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Friday, May 20, 2022

Anti-aging Drugs are Being Tested as a Way to Treat Covid

Covid advances from alternative  treatmens.

Anti-aging Drugs are Being tested as a way to treat covid

Drugs that rejuvenate our immune systems and make us biologically younger could help protect us from the disease’s worst effects.

By Jessica Hamzelou, May 17, 2022

Covid-19 is far more likely to kill you if you’re old. One reason is that aged immune systems struggle to cope with infections and recover from them. So why not try drugs that make bodies young again? That’s the bold idea now being explored in clinical trials around the world, which are testing drugs that reverse the impacts of age on the body, rejuvenate the immune system and clear out aged, worn-out cells. 

Some scientists avoid using the term “anti-aging” because of its snake oil connotations—but these drugs specifically target the biology of aging. It makes intuitive sense to use them to help older bodies fight back against any infection. These drugs could potentially help anyone with a worn-out immune system—whether as a result of age, childhood disease, or chronic illness.  ... ' 

Meta AI System

 Plan to test


Meta has built a massive new language AI—and it’s giving it away for free

Facebook’s parent company is inviting researchers to pore over and pick apart the flaws in its version of GPT-3

By Will Douglas    May 3, 2022

Meta’s AI lab has created a massive new language model that shares both the remarkable abilities and the harmful flaws of OpenAI’s pioneering neural network GPT-3. And in an unprecedented move for Big Tech, it is giving it away to researchers—together with details about how it was built and trained.

“We strongly believe that the ability for others to scrutinize your work is an important part of research. We really invite that collaboration,” says Joelle Pineau, a longtime advocate for transparency in the development of technology, who is now managing director at Meta AI.

Meta’s move is the first time that a fully trained large language model will be made available to any researcher who wants to study it. The news has been welcomed by many concerned about the way this powerful technology is being built by small teams behind closed doors.

“I applaud the transparency here,” says Emily M. Bender, a computational linguist at the University of Washington and a frequent critic of the way language models are developed and deployed.  

“It’s a great move,” says Thomas Wolf, chief scientist at Hugging Face, the AI startup behind BigScience, a project in which more than 1,000 volunteers around the world are collaborating on an open-source language model. “The more open models the better,” he says.  ... 

Beyond GDP: A Framework for Measuring Economic Progress

 From: Irving Wladawsky-Berger:   A collection of observations, news and resources  ...

Beyond GDP: A Framework for Measuring Economic Progress 

“What is meant by economic progress, and how should it be measured?,” asked economists Diane Coyle and Leonard Nakamura in a recent paper  , Time Use and Household-Centric Measurement of Welfare in the Digital Economy. “The conventional answer is growth in real GDP over time or compared across countries, a monetary measure adjusted for the general rate of increase in prices. However, there is increasing interest in developing an alternative understanding of economic progress, particularly in the context of digitalization of the economy and the consequent significant changes Internet use is bringing about in production and household activity.”  .... ' 

Beware Allure of Training Tech

 As it says, context matters a great deal when training. Will the VR actually change results? 

Beware the allure of training technology   By Tim Marler in Defense News

The allure of training technology can often overshadow its value. Today, virtual reality, or VR, is a hot topic in the military training community, but training tools must be developed and selected according to their anticipated use. Context matters, and sometimes the best and most cost-effective training tool may just be a book.

While VR offers many benefits, the Department or Defense could seek to ensure that virtual training content derives from operational needs, integrates with existing processes and curricula, and is validated. Furthermore, this process could be assessed and refined continuously because although we cannot predict the future of technology, we can be confident that what we need and what we want will change.

The United States military has always derived great benefit from novel technological advances, and today is no exception. Rapid acquisition and innovation are focal points for the DoD. This focus extends to training as well, where emerging technologies can present many opportunities. But too often the tie from various capabilities to actual training objectives can be tenuous at best.

Within the training arena, there is now considerable focus on virtual reality and augmented reality. VR involves a user being completely immersed in a virtual environment, and AR involves overlaying virtual entities on real items. The Army, for example, is developing the Integrated Visual Augmentation System that will allow soldiers to see what combat vehicles see, have 3D terrain maps projected onto their real field of view and enable other capabilities for increased situational awareness.

