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Saturday, August 31, 2019

IBM AI Open Source Tool Explainability Talk

Upcoming talk, looks to be quite interesting regarding AI explain-ability open source method.  The talk will be recorded and I will post its location afterwards.

 CSIG (Cognitive Systems Institute Group) Talk - Thursday Sep 5, 2019 - 10:30-11am US Eastern
Title: Al Explainability 360 Toolkit

Speakers: Vijay Arya & Amit Dhurandhar, IBM Research

As AI and ML algorithms make inroads into society, calls are increasing for algorithms to explain their outputs. Affected citizens, government regulators. domain experts. or system developers. present different requirements for explanations. To address these needs we introduce:

AI Explainability 360 (http://aix360.mybluemix.net/)  (good tutorials there) , an open-source software toolkit featuring 8 state-of-the-art explainability methods and 2 evaluation metrics. We provide a taxonomy to help entities require explanations to navigate the space of explanation methods, in the toolkit and in the broader literature.

We have implemented an extensible software architecture that organizes methods according to their place in the AI modeling pipeline. We discuss enhancements to bring research innovations closer to consumers of explanations. ranging from algorithms. to tutorials and an interactive web demo to introduce AI explainability to different and application domains. Together, the toolkit and taxonomy can help identify gaps where more are needed and provide a platform to incorporate them as they are developed. 

Zoom meeting Link: https://zoom.us/j/7371462221

Zoom Callin: (415) 762-9988 or (646) 568-7788 Meeting id 7371462221
Zoom International Numbers: https://zoom.us/zoomconference
Thu, Aug 2, 10:30am US Eastern https://zoom.us/j/7371462221
More Details and recording Here : http://cognitive-science.info/community/weekly-update/

Finnair Approach to Data as an Asset

Part of a recent scan of how companies are looking at data as an asset

Finnair Unlocks the Business Value of Data with Data Catalog
by Ron Powell in b-eye Network

This article is based on a podcast Ron Powell conducted with Minna Karha, Head of Data for Finnair, where she is responsible for enabling her business units to maximize the full potential of their data assets. Prior to Finnair, Minna held positions in BI, data management, analytics and data warehousing.  Ron is an independent analyst and industry expert for the BeyeNetwork and executive producer of The World Transformed Fast Forward Series. His focus is on business intelligence, analytics, big data and data warehousing.

Minna, Finnair is the largest airline in Finland and has been consistently recognized as one of the safest airlines in the world. Let’s begin by having you tell us more about Finnair?

Minna Karha: Finnair was established in 1923, so we will soon celebrate our 100th year of operations. We also are the national carrier of Finland and one of the world’s longest operating airlines. For the tenth consecutive year, Finnair has been selected by Skytrax at the World Airline Awards event as Northern Europe’s Best Airline, which makes us very proud.

Currently we carry more than 13 million passengers annually and have 6,300 employees. We have 19 destinations in Asia, 18 in the Americas and more than 100 in Europe. We are also a member of the One World Alliance.

What is your role at Finnair?

Minna Karha: My role is to help our units maximize the full potential of our data assets. The starting point, of course, is to understand that data in a modern business world is currency. We need to understand and manage the value of our data assets. This will enable us to unlock the business value of our data, thereby allowing us to continuously increase customer satisfaction. This means, of course, providing tools and best practices and also building the mind-set on new roles within the organization.

I realize that your goal is to become a data-savvy, data-driven organization. To do that, everyone must have access to relevant data. Also, the data literacy rate within your organization must be high. What initiatives have you put in place for people and processes to support your vision?

Minna Karha: Two years ago we started by establishing the role of Head of Data. That was when I joined Finnair. One of my first things was to get to know the organization and understand which roles and skills were lacking. I needed to determine what kind of team I should build to support the already existing organization and be a steward of the roles already in our company. So we ended up building a data solutions development team. We hired data engineers, data architects and data asset product owners. All of these roles were completely new to the company. Also, close cooperation with our analytics and data scientist teams is extremely critical. My data solutions development team is focusing on being a task force that can help different teams of different maturity levels in different situations use data and analytics. We try to help each team when they need help. Sometimes they need more help accessing the data so the data engineering team comes in to help. Sometimes they need more help in data utilization or understanding the inventory or just help to use already existing tools and dashboards, for example. Not only have we added these roles, but we have also started to build a tool. We are currently building a modern data platform that enables collaborative data and analytics work, supporting both machine learning and real-time analytics. .... "

AI Framework for Driverless Cars

Late to this, but a question about driver-less had someone send this to me.    Useful thoughts about the how and what kind of data is being gathered.

Framework for AI Driverless Cars: The Big Picture

Dr. Lance Eliot, CEO, Techbrium Inc. - techbrium.com - and is a regular contributor as our AI Trends Insider, and serves as the Executive Director of the Cybernetic AI Self-Driving Car Institute and has published 11 books on the future of driverless cars.

Follow Lance on Twitter @LanceEliot
By Dr. Lance B. Eliot, the AI Trends Insider

When I give presentations about self-driving cars and teach classes on the topic, I have found it helpful to provide a framework around which the various key elements of self-driving cars can be understood and organized. The framework needs to be simple enough to convey the overarching elements, but at the same time not so simple that it belies the true complexity of self-driving cars. As such, I am going to describe the framework here and try to offer in a thousand words (or more!) what the framework diagram itself intends to portray.

The core elements on the diagram are numbered for ease of reference. The numbering does not suggest any kind of prioritization of the elements. Each element is crucial. Each element has a purpose, and otherwise would not be included in the framework. For some self-driving cars, a particular element might be more important or somehow distinguished in comparison to other self-driving cars. You could even use the framework to rate a particular self-driving car, doing so by gauging how well it performs in each of the elements of the framework.

I will describe each of the elements, one at a time. After doing so, I’ll discuss aspects that illustrate how the elements interact and perform during the overall effort of a self-driving car.  .... "

Friday, August 30, 2019

ACM and Their Learning Center

It has been a while since I have promotionally mentioned the ACM:

Association for Computing Machinery
Advancing Computing as a Science & Profession.    (and as avid users of computing technology!)

We see a world where computing helps solve tomorrow’s problems – where we use our knowledge and skills to advance the profession and make a positive impact.  .... "

I have been a member since my days in school.   I am a guest blogger n their system.  I attend may webinars and talks they provide.  ....

And also, the   ACM Learning Center  Which has many,  many resources,  even for the non-member (although they are well worth joining!  Every professional and person interested in computing technology, whether as an observer, learner, user or developer.  Most anyone today.  Should check them out:

Providing a wide variety of resources for lifelong learning and professional development .... 

About ACM Learning Center:

The ACM Learning Center offers ACM members access to lifelong learning tools and resources. Our E-Learning collections offer complimentary access to more than 55,000 online books and videos from top content publishers. The ACM TechTalk series brings leading computing luminaries and visionaries to your screen. Members enjoy exclusive offers and discounts on IT industry certifications and vendor-specific training.  ... "

Connect with me to chat about their value ... Franz Dill

Update on North's Focals Smart Glasses

More updates on North's Focals Smart Glasses.  Now more closely connected to typical smart phone OS.  At this only to the Android.   Will this mean that we will soon see these as more common as a replacement for the smartphone,  as convenience rather than the need for hands-free?

North’s Focals smart glasses now support Android’s notification actions
Manage your emails or retweet directly from your face
By Jon Porter@JonPorty in TheVerge

North has added native support for Android’s notification actions to its Focals smart glasses. Using the new functionality, you’ll now be able to access any shortcuts app developers include in their app’s notifications. 9to5Google, which first spotted the update, notes that these actions can include deleting or archiving emails in the Gmail app or retweeting tweets on Twitter. .... " 

Simulating Softness

We were in a consumer space that had as one of it measures softness.   So the measurement and creation of softness was key.

How to simulate softness    by University of California - San Diego

UC San Diego researchers specially engineered a set of materials to mimic different levels of perceived softness. 

What factors affect how human touch perceives softness, like the feel of pressing your fingertip against a marshmallow, a piece of clay or a rubber ball? By exploring this question in detail, a team of engineers and psychologists at the University of California San Diego discovered clever tricks to design materials that replicate different levels of perceived softness.

The findings provide fundamental insights into designing tactile materials and haptic interfaces that can recreate realistic touch sensations, for applications such as electronic skin, prostheses and medical robotics. Researchers detail their findings in the Aug. 30 issue of Science Advances.

