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Friday, July 21, 2017

Robot Physical Therapy

This came to mind in a recent physical therapy session, with my PT describing how muscles could be trained back into health   Why not hook up  a sensory means to watch the muscles,  detect changes in pattern,  and adjust the regimen towards a goal.  Here an example of work in this direction from EPFL. Though here about neurological changes and strokes, why not for any kind of physical therapy?

 In Newscientist: 
" ... Researchers at the Swiss Federal Institute of Technology in Lausanne (EPFL) and Lausanne University Hospital in Switzerland have developed a smart harness that uses artificial intelligence to help people regain their mobility following certain neurological injuries. The smart harness collects information on leg movement, stride, and muscle activity from body sensors, and then uses that information to provide support specifically designed for the way the patient walks, determining how much force to apply to produce a natural gait. Following a single, one-hour training session with the smart harness, patients with spinal cord injuries showed immediate improvement in their gait out of the harness compared to those who did not use the harness, according to the researchers. The system helps patients rebuild lost muscle mass and relearn posture and movement, while also retraining the brain to handle the balance between gravity and forward motion that walking requires. ... " 

Towards Lights-Out Fulfillment

'Lights-Out' used to be a favorite term when we worked in AI applications for the enterprise. Dramatically implying no humans, or lights needed to be involved.    Near total automation is still not here, but is approaching.  Consider the implications.  I note that Amazon now has 341K employees.  
Also it seems that most significant technological change mentioned here has Amazon involvement.   Now well over the tipping point for Influencing broad changes. Towards lights-out.  Keep watching their activity in this space.

Bezos move spurs $20B of growth in logistics robotics
Lights-out fulfillment will be the new norm within a decade   By Greg Nichols for Robotics.  In ZdNet.

This year is turning out to be a tipping point for how companies manage e-commerce fulfillment.

Worldwide sales of warehousing and logistics robots hit a respectable $1.9 billion in 2016. By 2021, according to a forecast by research firm Tractica, the market will hit a whopping $22.4 billion.

To better conceptualize the market explosion underway, consider that 40,000 units of warehousing and logistics robots were sold last year. A projected 620,000 units will be sold in 2021.

Why the change? In short: Amazon. If the last couple Prime Days proved anything, it's that a) Jeff Bezos is allowed to declare national holidays, and b) the investment Amazon made in warehouse logistics when it bought Kiva Systems for $775 million in 2012 presaged a complete transformation in global commerce.  ... " 

AI Exceeding Human Performance

Predictions are cheap,  machines have been faster than humans for some time, but when inserted in a set of tasks that that need to be done can be very different.   Thoughtful ideas here:

Intelligent Machines
Experts Predict When Artificial Intelligence Will Exceed Human Performance

Trucking will be computerized long before surgery, computer scientists say.  by Emerging Technology from the arXiv  May 31, 2017

Artificial intelligence is changing the world and doing it at breakneck speed. The promise is that intelligent machines will be able to do every task better and more cheaply than humans. Rightly or wrongly, one industry after another is falling under its spell, even though few have benefited significantly so far.

And that raises an interesting question: when will artificial intelligence exceed human performance? More specifically, when will a machine do your job better than you?

Today, we have an answer of sorts thanks to the work of Katja Grace at the Future of Humanity Institute at the University of Oxford and a few pals. To find out, these guys asked the experts. They surveyed the world’s leading researchers in artificial intelligence by asking them when they think intelligent machines will better humans in a wide range of tasks. And many of the answers are something of a surprise. .... " 

Thursday, July 20, 2017

Sears Integrates Alexa in Appliances, Sells on Amazon

Have noted earlier that GE is also integrating voice control in appliances.  Here an example of where a form of AI kicks up stock price, a rare event.    In Adage: 

Sears to Integrate Alexa Into Appliances and Start Selling on Amazon
Shares in Sears Holdings kicked off their biggest rally in almost two months after the company agreed to sell its Kenmore line on Amazon.com and integrate Amazon's virtual assistant Alexa into the appliances. That means the company's air conditioners and other devices will respond to voice commands.

Terms of the partnership weren't disclosed, and it's unclear how much of a boost Sears will get from the arrangement. But the company is badly in need of growth. Once the world's largest retail chain, Sears has racked up more than $10 billion in losses over the past six years.   ... " 

(Update)   Did Amazon just send Sears a life line with their Kenmore deal?   by George Anderson in Retailwire,  includes expert discussion.

If you can’t beat ‘em, join them. That appears to be the thinking behind an announcement yesterday by Sears Holdings that its Kenmore brand will now be sold on Amazon.com. ... 

The deal between the two companies calls for Amazon to own the inventory, but Sears will ship orders to customers from its warehouses. Innovel Solutions, a Sears business unit, will deliver and install the appliances.  .... " 

Amazon Spark Crowdsources Advertising?

Amazon takes another step forward.  I would imagine this will also emerge on the new Amazon Show screen as well.  A crowdsourcing of advertising to enthusiastic consumers?  Note their previous creation of an Influencer program.  Seems most every possible media channel is being investigated or even created by Amazon.

Amazon adds a shoppable “Spark” to Prime   By Deena M. Amato-McCoy in Chainstore Age.

Amazon Prime is getting more social as the online giant looks for yet more ways to entice shoppers to buy. 

On Wednesday, the online giant launched Amazon Spark, a new shoppable social media feed for its Prime members. Described as “a place to discover things from people who share your interests,” Spark will help Prime users discover — and shop for -- merchandise found across followers’ stories and ideas, according to Amazon’s website.

In a process similar to Instagram or Pinterest, Prime members use Spark to share photos of products they like. While users browse their Spark feed, they can tap on merchandise that inspires them and order that item instantly.   ..... " 

(more details at link)

Analytics Magazine

The latest analytics Magazine from Informs.    A practically oriented view of how analytics can be used in business today.   Industry News and Articles.

Limitations of Deep Learning

Just the introductory paragraphs to a post in the Keras Blog.   Worth following.   Useful statement of limitations,  on both narrow aspects of deep learning, and more generally about AI.   Technical, but readable as well.   I agree that the success of such models is quite unexpected, and to be considered with caution outside narrow applications.

The limitations of deep learning   By Francois Chollet

This post is adapted from Section 2 of Chapter 9 of my book, Deep Learning with Python (Manning Publications). It is part of a series of two posts on the current limitations of deep learning, and its future.

This post is targeted at people who already have significant experience with deep learning (e.g. people who have read chapters 1 through 8 of the book). We assume a lot of pre-existing knowledge.

Deep learning: the geometric view

The most surprising thing about deep learning is how simple it is. Ten years ago, no one expected that we would achieve such amazing results on machine perception problems by using simple parametric models trained with gradient descent. Now, it turns out that all you need is sufficiently large parametric models trained with gradient descent on sufficiently many examples. As Feynman once said about the universe, "It's not complicated, it's just a lot of it"   .... " 

(Update) See also, the Future of Deep Learning, from the same blog.  (technical)

Game Theory and Competitive Strategy

A favorite topic for corporate strategy considerations, but as we discovered, somewhat hard to apply in realistic circumstances.   Especially for competitive interactions. Fairly non-technical view.

In Game Theory, No Clear Path to Equilibrium   In Quanta Magazine.
In 1950, John Nash — the mathematician later featured in the book and film “A Beautiful Mind” — wrote a two-page paper that transformed the theory of economics. His crucial, yet utterly simple, idea was that any competitive game has a notion of equilibrium: a collection of strategies, one for each player, such that no player can win more by unilaterally switching to a different strategy.

Nash’s equilibrium concept, which earned him a Nobel Prize in economics in 1994, offers a unified framework for understanding strategic behavior not only in economics but also in psychology, evolutionary biology and a host of other fields. Its influence on economic theory “is comparable to that of the discovery of the DNA double helix in the biological sciences,” wrote Roger Myerson of the University of Chicago, another economics Nobelist.

When players are at equilibrium, no one has a reason to stray. But how do players get to equilibrium in the first place? In contrast with, say, a ball rolling downhill and coming to rest in a valley, there is no obvious force guiding game players toward a Nash equilibrium.  .... " 

How Alibaba Works with Retail Data

Via O'Reilly.

