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Tuesday, December 31, 2019

Decade of Voice Assistants

General but simplified history, worth a look. Platforms have been constructed, with lots of users.  Now how will they filled with meaningful assistance? How close to general AI will that evolve to?  How will it change the workplace and home?

The Decade of Voice Assistant Revolution
 By Eric Hall Schwartz in Voicebot.ai

The last 10 years have utterly transformed how people think about voice technology. From limited uses in just a few outlets, voice assistants are now integrating into every part of people’s lives. To encapsulate everything that has happened in ten years, we’ve picked a notable event from each year of the last decade to highlight and show how they marked a milestone in the way voice assistants have evolved and spread.  .... " 

Retail Technology Updating

Always good to take a look at how existing tech will coexist with emerging.

Retailers take on massive legacy system challenges one module at a time   by Andrew Blatherwick

There’s a sea change underway in how retailers are thinking about technology solutions. Increasingly, in meetings with even the larger retailers, I hear from executives who are no longer interested in major system replacements. Instead, they’re looking at smaller point solutions to drive change within their businesses. Of course, the choice between best of breed and enterprise systems is not a new question. What is new, though, is a trend toward implementing in parts rather than as a whole, even within best of breed solutions.

Retailers today are highly focused on fast return, and this is most easily accomplished by reducing the scope of the problem at hand. Enterprise resource planning (ERP) implementations present an immense strategic challenge because they touch almost every part of a business. For a successful implementation, a large number of internal stakeholders must buy into the project’s vision, then agree to move in the same direction at the same pace. It’s not hard to understand why ERP projects can be difficult to execute.

A focused project, rolled out in phases, can still affect many departments and stakeholders. However, these projects are far easier to strategize and implement. Companies are able to drill down on an exact need and address it surgically rather than compromising on their vision across the board. ... "

Video: Interpretable Machine Learning

I mentioned this article in an earlier post, where I discuss in more detail, here here a short video introduction.

Techniques for Interpretable Machine Learning from CACM on Vimeo.

Mengnan Du and Xia Hu discuss "Techniques for Interpretable Machine Learning," a Review Article in the January 2020 CACM. ... 

MIT CSAIL Sees Thorough Walls

Mentioned once before, continues to draw interest.

A seemingly very radical capability, consider implications privacy and otherwise.  Again caution must be placed to know how directly practical and easy this is to do.  Demos are easy to do.

Artificial intelligence senses people through walls
Wireless smart-home system from the Computer Science and Artificial Intelligence Laboratory could monitor diseases and help the elderly “age in place.”

By Adam Conner-Simons | Rachel Gordon | CSAIL

X-ray vision has long seemed like a far-fetched sci-fi fantasy, but over the last decade a team led by Professor Dina Katabi from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has continually gotten us closer to seeing through walls.

Their latest project, “RF-Pose,” uses artificial intelligence (AI) to teach wireless devices to sense people’s postures and movement, even from the other side of a wall.

The researchers use a neural network to analyze radio signals that bounce off people’s bodies, and can then create a dynamic stick figure that walks, stops, sits, and moves its limbs as the person performs those actions.  ... "

Amazonification of Supply Chains

Driven on the consumer side by strong and rising expectations of in-stock and quick delivery.

The Amazonification of Supply Chains
December 30, 2019
Roddy Martin, In Supplychain Brain

In the past, suppliers such as those in the pharma industry stockpiled hundreds of days’ worth of inventory buffer to avoid shortfalls in patient demand. This was “affordable” with 80% margins, but it’s not the case in today’s competitive global marketplace. High margins are no longer guaranteed, and supply chains are responding by pivoting to end-to-end, customer-centric, demand-driven network operating models. In today’s world, business value comes from more than just measuring year-over-year reductions in supply-chain costs.

Modern-day logistics service providers are transforming their supply chains with new customer-centric processes, including demand sensing, demand insight analyses, and promotions capabilities. Contrast that with the billions of dollars spent on both on-premise and cloud-based enterprise resource planning (ERP) systems, which remain largely supply-driven, siloed, and disconnected across the ecosystem — particularly within healthcare.  .... " 

Assigning Machines to Tasks

Interesting question when we start to share work.  How is it most effectively done?   Thoughts from Kellogg linked to at the short Podcast linked to below.   But  I would offer that machines are still too simplistic to do this well.   Until now we have just applied them where they work best.

Podcast: How You Should Divvy Up Work between People and Machines

On this episode of The Insightful Leader: strategies for building a happier, more productive workplace.

Machines are taking on more and more new responsibilities at work. But are some jobs better left to humans?

On this episode of The Insightful Leader, Adam Waytz, associate professor of management and organizations at Kellogg and author of the book The Power of Human: How Our Shared Humanity Can Help Us Create a Better World, offers three guidelines for how managers can play to the unique strengths of both people and technology.    ... " 

Monday, December 30, 2019

Techniques for Interpretable Machine Learning

Very good piece I am reading in the January CACM.  The most important aspect of considering AI-ML type models in the real world.  Good introduction, useful key insights, but ultimately quite technical.  Bottom line is that research is still needed and 'Model explanation and surprising artifacts are often two sides of the same coin'.  Complex models may extract and codify biases and other 'artifacts' of metadata from training data.   Test and re-test under varying context.  Maintenance is more that just tracking performance over time.  Consider embedded models of risk.

I highly recommend subscribing to CACM if you are technically involved.

Techniques for Interpretable Machine Learning
By Mengnan Du, Ninghao Liu, Xia Hu

Communications of the ACM, January 2020, Vol. 63 No. 1, Pages 68-77

Machine learning is progressing at an astounding rate, powered by complex models such as ensemble models and deep neural networks (DNNs). These models have a wide range of real-world applications, such as movie recommendations of Netflix, neural machine translation of Google, and speech recognition of Amazon Alexa. Despite the successes, machine learning has its own limitations and drawbacks. The most significant one is the lack of transparency behind their behaviors, which leaves users with little understanding of how particular decisions are made by these models. Consider, for instance, an advanced self-driving car equipped with various machine learning algorithms does not brake or decelerate when confronting a stopped firetruck. This unexpected behavior may frustrate and confuse users, making them wonder why. Even worse, the wrong decisions could cause severe consequences if the car is driving at highway speeds and might ultimately crash into the firetruck. The concerns about the black-box nature of complex models have hampered their further applications in our society, especially in those critical decision-making domains like self-driving cars.

Interpretable machine learning would be an effective tool to mitigate these problems. It gives machine learning models the ability to explain or to present their behaviors in understandable terms to humans,10 which is called interpretability or explainability and we use them interchangeably in this article. Interpretability would be an indispensable part for machine learning models in order to better serve human beings and bring benefits to society. For end users, explanation will increase their trust and encourage them to adopt machine learning systems. From the perspective of machine learning system developers and researchers, the provided explanation can help them better understand the problem, the data and why a model might fail, and eventually increase the system safety. Thus, there is a growing interest among the academic and industrial community in interpreting machine learning models and gaining insights into their working mechanisms.

Interpretable machine learning techniques can generally be grouped into two categories: intrinsic interpretability and post-hoc interpretability, depending on the time when the interpretability is obtained.23 Intrinsic interpretability is achieved by constructing self-explanatory models which incorporate interpretability directly to their structures. The family of this category includes decision tree, rule-based model, linear model, attention model, and so on. In contrast, the post-hoc one requires creating a second model to provide explanations for an existing model. The main difference between these two groups lies in the trade-off between model accuracy and explanation fidelity. Inherently interpretable models could provide accurate and undistorted explanation but may sacrifice prediction performance to some extent. The post-hoc ones are limited in their approximate nature while keeping the underlying model accuracy intact.  ... "

Personality Detection by Autonomous Vehicles

More on personality determination to be used for autonomous vehicles.  Or any IOT device?  While it would appear this would be very useful, it leads to some kinds of private data, like behavioral personality, which could further be used to predict things that could be proxies for criminal behavior.

If I can quickly determine that a person drives erratically, say by observation, I would avoid them.  But I imagine this would likely be objected to as too deeply personal to be determined by an AI.   As we continue to do this kind of tagging with AI, expect more of this.