"We provide a formula to recreate a spectrum of softness. In doing so, we are helping close the gap in understanding what it takes to recreate some aspects of touch," said Charles Dhong, who co-led the study as a postdoctoral fellow at UC San Diego and is now an assistant professor in biomedical engineering at the University of Delaware. Dhong worked with Darren Lipomi, a professor of nanoengineering at UC San Diego and the study's co-corresponding author.

Based on the results from their experiments, the researchers created equations that can calculate how soft or hard a material will feel based on material thickness, Young's modulus (a measure of a material's stiffness), and micropatterned areas. The equations can also do the reverse and calculate, for example, how thick or micropatterned a material needs to be to feel a certain level of softness.  ....  "

Waterloo Develops Faster 5G for IOT

Implications of 5G for broader more effective IOT?

Waterloo Researchers Develop 200X Faster, Low-Cost Network for 5G Connectivity 
International Business Times
Soorya Kiran
August 29, 2019

Researchers at the University of Waterloo in Canada have developed a more affordable and efficient technique to enable 5G wireless connectivity for Internet of Things (IoT) devices. The mmX millimeter wave network delivers multi-gigahertz of unlicensed bandwidth, 200-fold more bandwidth than that allocated to current Wi-Fi and cellular networks. MmX supports a significantly higher bitrate than Wi-Fi and Bluetooth. Said Waterloo's Ali Abedi. "Any sensor you have in your home, which traditionally used Wi-Fi and lower frequency, can now communicate using high-speed millimeter wave networks. Autonomous cars are also going to use a huge number of sensors in them which will be connected through wire; now you can make all of them wireless and more reliable."  ... " 

Amazon Putting Alexa in the Car

Just put one in my own car and am starting to understand how it interacts with the smart home experience.   Its started to roll more broadly now as I hear colleagues chime in.  In this case Amazon  is well behind, with the usual competitors and car companies.  Good article on the complexity involved here.   Cheap and easy to use 'Echo Auto' gets the process started for those that already understand the basic infrastructure.  The new location channel for shopping is an intriguing step.

The article below contains an extensive article that follows a demo of what Amazon is developing and how they plan to connect the methods to mobility in general. 

Inside Amazon’s long game to put Alexa in your car

Competing with Apple and Google when you don’t have your own smartphone platform is tough. But Amazon has a plan—and lots of patience.    By Mark Sullivan in Fastcompany

The demo house Amazon built inside one of the towers at its Seattle headquarters to show off its Echo smart speakers has a new room, and an important one: a garage.

Inside the garage is a concept electric car—or, more specifically, the immobile insides of such a vehicle—that Amazon uses to show automakers the full spectrum of things its Alexa Auto software platform can do. That includes in-car versions of typical Alexa tasks such as audio streaming, messaging, voice calls, and reminders. And because it’s a car, Alexa can also do things like roll the windows up and down and control the cabin temperature, all at the verbal request of the driver.

Amazon has been working hard on Alexa Auto for the past two years. Now it hopes to convince automakers to embed the platform into their new cars.   .... " 

Influencers and Beauty Marketing

Beauty Marketing taken over by influencers

Lipstick Tips: How Influencers Are Making Over Beauty Marketing   by Dina Gerdeman in HBS

Influencer marketing has quickly become the best way to reach beauty consumers, proving more effective than celebrity endorsements and company ads, according to research by Alessia Vettese.

British makeup guru Katie Jane Hughes posts close-up photos of her face on Instagram almost daily for her 336,000 followers: shimmery gold eyelids; glossy pink lips that complement her auburn hair; eyebrows tinted with tiny brushstrokes of brown gel to fix her mistake in overplucking as a teenager.

And, in a video tutorial on YouTube, in which Hughes starts with a scrubbed-clean face (revealing some of the same splotchy spots many of us worry about), she demonstrates how she applies layer after layer of creams and cosmetics to achieve a glamorous look.

“This tingles a little bit when you put it on, but that’s normal because it’s got glycolic in it,” Hughes says, glancing between the camera and a mirror as she massages a moisturizer into her skin. “I don’t really quite understand how glycolic face creams work. All’s I can tell you is, my skin has been amazing ever since I started using this product.”

During the video’s 12-plus minutes of step-by-step instructions, Hughes holds up product after product close to the camera so viewers can get a good look at each brand name. Because, after all, Hughes isn’t merely sharing beauty tips. She’s also selling makeup.

While Hughes is not your typical celebrity cover girl, her social media posts compel thousands of customers to purchase the products she recommends. ...... " 

Thursday, August 29, 2019

Robot Morning For Aerospace Supply Chain

Just brought to my attention:

Robot Morning

Building the automated aerospace supply chain

Robot Morning creates software that automates and analyzes the data exchanged between customers and suppliers.

The DemandLine Client resides on your servers. It acts as a repository for data from your customers and handles communication with your ERP software. It takes responsibility for updating your sales orders, generating and sending commits, and managing ASNs – all fully automated.

The DemandLine Network coordinates the communication between your DemandLine Client and your customers’ systems. It is hosted by Robot Morning   ... "

Wal-Mart, Facebook and Digital Tokens for Inclusion

Fascinating piece on the notion of 'Financial Inclusion' and its use by retailers of both products and of marketing data,  like Wal-Mart and Facebook.    Meaning of this discussed in the Gartner Blog.  Does this mean that companies like these are attempting to construct their own monetary systems to improve this inclusion?  How will this be regulated?   Implications?

Libra and Walmart “Blockchain” Tokens: Financial or Walled Garden Inclusion?   by cuzureau    Gartner Blog

Facebook has announced the development of a digital currency, Libra (cf. “Facebook Libra — Liberator or Trojan Horse”1 ) and Walmart has filed a patent application for a digital token (cf. patent application2). Both initiatives rely on blockchain technology. The two companies have multiple rationales for launching or planning such initiatives. In this blog post, we explore their claims toward financial inclusion.

Facebook has stressed in the Libra white papers its objective of improving financial inclusion globally. And Walmart’s patent application’s introduction, stresses that: “The cost of having little money is high because of frequent short-term borrowing, accumulated interest on short-term borrowing that becomes long-term, high bank fees proportional to wealth, high credit card fees, and high payday loan interests…. Providing digital currency based on blockchain may overcome the drawbacks associated with the low-income households”

Having more companies try to address financial inclusion is positive and across all markets. Mature banking markets such the US also have to deal with a financial services access gap. The FDIC National Survey of unbanked and underbanked Households (cf.  https://www.fdic.gov/householdsurvey/) estimates that in 2017 there were 8.4m unbanked (no account at an insured institution) households and 24.2m underbanked (checking or savings account only with insured institution), in the USA.   ... " 

Collecting Soil Samples

More autonomous, continuous and precise means of gathering data to make decisions.

Autonomous robots collect precise soil samples, help farmers improve yields, reduce environmental impact   by Drew Schumacher, Purdue University

A pair of Purdue University graduates have founded a company called Rogo Ag LLC, a pioneering agricultural technology company that has developed an autonomous robot called Smartcore. Smartcore is designed to collect accurate, repeatable soil samples in fields and bring the samples directly to the farmers or growers.  ...

Collecting precise soil samples is essential for farmers because a small amount of soil determines the amount of nutrients needed for acres of crops and can determine crop yields.

The U.S. Department of Agriculture reports that soil testing can help farmers increase yields, reduce production costs and prevent surface and groundwater pollution.

"Smartcore," an autonomous robot developed by a pair of Purdue University College of Engineering graduates, is designed to collect accurate, repeatable soil samples in fields and bring to the edge of the field for shipment to the lab. Troy Fiechter and Drew Schumacher founded Rogo, officially Rogo Ag LLC, a startup to advance the technology and move it to the public.  .... " 

Webinar: Mixed Integer Programming plus Machine Learning

Highly recommended!   We used Mixed Integer Programming optimization methods for many years in the enterprise.  Used it every day to solve tough problems.  It was our horse for optimization problems.   Especially for complex combinatorial decisions.  Nice to see this upcoming Webinar as presenting it as complimentary to Machine Learning (ML).   Then ML can be used to directly make key resulting decisions!   Always better to get closer to the decision.  I will be attending.

Title: Mathematical Optimization + ML: Featuring Forrester Survey Insights
Date: 9/17/2019
Time: 9:00 AM PDT
Duration: 60 Minutes

Mathematical optimization (AKA Mixed Integer Programming) and Machine Learning (ML) are different but complementary technologies. Simply put – Mixed Integer Programming (MIP) answers questions that ML cannot. Machine learning makes predictions while MIP makes decisions. For Data Scientists to be effective, an understanding of MIP and when to use it is critical, as ML does not solve all problems effectively.