How Alibaba does retail data

What does it take to compete in a global market in which retail and the cloud are increasingly intertwined? Alibaba says it's domain-specific data science and machine learning for the masses. Here's how Alibaba's strategy differs from Amazon's—and how the company pulls it off.  

From ZDNet:  A view of Omnichannel.

Alibaba: Building a retail ecosystem on data science, machine learning, and cloud
Slide show By George Anadiotis for Big on Data     .... " 

Wednesday, July 19, 2017

IBM And Automation Anywhere Partner to Produce BPM Bots

I had been wondering for some time how IBM might be integrating business process management (BPM) and their cognitive methods to approach improving real business process.  Always seemed they had rule based systems, so why not?  Note the integration of software Bots.  Ultimately a very practical thing for improving operational management.   Powerful concept that we constructed piecemeal.  Don't like the term RPA, as it confuses the context.  Here from Forrester,  indications of some related steps: 

" ... IBM and Automation Anywhere (AA’s) today announced a collaboration (note-not a formal partnership yet) to integrate (AA’s) Robotic Process Automation (RPA) platform, used to create software bots to handle repetitive, task-based work, with IBM’s portfolio of digital process automation software, that includes IBM Business Process Manager and Operational Decision Manager. For AA, the partnership is a validation of its strong position in the RPA market, as shown in the Forrester Q1 RPA wave. For IBM, the partnership will enable clients to use AA’s RPA platform to create software bots that execute tasks within larger business processes managed by IBM’s software. Here’s our take.

IBM Can Add Smarts to AA’s RPA Platform

RPA works in a very dumb fashion today – mimicking human keystrokes and mouse movements – where all decisions must be explicitly programmed into the script. The result is that there are very few real decisions made beyond simple logic loops. Watson will be relevant down the road, but as a first step, RPA will benefit from IBM’s mature business rules engine (Decision Manager) or the embedded rules in the BPM platform. But as interesting, IBM’s content analytics, if part of the collaboration, can allow AA to keep pace with unstructured RPA intelligence from Workfusion and other RPA competitors moving quickly in that direction. RPA use cases that comb through unstructured content will be ahead of chatbot and AI-based digital workers. .... " 

Min Basadur's Simple Question

A former colleague of mine at Procter & Gamble,  Min Basadur's work is described.   Clever and very simple use of the question  "How Might we ... ?"  is mentioned.   Remember hearing of its use as a tool upon arrival at the company.  The very simplicity of the question makes it a great place to start.

Google and Facebook still use the 3-word question that saved a $225 billion company in the 1970s. 
... " 

Apple Journals its AI/Machine Learning Efforts

Apple has started blogging to draw attention to its AI work  : Sorry, it’s a ‘Journal’   by James Vincent@jjvincent in theVerge:

" ... The company’s new website, titled “Apple Machine Learning Journal,” is a bit grander than a blog. But it looks like it will have the same basic function: keeping readers up to date in a relatively accessible manner. “Here, you can read posts written by Apple engineers about their work using machine learning technologies,” says the opening post, before inviting feedback from researchers, students, and developers.

As the perennial question for bloggers goes, however: what’s the point? What are you trying to achieve? The answer is familiar: Apple wants more attention. .... " 

Looks to be very well worth following.

Claude Shannon

Great to see this article about Claude Shannon, who is little mentioned these days, but truly was a key element of understanding the value of knowledge in systems of information.  Had never heard the 'work habits' angle.

From Quora and Inc.
4 Brilliant Work Habits of History's Most Underrated Genius
Claude Shannon was the father of the information age, and we can all learn from him. .... " 

Google Glass Better for Business Applications

To put it simply,  Google Glass just looks more business-like than Augmented Reality Goggles.  It at least implies that you are still attached to solving problems in the real world.   Even better focused than you would be with AR.

Good piece in Engadget on the potential re-emergence in business.

Believe it or not, Glass may avoid being an all-time tech flop.
by Nathan Ingraham, @nateingraham  In Engadget.

" .... It was wild and impressive, but Google misjudged how that hype would translate into actual consumer usage. The look of someone wearing a camera on her face was too alienating, and Google never presented a complete vision of what Glass could do. That was part of the plan: The Explorer Edition that Google sold to early adopters was mostly meant for developers to use and figure out what apps made sense for it. But Glass never progressed beyond that experimental phase, and it was taken off the market in Jan. 2015, before a consumer edition even shipped.

Google never said Glass was dead, but it was clear the company's vision of a mass-market consumer product wasn't happening. So the company spent two years retooling and refocusing, and now Glass is back -- as an enterprise product meant to help workers get tricky jobs done. It's a rare example of parent company Alphabet significantly pulling back the ambition and scope of a product to serve a small market. In doing so, Google may give Microsoft's Hololens some unexpected competition in the augmented reality space. ... " 

CMO's Preparing for the Future

Former colleague of mine is interviewed. Business, now more than ever, is about prediction.

How CMOs Can Prepare For The Future: A Q&A With 'Predicting The Turn' Author Dave Knox   by Jennifer Rooney 

Dave Knox regards and engages with the marketing industry from an incredibly unique and insightful vantage point. As a veteran of Procter & Gamble, managing director of WPP Ventures, CMO of Rockfish, cofounder of The Brandery venture accelerator, startup advisor, blogger and author, he has a keen understanding of the power and challenges of big-name branding as well as the promise, innovation and opportunity of startup business.

His latest book, Predicting the Turn, provides CMOs with invaluable perspective on how to anticipate industry upheaval ahead and how best to prepare and lean in to those changes that can radically disrupt — even threaten — their businesses. Taking a page from startups, legacy companies can eschew the old habits that slow transformation and move forward for growth.  ... " 

On the Business of AI

Right now, for the second time in a long career, am involved directly in making AI part of a business.  So was struck by this view.

HBR:   On the business of AI. ...

".... What can AI do Today?

The term artificial intelligence was coined in 1955 by John McCarthy, a math professor at Dartmouth who organized the seminal conference on the topic the following year. Ever since, perhaps in part because of its evocative name, the field has given rise to more than its share of fantastic claims and promises. In 1957 the economist Herbert Simon predicted that computers would beat humans at chess within 10 years. (It took 40.) In 1967 the cognitive scientist Marvin Minsky said, “Within a generation the problem of creating ‘artificial intelligence’ will be substantially solved.” Simon and Minsky were both intellectual giants, but they erred badly. Thus it’s understandable that dramatic claims about future breakthroughs meet with a certain amount of skepticism.

Let’s start by exploring what AI is already doing and how quickly it is improving. The biggest advances have been in two broad areas: perception and cognition. In the former category some of the most practical advances have been made in relation to speech. Voice recognition is still far from perfect, but millions of people are now using it — think Siri, Alexa, and Google Assistant. The text you are now reading was originally dictated to a computer and transcribed with sufficient accuracy to make it faster than typing. A study by the Stanford computer scientist James Landay and colleagues found that speech recognition is now about three times as fast, on average, as typing on a cell phone. The error rate, once 8.5%, has dropped to 4.9%. What’s striking is that this substantial improvement has come not over the past 10 years but just since the summer of 2016. .... "

Multisensor Interfaces Reference

Of technical interest: 

Announcing: The Handbook of Multimodal-Multisensor Interfaces: Foundations, User Modeling, and Common Modality Combinations. Volume 1
Eeditors: Oviatt, Sharon; Schuller, Bjorn; Cohen, Philip R; Sonntag, Daniel; Potamianos, Gerasimos; Krueger, Antonio

Publisher: Morgan and Claypool/ACM Press.

https://lnkd.in/g93NPTD.

https://lnkd.in/gYPYKJU

This is a THREE volume series ..... "

Tuesday, July 18, 2017

Towards Innovation Cultures

Amazon, 3M, and Google All Have This Invisible Advantage
These five steps can help any organization gain an unseen edge over the competition.
By Soren Kaplan     Author, The Invisible Advantage  @sorenkaplan

Best Buy Wants to Install Smart Homes

Recall that Amazon just also announced a smart home consultation service, apparently aimed at getting their devices installed.  Probably a requirement for typical aftermarket installations of Smart Homes.  For the 'non digital native'.

Is Best Buy’s latest Geek Squad service a blueprint for niche IoT?  by Matthew Stern in Retailwire.  With discussion.

