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Monday, May 16, 2022

Robot Bartenders

Classic problem: the robot bartender

Robot Bartender Won't Flirt with Your Date, but You Still Have to Tip

By Hastings Tribune, May 16, 2022

Customers order their drinks on a tablet, customizing numbers of shots, levels of mixers, and garnishes. The robotic arms then swing into action, drawing precise measurements from among 140 liquor bottles and 16 mixers extended upside down from the ceiling

Italian robotic bartending systems developer Makr Shakr said its Bionic Bar system has been installed aboard Royal Caribbean's Wonder of the Seas cruise ship.

Bionic Bar's creators modeled the robots' movements after those of dancers, to make them seem less mechanical.

Customers order drinks on a tablet, and the system’s two robotic arms draw precise measurements from roughly 140 liquor bottles and 16 mixers extended upside down above the bar., Makr Shakr said the system can make up to 250 drinks per hour, and patrons of the system will find it charges the same 18% gratuity charged at every other bar on Royal’s cruise ships.

From Hastings Tribune   ...    View Full Article   

Flute: Scalable Federated Learning Simulation

New to me, of interest.  Considering use. 

FLUTE: A scalable federated learning simulation platform   From Microsoft Labs

Published May 16, 2022

By Dimitrios Dimitriadis , Principal Researcher  Mirian Hipolito Garcia , Research Software Engineer  Daniel Eduardo Madrigal Diaz , Senior Research Software Engineering  Andre Manoel , Senior Research Software Engineer  Robert Sim , Principal Research Manager

Federated learning has become a major area of machine learning (ML) research in recent years due to its versatility in training complex models over massive amounts of data without the need to share that data with a centralized entity. However, despite this flexibility and the amount of research already conducted, it’s difficult to implement due to its many moving parts—a significant deviation from traditional ML pipelines.

The challenges in working with federated learning result from the diversity of local data and end-node hardware, privacy concerns, and optimization constraints. These are compounded by the sheer volume of federated learning clients and their data and necessitates a wide skill set, significant interdisciplinary research efforts, and major engineering resources to manage. In addition, federated learning applications often need to scale the learning process to millions of clients to simulate a real-world environment. All of these challenges underscore the need for a simulation platform, one that enables researchers and developers to perform proof-of-concept implementations and validate performance before building and deploying their ML models. 

A versatile framework for federated learning

Today, the Privacy in AI team at Microsoft Research is thrilled to introduce Federated Learning Utilities and Tools for Experimentation (FLUTE) as a framework for running large-scale offline federated learning simulations, which we discuss in detail in the paper, “FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations.” In creating FLUTE, our goal was to develop a high-performance simulation platform that enables quick prototyping of federated learning research and makes it easier to implement federated learning applications. .... ' 

How Quantum Uncertainty Sharpens Measurements

 Useful thought about science progress, relate it to measurements

Physicists Pin Down How Quantum Uncertainty Sharpens Measurements

By Ben Brubaker  Contributing Writer  in Quanta magazine

Throwing out data seems to make measurements of distances and angles more precise. The reason why has been traced to Heisenberg’s uncertainty principle.

Scientific progress has been inseparable from better measurements.

Before 1927, only human ingenuity seemed to limit how precisely we could measure things. Then Werner Heisenberg discovered that quantum mechanics imposes a fundamental limit on the precision of some simultaneous measurements. The better you pin down a particle’s position, for instance, the less certain you can possibly be about its momentum. Heisenberg’s uncertainty principle put an end to the dream of a perfectly knowable world.

In the 1980s, physicists began to glimpse a silver lining around the cloud of quantum uncertainty. Quantum mechanics, they learned, can be harnessed to aid measurement rather than hinder it — the thesis of a growing discipline known as quantum metrology. In 2019, gravitational wave hunters used a quantum metrological technique called quantum squeezing to improve the sensitivity of the LIGO detectors by a whopping 40%. Other groups have employed the phenomenon of quantum entanglement to precisely measure weak magnetic fields.

But the most controversial and counterintuitive strategy for exploiting quantum mechanics to boost precision is called postselection. In this approach, researchers take photons, or particles of light, that carry information about some system of interest and filter some of them out; the photons that survive this filtering enter a detector. Over the past 15 years, experiments using postselection have measured distances and angles remarkably precisely, suggesting that discarding photons is somehow beneficial. “The community still debates how useful it is and whether [postselection is] a genuinely quantum phenomenon,” said Noah Lupu-Gladstein, a graduate student at the University of Toronto.

Now, Lupu-Gladstein and six co-authors have pinpointed the source of the advantage in postselected measurements. In a paper https://arxiv.org/abs/2111.01194  accepted for publication in Physical Review Letters, they trace the advantage to negative numbers that arise in calculations because of Heisenberg’s uncertainty principle — ironically, the same rule that constrains measurement precision in other contexts.

Researchers say that the new understanding forges links between disparate areas of quantum physics and that it could prove useful in experiments that use sensitive photon detectors.

The paper is “quite exciting,” said Stephan De Bievre, a mathematical physicist at the University of Lille in France who was not involved in the research. “It links this negativity, which is a sort of abstract thing, to a concrete measurement procedure.”  ... 

Ransomware Goes Deeper into Government

Ransomware Rampant

Ransomware gang threatens to overthrow Costa Rica government

Ransomware gang threatens to overthrow Costa Rica governmentA ransomware gang that infiltrated some Costa Rican government computer systems has upped its threat, saying its goal is now to overthrow the government.

The Russian-speaking Conti gang attacked Costa Rica in April, accessing multiple critical systems in the Finance Ministry, including customs and tax collection. Other government systems were also affected and a month later not all are fully functioning.   President Rodrigo Chaves declared a state of emergency over the attack as soon as he was sworn in last week. The U.S. State Department offered a $10 million reward for information leading to the identification or location of Conti leaders.

Conti responded by writing, "We are determined to overthrow the government by means of a cyber attack, we have already shown you all the strength and power, you have introduced an emergency."

The gang also said it was raising the ransom demand to $20 million. It called on Costa Ricans to pressure their government to pay. .... ' 

Predicting the Next Big Company in Tech

Loosely involved in such a move, what can best drive to succeed?  Here some thoughts

Predicting the next big company in tech  in Venturebeat

The past 40 years in tech have been more dynamic and innovative than any other 40 years in history. The pace of innovation has accelerated, and access to tech and capital has made for a highly active startup world. Every company is pitching the next great idea, but with thousands upon thousands of companies scrambling to make it big, how do you identify who will be the winners?  