In this latest Data Science Central webinar, you will hear the results of the 2019 Mathematical Optimization Survey commissioned by Gurobi and conducted by Forrester and insights on how Data Scientists can use tools such as MIP to make complex decisions.

You’ll learn:
- The latest trends in ML and Artificial Intelligence
- Key findings from the Mathematical Optimization Survey
- How you can use MIP in concert with ML techniques
- How industries are using MIP today to efficiently use resources, often resulting in time savings and millions of dollars in cost savings

All registrants will receive a copy of the 2019 Mathematical Optimization Study available in October 2019.

Mike Gualtieri, VP Principal Analyst, Application Development and Delivery Professionals - Forrester Research
Edward Rothberg, CEO and Co-Founder - Gurobi Optimization

Hosted by
Stephanie Glen, Editorial Director - Data Science Central
Not registered for the Mathematical Optimization + ML: Featuring Forrester Survey Insights webinar and interested in signing up? Click below:


Ring/Amazon Reveals How its working with Police in the US

Been a member since the network has been established, great idea. 

Working Together for Safer Neighborhoods: Introducing the Neighbors Active Law Enforcement Map     by Jamie Siminoff

At Ring, we believe that when communities work together, safer neighborhoods become a reality—that’s why we created the Neighbors app—we wanted to easily facilitate conversations around crime and safety among all members of the community, and we invited local law enforcement agencies to contribute to those discussions.

Today, 405 agencies use the Neighbors Portal, which is an extension of the Neighbors app that allow law enforcement to engage with their local community—from posting important information about crime and safety events in their neighborhoods to viewing and commenting on public posts as a verified law enforcement officer to asking for help on active investigations by submitting requests for video recordings.  .... " 

Further discussed outlining all the usual angst in Engadget.    We don't like safety?

Wednesday, August 28, 2019

More Very Small Healthcare Robotics

More MIT robotics advances, with very clear potential healthcare applications.

Robotic thread is designed to slip through the brain’s blood vessels
Magnetically controlled device could deliver clot-reducing therapies in response to stroke or other
brain blockages.  By Jennifer Chu | MIT News Office 

MIT engineers have developed a magnetically steerable, thread-like robot that can actively glide through narrow, winding pathways, such as the labrynthine vasculature of the brain.

In the future, this robotic thread may be paired with existing endovascular technologies, enabling doctors to remotely guide the robot through a patient’s brain vessels to quickly treat blockages and lesions, such as those that occur in aneurysms and stroke.

“Stroke is the number five cause of death and a leading cause of disability in the United States. If acute stroke can be treated within the first 90 minutes or so, patients’ survival rates could increase significantly,” says Xuanhe Zhao, associate professor of mechanical engineering and of civil and environmental engineering at MIT. “If we could design a device to reverse blood vessel blockage within this ‘golden hour,’ we could potentially avoid permanent brain damage. That’s our hope.”  .... '

Computational Sustainability

A new subfield of using computer based modeling and methods.

Video introduction:   https://vimeo.com/351182289

Carla Gomes of Cornell, discusses "Computational Sustainability" (cacm.acm.org/magazines/2019/9/238970), a Contributed Article in the September 2019 CACM.

" .. These are exciting times for computational sciences with the digital revolution permeating a variety of areas and radically transforming business, science, and our daily lives. The Internet and the World Wide Web, GPS, satellite communications, remote sensing, and smartphones are dramatically accelerating the pace of discovery, engendering globally connected networks of people and devices. The rise of practically relevant artificial intelligence (AI) is also playing an increasing part in this revolution, fostering e-commerce, social networks, personalized medicine, IBM Watson and AlphaGo, self-driving cars, and other groundbreaking transformations. .... "

Reality of Data Privacy

Long known that this is a difficult problem.  Here a considerable piece on the subject:

Is Data Privacy Real? Don’t Bet on It
Aug 23, 2019 North America in Knowledge@Wharton

In 2009, Netflix was sued for releasing movie ratings data from half a million subscribers who were identified only by unique ID numbers. The video streaming service divulged this “anonymized” information to the public as part of its Netflix Prize contest, in which participants were asked to use the data to develop a better content recommendation algorithm. But researchers from the University of Texas showed that as few as six movie ratings could be used to identify users. A closet lesbian sued Netflix, saying her anonymity was compromised. The lawsuit was settled in 2010.

The Netflix case reveals a problem about which the public is just starting to learn, but that data analysts and computer scientists have known for years. In anonymized datasets where distinguishing characteristics of a person such as name and address have been deleted, even a handful of seemingly innocuous information can lead to identification. When this data is used to serve ads or personalize product recommendations, re-identification can be largely harmless. The danger is that the data can be — and sometimes is — used to make assumptions about future behavior or inferences about one’s private life — leading to rejection for a loan, a job or worse.

A research paper published in Nature Communications last month showed how easy re-identification can be: A computer algorithm could identify 99.98% of Americans by knowing as few as 15 attributes per person, not including names or other unique data. Even earlier, a 2012 study showed that just by tracking people’s Facebook ‘Likes,’ researchers could identify if someone was Caucasian or African-American with a 95% certainty, male or female (93%), or gay (88%); whether they drink (70%); or if they used drugs (65%).

This is not news to people in the industry — but it is to the public. “Most people don’t realize that even if personal information is stripped away or is not collected directly, it’s often possible to link certain information with a person’s identity by correlating the information with other datasets,” says Kevin Werbach, Wharton legal studies and business ethics professor and author of the book, The Blockchain and the New Architecture of Trust. “It’s a challenging issue because there are so many different kinds of uses data could be put to.” Werbach is a faculty affiliate of the Warren Center for Network and Data Sciences, a research center of Penn faculty who study innovation in interconnected social, economic and technological systems.

For example, telecom companies routinely sell phone location information to data aggregators, which in turn sell them to just about anyone, according to a January 2019 article in Vice. These data buyers could include landlords screening potential renters, debt collectors tracking deadbeats or a jealous boyfriend stalking a former flame. One data aggregator was able to find an individual’s full name and address as well as continuously track the phone’s location. This case, the article says, shows “just how exposed mobile networks and the data they generate are, leaving them open to surveillance by ordinary citizens, stalkers, and criminals.” .... "

Software Architecture to Watch

Notable piece by O'Reilly on expanding and emergent software architecture methods:

The topics to watch in software architecture
Microservices, serverless, AI, ML, and Kubernetes are among the most notable topics in our analysis of proposals from the O’Reilly Software Architecture Conference. .... 

By Roger Magoulas, Chris Guzikowski  .... "

Linkedin Recruiting Spies

As might be expected, as a vast public collection of detailed HR data, with the ability to follow through with extended communication, it could be used to recruit anyone for anything.

LinkedIn reportedly used by some nations to recruit spies   By Trevor Mogg in DigitalTrends

LinkedIn isn’t only an excellent way to find new business opportunities and network with others who work in the same field. It’s also a great way for foreign powers to recruit spies, according to a New York Times report published on Tuesday, August 28.

The practice has been going on for a number of years, the report claims, with Western counterintelligence officials from several nations warning some individuals to be wary of foreign agents using the social networking site for recruitment purposes. Officials speaking to the Times described Chinese spies as “the most active” on LinkedIn.  .... " 

Machine Learning Astonishes

Free at the link, a short non-technical article in the latest Communications of the ACM, which describes how machine learning is taking over computing.  And how making machines learn has led to a new enthusiasm of devices, which are continually updating and discovering.   Its astonishing!

Polyglot!  By Vinton G. Cerf 

Communications of the ACM, September 2019, Vol. 62 No. 9, Page 6
10.1145/3352690     Google Vice President and Chief Internet Evangelist Vinton G. Cerf 

Google speaks 106 languages—or at least can understand queries in written form if not also oral form. When I watch someone interacting verbally with Google Assistant in languages other than English (my native tongue), I realize Google's language ability vastly exceeds my own. I have a modest ability to speak and understand German. I know a few phrases in Russian and French. But it suddenly strikes me that Google is usefully dealing with over 100 languages in written and oral form. Assistant is responding to queries by recognizing speech input, searching the Web, and voicing the answers in multiple languages. Google Lens is translating text seen in photos into the viewer's preferred language. Google Translate is converting text and speech in one language into another with increasing quality. The quality varies, of course, depending on the volume of training material available to configure deep neural machine learning networks, but the fact that it works at all across so many languages is nothing short of astonishing and even daunting. .... "

Body Sensors Use Gathered Power

Another example of the use of body gathered power.

