AI Adoption in Retail

General general overview, not enough direct examples. 

Forecasting AI Adoption in Retail: A Mixed Bag  By Alex Woodie in Datanami

You don’t have to look far to see the impact that artificial intelligence is having on the world around us. Across multiple facets of work and play, we’re surrounded by smart devices and applications that are strangely prescient at anticipating our wants and needs. But one industry where AI adoption has been surprisingly slow is retail — particularly around demand forecasting, where AI’s potential has scarcely been scratched.

A 2018 report from the McKinsey Global Institute concluded that AI has the potential to boost global GDP by 16% by 2030. In dollar terms, that’s a gain of $13 trillion, which is a huge number, to be sure. Companies today are scrambling to get their piece of that AI bounty – and at the same time, to avoid being devoured as the AI party unfolds.

Large retailers certainly are aware of what’s at stake. Retail is one of the largest sectors of the U.S. economy, accounting for $2.6 trillion in sales in 2016, which is nearly 15% of the country’s output. The retail sector employs nearly 29 million people directly, and supports another 13 million jobs indirectly.

Clearly, retailers are aware of AI, and have moved to adopt AI to improve their business processes. While they’ve had success in some aspects of the retail equation, few of them have figured out how to use AI to address some of more complex aspects of their businesses, such as demand forecasting and merchandise planning.

That’s the opinion of Nikki Baird, who’s the vice president of retail innovation at Aptos, a developer of enterprise software solutions for retailers. Baird has dozens of years of experience in the retail world, and has seen AI’s roll-out go surprisingly slow.

“You hear about all kinds of evolutionarily algorithms and genetic algorithms and all of the more hard-core future of AI kinds of stuff, and none of that is currently getting applied within the retail space,” Baird tells Datanami. “There’s even a question about whether some of the neural net kinds of algorithms and AI actually are applicable in the retail space.”  .... "

Wal-Mart Vudu Competes with Shoppable Ads

Had actually forgotten about the Wal-Mart streaming service Vudu.  Interesting experiment to understand what evokes interaction and get related data.  Buying directly from integrated product in video has long been a holy grail, is that what this is?  Also competes with Youtube.

Will shoppable ads help Walmart’s Vudu compete with Amazon and Netflix? in Retailwire  by George Anderson with further expert opinion.

Walmart’s Vudu video streaming service is following Amazon and Netflix in creating original programming to attract viewers. Unlike its rivals, however, Walmart will continue to offer Vudu as a free, ad-supported service rather than seeking subscription income. Management believes it can do this because of “new advertising technology” that will enable viewers of the shows to buy the products they see on the screen.

Bloomberg reports that Walmart has already lined up “tens of millions of dollars in upfront advertising” as brands look to cash in on the shoppable content opportunity.   .... " 

Improving Wifi Security

Wifi is so commonly used, it needs to be secure in its basic defaul tuse.

Enterprise Wi-Fi: We Need Devices That Are Secure by Default
By Alberto Bartoli, Eric Medvet, Andrea De Lorenzo, Fabiano Tarlao , Communications of the ACM, May 2019, Vol. 62 No. 5, Pages 33-35
10.1145/3319912  

Would you trust security technology that makes it possible (that is, quite likely) to steal the single sign-on enterprise credentials of any specific person in your enterprise by merely walking within 30 meters from that person? The attacker does not need to do any visible activity that might raise suspicions: a 50-euros device in a bag and a few seconds of physical proximity is all that is needed. Active cooperation of the target is not required and Internet connectivity is not required either. Thus, the attack may occur anywhere and the target would not notice anything. The attacker could steal the single sign-on credentials of a large fraction of people of your enterprise that happen to pass within 30 meters from the attacker. Perhaps at the office lunchroom, near a mass-transportation hub, or anywhere outside of the enterprise.  .... (Abstract)

Heat Transfer in Boiling Water

Had a  minor involvement, as a lab assistant, in studies about the transfer of heat,  at first in boiling water, and later applied to stellar atmospheres.  Its more complex than you think.

Getting to the bottom of the “boiling crisis”

New understanding of heat transfer in boiling water could lead to efficiency improvements in power plants.  David L. Chandler | MIT News Office

The simple act of boiling water is one of humankind’s oldest inventions, and still central to many of today’s technologies, from coffee makers to nuclear power plants. Yet this seemingly simple process has complexities that have long defied full understanding.

Now, researchers at MIT have found a way to analyze one of the thorniest problems facing heat exchangers and other technologies in which boiling water plays a central role: how to predict, and prevent, a dangerous and potentially catastrophic event called a boiling crisis. This is the point when so many bubbles form on a hot surface that they coalesce into a continuous sheet of vapor that blocks any further heat transfer from the surface to the water. ... "

Machine Behavior

We behave, machines exhibit behavior.   Both can be trained with examples and practice and direction.   Both have been collaborating for some time.   But only recently have machines been given the opportunity to take small amounts of autonomous opportunity.  With our direction.   But that direction is still largely imprecise once we get beyond fundamental but basic arithmetic, statistics  and logic.

A new paper frames the emerging interdisciplinary field of machine behavior   by Janine Liberty

As our interaction with “thinking” technology rapidly increases, a group led by researchers at the MIT Media Lab are calling for a new field of research—machine behavior—which would take the study of artificial intelligence well beyond computer science and engineering into biology, economics, psychology, and other behavioral and social sciences.

“We need more open, trustworthy, reliable investigation into the impact intelligent machines are having on society, and so research needs to incorporate expertise and knowledge from beyond the fields that have traditionally studied it,” said Iyad Rahwan, who leads the Scalable Cooperation group at the Media Lab.

Rahwan, Manuel Cebrian and Nick Obradovich, along with other scientists from the Media Lab convened colleagues at the Max Planck Institutes, Stanford University, the University of California San Diego, and other educational institutions as well as from Google, Facebook, and Microsoft, to publish a paper in Nature making a case for a wide-ranging scientific research agenda aimed at understanding the behavior of artificial intelligence systems.

“We’re seeing the rise of machines with agency, machines that are actors making decisions and taking actions autonomously,” Rahwan said. “This calls for a new field of scientific study that looks at them not solely as products of engineering and computer science but additionally as a new class of actors with their own behavioral patterns and ecology.” .... '

Related Nature article.

US to Use AI to Scan Passengers Faces

This is inevitable, and will sooner be in most non US airports.  Every CCTV camera will soon be online with face recognition.

U.S. Airports Will Use AI To Scan 97% Of Passengers' Faces Within 4 Years    in Forbes   By Nicole Martin

U.S. Customs and Border Protection (CBP) plans to expand its Biometric Exit program to cover 97% of outbound air passengers within four years, according to a recent U.S. Department of Homeland Security report. While the current imaging system can only look up photos based on flight manifests, a new Artificial Intelligence (AI) system will use an algorithm to scan the faces of those boarding international flights and compare them to millions of photos on file to find a match. The images in the database are pulled from visa and passport applications; if the image is not recognized, it can be looked up manually. The AI system has been implemented in 15 U.S. airports, and tested on more than 15,000 flights; it was able to identify more than 7,000 travelers who overstayed their visas. ... '

How Python is used at Netflix

An instructive piece in the Netflix tech blog.   Netflix has to reliably delivery large amounts of data, personalized to millions of consumers, reliably and securely.    While gathering information to tailor their sales and marketing to these same consumers.  See how they use Python and development support architectures.  Considerable piece, mostly technical.

Python at Netflix
 Netflix Technology Blog   By Pythonistas at Netflix, coordinated by Amjith Ramanujam and edited by Ellen Livengood

As many of us prepare to go to PyCon, we wanted to share a sampling of how Python is used at Netflix. We use Python through the full content lifecycle, from deciding which content to fund all the way to operating the CDN that serves the final video to 148 million members. We use and contribute to many open-source Python packages, some of which are mentioned below. If any of this interests you, check out the jobs site or find us at PyCon. We have donated a few Netflix Originals posters to the PyLadies Auction and look forward to seeing you all there.  ... " 

Feedback loops for Neural Nets

I remember something similar posed in the 90s, tat feedback could converge to better results. Or at least produce some better next step position.   Don't recall any work suggest progress back then.  Now its here?  Lots more detail at the link.

For Better Deep Neural Network Vision, just add Feedback (loops)  in MIT News
The DiCarlo lab finds that a recurrent architecture helps both artificial intelligence and our brains to better identify objects.