In addition, most of the services are developing aspects of live, virtual and constructive, or LVC, capabilities that can, for example, allow pilots in real jets (live) to train with pilots in flight simulators (virtual) in different locations, all interacting with computer-based (constructive) representations of adversary jets ..... ' 

GPT-3 Algorithm Is Now Producing Billions of Words a Day

Consider the huge moves of GPT-3.

OpenAI’s GPT-3 Algorithm Is Now Producing Billions of Words a Day   By Jason Dorrier -Apr 04, 202110,176  in Singularity Hub

When OpenAI released its huge natural-language algorithm GPT-3 last summer, jaws dropped. Coders and developers with special access to an early API rapidly discovered new (and unexpected) things GPT-3 could do with naught but a prompt. It wrote passable poetry, produced decent code, calculated simple sums, and with some edits, penned news articles.

All this, it turns out, was just the beginning. In a recent blog post update, OpenAI said that tens of thousands of developers are now making apps on the GPT-3 platform.  Over 300 apps (and counting) use GPT-3, and the algorithm is generating 4.5 billion words a day for them.

Obviously, that’s a lot of words. But to get a handle on how many, let’s try a little back-of-the-napkin math.

The Coming Torrent of Algorithmic Content

Each month, users publish about 70 million posts on WordPress, which is, hands down, the dominant content management system online.

Assuming an average article is 800 words long—which is speculation on my part, but not super long or short—people are churning out some 56 billion words a month or 1.8 billion words a day on WordPress.

If our average word count assumption is in the ballpark, then GPT-3 is producing over twice the daily word count of WordPress posts. Even if you make the average more like 2,000 words per article (which seems high to me) the two are roughly equivalent.

Now, not every word GPT-3 produces is a word worth reading, and it’s not necessarily producing blog posts (more on applications below). But in either case, just nine months in, GPT-3’s output seems to foreshadow a looming torrent of algorithmic content.

GPT-3 Is Powering a Variety of Apps

So, how exactly are all those words being used? Just as the initial burst of activity suggested, developers are building a range of apps around GPT-3.

Viable, for example, surfaces themes in customer feedback—surveys, reviews, and help desk tickets, for instance—and provides short summaries for companies aiming to improve their services. Fable Studio is bringing virtual characters in interactive stories to life with GPT-3-generated dialogue. And Algolia uses GPT-3 to power an advanced search tool.

In lieu of code, developers use “prompt programming” by providing GPT-3 a few examples of the kind of output they’re hoping to generate. More advanced users can fine-tune things by giving the algorithm data sets of examples or even human feedback.

In this respect, GPT-3 (and other similar algorithms) may hasten adoption of machine learning in natural language processing (NLP). Whereas the learning curve has previously been steep to work with machine learning algorithms, OpenAI says many in the GPT-3 developer community have no background in AI or programming.

“It’s almost this new interface for working with computers,” Greg Brockman, OpenAI’s chief technology officer and co-founder, told Nature in an article earlier this month.

A Walled Garden for AI

OpenAI licensed GPT-3 to Microsoft—who invested a billion dollars in OpenAI in return for such partnerships—but hasn’t released the code publicly.  .... ' 

Thursday, May 19, 2022

Risk, A Users Guide

 Just brought to my attention, now reading. Many of the examples are military, which is OK by me.    I would have liked more distinctly quantitative analyses.  Worth the read.  

Risk: A User's Guide Hardcover – October 5, 2021   by Stanley McChrystal (Author), Anna Butrico (Author)

From the bestselling author of Team of Teams and My Share of the Task, an entirely new way to understand risk and master the unknown.

Retired four-star general Stan McChrystal has lived a life associated with the deadly risks of combat. From his first day at West Point, to his years in Afghanistan, to his efforts helping business leaders navigate a global pandemic, McChrystal has seen how individuals and organizations fail to mitigate risk. Why? Because they focus on the probability of something happening instead of the interface by which it can be managed.