Sticker sensor monitors your body using wireless power
It wouldn't interfere with your behavior.

Jon Fingas, @jonfingas in Engadget

Wearable body sensors have a common problem: they need power and antennas, and all that equipment leads to bulky devices that influence your behavior. Stanford researchers, however, have developed a system that could be almost imperceptible. Their BodyNet sticker sensor gathers power and transmits data using an RFID connection to a receiver on nearby clothing, making the sensor itself about as comfortable and flexible as an adhesive bandage. It measures subtle changes in skin that provide a wealth of data for the body, whether it's your heartbeat, breathing rate or muscle activity.  .... " 

AI, Humanity and Civilization

A future look at AI.  I think too pessimistic, but suggests some cautions about how we will need to utilize it.   Augmentation rather than autonomy may be the best initial guide.

The Metamorphosis

AI will bring many wonders. It may also destabilize everything from nuclear détente to human friendships. We need to think much harder about how to adapt.    August 19, 2019  Atlantic

By  Henry A. Kissinger, the national security adviser and secretary of state to Presidents Richard Nixon and Gerald Ford; Eric Schmidt, former CEO and chairman of Alphabet; and Daniel Huttenlocher, the founder and former dean of Cornell Tech and the current dean of the MIT Schwarzman College of Computing, met regularly for three years to discuss AI. In an Atlantic article, they discuss the impact AI may have on society, from the fairly predictable (how will we monitor and regulate AI and what to do about AI weaponry) to what AI isn’t telling us that it’s learning and how AI could induce humans to feel emotions toward it that it’s incapable of reciprocating ....  Via O'Reilly: 

Humanity is at the edge of a revolution driven by artificial intelligence. It has the potential to be one of the most significant and far-reaching revolutions in history, yet it has developed out of disparate efforts to solve specific practical problems rather than a comprehensive plan. Ironically, the ultimate effect of this case-by-case problem solving may be the transformation of human reasoning and decision making.

This article appears in the August 2019 issue.

This revolution is unstoppable. Attempts to halt it would cede the future to that element of humanity more courageous in facing the implications of its own inventiveness. Instead, we should accept that AI is bound to become increasingly sophisticated and ubiquitous, and ask ourselves: How will its evolution affect human perception, cognition, and interaction? What will be its impact on our culture and, in the end, our history?

Such questions brought together the three authors of this article: a historian and sometime policy maker; a former chief executive of a major technology company; and the dean of a principal technology-oriented academic institution. We have been meeting for three years to try to understand these issues and their associated riddles. Each of us is convinced of our inability, within the confines of our respective fields of expertise, to fully analyze a future in which machines help guide their own evolution, improving themselves to better solve the problems for which they were designed. So as a starting point—and, we hope, a springboard for wider discussion—we are engaged in framing a more detailed set of questions about the significance of AI’s development for human civilization. ... "

Tuesday, August 27, 2019

Inability to Reproduce Results: A Crisis

 Its the scientific method.   I have seen many examples where you could not recreate the context involved, but the results were accepted as proof, because they followed some narrative that was generally accepted, or not accepted.  Bias of many types.   Dangerous crisis. Good article, but deeper than is stated.  Especially if investment and resulting risk is high.

An Inability to Reproduce   By Samuel Greengard 
Communications of the ACM, September 2019, Vol. 62 No. 9, Pages 13-15

Science has always hinged on the idea that researchers must be able to prove and reproduce the results of their research. Simply put, that is what makes science...science. Yet in recent years, as computing power has increased, the cloud has taken shape, and data sets have grown, a problem has appeared: it has becoming increasingly difficult to generate the same results consistently—even when researchers include the same dataset.

"One basic requirement of scientific results is reproducibility: shake an apple tree, and apples will fall downwards each and every time," observes Kai Zhang, an associate professor in the department of statistics and operations research at The University of North Carolina, Chapel Hill. "The problem today is that in many cases, researchers cannot replicate existing findings in the literature and they cannot produce the same conclusions. This is undermining the credibility of scientists and science. It is producing a crisis."

The problem is so widespread that it is now attracting attention at conferences and in academic papers, and even is garnering attention in the mainstream press. While a number of factors contribute to the problem—including experimental errors, publication bias, the improper use of statistical methods, and subpar machine learning techniques—the common denominator is that researchers are finding patterns in data that have no relationship to the real world. As Zhang puts it, "The chance of picking up spurious signals is higher as the nature of data and data analysis changes."

At a time when anti-science sentiment is growing and junk science is flourishing, the repercussions are potentially enormous. If results cannot be trusted, then the entire nature of research and science comes into question, experts say. What is more, all of this is taking place at a time when machine learning is emerging at the forefront of research. A lack of certainty about the validity of results could also lead people to question the value of machine learning and artificial intelligence.

Methods Matter

A simple but disturbing fact is at the center of this problem. Researchers are increasingly starting with no hypothesis and then searching—some might say grasping—for meaningful correlations in data. If the data universe is large enough—and this is frequently the case—there are reasonably good odds that by sheer chance, a valid p-value will appear. Consider: if a person tosses a coin eight times and it lands on heads every time, this is noteworthy; however, if a person tosses a coin 8,000 times and, at some point, the coin lands on heads eight consecutive times, what might appear to be a significant discovery is merely a random event.

The idea that scientific outcomes may be inaccurate or useless is not new. In 2005, John Ioannidis, a professor of health research and policy at Stanford University, published an academic paper titled Why Most Published Findings Are False, in the journal PLOS Medicine. It put the topic of reproducibility of results on the radar of the scientific community. Ioannidis took direct aim at methodologies, study design flaws, and biases. "Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true," he wrote in that paper.

Others took notice. In 2011, Glenn Begley, then head of the oncology division at biopharmaceutical firm Amgen, decided to see if he could reproduce results for 53 foundational papers in oncology that appeared between 2001 and 2011. In the end, he found he could replicate results for only six papers, despite using datasets identical to the originals. That same year, a study by German pharmaceutical firm Bayer found only 25% of studies were reproducible.  .... " 

Mining Scientific Applications by Analogies

This could also be done inside a company to look at publications like technical reports, and then also linking those to external publications as well.    Driven by specific goals as well.  The broad ability to use analogies usefully is a powerful thought.  The broad idea is one we looked at extensively, the tech is now here to do it.

AI analyzed 3.3 million scientific abstracts and discovered possible new materials  in MIT Technology Review

A new paper shows how natural-language processing can accelerate scientific discovery.
The context: Natural-language processing has seen major advancements in recent years, thanks to the development of unsupervised machine-learning techniques that are really good at capturing the relationships between words. They count how often and how closely words are used in relation to one another, and map those relationships in a three-dimensional vector space. The patterns can then be used to predict basic analogies like “man is to king as woman is to queen,” or to construct sentences and power things like autocomplete and other predictive text systems.

New application: A group of researchers have now used this technique to munch through 3.3 million scientific abstracts published between 1922 and 2018 in journals that would likely contain materials science research. The resulting word relationships captured fundamental knowledge within the field, including the structure of the periodic table and the way chemicals’ structures relate to their properties. The paper was published in Nature last week.

Because of the technique’s ability to compute analogies, it also found a number of chemical compounds that demonstrate properties similar to those of thermoelectric materials but have not been studied as such before. The researchers believe this could be a new way to mine existing scientific literature for previously unconsidered correlations and accelerate the advancement of research in a field.  .... "  ...

DAML: Contract Language of Distributed Ledgers

Quite an interesting piece on contract languages and 'Smart Contracts".  A recent proposal made me look deeper into this idea, especially as it might connect to supply chain and procurement efficiencies.  Considerable 7-page piece, admittedly technical here, but worth taking a close look.  And of  course this gets to workflow, always a particular angle of interest of mine.  Below just a few excerpts.

Case Study
DAML: The Contract Language of Distributed Ledgers
A discussion between Shaul Kfir and Camille Fournier

When Shaul Kfir cofounded Digital Asset in 2014, he was out to prove something to the financial services industry. He saw it as being not only hamstrung by an inefficient system for transaction reconciliation, but also in danger of missing out on what blockchain technology could do to address its shortcomings.

Since then, Digital Asset has gone to market with its own distributed-ledger technology, DAML (Digital Asset Modeling Language). And that does indeed take advantage of blockchain—only not in quite the way Kfir had initially intended. He and Digital Asset ended up taking an engineering "journey" to get to where they are today.