Sabbi Lall | McGovern Institute for Brain Research 

Your ability to recognize objects is remarkable. If you see a cup under unusual lighting or from unexpected directions, there’s a good chance that your brain will still compute that it is a cup. Such precise object recognition is one holy grail for artificial intelligence developers, such as those improving self-driving car navigation.

While modeling primate object recognition in the visual cortex has revolutionized artificial visual recognition systems, current deep learning systems are simplified, and fail to recognize some objects that are child’s play for primates such as humans.

In findings published in Nature Neuroscience, McGovern Institute investigator James DiCarlo and colleagues have found evidence that feedback improves recognition of hard-to-recognize objects in the primate brain, and that adding feedback circuitry also improves the performance of artificial neural network systems used for vision applications. ... " 

More on Dicarlo Lab at MIT, with more on the above and related activity

Strategy for Voice Technology

HBR on the topic.  Very good overview, some good stats referred to.   I think most consumer facing companies are thinking about voice, but a specific strategy is harder.    Recall the emergence of the smartphone and tablets, and strategies for those took some time.

Your Company Needs a Strategy for Voice Technology    By Bradley Metrock in the HBR

Voice assistants, smart speakers, and all manner of voice-first technology have enjoyed remarkable growth and adoption. Voicebot.AI reports that the smart speaker install base within the U.S. grew 40% from 2018 to 2019, now exceeding 66 million units. International markets have grown even more dramatically — Dutch adoption of smart speakers exploded from 0% to 5% in just four and a half months, for example, with no sign of slowing down.

How humans and machines will work together.
Voice-first doesn’t mean voice-only, though. Smart speakers with screens — generally referred to as “smart displays” — are surging in popularity as well. In January of 2018, there were 1.3 million smart display owners in the U.S., and by the end of the year, that number had risen to 8.7 million — an increase of 558%. Products like Amazon’s Echo Show and the Google Home Hub upped the ante on expectations for voice-first   .... " 

An Initial Look at Wal-Mart's Future Store

FastCompany takes an initial look.  Different it seems, from what we did in our future store.  Less direct research and more, promotion of themselves as a forward looking company.   Good piece, expect to see more on the topic.

Walmart’s AI-powered store of the future is nothing like Amazon Go
There are cameras. There is AI. And the similarities end there.    By MarkWilson

When Amazon launched its first Go store in 2018, the public lined up around the block to see the future of retail: a new experience where you could walk in, grab something off the shelf, and walk out. Sure, there were cameras on the ceiling and AI on computers tracking silently from above, but the promise was convenience through automation–maybe not The Jetsons, but a better 7/11 for certain.

Now Walmart has shared its version of the future of brick-and-mortar retail, the Intelligent Retail Lab, or IRL for short. Unlike Go, it doesn’t feature any futuristic user experience. There’s no automated checkout or similar whiz-bang head turner that people will Instagram about. Instead, IRL can track Walmart’s inventory in real time with unprecedented efficiency, making sure every item on every shelf is always in stock. .... " 

See also in the Chicago Tribune another report on this.

Emotions in Group Photos

More than just spotting but also getting the emotion of multiple people.     Could lead to the further understanding  of crowds in contect.

Spotting Faces in the Crowd
from University of Delaware   By Julie Stewart

University of Delaware (UD) researchers are using machine learning and deep learning with neural networks to identify the emotions of people in group photos, with the goal of automatically classifying images uploaded to websites. UD's Xin Guo said, "When people search, they would see the images they are looking for because the algorithm would run and label whether people are happy or not. It could be used to analyze the emotions of a group of people pictured at a protest, a party, a wedding, or a meeting, for example. This technology could also be developed to determine what kind of event a given image shows." Guo's team scored first place in the Group-level Emotion Recognition sub-challenge of the 6th Emotion Recognition in the Wild (EmotiW 2018) Challenge at the ACM International Conference on Multimodal Interaction 2018 in October, with an algorithm that accurately classified people in a set of images as happy, neutral, or negative.  .... '

Cheaper Robot Arms for Human Tasks

New ideas in lower cost robotics.

Blue Is a New Low-Cost Force-Controlled Robot Arm from UC Berkeley
Designed to safely perform human-scale tasks, Blue will cost $5k and help accelerate research towards useful home robots    By Evan Ackerman

Blue is a new robot arm designed to be useful and accessible to researchers working on AI and applied manipulation for human environments.

A Robot Arm That’s Safe, Low Cost, and Can Replicate Itself
Robots are well-known for being very good at some very specific things. They’re often defined by words like “precision” and “repeatability” and “speed,” because if you want a robot to be uniquely useful, it’s usually going to have to leverage one or more of those characteristics in a way that makes it better at some specific task than humans are. Robots have been doing this for decades, typically in places like industrial settings, but things are starting to change, and roboticists are beginning to look towards other applications in more unconstrained, dynamic environments, like non-industrial settings.

Such environments (our homes, for example) are the kinds of places that we really, really want robots to be useful in. We want them doing our chores so that we don’t have to, ideally without causing catastrophic damage or injury at the same time. And tasks like these need a much different set of capabilities—in order to do things that humans do in places that humans are, “speed” and “repeatability” and all that are far less important than compliance and the ability to make the most of clever, adaptable software. The upshot of all this is that the advances in artificial intelligence over the past few years have resulted in researchers developing software for (and on) robots that are over engineered for many of the tasks that we want them to do, more expensive than they need to be, and probably not as safe as we’d want. ... "

Training Data for Autonomous Driving

Getting, saving, and usefully tagging data and metadata for key purposes is a powerful idea.

Training Data for Autonomous Driving   By Karlsruhe Institute of Technology 

Using processed images, algorithms learn to recognize the real environment for autonomous driving.
Philip Kessler at the Karlsruhe Institute of Technology (KIT) in Germany has launched understand.ai, a startup that improves and accelerates the labeling of image elements for autonomous driving algorithms.

These labels, also called annotations, must agree with the real environment with pixel accuracy. The better the quality of the processed image data, the better the algorithm will be at using the data for training.

Traditionally, objects in images are labeled manually by human staff, but the process is troublesome and time-consuming; artificial intelligence makes the labeling process up to 10 times quicker and more precise.

Said Kessler, "As training images cannot be supplied for all situations, such as accidents, we now also offer simulations based on real data."    ....

From Karlsruhe Institute of Technology (More  article and data at the link)

Autonomous Vegetable Weeding

Another approach that will increase agricultural food production.

FarmWise turns to Roush to build autonomous vegetable weeders   By Matt Burns  @mjburnsy

FarmWise wants robots to do the dirty part of farming: weeding. With that thought, the San Francisco-based startup enlisted the help of Michigan-based manufacturing and automotive company Roush to build prototypes of the self-driving robots. An early prototype is pictured above.

Financial details of the collaboration were not released.

The idea is these autonomous weeders will replace herbicides and save the grower on labor. By using high-precision weeding, the robotic farm hands can increase the yield of the crops by working day and night to remove unwanted plants and weeds. After all, herbicides are in part because weeding is a terrible job.  .... " 

Nanoparticles for Drug Delivery

Yet another direction for pharmaceutical delivery is proposed

Nanoparticles take a fantastic, magnetic voyage
Tiny robots powered by magnetic fields could help drug-delivery nanoparticles reach their targets.

Anne Trafton | MIT News Office 

MIT engineers have designed tiny robots that can help drug-delivery nanoparticles push their way out of the bloodstream and into a tumor or another disease site. Like crafts in “Fantastic Voyage” — a 1960s science fiction film in which a submarine crew shrinks in size and roams a body to repair damaged cells — the robots swim through the bloodstream, creating a current that drags nanoparticles along with them.

The magnetic microrobots, inspired by bacterial propulsion, could help to overcome one of the biggest obstacles to delivering drugs with nanoparticles: getting the particles to exit blood vessels and accumulate in the right place.

“When you put nanomaterials in the bloodstream and target them to diseased tissue, the biggest barrier to that kind of payload getting into the tissue is the lining of the blood vessel,” says Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, a member of MIT’s Koch Institute for Integrative Cancer Research and its Institute for Medical Engineering and Science, and the senior author of the study. .... " 

Quantum Hype and Skepticism

Short piece looks at both sides.

