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Friday, April 30, 2021

Belief Propagation Algorithm for Complex Networks

Quite new to me,   see my link to 'belief propagation' ... which points to MIT work on Kalman Filters.  taking a closer look.    We worked with SFI.  

Can the 'Belief Propagation' Algorithm Accurately Describe Complex Networked Systems?  By Santa Fe Institute,  April 29, 2021

Researchers at the University of Michigan and the Santa Fe Institute (SFI) demonstrated a novel belief propagation algorithm to solve probabilistic models on networks containing short loops.

These algorithms can be used to model the spread of a disease, for instance, by looking at people in close contact with each other, not their entire network.

However, SFI's George Cantwell said, "Suppose Alice was in close contact with Bob, who was in contact with Charlotte. To know what happens to Alice, we need to know about Bob, and then Charlotte. But suppose it turns out that Charlotte was already in contact with Alice, now we've backed ourselves into a sort of infinite regress. To predict what happens to Alice, we need to first predict what happens to Bob, then Charlotte, then Alice again."

The researchers showed their method could make accurate theoretical predictions for realistic networks.

From Santa Fe Institute

  .. A messaging-passing algorithm known as belief propagation can be used to analyze large systems by breaking them down into smaller pieces and ensuring all the smaller solutions are consistent with each other. ... 

Ford Has Smarter Robotics

Some interesting advances mentioned.

Ford's Ever-Smarter Robots Are Speeding Up the Assembly Line By Wired

In 1913, Henry Ford revolutionized car-making with the first moving assembly line, an innovation that made piecing together new vehicles faster and more efficient. Some hundred years later, Ford is now using artificial intelligence to eke more speed out of today's manufacturing lines.

At a Ford Transmission Plant in Livonia, Michigan, the station where robots help assemble torque converters now includes a system that uses AI to learn from previous attempts how to wiggle the pieces into place most efficiently. Inside a large safety cage, robot arms wheel around grasping circular pieces of metal, each about the diameter of a dinner plate, from a conveyor and slot them together.

Ford uses technology from a startup called Symbio Robotics that looks at the past few hundred attempts to determine which approaches and motions appeared to work best. A computer sitting just outside the cage shows Symbio's technology sensing and controlling the arms. Toyota and Nissan are using the same tech to improve the efficiency of their production lines.

From Wired

Brain Like System Mimics Learning

Hmm, not sure of this, but interesting

 'Brain-Like Device' Mimics Human Learning in Major Computing Breakthrough

The Independent (U.K.), Anthony Cuthbertson, April 30, 2021

A device modeled after the human brain by researchers at Northwestern University and the University of Hong Kong can learn by association, via synaptic transistors that simultaneously process and store information. The researchers programmed the circuit to associate light with pressure by pulsing a light-emitting diode (LED) lightbulb and then applying pressure with a finger press. The organic electrochemical material enabled the device to construct memories, and after five training cycles it associated light with pressure and could detect pressure from light alone. Northwestern's Jonathan Rivnay said, "Because it is compatible with biological environments, the device can directly interface with living tissue, which is critical for next-generation bioelectronics."

Microsoft Does Mesh Presence and Shared Experiences

Microsoft seem to finally be bringing out AR/Telepresence/Mixed Reality for broader applications.  Much more at the link.  With offers to developers and some existing applications at the link.    Worth a look.  Have now seen several interesting past demonstrations, which lacked real usefulness.  

Introducing Microsoft Mesh

Microsoft Mesh enables presence and shared experiences from anywhere – on any device – through mixed reality applications. ... " 

Procter Aims to Modernize TeleDentistry

Seems a novel play: 

Grin Closes $14M Round With P&G, Triventures, and SpringRock Ventures To Modernize Teledentistry at Scale

Grin closes $14M round from P&G (NYSE: PG), Triventures, and SpringRock Ventures to modernize teledentistry at scale across the United States.  ... " 

Killing the Ad Cookie

Major players are talking about disabling the misused Cookie.  Still some argument about the method and implications.  And can we trust them to remove what drives their profits?


Apple and Google Are Killing the (Ad) Cookie. Here's Why, By Bloomberg, April 28, 2021

After years of debate, Apple Inc. and Google are making separate moves to effectively kill the software marketers use to track your online activity and tailor ads specifically for you. The moves are upending the way companies have reached audiences and made money from ads since the earliest days of the internet. Apple's plan has pleased privacy advocates but left mobile app developers, ad-tech firms and rivals (chiefly Facebook Inc.) worried and fuming. And Alphabet Inc.'s Google is nearing a similarly contentious update to its Chrome browser, which will radically alter how ads are targeted on websites. With these changes, both companies are wielding the kind of power normally only governments have.

1. What are Apple and Google actually doing?

Starting on Monday, Apple will require apps running on its devices to get consumer permission before tracking their activity on other apps and websites. The company has already outlawed the use of unauthorized third-party cookies on its Safari web browser. Now, that prohibition is coming to apps. Google, meanwhile, is inventing a cookie alternative, rather than crushing it. Google's feature will let marketers continue to target desired buckets of consumers, just no longer using an individual's web history. In theory, this will make it more difficult to mesh ad-tracking with information collected from data brokers and other providers, which has let marketers target consumers based on age, race and gender. Both companies are justifying their moves as improving privacy. Google, though, has pitched its effort as a balancing act between privacy and the survival of web publishing, which relies on ads.