Kfir readily admits his own background in cryptography and cryptocurrency—both as a researcher (at Technion and MIT) and as a cryptocurrency entrepreneur in Israel—had more than just a little to do with the course that was originally charted. As for lessons learned along the way, Camille Fournier, the head of platform development for a leading New York City hedge fund, helps to elicit those here. She brings to the exercise her own background in distributed-systems consensus (as one of the original committers to the Apache Zookeeper Project) and financial services (as a former VP of technology at Goldman Sachs).  ....  "

" .... To clarify, think about how large technology companies use their infrastructure to achieve greater agility. Most of them today have some logically centralized infrastructure that includes a central code repository and a CI/CD [continuous integration/continuous delivery] system. If these ideas can be expanded to an industry level in the sense that you can start rolling out workflows as smart contracts that are written only once and then made available for everyone to build upon, that's clearly more efficient than leaving it to each organization to write its own workflows. ... " 

Speeding Up Learning Inference by 2X

New methods, technical:

New Technique Speeds Up Deep-Learning Inference on TensorFlow by 2x
by  Anthony Alford  in InfoQ

Researchers at North Carolina State University recently presented a paper at the International Conference on Supercomputing (ICS) on their new technique, "deep reuse" (DR), that can speed up inference time for deep-learning neural networks running on TensorFlow by up to 2x, with almost no loss of accuracy.

Dr. Xipeng Shen, along with graduate student Lin Ning, authored the paper describing the technique, which requires no special hardware or changes to the deep-learning model. By taking advantage of similarities in the data values that are input into a neural network layer, DR eliminates redundant computation during inference, reducing the total time taken. Reducing computation also reduces power consumption, a key feature for mobile or embedded applications. In experiments running several common computer-vision deep-learning models on GPUs, including CifarNet, AlexNet, and VGG-19, DR achieved from 1.75X to 2.02X speedup, with an increase in error of 0.0005. In some cases, DR actually improved accuracy slightly. In similar experiments on a mobile phone, DR "achieves an average of 2.12x speedup for CifarNet and 2.55X for AlexNet."  .... "

Monday, August 26, 2019

IBM Gifts Supercomputer to MIT for AI Models

Summit architectecture still has the record for calculation intensive models.

IBM gives artificial intelligence computing at MIT a lift
Nearly $12 million machine will let MIT researchers run more ambitious AI models.

By Kim Martineau | MIT Quest for Intelligence 

IBM designed Summit, the fastest supercomputer on Earth, to run the calculation-intensive models that power modern artificial intelligence (AI). Now MIT is about to get a slice. 

IBM pledged earlier this year to donate an $11.6 million computer cluster to MIT modeled after the architecture of Summit, the supercomputer it built at Oak Ridge National Laboratory for the U.S. Department of Energy. The donated cluster is expected to come online this fall when the MIT Stephen A. Schwarzman College of Computing opens its doors, allowing researchers to run more elaborate AI models to tackle a range of problems, from developing a better hearing aid to designing a longer-lived lithium-ion battery. 

“We’re excited to see a range of AI projects at MIT get a computing boost, and we can’t wait to see what magic awaits,” says John E. Kelly III, executive vice president of IBM, who announced the gift in February at MIT’s launch celebration of the MIT Schwarzman College of Computing.    ...  "

New Discipline: Machine Behavior

Yes, behavior is important.   In biological behavior we don't claim to understand all of the mechanics involved.  So we accept the complexity being beyond simple tabulation.   In the case of machines, we build them and control their use.   So its been assumed we understand their behavior.  But no, as they have grown increasingly complex, its less and less so.  So how is studying machine behavior different?  How do we do it efficiently.  And most importantly whats the relevance of context?  So a nice idea.

The Anthropologist of Artificial Intelligence In Quantum by John Pavlus
The algorithms that underlie much of the modern world have grown so complex that we always can’t predict what they’ll do. Iyad Rahwan’s radical idea: The best way to understand them is to observe their behavior in the wild.

Sow do new scientific disciplines get started? For Iyad Rahwan, a computational social scientist with self-described “maverick” tendencies, it happened on a sunny afternoon in Cambridge, Massachusetts, in October 2017. Rahwan and Manuel Cebrian, a colleague from the MIT Media Lab, were sitting in Harvard Yard discussing how to best describe their preferred brand of multidisciplinary research. The rapid rise of artificial intelligence technology had generated new questions about the relationship between people and machines, which they had set out to explore. Rahwan, for example, had been exploring the question of ethical behavior for a self-driving car — should it swerve to avoid an oncoming SUV, even if it means hitting a cyclist? — in his Moral Machine experiment.

“I was good friends with Iain Couzin, one of the world’s foremost animal behaviorists,” Rahwan said, “and I thought, ‘Why isn’t he studying online bots? Why is it only computer scientists who are studying AI algorithms?’

“All of a sudden,” he continued, “it clicked: We’re studying behavior in a new ecosystem.”

Two years later, Rahwan, who now directs the Center for Humans and Machines at the Max Planck Institute for Human Development, has gathered 22 colleagues — from disciplines as diverse as robotics, computer science, sociology, cognitive psychology, evolutionary biology, artificial intelligence, anthropology and economics — to publish a paper in Nature calling for the inauguration of a new field of science called “machine behavior.”  .... ' 

Paper on Machine Behavior that relates to this.

Spotting Objects Among clutter

Key for any kind of real-world application.

Spotting objects amid clutter
New approach quickly finds hidden objects in dense point clouds, for use in driverless cars or work spaces with robotic assistants.

Jennifer Chu | MIT News Office

A new MIT-developed technique enables robots to quickly identify objects hidden in a three-dimensional cloud of data, reminiscent of how some people can make sense of a densely patterned“Magic Eye” image if they observe it in just the right way.

Robots typically “see” their environment through sensors that collect and translate a visual scene into a matrix of dots. Think of the world of, well, “The Matrix,” except that the 1s and 0s seen by the fictional character Neo are replaced by dots — lots of dots — whose patterns and densities outline the objects in a particular scene.

Conventional techniques that try to pick out objects from such clouds of dots, or point clouds, can do so with either speed or accuracy, but not both.  .... " 

Baidu Surpasses Google in Voice

No surprise with volumes of people talking.   And further, since progress in this space can often depend on the volume of data that can be used to develop deeper insight into intelligent conversation,  this may be hard to stop.

Chinese search engine Baidu surpasses Google as 2nd-largest smart speaker vendor   By Patrick Hearn in DigitalTrends

In the western world, it’s easy to think of Google and Apple as the key players in the tech market. On a global scale, however, they have quite a few competitors — particularly the Chinese search engine giant Baidu, which made headlines this week when it became the world’s second-largest vendor of smart speakers.

According to the research firm Canalys, Baidu now owns 17.3 percent of the global market and made 4.5 million shipments in the second quarter of 2019. This represents a staggering year-on-year growth of 3,700%. In spite of this growth and success, Amazon still dominates the smart speaker market..... ' 

Solutions for RansomWare Attacks?

Increasing number of Ransomware attacks.     What is the solution?  Caution with opening received messages certainly, better offline backups of all essential data.   Other Solutions?  Essential we find better and creative solutions to this.

See also comments in the 'Security Now' / Steve Gibson podcast for some thoughtful ideas.

In ZDNet also.

In NPR:  ".... State officials in Texas confirmed that computer systems in 22 municipalities have been hijacked by ransomware, with one town's mayor saying the hackers are demanding $2.5 million. The Texas Department of Information Resources suggested "one single threat actor" may be responsible. Mayor Gary Heinrich of the town of Keene said the attackers infiltrated information technology software used by the city and overseen by an outsourced provider, which supports many of the targeted cities. Recorded Future threat intelligence analyst Allan Liska said this event, the largest coordinated hack of its kind so far observed, "does present a new front in the ransomware attack." Research firm Recorded Future noted the increasing frequency of ransomware attacks targeting state and local government, detecting at least 169 cases since 2013. Liska said more than 60 such attacks have taken place this year alone. ... "

See also, Recorded Future, mentioned above.

Sunday, August 25, 2019

Deloitte Launches Blockchain Demonstrator

Helpful idea to have out there, since the process involved is still mysterious to many.

Deloitte launches ‘Blockchain in a Box’ hands-on demonstrator
The consultancy said a modular computing system will enable hands-on testing of the distributed ledger technology by enterprises hoping to get a grasp on what it can, or cannot, do.
Lucas Mearian By Lucas Mearian in Computerworld   Senior Reporter, Computerworld

Consultancy Deloitte this week unveiled a mobile, self-contained computing platform that can be used to host a blockchain network on a small-scale so companies can test its capabilities.

