by typing different letters.  .... " 

See more on morse code assistant technology.  In experiments with Google.

Sunday, December 02, 2018

The Farm is the Grid

Intriguing partnership for data.  Need more of this.   Metadata and data.   Data has value.

Airbus, John Deere connect tractors, satellite data
By Lawrence Specker | lspecker@al.com

Flying tractors may not be in the cards just yet, but the seemingly odd-couple pairing of Airbus and John Deere has jointly won a major European agriculture innovation award.

In conjunction with the upcoming 2019 SIMA agriculture industry show in Paris, the two companies have received a silver medal for their Live NBalance program, which Airbus describes as “a service merging satellite and tractor data to monitor intra-field nitrogen balance even more precisely during the growing season.”

Tractor data? So much for the dream of going back to the farm to get off the grid. Apparently now the farm is the grid.   ... "

Immortalizing Ourselves as a Chatbot?

We are still far afield from this.  Will we be able someday to chat with long gone people?   Made me think of TheBrain, this blog, Brand equities like Mr Clean?  None close.   I returned to a long ago employer and found my technology explanatory entries in a wiki we created ....  but they had removed all the bylines! ... So shall it be unless you are name-famous enough to draw a crowd.   Anyway, they are researching the idea below.

Soon you can immortalize yourself as an A.I. chatbot. But should you?   In Digital Trends by @lukedormehl

Until technology allows us to upload our consciousness to a computer when our physical bodies start irreparably failing, death is going to remain a real thing. But what if you could continue communicating with loved ones — or, at least, a reasonable facsimile of them — long after they’ve shuffled off this mortal coil? It might sound like an episode of Black Mirror (it is!), but it’s also the basis for a recently announced research project being carried out at India’s Shree Devi Institute of Technology.  ... " 

Power and Digital Surveillance

In HBR Big Idea: private data and targeted advertisement.

How to Exercise the Power you Didn't ask for    By Jonathan Zittrain

I used to be largely indifferent to claims about the use of private data for targeted advertising, even as I worried about privacy more generally. How much of an intrusion was it, really, for a merchant to hit me with a banner ad for dog food instead of cat food, since it had reason to believe I owned a dog? And any users who were sensitive about their personal information could just click on a menu and simply opt out of that kind of tracking.

But times have changed.

The digital surveillance economy has ballooned in size and sophistication, while keeping most of its day-to-day tracking apparatus out of view. Public reaction has ranged from muted to deeply concerned, with a good portion of those in the concerned camp feeling so overwhelmed by the pervasiveness of their privacy loss that they’re more or less reconciled to it. It’s long past time not only to worry but to act.

Advertising dog food to dog owners remains innocuous, but pushing payday loans to people identified as being emotionally and financially vulnerable is not. Neither is targeted advertising that is used to exclude people. Julia Angwin, Ariana Tobin, and Madeleine Varner found that on Facebook targeting could be used to show housing ads only to white consumers. Narrow targeting can also render long-standing mechanisms for detecting market failure and abuse ineffective: State attorneys general or consumer advocates can’t respond to a deceitful ad campaign, for instance, when they don’t see it themselves. Uber took this predicament to cartoon villain extremes when, to avoid sting operations by local regulators, it used data collected from the Uber app to figure out who the officials were and then sent fake information about cars in service to their phones.  ... "

Data Non Normal

A challenge we often encountered, good examples of how to address it in this article   What if your Data is not Normal? in Towards Data Science  

I Add:    A lot of hand things we usually assume will not work when our data is not normally distributed.   So its important to know. This piece does a good job of surveying the assumptions and alternatives.  I like in particular the list of methods you can no longer be sure of.  The list contains many approaches that are 'understood'  by management and decision makers.

But I will add something that was not covered. If you can't use the common assumption normality , it will typically be harder to convince decision makers that your methods are correct.   So preparation  for that will also be needed.   Depending how the management has been trained, also the measures and risk involved with the decision being made. This may also point to formal tests for normality to be included in analytical process.  "

People's Attitude Towards Algorithms

Though humans have broad concerns of the use of computer algorithms, it is inevitable they will be used ...