As Best Buy has worked to turn itself around, two of its biggest differentiators have been its Geek Squad service offerings and its focus on selling and supporting IoT devices. The chain’s latest move leverages both by focusing its Geek Squad resources on a very specific niche within the smart home/IoT area. Best Buy is offering smart home consultations and installations geared towards adults acting as caretakers for elderly parents.

The smart home service, called Assured Living, consists of a free assessment that allows caregivers to determine the right arrangement of in-home monitors, devices and alerts for effectively caring for the elderly people in question, the Star Tribune reported. Geek Squad employees then implement the technology. .... " 

Will start to cover these efforts on the term 'Smart Home Services' tag below.

Jumping Robotics

A small scale, jumping robot.  Quite impressive in details and related efforts.

Salto-1P Is the Most Amazing Jumping Robot We've Ever Seen,   By Evan Ackerman

Salto-1P uses a small motor and a system of linkages and gears to jump. Because it spends so little time in contact with the ground, the robot needs to do most of its control in the air. To do that, it uses a rotating inertial tail and two little thrusters to stabilize and reorient itself in between jumps..... "


Lucy from Equals 3

An example of Watson AI.

Superpower your marketing process with Lucy
Pull deep insights from piles of customer data. Make genius decisions. Compress months of work to one day.  ... Get big-brain assistance in research, segmentation, and planning.
Meet Lucy. Your ace time-saver — with A.I. skills.  (Uses Watson)

At your command, Lucy carries out vital tasks quickly with her superpowered information-gathering and analytic capabilities—freeing you for higher-order problem solving.

Lucy delivers brand Insights

Lucy is a voracious reader, digesting nearly 1,000 accredited news sources daily. That equates to roughly 250,000 articles a day! She then analyzes what she reads and delivers you up-to-date insights based on your brand mentions. .... "

Monday, July 17, 2017

Multiple Selves vs Better Bots

In Linkedin:

'Multiple Selves,' Not Better Bots, Is AI's 'Personal Productivity' Future

Published on April 3, 2017 Featured in: Big Ideas & Innovation, Productivity, Technology

by Michael Schrage,   visiting fellow at imperial college business school, innovation & entrepreneurship

MIT Sloan School's 'Initiative on the Digital Economy' recently published some of my new work on how the future of (inter)personal productivity inside the enterprise and out belongs to 'digital selves.' My essential argument: AI's true algorithmic impact will come more from 'Augmenting Introspection' than 'Artificial Intelligence.' We'll see 'Quantified Selves' emerging from the 'Quantified Self' as talented individuals and ambitious firms mash-up all manner of data and 'workplace analytics' in their collective quest to become more valuable and more productive. ... " 

EBay Looks at AI

We had some interactions with eBay in their early days.  Now Forbes does a quick look at how they are aiming to use AI methods to produce better focused personalized experiences.     Not a bad place to start, you already have a great deal of data, like customer scripts and resulting journies to start with.

More on the Google PAIR Effort: People+AI

 As important as how smart the methods will be,  will be the means by which we collaborate with them.   Thinking about this as a team, beyond just a person using a machine, will also be key.

Your Best Teammate Might Someday Be an Algorithm
A new program from Google seeks ways for AI systems to work more effectively with humans.
by Will Knight    In MIT Technology Review.  .... " 

(Update)  Wired writes about  'artificial stupidity' can arise.

Apple vs Google Maps

In Flowingdata:  

In Google and Apple mapping approaches.   I have looked at both of these for years now on the IOS smartphone.  A close comparative look at different mapping approaches.  Variation in data and design.   Choices in different user experience.  Shows the incredible investment and multiple redesigns that have been made.

Pharma and the Sharing of Data in Drug Discovery

Not quite what I call crowdsourcing, but rather a  means to make it easier to share and fund expensive research efforts.  Ultimately the very expensive genomic research efforts have to be funded too.   Good to see this direction being explored.

Big Pharma Buys into Crowdsourcing for Drug Discovery
By Menaka Wilhelm  in Wired

" .... Part of the problem is simply that drug design is hard. But many researchers point to the systems of paywalls and patents that lock up data, slowing the flow of information. So a nonprofit called the Structural Genomics Consortium is countering with a strategy of extreme openness. They’re partnering with nine pharmaceutical companies and labs at six universities, including Oxford, the University of Toronto, and UNC Chapel Hill. They’re pledging to share everything with each other—drug wish lists, results in open access journals, and experimental samples—hoping to speed up the long, expensive drug design process for tough diseases like Huntington’s. .... "

Machine Learning and Emergence

Complete article at the link in DSC:

The E-Dimension: Why Machine Learning Doesn’t Work Well for Some Problems?
by Shahab Sheikh-Bahaei, Ph.D.*
Principal Data Scientist,  Intertrust Technologies.

Introduction
Machine Learning (ML) is closely related to computational statistics which focuses on prediction-making through the use of computers. ML is a modern approach to an old problem:  predictive inference. It makes an inference from “feature” space to “outcome/target” space. In order to work properly, an ML algorithm has to discover and model hidden relationships between the feature space and the outcome space and create links between the two. Doing so requires overcoming barriers such as feature noise (randomness of features due to unexplained mechanisms).

In this article we argue that “Emergence” is also a barrier for predictive inference. Emergence is a phenomenon through which a completely new entity arises (emerges) from interactions among elementary entities such that the emerged entity exhibits properties the elementary entities do not exhibit. We present the idea that success of machine learning, and predictive inference in general, can be adversely affected by the phenomena of emergence. We argue that this phenomena might be partially responsible for unsuccessful use of current ML algorithms in some situations such as stock markets. .... " 

How Will People Interact with Machines

I see my former collaborators at IFTF have been working on this problem:

Forecasting How Humans Will Interact with Machines by 2030
By: Chris Preimesberger | July 12, 2017

The Dell-IFTF report forecasts that emerging technologies, supported by massive advancements in software, big data and processing power, will reshape lives and that society will enter a new phase in its relationship with machines. .... "

Sunday, July 16, 2017

Developing and Marketing Deep Learning

In Zdnet:

Automating automation: a framework for developing and marketing deep learning models 

Are you sold on the benefits of adding automation to your stack, but put off by the high entry barrier to this game? The NeoPulse Framework promises to ease the burden of developing Deep Learning models by introducing a number of interesting concepts.  .... "      By George Anadiotis

Assistant Mission Creep

When I read recently that a virtual assistant had called 911 in the US to report a crime in progress, my immediate reaction was:  No that will not work, for a number of reasons. Technical and regulatory. And that was confirmed soon after, it did not happen.  It was misreported.  But as AI's and their best known consumer examples, virtual assistants, continue to improve. our expectations will expand, leading to unexpected outcomes.  Will have to consider those circumstances and risk.  Nicely posed in Wired: 

“ ... Cyberservants will exhibit mission creep over time. They'll take on more and more functions. And they'll habituate us to become increasingly comfortable with always-on environments listening to our intimate spaces,” says Evan Selinger, a philosopher at the Rochester Institute of Technology, who focuses on how technology invades life.

SAVE's Reidenberg agrees, but thinks it’s inevitable that AIs will be given more power to intrude when necessary.“I don’t think we can avoid this. This is where it is going to go. It is really about us adapting to that,” he says.

Service Bot Examples

Systems that do sales bot interactions.  In cnbc:

" .... Here's how it works: When a company signs up with Conversica, they get to pick the name, gender and title of their new assistant. As leads come in, the AI assistant gets in touch with them through email or text message. If a lead is interested, the AI assistant routes the communication to a real-life member of the sales team to close the deal.

One advantage over humans is the AI isn't put off by unanswered emails — it doesn't mind being ignored or forget to follow up, so it can be programmed to be more persistent, emailing weeks after the initial contact. .... " 

Imagine a Future of Infinite Computing Power

Quite a way to go, but following how assistants can, learn, gather information, analyze and deliver.     I think its less about the speed of hardware and software, and more about how we model intelligent memory, data assets and interaction.

Amazon Imagines a Future of Infinite Computing Power
When David Limp thinks about the future of Alexa, the AI assistant he oversees at Amazon, he imagines a world not unlike Star Trek—a future in which you could be anywhere, asking anything, and an ambient computer would be there to fulfill your every need.