From Bloomberg

Thursday, April 29, 2021

Nuance and Microsoft Towards Healthcare

An indication by Microsoft about their seriousness in delivering healthcare.

 Microsoft's Nuance Gambit Shows Healthcare Shaping Up as Next Tech Battleground

The Wall Street Journal, Rolfe Winkler; Aaron Tilley, April 14, 2021

Microsoft's $16-billion acquisition of Nuance Communications Inc. comes as the pandemic highlights the healthcare industry's potential as a growth area for technology companies. Analysts say the deal will enable Microsoft to use the speech-recognition software provider as a way to sell more lucrative products and services to its healthcare customers. In addition, Microsoft will be able to integrate the understanding of medical terminology in Nuance's language-processing engine into products like Teams. The Nuance deal follows Amazon’s announcement of plans to roll out telehealth services nationwide. Meanwhile, Apple is selling its iPhone and Apple Watch devices to healthcare providers, and Google is working with two medical systems to make health records searchable. Gartner Inc.'s Gregg Pessin said, "The pandemic response by the healthcare industry has proven the value of technology to healthcare delivery. All the digital giants are paying attention."

Amazon and Walmart Eyeing Further Garage and in Home Drop off.

 I thought this approach had been limited, hearing little about it recently.   But apparently Amazon and Wal-Mart are thinking to expand it.   

Will Americans open their garages and homes to Amazon and Walmart?  by George Anderson in Retailwire

Amazon.com and Walmart are both planning to expand delivery services that give them access to the homes of customers.

Expansion of the services was likely sidetracked in the last year over safety concerns related to the spread of COVID-19. With millions of Americans getting vaccinated and some of the stress around the threat relieved, the two companies are looking to get closer to their customers than ever before.

Amazon announced that it is expanding its Key by Amazon In-Garage Grocery Delivery service to more than 5,000 cities and towns across the country. The service, which was originally announced in 2019, will now be made available to millions of eligible Prime members who order groceries from Amazon Fresh or Whole Foods.  ... ' 

Trust and Scientific Data Sharing

A key point.  Its trust in various contexts as well, like misuse.    And data is an asset, a concept we also experimented with.  We also discovered that data value often emerged much later.  So what then is the basis of the sharing?

Trustworthy Scientific Computing   By Sean Peisert

Communications of the ACM, May 2021, Vol. 64 No. 5, Pages 18-21  10.1145/3457191

Data useful to science is not shared as much as it should or could be, particularly when that data contains sensitivities of some kind. In this column, I advocate the use of hardware trusted execution environments (TEEs) as a means to significantly change approaches to and trust relationships involved in secure, scientific data management. There are many reasons why data may not be shared, including laws and regulations related to personal privacy or national security, or because data is considered a proprietary trade secret. Examples of this include electronic health records, containing protected health information (PHI); IP addresses or data representing the locations or movements of individuals, containing personally identifiable information (PII); the properties of chemicals or materials, and more. Two drivers for this reluctance to share, which are duals of each other, are concerns of data owners about the risks of sharing sensitive data, and concerns of providers of computing systems about the risks of hosting such data. As barriers to data sharing are imposed, data-driven results are hindered, because data is not made available and used in ways that maximize its value.

Hardware trusted execution environments can form the basis for platforms that provide strong security benefits while maintaining computational performance.

And yet, as emphasized widely in scientific communities,3,5 by the National Academies, and via the U.S. government's initiatives for "responsible liberation of Federal data," finding ways to make sensitive data available is vital for advancing scientific discovery and public policy. When data is not shared, certain research may be prevented entirely, be significantly more costly, take much longer, or might simply not be as accurate because it is based on smaller, potentially more biased datasets.

Scientific computing refers to the computing elements used in scientific discovery. Historically, this has emphasized modeling and simulation, but with the proliferation of instruments that produce and collect data, now significantly also includes data analysis. Computing systems used in science include desktop systems and clusters run by individual investigators, institutional computing resources, commercial clouds, and supercomputers such as those present in high-performance computing (HPC) centers sponsored by U.S. Department of Energy's Office of Science and the U.S. National Science Foundation. Not all scientific computing is large, but at the largest scale, scientific computing is characterized by massive datasets and distributed, international collaborations. However, when sensitive data is used, computing options available are much more limited in computing scale and access. .... ' 

USAF Researchers Partner with Quantum Computing Company

Had a short connect with the USAF regarding IP Development

ACM NEWS  Exclusive: Air Force Research Taps Quantum Computing   By Axios   April 29, 2021

U.S. Air Force researchers are partnering with a quantum computing company to use its machine learning algorithms, Axios has learned.

Why it matters: Quantum is the next generation of computing, and its growing adoption by the military shows the progress of the technology as it gradually moves out of the lab and into the real world.

Driving the news: Later this morning the Air Force Research Laboratory (AFRL) — its technological development wing — will announce a partnership with the quantum computing software company QC Ware to harness its algorithms to better surveil unmanned aircraft.  (to follow) 

From Axios

Ring Adds a Geofence

A geofence is a concept to integrate specific programmed reactions to changes in physical location.  Usually leaving some 'fence' or multidimensional area.  For example a geofence might be set to open a garage door when their automobile gets inside an established 'geofence'.   Ring describes its system: 

Geofence in the Ring App

This article will cover commonly asked questions about the Ring Geofence feature.

What is a Geofence?