I’ve spent the last four decades in tech, starting in sales and then later serving as a leader, investor, advisor, and board member at various software companies, VC firms, and cybersecurity startups. I can say with experience that picking the up-and-comer likely to make the biggest impact is a challenging undertaking. 

For a company is going to win and win big, there must be a real, unique business case.  

A few indicators can suggest that a company offers real value and might be on its way to massive success. Whether you seek to monitor the competition, join a new company, form a partnership, or identify the enterprise to emulate, the following tips can help you identify those companies that provide value.  

Look at the TAM  

Looking at the Total Addressable Market (TAM) allows you to objectively quantify a company’s potential for growth. If the market is saturated with an incalculable number of competitors, then a company entering that market is at a disadvantage. On the other hand, if a startup is entering a market with a compelling product to solve a challenge that no others — or very few others — are solving, there is a higher chance of market leadership. It’s common sense and a basic rule of economics: Early market leaders have an incredible advantage. The size of the TAM is also crucial, but make sure you consider both the current size and the potential size.   .... ' 

Boutique Search Again

Reminds me of the early days of search and things we set up for specialty use.   Especially healthcare based, but could be related to any domain.    Curated web and supporting search engines.    Recall setting up a search engine pointed (curated to) directly at a specific project.   See 'Zakta' as an example, is it still available? 

The Future of Search Is Boutique, By Sari Azout in future.a16z

This is an edited version of a post that originally ran here. 

For most queries, Google search is pretty underwhelming these days. Google is great at answering questions with an objective answer, like “# of billionaires in the world” or “What is the population of Iceland?” It’s pretty bad at answering questions that require judgment and context like “What do NFT collectors think about NFTs?”

The evidence is everywhere. These days, I find myself suppressing the garbage Internet by searching on Google for “Substack + future of learning” to find the best takes on education. We hack Twitter with the “what is the best” posts over and over again. When I’m researching a new product, I type “X item reddit” into Google. I find enormous value in small, niche, often forgotten sites like Spaghetti Directory.

There’s an emergence of tools like Notion, Airtable, and Readwise where people are aggregating content and resources, reviving the curated web. But at the moment these are mostly solo affairs — hidden in private or semi-private corners of the Internet, fragmented, poorly indexed, and unavailable for public use. We haven’t figured out how to make them multiplayer. In cases where we’ve made them public and collaborative — here is a great example — these projects are often short-lived and poorly maintained.

The stated mission of a company worth almost two trillion dollars is to “organize the world’s information” and yet the Internet remains poorly organized. Or, stated differently, in a world of infinite information, it’s no longer enough to organize the world’s information. It becomes important to organize the world’s trustworthy information.  .... ' 

Sunday, May 15, 2022

Its Not Eureka

Isaac Asimov once wrote; "The most exciting phrase to hear in science, the one that heralds new discoveries,  is not 'Eureka'' (I found it!) but 'That's Funny' ... ' ".   ....    Understanding that quote is a real key to innovative thought. 

How AR and VR are Changing Customer Experience

How AR and VR are transforming customer experiences  in Venturebeat

AR and VR technology was largely expedited by the past pandemic with at least 93.3 million and 58.9 million users respectively, according to a study conducted by eMarketer. This comes as no surprise since these immersive technologies have mitigated the massive disruptions in people’s lives. 

Their accelerated adoption at both individual and business levels are represented in daily activities. For example, as remote work became an essential part of many business models, AR/VR allowed a seamless transition from onsite training to a clear visualization of step-by-step instructions for many workers across multiple industries and locations.   ... '

Pulsing Networks in Simulations

Long time ago I needed to set up a simulation that included a pulsing network to support a solar astro model.    Found this interesting solution today.  Just for my own reference and possible the needs of others.  I like Wolframs broad application examples.

Building a Pulse-Forming Network with the Wolfram Language  In Wolfram Blog

May 6, 2022, Robert Mendelsohn, Product Manager, Strategic Initiatives

This has multiple applications in many physics- and electrical engineering–related systems, including radar, kicker magnets for accelerators and really any time a pulsed uniform voltage or current is needed. In my case, I needed this capability for a metal vapor vacuum arc plasma source that I’m using to study the properties of metallic plasmas in strong magnetic fields.

In this blog post, I’ll walk you through some pulse-forming network theory along with how I used the Wolfram Language to quickly and easily design a cost-effective pulse-forming network by using circuit theory, the interactive Manipulate function and data from an electronics vendor to explore practical design options. This will also show off the Quantity function in the Wolfram Language, which has proven helpful and easy to use.n.... '  (detailed model) 

A Chemical Computer

New design of computers, but how fast? 


Chemical Computer Can Be Programmed to Solve Hard Problems

By New Scientist, May 11, 2022

Researchers at the U.K.'s University of Glasgow have programmed a chemical computer to solve specific problems, following earlier research on encoding data into the system.

The computer consists of a plastic grid of interconnected chambers filled with a liquid acid-salt solution, which triggers a chemical reaction when mechanically agitated. The researchers adjust the speed of each stirrer to control the reaction rate in each cell, to program a specific problem.

The cells alternately flash red or blue lights during the reaction, with each flash equivalent to the 1s and 0s used in electronic computers; a video camera records the reds and blues, and uses that data to adjust the stirrers.

From New Scientist

View Full Article    

Russia Is Being Hacked at an Unprecedented Scale


Many cybercriminals and ransomware groups have links to Russia and don't target the nation. Now, it's being opened up.

in Wired  via ACM News | April 28, 2022 

The orders are issued like clockwork. Every day, often at around 5 am local time, the Telegram channel housing Ukraine's unprecedented "IT Army" of hackers buzzes with a new list of targets. The volunteer group has been knocking Russian websites offline using wave after wave of distributed denial-of-service (DDoS) attacks, which flood websites with traffic requests and make them inaccessible, since the war started.

Russian online payment services, government departments, aviation companies, and food delivery firms have all been targeted by the IT Army as it aims to disrupt everyday life in Russia. "Russians have noticed regular hitches in the work of TV streaming services today," the government-backed operators of the Telegram channel posted following one claimed operation in mid-April.