In this new book, General McChrystal offers a battle-tested system for detecting and responding to risk. Instead of defining risk as a force to predict, McChrystal and coauthor Anna Butrico show that there are in fact ten dimensions of control we can adjust at any given time. By closely monitoring these controls, we can maintain a healthy Risk Immune System that allows us to effectively anticipate, identify, analyze, and act upon the ever-present possibility that things will not go as planned.

Drawing on examples ranging from military history to the business world, and offering practical exercises to improve preparedness, McChrystalillustrates how these ten factors are always in effect, and how by considering them, individuals and organizations can exert mastery over every conceivable sort of risk that they might face.

We may not be able to see the future, but with McChrystal’s hard-won guidance, we can improve our resistance and build a strong defense against what we know—and what we don't. .... ' 

Deepmind Gato Applications

Thinking this and it application.

DeepMind Introduces Gato, A New Generalist AI Agent   in InfoQ

Gato, as the agent is known, is DeepMinds’s generalist AI that can perform many different tasks that humans can do, without carving a niche for itself as an expert on one task. Gato can perform more than 600 different tasks, such as playing video games, captioning images and moving real-world robotic arms. Gato is a multi-modal, multi-task, multi-embodiment generalist policy.

DeepMind is one of the most well-known AI companies dedicated to the advancement of artificial intelligence. With several programs, it aims to offer new ideas and improvements in machine learning, engineering, simulation, and computer infrastructure. The remarkable all-in-one machine learning kit has recently gained popularity in the worldwide tech market.

DeepMind says that Gato is trained on a large number of datasets comprising agent experience in both simulated and real-world environments, in addition to a variety of natural language and image datasets.

Gato, like all AI systems, learns by example, ingesting billions of words, images from real-world and simulated environments, button presses, joint torques and more in the form of tokens. These tokens served to represent data in a way Gato could understand, enabling the system to perform different tasks.

Gato's architecture isn't that different from many of the AI systems in use today. In the sense that it's a Transformer, it's similar to OpenAI's GPT-3. The Transformer has been the architecture of choice for complicated reasoning tasks, displaying abilities in summarizing texts, producing music, categorizing objects in photos, and analyzing protein sequences.

Even more remarkable, Gato has a parameter count that is orders of magnitude lower than single-task systems, including GPT-3. Parameters are system components learnt from training data that fundamentally describe the system's ability to solve a problem, such as text generation. GPT-3 has more than 170 billion, while Gato has only 1.2 billion. ... '

Widely Available AI Could Have Deadly Consequences

Misuses of Drug Discovery


Widely Available AI Could Have Deadly Consequences,     By Wired, May 18, 2022

In September 2021, scientists Sean Ekins and Fabio Urbina were working on an experiment they had named the "Dr. Evil project." The Swiss government's Spiez laboratory had asked them to find out what would happen if their AI drug discovery platform, MegaSyn, fell into the wrong hands.

In much the way undergraduate chemistry students play with ball-and-stick model sets to learn how different chemical elements interact to form molecular compounds, Ekins and his team at Collaborations Pharmaceuticals used publicly available databases containing the molecular structures and bioactivity data of millions of molecules to teach MegaSyn how to generate new compounds with pharmaceutical potential. The plan was to use it to accelerate the drug discovery process for rare and neglected diseases. The best drugs are ones with high specificity—acting only on desired or targeted cells or neuroreceptors, for instance—and low toxicity to reduce ill effects.

Normally, MegaSyn would be programmed to generate the most specific and least toxic molecules. Instead, Ekins and Urbina programmed it to generate VX, an odorless and tasteless nerve agent and one of the most toxic and fast-acting human-made chemical warfare agents known today.

From Wired

View Full Article  

Smartphone App Could Make It Easy to Screen for Neurological Disease

 Connected with UCSD

'Eye-Catching' Smartphone App Could Make It Easy to Screen for Neurological Disease 

UC San Diego News Center

Liezel Labios, April 29, 2022

University of California, San Diego (UCSD) researchers have enabled screening for neurological diseases through an eye-scanning smartphone application. The app employs the near-infrared camera built into many newer smartphones in combination with a conventional selfie camera to measure changes in the pupil's diameter, which could be used to evaluate a person's cognitive condition. The infrared camera allows the app to estimate pupil size with sub-millimeter accuracy across various eye colors, while the selfie camera records the stereoscopic distance between smartphone and user. Said UCSD's Colin Berry, “We hope that this opens the door to novel explorations of using smartphones to detect and monitor potential health problems earlier on.”   .. .