A geofence is a virtual perimeter or invisible boundary around a particular geographic location. When you configure a geofence in the Ring app, the Ring app can remind you to set your Mode to “Away” when you exit the geofence. When you come home and re-enter the geofence, your Ring app can automatically snooze alerts from your security cameras and doorbells.  ... " 

Ring devices are designed to make your home security simple and convenient. You want them to be helpful and there when you need them, and blend into the background when you don’t. Rolling out today, Geofence introduces certain automations for the Ring App, such as receiving fewer alerts from your Ring Video Doorbell and Security Cameras when you arrive home, and getting reminders to switch your Ring Alarm and other devices to Away Mode when you leave. Geofence makes your home security more convenient and tailored to your personal preferences than ever, for added peace of mind.

Automated Alerts and Reminders

When you set up Geofence, you create an invisible boundary around your home or business. Once Geofence is enabled, certain alerts can be automated based on the location of your mobile device in relation to the boundary. Your mobile device provides location updates to the Ring App, which will then determine what alerts should be sent whether or not your mobile device is entering or leaving the boundary..... '

Extended Reality to Support Innovation

Towards extended reality they say.  Ways to quickly formulate, test, record results, and use new data effectively would be most useful to support such apporaches. 

Researchers Develop First-of-Its-Kind Extended Reality Testbed to Speed Virtual, Augmented Reality Innovation.     By University of Illinois Urbana-Champaign

University of Illinois at Urbana-Champaign (UIUC) researchers have launched an open source extended reality (XR) testbed to democratize XR systems research, development, and benchmarking.

XR is an umbrella term for virtual, augmented, and mixed reality, and UIUC's Sarita Adve cited an orders of magnitude gap between the performance, power, and usability of current and desirable XR systems.

The Illinois Extended Reality (ILLIXR) testbed is an end-to-end XR system that all types of XR scientists can use to research, develop, and benchmark concepts in the context of a complete XR system, and observe the effect on end-user experience.

Facebook's Rod Hooker said, "ILLIXR's open source modular architecture enables the XR research community to address challenging problems in the areas of optimizing algorithms, system performance/power optimizations, scheduler development, and quality-of-service degradation."

From University of Illinois Urbana-Champaign

Wednesday, April 28, 2021

EBook on Ensemble Learning

I see that Jason Brownlee has a new book on Ensemble Learning,  a method  I recently mentioned here,  “Ensemble Learning Algorithms With Python“   at the link a considerable look at it. Have not examined it myself as yet.  

so What is Ensemble Learning?

Ensemble learning algorithms combine the predictions of two or more models.

The idea of ensemble learning is closely related to the idea of the “wisdom of crowds“. This is where many different independent decisions, choices or estimates are combined into a final outcome that is often more accurate than any single contribution.

This is the core idea behind major aspects of modern society, such as a scientific peer review, a jury of peers, and seeking a second opinion. It is an alternative to seeking out and taking the advice of an expert.

In applied machine learning, it means combining the predictions from multiple models trained on your dataset, instead of seeking the single best performing model. ... 

Why Regulation Won't Harm Cryptocurrencies?

Though I imagine they could.

Why Regulation Won’t Harm Cryptocurrencies   From Knowledge @ Wharton,  Apr 27, 2021 


Wharton’s Brian Feinstein speaks with Wharton Business Daily on SiriusXM about the regulation of cryptocurrencies.

Audio Player

The confirmation on April 14 of Gary Gensler as chairman of the Securities and Exchange Commission has fueled worries that increased regulation of cryptocurrencies would hurt trading volumes and prices and stifle innovation in the nascent segment, and prompt industry participants to flee to less stringent jurisdictions. However, those fears are unfounded, and tighter regulation could purge the industry of bad actors and engender trust, which in turn would help it grow, according to Brian Feinstein and Kevin Werbach, Wharton professors of legal studies and business ethics.

The day of Gensler’s confirmation coincided with the $85 billion IPO of Coinbase, the largest cryptocurrency trading platform in the U.S. The Coinbase IPO was “a watershed moment for an industry that began a decade ago as an experiment in digital money,” according to The Wall Street Journal. Cryptocurrencies will be high on Gensler’s agenda. He had described them as “catalysts for change” in his confirmation hearings, but also said they raise “new issues of investor protection.” In the least, he promised that the SEC would provide “guidance and clarity” on regulating the cryptocurrency market.

“With the confirmation of a new SEC chair who has his eye on cryptocurrency, we can expect the imposition of securities law framework onto cryptocurrencies in the U.S. and new investor protection measures,” Feinstein said in an interview on the Wharton Business Daily radio show on SiriusXM. (Listen to the podcast above.)

A Wall Street Journal editorial titled “The SEC’s Cryptocurrency Confusion” echoed the concerns raised by critics who are worried about regulatory overreach, stating that “regulators are creating danger for currency developers and retail investors” in the cryptocurrency market, the size of which it estimated at $2 trillion in market capitalization.  .... " 

Unlocking Category & Brand Growth with Data Science

Late to announce this, included some people I know from MIT.   I attended

Web Event Reminder: Unlocking Category & Brand Growth with Data Science will be held 04/28/2021 at 11:00 AM EDT  ... 

[  This was a good presentation, will place the link to it here in a day or  two ]

If you have any issues accessing the event or have any questions, please contact Betty Dong at bdong@ensembleiq.com.  .... 

Via Consumer Goods Technology  CGT

AI Agents for Lab Work

 Can see this useful for other kinds of 'labs',  A lab is a business process with specific goals, and scientific constraints, like those we worked with.  Better, faster cheaper, compliantly.  Carefully trained.  