The IT Army's actions were just the start. Since Russia invaded Ukraine at the end of February, the country has faced an unprecedented barrage of hacking activity. Hacktivists, Ukrainian forces, and outsiders from all around the world who are taking part in the IT Army have targeted Russia and its business. DDoS attacks make up the bulk of the action, but researchers have spotted ransomware that's designed to target Russia and have been hunting for bugs in Russian systems, which could lead to more sophisticated attacks.

Full article:  

ScrapMetal Disposal Automation

Useful capability at hand.


University of Colorado Boulder, Paul M.  Rady Mechanical Engineering

Mechanical engineering students build machine to automate scrap metal disposal

Published: April 12, 2022 • By Rachel Leuthauser

Matthew An – Logistics manager, Casey Cole – Test engineer, Blake Fardulis – Project manager, Kate Nichols – Manufacturing engineer, Wesley Schumacher – Systems engineer, Andrew Stiller – CAD engineer, Aleksey Volkov – Finance manager

A team of seniors in the Department of Mechanical Engineering have designed and built a device that automates the disposal of scrap metal, making it safer and more efficient.

The students created the device as their Senior Design project sponsored by Accu-Precision, a Littleton-based manufacturer of custom parts for customers in aerospace and industrial sectors. The Machining Chip Disposal System can lift and dump 600 lbs. of scrap material with the push of a button, cutting down the time it takes to dispose of the material from 30 minutes to five. That decreases the time spent per year on this cumbersome task from more than 1,000 hours to about 170 hours.  .... '

Saturday, May 14, 2022

Decision Trees

Quick overview if decision trees. 

Decision Tree Algorithm, Explained

All you need to know about decision trees and how to build and optimize decision tree classifier.

By Nagesh Singh Chauhan, Data Science Enthusiast on February 9, 2022 in Machine Learning


Classification is a two-step process, learning step and prediction step, in machine learning. In the learning step, the model is developed based on given training data. In the prediction step, the model is used to predict the response for given data. Decision Tree is one of the easiest and popular classification algorithms to understand and interpret.

Decision Tree Algorithm

Decision Tree algorithm belongs to the family of supervised learning algorithms. Unlike other supervised learning algorithms, the decision tree algorithm can be used for solving regression and classification problems too.

The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data(training data).

In Decision Trees, for predicting a class label for a record we start from the root of the tree. We compare the values of the root attribute with the record’s attribute. On the basis of comparison, we follow the branch corresponding to that value and jump to the next node.

Types of Decision Trees

Types of decision trees are based on the type of target variable we have. It can be of two types:

New form of Machine Learning Vision

Machine Learning Vision

MIT Advances Unsupervised Computer Vision with ‘STEGO’

By Oliver Peckham

Training machine learning models often means working with labeled data. For computer vision tasks, this might look, for instance, like an hour of camera footage from a car, meticulously sectioned by humans to designate roads, road signs, vehicles, pedestrians and so forth. But labeling even this small amount of data could take hundreds of hours for a human, bottlenecking the training process. Now, researchers from MIT’s Computer Science & Artificial Intelligence Laboratory (CSAIL) are introducing a new, state-of-the-art algorithm for unsupervised computer vision tasks that operates without any human labels.

The model is called STEGO, short for “Self-supervised Transformer with Energy-based Graph Optimization.” STEGO is a semantic segmentation algorithm, the process of labeling the pixels in an image. Historically, semantic segmentation has been easiest for discrete objects like people or vehicles and harder for more amorphous, blended elements of the environment like clouds or bushes—or cancers.

“If you’re looking at oncological scans, the surface of planets, or high-resolution biological images, it’s hard to know what objects to look for without expert knowledge. In emerging domains, sometimes even human experts don’t know what the right objects should be,” explained Mark Hamilton, a research affiliate of MIT CSAIL, software engineer at Microsoft, and lead author of the paper describing STEGO, in an interview with MIT’s Rachel Gordon. “In these types of situations where you want to design a method to operate at the boundaries of science, you can’t rely on humans to figure it out before machines do.”

STEGO is built on top of the DINO algorithm, itself trained on 14 million images. The researchers tested STEGO on a variety of test cases, including the incredibly diverse COCO-Stuff image dataset. The researchers reported that STEGO doubled the performance of prior unsupervised computer vision models on the COCO-Stuff benchmark, and performed similarly well on tasks like driverless car datasets and space imagery datasets.  ... ' 

SmartMaterials Microscope


Self-Driving Microscopes Discover Shortcuts to New Materials  

Scientists at the U.S. Department of Energy's Oak Ridge National Laboratory are training microscopes to find new materials faster using an intuitive algorithm. ...

Oak Ridge National Laboratory  ... 

Automatic Defect Inspection

Inspection for defects

 AutoInspect takes the quality of industrial inspection processes to a new level    Research News / May 02, 2022

In the AutoInspect demonstrator, the car body is transported to the inspection stations on a conveyor system. The picture shows the deflectometry portal: The software can detect surface defects based on the reflection of the striped patterns displayed on the monitors.

© Fraunhofer

The quality of industrial production processes is ensured by a large number of sensor-based individual inspections. This generates large amounts of data. However, until now, the information from the individual sensors has generally only been looked at in isolation. The AutoInspect solution from the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB overcomes this issue by linking all of the data to create a consolidated overview. Now, for the first time, linking the measured values is facilitating intelligent evaluation and the detection of hidden faults. This increases efficiency and ultimately improves product quality. A demonstrator will be presented at the Hannover Messe 2022 from May 30 to June 2 at the joint Fraunhofer booth in Hall 5, Booth A06.   More

The way that Crude Costs Influence Retail Prices

Costs Interacting in many ways. 

Gas Prices Raise Costs In 8 Surprising Ways

Bryan Pearson in CustomerThink 

There’s a reason the price of chewing gum is up 7% from last year, and it’s not all related to supply and demand. It turns out that chewing gum is a crude habit, regardless of personal opinion.

The average 42-gallon barrel of oil historically has produced nearly 20 gallons of gasoline and four gallons of jet fuel, according to Earth Science Week. That leaves 18 gallons for other uses, from making plastics and paint to asphalt and ammonia. And yes, to make some candies and gum.