Public Attitudes Toward Computer Algorithms  By   Aaron Smith in Pew
Americans express broad concerns over the fairness and effectiveness of computer programs making important decisions in people’s lives

Real-world examples of the scenarios in this survey
All four of the concepts discussed in the survey are based on real-life applications of algorithmic decision-making and artificial intelligence (AI):

Numerous firms now offer nontraditional credit scores that build their ratings using thousands of data points about customers’ activities and behaviors, under the premise that “all data is credit data.”
States across the country use criminal risk assessments to estimate the likelihood that someone convicted of a crime will reoffend in the future.

Several multinational companies are currently using AI-based systems during job interviews to evaluate the honesty, emotional state and overall personality of applicants.
Computerized resume screening is a longstanding and common HR practice for eliminating candidates who do not meet the requirements for a job posting.

Algorithms are all around us, utilizing massive stores of data and complex analytics to make decisions with often significant impacts on humans. They recommend books and movies for us to read and watch, surface news stories they think we might find relevant, estimate the likelihood that a tumor is cancerous and predict whether someone might be a criminal or a worthwhile credit risk. But despite the growing presence of algorithms in many aspects of daily life, a Pew Research Center survey of U.S. adults finds that the public is frequently skeptical of these tools when used in various real-life situations. .... "

Saturday, December 01, 2018

Delta Biometric Atlanta Terminal

Thought this was only in China, but its here now.    A needed use for security.

Here’s a look at Delta’s all-seeing, face-scanning, biometric airline terminal    By Melissa Locker in Fast Company

Delta Air Lines promised it would open the country’s first all-biometric terminal before the end of the year, and it has delivered. Starting December 1, customers flying Delta through the Atlanta airport’s Terminal F will be able to use facial recognition technology “from curb to gate” as a way to make it easier to fly through the airport.

For the biometric terminal, Delta worked with the Customs and Border Protection and the Transportation Security Administration to let travelers check in, drop bags, pass through TSA checkpoints, and board their flights–all using facial recognition systems powered by in-terminal cameras to verify their identity. The airline already lets some customers use their fingerprint as a boarding pass. ....  "

E-Ink New Digital Paper

We worked with e-ink for a time in the lab.

E Ink’s new digital paper lets you draw with almost no lag in Thenextweb.
Almost like the real thing.

The hypothetical pinnacle of digital paper is when it becomes indistinguishable from the real article, both in terms of reading and writing. Today, at the Connected Ink conference in Tokyo, E Ink Holdings took us a little bit closer with its new JustWrite technology.

JustWrite is designed to feel as close as possible to writing on a sheet of standard A4, without the inclusion of a bulky TFT backplane. It requires very little electricity to run, and boasts very low latency, in order to offer a natural-feeling writing experience.

So, how does this work in practice? You can see an artist demonstrate the technology in this video. As you’ll see, pencil strokes appear virtually instantaneously.

According to E Ink Holdings, JustWrite only requires a writing stylus and simple electronics to work, and works with a variety of compatible writing implements, including pens, brushes, markets, and stamps. Thanks to the simple construction of the JustWrite film, the e-ink displays are lightweight, bendable and highly flexible.  ...." 

E-Skin Functions as Bionic Compass

New idea, with details at the link:

E-Skin Functions as a Bionic Compass in IdeaConnection

An electronic skin able to detect motion relative to the Earth’s magnetic field could have applications in humans and robotics.

The e-skin was created by a team from Helmholtz-Zentrum Dresden-Rossendorf (HZDR) using a thin sheet of polymer foil equipped with layers of magnetic sensors able to detect geomagnetic fields. The resistance of the layers will alter based on their orientation to the Earth’s magnetic field, resulting in a bionic compass that can be affixed to a surface (including human skin). When worn on the tip of a finger, the e-skin was able to detect the direction the wearer was walking—displaying the information on a compass—and also transmit that information to a VR character on nearby screen. ... " 

Friday, November 30, 2018

Amazon Opens its Internal Machine Learning to All for Free

Nice, especially with regards to how machine learning links to its own devices.  I am noting Amazon Comprehend.