Predicting People's Driving Personalities
MIT News   By Adam Conner-Simons

A team led by researchers at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL) developed a system that classifies drivers' behavior, in order to determine whether autonomous vehicles (AVs) can be programmed to gauge other drivers' personalities in order to predict other vehicles' behaviors. The researchers employed social value orientation to quantify a person's selfishness or cooperativeness, and mapped out real-time driving trajectories for driverless vehicles based on that measurement. The researchers designed and tested an algorithm in scenarios of merging lanes and making unprotected left turns, and demonstrated that they could better predict other cars' behaviors. CSAIL's Wilko Schwarting said, "Creating more human-like behavior in autonomous vehicles (AVs) is fundamental for the safety of passengers and surrounding vehicles, since behaving in a predictable manner enables humans to understand and appropriately respond to the AV's actions."

Geometrically: What Should You Read Next?

Classifying and suggesting documents that point to our goals.  An old problem, but now being done with new tools.   'Geometric Data Processing'  an interesting term,  see more on that here"Our group studies geometric problems in computer graphics, computer vision, machine learning, optimization, and other disciplines" 

Finding a good read among billions of choices
As natural language processing techniques improve, suggestions are getting speedier and more relevant.

Kim Martineau | MIT Quest for Intelligence
With billions of books, news stories, and documents online, there’s never been a better time to be reading — if you have time to sift through all the options. “There’s a ton of text on the internet,” says Justin Solomon, an assistant professor at MIT. “Anything to help cut through all that material is extremely useful.”

With the MIT-IBM Watson AI Lab and his Geometric Data Processing Group at MIT, Solomon recently presented a new technique for cutting through massive amounts of text at the Conference on Neural Information Processing Systems (NeurIPS). Their method combines three popular text-analysis tools — topic modeling, word embeddings, and optimal transport — to deliver better, faster results than competing methods on a popular benchmark for classifying documents.

If an algorithm knows what you liked in the past, it can scan the millions of possibilities for something similar. As natural language processing techniques improve, those “you might also like” suggestions are getting speedier and more relevant.   .... " 

Smart Contracts and FMCG

A point by point set of examples, includes some examples such as what Wal-Mart is doing.   Biggest possibility I see is the sharing of operational data between retailers and suppliers to assure quality and future predictive supply and demand measures.  Other possibilities?   The better integration of data sharing ... ?

How Will Blockchain Smart Contracts affect the FMCG Sectors?
Kuldeep Kundal  in CustomerThink

Blockchain, which acts as the foundation for digital currencies like Bitcoin and other cybersecurity systems is receiving growing media attention. Depending on a distributed record system, where every transaction is logged for all related and authorized stakeholders to see, it is perceived as a conceivable way of strengthening trust and security and fast-tracking business processes, serving to remove the human component. Many administrations, tech moguls and industries are beginning to try out blockchain technology.

Smart contracts are self-executing contracts in which the conditions of the agreement between buyer and seller are clearly written into lines of code. The code and the agreements enclosed within are stored across a distributed, decentralized blockchain network.

Businesses are looking at ways to automate transactions to make them smoother, more efficient, and more secure for all parties, and it looks like blockchain and smart contracts are viable solutions.

Smart contracts development enable trusted transactions and agreements to be implemented among different, anonymous parties without the necessity of any central authority, legal structure, or external enforcement system. They make sure transactions visible, clear, and unalterable. .... " 

Bring Blockchain Undertanding into Physical World

Fascinating to see how the emergence of new tech is quickly tried against problems, and older metaphors are used to improve understanding. 

Bringing the Blockchain into the Physical World
Lancaster University
July 10, 2019

Computer scientists at the Universities of Lancaster and Edinburgh in the U.K., and the Universiti Teknologi MARA in Malaysia, have developed a kit containing everyday objects that can help people understand how digital blockchains work. The kit, known as BlocKit, includes items such as plastic tubs, clay discs, padlocks, envelopes, sticky notes, and battery-powered candles, which fulfill the roles of different parts of the blockchain, to make it easier to understand how it works. Said University of Lancaster researcher Corina Sas, "We received very positive feedback from the people who used the kit in our study and, interestingly, we found that the BlocKit can also be used by designers looking to develop new services based around blockchain, such as managing patients' health records for example."

Reconstructing Spoken Words from NonHuman Brains

Fascinating challenge.   Implications for future understanding of animal brains and human speech perception.

Researchers Reconstruct Spoken Words as Processed in Nonhuman Primate Brains
Brown University
By Kevin Stacey

Researchers at Brown University used a brain-computer interface to reconstruct English words from neural signals recorded in the brains of rhesus macaque monkeys. The researchers recorded the activity of neurons in their brains while the primates listened to recordings of one- or two-syllable individual English words and macaque calls. The team processed the neural recordings using algorithms designed to recognize neural patterns associated with particular words; then, the neural data was translated into computer-generated speech. The research showed that recurrent neural networks produced the highest-fidelity reconstructions compared to other tested algorithms. Brown's Arto Nurmikko said, “The same microelectrodes we used to record neural activity in this study may one day be used to deliver small amounts of electrical current in patterns that give people the perception of having heard specific sounds.”)."  ... " 

Sunday, December 29, 2019

Enabling AI in Hospitals for Training

Distributed learning method. deep learning on the edge to provide privacy.

Nvidia uses federated learning to enable AI in hospitals

Nvidia Corp. wants to make artificial intelligence a staple of the healthcare industry with a new distributed learning technique announced today that can train machine learning models while protecting patient privacy.

AI holds great promise, but for industries such as healthcare where data privacy is of paramount importance, tapping into that potential is a big challenge. The problem is that any data that might be useful to train models is almost always confidential, which means it can’t be shared with technology partners.

Nvidia reckons it can solve this problem with its new Clara Federated Learning technique, which ensures that patient data remains within healthcare providers’ systems at all times.

Clara FL is a reference application for distributed AI training that’s designed to run on Nvidia’s recently announced EGX intelligent edge computing platform. Those systems are capable of performing deep learning training locally at the “network edge,” where the data resides, without moving it. .... " 

Smarter Offices with IOT

Very much makes sense to integrate further facilities management.  Add more elements of autonomy.

Increasing Business ROI with IoT in Facilities Management
By Michael Georgiou  in ReadWrite / 30 Nov 2019 / IoT
IoT in facilities management
Thanks to the advanced technologies, the idea of smart offices is now becoming more trendier than ever. It’s just a matter of time until the majority of businesses will have intelligent offices. As the workplaces are getting smarter, the one thing that remains obsolete is the way facility management companies operate. Here is increasing business ROI with IoT in facilities management.

Keeping various supplies in check is a tedious job for busy offices. That’s why often such non-core tasks are outsourced to facilities management companies. Today’s tech-heavy environment, offices still have to make calls or send emails to their facilities manager to get the issues resolved.

Considering the fierce competition, FM business owners can’t simply afford to keep offices waiting. Enter the IoT (Internet of things). IoT is a network of physical devices that collect and share data over the Internet.

Using IoT, facilities management companies can drastically improve their efficiency, customer relationship, and business ROI. But, how exactly IoT benefits facilities managers to improve their business bottom line? In this guide, we’re going to discuss this in detail, but let’s first understand the concept of IoT ..... "

An IOT Security Crisis?

Well hardly usual, in this case the device was placed in a bedroom and used to communicate. Hardly its stated purpose.   Any surveillance camera could have been used that way.  Its like the alleged warning on a lawn mower suggesting it should not be used to trim hedges.  By this argument the Net is the most dangerous thing of all.

Why Ring Doorbells Perfectly Exemplify the IoT Security Crisis  in Wired.
A new wave of reports about the home surveillance cameras getting hijacked by creeps is painfully familiar.

There's been a lot of creepy and concerning news about how Amazon's Ring smart doorbells are bringing surveillance to suburbia and sparking data-sharing relationships between Amazon and law enforcement. News reports this week are raising a different issue: hackers are breaking into users' Ring accounts, which can also be connected to indoor Ring cameras, to take over the devices and get up to all sorts of invasive shenanigans.

In Mississippi, a Tennessee news channel reported on Tuesday about a case where hackers hijacked an indoor Ring camera one family had placed in a bedroom and used it to talk to three young girls. And as Motherboard first showed, there are tools available online for breaking into Ring accounts by strategically guessing the login credentials. When account thieves record enough juicy audio from people's Ring feeds, there's even a podcast where they can broadcast it.  ..... "

Assembling, Using, Visual Knowledge

We also looked at ways to assemble visual information, for use in training, communication, archiving, data.    And at patterns in that data that wold make it more useful.   One thing that came up was how to augment it to make it most useful to the largest group.  A recognition of it as an asset.  And the need for related metadata.