Many of these other uses for petroleum affect the operating costs of retailers and the brands they carry well beyond the length of a gas pump. From product ingredients to the containers that carry the products to the light needed to read the labels, petroleum and natural gas are necessary through virtually every step of the path to purchase. 

Fuel For Thought: 6 Ways Crude Boosts Retail Prices

Thousands of everyday products spring from petroleum today, thanks to chemists who have been – for more than a century – exploring new uses for it. So when the price of a barrel nears $100, the ripple effect is extensive. Here are six ways through which the ripples reach consumers in the retail industry.  ... 

Sites Gathering every Word you Type, Before You Hit Enter.

Quite a simple surprise. 

Some top 100,000 websites collect everything you type—before you hit submit

A number of websites include keyloggers that covertly snag your keyboard inputs.

LILY HAY NEWMAN, WIRED.COM - 5/14/2022, 7:00 AM

When you sign up for a newsletter, make a hotel reservation, or check out online, you probably take for granted that if you mistype your email address three times or change your mind and X out of the page, it doesn't matter. Nothing actually happens until you hit the Submit button, right? Well, maybe not. As with so many assumptions about the web, this isn't always the case, according to new research: A surprising number of websites are collecting some or all of your data as you type it into a digital form.

Researchers from KU Leuven, Radboud University, and University of Lausanne crawled and analyzed the top 100,000 websites, looking at scenarios in which a user is visiting a site while in the European Union and visiting a site from the United States. They found that 1,844 websites gathered an EU user's email address without their consent, and a staggering 2,950 logged a US user's email in some form. Many of the sites seemingly do not intend to conduct the data-logging but incorporate third-party marketing and analytics services that cause the behavior.

After specifically crawling sites for password leaks in May 2021, the researchers also found 52 websites in which third parties, including the Russian tech giant Yandex, were incidentally collecting password data before submission. The group disclosed their findings to these sites, and all 52 instances have since been resolved.  .... ' 

Friday, May 13, 2022

Berners-Lee Wants Meta VR

 Interesting view here.    But in particular if you see VR as a means of  interacting with lots of complex visual contextual data, its like interacting with data in a structured Web. 


World Wide Web's Creator Wants Metaverse VR     By Bloomberg, May 13, 2022

World Wide Web creator and 2016 ACM A.M. Turing Award recipient Tim Berners-Lee expects virtual reality (VR) and metaverse-associated technologies to shape future online interaction.

"People ask about virtual reality, and if the metaverse is going to be the whole future, and the answer is that it's going to be part of the future," he said., Berners-Lee said he envisions VR becoming a new form of media, one in which "you'll be able to sit between a movie and a VR world of that movie, for example."

He is firmly opposed to the largest technology companies controlling much of their users' personal data. ...

“People ask about virtual reality, and if the metaverse is going to be the whole future, and the answer is that it’s going to be part of the future,” Berners-Lee said. ... 

From Bloomberg

View Full Article - 

Recent Conversation with Andrew Ng

Good piece, have followed Ng for some time.

Meet Andrew Ng, a 2022 Datanami Person to Watch

Alex Woodie in Datanami

Andrew Ng is one of the most influential individuals in big data and AI. He’s also one of the busiest, with stints at Google and Baidu, not to mention co-founding Coursera and his latest ventures, Landing AI and DeepLearning.AI. We’d be thrilled if he added one more credential to his stellar resume: Datanami Person to Watch for 2022.

Ng kindly responded to our questionnaire, which follows.

Datanami: You’ve had a storied career, from your work at Google and Baidu to founding Coursera and now Landing AI. What do you attribute your great success to?  ... '

Zoom Wants to do More

And want to see more, especially that saves time, records things, organizes things intelligently.  Give us us an after Covid present.   Here for customer service ....

Zoom is driving further into the customer service market

By Anthony Spadafora in Techradar

Video conferencing giant expands its contact center offering with Solvvy acquisition

In its latest move into the customer service market, Zoom has announced that it has entered into a definitive agreement to acquire the AI and automation platform for customer support Solvvy.

Once the acquisition closes, the two companies will provide elevated customer service experiences to enterprise businesses on a global scale and work together quickly to capitalize on new opportunities in both the contact center and customer support segments.

President of product and engineering at Zoom, Velchamy Sankarlingam explained in a press release how acquiring Solvvy will help boost its Zoom Contact Center offering which launched earlier this year, saying:  .... '

Cryptocurrencies Melt Down

Not so stable in this context.


Cryptocurrencies Melt Down in a ‘Perfect Storm’ of Fear and Panic

By The New York Times, May 13, 2022

The price of Bitcoin plunged to its lowest point since 2020. Coinbase, the large cryptocurrency exchange, tanked in value. A cryptocurrency that promoted itself as a stable means of exchange collapsed. And more than $300 billion was wiped out by a crash in cryptocurrency prices since Monday.

The crypto world went into a full meltdown this week in a sell-off that graphically illustrated the risks of the experimental and unregulated digital currencies. Even as celebrities such as Kim Kardashian and tech moguls like Elon Musk have talked up crypto, the accelerating declines of virtual currencies like Bitcoin and Ether show that, in some cases, two years of financial gains can disappear overnight.

The moment of panic amounted to the worst reset in cryptocurrencies since Bitcoin plummeted 80 percent in 2018. But this time, the falling prices have broader impact because more people and institutions hold the currencies. Critics said the collapse was long overdue, while some traders compared the alarm and fear to the start of the 2008 financial crisis.

"This is like the perfect storm," said Dan Dolev, an analyst who covers crypto companies and financial technology at the Mizuho Group.

From The New York Times

View Full Article  

Disrupting Data Management with AI?

 Value of intelligently positioned disruption.   From Deloitte

To achieve the benefits and scale of AI and MLOps, data must be tuned for native machine consumption, not humans, causing organizations to rethink data management, capture, and organization.

With machine learning (ML) poised to augment and in some cases replace human decision-making, chief data officers, data scientists, and CIOs are recognizing that traditional ways of organizing data for human consumption will not suffice in the coming age of artificial intelligence (AI)–based decision-making. This leaves a growing number of future-focused companies with only one path forward: For their ML strategies to succeed, they will need to fundamentally disrupt the data management value chain from end to end.