AI Agent Helps Identify Material Properties Faster,  By Ruhr-University Bochum (Germany), April 27, 2021

Researchers at Brookhaven National Laboratory, the University of Liverpool in the U.K., and the Ruhr-University Bochum in Germany demonstrated that artificial intelligence (AI) can speed up X-ray diffraction data (XRD) analysis and improve accuracy in searches for new materials.

The researchers developed an AI agent, Crystallography Companion Agent (XCA), that collaborates with scientists when it comes to decision-making,  XCA can perform autonomous phase identifications from XRD data while it is measured and works with both organic and inorganic material systems.

The algorithm was trained using a large-scale simulation of physically correct X-ray diffraction data.

Ruhr's Lars Banko said the decision-making process "is simulated by an ensemble of neural networks, similar to a vote among experts. This is accomplished without manual, human-labelled data and is robust to many sources of experimental complexity."

Ruhr's Alfred Ludwig called the research "an important step in accelerating the discovery of new materials."

From Ruhr-University Bochum (Germany)

Support a Bounty for Prior Art

Was slightly involved with an effort regarding patent trolls.  Very long since I touched on this.   Push obviousness.   Like this approach. Agree its the way to go.  PTO needs to be evolved.   Which reminded me of:   Trolls are 'Non practicing entities'   MUCH more at the link, though business-IP technical.

Project Jengo Redux: Cloudflare’s Prior Art Search Bounty Returns

04/26/2021, By Doug Kramer  in Cloudflare's Blog. 

Here we go again.

On March 15, Cloudflare was sued by a patent troll called Sable Networks — a company that doesn’t appear to have operated a real business in nearly ten years — relying on patents that don’t come close to the nature of our business or the services we provide. This is the second time we’ve faced a patent troll lawsuit.

As readers of the blog (or followers of tech press such as ZDNet and TechCrunch) will remember, back in 2017 Cloudflare responded aggressively to our first encounter with a patent troll, Blackbird Technologies, making clear we wouldn’t simply go along and agree to a nuisance settlement as part of what we considered an unfair, unjust, and inefficient system that throttled innovation and threatened emerging companies. If you don’t want to read all of our previous blog posts on the issue, you can watch the scathing criticisms of patent trolling provided by John Oliver or the writers of Silicon Valley.

We committed to fighting back against patent trolls in a way that would turn the normal incentive structure on its head. In addition to defending the case aggressively in the courts, we also founded Project Jengo — a crowdsourced effort to find evidence of prior art to invalidate all of Blackbird’s patents, not only the one asserted against Cloudflare. It was a great success — we won the lawsuit, invalidated one of the patent troll’s other patents, and published prior art on 31 of Blackbird’s patents that anyone could use to challenge those patents or to make it easier to defend against overbroad assertion of those patents. And most importantly, Blackbird Technologies went from being one of the most prolific patent trolls in the United States to shrinking its staff and filing many fewer cases.

We’re going to do it again. And we need your help.

Turning the Tables — A $100,000 Bounty for Prior Art  ..... '

Navigating Complex Computer Instructions

Technical look at improvements in acceleration by better understanding computer instructions.

A Tool for Navigating Complex Computer Instructions

MIT Computer Science and Artificial Intelligence Laboratory, Rachel Gordon, April 16, 2021

A new tool developed by researchers at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the University of Illinois at Urbana-Champaign automatically generates compiler plugins that can handle more complex instructions. The tool, VeGen, could help eliminate the need for software developers to manually write assembly code for new Intel computer chips. The compiler plugins generated by VeGen allow for the exploitation of non-Single Instruction Multiple Data (SIMD), which allows multiple operations, like addition and subtraction, to be performed simultaneously. CSAIL's Yishen Chen said, "The long-term goal is that, whenever you add new features on your hardware, we can automatically figure out a way—without having to rewrite your code—to use those hardware accelerators."... ' 

Tuesday, April 27, 2021

Pluribus Networks

Brought to my recent attention:

Pluribus Netvisor® ONE R6.1 Delivers Innovations in Data Center Fabric Scalability, Services and Automation and Expands Portfolio of Disaggregated Switches

Enhancements within Netvisor ONE and the Adaptive Cloud Fabric™ Resonate with Customers, Supporting Larger, Seamlessly Interconnected Fabrics and a Dynamic Packet Broker Solution

SANTA CLARA – April 27, 2021 – Pluribus Networks, the leader in SDN automation and disaggregated networking, today announced the general availability of release 6.1 of its Linux Netvisor® ONE network operating system (OS). Recognized by the Financial Times as one of the 500 fastest growing companies in the Americas for a second consecutive year in 2021, Pluribus continues to demonstrate architectural innovation at a rapid pace, including feature enhancements that deliver affordable and highly automated data center fabrics for private cloud deployments.

Netvisor ONE 6.1 includes enhancements to the Adaptive Cloud Fabric™ that enable Pluribus customers to build bigger, faster fabrics with more services and even simpler operations, and also features the industry’s most flexible and scalable packet broker solution for network monitoring, security monitoring and visibility. R6.1 also further extends the Pluribus switch portfolio with support of multiple new Edgecore switches for 10/40/100 GbE deployments and delivers a highly automated BGP EVPN implementation for brownfield interoperability ...."

Quantum Sensing

New concept to me, but very much emerging.   This explains it.