Faster Ransomware Detection

But is the method easily side-stepped?

New Approach for Faster Ransomware Detection

By NC State University News, May 18, 2022

Engineering researchers at North Carolina State University (NC State) and Hewlett Packard Enterprise have come up with a new technique that can detect ransomware faster than previous systems.

The Field-Programmable Gate Array-Accelerated XGBoost Inference for Data Centers using High-Level-Synthesis (FAXID) approach is a hardware-based implementation of the ransomware-detecting XGBoost algorithm.   The researchers found FAXID was up to 65.8 times faster than software running XGBoost on a central processing unit, and 5.3 times faster than graphic processing unit-based deployment.

NC State's Archit Gajjar said FAXID can allocate security hardware's computational muscle to separate problems. "For example, you could devote a certain percentage of the hardware to ransomware detection and another percentage of the hardware to another challenge—such as fraud detection," he explained. .... '

The researchers found the new approach was just as accurate as software-based approaches at detecting ransomware, and up to 65.8 times faster. ...'

From NC State University News

View Full Article   

Combatting Brand Exposures with Trusted Intelligence

 Trusted Brand Intelligence

Combatting Brand Exposures with Trusted Intelligence


The only way to stay one step ahead of the adversary is by knowing their intent, toolset, infrastructure, target – and using this intelligence to inform action. As discussed in the recent webinar Dark Web Exposures Brought to Light, mitigating digital risk to your brand is not simply a matter of stumbling across a typosquatting domain or some isolated piece of stolen data. Both automation and human expertise are essential to proactively collecting mass amounts of data, sifting through thousands of data points, analyzing relationships among the data points, deciding on priorities, and ultimately taking action. 

This is especially true when trying to understand your brand exposure on the dark web. The dark web is where criminals sell leaked company data, ransomware actors buy direct access to corporate networks, threat actors coordinate attacks, and more. As such, it is a mine of valuable intelligence, but sources, such as forums, can be volatile and hard to track — not to mention noisy. They also frequently present technical and financial barriers to entry, making it difficult, inefficient, time consuming, and risky for an organization’s security team to access the relevant information and context.

To ensure security teams have access to relevant, real-time context on their brand exposure, Recorded Future pairs automation capabilities with our expert research team, Insikt Group, within the Intelligence Graph in order to discover, analyze, and map associations across billions of entities in real time. Our expert analyst team confirms the accuracy of the machine-generated links, trains the machine on new or important data points, and adds their own human-generated links based on advanced research and robust collections of special-access and dark web sources, based on years of experience, perception, and awareness that no machine could provide. 

With Brand Intelligence from Recorded Future, security teams can then make fast, informed decisions based on the most current intelligence related to threat actors, internet infrastructure, and attack targets. By collecting and scanning from the broadest range and variety of sources — not only from open web sources, but also from the dark web and technical sources — security teams have access to insights from the attacker to their victims, and can be more proactive, strategic, and effective in carrying out their security strategy to uncover and respond to brand exposures. 

Unmatched Brand Intelligence

The latest updates to the Brand Intelligence module are designed to help security teams focus their precious time on the most important and urgent brand-related threats:

Continuous monitor the dark web and beyond

By automatically collecting, aggregating, and analyzing data from an unrivaled range of sources spanning the open, closed, deep, and dark web, security teams are able to proactively detect and take down malicious sites faster and more efficiently. The Brand Intelligence module includes extensive visibility into domain registration data, malware logs, messaging platforms, social media profiles, and web pages with malicious content, saving analysts time in understanding and responding to brand-related threats. ... ' 

Wednesday, May 18, 2022

Advanced Recycling: Opportunities for Growth

Noting especially plastics. 