NBA Teams Enhancing Fan Experience with High-Tech Replays
ABC News
Charles Odum
November 15, 2019

Six National Basketball Association (NBA) teams are implementing 360-degree video replays in their arenas to augment the fan experience. The technology allows fans to review shots and gameplay by changing the angle, similar to video-game players' use of all-angle replays. The teams partnered with technology provider Intel to install 38 5K video cameras in their arenas, which work in concert to bring the replays to in-game video boards, TV broadcasts, and fans' devices via social media. The replays not only enhance the fan experience, but also can help coaches and scouts refine player assessments. Joe Abercrombie with the NBA's Atlanta Hawks called the technology “the wave of the future,” adding that it is “one more thing to give people a reason to come” to watch games at the arenas.

See:  Northeastern University Institute for Experiential AI  ...  

Google Seeks Patent for ML Navigation Solution

Machine Learning patent for a particular application by Google:

Google seeks patent for ML model speed prediction to improve navigation services
The prediction of the speed of the vehicle can be used to predict a travel time, or recommend a route to the user.

By: Sajan C Kumar in FinancialExpress

In a bid to further strengthen its navigation services, American tech major Google has moved the Indian patent office seeking a patent to its new machine learning (ML) model for prediction of the speed of vehicles on particular routes, which will provide users the accurate travel time. ... " 

Saturday, December 28, 2019

Comments in this Blog

All comments in this blog need to be approved before publishing.    In general I won't permit or usually answer a comment unless it is relevant and  lends itself to the general content of this blog.   I reserve editorial additions.  I won't approve pure advertisements.   You can ask questions or suggest things in the comments.  Usually open to ideas.   If you want a personal answer leave me an address, I will not reveal the address in the blog.    Blog posts since 2005:     20,256    Reads: 2.33 Million

China Blockchain Dominance

Previously noted.  What are the consequences?  Fewer intermediaries for sharing key data sources and analyses.

China’s Blockchain Dominance: Can the U.S. Catch Up?

By all counts, China is leading the world in the use and development of blockchain technology. It has far and away filed the most patents related to blockchain in the world and some of the biggest names in the blockchain and cryptocurrency community are Chinese firms. What’s more, blockchain is also a national priority: The Chinese State Council included its development in the nation’s 13th Five-Year Plan. And last year, President Xi Jinping said China seeks to lead in innovation worldwide, citing blockchain, AI, the Internet of Things and other technologies as the driving forces.

This national focus was confirmed by Chinese executives and entrepreneurs involved in blockchain endeavors at the recently held invitation-only roundtable discussion on blockchain hosted by the Penn Wharton China Center. Two-thirds of blockchain-related patents come from Chinese firms or entities, one participant said, adding that China also holds 72% of the mining power for bitcoin. “China is very pro-blockchain technology and the government has positioned itself to dominate the blockchain space in the world.”

For the West, however, there is a bit of a conundrum about this focus. Blockchain, the underlying ledger technology of the bitcoin cryptocurrency, was created in 2009 by a mysterious entity called Satoshi Nakamoto to be a decentralized system. That means there is no central authority in control, which flies in the face of the current political system in China. But comments on China Central Television by Chinese official Xu Hao clarify the party’s stance: Blockchain in China is not about decentralization but “de-intermediarization. There is no way to get rid of the center.”   ... "

Your Data is Shared and Sold

Further look at personal data and its use and regulations.

Your Data Is Shared and Sold…What’s Being Done About It?
Oct 28, 2019 Europe, North America

Earlier this month, California Gov. Gavin Newsom signed into law amendments to the California Consumer Privacy Act (CCPA), the most sweeping state data privacy regulations in the country. The law, which takes effect on Jan. 1, regulates how data is collected, managed, shared and sold by companies and entities doing business with or compiling information about California residents. Some observers contend that because no business would want to exclude selling to Californians, the CCPA is de facto a national law on data privacy, absent an overarching federal regulation protecting consumer information.

“The new privacy law is a big win for data privacy,” says Joseph Turow, a privacy scholar and professor of communication at the Annenberg School for Communication at the University of Pennsylvania. “Though it could be even stronger, the California law is stronger than anything that exists at the federal level.” Among other stipulations, the CCPA requires businesses to inform consumers regarding the types of personal data they’ll collect at the time they collect it and also how the information will be used. Consumers have the right to ask firms to disclose with whom they share the data and also opt out of their data being sold.

The CCPA comes on the heels of the EU’s General Data Protection Regulation (GDPR), which took effect in May 2018. According to the United Nations Conference on Trade and Development, 107 countries have data privacy rules in place including 66 developing nations. In the U.S., there was a “significant” increase in data privacy bills being introduced this year, with at least 25 states and Puerto Rico starting such legislation, according to the National Conference of State Legislatures. Notably, this bill count doesn’t include related legislation on topics such as cybersecurity.  .... "

AI Improves the Way Humans Think

After reading this a few times I wondered.   Because we can use an AI to explore ideas more quickly? Things that wold have taken more time to examine?

Mind meld: Artificial intelligence is improving the way humans think

When AIs and humans work together they discover superior solutions to the world’s problems that would elude either working alone. Together, they will change the very process of thinking

By Douglas Heaven

IKE other human champions facing a machine opponent, Grzegorz “MaNa” Komincz rated his chances. “A realistic goal would be 4-1 in my favour,” he told an interviewer before the match.

One of the world’s best players of video game StarCraft II, Komincz was at the height of a successful esports career. Artificial intelligence company DeepMind invited him to face its latest AI, a StarCraft II-playing bot called AlphaStar, on 19 December 2018.

Komincz was expected to be a tough opponent. He wasn’t. After being thrashed 5-0, he was less cocky. “I wasn’t expecting the AI to be that good,” he said. “I felt like I was learning something.”

It was just the latest in a series of unexpected victories for machines that stretch back to chess champion Garry Kasparov’s 1997 defeat by IBM’s Deep Blue. In 2017, another of DeepMind’s AIs, AlphaGo Master, beat the world number one Go player a decade before most researchers predicted it would be possible. The company’s AIs then mastered chess and StarCraft – a game played with dozens of different pieces with hundreds of moves a minute.

But this isn’t just a case of humans being humbled by superhuman AI. The real story is that each win gives us a glimpse of how AIs will make us superhuman too. That’s because thinking is set to become a double act. Working together, humans and AIs will bounce ideas back and forth, each guiding the other to better solutions than would be possible alone.  .... '

(Requires subscription, sorry,  but I liked the premise)

Read more: https://www.newscientist.com/article/mg24332440-700-mind-meld-artificial-intelligence-is-improving-the-way-humans-think/#ixzz5yOTMjYzB

Hiding Cryptocurrency Transactions

Addressing visibility of transactions.

Some crypto-criminals think jumping across blockchains covers their tracks. Big mistake.
A popular cryptocurrency service that may appear to enhance anonymity actually doesn’t, according to new research.     by Mike Orcutt via Technologyreview

Tracing Transactions Across Cryptocurrency Ledgers
Haaroon Yousaf, George Kappos, and Sarah Meiklejohn
University College London, Usenix

One of the defining features of a cryptocurrency is that its ledger, containing all transactions that have ever taken place, is globally visible. As one consequence of this degree of transparency, a long line of recent research has demonstrated that — even in cryptocurrencies that are specifically designed to improve anonymity— it is often possible to track money as it changes hands, and in some cases to de-anonymize users entirely. With the recent proliferation of alternative cryptocurrencies, however, it becomes relevant to ask not only whether or not money can be traced as it moves within the ledger of a single cryptocurrency, but if it can in fact be traced as it moves across ledgers. This is especially pertinent given the rise in popularity of automated trading platforms such as ShapeShift, which make it effortless to carry out such cross-currency trades. In this paper, we use data scraped from ShapeShift over a thirteen-month period and the data from eight different blockchains to explore this question. Beyond developing new heuristics and creating new types of links across cryptocurrency ledgers, we also identify various patterns of cross-currency trades and of the general usage of these platforms, with the ultimate goal of understanding whether they serve a criminal or a profit-driven agenda.  .... '

MIT Model Forecasts Business Financials

If real, here is something of considerable value ... Note 'Belief Propagation' .... which we tested for things like predicting future product sales in varying context.  Looking more closely.