Amazon Opens Its Internal Machine Learning Courses to All for Free 
in TechCrunch   By Connie Loizos

Amazon is opening the internal machine learning courses it uses to train its own engineers for the first time to people outside the company, for free. According to the company's Matt Wood, Amazon has made available 30 different courses comprising more than 45 hours of training for developers, data scientists, data platform engineers, and business professionals. Wood said every course "starts with the fundamentals, and builds on those through real-world examples and labs, allowing developers to explore machine learning through some fun problems we have had to solve at Amazon. These include predicting gift wrapping eligibility, optimizing delivery routes, or predicting entertainment award nominations using data from IMDB (the Internet Movie Database)." Wood also said the coursework helps streamline best practices, and shows trainees how to begin work on a variety of Amazon Web Services (AWS) machine learning services, such as Amazon SageMaker, AWS DeepLens, Amazon Rekognition, Amazon Lex, Amazon Polly, and Amazon Comprehend.  ... "

Link to Courses.

(Updated) Amazon Extracting Information from Unstructured Medical Text

Announced at Amazon Invent this week.  This was just pointed out to me.  (Via Walter Riker)  I had heard of this being used in conjunction with assistant style interfaces,  How it might be accurate enough to purpose is unclear.  Worth a look.

Amazon Comprehend Medical     

Extract information from unstructured medical text accurately and quickly
No machine learning experience required

Amazon Comprehend Medical is a natural language processing service that makes it easy to use machine learning to extract relevant medical information from unstructured text. Using Amazon Comprehend Medical, you can quickly and accurately gather information, such as medical condition, medication, dosage, strength, and frequency from a variety of sources like doctors’ notes, clinical trial reports, and patient health records.

One of the important ways to improve patient care and accelerate clinical research is by understanding and analyzing the insights and relationships that are “trapped” in free-form medical text, including hospital admission notes and a patient’s medical history.

Today this is achieved by writing and maintaining a set of customized rules for natural language processing software, which are complicated to build, time-consuming to maintain, and fragile. A change to a single classification code name, for example, can impact dozens of hard-coded rules and failing to update a single one of them can result in missed or incorrect data. Machine learning can change all that with models that can reliably understand the medical information in unstructured text, identify meaningful relationships, and improve over-time.   ... "

(Update) Another piece on the same system:

Amazon launches patient data-mining service to assist docs
Through its Amazon Web Services platform, Amazon is offering an A.I. engine that can cull useful information from millions of unstructured electronic files, including patient electronic medical records.
By Lucas Mearian  Senior Reporter, Computerworld 

See alsoAmazon has now opened its internal training for this and other AWS AI systems to all for free, examining. See:  https://eponymouspickle.blogspot.com/2018/11/amazon-opens-it-internal-machine.html  

Smart Contracts for Supply Chains

Still some details about exactly how.    But no doubt there will be applications using this ongoing.  Be ready for it.
By Marisa Brown (see all posts) on Nov 20, 2018 Posted in Supply Chain Management
Marisa Brown's picture

“As the [blockchain] technology pushes the globe towards new economic models, we will only demand more from smart contracts,” Forbes, July 2018.

From the American Bar Association this September: “In the future, litigation attorneys may no longer be litigating the ‘four-corners’ of the contract, but rather expanding into the intent of the code.”

Smart contracts. We’ve been hearing a lot of hype about them in the media, but are they a business reality yet? Back in 2014, Fast Company called smart contracts “cryptocurrency's killer app.” At that time, it was all about the promise and potential of blockchain and smart contracts. The digital world was coming. And that has not changed: in APQC's 2018 supply chain management priorities and challenges research, respondents rated digitalization as the number one impact on the supply chain in the next three years.

But has the reality of smart contracts finally arrived? Recently, EY released its Marine Hull Insurance product offering that has been built on a blockchain architecture and is supported by the use of smart contracts. TradeLens from Maersk and IBM is a blockchain-enabled shipping solution using smart contracts that has now captured more than 235 million shipping events. So smart contracts are becoming a reality for early adopters.

But what exactly is a smart contract? How does it work? And what are the implications of using them?  ... '

Decision Trees with Python

With a full conceptual implementation in Python:

A breath of fresh air with Decision Trees in Medium

A very versatile decision support tool, capable of fitting complex algorithms, that can perform both classification and regression tasks, and even multi output tasks.