In the next 18 to 24 months, we expect to see companies begin addressing this challenge by reengineering the way they capture, store, and process data. As part of this effort, they will deploy an array of tools and approaches including advanced data capture and structuring capabilities, analytics to identify connections among random data, and next-generation cloud-based data stores to support complex modeling.  ... ' 

Ancient Art Meets AI

 Reported on this before,   unexpected connection.

Ancient Art Meets AI for Better Materials Design

Argonne National Laboratory, John Spizzirri, April 7, 2022

University of Southern California (USC) researchers combined kirigami, the ancient Japanese art of paper cutting, with autonomous reinforcement learning to help improve materials design. In an effort to create a two-dimensional molybdenum disulfide structure embedded with electronics that can stretch while remaining stable, the researchers determined that a series of precise cuts could enable the thin material to stretch up to 40%. To determine the correct combination of cuts, the researchers performed simulations on the Theta supercomputer at the U.S. Department of Energy's Argonne National Laboratory. The model was trained on 98,500 simulations of kirigami design strategies involving one to six cuts; even without additional training data, it determined in a matter of seconds that 10 cuts would provide more than 40% stretchability. USC's Pankaj Rajak said, "It learned something the way a human learns, and used its knowledge to do something different."

Uncovering Competitive Strategies

Leveraging competitive intelligence.  

How to Use Competitive Intelligence to Uncover your Competitors’ Strategies | Octopus Competitive Intelligence consulting agency 

How to Use Competitive Intelligence to Uncover your Competitors’ Strategies

To stay ahead of your competitors, you must learn faster than them. This is where Competitive Intelligence comes in. Getting on the front foot and knowing what they are doing before they do. By understanding their patterns and behaviours, you can create a competitive advantage. This article suggests how to use Competitive Intelligence to uncover your competitors’ strategies.

Uncover your competitors’ strategies

Do you know your understanding of your competitors is highly likely to be entirely wrong? And if you don’t have any Competitive Intelligence in place then you will be entirely wrong. Do you know how powerful it is to understand what your competitors are actually doing instead of thinking you know? And more importantly what they are going to do. Success and failure depend on how much you know your competitive environment. And yes, it’s not just about competitors.

What is Competitive Intelligence?

Competitive Intelligence is the finding, sorting and critical analysis of information. To make sense of what’s happening and why. Predict what’s going to happen and give the options to help you control the outcome. Competitive Intelligence offers more certainty, competitive advantage, insight, growth & security.  .... ' 

Thursday, May 12, 2022

Surveillance By Driverless Car

 Reported in Schneier  ...   which points to an article mentioning use by SF Police.   Makes sense for a number of reasons.   Can be any kind of autonomous vehicles.  Its mentioned that it includes the generation of large amounts of supporting video data.   Quotes privacy advocates as not liking the idea in general as trolling for law breaking.    Expect much more of it as driverless expands.   Whats next, launchable drones?   And since you are already checking for movement it would be an easy next step for speeding and other violations.

Unpacking Black Box Models

Quite interesting development.  I had to talk the nature and implications of What a 'black box' (BB) . was for management many times.  A BB is simply a method that is not precisely know in its operation.  Usually such an algorithm's method IS known to the person or AI that developed it, but is obscure to the people who need its operation in context. .  It may be 'explainable',  but it has never been sufficiently explained to the user who wants or needs it. .  It may be the explanation is too difficult.  It may require considerable math, statistics or AI.   Or, and not uncommon, the user may not have asked for an explanation.  Perhaps because they liked the outcome of the BB.   Lots of practical subtilties here. Measuring understanding is a useful step.

Unpacking Black-Box Models

By MIT News, May 11, 2022

A mathematical framework developed by researchers at the Massachusetts Institute of Technology and Microsoft Research aims to quantify and evaluate the understandability of a machine learning model's explanations for its predictions.

The framework, called ExSum (explanation summary), can evaluate a rule on an entire dataset. ExSum enables the user to see if a rule holds up based on three metrics: coverage, or how broadly applicable the rule is across the entire dataset; validity, or the percentage of individual examples that agree with the rule; and sharpness, or how precise the rule is.

Said MIT's Yilun Zhou, "Before this work, if you have a correct local explanation, you are done. You have achieved the holy grail of explaining your model. We are proposing this additional dimension of making sure these explanations are understandable." ... 

Researchers have created a mathematical framework to evaluate explanations of machine-learning models and quantify how well people understand them.... 

MIT News, full article.

Commercial Space Opportunities


Entrepreneurs create a space “academy” as commercial space flourishes

This is a bet that the long-promised space economy continues taking off.

ERIC BERGER 5/10/2022

A group of astronauts, engineers, and business executives is betting on a vibrant space economy by launching a new initiative called "Star Harbor." Among several planned activities, this spaceflight campus would train future astronauts and make facilities such as a neutral buoyancy laboratory and high-gravity centrifuge publicly available.

Star Harbor has already acquired 53 acres in Lone Tree, Colorado, for about $25 million, said Star Harbor founder and Chief Executive Maraia Tanner in an interview. The company plans to open the mixed-use development campus, just south of Denver, beginning in 2026.

The centerpiece of the new development will be Star Harbor Academy, Tanner said, estimating its development cost at $120 million. The academy will include the capability for microgravity flights, a neutral buoyancy facility, high-gravity centrifuge, land-based and underwater habitats, hypobaric and hyperbaric chambers, a human performance center, and more.

Starting with payloads

Initially, Star Harbor will seek to serve research and development customers, such as university groups, startup companies, and other ventures that don't have access to facilities to test their payloads. There are only a handful of facilities around the world with some of the amenities built to mimic spaceflight conditions, such as a centrifuge or large pool, Tanner said, and most of those are reserved for government use.

"I think that there is a lot of new technology and new ideas being brought to the forefront," she said. "But there’s a bottleneck in moving them forward that we’re really looking to assist with." In this sense, Star Harbor seeks to become a technology incubator and may accept payment from companies in equity.

Tanner said she expects that about 60 percent of Star Harbor's revenue will come from such research and development efforts, with a much smaller segment initially derived from commercial astronaut training.