Model Beats Wall Street Analysts in Forecasting Business Financials
MIT News
By Rob Matheson

Massachusetts Institute of Technology (MIT) researchers have developed an automated model that significantly outperforms humans in predicting business sales using only anonymized weekly credit card transactions and three-month earnings reports. The researchers used the model to predict quarterly earnings of more than 30 companies, and found that it outperformed the combined estimates of expert Wall Street analysts on 57% of predictions. The human analysts had access to any available private or public data and other machine learning models, while the MIT model used a very small dataset of the two data types. The researchers used a variation of the standard inference algorithm, called Kalman filtering or Belief Propagation. This technique uses data measurements observed over time, containing noise inaccuracies, to generate a probability distribution for unknown variables over a designated timeframe .... " 

Friday, December 27, 2019

Russia Unplugs Its Domestic Internet

Now What?  Implications?  Note mention of how successful such an attempt might be.  One-way or both?

Russia Announces 'Successful Test' of Its Unplugged Internet
Jane Wakefield in the BBC
December 24, 2019

Russia's Ministry of Communications announced a successful test of a nationwide alternative to the Internet and claimed ordinary users did not detect any changes. The project entails restricting the points at which Russia's version of the Internet connects to its global counterpart, giving the government more control over citizens' accessibility. The effort also involves obstructing or regulating data transmission via undersea cable or nodes through cooperation of domestic Internet service providers; Russia then would have to develop an alternative system. Observers fear this could spark similar moves by authoritarian regimes and repress free speech, although Justin Sherman at the New America think tank said success is not guaranteed. Said Sherman, "Without more information about this test ... it's hard to assess exactly how far Russia has progressed in the path towards an isolatable domestic Internet."  ... '  

XAI: Google Explainable AI as a Service

Google takes on Explainable AI, try it free at the link ... Note in contrast IBM's Explainability Toolkit.  Now ask explainability of what, to whom?  Further KDNuggets has a good view of this as 'explainable AI as a service'.

Understand AI output and build trust

Explainable AI is a set of tools and frameworks to help you develop interpretable and inclusive machine learning models and deploy them with confidence. With it, you can understand feature attributions in AutoML Tables and AI Platform and visually investigate model behavior using the What-If Tool. It also further simplifies model governance through continuous evaluation of models managed using AI Platform.

Design interpretable and inclusive AI

Build interpretable and inclusive AI systems from the ground up with tools designed to help detect and resolve bias, drift, and other gaps in data and models. AI Explanations in AutoML Tables and AI Platform provide data scientists with the insight needed to improve data sets or model architecture and debug model performance. The What-If Tool lets you investigate model behavior at a glance.

Simple and fully managed

Deploy AI with confidence

Grow end-user trust and improve transparency with human-interpretable explanations of machine learning models. When deploying a model on AutoML Tables or AI Platform, you get a prediction and a score in real time indicating how much a factor affected the final result. While explanations don’t reveal any fundamental relationships in your data sample or population, they do reflect the patterns the model found in the data. .... "

Definitions for Use Cases of Blockchains

Useful simple user case examples, definitions, Major Players and cautions:

Understanding Blockchain Basics and Use Cases in Infoq

Key Takeaways:

Blockchains can be either public or private, permissioned or trustless
IBM Hyperledger and R3 Corda are two of the most widely used enterprise blockchains
Deployment of real solutions is still limited and patchy
The space is continuing to evolve and is in its early stages
Enterprise adoption is still cautious
Navigating the blockchain space can be very challenging.
A large number of articles have been written about the subject, many of which are filled with a large amount of hot air and hype, as well as specialist technical and other jargon.

In this article, we will explain the difference between the two major branches of blockchain projects (public and private) as well as some fundamental technical terms related the area.
This will allow us to address a fundamental question in the current discussion of blockchains and related solutions: What are the valid use cases for using a public, trustless blockchain vs a distributed private ledger vs a traditional database?  ... "

Procter Sponsors Video Game Competition

A new kind of effort by big CPG to my knowledge, course Gillette has been sponsoring sports for somet ime.

Gillette parent boosts esports sponsorship via video game competition  in BizJournals

Gillette parent company Procter & Gamble is elevating its presence in electronic sports via a sponsorship deal involving gaming tournaments with more than $3 million in prize money. The sponsorship is intended to drive engagement and connect the Gillette brand with younger audiences through esports and soccer..... "

Learn a task by Reading About it

Chess, analyzed from a description?  Research yes, but mastery takes experience.

Artificial Intelligence / Machine Learning inTechnology Review.
Instead of practicing, this AI mastered chess by reading about it
Machines that appreciate “brilliant” and “dumb” chess moves could learn to play the game—and do other things—more efficiently.
by Will Knight

Chess fans love nothing more than discussing a masterful sacrifice by Bobby Fischer or an ingenious line of attack from current world champion Magnus Carlsen. It turns out that this chatter could help AI programs learn to play the game in a new way. One day, the same technique could allow machines to use the emotional content of our language to master various practical tasks.

The chess algorithm, called SentiMATE, was developed by a team of researchers at University College London. It evaluates the quality of chess moves by analyzing the reaction of expert commentators.

The team analyzed the text of 2,700 chess game commentaries available online. They pruned out commentary that didn’t relate to high-quality moves, and examples that were too ambiguous. Then they used a special type of recurrent neural network and word embeddings (a mathematical technique that connects words on the basis their meanings), trained on another state-of-the-art model for analyzing language.

AI has recently made significant progress in parsing language. For example, an algorithm developed by researchers at OpenAI, a research company in San Francisco, proved capable of generating whole news stories from a prompt of a few words.

“The next step in the advancement of natural language processing is to convert this learnt information into tangible actions to help solve real-world tasks,” the researchers said in an email to MIT Technology Review. “We felt that learning strategy from text-based data could be a very important research avenue to explore.”   ..... '

Apple (or Amazon) as a Store Anchor

Does Apple Anchor a Shopping Mall?

This came to mind as well as we noticed all the failing local malls.  Used to go to them for holiday shopping, just for the atmosphere, but many have descended below that. ....

Does Apple Anchor a Shopping Mall? The Effect of the Technology Stores on the Formation of 
Market Structure - HBS Working Knowledge - Harvard Business School .... '

Is 2020 the Year of Consumer VR?

Good piece in engadget.  Not quite convinced of the conclusion.   Can VR create consumer experiences that are really better enough than on a screen?  Agree that for relatively narrow business context, makes lots of sense.  but for insertions into everyday life, or even gaming-life  ... still not there.

2020 is VR's make-or-break year in 
The stars might finally align for virtual reality next year.

Devindra Hardawar, @devindra in Engadget

In the nearly four years since the Oculus Rift and HTC Vive hit retail shelves, VR has gone from being the most exciting new computing medium around -- something that could be as transformational as the internet itself -- to a niche accessory for gamers with too much money. New headsets have come and gone, cheap mobile VR was briefly popular (before going extinct) and standalone virtual reality devices have finally arrived. It'd be wrong to say there's been no progress in the world of VR, but it still feels as if we're waiting for it to truly take off as a medium.

Where's the killer app? Where's the affordable hardware that everyone can buy (that doesn't deliver a dumbed down experience)? How, exactly, will developers make money without releasing yet another zombie game? There's still so much left up in the air for a medium that arrived amid a torrent of hype. .... "

Thursday, December 26, 2019

IOTA, FiWare and more

Brought to my attention regarding IOTA, also the connection to Fiware, which was new to me.  Regarding identification and secure use of knowledge/data.  Mentioning this here for later examination.

Video from the IOTA meetup in Karlsruhe gives a great overview of identities and the semantic layer of the decentralized IOTA marketplace using eClass…    https://youtu.be/nbQbLeKLUkQ

... IOTA is also collaborating with FIWARE  https://www.fiware.org/

-Driving key standards for breaking the information silos
-Making IoT simpler
-Transforming Big Data into knowledge
-Unleashing the potential of right-time Open Data
-Enabling the Data Economy
-Ensuring sovereignty on your data  .... 


Article Summarization by Microsoft

Had just mentioned this classic AI problem, was pointed to work underway by Microsoft, which points to this.   Pointd to the article below,  which after the abstract gets technical.    Like I have mentioned before, its what humans do well,  and is a subtask of common conversation.  Absorbing what others say, summarizing it based on context and what we understood, asking for clarification and formulating some measure of our understanding.