Quantum Sensing Takes Shape   By Samuel Greengard

Commissioned by CACM Staff, April 27, 2021

" ...By measuring movements, rotations, absorption, and numerous other physical properties, quantum sensors can peer into previously invisible places...."

From compasses and thermometers to accelerometers and LiDAR, scientists and inventors have long searched for tools that help uBy measuring movements, rotations, absorption, and numerous other physical properties, quantum sensors can peer into previously invisible places.s understand our world better. Yet these devices typically run into the same basic limitation: they can only detect signals across a relatively narrow spectrum of light, sound, motion, and gravity waves.

That's poised to change. An emerging field called quantum sensing allows scientists to peer deeper into the surrounding world by detecting quantum state changes at an atomic and sub-atomic level. This technology would allow cars to see through fog, doctors to conduct medical scans with millimeter accuracy, and scientists to identify changes in the Earth that lead to seismic events such as earthquakes and volcanic eruptions.

The technology is nothing less than revolutionary. "Quantum sensors take detection far beyond what has ever been possible," says Kai Bongs, a professor in the School of Physics and Astronomy at the University of Birmingham in the U.K. "The field is likely to disrupt science and the economy in a major way."

Deep Sensing

The technology represents a quantum leap in sensing. Explained Jonathan L. Habif, a research assistant professor of electrical and computer engineering and research lead at the University of Southern California (USC), "For hundreds of years, we've modeled light and other properties as a wave based on their physical characteristics. But we're not able to calculate the fundamental structure and limits of nature simply by measuring light, sound or magnetic performance."

Yet characteristics such as light, sound, vibration, pressure, and magnetism are more than electromagnetic waves: "They're quantum mechanical systems," Habif says. This means some characteristics, qualities, and details lie beyond the scope of classical sensors. Yet by measuring movements, rotations, absorption, and numerous other physical properties, quantum sensors can peer into these previously invisible places.

Some quantum methods involve manipulating or "squeezing" photons to produce a higher signal-to-noise ratio, which enables ultrasensitive measurements. Others enhance or alter light-matter interactions. In the latter case, "This uniquely identifies the 'useful' signal from a classical background noise," says Daniele Faccio, Royal Academy of Engineering Chair in Emerging Technologies at the University of Glasgow School of Physics & Astronomy.

"Everything you can do classically, you can do quantum-mechanically," says Federico Spedalieri, a research assistant professor at USC, "but quantum mechanics may allow you to perform some sensing tasks better." In addition, he says quantum mechanics "introduces certain measurements that have no equivalent in classical systems." For example, it would allow a LiDAR system to see through fog, and perhaps around corners. It also makes it possible to develop sensing systems that find buried objects. ... " 

Implementing Insider Defenses

Quite a considerable look at the problem.   With video and overview.  Hardly all encompassing, but a useful broad look at the problem.

Implementing Insider Defenses By Eric Grosse, Fred B. Schneider, Lynette L. Millett  in CACM

Communications of the ACM, May 2021, Vol. 64 No. 5, Pages 60-65  10.1145/3418296

Classical approaches to cyber-security—isolation, monitoring, and the like—are a good starting point for defending against attacks, regardless of perpetrator. But implementations of those approaches in hardware and/or software can invariably be circumvented by insiders, individuals who abuse privileges and access their trusted status affords. An organizational culture in which people and procedures are part of the system's defenses is thus necessary. Such a culture would instantiate classical approaches to cyber-security but implemented by people who follow administrative procedures. So, a careful look at a system's defenses finds that many of the same classical approaches reappear at each level. But the implementation at the lowest layers—structures we might term insider defenses—involves people.

People do not slavishly follow administrative procedures the way a computing system executes its programs. In addition, people are more prone than computing systems to making errors, and people can be distracted or fooled. Finally, because they can be influenced by events both inside and outside of the workplace, people have very different kinds of vulnerabilities than computing systems. But people alter their behaviors in response to incentives and disincentives and, when empowered by organizational culture, they will (unlike computing systems) respond in reasonable ways to unusual or unanticipated circumstances. Thus, the use of people in a defense both offers benefits and brings different challenges than using hardware or software.

Those benefits and challenges are the focus of this article, which is informed by some recent discussions about best practices being employed at global IT companies and at the U.S. Department of Defense (DoD) for defense against insider attacks. The private sector and DoD are quite different in their willingness and ability to invest in defenses, in the consequences of successful attacks, and in the inclinations of their employees to tolerate strict workplace restrictions. Given those differences, two things we heard seemed striking and worth documenting for broader dissemination: How similar are the practices being used, and how these organizational structures and procedures to defend against insider threats can be seen as instantiating some classical approaches to cyber-security.  ..... " 

Origami Based Tire Design

Had not heard of such a design.   Pictures and some stats at the link.

Origami based tires can change shape while a vehicle is moving  by Bob Yirka , Tech Xplore

A team of researchers affiliated with Seoul National University, Harvard University and Hankook Tire and Technology Co. Ltd., has developed a tire based on an origami design that allows for changing the shape of a tire while a vehicle is moving. In their paper published in the journal Science Robotics, the group describes their new tire design and how well it worked when tested.

Origami is an art that involves folding paper to create a desired shape or figure. Originating with Japanese artists hundreds of years ago, it has become an international pastime. In more recent years, it has caught the interest of engineers who have used origami designs to create usable objects out of plastics and metals. In this new effort, the researchers have extended an origami design called a waterbomb tessellation—it involves creating a single wheel that can have two configurations depending on how it is used by a person holding it. The researchers have ramped up the design by making its facets out of metals such as aluminum and connecting them together using other materials.