Called "Blockchain in a Box" (BIAB), the platform consists of four, small-form-factor compute nodes, three video displays and networking components that can be connected to external services such as cloud providers.   .... " 

Monetizing Your Dark Data

Worked several projects along these lines.  Good provocative thoughts here.   More links to process using data and the means to monetizing that description of business effectively.

Untapped Economic Assets? How to Monetize Your Dark Data
Posted by Bill Schmarzo   in DSC

What if you had a corporate asset that was never used?  Your first response might be that corporate asset obviously has no value.  And you’d probably be right. However, there are costs – acquisition costs, maintenance costs, storage costs, depreciation costs, salvage costs – associated with all assets. So, to incur all of those costs and then not do anything with that asset would be fiduciary negligence at its worse. 

Welcome to the world of dark data! 

And it’s not just dark data; it’s Dracula Datain the sense that the costs and potential liabilities (associated with GDPR, Personal Identifiable Information, Fair Credit Reporting Act, etc.) slowly eat away at the organization’s balance sheet while exposing the organization to unnecessary compliance and regulatory risks.

But if you think dark data is an Information Technology (IT) problem, then that’s probably why you have a dark data problem.  Let me explain…

Data Strategy Driven by the Business Strategy

“Organizations do not need a big data strategy; they need a business strategy that incorporates big data!” – Bill Schmarzo

I love starting my customer meetings with this statement. I want to immediately challenge my customers with how they determine the value of data.  Many organizations view data as a cost to be minimized.  These organizations view their data strategy as an activity independent of supporting the organization’s business strategy.  The result: Dracula Data.

Instead of developing your data strategy as an independent activity owned by IT, contemplate how your data strategy supports your business strategy with the customer, product and operational insights uncovered in the data. Organizations need a value engineering mindset that links their data strategy to the organization’s business initiatives (see Figure 1).    ... "  (Much more at the link)

Appian and Business Process

Happened to look at Appian which we used in the enterprise.

We used them for BPM (Business process management)  And we talked to them first around 2007.  Had some relationship to CACI, which does process simulation and optimization for the DOD as well.

Appian now does RPA (Robotic Process Automation), using 'Blue Prism',  an 'AI' type method.      See:  https://www.appian.com/platform/robotic-process-automation-rpa/ 

Read their Acquisition Management Overview:  https://www.appian.com/industries/public-sector/acquisition-management/

Assisting Visually Impaired Web Browsing

Screen reading plus voice assistance.   Good idea.

New Tool Makes Web Browsing Easier for the Visually Impaired 
University of Waterloo News
August 20, 2019

Researchers at the University of Waterloo in Canada, the University of Washington, and Microsoft have developed a tool that merges the best elements of voice assistants and screen readers to make free-form Web searches easier. The VERSE (Voice Exploration, Retrieval, and Search) tool allows people with visual impairments to get Web content quickly and easily. VERSE adds screen reader-like capabilities to virtual assistants, and allows other devices to serve as input accelerators to smart speakers. The researchers surveyed 53 visually impaired Web searchers, and found that more than half used voice assistants multiple times a day. Said Waterloo researcher Alexandra Vtyurina, "If people need more information, they can use VERSE to access other search verticals, for example, news, facts, and related searches, and can visit any article that appears as a search result."  .... " 

Data Labeling

We worked with both the crowdsourcing methods for this and automated methods. 

AI's New Workforce: The Data-Labeling Industry Spreads Globally
in Financial Times
By Madhumita Murgia

There is a growing international data-labeling industry that employs hundreds of thousands of workers in lower-income countries. Many small companies are forming parts of a so-called "artificial intelligence (AI) supply chain" helping to train algorithms that can interpret material including driving footage, search results, and photos for some of the world's largest multinational corporations. Companies are embracing AI as a way to automate decision-making and help drive new business opportunities, but first they must train their algorithms on millions of labelled examples. Said Leila Janah, founder and chief executive of data labeling vendor Samasource, "We work with a population usually coming from informal settlements, rural villages, so the chance to have a job that pays well, and gives you computer skills and exposes you to AI, it means people treat this very seriously." ....."

Papercraft Inspired Math

I had previously reported on the use of Origami and Kirigami for real problems,  here more out of Harvard:

Papercraft-inspired math turns any sheet into any shape
Algorithms would just have to determine when to make the right cuts.

By Jon Fingas, @jonfingas    in Engadget

You might not need exotic manufacturing techniques to produce custom-shaped objects. If Harvard scientists have their way, you could start with little more than a sheet and some math. They've created a math framework that borrows from the Japanese papercraft technique of kirigami (which uses strategic cuts to produce art) to transform any sheet into any shape. Effectively, it involves designing backwards -- the intended shape is the last part of the process. ... " 

Saturday, August 24, 2019

More on Imminent Audible Captioning

Recently have been reading/hearing long texts in Audible and Kindle,  usually non-fiction.   So gaining an appreciation for the difference in the way we utilize recorded knowledge in varying contexts.  Having the option of having it read to us is good, but seeing it in context provides better retention and integration.     And also has implications for accessibility.   Which leads to this new article in ArsTechnica, considerable additional discussion there:

Seven of the nation's top book publishers sued Amazon subsidiary Audible on Friday, asking federal courts to block the company from releasing a new feature called Audible Captions that's due out next month. The technology does exactly what it sounds like: display text captions on the screen of your phone or tablet as the corresponding words are read in the audio file.

The publishers argue that this is straight-up copyright infringement. In their view, the law gives them the right to control the distribution of their books in different formats. Audio is a different format from text, they reason, so Audible needs a separate license.  ......

The caption feature "is not and was never intended to be a book," Audible explained in an online statement following the lawsuit. "Listeners cannot read at their own pace or flip through pages as they could with a print book or eBook." Instead, the purpose is to allow "listeners to follow along with a few lines of machine-generated text as they listen to the audio performance."

"We disagree with the claims that this violates any rights and look forward to working with publishers and members of the professional creative community to help them better understand the educational and accessibility benefits of this innovation," Audible added.  ... "

Qualcomm Won't Have to Offer Patent Licenses Yet

Intriguing insight to antitrust vs patent licensing.  Note the embedded predictive aspect included here.  Predicting Qualcomm's income from patent licensing?

Qualcomm won't have to offer patent licenses to rivals, for now
A court has granted a partial reprieve from a US antitrust ruling.
 BY Jon Fingas, @jonfingas in Engadget

Qualcomm won't face the full consequences of the antitrust ruling, at least not right away. The Ninth Circuit Court of Appeals has granted a request to temporarily halt requirements that it both grant patent licenses to rivals and stop demanding patent licenses before customers can buy chips. The stay will only last as long as Qualcomm's appeal of the antitrust case wends its way through the courts, but Qualcomm was convinced the original decision "will be overturned."

The company claimed the reprieve was vital to investing in technologies as part of a "critical time of transition to 5G."

Of course, there's a more pragmatic factor behind the request: the ruling would have dramatically altered Qualcomm's existing patent strategy. Reuters noted that Qualcomm would have to renegotiate all of its current chip and patent deals, and any new deals would need to honor stricter requirements. Those could require extensive work and likely hurt Qualcomm's substantial income from patent licenses.   .... " 

Pfizer Using Mutiple Data Sources for Shopper Insight

Makes sense to get multiple sources, at very least to check the accuracy of predictions.  And inthis case because shoppers usually go to many places, tracking their behavior completely may require that.  But in practice than can be a luxury. Sometimes you may have to build data predictive models.  Or create data prediction with shopper lab experiments or crowdsourcing.

Pfizer relies on multiple data sources for better shopper insights
By Pat Lenius in Retailwire   (Much more at the link)
By mixing and matching data resources, Pfizer Consumer Healthcare, the maker of Advil, Centrum and other over-the-counter (OTC) brands, has been able to target shoppers more effectively and identify growth opportunities for its retailer customers.

“It’s all about marketing and personalization. It’s no longer one size fits all. Where is my customer shopping,” said Amy Joyce, director-Walmart shopper and category insights to activation for Pfizer Consumer Healthcare, at the 2019 Shopper Insights & Retail Activation conference in Chicago. “The data sources I use include Path to Purchase Institute, Mintel, WSL, Kantar Consulting.”

She said using multiple sources of data generates more tools and more information for omnichannel insights. By relying on these multiple data sources to look at emerging shoppers/consumers of its product categories, Pfizer discovered a $130 million opportunity for Retailer X via driving shopping trips and online spending by boomers, based on data from IRI and Numerator.