But that could change over time. Presently, NASA astronauts train primarily at NASA facilities for their orbital missions, and space tourists taking suborbital flights on Blue Origin and Virgin Galactic vehicles train at those companies' own facilities. However, Tanner said, there is already an unserved market that is expected to grow. ... '

Emerging Drone uses in War

Cheaper and increasingly autonomous, they will be in our  future.  For war and for humanitarian aiding  in its aftermath. 

The Drones of War

By Esther Shein, Commissioned by CACM Staff, May 10, 2022

North American professional drone maker Draganfly has sent the first of nearly a dozen humanitarian drones to the non-profit Ukraine organization Revived Soldiers Ukraine (RSU) in Europe, to be used to deliver insulin to hard-to-reach hospitals in the war-torn country.

RSU has ordered 200 medical response drones from Draganfly, each costing $30,000 and equipped with temperature-managed payload boxes that can transport up to 35 pounds of blood, pharmaceuticals, insulin/medicines, vaccines, and wound care kits, the drone maker said. Because insulin is a temperature-sensitive product, quick and safe transportation is a top priority.

There are roughly 2.3 million people living with diabetes in Ukraine, according to the International Diabetes Association, many of whom have Type 1 diabetes and require multiple daily injections of insulin to survive. For those living in high-conflict areas of the country, access to life-saving insulin is limited or non-existent.

Draganfly's drones are equipped with temperature-managed payload boxes that can transport blood, pharmaceuticals, insulin/medicines, vaccines, water, and wound care kits. 

Also aiding in the delivery of medical supplies in Ukraine is Coldchain Delivery Systems, a Spring Branch, TX-based company that provides logistics services and connected RSU with Draganfly to deliver the medical equipment to people in besieged areas.

Because Draganfly's drones are equipped with thermal cameras, they can "look through debris to see if there are heat signatures, meaning a warm body,'' according to CEO Cameron Chell.

So far, RSU has purchased 10 drones and Draganfly has donated three, he said. There are three types of Draganfly drones being sent to Europe, ranging in price from $7,500 to $30,000, Chell said.

Other organizations have reached out to offer to provide insulin and other medical suppies, and "We're going to work with Revived Soldiers Ukraine and help them continue to do what it takes to accept donations and let people be involved,'' he said. "I suspect it will become a long-term thing for us."

After seeing how Draganfly's advanced drones were being used to deliver temperature-sensitive medical supplies and to assist search-and-rescue operations, "We knew they would be invaluable to our crews on the ground,'' said RSU president Iryna Vashchuk Discipio. She added that Draganfly is providing its drones at cost. ... ' 

Success of AI is in Infrastructure

 In VentureBeat

Artificial intelligence (AI) is bringing many changes to the enterprise, none of which is more vital to its success than infrastructure. Changing the nature of workloads – not just how they are generated and processed but how they apply to the operational goals – requires changes in the way raw data is handled, and this extends right down to the physical layer of the data stack.

As VB pointed out earlier this year, AI is already changing the way infrastructure is being designed all the way out to the edge. On a more fundamental level, basic hardware is becoming optimized to support AI workloads, and not just on the processor level. But it will take a coordinated effort, and no small amount of vision, to configure hardware to handle AI properly – and indeed, there isn’t likely to be one right way of doing it anyway.

How Gap Inc. is leveraging the modern data-stack and building AI to solve age-old customer problems

Foundational change for AI infrastructure

In a recent survey of more than 2,000 business leaders by IDC, one of the lead findings was the growing realization that AI needs to reside on purpose-built infrastructure if it is to bring real value to the business model. In fact, lack of proper infrastructure was cited as one of the primary drivers for failed AI projects, which continues to stymie development in more than two-thirds of organizations. As with most technological initiatives, however, key hurdles to more AI-centric infrastructure include costs, lack of clear strategies and the sheer complexity of legacy data environments and infrastructure.

All hardware is interrelated in the enterprise, whether it sits in the data center, the cloud or the edge, and this makes it difficult to simply deploy new platforms and put them to work. But as tech author Tirthajyoti Sarkar points out, there are plenty of ways to gain real value from AI without the latest generation of optimized chip-level solutions entering the channel.

Cutting-edge GPUs, for example, may be the solution-of-choice for advanced deep learning and natural language processing models, but a number of AI applications – some of them quite advanced, such as game theoretics and large-scale reinforcement learning – are better-suited to the CPU. And since much of the heavy-lifting in AI development and utilization is typically performed by front-end data conditioning tools, choices over cores, acceleration technologies and cache may prove more consequential than the type of processor. ... '

Wednesday, May 11, 2022

Alexa Together Caregiving

 Newly announced, recalls work we saw in Japan, which also connected multiple people, as needed, to the eldercare dynamic.

Alexa Together will let caregivers remotely set up routines for aging loved ones

A person receiving support can now have up to 10 caregivers through the service.

K. Holt   @krisholt

Amazon is rolling out some more features for Alexa Together, a service designed to help aging folks and caregivers stay connected using the voice assistant and Echo devices. One of these is called Circle of Support, which is now available to all users. This allows the person receiving support to have up to 10 designated caregivers.

Both that person and their primary caregiver can add or remove trusted people such as siblings, cousins, friends and close neighbors. All caregivers will receive daily alerts and check-ins through the activity feed. Circle of Support could be especially useful if the primary caregiver doesn't live close to the person receiving care. If the person receiving support enables Remote Assist, only the primary caregiver will be able to use it. 

Speaking of Remote Assist, Amazon will soon upgrade that feature to let the primary caregiver set up Alexa Routines for their loved one. For instance, to make life a little simpler for the person receiving care, a routine might group together early morning actions like switching off the alarm, playing a news bulletin and turning on the coffee machine, all of which can be triggered with a single voice command.   .... ' 

Earthquake Detection Algorithms

Relates to our previous examination of work  done on earthquake detection.  Makes sense such work is out of Japan.

Gravity signals could detect earthquakes at the speed of light

Algorithm set for deployment in Japan could identify giant temblors faster and more reliably


Two minutes after the world’s biggest tectonic plate shuddered off the coast of Japan, the country’s meteorological agency issued its final warning to about 50 million residents: A magnitude 8.1 earthquake had generated a tsunami that was headed for shore. But it wasn’t until hours after the waves arrived that experts gauged the true size of the 11 March 2011 Tohoku quake. Ultimately, it rang in at a magnitude 9—releasing more than 22 times the energy experts predicted and leaving at least 18,000 dead, some in areas that never received the alert. Now, scientists have found a way to get more accurate size estimates faster, by using computer algorithms to identify the wake from gravitational waves that shoot from the fault at the speed of light.