The researchers realized the design in a variety of sizes—some of which were as large as automobile tires. The design could switch between configurations while bearing a heavy load and while serving as tires on a vehicle in motion. To test the capabilities of the design, they created several wheels that served as tires on a variety of vehicles. In all cases, the main difference between the two configurations was height. They demonstrated, for example, a vehicle sporting the specialized tires in the tall configuration as it approached a low underpass—too low for the vehicle to drive under with its initial configuration. The driver switched the tires to the low configuration as the vehicle was still moving, allowing the vehicle to pass beneath the underpass.  ... ' 

Amazon Opens a Hair Salon

 Intriguing leverage of expertise.  Also note 'point and learn' concept.  Amazon continues to consider other tech links to improved consumer interaction.

Why did Amazon open a hair salon?  in Retailwire   by Tom Ryan  with further expert comment

Amazon.com has opened a hair salon in its latest bricks-and-mortar experiment. The London location promises to allow the online giant to test new technologies, expand its B2B business with haircare professionals and potentially explore the haircutting opportunity.

Called Amazon Salon, the two-story, 1,500-square-foot location offers entertainment streaming on Amazon Fire tablets at each styling station as well as augmented reality hair consultations that lets individuals imagine a hair color before the dye is made up.

Amazon is testing a “point and learn” technology that allows customers to point at an item on a shelf and display product information on a screen mounted behind. The customer can then scan a QR code to order an item for home delivery.

Amazon Salon could be a showroom for technology bound for other salons. Just Walk Out technology was piloted at Amazon’s own Go convenience stores before being licensed to others.  ... " 

Ramsey Theory and Commercial Cliques

A colleague of mine and I brought this up and how we might potentially use it to understand some kinds of consumer group commercial behavior.   Glad to be reminded of this, and  thinking of how it might be tested with more data.  Ultimately this is technically deep,  but I think does have some useful insight.

 New Proof Reveals That Graphs With No Pentagons Are Fundamentally Different  By Steve Nadis in Quanta

Researchers have proved a special case of the Erdős-Hajnal conjecture, which shows what happens in graphs that exclude anything resembling a pentagon. 

When you walk into a room full of people, you can speculate about all sorts of things, from political leanings to TV viewing habits. But if the room has at least six people, you can say something about them with absolute mathematical certainty, thanks to a 1930 theorem by Frank Ramsey: Among those people, there’s either a group of three who all know each other, or a group of three who have never met.

The scope of Ramsey theory, which examines the patterns that emerge as a group gets larger, extends well beyond social gatherings. It also has direct and crucial implications for a branch of mathematics known as graph theory. These graphs consist of collections of points, or vertices, that may (or may not) be connected to each other by an edge — equivalent to people at a party who may (or may not) have met before. The size of a graph is set by n, the number of vertices it has. A portion of a graph in which every vertex is connected by an edge to every other vertex is, fittingly, called a clique. Conversely, a portion of a graph in which no vertex is connected to any other vertex is called an anticlique, or stable set.  ... " 

Sample Patterns and Predictions

 Like to see examples of this type to show what can be done with emerging tech. 

Open Source AI Can Predict Electrical Outages from Storms with 81% Accuracy  by Anthony Alford in Infoq

Development Group Manager at Genesys Cloud Services

A team of scientists from Aalto University and the Finnish Meteorological Institute have developed an open-source AI model for predicting electrical outages caused by storm damage. The model can predict storm location within 15km and classifies the amount of transformer damage with 81% accuracy, allowing power companies to prepare for outages and repair them more quickly.

The work was described in an article published in the European Geosciences Union's (EGU) Natural Hazards and Earth System Sciences (NHESS) journal. The model predicts damage to power transformers from large low-pressure storms up to 10 days in advance, categorizing the results as either no damage, low damage (less than 140 transformers damaged), or high (more than 140). The predictions are based on a support-vector classifier, which achieves 81% precision and 61% recall. Using this model, power companies can prepare materials and repair crews, restoring power to customers more quickly.

Because Finland is a heavily forested country, its overhead power lines are often damaged by falling trees, especially during strong extratropical storms; on average, about 46% of the country's power outages were caused by these storms. Because the power suppliers are required by law to provide their customers with financial compensation for prolonged outages, the companies maintain a large workforce for rapid repair. While several researchers have applied AI techniques to predict power outages from hurricanes, as well as damage to trees (not surprisingly, random forests work quite well for this task), there has been little work specifically on power outages due to extratropical storms. ... '

Data Monetization / Data as an Asset

A long time area of study for us.   Measuring the value of data in context.

Greasing the Wheels for Data Monetization   by 7wData

Data is a critical asset to business success.” That’s probably the closest thing to a self-evident truth you’re likely to find in today’s ultra-competitive business landscape. We all know how important data is. Those who have more of it, and know how to wield AI and advanced analytics upon it, have a substantial advantage. And yet, businesses face headwinds when trying to monetize their data, particularly outside their company. That’s why, when it comes to data monetization, we are still in the early stages of the game.

Doug Laney has dedicated a portion of his career to finding methods to break down the value behind data. His data valuation journey started after the Twin Towers came tumbling down on 9/11. The loss of life was tragic, but companies also lost enormous amounts of data. Insurance companies claimed that data had no value, hence Laney’s study of “Infonomics” was born.