“Imagine a world in the not-so-distant future where you could have infinite computing power and infinite storage,” Limp said today at WIRED’s 2017 Business Conference in New York. “If you take off the constrains of servers and building up infrastructure, what could you do?”  ..... "

Saturday, July 15, 2017

Wal-Mart IOT Patent for Replenishment

Noted this before,  worth taking another look.  Note the implication of inclusion within the product.  Via CBInsights: 

Walmart’s IoT Patent Application Takes Aim At Amazon Dash

" ... The system is reminiscent of Amazon Dash — the connected buttons offered by Amazon that let users quickly re-order products. Launched over two years ago, Amazon Dash buttons now cover over 300 products. However, as we’ll describe below, Walmart’s system would require even less effort than Amazon’s. While Dash buttons still require users to press a physical button separate from the product (easy though that may be), Walmart aims to integrate IoT into the products themselves for automatic re-ordering with no user input at all. ... " 

Kasparov on Intelligent Machines

Kasparov talks from a unique perspective about machines and their intelligent use.

Don't fear intelligent machines. Work with them  Garry Kasparov TED Talk.

We must face our fears if we want to get the most out of technology -- and we must conquer those fears if we want to get the best out of humanity, says Garry Kasparov. One of the greatest chess players in history, Kasparov lost a memorable match to IBM supercomputer Deep Blue in 1997. Now he shares his vision for a future where intelligent machines help us turn our grandest dreams into reality.... " 

Whiskers as Sensors

Tactile sensors, like the idea of using new kinds of sensors.  Imagine the increased number of data points that could be gathered and fed to deep learning techniques.   Added to visual sensory input.

Want a Robot that can really feel?  Give it Whiskers.   By Matt Simon in Wired
" ... Whiskers are all the rage in nature, so why not give them to robots? Mechanical engineer Mitra Hartmann of Northwestern University is doing just that. In a new paper published in the journal Soft Robotics, Hartmann and her team detail how they’ve pulled one step closer to a rat-like machine that can feel an object and pinpoint it in 3-D space. Meaning robots of all kinds could soon get a powerful new sense. ... " 

How Will GE Adapt to Change?

Will be interesting to follow. They impressed me as a talented group, but also lumbering about as a big company without paying enough attention to good standards.  Will their Predix system take them in the right direction? In Knowledge@Wharton.

Friday, July 14, 2017

Thinking Avatar Dreams

Reimagining the Avatar Dream, illustrationHad never specifically heard of the term avatar dream.  Its not in the Wikipedia.   I could imagine a definition.  As we drift into AI, its like the carpenter or crafts person identifying strongly with their  tools.  But now taking that much further.  So can we be anything we want to be?   Computational surrogates for ourselves?  Models of our brand equities?   Have done that.   Very smart bots?   The Communications of the ACM spends some time working with it in their current issue.

Virtual Identity technologies and more .....   Video and more.

Computer science has long been intertwined with society's technological dreams. The dream of automated homes relates to ubiquitous computing, just as the dream of sentient machines relates to artificial intelligence (AI). Another of society's dreams could be called the "Avatar Dream," a culturally shared vision of a future in which, through the computer, people can become whomever or whatever we want to be. ....

Defining the Avatar Dream. The Avatar Dream has two elements. One is technical, enabling users to control a virtual surrogate for themselves in a virtual world. These computational surrogate selves are often computer-generated images (CGI) but can range from text descriptions in games or social media to virtual representations that engage all the senses in futuristic virtual reality environments. The second is experiential, enabling users of these virtual surrogate selves to have experiences beyond those they encounter in the physical world, ranging from having new abilities to better understanding the experiences of others (such as of another gender or even another type of creature). .... " 

Explanation Leading to Trust of Computers

Learning to explain.   Ultimately a very important topic.  Leading to trust.

AI Research Seeks to Grow Trust between Humans and Computers  By BU Today 

Researchers at Boston University and the University of California, Berkeley received a four-year, $7.55-million grant from the U.S. Defense Advanced Research Projects Agency to find new ways of getting inside the "mind" of artificial intelligence (AI), creating a translation tool that explains its decision-making process to human users.

Getting feedback on why an AI device makes a particular decision could help improve its accuracy by giving opportunities for humans to offer small corrections.

In addition, it could increase the trust that humans put into a machine, making it a better collaborator on complex jobs.

All of the primary neural network's processing is devoted to solving its task. "That's why we want to use a second neural network that has access to that machinery and input data, and can learn to translate all that into a textual version that humans can understand," says BU professor Kate Saenko. .... " 

Vision, Real and Virtual

There have been many years of research about how vision works, but not enough about how this effects virtual and augmented reality.    Ultimately it drives perception.  An extended look at the topic:

 Perception is Reality -- and Virtual Reality  By Rebecca Guenard
Virtual reality is here. In fact, it’s everywhere. Beyond video games, it is helping therapists to treat PTSD, allowing medical students to do virtual operations, and letting engineers test vehicle safety before the car is built. 

But in order to provide a genuine experience through virtual reality (VR), manufacturers must first understand how vision works in the real world. And understanding a complex system like vision requires advances on multiple fronts. At Penn Arts and Sciences, psychologists and physicists are looking more closely at the basics of how we see. ... "

AI Sleep Technologies

This covers a number of approaches now being examined to provide 'personalized optimization' for sleep related problems.  Nicely laid out.  Very similar to other health related pattern recognition problems.  InVenturebeat.

Augmented Reality Try-it-on App

So here is, at least in theory, the ideal augmented reality App.  We tested a number of such related methods in the past with limited success.  Except in its novelty.  But will it succeed because of fewer returns?  See especially the attached expert discussion.  In Retailwire:

Will an AR try-on app cut down on online clothing returns?     by Matthew Stern

Part of the reason returns have become such a significant part of the online apparel shopping experience is because there’s no great way to get a feel for how clothing fits without first trying it on. But an augmented reality solution that’s been gaining popularity abroad has gotten some funding, and made some partnerships, that might make it easier for U.S. shoppers to make the right choice the first time around.

The Metail app allows users to virtually try on clothing by superimposing digitized versions of garments onto a virtual “body” within the app, according to Business Insider. The 3-D modeled version of the clothing is created taking into account features such as fabric texture while the simulated body created in the app factors in size and weight. The U.K.-based startup received a round of funding led by TAL, a Hong Kong-based apparel manufacturer that purports to make one in every six dress shirts sold in the U.S. Metail hopes to use this as the foundation for a U.S. expansion.  ... " 

Mapping Critical Knowledge

Always liked the idea of using a map, especially for group interactions.  Does require paying attention to maintaining the knowledge involved.  Here in Knowledge@Wharton:

Mapping Critical Knowledge for Digital Transformation.  Podcast and text:  " ... Strategic knowledge mapping helps to uncover these critical knowledge assets, providing the context for discovering the most promising digitalization strategies. It helps to identify those knowledge assets that digital transformation can leverage, or illuminates gaps in an organization’s knowledge network.    .... " 

Quantum Machine Learning

If this says what I think it does, it could rapidly advance machine learning in a quantum computing world.     Will this kind of thing bring true machine intelligence closer much more quickly?   Technical.

Physicists uncover similarities between classical and quantum machine learning  by Lisa Zyg

Read more at:
(Phys.org)—Physicists have found that the structure of certain types of quantum learning algorithms is very similar to their classical counterparts—a finding that will help scientists further develop the quantum versions. Classical machine learning algorithms are currently used for performing complex computational tasks, such as pattern recognition or classification in large amounts of data, and constitute a crucial part of many modern technologies. The aim of quantum learning algorithms is to bring these features into scenarios where information is in a fully quantum form. ... "

Thursday, July 13, 2017

Data Science Workflow Pipelines

So rarely well thought out in the enterprise, a high level view.    Well presented.  Via O'Reilly and in Medium:

How to build a data science pipeline  by Balázs Kégl 
Start with y. Concentrate on formalizing the predictive problem, building the workflow, and turning it into production rather than optimizing your predictive model. Once the former is done, the latter is easy.  .... " . Link to online course.  

Measuring Omnichannel in Retail

With some good expert discussion:

Are retailers measuring omnichannel all wrong?     by Nikki Baird

Through a special arrangement, what follows is an excerpt of an article from Retail Paradox, RSR Research’s weekly analysis on emerging issues facing retailers, presented here for discussion.