Quantum Hype and Quantum Skepticism   By Moshe Y. Vardi 
Communications of the ACM, May 2019, Vol. 62 No. 5, Page 7
10.1145/3322092

" .... The popular media regularly reports breathlessly on quantum computing: "Quantum computing will break your encryption in a few years"; "Why quantum's computing time is now"; and "The computer that could rule the world." Yet the physical realization of quantum computing has been a hard slog. A Canadian company, D-Wave Systems, has claimed to be the world's first company to sell computers that exploit quantum effects in their operation. But the D-Wave machine is far from being a general quantum computer, and several researchers disagree with D-Wave's claims.

In fact, several quantum-computing researchers have expressed skepticism regarding the physical realizability of the quantum-computing dream.a Quantum skeptics agree that quantum computation does offer an exponential advantage of classical computation in theory, but they argue it is not physically possible to build scalable quantum computers. Gil Kalai is one of the most prominent quantum skeptics. All physical systems are noisy, he argues,b and qubits kept in highly sensitive superpositions will inevitably be corrupted by any interaction with the outside world. In contrast, quantum-skepticism skeptics, such as Scott Aaronson, view the realizability of quantum computing as an outstanding question in physics,c and regard the skeptical view as representing an implausible revolution in physics. .... " 

RSR Research on Clouds

Brought to my attention:

The Candid Voice in Retail Technology: Objective Insights, Pragmatic Advice
RSR is the candid voice in retail technology

Since our founding in 2007, we have combined our extensive retail industry backgrounds and on-going retailer survey data to bring objective and pragmatic insights to the entire retail community. ...... 

Cloud Computing In Retail: Pushing The ‘Go Faster’ Button
Retailers have definitely warmed up to the cloud.

The data from the survey that formed the basis of this benchmark report clearly shows us that. But the data also showed us some very surprising reasons WHY retailers are moving to the cloud, what their expectations are, and who, within the enterprise, are the biggest proponents of cloud.

It also gives us real insights into the business partners retailers hope will support their efforts.

The answers surprised us. We think they’ll surprise you too. Download this report to find out why. ... " 

The Risks of Artificial Intelligence

Having now been involved in many applications using AI oriented methods,  it was rare that there were not risks in their application.  We saw them all.  From legal exposure to regulatory penalties to the loss of public trust to shifts in context that made the results wrong.    Because cognitive AI is always to some degree utilizing something that is like human decision making, or mimics cognitive facilities, we always included risk analyses.   Depending on the nature of the problem, these could be extensive in place testing,  direct comparisons to other methods,  exposure to teams of users or consumers, or formal risk models.

As the article suggests, the risks need to be confronted.   This is rarely done for many kinds of analytics.    Because the intent is often to use these methods predictively, the assumption is that they will enable, enhance or even replace human decision making, so you have to understand the implications of that.  If your system is working with human resources, you need to further consider risk of how those teams will work.    The human, machine and combined elements of such an intelligence will behave in different, sometimes unexpected ways.

McKinsey provides a good article:

Confronting the risks of artificial intelligence  in McKinsey Quarterly
 By Benjamin Cheatham, Kia Javanmardian, and Hamid Samandari

With great power comes great responsibility. Organizations can mitigate the risks of applying artificial intelligence and advanced analytics by embracing three principles.

Artificial intelligence (AI) is proving to be a double-edged sword. While this can be said of most new technologies, both sides of the AI blade are far sharper, and neither is well understood.

Consider first the positive. These technologies are starting to improve our lives in myriad ways, from simplifying our shopping to enhancing our healthcare experiences. Their value to businesses also has become undeniable: nearly 80 percent of executives at companies that are deploying AI recently told us that they’re already seeing moderate value from it. Although the widespread use of AI in business is still in its infancy and questions remain open about the pace of progress, as well as the possibility of achieving the holy grail of “general intelligence,” the potential is enormous. McKinsey Global Institute research suggests that by 2030, AI could deliver additional global economic output of $13 trillion per year.

Yet even as AI generates consumer benefits and business value, it is also giving rise to a host of unwanted, and sometimes serious, consequences. And while we’re focusing on AI in this article, these knock-on effects (and the ways to prevent or mitigate them) apply equally to all advanced analytics. The most visible ones, which include privacy violations, discrimination, accidents, and manipulation of political systems, are more than enough to prompt caution. More concerning still are the consequences not yet known or experienced. Disastrous repercussions—including the loss of human life, if an AI medical algorithm goes wrong, or the compromise of national security, if an adversary feeds disinformation to a military AI system—are possible, and so are significant challenges for organizations, from reputational damage and revenue losses to regulatory backlash, criminal investigation, and diminished public trust.   .... "

Scientific American on Deep Learning

Scientific American does a good job of providing a good,  intuitive and largely non-technical view of the math and applications of deep learning.   Good for use with management with a reasonable amount of patience.   I would not call it deep or complete, but enough for a useful intro.

A Deep Dive into Deep Learning
A personal journey to understand what lies beneath the startling powers of advanced neural networks
By Peter Bruce on April 10, 2019 in Sciam

On Wednesday, March 27, the 2018 Turing Award in computing was given to Yoshua Bengio, Geoffrey Hinton and Yann LeCun for their work on deep learning. Deep learning by complex neural networks lies behind the applications that are finally bringing artificial intelligence out of the realm of science fiction into reality. Voice recognition allows you to talk to your robot devices. Image recognition is the key to self-driving cars. But what, exactly, is deep learning?

Dozens of articles tell you that it’s a complex, multilayered neural network. But they don’t really shed much light on deep learning’s seemingly magical powers. For example, to explain how it can recognize faces out of a matrix of pixel values (i.e., an image).

As a data science educator, for years I have been seeking a clear and intuitive explanation of this transformative core of deep learning—the ability of the neural net to “discover” what machine learning specialists call “higher level features.” Older statistical modeling and machine learning algorithms, including neural nets, worked with databases where those features with predictive power already exist. In predicting possible bank failure, for example, we would guess that certain financial ratios (return on assets, return on equity, etc.) might have predictive value. In predicting insurance fraud, we might guess that policy age would be predictive.  .... " 

Automating Science Writing

How different is this from script writing mentioned previously?      Accurate summarization of text is another example of a challenge for AI type methods, similar in goal to finding a pattern in complex data.

Can Science Writing Be Automated? 
MIT News   by David L. Chandler

Massachusetts Institute of Technology researchers have developed artificial intelligence (AI) that can read scientific papers and produce a plain-English summary in a sentence or two. The team's neural network is based on vectors rotating in a multidimensional space, rather than on multiplication of matrices. The rotational unit of memory (RUM) system basically represents each word in the text by a vector in multidimensional space, with each subsequent word skewing this vector in some direction, represented by a theoretical space that can ultimately have thousands of dimensions. At the conclusion, the final vector or set of vectors is translated back into its corresponding string of words. Testing suggested RUM could be useful with natural language processing, so the researchers fed scientific papers through the network, generating a much more readable summary than a conventional neural network yielded  .... "

McKinsey on Automating Logistics

Good description of the space and the large opportunities.

Automation in Logistics: Big Opportunity, Bigger uncertainty     Via McKinsey by Ashutosh Dekhne, Greg Hastings, John Murnane, and Florian Neuhaus

As e-commerce volumes soar, many logistics and parcel companies hope that automation is the answer. But as this second article in our series on disruption explains, things are not so simple.

The history of logistics is also a history of automation, from the steam engine to the forklift to today’s robotic pickers and packers. So today’s fevered interest in new machinery, after a lull of several years, has plenty of precedent. Many trends are thrusting automation toward the top of the logistics CEO’s agenda, not least these three: a growing shortage of labor, an explosion in demand from online retailers, and some intriguing technical advances. Put it all together, and McKinsey Global Institute estimates that the transportation-and-warehousing industry has the third-highest automation potential of any sector1 . Contract logistics and parcel companies (which, for sake of convenience, we will call simply “logistics companies”) particularly stand to benefit. (Automation is also on the table at other transport companies, such as trucking companies and port operators. See sidebar “Automating freight flows: Changes for every sector”.)

Yet for all the excitement, most logistics companies have not yet taken the plunge. For every force pushing companies to automate, countervailing factors suggest they should go slowly. We see five reasons companies are hesitating: the unusual competitive dynamics of e-commerce, a lack of clarity about which technologies will triumph, problems obtaining the new gizmos, uncertainties arising from shippers’ new omnichannel-distribution schemes, and an asymmetry between the length of contracts with shippers and the much-longer lifetimes of automation equipment and distribution centers.