Patrick Fernandes, Miltiadis Allamanis & Marc Brockschmidt
Microsoft Research
Cambridge, United Kingdom  

Summarization of long sequences into a concise statement is a core problem in natural language processing, requiring non-trivial understanding of the input. Based on the promising results of graph neural networks on highly structured data, we develop a framework to extend existing sequence encoders with a graph component that can reason about long-distance relationships in weakly structured data such as text. In an extensive evaluation, we show that the resulting hybrid sequence-graph models outperform both pure sequence models as well as pure graph models on a
range of summarization tasks.

Summarization, the task of condensing a large and complex input into a smaller representation that
retains the core semantics of the input, is a classical task for natural language processing systems. Automatic summarization requires a machine learning component to identify important entities and
relationships between them, while ignoring redundancies and common concepts  ... "

Summarized in a Venturebeat article.

See also Google's work in this at Summarization tag.   See also work by Salesforce in this area that slipped my mind,, will be reviewing that.

Walgreens Explores Drone Delivery

Exploring new means of delivery.

History made: Walgreens takes off with first drone delivery
By Dan Berthiaume - 10/18/2019

Walgreens is officially in flight with a pilot of on-demand drone deliveries in Virginia.

As of Oct. 18, 2019, the drugstore giant is live with a trial of “store to door” delivery of health and wellness, food and beverage and convenience items via drone delivery in Christianburg, Va. (Prescription deliveries are not available in the pilot.) The very first drone-based delivery from Walgreens went to local residents Michael and Kelly Collver, who received a cough and cold pack including Tylenol, Halls cough drops, tissues, Emergen-C and bottled water.

Walgreens is conducting the pilot in partnership with Wing Aviation, a subsidiary of Google parent company Alphabet. Launch of the pilot makes Walgreens the first retailer to offer on-demand drone delivery service in the U.S. The companies are running the test in conjunction with FedEx in Christiansburg, Va.   .... " 

Tuesday, December 24, 2019

AI for Boosting Online Training Business

Good thoughts, though ultimately we need better ways to create and maintain conversations to make training work well.   Moving in that direction, but lots of work yet to do.

Huge Benefits of AI For Boosting Your Online Training Business  Via Gibb Bassett
There are many benefits of AI (artificial intelligence) when it comes to boosting your online training business. Here's what to know about it.

By Sean Mallon in SmartData Collective

Countless businesses are using AI to revamp their operating models. AI is being used for a variety of purposes:

Predictive analytics tools can help
 them forecast future revenue, which helps with tax and inventory planning
AI helps them identify future consumer trends, so they can adapt their marketing strategies
AI has made it easier for companies to optimize chatbots to provide better customer service
There are countless benefits of using AI in business. One of the industries that is benefiting from AI the most is the online training industry. .... " 

The Future will be More Autonomous, Humans will be Involved.

True, its been going that way for a long time ,  but has it really sped up greatly at the macro level?    At the level of 'self driving', 'identifying', 'charging' ....where people are integrated with larger context systems we are part of ?    We still have to be part of many systems in mundane ways.   Those systems have gotten very, very complex,  and  once they interact with humans, they slow down.   And because systems have been shown to be biased at times,  some would say we need to include humans.   I assume to be fairer, or at least to have someone to blame, or sue.

Good piece, which at the link below starts with RPA methods.

The future is autonomous: 5 reasons why automation will be tech’s major story in 2020

By Mark Albertson in SiliconAngle

This article wasn’t written by a robot, but it could have been. That, along with literally thousands of other uses, is why automation will be big news in 2020.

Over the course of 2019, it was nearly impossible to cover any major tech conference without discussing an innovation in robotics, artificial intelligence or a similar automation solution. Not every automated advance will be a surefire winner, but the body of evidence offers a convincing case that the field is moving rapidly and adoption will only continue to grow.  ....  "

Amazon Ships More Things

The numbers continue to expand.  The efficiency amazes.  Stats and quality measures interesting.

Amazon Is Its Own Biggest Mailman, Shipping 3.5 Billion Parcels in SupplychainBrain

Source: Bloomberg

As Amazon.com Inc. works to speed orders to customer doorsteps before Christmas, the e-commerce giant is touting an accomplishment that would have seemed absurd just a few years ago: Amazon is now its own biggest carrier.

In the U.S., delivery contractors and on-demand workers now account for a majority of deliveries to customers, an Amazon spokeswoman said. Globally, “approximately half” of Amazon deliveries are completed by Amazon Logistics, the network the company built in recent years to handle a surge in deliveries that United Parcel Service Inc., FedEx Corp. and the U.S. Postal Service were unprepared to handle.

In a press release last week touting the scale of Amazon’s network, Dave Clark, the increasingly influential executive who oversees Amazon’s logistics organization, said Amazon was on pace to deliver 3.5 billion of its own packages to customers this year. That exceeded some analyst estimates. Morgan Stanley earlier this month estimated that Amazon shipped some 2.5 billion of its own packages a year.  .... " 

Being Paid for Data

Considering the design of methods of payment and ensuring their security.   An example.

AI Needs your Data and you should get pad for it.  By Gregory Barber in Wired

ROBERT CHANG, A Stanford ophthalmologist, normally stays busy prescribing drops and performing eye surgery. But a few years ago, he decided to jump on a hot new trend in his field: artificial intelligence. Doctors like Chang often rely on eye imaging to track the development of conditions like glaucoma. With enough scans, he reasoned, he might find patterns that could help him better interpret test results.

That is, if he could get his hands on enough data. Chang embarked on a journey that’s familiar to many medical researchers looking to dabble in machine learning. He started with his own patients, but that wasn’t nearly enough, since training AI algorithms can require thousands or even millions of data points. He filled out grants and appealed to collaborators at other universities. He went to donor registries, where people voluntarily bring their data for researchers to use. But pretty soon he hit a wall. The data he needed was tied up in complicated rules for sharing data. “I was basically begging for data,” Chang says.

Chang thinks he might soon have a workaround to the data problem: patients. He’s working with Dawn Song, a professor at the University of California-Berkeley, to create a secure way for patients to share their data with researchers. It relies on a cloud computing network from Oasis Labs, founded by Song, and is designed so that researchers never see the data, even when it’s used to train AI. To encourage patients to participate, they’ll get paid when their data is used.  ... "

Shutters for Star Watching

Watching the skies for anomalous behaviour in real time:

NASA to demonstrate new star-watching tech with thousands of shutters
by Lori Keesey, NASA's Goddard Space Flight Center..... "

The Goddard-developed microshutter array technology has evolved since its initial development in the 1990s for the James Webb Space Telescope. Here are images of its various incarnations. A Next-Generation Microshutter Array will fly in space for the first time on October 27, 2019. Credit: NASA
NASA scientists plan to demonstrate a revolutionary technology for studying hundreds of stars and galaxies at the same time—a new capability originally created for NASA's James Webb Space Telescope.

The technology, called the Next-Generation Microshutter Array (NGMSA), will fly for the first time on the Far-ultraviolet Off Rowland-circle Telescope for Imaging and Spectroscopy, or FORTIS, mission on October 27. The array includes 8,125 tiny shutters, each about the width of a human hair, that open and close as needed to focus on specific celestial objects.  .... " 

Monday, December 23, 2019

Google's Summarization Performance: Pegasus

A kind of AI.   Summarization is useful and powerful concept.  But consider that summarization also exists in a context.   Its output is only useful in a particular context, and that exists based  also on the requester.  And that can also change over time, location, requesters current goals, etc.    And influenced by the metadata involved with its construction.   Still a very useful step forward.

Google Brain’s AI achieves state-of-the-art text summarization performance
Kyle Wiggers in Venturebeat

Summarizing text is a task at which machine learning algorithms are improving, as evidenced by a recent paper published by Microsoft. That’s that’s good news — automatic summarization systems promise to cut down on the amount message-reading done by enterprise workers, which one survey estimates amounts to 2.6 hours each day.

Not to be outdone, a Google Brain and Imperial College London team built a system — Pre-retraining with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence, or PEGASUS — that leverages Google’s Transformers architecture combined with pre-training objectives tailored for abstractive text generation. They say it achieves state-of-the-art results in 12 summarization tasks spanning news, science, stories, instructions, emails, patents, and legislative bills, and that it shows “surprising” performance on low-resource summarization, surpassing previous top results on six data sets with only 1,000 examples.  .... " 

Amazon Echo Flex: Plug+Simple speaker

Amazon seems ready to inexpensively (for now $20) replace every wall plug with a link to Alexa.      Now lets give these devices something more intelligent to do.  Should every plug and switch plate be able to talk to you?