Trees are very interesting beings… they can start from a single branch and develop into a very complex network of branches with millions of leaves at their ends. It’s curious that a great number of technologies and methodologies are created based on what we see in Nature. Machine Learning Decision Tree algorithm is one of those cases!

A decision tree is a Supervised Machine Learning algorithm. This non-parametric system, contrary to Linear Regression models (which assume linearity), makes no underlying assumptions about the distribution of the errors or the data. It is a flowchart-like structure, composed of several questions (node) and depending on the answers (branch) given it will lead to a class label or value (leaf) when applied to any observation.  ... "

Berners-Lee Solid Project

More on Berners-Lee's SOlid Project, aimed to save the Web.  Informative.  Un-wall the gardens?  Better privacy and identity?   Too late?

Tim Berners-Lee’s Solid Project: Can It Save the Web?    By David Cardinal 

Not everyone thinks the web needs saving. After all, it’s a bigger and more essential part of our lives than almost anyone could have predicted when Tim Berners-Lee first wrote a browser for what became the World Wide Web. But the original peer-to-peer, open-protocol, read-write architecture has been overshadowed in many ways by walled gardens like Facebook, Google, and Amazon. One reason for that is that the original web protocols were limited. While they provided the means for browsing and linking, they didn’t come with standard solutions for identity, personal data storage, or social applications. So corporations stepped in to fill the void with their own best interests at heart and not those of their customers or the web at large. Decades later, Berners-Lee thinks he has a solution: his Solid (SOcial LInked Data) system.

Thursday, November 29, 2018

A Toy Car for Reinforcement Learning

Amazon shows come clever ways to demonstrate development for Reinforcement learning.  Toys, carefully designed and implemented can be an innovative easy to learn complex development lessons.

Go, DeepRacer, Go: How a toy car makes machine learning fun for developers

BY BEV BELLILE in SiliconAngle  With Video. 

At this year’s AWS re:Invent in Las Vegas, Amazon launched its AWS DeepRacer. While it is a toy car on the outside, it is also a highly sophisticated reinforcement learning platform that is designed to teach developers build, train and optimize models in the cloud, leveraging Amazon SageMaker and AWS RoboMaker. DeepRacer was demonstrated during AWS re:Invent in conjunction with a developer workshop that taught them how to use DeepRacer to build a reinforcement learning virtual model in the cloud and then deploy it to the “real-world” car.

“We believe that AWS DeepRacer is … [a] tool for us to help get this kind of innovative technology into the hands of everyday developers and data scientists,” said Mike Miller (pictured), senior manager of product management for AWS AI at Amazon Web Services Inc. He explained that this type of machine learning can have a steep learning curve and can be cost-prohibitive and limited to large enterprises with deep pockets. DeepRacer is a way to make it more accessible to more people. ..."

AI and the Barrier of Meaning: Human level AI?

Excerpt from NYT Op Ed, Good thoughts.  Human level AI is the intelligence of context.

Artificial Intelligence Hits the Barrier of Meaning

Machine learning algorithms don’t yet understand things the way humans do — with sometimes disastrous consequences.   By Melanie Mitchell

" .... Ms. Mitchell is Professor of Computer Science at Portland State University.
The Facebook founder, Mark Zuckerberg, recently declared that over the next five to 10 years, the company will push its A.I. to “get better than human level at all of the primary human senses: vision, hearing, language, general cognition.” Shane Legg, chief scientist of Google’s DeepMind group, predicted that “human-level A.I. will be passed in the mid-2020s.”

As someone who has worked in A.I. for decades, I’ve witnessed the failure of similar predictions of imminent human-level A.I., and I’m certain these latest forecasts will fall short as well. The challenge of creating humanlike intelligence in machines remains greatly underestimated. Today’s A.I. systems sorely lack the essence of human intelligence: understanding the situations we experience, being able to grasp their meaning. The mathematician and philosopher Gian-Carlo Rota famously asked, “I wonder whether or when A.I. will ever crash the barrier of meaning.” To me, this is still the most important question.   ... "

AI Disrupting Job Markets

Jobs and AI. 