This is the second in a series of five articles on disruption in transport and logistics. In the first, we examined the implications of autonomous trucks. Automation is no less potent a force. In this article, we will review the reasons automation is coming to the fore, examine the five factors that are hindering investment, and lay out strategies that can position contract logistics companies to prepare for an uncertain future. .... " 

BPA, RPA or DPA? Automating Process

Interesting piece, with criticism of robotic process automation.   It has somewhat focused application I agree.   Contrast of options is interesting.  I like the term DPA only because it does not include the confusing 'robotic' aspect.  Software is key, and it has to replicate the specific outcome of details involved.    I am always also concerned about maintaining the process context. 

It’s all about people: Dispelling the five myths of process automation By Jason Bloomberg in SiliconAngle

In a memorable scene from the movie “The Founder” about the origin of McDonald’s, the McDonald brothers plot the layout of their restaurant in a life-sized mockup drawn in chalk on a parking lot.

This example of process optimization was certainly “lean,” but it involved no software whatsoever. Today, in contrast, optimizing business processes almost always means automating them – at least in part. And when we say automation, we mean with software.

Just what software, however, is an open question, as today’s frothy software marketplace has spawned several contenders. From the business process automation or BPA of the last decade to today’s robotic process automation or RPA to the latest entrant, digital process automation or DPA, information technology decision makers have a plethora of options to choose from.

Be warned: This is a clear-cut case of caveat emptor. With the help of the big IT analyst firms, the providers in these overlapping categories have stirred up massive confusion. Let’s clear up the biggest misconceptions.

Myth No. 1: Digital process automation is more ‘digital’ than business process automation: .... '

MuseNet Writes Music

OpenAI does some things with generating music.     Back to the meaning of creativity, will we ultimately be able to tell?  I listened to a number of their examples, impressive.

MuseNet
We’ve created Musenet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of MIDI files. MuseNet uses the same general-purpose unsupervised technology as GPT-2, a large-scale transformer model trained to predict the next token in a sequence, whether audio or text.  ... " 

Workplace Surveillance

Agree that doing this more universally will much chage the workplace.   Indications are that Amazon has closed the loop for warehouse workers, but the the idea is likely implemented most everywhere.    Will this then be posted publically in a game format to induce competition?

AI Surveillance Is Coming: How will it Change Your Workplace? in InformationWeek

There isn't much you can do to stop AI surveillance's encroachment on your life, but you can equip yourself with better understanding and more appropriate skills and behaviors.
Your employer probably has some kind of monitoring system in place. They might have stationary cameras in your store, monitoring software to track your online activity, or some other system designed to keep an automated eye on things.

But we’re about to see the rise of new, high-tech systems that take surveillance to a new level of awareness and sophistication — artificial intelligence driven surveillance — and it has the potential to completely change the workplace as we know it.  .... "

Machines Firing Humans

First I had heard of such a thing, certainly the PR would be bad enough to add a human in the loop.  Somewhat skeptical, but perhaps a warning of the future.

Amazon's system for tracking its warehouse workers can automatically fire them by Charlotte Jee, Technology review.

A world where people are monitored and supervised by machines isn’t confined to the realms of sci-fi. It’s here now.

Tough conditions: There have been many reports over recent years about unpleasant conditions workers face at Amazon warehouses. Employees are under pressure to pack hundreds of boxes per hour, and face being fired if they aren’t fast enough. .... "

Supply Chain Integrity Month

Had not heard this was a month, note here from Recorded Future, but the topic is very important.    Some good free resources at the link on related threat intelligence. 

April Is National Supply Chain Integrity Month — Reduce Third-Party Risk With Threat Intelligence By Zane Pokorny on April 26, 2019

The National Counterintelligence and Security Center (NCSC) declared April to be “National Supply Chain Integrity Month,” highlighting the growing cybersecurity risks coming from third parties in our increasingly connected world.

“Foreign intelligence entities and other adversaries are increasingly exploiting supply chain vulnerabilities to steal America’s intellectual property, corrupt our software, and surveil our critical infrastructure,” said NCSC director William R. Evanina.

“Bypassing our security perimeters, they’re infiltrating our trusted suppliers to target equipment, systems, and information used every day by the government, businesses, and individuals. The cost to our nation comes not only in lost U.S. innovation, jobs, and economic advantage, but also in reduced U.S. military readiness.”

To help combat third-party risk, the NCSC has developed new resources that outline best practices and more.  .... "

Automating Ethics

Very good piece.   A difficult problem.Yes as get closer to embedding ethics in systems and machines,how do we address this?   By just warning the humans in the loop, or can we actually close the loop to include ethical reasoning?   As we progress, the reasoning has to occur more quickly.

Automating ethics
Machines will need to make ethical decisions, and we will be responsible for those decisions.

By Mike Loukides  in O'Reilly

We are surrounded by systems that make ethical decisions: systems approving loans, trading stocks, forwarding news articles, recommending jail sentences, and much more. They act for us or against us, but almost always without our consent or even our knowledge. In recent articles, I've suggested the ethics of artificial intelligence itself needs to be automated. But my suggestion ignores the reality that ethics has already been automated: merely claiming to make data-based recommendations without taking anything else into account is an ethical stance. We need to do better, and the only way to do better is to build ethics into those systems. This is a problematic and troubling position, but I don't see any alternative.

The problem with data ethics is scale. Scale brings a fundamental change to ethics, and not one that we're used to taking into account. That’s important, but it’s not the point I’m making here. The sheer number of decisions that need to be made means that we can’t expect humans to make those decisions.  ... "

Wal-Mart AI Store of the Future Opens to Public

Good to see this, and new competition with Amazon in brick and mortar.  Look forward to learning about other technical details.  How about their Fresh Block chain?  More for now at the link.

Walmart unveils an A.I.-powered store of the future, now open to the public   By Sarah Perez@sarahintampa in TechCrunch

Walmart this morning unveiled a new “store of the future” and test grounds for emerging technologies, including A.I.-enabled cameras and interactive displays. The store, a working concept called the Intelligent Retail Lab — or “IRL” for short — operates out of a Walmart Neighborhood Market in Levittown, New York.

The store is open to customers and is one of Walmart’s busiest Neighborhood Market stores containing over 30,000 items, the retailer says, which allows it to test out technology in a real world environment.

Similar to Amazon Go’s convenience stores, the store has a suite of cameras mounted in the ceiling. But unlike Amazon Go, which is a grab-and-go store with smaller square footage, Walmart’s IRL spans 50,000 square feet of retail space and is staffed by over 100 employees.

Plus, in Walmart’s case, these A.I.-powered cameras are not being used to determine what items customers are buying in order to automatically charge them. It still has traditional checkout stations. Instead, the cameras will monitor inventory levels to determine, for example, if staff needs to bring out more meat from the backroom refrigerators to restock the shelves, or if some fresh items have been sitting too long on the shelf and need to be pulled. ... " 

Wal-Mart's Food Safety Blockchain

For an upcoming talk, took a re-look at the Wal-Mart's food safety Blockchain effort.  Will be following up with more details. good simple example, as stated in a previous mention. Know more about tech details?  Pass them along.

Walmart is betting on the blockchain to improve food safety    By Ron Miller @ron_miller in TechCrunch    9/24/2018

Walmart has been working with IBM on a food safety blockchain solution and today it announced it’s requiring that all suppliers of leafy green vegetable for Sam’s and Walmart upload their data to the blockchain by September 2019 .

Most supply chains are bogged down in manual processes. This makes it difficult and time consuming to track down an issue should one like the E. coli romaine lettuce problem from last spring rear its head. By placing a supply chain on the blockchain, it makes the process more traceable, transparent and fully digital. Each node on the blockchain could represent an entity that has handled the food on the way to the store, making it much easier and faster to see if one of the affected farms sold infected supply to a particular location with much greater precision.

Walmart  has been working with IBM for over a year on using the blockchain to digitize the food supply chain process. In fact, supply chain is one of the premiere business use cases for blockchain (beyond digital currency). Walmart is using the IBM  Food Trust Solution, specifically developed for this use case.  .... " 

Where are my Robot Servants?

Note from 5 Years ago, note what has happened, and what has not.

So, Where Are My Robot Servants?  In IEEE Spectrum
Tomorrow’s robots will become true helpers and companions in people’s homes—and here’s what it will take to develop them

By Erico Guizzo  .... '

AI Sensor Environment Chip

More players in the stream for enabling analytics AI from sensor data.