Advanced recycling: Opportunities for growth  in McKinsey

May 16, 2022 | ArticleBy Zhou Peng, Theo Jan Simons, Jeremy Wallach, and Adam Youngman

Advanced recycling: Opportunities for growth

As interest in the circular economy grows, emerging recycling technologies that are complementary with mechanical recycling are accelerating.

 Article (8 pages)

As industries continue to shift away from fossil fuels and toward sustainability, many consumer-packaged-goods (CPG) companies have pledged to sell goods that have less impact on the environment. These pledges affect a large portion of the plastic products people use or encounter in everyday life, including packaging materials such as bottles, caps, meal trays, and flexible film wrap. As a result, the demand for circular polymers is rapidly increasing—but capacity announcements are not on pace with demand growth.1

Advanced recycling offers one potential solution. This term refers to recent technological developments meant to complement mechanical recycling—which has generally been the default approach to recycling for the past 30 years. Mechanical recycling is most effective with high-quality, relatively clean sorted waste; it faces structural limitations such as limited pools of appropriate feedstock and resulting material properties that limit end-market applications.

Advanced recycling can not only expand the types of plastics that are recyclable but also produce plastics that have tailored molecular weight distributions and comonomers that are suited for high-value applications, such as flexible packaging for food. However, capacity is limited today; many of these technologies are still developing and scaling.

Given the still-limited scale and uncertain financial returns, advanced recycling is a work in progress. This article addresses the current state of affairs as well as how to mature advanced-recycling technologies, building out infrastructure and sortation, and setting up end-to-end partnerships.

Accelerating demand for recycled plastics

Demand for recycled polymers is growing, primarily because of increased consumer awareness, CPG pledges, and regulations (Exhibit 1). These plastics can be produced through either mechanical recycling or advanced recycling. In mechanical recycling, plastic waste is washed, shredded, and pelletized, while in advanced recycling there is a chemical change and a longer route to go from plastic waste to ready-to-use plastic.  ..... '

Are Shoppable Ads Finally Ready for Prime Time?

 Or has prime time completely changed its shopping dimensions?

Are Shoppable Ads Finally Ready for Prime Time?                by Tom Ryan in RetailWire 

At International Advertising Bureau’s (IAB) NewFronts showcase for digital marketers, Condé Nast, AMC Networks, Roku, YouTube, NBCUniversal and Amazon’s Twitch platform were among those pitching the promise of shoppable ads.

“How cool would it be if you could buy dresses right off the red carpet?” wondered Pam Drucker Mann, Condé Nast’s global chief revenue officer and president, during the publisher’s NewFront presentation in early May, according to Advertising Age.

Shoppable television ads — called t-commerce (television commerce), back in the day — were first hyped in the nineties when network executives promoted the idea of couch potatoes clicking a “buy” button on their remote control to purchase the sweater worn by Friends’ star Jennifer Aniston. Since then, experiments with apps, QR codes, website links, chatbots and screen placement to drive TV-watching impulse buys have taken place to little progress.  ... ' 

A New Language Interface for Object Detection

 A New Language Interface for Object Detection

Pix2Seq: A New Language Interface for Object Detection  in the Google AI Blog

Friday, April 22, 2022

Posted by Ting Chen and David Fleet, Research Scientists, Google Research, Brain Team

Object detection is a long-standing computer vision task that attempts to recognize and localize all objects of interest in an image. The complexity arises when trying to identify or localize all object instances while also avoiding duplication. Existing approaches, like Faster R-CNN and DETR, are carefully designed and highly customized in the choice of architecture and loss function. This specialization of existing systems has created two major barriers: (1) it adds complexity in tuning and training the different parts of the system (e.g., region proposal network, graph matching with GIOU loss, etc.), and (2), it can reduce the ability of a model to generalize, necessitating a redesign of the model for application to other tasks.

In “Pix2Seq: A Language Modeling Framework for Object Detection”, published at ICLR 2022, we present a simple and generic method that tackles object detection from a completely different perspective. Unlike existing approaches that are task-specific, we cast object detection as a language modeling task conditioned on the observed pixel inputs. We demonstrate that Pix2Seq achieves competitive results on the large-scale object detection COCO dataset compared to existing highly-specialized and well-optimized detection algorithms, and its performance can be further improved by pre-training the model on a larger object detection dataset. To encourage further research in this direction, we are also excited to release to the broader research community Pix2Seq’s code and pre-trained models along with an interactive demo.  .... 