It’s not just where the dollars are going, but what they are buying at the competing store that proved to be helpful information. By using multiple sources of data, Pfizer was able to learn about the categories, brands and items those boomers were buying at the other stores. ..... '

Simple Statistics Types in one Picture

A good, nontechnical infographic that describes commonly used simple statistics.  Just enough to use with non-technical management and decision makers.  Make sure to follow up with examples from your own data to make the usage clear.

Descriptive vs. Inferential Statistics in One Picture  From DSC
Posted by Stephanie Glen 

This simple picture shows the differences between descriptive statistics and Inferential statistics.  ... '

Bold Bridge Advisors

New Affiliation:  Bold Bridge Advisors

Bold Bridge Advisors 

1. Clarify WHY, WHO, SO WHAT, before technology and solutions are defined.
2. Seek and speak truth, even when it hurts.
3. Assuming nothing. Listen, analyze, reframe, and confirm. 
4. Start small and focused, then scale. 
5. Be essential to every client's success.  ... 

More to follow.  

IBM Develops Cloud Services for Quantum Computers

More on the use and interaction of quantum computing with current needs, like secure cryptography.  Is likely to increasingly become an important issue.  Note the offer of a Quantum Risk Assessment.

From PRNewswire via Cision:

IBM Developing New Cloud Services and Technology to Help Keep Data Secured from Future Fault-Tolerant Quantum Computers

- New quantum risk assessment and subscription services available to clients

- IBM Cloud will begin to provide quantum-safe cryptography services on the public cloud in 2020

- IBM Research demonstrates world's first quantum computing safe tape drive prototype

- IBM donates quantum-safe cryptographic algorithms to open source community   

ARMONK, N.Y., Aug. 23, 2019 /PRNewswire/ -- Today at the Second Post-Quantum Cryptography Standardization Conference organized by the National Institute of Standards and Technology (NIST), IBM (NYSE: IBM) took a major step towards maintaining the highest level of security of its client's data and privacy in the future from fault-tolerant quantum computers. 

IBM took a major step today towards maintaining the highest level of security of its client’s data and privacy in the future from fault-tolerant quantum computers with the demonstration of the world’s first quantum computing safe tape drive prototype. Credit: IBM Research

IBM took a major step today towards maintaining the highest level of security of its client’s data and privacy in the future from fault-tolerant quantum computers with the demonstration of the world’s first quantum computing safe tape drive prototype. Credit: IBM Research

With today's news, IBM is announcing that it will begin to provide, what the industry would call, quantum-safe cryptography services on the IBM public cloud in 2020 and is now offering a Quantum Risk Assessment from IBM Security to help customers assess their risk in the quantum world. Additionally, IBM cryptographers have prototyped the world's first quantum computing safe enterprise class tape, an important step before commercialization.

IBM is also committed to making quantum-safe algorithms available through the open source community. As an industry, we can only become secure if new quantum-safe algorithms are tested, interoperable and easily consumable in common security standards. To this end, IBM is donating algorithms and support to a number of open source projects such as OpenQuantumSafe.org.   ... " 

Friday, August 23, 2019

Battery-Free Sensors Underwater with Piezoelectricity

Another example of new ways to add power sources.   I recall piezoelectric methods being suggested as gained from customers walking across a floor.  Harvesting electric power.   Too low power in that case, it turned out.   But it continues to be examined, here underwater.

A Battery-Free Sensor for Underwater Exploration
MIT News  By Rob Matheson
August 20, 2019

Researchers at the Massachusetts Institute of Technology (MIT) have developed a battery-free underwater communication system that uses near-zero power to transmit sensor data. The system makes use of the piezoelectric effect, in which vibrations in certain materials generate an electric charge, along with backscatter, a communication technique that transmits data by reflecting modulated wireless signals off an RFID tag and back to a reader. In the MIT system, a transmitter sends acoustic waves through water toward a piezoelectric sensor that has stored data. When the wave hits the sensor, the material vibrates and stores the resulting electrical charge, which the sensor uses to reflect a wave back to a receiver for decoding. Said MIT’s Fadel Adib, “Basically, we can communicate with underwater sensors based solely on the incoming sound signals whose energy we are harvesting.”  .... '

Russian Fedor Robot Assistant in the ISS

Much in the press this week.    Looks to be of real value based on the description. Unclear here if this is voice driven and other specifics.  Note it is communicating its activities, will be checking on that. Note also the previous post on 'robotic bees' in the ISS.

Russia Sends Its First Humanoid Robot into Space 
Agence France-Presse
August 22, 2019

Russia dispatched an unmanned spacecraft containing a life-size humanoid robot to the International Space Station (ISS), where it will learn skills for assisting astronauts. The robot Fedor (Final Experimental Demonstration Object Research) communicates its activities and progress via Instagram and Twitter accounts, and it will test newly-acquired manual skills in the ISS' microgravity environment. The Roscosmos Russian space agency's Alexander Bloshenko said such skills include "connecting and disconnecting electric cables [and] using standard items, from a screwdriver and a spanner to a fire extinguisher." Fedor mimics human movements, which allows it to remotely assist astronauts, and people on Earth, in executing tasks.  .... "

Alexa with Skill Flow Creation. And Beyond?

Alexa Dev announces a way to create skill flow for games, stories.  When I saw this I thought, could this also be used to develop skills based on business process flow?  Thinking that. Your thoughts?  If I think so I will make a proposal in that direction.

Create Story-Based Game Skills Faster with Skill Flow Builder    By Chris Morrow

We've built game skills ourselves, and have met with game studios to understand how we can help with creating game skills faster. Throughout the process, we discovered an opportunity to create a tool that is optimized for game skills with game development cycles in mind. We are excited to introduce Skill Flow Builder (SFB), a new tool that enables you to build story-based game skills faster, including interactive fiction, branching narratives, and role-playing games. Skill Flow Builder is now available to game skill creators in all locales (please note, Hindi isn't supported yet).

SFB complements tools like the Alexa Skills Kit (ASK) SDK, and provides an easy-to-use solution for the creation of skill flow and content by separating content creation from skill code. The tool has two components: The editor desktop application for content creators, and the VSCode extension for developers. Both components share a common SFB file format (.abc), which enables more efficient hand-offs between teams.

Superior Collaboration Between the Content and Development Teams:
SFB allows both the content and the development teams to focus on what they do best, and help increase productivity by minimizing dependencies that slow them down. Content teams can focus on quickly prototyping without having to rely on the development team every time they make content changes. In the meantime, development teams can focus on building differentiated features instead of having to change code for every content update.  .... " 

An Analysis of IOTA

Mentioned I was looking at the blockchain IOTA sometime back, was just pointed to this analysis that I had missed:   Has pointers to much more:

Analysis of IOTA   By Marvin Neuefeind in Medium

 One of the most popular coins, which is also dividing the community, is IOTA. IOTA is a Tangle based cryptocurrency which main purpose is to serve the economy, namely Internet of Things. In the following article we are going to conduct a complete Fundamental Analysis, which orientates on the guideline of our book ( Amazon.com: Cryptocurrency — A Trader’s Handbook: A Complete Guide On How To Trade Bitcoin And Altcoins eBook: Marvin Neuefeind, Marcin Kacperczyk: Kindle Store).

We will start by giving you a broad idea what IOTA is all about and then conclude to the core research and the additional research.

IOTA was the first cryptocurrency which utilized the Tangle technology. The Tangle is different from the traditional blockchain in which each block follows another in a certain order. Tangle on the other hand is completely confused as you can see in the picture below.  .... " 

Visions of the Future, Then and Now

Quite a considerable look at how future has been predicted, why were they so accurate? what sources can we look at today?    As a futurist myself, always seeking sources.   Read it:

Futurology: How a group of visionaries predicted today's world a century ago   by Max Saunders, The Conversation in Techexplore

From shamanic ritual to horoscopes, humans have always tried to predict the future. Today, trusting predictions and prophecies has become part of daily life. From the weather forecast to the time the sat-nav says we will reach our destination, our lives are built around futuristic fictions.

Of course, while we may sometimes feel betrayed by our local meteorologist, trusting their foresight is a lot more rational than putting the same stock in a TV psychic. This shift toward more evidence-based guesswork came about in the 20th century: futurologists began to see what prediction looked like when based on a scientific understanding of the world, rather than the traditional bases of prophecy (religion, magic, or dream). Genetic modification, space stations, wind power, artificial wombs, video phones, wireless internet, and cyborgs were all foreseen by "futurologists" from the 1920s and 1930s. Such visions seemed like science fiction when first published.