Twenty years later, after a stint as a Gartner analyst Laney continues to study the nature of data at the business consulting firm West Monroe. He helps clients come up with strategies for managing data like the real asset that it is, and finding ways to use it for competitive advantage.  ... ' 

Monday, April 26, 2021

AI's Will Start to Hack

 Very good pieces below.  Something we talked about early in the days of AI, and when hacking did start to adapt to its environments.    Started with simplistic worms, that aimed to change their locations to find the most vulnerable place to attack.    We included it our predicted vulnerability reports, and it proved true, though needed time to adapt.  And now, since AI can find patterns of ideal vulnerability to adapt to, it is inevitable.  And will know how to cover their tracks.  Below his intro, then much more at the link and report below

When AIs Start Hacking  in Bruce Schneier

If you don’t have enough to worry about already, consider a world where AIs are hackers.

Hacking is as old as humanity. We are creative problem solvers. We exploit loopholes, manipulate systems, and strive for more influence, power, and wealth. To date, hacking has exclusively been a human activity. Not for long.

As I lay out in a report I just published, artificial intelligence will eventually find vulnerabilities in all sorts of social, economic, and political systems, and then exploit them at unprecedented speed, scale, and scope. After hacking humanity, AI systems will then hack other AI systems, and humans will be little more than collateral damage.

Okay, maybe this is a bit of hyperbole, but it requires no far-future science fiction technology. I’m not postulating an AI “singularity,” where the AI-learning feedback loop becomes so fast that it outstrips human understanding. I’m not assuming intelligent androids. I’m not assuming evil intent. Most of these hacks don’t even require major research breakthroughs in AI. They’re already happening. As AI gets more sophisticated, though, we often won’t even know it’s happening.  .... ' 

Considering Composite AI:

Could not agree more, but I am seeing practitioners wanting to stay with pure 'AI/Machine Learning'. It stays with the 'magic' of AI.  When hybrid methods should be used.  Why?  Because the other methods are seen as dated?  And require quite different training.  Are just classic analytics?  In typical analytics these are called 'Ensemble Methods', often mentioned here, we used them often, see the tags below.

Composite AI: What Is It, and Why You Need It    Alex Woodie in DataNami

You might have noticed a new term, “composite AI,” floating around the cybersphere. Don’t worry–it’s not a complex new technology that you must master. In fact, while the term may be new, the core idea behind it is not. Nevertheless, it’s likely a technique that you should be thinking about incorporating in your enterprise AI processes.

Gartner helped put composite AI on the map last summer, when it published its 2020 Hype Cycle for Emerging Technologies. Simply put, Composite AI refers to the “combination of different AI techniques to achieve the best result,” according to Gartner. That’s it. Simple enough, right?

So, what other AI techniques could that mean? It’s important here to keep in mind that AI is a very broad term. While some might believe that AI refers to the latest, greatest deep learning and neural network algorithms, AI actually covers much more under its sizable umbrella.

Machine learning and deep learning are types of AI. But there are many other types of AI that should be in your wheelhouse that fall outside of the machine learning/deep learning bubble. That includes traditional rules-based systems, natural language processing (NLP), optimization techniques, and graph techniques, according to Gartner.

A composite AI system is to be built atop a “composite architecture,” which Gartner identified as its number one Hype Cycle trend for 2020. A composite architecture (you might have guessed) incorporates packaged business capabilities that run atop a flexible data fabric, thereby enabling users to take be flexible and adaptable amidst rapidly changing systems and requirements.   ... "

Incomplete Contracts

Followup on previous piece: 

Incomplete Contracts  by Jesse Walden  in Andreessen Horowitz

cryptocurrencies & blockchains

One way to think about various kinds of crypto projects is through the lens of contract theory. An axiom of this area of legal scholarship states: “all but the simplest contracts are incomplete”. That is, contractual arrangements cannot anticipate every possible outcome or set of actions, given complex and dynamic changes in the world the contract lives in.

When contracts are incomplete, they rely on renegotiation when unexpected contingencies like bankruptcy, regulation or even simple changes in details emerge. Such contingencies often require third parties like the legal system to help interpret and mediate between the two parties, and can lead to unpredictable outcomes. In this way, contracts are always about the unknown eventualities of decision making, incentives, and governance authority.

But if we accept that contracts are simply decision logic — akin to computer programs, then contract theory gives us a framework for thinking about different types of smart contracts and crypto-enabled projects — and how they can scale (including governance of them) .... ' 

Comments on Solar Winds Security Event

 Well done piece on the implications and future considerations for  the recent Solar Winds cybercriminal Data compromise.   Some good thoughts.  Below the introduction ....  and linkon for the detail.  Full coverage at the link.

The Winds of Change – What SolarWinds Teaches Us

Gary Hibberd is the ‘The Professor of Communicating Cyber’ at Cyberfort and is a Cybersecurity and Data Protection specialist with 35 years in IT. 

In December 2020, the world discovered that the SolarWinds’ Orion Platform had been compromised by cybercriminals, potentially affecting thousands of businesses the world over. Security groups such as the National Cyber Security Centre (NCSC) provided advice and guidance to security teams and IT companies on what actions they should take to minimize the impact on them and their customers.

But the Advanced Persistent Threat (APT) carries with it a worrying sub-text that requires further exploration as companies continue to tackle the ongoing issues of a global pandemic and an increasingly fatigued and remote workforce.