AIStorm raises $13.2M for its analog data-reading sensor chips   By Mike Weatley

AIStorm, a maker of specialized computer processors for sensors that detect events or changes in their environments, is emerging from stealth mode with a $13.2 million early-stage round of funding.

The Series A round was led by Egis Technology Inc., a supplier of biometrics technology for handsets, gaming and advanced driver-assistance systems. Image sensor maker TowerJazz, food preparation equipment manufacturer Meyer Corp. and Linear Dimensions Semiconductor Inc., a maker of biometric authentication and digital health products, also participated in the round.

These are not your usual kind of investors for a technology-related startup, but their interest in AIStorm isn’t a surprise considering how useful the new computer chips could be to them.

AIStorm has built an “AI-in-Sensor” system-on-chip that enables faster processing of complex artificial intelligence problems at the very edge of the network. The chip is designed to be integrated within the sensors that are embedded into mobile devices, “internet of things” machinery and self-driving cars, processing data directly within them. .... "

Institutions that last Ten Thousand Years

We had early interaction with some of the founders of the Long Now Foundation, which was very thought provoking.   Here an interview with its Exec Director in the Edge:

How to Create an Institution That Lasts 10,000 Years
A Conversation with Alexander Rose

We’re also looking at the oldest living companies in the world, most of which are service-based. There are some family-run hotels and things like that, but also a huge amount in the food and beverage industry. Probably a third of the organizations or the companies over 500 or 1,000 years old are all in some way in wine, beer, or sake production. I was intrigued by that crossover.

What’s interesting is that humanity figured out how to ferment things about 10,000 years ago, which is exactly the time frame where people started creating cities and agriculture. It’s unclear if civilization started because we could ferment things, or we started fermenting things and therefore civilization started, but there’s clearly this intertwined link with fermenting beer, wine, and then much later spirits, and how that fits in with hospitality and places that people gather.

All of these things are right now just nascent bits and pieces of trying to figure out some of the ways in which organizations live for a very long time. While some of them, like being a family-run hotel, may not be very portable as an idea, some of them, like some of the natural strategies, we're just starting to understand how they can be of service to humanity. If we broaden the idea of service industry to our customer civilization, how can you make an institution whose customer is civilization and can last for a very long time?

ALEXANDER ROSE is the executive director of The Long Now Foundation, manager of the 10,000 Year Clock Project, and curator of the speaking series' at The Interval and The Battery SF.  ... " 

Autonomous in-Body Navigation

A considerable development.

A first in medical robotics: Autonomous navigation inside the body in TechExplore

Bioengineers at Boston Children's Hospital report the first demonstration of a robot able to navigate autonomously inside the body. In an animal model of cardiac valve repair, the team programmed a robotic catheter to find its way along the walls of a beating, blood-filled heart to a leaky valve—without a surgeon's guidance. They report their work today in Science Robotics.

Surgeons have used robots operated by joysticks for more than a decade, and teams have shown that tiny robots can be steered through the body by external forces such as magnetism. However, senior investigator Pierre Dupont, Ph.D., chief of Pediatric Cardiac Bioengineering at Boston Children's, says that to his knowledge, this is the first report of the equivalent of a self-driving car navigating to a desired destination inside the body. .... " 

(Video included)

IBM Maximo for Civil Infrastructure

A considerable move, including IOT and AI powered solutions.

IBM to Develop an AI-Powered IoT Solution to Help Clients Manage and Monitor Aging Bridges, Tunnels, Highways and Railways

Using drones for inspection. ORLANDO, Fla., April 24, 2019 /PRNewswire/ -- At IBM's IoT Exchange, IBM (NYSE: IBM) today announced a collaboration with Sund & Bælt — which owns and operates some of the largest infrastructure in the world — to assist in IBM's development of an AI-powered IoT solution designed to help prolong the lifespan of aging bridges, tunnels, highways, and railways. The new industry solution, IBM Maximo for Civil Infrastructure, further extends the IBM Maximo portfolio while  ... 

The Amazon Pricing Effect

Some good data and analysis here.   How much is the effect and in what business contexts?  Striking how much private label development is going on now in traditional Grocery, price competition there too. 

The 'Amazon Effect' Is Changing Online Price Competition—and the Fed Needs to Pay Attention
by Roberta Holland  in HBSWK

Amazon's power in the retail sector puts price pressure on what competitors charge, with implications for how federal regulators govern inflation, says Alberto F. Cavallo.

It’s no secret that fierce competition from Amazon puts downward pressure on prices charged by Walmart and other big multichannel retailers for the same items. However, the bigger “Amazon effect” relates not to the prices themselves but to the pricing behaviors of these more traditional retailers, according to Alberto Cavallo, the Edgerley Family Associate Professor at Harvard Business School.

Cavallo, who bases his findings on a decade’s worth of pricing data, sees two notable changes with large multichannel retailers: faster price increases and more uniform pricing between disparate locations.

“It’s not about just the markup, which, to some extent, is just a temporary effect,” Cavallo says. “If competition with Amazon changes the way firms such as Walmart or Best Buy make pricing decisions, it can have much longer-lasting effects on inflation dynamics and other macroeconomic phenomena.” .... " 

Painting Streets with Augmented Reality

Not a new idea, though the approach is closer to making this work broadly.  Why not start with existing mapping examples?

Mapping the World in 3D Will Let Us Paint Streets With Augmented Reality 
Technology Review    By Charlotte Jee

The U.K. startup Scape provides a visual positioning service that uses global positioning systems (GPS) and multiple camera images to localize users. The company has collected more than 2 billion street images that allow it to map in three dimensions more than 100 cities. Scape's algorithms extract "points of interest" from any image, compare it with the billions of images in its database, then use triangulation to infer the angle and distance from which the object was observed, returning its precise location to the end user. Scape co-founder Edward Miller hopes the company's location services will become the underlying infrastructure for driverless cars, robotics, and AR services. Said Miller, "Our end goal is a one-to-one map of the world covering everything.".... '

Managing the Managers

More insertion of AI into daily interactions and tasks.  Considering, when and how ... and how do you measure the uptake? 

The Robots That Manage the Managers    By The Wall Street Journal  (Will require registration)

The platforms are based on research showing periodic repetition and reminders are good ways to learn new material.

A new wave of artificial intelligence-driven coaching apps and platforms aim to provide new managers with training in traditional supervisory skills.

As millennials move into management positions, many find they lack even introductory training in traditional supervisory skills such as delivering feedback and delegating work.

A new wave of artificial intelligence (AI)-driven coaching apps and platforms aim to fill the gap, including Butterfly, Qstream, and LEADx.

The platforms are based on research showing periodic repetition and reminders are good ways to learn new material; they suit a generation of digital natives that prefer checking an app over sitting through a PowerPoint tutorial.

However, the apps' text and email reminders are easy to ignore, and it can be strange when a bot gets too personal.

The coaching programs use AI in various ways, typically by factoring a user's responses over time into the selection and timing of coaching tips.

For example, a user who has almost mastered material might be nudged to recall it less often than one who is being exposed to it for the first time. .... "

From The Wall Street Journal 

Assistants Answering All Your Questions?

Good research being done here.  Good points made,  no they can't, but I think that they can be helpful in certain focused skill areas.    We had lots of experience creating these for certain skill areas for CPG, like cleaning.     Think also about having several levels of assistant, like a concierge model.  Which can lead to humans as needed.   Key is having supporting data, and common journeys established and maintained.

Voice Assistants Cannot Answer All Your Questions
Collin Colburn, Analyst  in Forrester Blog
Arleen Chien, Researcher

Let’s be honest: there is a lot of hype around voice assistants (or as we call them at Forrester, Intelligent Agents (IAs)). Marketers, agencies, and vendors alike are all excited about this potential voice search future. But have you ever had a voice search experience with an IA like the cartoon below?

We wanted to conduct rigorous research to understand just how “intelligent” these intelligent agents were when it came to answering commercial voice searches. We decided to:

Come up with 180 commercial questions… We specifically wanted to ask the IAs questions that were commercially applicable like “What’s the best water-proof mascara?” or “Where can I get advice on my 401k?”.