They all appeared in the brilliant and innovative "To-Day and To-Morrow" books from the 1920s, which signal the beginning of our modern conception of futurology, in which prophecy gives way to scientific forecasting. This series of over 100 books provided humanity—and science fiction—with key insights and inspiration. I've been immersed in them for the last few years while writing the first book about these fascinating works—and have found that these pioneering futurologists have a lot to teach us.

In their early responses to the technologies emerging then—aircraft, radio, recording, robotics, television—the writers grasped how those innovations were changing our sense of who we are. And they often gave startlingly canny previews of what was coming next, as in the case of Archibald Low, who in his 1924 book Wireless Possibilities, predicted the mobile phone: "In a few years time we shall be able to chat to our friends in an airplane and in the streets with the help of a pocket wireless set."  .... " 

Blockchain for Hotel Commissions

Another indication of IBM working strongly in this space.  Had not heard this particular kind of application before.  And also new to the hospitality space.

Travelport, IBM Collaborate on Blockchain for Hotel Commissions

Travelport, a business and consumer travel services provider, announced it is using IBM’s Hyperledger Fabric to guarantee commissions paid to travel agencies.

According to a statement released on August 20, the blockchain was designed with input from IBM, travel management company BCD Travel, and three unnamed hotel chains. The system aims to “put the lifecycle of a booking on the blockchain,” to reduce the amount of payment disputes.

In 2018, Travelport processed over $83 billion of travel spend over $2.4 billion in net revenue.

“Traveler modifications at property, no shows, and complimentary room nights are just a few examples that drive commission discrepancies which in turn generate escalations, cost, and revenue loss,” said Ross Vinograd, Travelport’s Senior Product Director.

“The traveler can modify their booking multiple times, leaving room for information to go missing. For example, if a traveler arrives and then extends a hotel stay, that information might not make its way back to us as booking data,” said Marwan Batrouni, Vice President of Global Hotel Strategy, BCD Travel. Additionally, blockchain will help close the “gaps” made by different payments systems.  ... " 

Thursday, August 22, 2019

Ultimate ID: Facial Recognition?

Where you would expect it, but the results are still less than perfect.  And where it is mostly likely to be spoofed for direct fraud. 

Facial Recognition Making Its Way in Banking    By AI Trends Staff

Facial recognition technology is making its way into the banking industry, used primarily for physical security and ID recognition.

A handful or startups have emerged to serve the niche, the largest being Yitu Technology, a company with some 200 employees based in Shanghai, according to a report in emerj. Started in 2012 by a founder with a PhD in statistics from the University of California, the company employs a number of machine learning researchers. The company makes the Yitu Dragonfly Eye Intelligent Security System.

Another is Cloudwalk Technology of China, which had raised $507 million as of September 2018. They have contracts with the Bank of China and Bank of Chongqing. The president has a PhD in electrical engineering from the University of Illinois- Urbana Champaign. In facial recognition, the company appears to be in startup mode with few data scientists and machine learning researchers employed.

Other startups include IntelliVision, which offers Face Recognizer, which can recognize a customer’s face as shown on a stored image, when the customer is trying to access their bank account from an ATM with a camera, for example. If the customer’s photo is not stored in the bank’s database, the ATM can record the persons face and associate it with the account being accessed. IntelliVision has raised $6 million.

FaceFirst is offering software of the same name for access control using machine vision. The system is able to authorize identities, deliver mobile notifications to the security team, and recognition priority customers so that they receive the appropriate preferences. The companies say clients can integrate the software with existing image databases and with video footage. FaceFirst has raised $9.5 million in investment capital.  ... "

Good Data Science Examples

A number of good inspirational  examples.  Needs more tech details, but still useful.

Remarkable Applications of Data Science
Posted by Sudhanshu Ahuja in DSC

We are living in a time of slow yet steady insurgence of data science and AI in our lives. It spans more industries than we’d expect.

Over the past decade, Data Science has stretched out into almost every industry. Form industries like Automobiles and Healthcare to Finance as well as the Gaming Sector. It plays a significant part in the government sectors.  So here are some instances of the most impactful applications of data science.

Project Soli

One of the most significant technological transitions was the switch from buttons to touch screen. It transformed the operation of phones and computers. However, we're moving on to the next big thing, touch-free phones.

Approved by the federal communications commission (FCC), Google has started working upon "Project Soli”. Project Soli is a system that is designed to track hand movements from a millimetre away by using miniature motion sensor radar. This system will enable people to control devices from TV's to smartphones through gesture control. 

How does it work?

Soli’s sensor technology emits electromagnetic waves in a broad beam. If an object falls within the radius of the beam, it scatters the energy of the electromagnetic waves. This causes a certain amount of the energy to reflect at the radar antenna. Elements such as energy, time delay and frequency shift within the reflected signal capture important information about the characteristics and dynamics of the object. 

The radar technology uses high-frequency radio waves to detect moving objects which, according to Google, is profoundly more accurate than gesture tracking cameras. The sensor chips in Soli are capable of capturing up to 10,000 frames per second. .....  "

Webinar: Driving Business Outcomes with AI

Leaders in the area of machine learning and AI talk goals and workflow:

On-Demand Webinar

Enterprises understand that driving business outcomes with machine learning and AI will soon become a critical driver for success. Yet, many struggle to connect together siloed data pipelines and artisanal data science experiments into agile and repeatable processes to drive scale and impact.

Hear Nielsen’s Chief Research Officer Mainak Mazumdar and Forrester Senior Analyst guest speaker Kjell Carlsson, PhD share experiences and perspectives into unifying data science and engineering with business needs. Learn how teams operationalize machine learning models and AI more rapidly, with insights into:

- Improving model development performance from 1 week to less than 2 hrs 
- Transforming data science workflows and deepening team collaboration
- Accelerating the end-to-end machine learning lifecycle  .... " 

What will Quantum Computing Mean?

A largely non-technical view of what Quantum Computing will mean.  Our own minor investigations looked at how very complex combinatorial problems (problems with many, many solutions) that might then be solved with these methods more easily.   These problems also relate to things like cryptography.

You Won't See Quantum Internet Coming   By Ryan F. Mandelbaum   in Gizmodo.

 The quantum internet is coming sooner than you think—even sooner than quantum computing itself. When things change over, you might not even notice. But when they do, new rules will protect your data against attacks from computers that don’t even exist yet.

Despite the fancy name, the “quantum internet” won’t be some futuristic new way to navigate online. It won’t produce any mind-blowing new content, at least not for decades. The quantum internet will look more or less the same as the internet you’re using now, but scientists and cryptographers hope it could provide protection against not only theoretical threats but also those we haven’t dreamed up yet.

“The main contribution of a quantum internet is to allow encrypted communication in a perfectly secure fashion that can’t be broken in principle, even if in the future we develop a more fundamental theory of physics,” Ciarán Lee, a researcher at University College, London, explained to Gizmodo. In short, the quantum internet would hopefully protect us from planned new computers, along with every theoretical computer for the foreseeable future.

So what’s the quantum internet? It’s what happens when you apply the weird rules of quantum mechanics to the way computers communicate with one another.  ... " 

Contract Languages of Distributed Ledgers

Quite worthwhile piece in the 'smart contract'  blockchain space,  in Financial industry,  examining:

In ACM Queue: 

  Download PDF version of this article PDF August 19, 2019
Volume 17, issue 3
Case Study
DAML: The Contract Language of Distributed Ledgers
A discussion between Shaul Kfir and Camille Fournier

When Shaul Kfir cofounded Digital Asset in 2014, he was out to prove something to the financial services industry. He saw it as being not only hamstrung by an inefficient system for transaction reconciliation, but also in danger of missing out on what blockchain technology could do to address its shortcomings.

Since then, Digital Asset has gone to market with its own distributed-ledger technology, DAML (Digital Asset Modeling Language). And that does indeed take advantage of blockchain—only not in quite the way Kfir had initially intended. He and Digital Asset ended up taking an engineering "journey" to get to where they are today.

Kfir readily admits his own background in cryptography and cryptocurrency—both as a researcher (at Technion and MIT) and as a cryptocurrency entrepreneur in Israel—had more than just a little to do with the course that was originally charted. As for lessons learned along the way, Camille Fournier, the head of platform development for a leading New York City hedge fund, helps to elicit those here. She brings to the exercise her own background in distributed-systems consensus (as one of the original committers to the Apache Zookeeper Project) and financial services (as a former VP of technology at Goldman Sachs).   .... "