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Saturday, July 22, 2017

Design for the Users, not a Mythical Generation

The other day the question came up about how we should carefully design our user interface to match the generation of the current predicted user base.  Were they Gen X or Gen Y?   But have always felt this was a lame way to design. Consider the real needs first, and perhaps you won't need to fine tune the design at all.  Jimmie Lenz considers this:

Guest Opinion: Know Your Customer? Are You Sure? by Dr. Jimmie Lenz
July 21, 2017 The Financial Revolutionist  .... " 

Using Social Media to Find Top Customers

In Knowedge@Wharton.  

Influencing the Influencers: Using Social Media to Find Top Customers


Wharton's Gad Allon discusses his research on using social media data to identify a company's top customers.

Podcast/Text

Social media offers an almost endless stream of data for businesses to collect on their customers. But what good is data without a smart way to apply it? The latest research from Gad Allon, Wharton professor of operations, information and decisions, offers a lifeline for firms drowning in the deep waters of social networks. Allon and his team devised an analytics model that can help businesses identify high-value customers. The paper, “Managing Service Systems in the Presence of Social Networks,” was co-authored with Washington University professor Dennis J. Zhang. He talked with Knowledge@Wharton about the process. .... " 

Disney Tests Facial Expression Analysis for Movies

Back to using facial expression detection and coding.  Not new, Something we also experimented with, in lab settings, but here with new data science doing the analysis.  Some details in Phys.org.

Disney Uses Neural Net Technology to see if you Love its Movies like you Should  By Mark Coppock

Disney really wants to know if you like its movies. The entertainment company conducts copious research to answer that question, and in fact, it has its own division, Disney Research, that’s focused on figuring out ways to make you love its movies even more. Now, the company is applying neural net technology to determining if audiences are reacting as they should to Disney’s latest films.

The information comes via Phys.org,  https://phys.org/news/2017-07-neural-nets-audience-reactions-movies.html  which took a look at some recent work by Disney Research to apply deep learning concepts to figure out how audiences are reacting based on their facial expressions. So far, the methods are having better results than the organization’s usual techniques.

Researchers are using what they’re calling “factorized variational autoencoders,” or FVAEs, to use an audience member’s early facial expressions to predict how that person will react to a movie in its entirety. The data was gathered by using infrared cameras that monitored audience faces during 150 showings of a total of nine movies including Big Hero 6, The Jungle Book, and Star Wars: The Force Awakens. .... 

Origami Robots Moving Without Battery Power

Following uses of origami folding methods for simplifying robotics.   See much written before on this space regarding practical Origami, at the tag below.

Harvard's Folding Origami Robot can move without Requiring Battery Power     By Luke Dormehl   ....

Aspen Ideas on Future of Intelligence

The Future of Intelligence   Aspen Ideas Festival

Bill Gates portends doomsday is coming. Stephen Hawking says we should prepare for our robot overlords to take their thrones. But is the future as glaring as Hal’s red eye? Or is it more complicated than that? What does a future powered by algorithms and big intelligence mean for our lives? What are game-changing developments made possible by AI? What promises do these technologies hold? With responsible R&D, might we be looking at an application that can better the world? What are specific instances of AI’s promising power?

Speakers:
Gary Marcus, Tim O'Reilly, Michael Chui, Erik Schatzker ..... " 

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?”  ..... "