“This is a completely new [way to recognize] large-magnitude earthquakes,” says Richard Allen, a seismologist at the University of California, Berkeley, who was not involved in the study. “If we were to implement this algorithm, we’d have that much more confidence that this is a really big earthquake, and we could push that alert out over a much larger area sooner.”

Scientists typically detect earthquakes by monitoring ground vibrations, or seismic waves, with devices called seismometers. The amount of advance warning they can provide depends on distance between the earthquake and the seismometers, and the speed of the seismic waves, which travel less than 6 kilometers per second. Networks in Japan, Mexico, and California provide seconds or even minutes of advance warning, and the approach works well for relatively small temblors. But beyond magnitude 7, the earthquake waves can saturate seismometers. This makes the most destructive earthquakes, like Japan’s Tohoku quake, the most challenging to identify, Allen says.  ...

Context In Machine Intelligence

I often make this point ... context is everything ... in fact I like to make the expansion of this as well:  'Context is everything', and its always changing"      Its like how we use all 'intelligence' that  is presented in a context, and included in that context are usually a number of uncontrolled time dimensions, like history and customer status and  other domain considerations, random context elements, etc  

Advancing Machine Intelligence: Why Context Is Everything  in TowardsDataScience  By Gadi Singer May 10

Most of us have heard the phrase, “Image is everything.” But when it comes to taking AI to the next level, it’s context that is everything.

Contextual awareness embodies all the subtle nuances of human learning. It is the ‘who’, ‘why’, ‘when’, and ‘why’ that inform human decisions and behavior. Without context, the current foundation models are destined to spin their wheels and ultimately interrupt the trajectory of expectation for AI to improve our lives.

This blog will discuss the significance of context in ML, and how late binding context could raise the bar on machine enlightenment.

Why Context Matters

Context is so deeply embedded in human learning that it is easy to overlook the critical role it plays in how we respond to a given situation. To illustrate this point, consider a conversation between two people that begins with a simple question: How is Grandma?

In a real-world conversation, this simple query could elicit any number of potential responses depending on contextual factors, including time, circumstance, relationship, etc.:

Fig 1. A proper answer to “How’s Grandma?” is highly context-dependent. 

The question illustrates how the human mind can track and take into account a vast amount of contextual information, even subtle humor, to return a relevant response. This ability to fluidly adapt to a variety of often subtle contexts is well beyond the reach of modern AI systems.

To grasp the significance of this deficit in machine learning, consider the development of reinforcement learning (RL)-based autonomous agents and robots. Despite the hype and success that RL-based architectures have had in simulated game environments like Dota 2 and StarCraft II, even purely gaming environments like NetHack pose a formidable obstacle to current RL systems due to the highly conditional nature and complexity of policies that are required to win the game. Similarly, as noted in many recent works, autonomous robots have miles to go before they can interact with previously unseen physical environments without the need of a serious engineering effort to either simulate the correct type of environment prior to deployment, or to harden the learned policy.

Current ML and Handling of Contextual Queries

With some notable exceptions, most ML models incorporate very limited context of a specific query, relying primarily on the generic context provided by the dataset that the model is trained or fine-tuned on. Such models also raise significant concerns about bias which makes them less suited for use in many business, healthcare, and other critical applications. Even state-of-the-art models like D3ST used in voice assistant AI applications require manually creating descriptions of schemata or ontologies with possible intents and actions that the model needs to identify context. While this involves a relatively minimal level of handcrafting, it nonetheless means that an explicit human input is required every time the context of the task is to be updated.

That’s not to say there haven’t been significant developments in context awareness for machine learning models. GPT-3, a famous large language model from the OpenAI team, has been used to generate full articles that rival human composition — a task that requires keeping track of at least local context. The Pathways Language Model (PaLM), introduced by Google in April 2022, demonstrates even greater capability, including the ability to understand conceptual combinations in appropriate contexts to answer complex queries.  ... 

Interactive Big Data Journalism

Finding information and useful interaction with it.   Though unclear what a 'big data journalism' means here. 

Interactive Tools May Help People Become Big Data Journalists

By Penn State News, May 6, 2022

Pennsylvania State University (Penn State) researchers say people could use interactive tools to navigate, save, and tailor online content to extract meaning from big data.

The researchers found people more engaged with news websites that offered modality, message, and source interactivity tools than with sites that did not.

Penn State's S. Shyam Sundar said user experience is shaped by how these tools may be combined and how engaged users are in the topic; for example, the most engaging sites boasted a high concentration of modality tools and message interactivity.

"The types of interactivities we are talking about here can help users find information that they find personally meaningful and that they care about," Sundar said.

From Penn State News

View Full Article  

Archaeological Artifact Visualization

Thinking of some other uses of creation and identification.

 DIY Digital Archaeology: Methods for Visualizing Small Objects, Artifacts

Max Planck Institute for the Science of Human History, April 13, 2022

Researchers at Germany's Max Planck Institute for the Science of Human History (SHH), the U.K.'s University of Exeter, and Japanese videogame developer Cygames collaborated on new techniques for visualizing small artifacts. The Small Object and Artifact Photography (SOAP) protocol guides users through the process of photographing small objects and artifacts. The High Resolution Photogrammetry (HRP) protocol is a manual for developing high-resolution three-dimensional models by combining methods applied in academic and computer graphic fields. The researchers developed the techniques using Adobe Camera Raw, Adobe Photoshop, RawDigger, DxO Photolab, and RealityCapture, leveraging native functions and tools that simplify and accelerate image capture and processing. "By clearly explaining every step of the process, including theoretical and practical considerations, these methods will allow users to produce high-quality, publishable two- and three-dimensional visualizations of their archaeological artifacts independently," said SHH's Jacopo Niccolò Cerasoni. .... ' 

Tuesday, May 10, 2022

UK Blames Russia For Satellite Hack

In the BBC, more examples of tech warfare and implications.