There is a point where customer engagement leads to more sales. But there is also a point where it leads to diminishing returns. That’s the beauty of the sales per engagement-minute spent metric.

This metric enables a breakdown to identify causal factors. If an employee is spending a lot of time with customers but not selling much, they need some sales training help. If a store is getting a lot of traffic and employees are spending less and less time with customers, they need sales help. If a store is spending more and more time fulfilling orders instead of helping the customers who walk through the door, they need more fulfillment staff. Where are the engagement minutes coming from, and where are they delivering value vs. detracting from value? .... " 

Microsoft Pushes AI Research

Microsoft creates an AI research lab to challenge Google and DeepMind
 by Darrell Etherington (@etherington)

Microsoft has created a new research lab with a focus on developing general-purpose artificial intelligence technology, the company revealed today. The lab will be located at Microsoft’s Redmond HQ, and will include a team of more than 100 scientists working on AI, from areas including natural language processing, learning and perception systems. ... " 

Banning Recordings

I used to work gathering data about retail practices, and it was drilled into us that we needed to get permission from a store manager to do picture or video recordings in a store.     As a customer I also gathered data from a nearby retailer with novel engagement ideas, but they had a sign on the door saying picture taking was not allowed.  We obeyed that for many years.   Owners can control their spaces.  The sign disappeared.

Course the world has changed, we all carry sophisticated video and still image cameras in our phones. Every day we see things being recorded and shared within minutes.  So has the standard changed?  Is the assumption now that all recording is implicitly allowed,  at least in places where we do not expect privacy? What are the implications for prohibiting recording by a customer?  Is it literally 'destroying evidence', as a commentor suggests.   And it is it still always bad PR?

HBS discusses the topic of recording bans in general.

Decisions and Process

In McKinsey:

" ... Untangling your organization’s decision making
By Aaron De Smet, Gerald Lackey, and Leigh M. Weiss

Any organization can improve the speed and quality of its decisions by paying more attention to what it’s deciding. ..." 

" ... In today’s world, there is the added complexity that many decisions (or parts of them) can be “delegated” to smart algorithms enabled by artificial intelligence. Identifying the parts of your decisions that can be entrusted to intelligent machines will speed up decisions and create greater consistency and transparency, but it requires setting clear thresholds for when those systems should escalate to a person, as well as being clear with people about how to leverage the tools effectively. .... " 

Wednesday, July 12, 2017

Google's MultiModel for Multiple Tasks

New to me, examining.  Premise sounds very useful.  Or is it carrying the neural model architecture too far?   Defining a useful task as?  The architecture does make you think.

Google Presents MultiModel: A Neural Network Capable of Learning Multiple Tasks in Multiple Domains    intro by Roland Meertens  In InfoQ

Google created an algorithm that can take inputs from multiple modalities and can generate output in multiple modalities.

Currently, many machine learning applications focus on one domain. Machine translation builds models for one language pair, and image recognition algorithms only perform one task (e.g. describe an image, say what category an image belongs to, or find objects in the image). However, our brain performs very well on all tasks and transfers knowledge from one domain to another. The brain can even transfer what we learned by listening to other domains: things we see or read.

Google built a model that performs 8 tasks in multiple domains: speech recognition, image classification and captioning, sentence parsing, and back and forth translation of English-German and English-French. It consists of an encoder, decoder, and an "input-output mixer" that feeds previous input and output to the decoder. In the image below, each "petal" indicates a modality (either sound, text, or an image). The network can learn every task with one of these inputs and output modalities. ... "

KDNuggets Observer Paper

The latest headline paper from KDNuggets, a source that has been around for a long time, and always very useful.  Good place to quickly scan Analytics and Machine Learning news and resources.    Worth following.   I won't continue to mention each of these here, but will retweet them on my twitter stream: @FranzD.     Follow there for this and more, updated daily.

The KDnuggets Observer   #KDn
What's Interesting in Data Science and Machine Learning  ....  " 

Amazon Launches 'Echo Squad' Help for Alexa Installs and Beyond

Had only a minor problem installing Alexa,  Had somewhat more trouble with Google Home, which could have stymied a non tech user.  In both cases dial-in help was helpful.  Though depending on the 'smarthome 'architecture', there might be some complete show stoppers.   The typical user will need help to install.

Will Amazon’s answer to the ‘Geek Squad’ help put Alexa in more homes?
by Matthew Stern in Retailwire.

There’s a learning curve for setting up, troubleshooting and using voice assistant technologies like Alexa. Amazon.com is now addressing that with a new in-home installation and repair service that’s reminiscent of the Best Buy Geek Squad.

Amazon has been hiring skilled professionals over the past few months to install and repair in-home gadgets, according to Recode. The company sees offering professional smart home setup as a way to reduce the number of returns of Alexa-enabled devices. The service, which is already live in seven markets, comes directly from Amazon and is not related to the website’s marketplace for third-party services.

The section of Amazon’s website that describes the service gives users an opportunity to book a “smart home consultation for Alexa” and set up an in-home visit from an expert. It states that experts will install and customize the smart home setup complete with configuring settings and connecting devices to Alexa. The expert will also train users on how to control wired devices via Alexa and give the customer the opportunity to test new wired devices in-home.   ....  " 

More Uses of Digital Twins

Datascience Central article on Digital Twins.  I was introduced to the idea at GE, and then later through interaction with their analytics methods.  This example is interesting because it addresses other kinds of applications, beyond the often hardware orientation of a GE.   Further, it can to mind when reading this, a 'twin', could entirely be a simulation or emulation,  of a new design or proposal.

iPhone Security

Don't usually follow this kind of news, but this seems very serious.  Apple has this reputation for good security, which this seems to erode considerably, even on current and up to date devices.  Contact Apple and complain, else a stolen iPhone might be readily compromised.  In Computerworld, by Darlene Storm:

Easy way to bypass passcode lock screens on iPhones, iPads running iOS 10
The vulnerability allowing anyone to bypass the passcode lock screen still exists in iOS 10.3.2 and the 10.3.3 beta .... 

Why People Can't Write

Steven Pinker writes about writing, have heard this point of his before.  Good thoughts.  Particularly important in technical topics.  Where communications have to be made to non technical management.

The Single Reason Why People Can't Write, According to a Harvard Psychologist
This common affliction is behind so much unclear and confusing writing in the world today.  By Glenn Leibowitz in Inc.

" ... These are questions Harvard psychologist Steven Pinker asks in his book, The Sense of Style: The Thinking Person's Guide to Writing in the 21st Century. They're questions I've often encountered --and attempted to tackle-- throughout my career as a business writer and editor. Whenever I see writing that is loaded with jargon, clichés, technical terms, and abbreviations, two questions come immediately to mind. First, what is the writer trying to say, exactly? And second, how can the writer convey her ideas more clearly, without having to lean on language that confuses the reader?

For Pinker, the root cause of so much bad writing is what he calls "the Curse of Knowledge", which he defines as "a difficulty in imagining what it is like for someone else not to know something that you know. The curse of knowledge is the single best explanation I know of why good people write bad prose."   ...  " 

Linkedin Mentor Matching

Been looking for how Linkedin, after acquisition, will be planning to innovate with its gigantic, novel and ubiquitous database.   Can they use it to help assign mentors?  By Lydia Dishman in Fast Company:

LinkedIn Is Testing A New Feature That Matches You With A Mentor

"... LinkedIn aims to tap the entire user community to make matches between mentees and leaders with less commitment than traditional mentorship relationships. ... 

 .... Today, LinkedIn is testing out a new free service for members that will match them with other professionals who can give them that much needed career advice. “Think of it as a new form of mentorship that’s virtual, lightweight, and that fits today’s changing workplace,” says Suzi Owens, group manager of Consumer Products, Corporate Communications  at LinkedIn.  ... " 

Tuesday, July 11, 2017

AI Methods in Enterprise Software

OK , but with still a narrow view of AI, by these definitions we were using analytics/AI in the enterprise in the 80s.  Still some good recent examples and a good direction to make these new business process and operations oriented methods more often used.

AI Makes Inroads into Enterprise Software
By Alex Woodie  in  Datanami

Enterprise software is often maligned as a legacy holdover from a previous age, a low-growth market dominated by stodgy software companies out to milk maintenance streams from hapless victims. But two giants of enterprise software, OpenText and Infor, today showed that even giants can move nimbly when it comes to putting artificial intelligence into the hands of its customers.