Voices in AI – Episode 74: A Conversation with Dr. Kai-Fu Lee   By Byron Reese in GigaOM

About this Episode
Episode 74 of Voices in AI features host Byron Reese and Dr. Kai-Fu Lee discussing the potential of AI to disrupt job markets, the comparison of AI research and implementation in the U.S. and China, as well as other facets of Dr. Lee’s book “AI Superpowers”. Dr. Kai-Fu Lee, previously president of Google China, is now the CEO of Sinovation Ventures.

Visit www.VoicesinAI.com to listen to this one-hour podcast or read the full transcript. ... "

Target: Its About the Data

Useful view of how Target has addressed Online data

On Target: Rethinking the Retail Website  In HBS Working Data
Target is one big-brand retailer that seems to have survived and even thrived in the apocalyptic retail landscape. What's its secret? Srikant Datar discusses the company's relentless focus on online data. .... "     by Dina Gerdeman

Wednesday, November 28, 2018

Amazon Debuts Inferentia Chip

Amazon loads up the AWS cloud with Chips for prediction for machine learning.

Amazon debuts Inferentia, a custom machine learning prediction chip  in SiliconAngle

In another sign of Amazon.com Inc.’s broad ambitions in cloud computing, the company’s cloud company today debuted a new processor chip designed for machine learning.

The chip, called Inferentia, will be available via Amazon Web Service Inc.’s EC2 computing service as well as its SageMaker AI service and Amazon Elastic Inference, a new service also announced today. It’s designed to speed the process of inference, or predictions, carried out by machine learning models, helping power services such as Amazon’s Alexa and self-driving cars..... " 

New Way to Think About Cooling With Shade

Clever idea.  With images.

A new way to provide cooling without power
Device developed at MIT could provide refrigeration for off-grid locations.

David L. Chandler | MIT News Office 

MIT researchers have devised a new way of providing cooling on a hot sunny day, using inexpensive materials and requiring no fossil fuel-generated power. The passive system, which could be used to supplement other cooling systems to preserve food and medications in hot, off-grid locations, is essentially a high-tech version of a parasol. 

The system allows emission of heat at mid-infrared range of light that can pass straight out through the atmosphere and radiate into the cold of outer space, punching right through the gases that act like a greenhouse. To prevent heating in the direct sunlight, a small strip of metal suspended above the device blocks the sun’s direct rays.

The new system is described this week in the journal Nature Communications in a paper by research scientist Bikram Bhatia, graduate student Arny Leroy, professor of mechanical engineering and department head Evelyn Wang, professor of physics Marin Soljačić, and six others at MIT. ... " 

Analytics Solutions for Monitoring Conduct Risk

Risk should be considered in any kind of decision process.  Even seemingly very simple decisions can have high risk.  So, this means they are not simple decisions after all.   Conduct risk, or how people: individuals or groups (or cognitive agents) act or react, is particularly difficult in today's networked world.  Or how regulation is a kinds of conduct.   Good piece addressing this, but not quite enough about how the context of conduct can also make a huge difference.  But good start here.

The advanced-analytics solution for monitoring conduct risk  in McKinsey

Advanced analytics and machine learning can help institutions “connect the dots” across customer and other data to detect conduct risk comprehensively and cost-effectively.

Advanced analytics and machine learning can help institutions “connect the dots” across customer and other data to detect conduct risk comprehensively and cost-effectively.

The fallout from highly visible instances of misconduct—including reputational damage, material losses, and increased regulatory focus—have led financial institutions to treat conduct risk as an important priority. As a risk category, however, conduct has proved difficult to monitor effectively with traditional controls and testing. The varieties of potential misconduct are numerous, and transgressing individuals or whole departments find ever-changing ways to circumvent rules. In addition, sample-based tests such as transactional reviews are not effective in finding isolated instances of misconduct.

Effective misconduct detection requires a new approach, one that can “connect the dots” across individual and team activities. These connections are often hidden in data that derive from multiple sources. They can be revealed by deploying advanced analytics and machine learning to mine the rich data and thereby identify incongruous sales or transaction patterns, misaligned incentives, and inappropriate customer interactions. Frequently underutilized records (such as the transcripts of customer interactions), can be automatically analyzed for potentially inappropriate treatment that customers may have experienced. But advanced-analytics solutions go beyond the detection of past instances of misconduct—by which the damage to an institution, if any, has already been done—to intercept the outlying patterns of activity that could lead to future losses.