Simpler Desalinization for Disaster

 Did a survey of desalinization methods in college.  Likely best for disaster relief.


By Payal Dhar (Freelance Blogger)

MIT researchers have developed a prototype of a suitcase-size device that can turn seawater into safe drinking water.

According to the International Desalination Association, more than 300 million people around the world now get their drinking water from the sea. With climate change exacerbating water scarcity globally, seawater desalination is stepping in to fill the void. But whereas commercial desalination plants are designed to meet large-scale demand, there is also a need for portable systems that can be carried into remote regions or set up as stand-ins for municipal water works in the wake of a disaster.

A group of scientists from MIT has developed just such a portable desalination unit; it’s the size of a medium suitcase and weighs less than 10 kilograms. The unit’s one-button operation requires no technical knowledge. What’s more, it has a completely filter-free design. Unlike existing portable desalination systems based on reverse osmosis, the MIT team’s prototype does not need any high-pressure pumping or maintenance by technicians.

The MIT researchers described their invention in a paper titled “Portable Seawater Desalination System for Generating Drinkable Water in Remote Locations.” The paper was posted in the 14 April online edition of Environmental Science & Technology, a publication of the American Chemical Society.

The unit uses produces 0.3 liters of potable drinking water per hour, while consuming a minuscule 9 watt-hours of energy. Plant-scale reverse-osmosis water-treatment operations may be three to four times as energy efficient, and yield far greater quantities of freshwater at much faster rates, but the researchers say the trade-off in terms of weight and size makes their invention the first and only entrant in a new desalination niche.

The most notable feature of the unit is its unfiltered design. A filter is a barrier that catches the impurities you don’t want in your water, explains Jongyoon Han, an electrical and biological engineer, and lead author of the study. “We don’t have that specifically because it always tends to clog, and [then] you need to replace it.” This makes traditional portable systems challenging for laypeople to use. Instead, the researchers use ion-concentration polarization (ICP) and electrodialysis (ED) to separate the salt from the water.

“Instead of filtering, we are nudging the contaminants [in this case, salt] away from the water,” Han says. This portable unit, he adds, is a good demonstration of the effectiveness of ICP desalination technology. “It is quite different from other technologies, in the sense that I can remove both large particles and solids all together.” .... ' 

Brain Has a Built-in System to Keep Unwanted Memories Out

 Potential applications?

The Brain Has a Built-in System to Keep Unwanted Memories Out, Study Finds

By Shelly Fan in SiggularityHub

We all have memories we’d rather forget. Yet too often they bubble up into our consciousness. That gaffe at work or during an interview? A faceplant after slipping on ice on a first date? An accidental reply-all to the whole family? (Cringe).

For most, a quick jab of embarrassment, anger, or fear is all we feel and it quickly dissipates. But for people with post-traumatic disorders (PTSD) or depression, unwanted memories from their trauma can seriously derail their lives.

So how is it that these memories only sometimes invade unsuspecting minds?

A new study in the Journal of Neuroscience has some answers. By scanning the brains of 24 people actively suppressing a particular memory, the team found a neural circuit that detects, inhibits, and eventually erodes intrusive memories.

A trio of brain structures makes up this alarm system. At the heart is the dACC (for “dorsal anterior cingulate cortex”), a scarf-like structure that wraps around deeper brain regions near the forehead. It acts like an intelligence agency: it monitors neural circuits for intrusive memories, and upon discovery, alerts the “executive” region of the brain. The executive then sends out an abort signal to the brain’s memory center, the hippocampus. Like an emergency stop button, this stops the hippocampus from retrieving the memory.

The entire process happens below our consciousness, suppressing unwanted memories so that they never surface to awareness.

But what happens if memories do break into our thoughts? Here, the dACC has another task. When proactive surveillance fails, the brain region increases its alert signal to the executive—think DEFCON1—probing it to further damp down activity in the hippocampus.