Infor‘s big announcement today was Coleman, its new AI platform for its cloud-based enterprise software suites. The ERP giant says Coleman’s will help Infor clients by recommending actions to take and automating repetitive tasks currently performed by human employees.

“Coleman is our cloud-based AI platform with a collection of industry-specific AI services that harnesses our vast data set and industry knowledge,” Infor co-president Duncan Angove in a keynote address at today’s Inforum conference in New York City. “Coleman brings the power of artificial intelligence and machine learning to the enterprise and it helps you seize the moment by making the best decision every time.” .... " 

Adam Optimization for Machine Learning

Been enjoying some of the writing of Jason Brownlee, who below introduces us to Adam Optimization, new to me.    He has compiled some of his other writing at the link, worth examining and buying.  Have done that.  As in all methods, optimizing their application is useful.

Gentle Introduction to the Adam Optimization Algorithm for Deep Learning
by Jason Brownlee

The choice of optimization algorithm for your deep learning model can mean the difference between good results in minutes, hours, and days.

The Adam optimization algorithm is an extension to stochastic gradient descent that has recently seen broader adoption for deep learning applications in computer vision and natural language processing.

In this post, you will get a gentle introduction to the Adam optimization algorithm for use in deep learning.

After reading this post, you will know:

What the Adam algorithm is and some benefits of using the method to optimize your models.

How the Adam algorithm works and how it is different from the related methods of AdaGrad and RMSProp.  How the Adam algorithm can be configured and commonly used configuration parameters. ...  " 

Morphological Analysis Update

Tom Ritchey sends this along, see my previous notes on this under the tag GMA.   Note that Morphology means structure ....  and just the structure of a problem, rather than including numerical specifications.

Dear Network,

General Morphological Analysis: Modelling, Forecasting, Innovation
Guest Editors: Tom Ritchey & Tomasz Arciszewski

We are happy to announce a Special Issue of Technological Forecasting and Social Change featuring General Morphological Analysis (GMA). The articles appearing in this issue are based both on papers presented at The Second International Symposium on General Morphological Analysis (ISGMA 2016), held in Bilbao 11-12 June, and on additional contributions provided by selected GMA practitioners globally. The articles for the Special Issue are now in press and will be available on-line shortly. The "hard copy" version will be available later this year.

Table of Contents
1. Introduction and Historical background (Editors)
2. General Morphological Analysis as a Basic Scientific Modelling Method
3. A Collaborative Process Model and Web-based Software-Support for GMA
4. Scenario Development with General Morphological Analysis
5. On a Morphology of Contact Scenario Space
6. Morphological Analysis in Inventive Engineering
7. Morphology of Conceptual Building Design
8. From Morphological Analysis to Optimizing Complex Industrial Operation Scenarios
9. Linking Fields with GMA: Sustainability, Companies, People and Operational Research 
10. Investigating Traffic Congestion: Targeting Technological and Social Interdependencies
11. An Informal Survey on the Application of Morphological Analysis in the Private Sector 
Kind regards,

  Tom

Algorithms Playing the Marketing Game

Gartner on Algorithms and games in Marketing.

So its an AI, but ultimately it is playing against and with a context of customers and clients and competitors.   An AI implies you can find  a best solution in a given context.   A Game implies there are others playing too (and there are).   So thinking of content as an asset should ultimately include that.  ....

WorkFlow for AI

In O'Reilly:

Artificial intelligence in the software engineering workflow
The workflow of the AI researcher has been quite different from the workflow of the software developer. Peter Norvig explores how the two can come together. ...  "

Monday, July 10, 2017

How do People and AI Interact?

 Addressing one of the most fundamental questions:  How do people and AI work together?   There are so many components, and they are likely to be continually changing as we progress.   We examined, and continue to examine modes like interactive conversations, Attentive systems, Intelligent micro services,  Task analysis,  Process design, Visual interactions and more.  I much like the emphases described below.

Where are we going from here?   How will humans and machines need to adjust to make these interactions efficient?   Where do we start to make success likely?   Following the below, and look forward to the published tools promised.   Join us.

Google announces: PAIR: the People + AI Research Initiative
Written by  
Martin Wattenberg, Senior Staff Research Scientist, Google Brain
Fernanda Viégas, Senior Staff Research Scientist, Google Brain

The past few years have seen rapid advances in machine learning, with dramatic improvements in technical performance—from more accurate speech recognition, to better image search, to improved translations. But we believe AI can go much further—and be more useful to all of us—if we build systems with people in mind at the start of the process.

Today we’re announcing the People + AI Research initiative (PAIR) which brings together researchers across Google to study and redesign the ways people interact with AI systems. The goal of PAIR is to focus on the "human side" of AI: the relationship between users and technology, the new applications it enables, and how to make it broadly inclusive. The goal isn’t just to publish research; we’re also releasing open source tools for researchers and other experts to use.

PAIR's research is divided into three areas, based on different user needs:

Engineers and researchers: AI is built by people. How might we make it easier for engineers to build and understand machine learning systems? What educational materials and practical tools do they need?

Domain experts: How can AI aid and augment professionals in their work? How might we support doctors, technicians, designers, farmers, and musicians as they increasingly use AI?

Everyday users: How might we ensure machine learning is inclusive, so everyone can benefit from breakthroughs in AI? Can design thinking open up entirely new AI applications? Can we democratize the technology behind AI? .... " 

Google Releases Massive Visual Databases

To train and use machine learning methods, you need lots of data to start with.  Very significant amounts. Here Google releases much training data.  In the work I have done in this space, you almost never have enough.  And in real contexts, you need more over time to detect drift from your solutions.  Initially via DSC.   See their post for more on data resources and methods.

Google releases massive visual databases for machine learning  in Engadget by Richard Lawler.

Millions of images and YouTube videos, linked and tagged to teach computers what a spoon is.
It seems like we hear about a new breakthrough using machine learning nearly every day, but it's not easy. In order to fine-tune algorithms that recognize and predict patterns in data, you need to feed them massive amounts of already-tagged information to test and learn from. For researchers, that's where two recently-released archives from Google will come in. Joining other high-quality datasets, Open Images and YouTube8-M provide millions of annotated links for researchers to train their processes on.   .... " 

Booz Allen Makes Sailfish Free for Government and Academia

Worth a look, impressed by their online presence.  Giving this a try.

Booz Allen Makes its Analytics Platform Free for Government (and Academia)
by: Morgan Lynch

Booz Allen Hamilton made its analytics platform free June 29 for the government, military, and academic sectors.

The Treasury Department recently launched beta.usaspending.gov, giving Federal agencies and citizens insight into how taxpayer money is being spent. The platform, Sailfish, would help government agencies make sense of the spending data. Booz Allen helped begin this governmentwide reform using open source code and agile design.

“We had a set of systems and processes that I think have been broken for a while,” said Bryce Pippert, vice president at Booz Allen Hamilton, at the DATA Act Summit on June 29. “We lost the ability to have the big picture, connect the link between those things. The DATA Act was pushed forward to solve that challenge.”

Now that the Federal spending data is open to the public, researchers have to make sense of what it all means. The department of Treasury continues to enhance the open data website to make it user friendly.

“This is a big, new, robust data set that is connected and is fulfilling the vision for the DATA Act,” Pippert said.

Booz Allen Hamilton wants its platform to be an easy solution for the government to comprehend this data.  .... "

Brands According to Byron Sharp

World According to Byron Sharp.  Former correspondent.   Read by many in the CPG space.   In Adage: " ... In the years since Byron Sharp published  'How Brands Grow,' his unorthodox theories have taken root with major marketers and begun changing how they buy media. Among the new rules: Loyalty is a crock and broad reach can be more productive than surgical targeting. ... " 

" ... Byron Sharp would like you to know that almost everything you've learned about marketing is wrong.

Here's the real truth, according to the University of South Australia marketing professor, whose 2010 book has recently grown surprisingly influential among top brands: 20% of your brand's biggest buyers don't really account for 80% of sales. These "loyal" consumers aren't really that loyal. The best way to grow is to get more sales from people who care even less about your brand than the loyalists.  ... " 

Strategies for Digital Groceries

Some thoughtful views on the topic.