…Across six industries… We chose questions within industries that are most relevant to Forrester’s client base: CPG and retail, travel and hospitality, financial services and insurance, tech and telecom, healthcare, and automotive

And ask our questions to each of the four major IAs. We chose the four most popular IAs to test to see what their “answers” to our voice search questions were: Amazon Alexa, Apple’s Siri, Google Assistant, and Microsoft’s Cortana. .... "

Better Way to Use Predictive Analytics

Good thoughts about analytics using proxies.   And the ever present issue of the lack of needed data.  We often did something similar, but not as sophisticated.   The use of proxies for many predictions is a common thing.  Just make sure your proxy operates in the same way in changing contexts.  And make sure you included it in your documented assumptions.   I have seen examples where that was somehow forgotten. 

Podcast and transcript:

Beyond Clicks: Getting the Most out of Big Data
Wharton's Hamsa Bastani discusses her research on a better way to use predictive analytics.

In the deep ocean of big data, it’s hard for companies to know what’s true or even relevant to their operations. The latest research from Hamsa Bastani, Wharton professor of operations, information and decisions, can help companies navigate the waters by offering a better way to use predictive analytics. Bastani spoke with Knowledge@Wharton about her paper, “Predicting with Proxies.”

An edited transcript of the conversation follows.

Knowledge@Wharton: This paper focuses on predictive analytics. How do companies use predictive analytics today?

Hamsa Bastani: A lot of companies across a variety of applications are starting to use predictive analytics to guide their decision-making. For example, in e-commerce, companies like Amazon or Expedia use customer-specific data to try to predict what sorts of products a customer might be interested in and then use that to make personalized product recommendations.

Knowledge@Wharton: This process often uses something called a proxy outcome. What’s the difference between a proxy outcome and an actual outcome? And why do firms settle for proxies?

Bastani: It’s often the case that the data that we want are available in a very limited quantity, and this is what I would call the true outcomes. What we have instead is a large amount of data from a closely related outcome, which is what we call proxy outcomes.

In the e-commerce example again, a company like Amazon typically will have very little data on customer purchases for a particular item, but they’ll have lots and lots of click data. If you think about it, clicks are a pretty good proxy for purchases because a customer will typically not click on a product unless they have some intent of purchasing it. Of course, these two outcomes are not exactly the same. What I’ve found in some of my research looking at, for instance, personalized hotel recommendation data for Expedia is that these outcomes can be different along a few dimensions. ... " 

The Psychology of Selling

Some interesting thoughts on selling vs buying and how we arrange to influence the proposition.

Selling Versus Buying  By Frank Sarr  in CustomerThink

The Premise: The “psychology of purchase” dictates that a person’s drive to buy is heightened in direct proportion to their perceived personal need for something. A buyer also reacts much more readily to specifics than to generalities. By bringing a prospect’s deeply-felt concerns to the surface, the seller can help them see the concrete, specific benefits of a product or service.

Selling the Product vs. Selling the Prospect

It has been said that people don’t buy life insurance; they’re sold life insurance. This is true in almost all sales environments including the sales of life insurance. The buy/sell dynamic typically works this way: 1) the prospect mentions a need, 2) the sales person pounces on it and 3) makes an all-out effort to convince the prospect that their solution is the only thing that can address that need.

Whether the “need” is sales training, management development, supervisory training, or something else, the seller’s immediate response is to explain to the prospect why this is a problem they should attend to, with the close being something like: “Don’t you feel it’s important to address this issue?”

Thus, the salesperson immediately attempts to “sell” both the problem and the solution. If we applied Pareto’s 80/20 rule to this scenario, the seller would probably be doing 80% of the talking and 20% of the listening. While this approach might engage the prospect, instead of promoting a sale it tends to promote an image of a fast-talking, foot-in-the-door “salesperson” rather than someone interested in understanding what their problem really is before coming up with a solution.

What the seller should be doing is engaging the prospect on an empathetic and emotional level so that the buyer can not only recognize the problem, but can also personalize it as a need.  This internal perception is what gives the prospect the incentive to commit to the solution that the seller is proposing—in other words, to become a buyer.  .... "

P&G Direct to Consumer Very Quickly Growing

GMA Smartbrief quotes CNBC:
P&G CFO: Direct-to-consumer category is "very quickly growing"
(Procter & Gamble)

Procter & Gamble is working to ensure its products are in all shopping channels, and it is considering the direct-to-consumer market an area of opportunity, said Chief Financial Officer Jon Moeller. "Direct-to-consumer itself is still a relatively small segment of the overall market; I would estimate less than 2%. That doesn't mean it's not relevant -- it's very quickly growing, and it's something we're increasingly competing in," he said.  ... ."

Waymo to Build L4 Autonomous Cars in Detroit

A move ahead it seems.  Coming soon to a road near you?  We note that Waymo is part of Google via Alphabet.

Waymo will build its self-driving vehicle fleet in Detroit
The company will repurpose an existing facility in Motor City.

By Amrita Khalid, @askhalid in Engadget

Waymo will build its autonomous vehicles in Detroit. CEO John Krafcik wrote Tuesday in a Medium post that the company will repurpose an existing facility in Motor City with the goal of being operational by mid-2019. Back in January, the company announced it had chosen Southwest Michigan as the location of its new facility for the mass production of L4 autonomous vehicles, the first of its kind in the world.

The company will create anywhere between 100 to 400 jobs as a result of the venture, according to The Detroit Free Press. Waymo will also receive incentives from the Michigan Economic Development Corporation. ... " 

So what is the definition of a Level 4 Autonomous car?  From the Wikipedia:

" ... Level 4 ("mind off"): As level 3, but no driver attention is ever required for safety, e.g. the driver may safely go to sleep or leave the driver's seat. Self-driving is supported only in limited spatial areas (geofenced) or under special circumstances, like traffic jams. Outside of these areas or circumstances, the vehicle must be able to safely abort the trip, e.g. park the car, if the driver does not retake control. ... " 

Level 5 is what might be considered fully autonomous;   'Steering wheel optional' ... "   

And in the Skies:     Google Wing Drones FAA Approved for US home deliveries

Market Basket Analysis

Some of the very earliest analysis (1970s) we supported in the enterprise were variants on market basket analysis.    So I was pleased to find this relatively simple example posted in DSC, by Ayumi Owada,  here using Apriori in Python.   Every marketing person should know of this capability, answering the question: What do people buy with this?

Maximizing Sales with Market Basket Analysis    Posted by Ayumi Owada  

Sales data analyses can provide a wealth of insights for any business but rarely is it made available to the public. In 2018, however, a retail chain provided Black Friday sales data on Kaggle as part of a Kaggle competition. Although the store and product lines are anonymized, the dataset presents a great learning opportunity to find business insights! In this post, we’ll cover how to prepare data, perform basic analysis, and glean additional insights via a technique called Market Basket Analysis.

Let’s see what the data looks like. We use Pivot Billions to analyze and manipulate large amounts of data via an intuitive and familiar spreadsheet style. After importing, we see that the data contains over 500K rows at the bottom, along with example data for each column.  ... "

Cloaking Resource Operations Data in the Cloud

Fascinating play.  How this differ from methods like blockchains?  Maybe better than BC methods?

Creating a Cloak for Grid Data in the Cloud   By Argonne National Laboratory 

Delivering modern electricity is a numbers game. From power plant output to consumer usage patterns, grid operators juggle a complex set of variables to keep the lights on. Cloud-based tools can help manage all of these data, but utility owners and system operators are concerned about security. That concern is keeping them from using the cloud—a collective name for networked Internet computers that provide scalable, flexible, and economical computing power.

Scientists at the U.S. Department of Energy's Argonne National Laboratory are developing and deploying tools to facilitate cloud computing for grid operations and planning. A framework being developed at Argonne masks sensitive data, allowing grid operators to perform complex calculations in the cloud to determine where and when to dispatch resources. By facilitating these calculations without compromising data security and integrity, the framework helps grid operators take the electricity system into the future while avoiding costly investments in computer infrastructure. ... " 

Prescribing Fruits and Veggies

A clever idea, well worth a trial.   Though there is usually no direct joy in prescriptions,  unless they directly kill pain, so I wonder that they feed into the immediate gratification that comes from less than healthy food.   Not the same as cash payment.   Will track progress.    Read more of the expert comments in the link.

Giant Food to fill prescriptions for fruits and veggies in Retailwire   by George Anderson

Giant Food has announced that it is participating in a single-store pilot program in Washington, DC that will allow Medicaid beneficiaries suffering from diet-related chronic illnesses to receive a $20 coupon at the pharmacy to buy fresh fruits and vegetables in the produce section if they bring a doctor’s prescription.