“Preventing unwanted memories from coming to mind is an adaptive ability of humans,” wrote the authors, led by Dr. Michael C. Anderson at the University of Cambridge and Dr. Xu Lei at Southwest University in Chongqing, China. .... '

Tuesday, May 17, 2022

Data Poisoning in AI

 Out of O'Reilly, had never heard of it, but can understand it happening: 

O'Reilly Infrastructure and Ops Newsletter: "...The next cybersecurity crisis: Poisoned AI was inevitable that AI and cybersecurity would collide in ways that are both beneficial and bad. One specific danger: data poisoning.      Manipulating the information used to train machines can be a nearly untraceable method for getting around AI-powered defenses..... " 

No Known Flaws in NIST Quantum Resistant Algorithms

Been re-involved in a quantum encryption effort, the below is from Schneier, has further comments, more at the link with some useful concerns about related flaws. 

The NSA Says that There are No Known Flaws in NIST’s Quantum-Resistant Algorithms

Rob Joyce, the director of cybersecurity at the NSA, said so in an interview:

The NSA already has classified quantum-resistant algorithms of its own that it developed over many years, said Joyce. But it didn’t enter any of its own in the contest. The agency’s mathematicians, however, worked with NIST to support the process, trying to crack the algorithms in order to test their merit.

“Those candidate algorithms that NIST is running the competitions on all appear strong, secure, and what we need for quantum resistance,” Joyce said. “We’ve worked against all of them to make sure they are solid.”

The purpose of the open, public international scrutiny of the separate NIST algorithms is “to build trust and confidence,” he said.

I believe him. This is what the NSA did with NIST’s candidate algorithms for AES and then for SHA-3. NIST’s Post-Quantum Cryptography Standardization Process looks good. ... ' 

Cognitive T-slot Sensor concept

Thinking this .... Cognitive slot ....smart notch ...  If you go, give us a report.  I will report it

Cognitive T-slot sensor concept: Increasing forming machine efficiency with cognitive transformation of industrial processes

Research News / May 02, 2022

Forming presses are widely used as key elements of industrial production processes. From automotive technology to refrigerators, almost every product we encounter contains formed parts. The purchasing costs of these machines can reach double-digit millions, and it takes a great deal of time to set up and adjust precisely as needed. Given such a high level of investment, buyers expect machinery of this kind to keep running efficiently for a long time without any loss in quality. At the Hannover Messe 2022, the Fraunhofer Cluster of Excellence Cognitive Internet Technologies CCIT will demonstrate how cognitive transformation of industrial processes can improve the efficiency of forming machines (Hall 5, Booth A06). The technology that serves as the basis for the exhibit is smartNOTCH – a cognitive T-slot.

A forming press demonstrator provides visitors with live insights into how a cognitive T-slot works. The process data transferred by smartNOTCH is visualized on a connected terminal.

During operation, forming presses create vast quantities of data that are captured and stored automatically – covering everything from process information (including the forming force or the number of strokes) and quality specifications to status-related data and process variables (such as the service life). To date, machine users have in most cases only been able to collect this data at the machine itself: It has not been possible for them to gain aggregated stocks of data from machine pools or to share it with stakeholders such as manufacturers or suppliers. Additionally, previous solutions have rarely provided structured analysis, evaluation and application options for data. They have not incorporated concepts and technology for closed data life cycles in which data can be sustainably processed, retrieved and easily distributed as a way of generating new findings. In short, there has been a lack of cognitive internet technologies.

Cognitive T-slot

At the Hannover Messe 2022, Fraunhofer CCIT will use forming machines as an example for showcasing a solution in which cognitive internet technologies ensure consistently transparent processes and, as a result, enhance overall equipment effectiveness. At the heart of this new technology is smartNOTCH, a cognitive T-slot that continually monitors production processes with automated methods. The new sensor concept can be integrated into the interior of a forming press easily and with flexibility – and once installed, it is able to measure deformations and loads at interfaces with tools as well as transfer data to evaluation systems wirelessly. “The technology enables continuous monitoring that can be used inline for wear detection, protection, acceptance and tool integration. This makes it possible to streamline workflows and make processes more agile,” says Robin Kurth, Head of Group Forming Machines at Fraunhofer CCIT.