What is conduct risk?

The definition of conduct risk varies somewhat by industry and region but can be commonly understood as individual or group actions that could cause unfair outcomes for customers, undermine market integrity, and damage the firm’s reputation and competitive position.

Conduct risk has only recently become recognized as a stand-alone risk category, in the aftermath of a number of high-profile incidents of misconduct (and regulatory responses) in retail and commercial banking, capital markets, and wealth management ....

Adjusting the Level of Goals

Goals make  me think of specific numerically defined measures, so if we measure a goal, which this piece suggests we can, can we use optimization techniques, and newer methods like GANs to drive towards them?   In theory, at least, yes.   Worth a thought and a test.

Why You Should Stop Setting Easy Goals  in the HBR
By Amitava Chattopadhyay,  Antonios Stamatogiannakis, Dipankar Chakravarti

When setting team goals, many managers feel that they must maintain a tricky balance between setting targets high enough to achieve impressive results and setting them low enough to keep the troops happy. But the assumption that employees are more likely to welcome lower goals doesn’t stand up to scrutiny. In fact, our research indicates that in some situations people perceive higher goals as easier to attain than lower ones — and even when that’s not the case, they still can find those more challenging goals more appealing.

In a series of studies we describe in our latest paper  , we tested how people perceive goals by asking participants on Amazon’s crowdsourcing marketplace, known as Mechanical Turk, to rate the difficulty and appeal of targets set at various levels and across spheres from sports performance and GPA to weight loss and personal savings. We asked about both “status quo” goals, in which the target remained set at a baseline level similar to recent performance, and “improvement goals” in which the target was set higher than the baseline by varying degrees. .... "

ACM Tech Talk: From Media to Meaning: Classic Machine Learning

Good piece.   With frightening implications of the combination surveillance, neural methods,  and the use of high speed video generation to fake anything we want. Notable explanation of Adversarial neural networks (GAN).

Watch First ACM Tech Talk: “From Media to Meaning: Classic Machine Learning” with Blaise Agüera y Arcas

Blaise Agüera y Arcas is a Distinguished Scientist at Google AI, where he leads a team that works on intersections of neural nets and neuromorphic AI. In this talk, Blaise examines the recent revolution in deep networks which has enabled the use of classic machine learning techniques to go from media to meaning. He covers neural nets, generative adversarial techniques, and the ethical implications of these new technologies.  ... "

The Evolution of Machine Learning

Abstract of a good paper, describes well the reasons neural network methods evolved from our early uses in the 90s to the current day.  Would not have guessed its current uses from early examples.  How will it continue to evolve?

Learning Machine Learning    By Ted G. Lewis, Peter J. Denning 
Communications of the ACM, December 2018, Vol. 61 No. 12, Pages 24-27

Machine learning has evolved from an out-of-favor subdiscipline of computer science and artificial intelligence (AI) to a leading-edge frontier of research in both AI and computer systems architecture. Over the past decade investments in both hardware and software for machine learning have risen at an exponential rate matched only by similar investments in blockchain technology. This column is a technology check for professionals in a Q&A format on how this field has evolved and what big questions it faces.

Q: The modern surge in AI is powered by neural networks. When did the neural network field start? What was the first implementation? ... " 

Tuesday, November 27, 2018

Bitcoin for Real World Payments Drops 80%

Ultimately Bitcoin has to be usable for real-life exchange.  Its use there has dropped considerably.   More evidence towards a cryptocurrency winter.  At least until capabilities and regulation catch up.  Note in particular the mention of better infrastructure.

Bitcoin for payments a distant dream as usage dries up    By Tom Wilson in Reuters

LONDON (Reuters) - The use of bitcoin for commercial payments has dropped dramatically this year, even as the original digital coin starts to fulfill one of the basic features of any payment currency: stability.

The value of bitcoins handled by major payment processors shriveled nearly 80 percent in the year to September, data from blockchain researcher Chainalysis shows. That suggests the cryptocurrency is struggling to mature from speculative asset to a serious alternative to state-issued money.