Amazom's Echo Flex Turns any wall outlet into a Smart Speaker    By Alexandria Haslam in TechConnect

".... The Echo Flex is a compact mini speaker that plugs directly into your wall outlet. While its small size means it’s not optimal for listening to music, it still brings all the smarts of Alexa. You’ll be able to ask questions, take calls, add items to your Amazon shopping cart, check weather and news, and control other smart devices all with just the sound of your voice. In addition, a built-in USB-A port allows you to either charge your phone or connect another accessory.

While we haven’t reviewed the Echo Flex yet, the ultra-tiny smart speaker averages 4.1 stars out of 5 on Amazon across nearly 1,000 user ratings. ... "

AR Games for Grocery Aisles

Interesting,  but how well will this interact with traffic in store?  Gets in the way of of basic goals I believe.    Article contains other examples of the concepts that have been tested.

Giant thinks AR-games are ripe for grocery aisles  by Tom Ryan in Retailwire

Giant Food Stores has introduced an augmented reality (AR) promotion, Snowflake Search, designed to send kids on scavenger hunts in stores while their parents shop.

To play, customers scan a QR code on special in-store signage with their smartphones. An audio introduction by a snowman directs users to search for six unique snowflake signs throughout the store. Each snowflake triggers an interactive character on the phone, like a polar bear juggling clementines and bananas in the fruit section. Customers track the characters and receive clues to find the remaining ones.

Members of Giant Choice Rewards earn 50 points for each character found, with the ability to earn a total of up to 300 points each time they play. Under the rewards program, 300 points can be redeemed for $3.00 in savings.

Rewards members can redeem up to 1,500 points with a limit of five games until the promotion ends January 30. The game will be featured in 15 Harrisburg, PA-area stores.  ...."

Sorting Legos is Intelligent

An example of sorting that is fun and interesting.  Discerning, categorizing and selecting is a classic kind of intelligence

AI-powered Lego sorter knows the shape of every brick
It’s powered by motors, a Raspberry Pi and, of course, Lego.  ... 

Marc DeAngelis in Engadget

Vehicle Hacking Spreads

Increasing amount of vehicle hacking is occuring.  Note the increasing ability to effect these cybercrimes remotely.    Some telling statistics.

New Study Shows Just How Bad Vehicle Hacking Has Gotten
in CNet   By Kyle Hyatt
December 18, 2019

A new report from Israeli security firm Upstream.auto has painted a grim picture of the state of vehicular cybersecurity. Automobiles have not been immune to the tsunami of Internet-connected upgrades that has swept through everyday life in recent times. The increased connectivity has made life easier, but it has also opened up more opportunities for hackers scheming to seize unauthorized control of automobiles. According to Upstream, there were 150 cases of vehicle hacking in 2019, a 99% increase from 2018. Moreover, the auto industry has experienced 94% year-over-year growth in hacks since 2016. Car manufacturers have turned to white hat hackers and bug bounty programs to expose flaws before malicious actors can exploit them, but bad actors are still responsible for 57% of cybersecurity incidents in the auto industry. About 82% of the hacks are done remotely, an alarming indication that hackers are capable of breaking into cars from the comfort of their own homes. .... "

Sunday, December 22, 2019

Digital Twin for Electricity Grid

Grids have a potential for hacking, also the potential for reacting to things like solar mass ejections and other completely natural events. So stimulating them well makes lots of sense.   As well as how the grids interact with renewable energy.

Developing a digital twin for the electricity grid
by Delft University of Technology

The rapid transition to renewable energy threatens to cause major problems to the very expensive electricity grid in the Netherlands. In his quest for solutions, Professor Peter Palensky is now working on a "digital twin" to make it possible to study the grid effectively.

Imagine you have been working quietly for years in the confines of a large academic institute, and, all of a sudden, dramatic changes turn your familiar world on its head. The spotlights are pointing in your direction and suddenly all eyes are on you. What would you do?

This is exactly what happened to Peter Palensky, professor at TU Delft. His specialism—intelligent electricity grids—has suddenly become a hot topic in recent years. The rapid transition to renewable energy has raised an important question: is our existing electricity grid capable of withstanding such far-reaching changes? Palensky and his colleagues need to answer that key question to prevent the move towards increased sustainability from faltering.

Palensky is certainly not the type to shy away from a challenge like that. Quite the contrary. "As a scientist, it's actually quite a privilege to find yourself in this position," he says. "It's as if we are at a turning point in history and have a real chance of changing the world for the better. It's an absolutely huge responsibility, but one day we may be able to say to our children: we did it." .... ' 

Hacking Connected Cars

No doubt increasingly connected cars are the future.   And they can be hacked like other IOT systems can.  Here a short piece on how this is evolving and companies are responding.

What to expect from car hackers in 2020 and beyond
By Yosi Vardi  in Venturebeat

 If connected cars are the future, connected car hacking will need to become a dominant focus of cybersecurity. Unfortunately, the latest battlefront in cybersecurity is beginning to look hauntingly like IT cybersecurity: Companies respond after hackers expose glitches and security holes.  ... "

Data Science in Film Industry

Fairly generalized thoughts, but an areas which is underdeveloped. 

How Data Science Is Used Within the Film Industry

As Data Science is becoming pervasive across so many industries, Hollywood is certainly not being left behind. Learn about how Big Data, analytics, and AI are now core drivers of the movies we watch and how we watch them. 

By Frankie Wallace. in KDNuggets

There are countless factors at play in filmmaking, from determining production costs to developing targeted marketing campaigns. Data science is involved in practically every step of the process, and professionals who work in data science can learn many things from the film industry.

Streaming services are at the forefront of the data science revolution. Production companies, including Amazon, Hulu, and Netflix, analyze patterns in big data to determine the types of content they create and make personalized viewing recommendations. In this way, data science can aid the art of producing and marketing entertainment at levels never before seen.

The field of data science also pops up as meaty subject matter in a variety of films. The stories of real-life innovators such as Alan Turing and John Nash have been turned into major films in recent years, living alongside fictionalized tales that use predictive analysis, machine learning, and AI as central plot themes. .... "  ...'

Saturday, December 21, 2019

Sweden Examining E-Krona

After the recent information from China.  Interest in E-Currency expanding.

Accenture Picked to Build Sweden’s E-Krona Digital Currency Pilot
By Danny Nelson in Coindesk

Sweden’s central bank has tapped Accenture to develop its e-krona digital currency pilot project, the Riksbank announced in a press release Friday.

Accenture will build out the e-krona’s consumer-facing features – such as how a user would pay on various mobile platforms – and run them in a test environment with “simulated stores.” Its initial contract lasts for one year, but Riksbank said it is open to as many as seven years of tests. 

Riksbank hasn't committed to issuing an e-krona at this time.  ... '

Recorded Future Engine for Security Intelligence

Interesting look at an analytical and visual approach that is worth a look. Note the long term use of data, and the Digital Twin model evoked.

The Engine RF Uses for  Security Intelligence Explained  By  Staffan Truve

Recorded Future captures all information gathered from the internet for over a decade and makes it available for analysis in a structured and organized way. We call this the Security Intelligence Graph, and it is at the heart of all services offered by Recorded Future.

Having all information readily available in the Security Intelligence Graph offloads a tremendous amount of work from analyst teams. It could take an organization thousands of man hours to build out a fraction of what is now available, and that time can instead be spent on analysis. By adding their own analyst notes, security teams can even connect their own findings to the Security Intelligence Graph. Navigation in the graph is what powers the easy pivoting between different views in the Recorded Future® Platform, and relationships in the graph underlie the risk score calculations that enable analysts to make quick, informed decisions.

To make full use of Recorded Future, it helps to have a good understanding of our underlying data model and design philosophies — explaining this is the purpose of this blog. The following is an excerpt from our Security Intelligence Graph white paper. To read the full white paper, download your complimentary copy today.

The Security Intelligence Graph Explained

Just as many industrial companies today are creating “digital twins” of their products, we aim to build a digital twin of the world, representing all entities and events that are talked about on the internet — with a particular focus on threat intelligence. The Security Intelligence Graph is that representation of the world, and our goal is to make this information available at the fingertips of all security analysts to help them work faster and better. ... "

Apple, Google and Amazon

More on this, good direction for assistants.  And security is a good place to start.   This is key way to make the average consumer invest in such infrastructure, the assurance that today and tomorrow they will work together.  Now that the market has been established, clean it up for design and operating value.  Further, there needs to be ways that skills/knowledge can effectively shared, and linked to new ideas for for their collective  use.  Microsoft?