The program, which kicks off tomorrow, is run in concert with DC Greens, a local nonprofit dedicated to giving the city’s residents access to healthy foods.  

“We believe that cross-sector partnerships are the only way to achieve health equity in our city,” said Lauren Shweder Biel, executive director of DC Greens, in a statement. “Doctors and patients both need more tools to address food insecurity and diet-related chronic illness. Through Produce Rx, our healthcare system can be a driver to get patients access to the healthy food that they want and need.”

.... '

Process Mining

A mostly historical look at process mining.    Not a convincing enough view of why you should use it,  and in particular link it to AI.   Also its need to actual know the process, in other words model it, both current and proposed, and its links to BPM.   We did to great success. 

What Process Mining Is, and Why Companies Should Do It
Thomas H. Davenport, Andrew Spanyi in the HBR  ....

Can a Computer Write a Script? Or an Ad? Or Manage a Marketing plan?

A writer of ads, or a manager of marketing plans learns what works based on results in context.  So why not?      The idea of 'a script' was used in the earliest days of AI to create directions and goals to forge results.  We did parts of what is described here to efficiently fit ads into TV and radio slots.  The idea is not far away.  And a marketing plan is a known process based on data, so use it to deliver.

Can a Computer Write a Script? Machine Learning Goes Hollywood   By Los Angeles Times 

The idea of using machine learning programs to help write scripts and other tasks is becoming increasingly popular in Hollywood.

Entertainment companies are using the technology to color-correct scenes, identify popular themes in book adaptations, and craft successful marketing campaigns.

In addition, talent agencies are using the technology for suggestions on how to market actors and actresses.

Machine learning can provide vast amounts of data on why certain movies or TV shows work and why others fail.

Last year, the Entertainment Technology Center presented analysis showing correlations between a movie's story structure and how well it performed worldwide at the box office.

For example, films that led with action sequences did more than 13 times better at the box office on average than films that started with memory sequences.

Machine learning can also identify which stories are resonating online, pinpointing specific scenes or characters about which viewers are most passionate. .... " 

Accoustical Watermarking and the Second Screen

And yet more on context switching for the voice assistant.    Here work by Amazon, to be presented at an upcoming conference.   Originating from work to ignore 'wake words' in 'second screens' from other media.  Which seems to work quite well now.   But immediately made me think of:  Why not include more data in the watermark to identify it further, transmit information it learns about a context.  Nice direction.

Audio Watermarking Algorithm Is First to Solve "Second-Screen Problem" in Real Time   By Yuan-yen Tai

Audio watermarking is the process of adding a distinctive sound pattern — undetectable to the human ear — to an audio signal to make it identifiable to a computer. It’s one of the ways that video sites recognize copyrighted recordings that have been posted illegally.

To identify a watermark, a computer usually converts a digital file into an audio signal, which it processes internally. If the watermark were embedded in the digital file, rather than in the signal itself, then re-encoding the audio in a different file format would eliminate the watermark.

Watermarking schemes designed for on-device processing tend to break down, however, when a signal is broadcast over a loudspeaker, captured by a microphone, and only then inspected for watermarks. In what is referred to as the second-screen problem, noise and interference distort the watermark, and delays from acoustic transmission make it difficult to synchronize the detector with the signal. 

At this year’s International Conference on Acoustics, Speech, and Signal Processing, in May, Amazon senior research scientist Mohamed Mansour and I will present a new audio-watermarking algorithm that effectively solves the second-screen problem in real time for the first time in the watermarking literature.   .... "

From Web to Blockchain

Fascinating historical view of the Web, is the blockchain a natural architectural extension?

Moving Towards web3.0 Using Blockchain as Core Tech  By Shahid Shaikh

The invention of Bitcoin and blockchain technology sets the foundations for the next generations of web applications. The applications which will run on peer to peer network model with existing networking and routing protocols. The applications where centralized Servers would be obsolete and data will be controlled by the entity whom it belongs, i.e., the User.

From Web 1.0 to Web 2.0
As we all know, Web 1.0 was static web, and the majority of the information was static and flat.  The major shift happened when user-generated content becomes mainstream. Projects such as WordPress, Facebook, Twitter, YouTube, and others are nominated as Web 2.0 sites where we produce and consume verity of contents such as Video, Audio, Images, etc.

The problem, however, was not the content; it was the architecture. The Centralized nature of Web opens up tons of security threats, data gathering of malicious purpose, privacy intrusion and cost as well.

The invention of Bitcoin and successful use of decentralized, peer to peer, secure network opens up the opportunity to take a step back and redesign the way our web works. The blockchain is becoming the backbone of the new Web, i.e., Web 3.0.  .... "

Another Amazon Go Store

Why is Amazon building brick-and-mortar locations?   In Supermarketnews:

Amazon adds to physical retail footprint with latest Go store
Jeff Bezos highlights importance of brick-and-mortar locations to shareholders  By Russell Redman

Moving ahead with its brick-and-mortar expansion, Amazon.com Inc. this week opened a new Amazon Go cashierless store in San Francisco, its 11th overall.

Located at 575 Market St., the 1,750-square-foot store marks the third Amazon Go in the city. Customers can choose from an array of ready-to-eat breakfast, lunch, dinner and snack options made by the store’s kitchen or brought in from favorite local kitchens and bakeries.  .... " 

Wake Words for Assistance Context

Been experiencing the strange concept of a 'wake word' for a few years now.   Its means of switching context ... saying that after I say this special word or phrase, you can interpret everything I said afterwards as special, like a command.  My Echos and Google Homes and Siri do that.  Sometimes well, some times not.  And if there are multiple devices, what if several 'wake'?

  It seems that some devices, in certain places, can do it better or worse, leading to misinterpretation. Sometimes this is annoying, even dangerous.   I have set timers, and when I didn't carefully wait for a confirmation, discovered they were not set.   Its about the acoustics and expectations, I understand,  like when you are talking to people.  This technical article shows there is lots going on with the wake word now:

Using Wake Word Acoustics to Filter Out Background Speech Improves Speech Recognition by 15%   By Xing Fan  Amazon Alexa.

One of the ways that we’re always trying to improve Alexa’s performance is by teaching her to ignore speech that isn’t intended for her. 

At this year’s International Conference on Acoustics, Speech, and Signal Processing, my colleagues and I will present a new technique for doing this, which could complement the techniques that Alexa already uses.

We assume that the speaker who activates an Alexa-enabled device by uttering its “wake word” — usually “Alexa” — is the one Alexa should be listening to. Essentially, our technique takes an acoustic snapshot of the wake word and compares subsequent speech to it. Speech whose acoustics match those of the wake word is judged to be intended for Alexa, and all other speech is treated as background noise.

Rather than training a separate neural network to make this discrimination, we integrate our wake-word-matching mechanism into a standard automatic-speech-recognition system. We then train the system as a whole to recognize only the speech of the wake word utterer. In tests, this approach reduced speech recognition errors by 15%.

We implemented our technique using two different neural-network architectures. Both were variations of a sequence-to-sequence encoder-decoder network with an attention mechanism. A sequence-to-sequence network is one that processes an input sequence — here, a series of “frames”, or millisecond-scale snapshots of an audio signal — in order and produces a corresponding output sequence — here, phonetic renderings of speech sounds.  ... "

Decreasing Drilling Costs

Subsurface data is voluminous and complex.   So why not look at it to determine patterns of value?  AI today can be defined as looking for patterns of data that can be used to improve value in process.  Here is an excellent example.  Its not JUST about finding valuable things in patterns, its about finding better ways to make better use of them.   Less costly and more efficiently.   And putting in place a data collection and analysis method for future improvement.

Total Plans to Use Artificial Intelligence to Cut Drilling Costs in SupplychainBrain
Total SA plans to start a digital factory in the coming weeks to tap artificial intelligence in a bid to save hundreds of millions of dollars on exploration and production projects, according to an executive.

The use of artificial intelligence to screen geological data will help identify new prospects, and shorten the time to acquire licenses, drill and make discoveries, Arnaud Breuillac, head of E&P, said at a conference organized by IFP Energies Nouvelles in Paris on Friday. It will also help optimize the use of equipment and reduce maintenance costs, he said.

The digital factory will employ between 200 and 300 engineers and build on successful North Sea pilot projects, Chief Executive Officer Patrick Pouyanne said at the same event. It will also be a way to attract “young talent” to the industry.  .... "

Data Science Mistakes with the IOT

Good, short and non-technical article.  Obvious and useful.   And I as I often add, carefully map the business process,  get decision makers involved early and often.