Months of relative calm in bitcoin prices after the wild swings of last winter had fueled hopes it would become widely used for payments, its intended purpose.

But its collapse in use as a payment currency has instead left big finance and crypto insiders eyeing better technological infrastructure to help bitcoin take off as a way to pay.  .... " 

See also:   Top 5 Crypto Performers Overview: XEM, Ripple, EOS, Bitcoin, IOTA  ... 

Cryptocurrency Winter Upon Us? Blockchain Still Rising

Once again,  I am promoting MIT Tech Reviews Chain newsletter.   Lots of useful introductory links in their newsletter link below.   I won't do this forever, suggest you subscribe at the link.  Lots of breaking news here.   I note again, because it has created confusion:  Blockchains, and more broadly stated Distributed Ledgers,  are technologies that are used to implement cryptocurrencies ... the are NOT the same thing.   Note below emerging regulation SEC movement on cryptocurrencies.

Chain Letter:   Are we approaching a Cryptocurrency 'Winter'?  
Blockchains, cryptocurrencies, and why they matter
11.20: Turning over a new leaf

Welcome to Chain Letter! Great to have you. Here’s what’s new in the world of blockchains and cryptocurrencies.  ..... 

The ICO is probably dead. The US Securities and Exchange Commission sent shockwaves through the cryptocurrency world on Friday with an announcement that it has settled charges against a pair of companies for conducting illegal digital token sales. The two initial coin offering (ICO) projects, called Airfox and Paragon, resemble many others that have occurred during the past two years. That probably means more busts are on their way.

The SEC has already cracked down on a few ICOs, but these charges are the first that did not involve charges of fraud as well. Airfox and Paragon simply failed to register with the SEC before selling their tokens, which the agency says are not exempt from regulations that govern traditional securities investments like stocks and bonds. That’s important, because it appears the agency has developed a template for future prosecutions, writes Stephen Palley, a lawyer at the DC firm Anderson Kill.  ... " 

Wal-Mart has a Toy Lab

In a completely different domain, we asked the same question:  How can we get consumers to feel they are very involved with us,  are our special customer?   Special testers of product and experience?   Here the more recent concept of the 'unboxing video' is being used.   Plus some aspects of humor and scripted interaction.   Nice idea.

Can online unboxing videos turn Walmart into ‘America’s Best Toy Shop?’
 This article was written jointly by Tom Ryan and Matthew Stern. In Retailwire,

Walmart this holiday introduced an online shop, The Walmart Toy Lab, that invites kids to become a “Walmart toy tester” and play with 20 top trending toys from their computer or tablet.

“Like stepping into an interactive unboxing video, The Walmart Toy Lab lets kids take on the role of an official Walmart Toy Tester,” wrote Walmart in a statement.

Unboxing and toy feature videos have shown to be a huge draw for toy-shopping kids. Earlier this year, Walmart partnered with pre-teen YouTube star Ryan of RyansToyReviews, who in 2016 made a whopping $11 million off his unboxing videos.

The Toy Lab rollout comes a few months after Walmart’s announcement that it was branding itself as “America’s Best Toy Shop” with expanded toy aisles and assortments in its stores, an improved toy demoing experience in-store and exclusive toy-related content online.

At the Walmart Toy Lab microsite, an interactive video first introduces the game’s host, Burt, who guides kids through the toy-testing steps. Using a “Funtroller,” kids select toys to test and can choose to take a closer look, try their main features and watch other children play with them. Kids can also click the “Don’t Push” button and see Burt enter a dream sequence, hang upside down or otherwise face an “unexpected surprise.”  ... "

Teams for Digital Procurement

Procurement a long time interest ... huge amounts of money involved, a classic place for better analytics.

Digital Procurement: The Benefits Go Far Beyond Efficiency
Procurement teams can play a key role in shaping a company’s digital strategy.

By Coleman Radell  and David Schannon  of Bain.

Simpson's Paradox Again

Mentioned this topic once before, here is a more data oriented explanation,  less technical and practical to real world problems .  Everyone should understand this, but too rare to find even a data scientist with an understanding.   Nicely done.