Apple, Google, Amazon Decide to 'Play Nice' Over Smart Home Tech
BBC News
December 18, 2019

Apple, Google, and Amazon have announced a partnership to improve smart-home technology's ease of use by creating a new standard to ensure their smart products are compatible with all three companies’ smartphones and voice assistants. The three tech giants also will work with the Zigbee Alliance, and a successful effort could remove consumers and manufacturers' burden of favoring one smart-home technology over others. Draft specifications for the new standard are not expected before late 2020. The companies said current smart-home products should continue to operate after the new standard is implemented. The first product category to be targeted by the new standard will be smart home security products.  ..."

Mapping Job Personalities

At very least an organization could see how these mapped internally, then use them to understand how they relate to internal skills, goals and results.  Also, how about group clusters using the same idea?

Mapping Job Personalities
University of Melbourne
Lito Vilisoni Wilson

A study by researchers at Australia's University of Melbourne, University of Technology Sydney (UTS), and University of New South Wales suggested defining the personality traits and values of different occupations could be critical to matching people with their ideal professions. The researchers examined more than 128,000 Twitter users representing some 3,500 occupations; a combination of artificial intelligence, machine learning, and data analytics yielded a data-driven vocation compass to recommend careers for certain personalities. UTS' Marian-Andrei Rizoui said the model could recommend an occupation that lined up with personality traits with more than 70% accuracy. Said Rizoui, “Even when the system was wrong it was not too far off, pointing to professions with very similar skill sets. .... "

Use 2-Factor Authentication for Home

Am a big proponent of 2 Factor Authentication, should be in general use

Protect your Ring camera from hackers by setting up two-factor authentication
A rash of takeovers of Ring cameras is a good reminder to lock down your security devices.

Laura Hautala in CNET

 ....  Passwords aren't good enough
Telling consumers not to reuse passwords is unrealistic. First of all, many people have dozens or even hundreds of accounts, and only a robot could memorize unique, complex passwords for each of them. There are tools to make this easier, like password managers, but they can be challenging to use. That's a disincentive for many people to rely on them. ...

Two-factor authentication is one way companies could secure smart-home tech for their customers even if they use bad passwords. If 2FA were required, consumers would need a second form of identity, often a one-time code sent to a phone after a username and password are entered, or a physical token that's plugged in.   ... "

EU Data Transfers Approved

Appears to be a fundamental result.   Likely much more in the details.

Facebook Wins Landmark Case as EU Finds Data Transfers Legal
The Telegraph (U.K.)

By Hasan Chowdhury
December 19, 2019

An adviser to the European Court of Justice (ECJ) declared the transfer of data outside the European Union (EU) to be legal. ECJ advocate general Henrik Saugmandsgaard Oe's non-binding opinion refutes Austrian lawyer Max Schrems' claim that Facebook's data-transfer protocol via contractual clauses breaches EU users' privacy because it lacks sufficient online protection. Schrems said he was "generally happy" with the results of the case. “Everyone will still be able to have all necessary data flows with the U.S., like sending emails or booking a hotel in the U.S.,” he said, adding, “It is really upon the United States to ensure baseline privacy protections for foreigners. Otherwise, no one will trust U.S. companies with their data.  ... "

Azure Kinect DK for AI Sensors

Microsoft continues to expand from the developer direction.   Like I have said before was impressed by their capabilities for delivering in Azure from the basic knowledge structure level.

Azure Kinect DK
Developer kit with advanced AI sensors for building computer vision and speech models
Build your way with a versatile sensing device

Azure Kinect DK is a developer kit with advanced AI sensors for sophisticated computer vision and speech models. Designed for versatility, it combines an advanced depth sensor and spatial microphone array with a video camera and orientation sensor—with multiple modes, options, and SDKs.

Explore documentation  ...

Friday, December 20, 2019

AI as Creative Partner

Another good thought, but still hard to do well. And how?    Should such a system generate and test possible new ideas?    Then we need to carefully test what a solution in context looks like.  You can start such a context with stated constraints.   You then will typically need a means to judge a solution, also in current and future context.  True general creativity is different from business creativity, but the two can be used to feed each other,with by linking them to human decision makers, or simulations of human and business needs.   Or judged crowdsourced opinion,  or trained on data sets, or played against with 'Digital Twin' models.   Can all be done,  do lots of tests.

AI Is A New Kind Of Creative Partner
Thomas Husson, VP, Principal Analyst, Forrester

Brands and agencies have always placed creativity at the heart of advertising. But as digital channels proliferate, the cost, complexity, and demand for media’s measurability have driven the emphasis to marketing technology. For those reasons, CMOs are starting to apply artificial intelligence to digital media buying, campaign automation, or marketing mix optimization. Few brands, however, use AI as a partner in the creative process to help scale creative capability and capacity within data-driven marketing approaches.

Luc Julia, cocreator of Siri, believes artificial creativity does not exist yet. Indeed, let’s not confuse artistic creativity with business creativity. AI has helped write songs, mimic the styles of painters by creating a piece of art that sold for over $400,000, and inform creative decisions in filmmaking. Artistic creativity may be more about pattern and algorithm than we give it credit for, and very often, the patterns are hidden — that’s something AI can help discover. But let’s be clear: AI’s impact on creativity is not about machines taking over — it’s about infusing intelligent technology into the creative process to augment the human capacity to create and execute ideas with the benefit of saving time, solving capacity challenges, and enhancing the ability to find the best idea possible.  ... ." 

Statistical vs Mathematical Modeling

Interesting comments,  having been involved in 'mathematical modeling' for a long time ...  it, like statistics has to be evaluated with terms like significance.    Had to be done then, and also needs to be done now.  Math modeling is, as much as statistics, also a discipline.

A short comment on statistical versus mathematical modelling
Andrea Saltelli
Nature Communications volume 10, Article number: 3870 (2019)

While the crisis of statistics has made it to the headlines, that of mathematical modelling hasn’t. Something can be learned comparing the two, and looking at other instances of production of numbers.Sociology of quantification and post-normal science can help.

While statistical and mathematical modelling share important features, they don’t seem to share the same sense of crisis. Statisticians appear mired in an academic and mediatic debate where even the concept of significance appears challenged, while more sedate tones prevail in the various communities of mathematical modelling. This is perhaps because, unlike statistics, mathematical modelling is not a discipline. It cannot discuss possible fixes in disciplinary fora under the supervision of recognised leaders. It cannot issue authoritative statements of concern from relevant institutions such as e.g., the American Statistical Association or the columns of Nature.

Additionally the practice of modelling is spread among different fields, each characterised by its own quality assurance procedures (see1 for references and discussion). Finally, being the coalface of research, statistics is often blamed for the larger reproducibility crisis affecting scientific production2.

Yet if statistics is coming to terms with methodological abuse and wicked incentives, it appears legitimate to ask if something of the sort might be happening in the multiverse of mathematical modelling. A recent work in this journal reviews common critiques of modelling practices, and suggests—for model validation, to complement a data-driven with a participatory-based approach, thus tackling the dichotomy of model representativeness—model usefulness3. We offer here a commentary which takes statistics as a point of departure and comparison.  .... "

Managing Data with Brexit

Useful thoughts, How will the flow of data change in new regulatory environments.

How to Manage Your Data When Expecting Brexit
By Ralph O'Brien in Datanami

The implications of a possible Brexit on privacy and compliance-related statutes, such as the General Data Protection Regulation (GDPR), Privacy Shield, and the Data Protection Act of 2018 (DPA) are vast. These regulations govern the handling and transfer of consumers’ private data between entities in the EU, UK, and the rest of the world. If the landscape of the European Union changes, so, too, do the jurisdictions of these regulations.

In the wake of Brexit, data transfer relationships will require mending. Taking data that belongs to people in the UK and transferring it to the EU will still be an acceptable transfer. If the UK leaves the EU and loses its stature as a member state, the country will cease to be a trusted party and deemed inadequate for data transfers from the EU to the UK.

In order to reopen the flow of data westward across the English Channel, the EU and UK will have to establish a new data transfer agreement, with the European Commission reviewing the privacy laws of the UK and deem them adequate for data transfers. Similarly, Privacy Shield, which currently regulates data transfers between the EU and U.S., will no longer cover instances when companies transfer data from the UK to the U.S. (as it is an EU/U.S. arrangement!) though it is understood the UK and U.S. will be making amendments to enable this in the near future.   .... " 

Breaking Things Productively

Have never used Chaos engineering, but the idea is interesting. Second read about the concept:

How to Use Chaos Engineering to Break Things Productively  by  Sam Bocetta in Infoq

More people connected to more servers, increased reliance on complex distributed networks, and a proliferation of apps in development mean more opportunities for data leaks and breaches.