A Strategist’s Guide to the Digital Grocery
As Amazon and Walmart disrupt the grocery industry, smart retailers can compete by plying their wares in a technologically enabled way.

by Tim Laseter, Steffen Lauster, and Nick Hodson  In Strategy + Business

Sometimes industries hit a tipping point. It looks like nothing is happening for a long time, while forces of change build up, and then everything shifts at once. That is happening in the grocery industry now. A shift is taking place in the most fundamental form of shopping: consumers’ purchases of food products and other basic household goods. The most visible signal of this shift occurred in June, when Amazon announced its acquisition of the Whole Foods grocery chain, but the basic trajectory was already long under way.

Central to this shift is the new digital grocery platform rapidly emerging in industrialized countries. In the U.S., Walmart and Amazon are each leveraging their scale advantages, but under different paradigms. Walmart has achieved unparalleled success with a “push” model that ships full truckloads of goods to more than 4,000 Walmart stores across the country, offering “everyday low prices,” as the slogan puts it, without sales or promotions. Amazon operates a similarly powerful supply chain but with a “pull” model that responds directly to customer demand by shipping packages rather than pallets of goods. The rest of the nation’s supermarkets and grocers must find a way to compete in this environment. Other industrialized countries have similar dynamics: traditional grocery competitors are squeezed between a “push” leader like Walmart and a digital native “pull” player like Amazon or Alibaba.  .... " 

Tracking Humans in 3D with Off-the-shelf Webcams

We experimented with this idea using security cameras, but not in 3D.

Tracking Humans in 3D With Off-the-Shelf Webcams 
Saarland University

Researchers at the Max Planck Institute for Computer Science in Germany have developed VNect, a system for capturing human movements digitally in three dimensions (3D) in real time using a single video camera. The system also can estimate the 3D pose of a person acting in a pre-recorded video, offering new applications in character control, virtual reality, and ubiquitous motion capture with smartphones. VNect is based on a convolutional neural network that can calculate the 3D pose of a person from the two-dimensional information of the video streams. The new system avoids wasting computations on image regions that do not contain a person. The neural network was trained using tens of thousands of annotated images during the machine learning process. Although the accuracy of the pose estimation is slightly lower than the accuracy obtained with multi-camera or marker-based pose estimation, the researchers believe the technology will further mature and be able to handle increasingly more complex scenes.  .... " 

Sunday, July 09, 2017

Exploration of Business Apps for VR

Virtual Reality: Exploring The Business Applications

Charles Deering in VRFocus gives an overview on the story of VR so far - and the story yet to come. ... 

Interesting, but the focus is still narrow.

Polinode and NodeXL

Via Andrew Pitts and  Marc Smith (SMRF, NodeXL)  Podcast:

Polinode and the Social Media Research Foundation recently announced an integration between NodeXL Pro and Polinode’s Networks product. Polinode Networks is a tool for visualising and analysing network data in a web-browser. NodeXL Pro is an Microsoft Office Excel add-in that performs advanced social data acquisition .... "

Sideways Elevators

Recall this being discussed for use in the design of large hotels and in aggregated cityscapes.    More than a quantum escalator.  Does it have a real future?  At the link, fascinating pictures of how it works.  See also my posts on modeling elevators.

The Sideways Eleveator of the Future is Here, and It's Wild
by Elizabeth Stinson in Wired.

PEOPLE LAUGHED WHEN ThyssenKrupp, a company synonymous with elevators, announced it was developing one that goes every which way. Who'd ever heard of such a thing? Everyone knows elevators go just two directions: Up and down. Some took to calling it the Wonkavator, after Willy Wonka’s wacky lift that goes sideways, slantways, and longways.

"There were some doubts," company CEO Patrick Bass says with just a bit of understatement. Put aside your doubts. After three years of work, the company is testing the Multi in a German tower and finalizing the safety certification. This crazy contraption zooms up, down, left, right, and diagonally. ThyssenKrupp just sold the first Multi to a residential building under construction in Berlin, and expects to sell them to other developers soon.  ... "

Google Lens as Augmented Reality

We are soon to see a number of applications that will use our advanced smartphones as a form of 'augmented reality'.    I saw the 'Google Lens' demonstrated this year which allows you point your phone at a flower, and the system will identify it. Imagine this kind of recognition and classification system working with many things in personal and business life.  A sort of search based on visual images coming from a smartphone.   Like barcode scan, but based on images.  Apple seems to have related methods planned for its AR offerings.   Probably where we will see AR much sooner than as a general interface.  Much more at link below:

Google Lens offers a snapshot of the future for augmented reality and AI  by Adam Sinicki

"... What is Google Lens?
Google Lens is a tool that effectively brings search into the real world. The idea is simple: you point your phone at something around you that you want more information on and Lens will provide that information.

So yes, it sounds a lot like Google Goggles. It might also sound familiar to anyone who has tried out Bixby on their Galaxy S8s. Only it’s, you know, much better than either of those things. In fact, it is supposedly so good, that it can now identify the species of any flower you point it at. It can also do OCR tricks (Optical Character Recognition – i.e. reading) and a whole lot besides. ... " 

Randomizing Routine

I can imagine a number of managers I have known who would have reacted to this as a person admitting they did not enough to do.   But OK,  might be worth a try, if you can obey an odd process ....

This Google Engineer Built an App to Randomize His Life. Amazing Things Happened    Routine? What's routine?       By Jessica Stillman

Saturday, July 08, 2017

Can In-Store Experiences Save Retail?

I notice this article mentions my favorite experience store, Jungle Jims.   Have covered from time to time here.   Even they have been doing less of that, it seems, in recent years.  More live action is needed.   Is it enough?   Does it compete against price, selection and fast delivery?

Can In-store ‘Experiences’ Save Retail?  In Knowledge@Wharton

At the Rebecca Minkoff store in New York’s Soho, “smart” digital walls and mirrors let you tap for a different clothing size or color — as well as a free glass of champagne. At the Warby Parker store near Hollywood, you and your friends can create your own 15-second shareable video in a “green room” furnished with props and backdrops. At Jungle Jim’s International Market near Cincinnati, bizarre animatronic figures entertain you while you browse unusual gourmet foods. And at Pirch’s luxury home appliance stores, you can try out the appliances before buying them, including shower heads (just bring your own swimsuit.)

Other brick-and-mortar retailers offer cooking classes, celebrity appearances, personalized makeup advice, wine tastings: the list goes on and on. Much of this activity, of course, is intended to combat the juggernaut of online ordering via Amazon and other sites.

“The customer can get all of their clothing without ever leaving their bed,” says Stacey Bendet, CEO and creative director of designer clothing company Alice + Olivia. “So the experience in-store has to become more VIP, more exciting.”

But are these in-store “experiences” worth the effort and money that retailers are pouring into them? .... " 

Adobe Voice Analytics

Intriguing play, not where I would expect Adobe.  We do need better understanding of voice interaction, especially in noisy environments.  And understanding who the actual audience and context of these systems are, especially in business.

New Adobe voice analytics will capture data from all the major virtual assistants

Speech inputs from Amazon Alexa, Google Assistant, Cortana, Siri and Bixby can be combined with other data sets for deeper audience insights.    by Greg Sterling   ....  "

More explanation in PCMag.

Microsoft Discusses Their Mixed Reality Focus

Interesting to watch,  because Microsoft crafts or influences much of the worlds personal computer user experience.  So will user experience become VR or mixed reality?   These technologies give great demonstrations, but how much value do they give to the experience, unless you are gaming or working with a hands-free application of some sort?  Competition with phone based systems?   Links to the conference presentations.

Microsoft Discuss Their Mixed Reality Future

Watch their Taipei conference session in full.
By Kevin Eva   

Earlier this week we brought you news from Taipei where Microsoft were taking part in a ‘WinHEC’ – a Windows Hardware Development Conference, where a number of representatives went through the current crop of mixed reality (MR) related Microsoft products, demonstrated problems and solutions that the technology can solve and explained what the way the technology works. All with an overview of Microsoft’s current plans with regard to MR. ... "

Untangling Decision Making

Untangling your organization’s decision making
Any organization can improve the speed and quality of its decisions by paying more attention to what it’s deciding.   By Aaron De Smet, Gerald Lackey, and Leigh M. Weiss  by McKinsey

Any organization can improve the speed and quality of its decisions by paying more attention to what it’s deciding.