Don’t Make These Data Science Mistakes in IoT  in Datanami by Alex Woodie

Data science is tough enough already. Whether you’re looking to act upon data collected from IoT sensors or human generators, don’t make it harder than it has to be by making these three common data science mistakes.

Failure, unfortunately, is not unusual when it comes to big data and data science — and it’s even more troublesome when dealing with large amounts of sensor data from the Internet of Things. When you consider the number of organizations with data science practices versus those that are getting a positive return on investment, it’s clear that many (if not most) organizations struggle to bring it all together before finding repeatable recipes for monetizing data. .... "

Self Driving Expectations

Was recently interviewed on exactly this question.   When?   And what will the phrase include?    Good piece.

Are we There Yet?  A Reality Check on Self-Driving Cars in Wired by Alex Davies

READ THE BREATHLESS articles and bold tweets and you could be forgiven for thinking that the fully autonomous vehicle is around the corner, with a collision- and congestion-free future riding shotgun.

Prepare for disappointment. A decade of massive investment in robocar tech has spawned impressive progress, but the arrival of a truly driverless car—the car that can go anywhere anytime, without human help—remains delayed indefinitely. Despite Elon Musk's self-assured claim that Teslas will have “full self-driving” capability by the end of 2020, the world is too diverse and unpredictable, the robots too expensive and temperamental, for cars to navigate all the things human drivers navigate now. Even John Krafcik, CEO of Waymo (the grown-up company that was Google's self-driving car project), agrees, saying last year, “Autonomy always will have some constraints.” .... '

AI Powered Home Tours

Something similar was suggested and tested to get data for plant maintenance by providing remote tours of key parts of facilities, then extracting data for simulations.  Or to document assets and inventory of facilities.

Virtually walk through dream homes with Zillow’s new A.I.-powered 3D home tours  in Digital Trends by Bruce Brown 

Home sellers and real estate agents listing properties on Zillow’s real estate marketplace now can add 3D tours for no charge to their listings. Zillow 3D Home uses artificial intelligence (A.I.) on an iOS mobile device app to create the tours with 360-degree panoramic photos taken in and around a home.

Zillow began testing the app in 2018. The impetus behind the project came from a survey report from Zillow’s research group that found 45% of Gen Z and 41% of Millennial home buyers stated 3D home tours and videos were very important or extremely important in their home buying decision process ... "

5G and IoT Security

Will 5G play a role in IoT security? in 7wdata?

The Internet of Things (IoT) continues to grow as more and more devices, sensors, assets, and other "things" are connected and share data. Still, many remain concerned about the security threats and vulnerabilities of this environment -- whether it involves IoT networks, data, or the connected devices themselves.

Can 5G, the upcoming fifth generation of wireless mobile communications, help enhance the security of IoT?

IoT ecosystems can be especially appealing as the targets of attacks such as distributed denial of services (DDoS), in part because there are so many different components involved..... "

TensorFlow

Was asked this question recently.  Here a quick, non technical answer.  But does also include code, which is by its nature technical.

What is Tensorflow?

ODSC    https://opendatascience.com/  

It would be a challenge nowadays to find a machine learning engineer who has heard nothing about TensorFlow. Initially created by Google Brain team for some internal purposes, such as spam filtering on Gmail, it was open-sourced in 2015 and became the most popular deep learning framework in the next few years.

Tensorflow is often used for solving deep learning problems and for training and evaluating processes up to the model deployment. Apart from machine learning purposes, TensorFlow can be also used for building simulations, based on partial derivative equations. That’s why it is considered to be an all-purpose tool for machine learning engineers.  ... " 

Don't Panic about the Digital Revolution

I like to think about the future as having a history, that way we can connect it to other (past) history.  Will we be able to find patterns in each to prepare?

Don’t Panic: The Digital Revolution Isn’t as Unusual as You Think  in Knowledge@wharton
Apr 17, 2019 Books Business Radio Podcasts  North America

Former FCC chair Tom Wheeler discusses his new book, which places the current digital revolution into context with other periods of game-changing innovations.

The digital revolution has dramatically changed life on Earth, making it easy to think we’re living in the greatest time of innovation. But a new book by Tom Wheeler, former chairman of the Federal Communications Commission, is a reminder that remarkable change has happened many times before. The invention of the printing press in the 15th century created upheaval and reorganized everything in society, as did the subsequent inventions of the telegraph, telephone and railroad. From Gutenberg to Google: The History of Our Future is an insightful look at the development of networks, the physical links that bind people together. Wheeler, a visiting fellow at the Brookings Institution, recently joined the Knowledge@Wharton radio show on SiriusXM to talk about why history often repeats itself. (Listen to the podcast at the top of this page).

An edited transcript of the conversation follows.  .... "

Military Aviation Automation Operations

Though we are still working with pilots interacting with systems, as apparently happened in the recent 737 systems.   We will soon have to consider many such collaborative systems.

Aviation Automation Climbs New Heights With ALIAS 
Federal Computer Week   By Lauren C. Williams

The U.S. Defense Advanced Research Projects Agency (DARPA)'s Aircrew Labor In-Cockpit Automation System (ALIAS) project aims to develop autonomous artificial intelligences (AIs) to improve flight safety and performance in battlefield operations. ALIAS' goals include producing a customizable, drop-in, removable kit so fewer onboard crew members will be needed on military aircraft. With its initial fly-by-wire experiment led by Sikorsky scheduled for completion in May or June, ALIAS would enable advanced automation to be added to existing aircraft. DARPA in 2016 proved the effectiveness of the effort's sensory and avoidance capabilities with a Cessna 172G aircraft, approaching an unmanned aerial system from multiple angles. DARPA's Lt. Col. Philip Root said once a fly-by-wire AI has been successfully demonstrated, "we can begin adding the autonomy flight controls—operating in the background like a lane assist [feature in cars that helps] the human operator avoid a tree."

AI Impact on Demand Forecasting

Good short piece,  makes good points about what is needed, and should be expected.  I have taught forecasting in the enterprise, and its more about how the forecast is used than what it is.   You would love to have it perfect, but it will not be.   AI provides another useful component.

Is AI’s impact on demand forecasting more hype than reality?   by Nikki Baird in Retailwire

Through a special arrangement, presented here for discussion is a summary of a current article from the blog of Nikki Baird, VP of retail innovation at Aptos. The article first appeared on Forbes.com.

The forecast error in retail is as high as 32 percent, according to some estimates. Will artificial intelligence (AI) technology do any better?

AI promises to change the way demand forecasting works in retail in six key ways, but those promises include a bit of hype:  .... " 

Wing Delivers from Drones in Australia

Have not seen it in the US except for specialty examples, but Alphabet is doing it in Australia.

Wing Officially Launches Australian Drone Delivery Service in IEEE Spectrum

After years of testing, Wing is now offering consumer drone delivery to select Australian suburbs   By Evan Ackerman

This drone can deliver your morning coffee directly to your house. But is that something people really want?

Alphabet’s subsidiary Wing announced this week that it has officially launched a commercial drone delivery service “to a limited set of eligible homes in the suburbs of Crace, Palmerston and Franklin,” which are just north of Canberra, in Australia. Wing’s drones are able to drop a variety of small products, including coffee, food, and pharmacy items, shuttling them from local stores to customers’ backyards within minutes.    ..... "

Overpromise of AI for Healthcare?

IBM has created lots of interesting pieces of the solution, but not the harder solution of the broader process involved.   Can these be connected into big value?  And Hype has an element as well.   Not too dissimilar from what happened in the previous AI solutions in the 80s,  healthcare solutions emerged quickly to ultimately retract.  Good article:

How IBM Watson Overpromised and Underdelivered on AI Health Care
After its triumph on Jeopardy!, IBM’s AI seemed poised to revolutionize medicine. Doctors are still waiting   By Eliza Strickland in IEEE Spectrum

In 2014, IBM opened swanky new headquarters for its artificial intelligence division, known as IBM Watson. Inside the glassy tower in lower Manhattan, IBMers can bring prospective clients and visiting journalists into the “immersion room,” which resembles a miniature planetarium. There, in the darkened space, visitors sit on swiveling stools while fancy graphics flash around the curved screens covering the walls. It’s the closest you can get, IBMers sometimes say, to being inside Watson’s electronic brain.  ... "