Modern problems require modern solutions, as Amazon found out the hard way. Netflix escaped with minor inconvenience by being prepared.

What did they do differently?

Amazon Web Services (AWS), Amazon's cloud-based platform, experienced an outage on September 20, 2015, that crashed their servers for several hours and affected many vendors. Netflix experienced the issue as a blip because they've been there and done that when they changed their service delivery model. This led their engineering team to craft a unique solution for software production testing.

The solution? Chaos as a preventative for calamity. It's predicated on the idea of failure as the rule rather than the exception, and it led to the development of the first dedicated chaos engineering tools. Otherwise known as the Simian Army, they're called Chaos Monkey, Chaos Kong, and the newest member of the family, Chaos Automation Platform (ChAP).

What Are the Benefits of Chaos Engineering in DevOps?

Focusing only on a network environment and the associated security considerations (because the world of chaos engineering is quite large), we have already seen it as a positive force in an already strong cybersecurity market for improving business risk mitigation, fostering customer confidence, and reducing the workload for IT teams. If you're a business owner, you'll be blessed with happier engineers, reduced risk of revenue loss, and lower maintenance costs.

Customers, whether B2B or B2C, will enjoy greater service availability that's more reliable and less prone to disruptions. Tech teams will be able to reduce failure incidents and gain deeper insight into how their apps work. It will also lead to better design, faster mean time in response to SEVs, and fewer repeat incidences. ....  " 

Thursday, December 19, 2019

Causal Theory Of Views

Good piece.    It is all ultimately about context, in the sense of location, events, agents, results ... connects to the rest of the world.   It drives things like goals, value, transparency and risk.   We diagrammed these in views that helped us understand their role in decisions.

The Causal Theory of Views
A Conversation with Lee Smolin  in The Edge

An event has a view of the world. First, let me tell you what I mean by a view. A view is the information that that event has about how it fits into the rest of the world. That includes who its parents were (by which I mean the events in its past that gave rise to it) and how much energy and momentum was propagated to it from them. If I am an event, my view of the world is what I see when I look around. I see light comes to me from the past, which I perceive as a pattern of colors, which come from photons of different energies striking my eye. That's my view; it's a property of a moment. That contains all that I, as an event, know about how I fit into the rest of the world.

Now, if you know the things that I just said were real—the events, the causal relations, the distribution of energy and momentum flowing—I can tell you what the view of each event is, but I can also flip it around. There's a dual description in which I just say what the views are and that's the whole description. So, I just say there's a view, and that view is that makes a kind of picture. You see the sky, a two-dimensional sphere around you, and there are some colors, which are photons coming in of different energies—that's the view. I can hypothesize that all that exists in the world is views and a process that continually makes new views out of old views. That's what I call the causal theory of views.  .... '

LEE SMOLIN, a theoretical physicist, is a founding and senior faculty member at the Perimeter Institute for Theoretical Physics in Canada. His main contributions have been so far to the quantum theory of gravity, to which he has been a co-inventor and major contributor to two major directions, loop quantum gravity and deformed special relativity. He is the author, most recently, of Einstein's Unfinished Revolution. ... Lee Smolin's Edge Bio Page  .... "

IKEA Previews its Smart Home Experience

Good overview here.  Unclear if they will be able to establish the needed infrastructure that consumers need to make this happen.   TheVerge make a good point that current installation methods are buggy and messy,  and hard to use by the average consumer.   The Ikea methods for these apparently were developed by Sonos,  but I have found  problems with Sonos as well.   Its not that methods used by Amazon, Google, Apple or Sonos are bad, it's just that they have to be made to work in many different contexts.   The expectation today is that most of these systems are installed, extended and maintained by the average consumer.   Will we have to move to professional installation only?   That could considerably decrease their sale.    Again below an excellent link to what Ikea is intending:

Ikea previews its improved 2020 smart home experience
By Thomas Ricker in TheVerge
But can it get the software right?

Now that the smart home is no longer just a hobby for Ikea, it’s addressing two of Home Smart’s biggest shortcomings: it lacks some of the basic features required to make homes truly smart, and the platform can be buggy and confusing to set up. The first issue will be addressed with the introduction of scenes and new Shortcut Buttons, and the second by a complete overhaul of the onboarding procedure, which is the way Ikea blinds, lights, and accessories are added to the Home Smart network.  .... " 

Modeling Chaotic Systems

The breadth of modeling capability is always important.  From a continuing investigation.

Numbers Limit How Accurately Digital Computers Model Chaos
UCL News

Researchers at University College London (UCL) in the U.K. and Tufts University found digital computers employ numbers that are based on flawed versions of actual numbers, which may lead to inaccuracies in simulations of chaotic systems and limit high-performance computing and machine learning applications. Digital computers only use rational numbers—which can be expressed as fractions—and these fractions' denominators must be a power of 2. The researchers used 4 billion single-precision floating-point numbers, ranging from plus to minus infinity, to compare the mathematical reality of a one-parameter chaotic system to digital systems' forecasts if all available single-precision floating-point numbers were utilized. The predictions were completely incorrect for certain values of the parameter, while calculations for others appeared correct, but deviated by up to 15%. Said UCL’s Peter Coveney, “Chaos is more commonplace than many people may realize and even for very simple chaotic systems, numbers used by digital computers can lead to errors that are not obvious but can have a big impact. Ultimately, computers can't simulate everything."... '

Emergent AI by Minimizing Chaos

Article is ultimately quite technical, but the basic proposal is interesting.   A way to predict, measure, drive particular goals that lead to behaviors?    Intriguing direction.

Emergent Behavior by Minimizing Chaos

BY Glen Berseth   Dec 18, 2019   Berkeley AI Blog

All living organisms carve out environmental niches within which they can maintain relative predictability amidst the ever-increasing entropy around them (1), (2). Humans, for example, go to great lengths to shield themselves from surprise — we band together in millions to build cities with homes, supplying water, food, gas, and electricity to control the deterioration of our bodies and living spaces amidst heat and cold, wind and storm. The need to discover and maintain such surprise-free equilibria has driven great resourcefulness and skill in organisms across very diverse natural habitats. Motivated by this, we ask: could the motive of preserving order amidst chaos guide the automatic acquisition of useful behaviors in artificial agents?

How might an agent in an environment acquire complex behaviors and skills with no external supervision? This central problem in artificial intelligence has evoked several candidate solutions, largely focusing on novelty-seeking behaviors (3), (4), (5). In simulated worlds, such as video games, novelty-seeking intrinsic motivation can lead to interesting and meaningful behavior. However, these environments may be fundamentally lacking compared to the real world. In the real world, natural forces and other agents offer bountiful novelty. Instead, the challenge in natural environments is allostasis: discovering behaviors that enable agents to maintain an equilibrium (homeostasis), for example to preserve their bodies, their homes, and avoid predators and hunger. In the example below we shown an example where an agent is experiencing random events due to the changing weather. If the agent learns to build a shelter, in this case a house, the agent will reduce the observed effects from weather  .... "

An AI Transparency Risk Paradox

Risk is not thought of formally enough.   And the point made in the article points out that to do current AI med\methods you need more data, but more data creates higher risk.   In our own work in the area we looked at valuation of data ... but also the cost risk of storing and moving it around, sharing it with suppliers and tech vendors.      Assets can have negative value.

The AI Transparency Paradox
By Andrew Burt  HBR 

In recent years, academics and practitioners alike have called for greater transparency into the inner workings of artificial intelligence models, and for many good reasons. Transparency can help mitigate issues of fairness, discrimination, and trust — all of which have received increased attention. Apple’s new credit card business has been accused of sexist lending models, for example, while Amazon scrapped an AI tool for hiring after discovering it discriminated against women.

At the same time, however, it is becoming clear that disclosures about AI pose their own risks: Explanations can be hacked, releasing additional information may make AI more vulnerable to attacks, and disclosures can make companies more susceptible to lawsuits or regulatory action.

Call it AI’s “transparency paradox” — while generating more information about AI might create real benefits, it may also create new risks. To navigate this paradox, organizations will need to think carefully about how they’re managing the risks of AI, the information they’re generating about these risks, and how that information is shared and protected. .... "