It’s the best and worst of times for decision makers. Swelling stockpiles of data, advanced analytics, and intelligent algorithms are providing organizations with powerful new inputs and methods for making all manner of decisions. Corporate leaders also are much more aware today than they were 20 years ago of the cognitive biases—anchoring, loss aversion, confirmation bias, and many more—that undermine decision making without our knowing it. Some have already created formal processes—checklists, devil’s advocates, competing analytic teams, and the like—to shake up the debate and create healthier decision-making dynamics.

Now for the bad news. In many large global companies, growing organizational complexity, anchored in strong product, functional, and regional axes, has clouded accountabilities. That means leaders are less able to delegate decisions cleanly, and the number of decision makers has risen. The reduced cost of communications brought on by the digital age has compounded matters by bringing more people into the flow via email, Slack, and internal knowledge-sharing platforms, without clarifying decision-making authority. The result is too many meetings and email threads with too little high-quality dialogue as executives ricochet between boredom and disengagement, paralysis, and anxiety (Exhibit 1). All this is a recipe for poor decisions: 72 percent of senior-executive respondents to a McKinsey survey said they thought bad strategic decisions either were about as frequent as good ones or were the prevailing norm in their organization. ... " 

Visions of the Future of Work

Reviewing:

The Commission on Work, Workers, and Technology
We’re imagining scenarios for the future of work

Findings of Shift: The Commission on Work, Workers, and Technology
What do a hundred American leaders find when they compare different possibilities for the effect of technology on work’s future?

Full text of Shift Commission findings on the future of work in the U.S.
For those who prefer to read the whole thing in all its detail, we’re including it here 
 (34 page report)

Via O'Reilly:

Four visions of the future of work

New America and Bloomberg have come together to convene Shift: The Commission on Work, Workers, and Technology, with the goal of analyzing theories of the future of work. In a new report drawn from discussions with leaders in technology, business, policy, and culture as well as those whose livelihoods are already being affected by automation, the commission outlines four possible future economies: some with more work and some with less, some focused on task-based work and some oriented around traditional jobs.  ....  Fulltext PDF. 

Friday, July 07, 2017

Tracking Ad Effects Offline

Snap Seeking offline ad success measures:   In Adage: 

" ... Snap Inc. has acquired Placed, a startup that measures the offline success of digital advertising campaigns, for about $125 million, according to people familiar with the matter.

Including stock payouts, the full value of the deal could exceed $200 million, said two other people with knowledge of the deal, who asked not to be named because the terms aren't being disclosed. Snap confirmed the acquisition on Monday, while declining to comment on the price.

The acquisition will help Snap expand its efforts to show that ads on its photo and video-sharing app Snapchat are driving users to stores. Placed, based in Seattle, will continue to operate independently, with David Shim, the startup's chief executive officer, reporting to Snap's chief strategy officer, Imran Khan. .... " 

Charting Change

Last year taught a course at Columbia on change management.  To my students who are still following, here is a nice piece out of Innovation Excellence on charting change.  Some very useful points included.

AI Revolution in Science

Well done and non-technical explanation of this in Science Mag.   Not about the automation of these capabilities, but the techniques that can be used to work with the vast amounts of data being gathered. Most every segment of science and industry is examining these methods to simplify their data.

The AI revolution in science   By Tim Appenzeller 

Big data has met its match. In field after field, the ability to collect data has exploded—in biology, with its burgeoning databases of genomes and proteins; in astronomy, with the petabytes flowing from sky surveys; in social science, tapping millions of posts and tweets that ricochet around the internet. The flood of data can overwhelm human insight and analysis, but the computing advances that helped deliver it have also conjured powerful new tools for making sense of it all. 

AI is changing how we do science. 

In a revolution that extends across much of science, researchers are unleashing artificial intelligence (AI), often in the form of artificial neural networks, on the data torrents. Unlike earlier attempts at AI, such “deep learning” systems don’t need to be programmed with a human expert’s knowledge. Instead, they learn on their own, often from large training data sets, until they can see patterns and spot anomalies in data sets that are far larger and messier than human beings can cope with. .... "

Driverless AI

The term was new to me, but not the concept.   Makes sense,  if it is really AI then it should manage itself.  Easier/cheaper than having room fulls of scientists building systems.   But here also aspects like testing, maintaining and connecting to corporate systems creates most of the difficulty.   How close is this?

H2O.ai’s Driverless AI automates machine learning for businesses
 Driverless AI is the latest product from H2O.ai aimed at lowering the barrier to making data science work in a corporate context. The tool assists non-technical employees with preparing data, calibrating parameters and determining the optimal algorithms for tackling specific ...   In Techcrunch.

(Update):And further, in Datanami:
H2O.ai Boasts New AI Product Like ‘Kaggle Grandmaster in a Box’  by Alex Woodie

Apples Talking in the IOT

Uday Prabhu, General Manager, Internet of Things
Robert Bosch Engineering & Business Solutions Pvt Ltd writes: 

Talking Apples! The Conversation with Things  in Linkedin. 

Here he talks an internet of vegetable things in the grocery store.   We will likely see many mundane products added to the IoT,  but the mechanics of plugging in an apple will make this later rather than sooner.  But this a story of how Bosch and others are thinking.   Expect much more.  Liked it.

Intelligent Video Analytics

Recently asked to look at this… for applications beyond security:

What it can do for your business
IBM Intelligent Video Analytics helps security and public safety organizations develop comprehensive security, intelligence and investigative capabilities using video. You can use advanced search, redaction and facial recognition analytics to find relevant images and critical information across multiple video files from multiple camera types. Selected live-streaming cameras plus pre-recorded video ingestion from both fixed cameras and cameras in motion are supported. Augment staff and improve camera investment ROI by extracting information from captured video to uncover insights and patterns.  … "

Thursday, July 06, 2017

Intel Chief Talks Augmented vs Artificial

Always interesting to hear opinions on rapidly emerging technologies from the big players.   Ultimately they must make the investments that need to be made.

Artificial or Augmented Intelligence: Talks with Intel’s Chief Data Scientist,  Bob Rogers
Interview by Ronald van Loon  In DSC. .... " 

Chasing Focus

Your Brain Can Only Take So Much Focus     By Srini Pillay

The ability to focus is an important driver of excellence. Focused techniques such as to-do lists, timetables, and calendar reminders all help people to stay on task. Few would argue with that, and even if they did, there is evidence to support the idea that resisting distraction and staying present have benefits: practicing mindfulness for 10 minutes a day, for example, can enhance leadership effectiveness by helping you become more able to regulate your emotions and make sense of past experiences.  Yet as helpful as focus can be, there’s also a downside to focus as it is commonly viewed. .... " 

Disney and Kid-Robot Interactions

Interesting thought.  Applications to robot-people interactions?     Storytelling mentioned.   Robots as androids, or more generally as devices? Do COPPA,  and other regulations,  apply the same way with robots?  What does natural mean here?  Engaging, friendly, teaching?

Disney experiments look to make kid-robot interactions more natural    by Devin Coldewey

Sooner or later, our children will be raised by robots, so it’s natural that Disney, purveyor of both robots and child-related goods, would want to get ahead of that trend. A trio of studies from its Research division aim at understanding and improving how kids converse with and otherwise interact with robots and other reasonably smart machines.  .... " 

How we Draw

Fascinating piece on how different cultures draw, using the circle as an example.   A piece of metadata to understand and classify people and cultures?   Note Google's recent drawing system experiment: AutoDraw, linked to below.  Also their online game:  Quick Draw.  In Quartz:

How do you draw a circle? We analyzed 100,000 drawings to show how culture shapes our instincts Written by:   Thu-Huong Ha,  Nikhil Sonnad   @thuhuongha  ... " 

Effectiveness of Retail Loyalty Programs

Good piece, and especially discussion on use and effectiveness of retail loyalty programs.

How can retailers make loyalty programs more effective?     by Tom Ryan
According to the 2017 COLLOQUY Loyalty Census Report, growth in memberships in customer loyalty programs slowed to 15 percent during the census period versus 26 percent in 2015.

“The membership growth slowdown signals the U.S. loyalty market is maturing and retailers need to up their game on how to attract and retain members within their loyalty programs,” said Melissa Fruend, LoyaltyOne partner and COLLOQUY Census author, in a statement. .... "