Simpson’s Paradox: How to Prove Opposite Arguments with the Same Data

Understanding a statistical phenomenon and the importance of asking why
Imagine you and your partner are trying to find the perfect restaurant for a pleasant dinner. Knowing this process can lead to hours of arguments, you seek out the oracle of modern life: online reviews. Doing so, you find your choice, Carlo’s Restaurant is recommended by a higher percentage of both men and women than your partner’s selection, Sophia’s Restaurant. However, just as you are about to declare victory, your partner, using the same data, triumphantly states that since Sophia’s is recommended by a higher percentage of all users, it is the clear winner.

What is going on? Who’s lying here? Has the review site got the calculations wrong? In fact, both you and your partner are right and you have unknowingly entered the world of Simpson’s Paradox, where a restaurant can be both better and worse than its competitor, exercise can lower and increase the risk of disease, and the same dataset can be used to prove two opposing arguments. Instead of going out to dinner, perhaps you and your partner should spend the evening discussing this fascinating statistical phenomenon.

Simpson’s Paradox occurs when trends that appear when a dataset is separated into groups reverse when the data are aggregated. In the restaurant recommendation example, it really is possible for Carlo’s to be recommended by a higher percentage of both men and women than Sophia’s but to be recommended by a lower percentage of all reviewers. Before you declare this to be lunacy, here is the table to prove it. ... "

Monday, November 26, 2018

ACM on Emotionally Sentient Agents

Designing Emotionally Sentient Agents

Welcome to the December 2018 Communications of the ACM. The full issue and related content is available through the CACM Issue link, and also through the Table of Contents below.

In this issue:

"Designing Emotionally Sentient Agents," by Daniel McDuff and Mary Czerwinski, explains the importance of emotional components in the design of computer agents and assistants. McDuff describes the work behind emotionally sentient systems in an original video at bit.ly/2BlPjBG.

"Uncertainty in Current and Future Health Wearables," by Bran Knowles, et al., explores the difficulties that arise from the unpredictability of health wearables and related data.

"Point/Counterpoint presents two sides of a debate over AI regulation: "Should AI Technology Be Regulated? Yes, and Here's How," by Oren Etzioni, is countered by "Regulators Should Allow the Greatest Space for AI Innovation," by Andrea O’Sullivan and Adam Thierer. Etzioni and Thierer discuss their positions in an original video at bit.ly/2OTVqkv.

And more in the table of contents.  https://cacm.acm.org/magazines/2018/12

Wharton, MIT and BC Aim to Disrupt Global Supply Chain

Another example of verification and validation applications of Blockchain infrastructure, here in supply chain.   Such applications are an ideal experimental first step.   Useful details at the link. 

How a New Technology Can Disrupt the Global Supply Chain
Operations Management  In Knowledge@Wharton

An interdisciplinary team from MIT, Wharton and Boston College has created a new blockchain-based system that has the potential to disrupt the global supply chain. Called ‘b_verify,’ the system is designed to help small and medium-size enterprises — especially those in developing nations — get financing from lenders at potentially better terms while mitigating warehouse deposit fraud. The system brings greater transparency to a key part of the supply chain, which can have a big impact on global trade financing. B_verify introduces a series of blockchain technology innovations tailored to facilitate supply chain finance and operations management.

“The potential benefits are vast and global in scale,” said Gerry Tsoukalas, Wharton professor of operations, information and decisions, who was part of the team. Small and medium-size enterprises, he said, represent the backbone of many economies in the world, and they account for more than half of the jobs as well as a third of global GDP. But despite their scope and impact, these companies have a harder time getting financing than larger established firms. He said the World Bank estimates their global financing shortfall to be $2.6 trillion.

Small and medium-sized firms also find it difficult to get financing on terms as favorable as the ones big companies get because they usually lack the latter’s track record and reputation. Banks typically would charge higher interest rates or put more restrictions on loans to smaller enterprises because they are less certain of repayment. Add to the mix the propensity for fraud, especially in the developing world, and smaller firms get the worse end of the proverbial stick. “Obtaining loans at reasonable rates can be very challenging for small firms,” Tsoukalas said.   .... "