UK blames Russia for satellite internet hack at start of war   By Chris Vallance,  BBCTechnology Reporter

Russia was behind a cyber-attack targeting American commercial satellite internet company Viasat, UK and US intelligence suggests. The attack began about an hour before Russia invaded Ukraine, on 24 February.

It caused outages for several thousand Ukrainian customers - and affected windfarms and internet users in Central Europe. Officials have long believed Russia was to blame but lacked the evidence to say so publicly. Viasat provides high-speed satellite broadband to commercial and military customers.

The company has previously said "tens of thousands of terminals" were damaged beyond repair, in the cyber-attack, though its core network infrastructure and the satellite itself remained unscathed.  .... ' 

IBM's Plan for Quantum

Reasonable?  See links in the article to former quantum roadmaps. 

 IBM wants its quantum supercomputers running at 4,000-plus qubits by 2025  By A. Tarantola in Engadget

That's nearly a full magnitude more powerful than today's state-of-the-art systems.

Forty years after it first began to dabble in quantum computing, IBM is ready to expand the technology out of the lab and into more practical applications — like supercomputing! The company has already hit a number of development milestones since it released its previous quantum roadmap in 2020, including the 127-qubit Eagle processor that uses quantum circuits and the Qiskit Runtime API. IBM announced on Wednesday that it plans to further scale its quantum ambitions and has revised the 2020 roadmap with an even loftier goal of operating a 4,000-qubit system by 2025.

Before it sets about building the biggest quantum computer to date, IBM plans release its 433-qubit Osprey chip later this year and migrate the Qiskit Runtime to the cloud in 2023, “bringing a serverless approach into the core quantum software stack,” per Wednesday’s release. Those products will be followed later that year by Condor, a quantum chip IBM is billing as “the world’s first universal quantum processor with over 1,000 qubits.”

This rapid four-fold jump in quantum volume (the number of qubits packed into a processor) will enable users to run increasingly longer quantum circuits, while increasing the processing speed — measured in CLOPS (circuit layer operations per second) — from a maximum of 2,900 OPS to over 10,000. Then it’s just a simple matter of quadrupaling that capacity in the span of less than 24 months. .... '

Ricardian Contracts vs Smart Contracts

 Brought to my attention, unsure as yet how broadly the definition is used at this time, can see the need for the understanding of such an agreement by human and machine means.

The Ricardian contract, as invented by Ian Grigg in 1996, (Wikipedia)  is a method of recording a document as a contract at law, and linking it securely to other systems, such as accounting, for the contract as an issuance of value.[1][2] It is robust through use of identification by cryptographic hash function, transparent through use of readable text for legal prose and efficient through markup language to extract essential information.

A Ricardian contract places the defining elements of a legal agreement in a format that can be expressed and executed in software.[3] The key is to make the format both machine-readable, such that they can easily be extracted for computational purposes, and readable as an ordinary text document such that lawyers and contracting parties may read the essentials of the contract conveniently.[4]

From a legal perspective, the use of markup language embedded within a mostly legal prose document leads to reduced transaction costs, faster dispute resolution, better enforceability and enhanced transparency.[4][5] From a computing perspective, the Ricardian contract is a software design pattern to digitize documents and have them participate within financial transactions, such as payments, without losing any of the richness of the contracting tradition. Publication of the content and reference to that content by the unique cryptographic message digest eliminates frauds based on multiple presentations.[5]

The method arises out of the work of Ian Grigg completed in the mid-1990s in contributions to Ricardo,[6] a system of assets transfers that was built in 1995-1996 by Systemics and included the pattern. The system and the design pattern was named after David Ricardo in honour of his seminal contribution to international trade theory.  .... '  

Government Authority Falls Due to Algorithm

Regulation 0f algorithms causes Dutch Tax Authority to fail.  An unusual event.  Fairness and impacts. 

The Dutch Tax Authority Was Felled by AI—What Comes Next? European regulation hopes to rein in ill-behaving algorithms by RAHUL RAO     in Spectrum IEEE

Until recently, it wasn’t possible to say that AI had a hand in forcing a government to resign. But that’s precisely what happened in the Netherlands in January 2021, when the incumbent cabinet resigned over the so-called kinderopvangtoeslagaffaire: the childcare benefits affair.

When a family in the Netherlands sought to claim their government childcare allowance, they needed to file a claim with the Dutch tax authority. Those claims passed through the gauntlet of a self-learning algorithm, initially deployed in 2013. In the tax authority’s workflow, the algorithm would first vet claims for signs of fraud, and humans would scrutinize those claims it flagged as high risk.

In reality, the algorithm developed a pattern of falsely labeling claims as fraudulent, and harried civil servants rubber-stamped the fraud labels. So, for years, the tax authority baselessly ordered thousands of families to pay back their claims, pushing many into onerous debt and destroying lives in the process.

“When there is disparate impact, there needs to be societal discussion around this, whether this is fair. We need to define what ‘fair’ is,” says Yong Suk Lee, a professor of technology, economy, and global affairs at the University of Notre Dame, in the United States. “But that process did not exist.”

Postmortems of the affair showed evidence of bias. Many of the victims had lower incomes, and a disproportionate number had ethnic minority or immigrant backgrounds. The model saw not being a Dutch citizen as a risk factor.

“The performance of the model, of the algorithm, needs to be transparent or published by different groups,” says Lee. That includes things like what the model’s accuracy rate is like, he adds.  .... '

Reducing COVID-19 Patient Breathing Effort

 Respitatory Support for COVID Patients with computational modeling

Reducing COVID-19 Patients' Breathing Efforts Could Be Key to Success of Non-Invasive Respiratory Support

University of Warwick (U.K.),   April 21, 2022

A team of U.S., U.K., and Irish researchers has used computational modeling to demonstrate that non-invasive respiratory support is more likely to be successful if it relies on significantly reducing patients' efforts to breath. Researchers at the U.K.'s University of Warwick created computer simulations of 120 COVID-19 patients to measure the internal mechanics generated by different types of non-invasive support at different levels of breathing intensity. They found that while non-invasive measures improved oxygenation, stresses and strains within the lung could be elevated to potentially dangerous levels without any reduction in breathing effort. Said Dr. Luigi Camporata, “These results provide urgently needed evidence to help clinicians manage and optimize the treatment of COVID-19 patients in a way that averts additional and preventable lung injury.” .... '