Usage conditions can be attached to the data obtained through smartNOTCH, giving machine users the ability to decide who they want to share forming press data with, for what purpose and under what conditions. In this context, intelligent, secure and standardized edge devices provide the necessary interfaces for networked processing chains that straddle regional, national or international company boundaries. When data sovereignty is assured, and intellectual property (IP) along with it, data silos can be compiled. Users, manufacturers and suppliers of forming machines can then apply machine learning (ML) and artificial intelligence (AI) methods to the aggregated data, giving rise to new insights into the performance and error susceptibility of the machines. When developing a suitable analysis algorithm, the experience acquired by specialist employees throughout the long service life of a forming machine can provide additional input. Fraunhofer CCIT’s informed machine learning approach makes it possible to integrate this information.

Using data and creating new insights

The solution provides users, manufacturers and suppliers with precisely the information they need to increase the efficiency of forming machines – whenever they need it. This makes it possible to start up new machines and processes more quickly, test out new pressing tools with more specific aims in mind and perform preventive maintenance on presses, for example. Intelligent capturing, secure sharing and systematic evaluation of data can also allow new business models to emerge, enabling manufacturers and suppliers, for example, to provide their customers with not only hardware, but also smart services based on data. Examples include the remote operation of entire machines (Equipment-as-a-Service/EaaS) and targeted upgrading and modernization (retrofitting) of existing presses.

The Hannover Messe exhibit will put the smartNOTCH at the forefront: A forming press demonstrator provides visitors with live insights into how a cognitive T-slot works.

Federated Learning and Privacy

Definitions of the terms and much more...  

Federated Learning and Privacy

By Kallista Bonawitz, Peter Kairouz, Brendan Mcmahan, Daniel Ramage

Communications of the ACM, April 2022, Vol. 65 No. 4, Pages 90-97  10.1145/3500240

Machine learning and data science are key tools in science, public policy, and the design of products and services thanks to the increasing affordability of collecting, storing, and processing large quantities of data. But centralized collection can expose individuals to privacy risks and organizations to legal risks if data is not properly managed. Starting with early work in 2016,13,15 an expanding community of researchers has explored how data ownership and provenance can be made first-class concepts in systems for learning and analytics in areas now known as federated learning (FL) and federated analytics (FA).

With this expanding community, interest has broadened from the initial work on federations of mobile devices to include FL across organizational silos, Internet of Things (IoT) devices, and more. In light of this, Kairouz et al.10 proposed a broader definition:

Federated learning is a machine learning setting where multiple entities (clients) collaborate in solving a machine learning problem, under the coordination of a central server or service provider. Each client's raw data is stored locally and not exchanged or transferred; instead, focused updates intended for immediate aggregation are used to achieve the learning objective.

An approach very similar in both philosophy and implementation, federated analytics17 can be taken to allow data scientists to generate analytical insight from the combined information in decentralized datasets. While the focus here is on FL, much of the discussion on technology and privacy applies equally well to FA use cases.

This article provides a brief introduction to key concepts in federated learning and analytics with an emphasis on how privacy technologies may be combined in real-world systems and how their use charts a path toward societal benefit from aggregate statistics in new domains and with minimized risk to individuals and to the organizations who are custodians of the data.  ...... ' 

Amazon AWS Podcast

Following some useful information from Amazon:

 Emily Freeman

Emily Freeman is a technologist and a storyteller who helps engineering teams improve their velocity. As the author of DevOps for Dummies and the co-curator of 97 Things Every Cloud Engineer Should Know, she believes the biggest challenges facing developers aren’t technical, but human. Her mission in life is to transform technology organizations by creating company cultures in which diverse, collaborative teams can thrive. Emily focuses on DevOps and Developer Tooling at AWS.

Podcast host Dave Isbitski

Dave has been a professional speaker, trainer, and developer relations advocate for over two decades. He has taught full-day courses on many topics including software development, DevOps, mobile, voice and the cloud. Dave has helped launch numerous technology platforms and devices while at both Microsoft and Amazon. He can also be found on Twitter as theDaveDev. .... 

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.  ...