Knowledge is power

In the wake of the discovery of the breach, national security agencies such as the NCSC were prompt in providing advice and guidance. Using tools such as the Cyber Information Sharing Programme (CiSP), they shared technical information on how to assess if an organization was at risk and what actions they should take if they were. Following the announcement, SolarWinds provided comprehensive advice and information, which is well worth reviewing as it also provides a detailed ‘FAQ’ section. However, it’s easy for such information to get lost in the midst of the social media hysteria and noise that tends to follow any large-scale attack.

The advice offered by the CiSP includes the following steps;

Sunday, April 25, 2021

Some No Code Platforms

A general exploration of current N-Code platforms.    Have been asked. 

12 No-Code Platforms for Some DIY Machine Learning   In NAnalyze

Only 25% of organizations are using artificial intelligence (AI) in their businesses today. Why? Custom AI-enabled solutions are expensive to build, as talented data scientists are a hot commodity today and don’t come cheap. Top performers can easily command over $250,000 in annual salary, which seriously makes us question the money we wasted invested in getting our MBAs. Not to mention, it can take months or even years to implement. CTOs are understandably suspicious of the latest buzzword du jour, so you need to show results fast.  ... ' 

From Blockchain to Contracts

Have been looking at the use of 'smart contracts' in a broader way.  Is this one direction?   Incorporating trust.

Investing in Aleo  by Katie Haun and Ali Yahya  in Andreessen Horowitz

From the beginning, our core thesis has been that the best way to think of a modern blockchain is as a new class of computer that has the ability to run a special kind of program. These programs are sometimes called smart contracts, and they’re different from ordinary programs in that they have a life of their own. They are independent, and once written, they obediently execute themselves subject to nobody’s authority. Because of this property, smart contracts are uniquely capable of earning trust. 

But smart contracts today have two big limitations: (1) they are fully transparent by design and therefore don’t allow for privacy (2) they don’t scale to millions (let alone billions) of users. These limitations exist because trust requires verification. Transactions on a blockchain need to be transparent so that everyone can verify that they are correct. And, they tend not to scale because it takes time and energy for all computers on the network to perform that verification.

But research in a cutting edge area of cryptography called zero-knowledge proofs promises to unlock an elegant solution to the privacy and scalability problems. We spent a great deal of time looking at various approaches and teams working on this. Aleo’s solution is both elegant and pragmatic.  ... '

NASA and NVIDIA Collaborate

Example of data science uses: NASA and NVIDIA addressing pollution data. ,   Including some instructive code snippets. 

NASA and NVIDIA Collaborate to Accelerate Scientific Data Science Use Cases, Part 2

By Christoph Keller and Zahra Ronaghi   in NVIDIA Developer

Over the past couple of years, NVIDIA and NASA have been working closely on accelerating data science workflows using RAPIDS, and integrating these GPU-accelerated libraries with scientific use cases. This is the second post in a series that will discuss the results from an air pollution monitoring use case conducted during the COVID-19 pandemic, and share code snippets to port existing CPU workflows to RAPIDS on NVIDIA GPUs. This first post of this series, we covered Accelerated Simulation of Air Pollution.

Monitoring the Decline of Air Pollution Across the Globe During the COVID-19 Pandemic   ... 

FlavorGraph: Food Pairings with AI and Molecular Science

Combines a number of interests of mine.  Food science and AI, Chemistry and Graph Analytics.   At the link see some impressive graphs that look at the connections  Nicely done approach to loooking at a complex problem.  In our own food industry area, coffee blending, we looked at some aspects of this, but just barely.  Worth a look if you are in the area.

 (Update:  Hmmm ... just acted as a tester of new spice blends for McCormick. Might this act as a means of generating potential new blends for them? )

FlavorGraph Serves Up Food Pairings with AI, Molecular Science  By Isha Salian

Tags: Data Science, featured, Machine Learning & Artificial Intelligence, News

It’s not just gourmet chefs who can discover new flavor combinations— a new ingredient mapping tool by Sony AI and Korea University uses molecular science and recipe data to predict how two ingredients will pair together and suggest new mash-ups. 

Dubbed FlavorGraph, the graph embedding model was trained on a million recipes and chemical structure data from more than 1,500 flavor molecules. The researchers used PyTorch, CUDA and an NVIDIA TITAN GPU to train and test their large-scale food graph.

Researchers have previously used molecular science to explain classic flavor pairings such as garlic and ginger, cheese and tomato, or pork and apple — determining that ingredients with common dominant flavor molecules combine well. In the FlavorGraph database, flavor molecule information was grouped into profiles such as bitter, fruity, and sweet. 

But other ingredient pairings have different chemical makeups, prompting the team to incorporate recipes into the database as well, giving the model insight into ways flavors have been combined in the past. .... " 

Labor Intensive Work and Analytics

There will continue to be labor intensive jobs, with key skills required. 

Labor-intensive factories—analytics-intensive productivity

April 21, 2021 | Article in McKinsey

By Manuel Gómez, Jorge Riveros, and Kevin Sachs

New analytics tools can help manufacturers in labor-intensive sectors boost productivity and earnings by double-digit percentages.

Amid the extraordinary transformation of manufacturing over the past decade as the Fourth Industrial Revolution (4IR) advances through sector after sector, some manufacturers still face a challenge almost as old as manufacturing itself: how to achieve lasting productivity gains from labor-intensive operations.

  00:00   Audio  Listen to this article

The seemingly obvious solution is sometimes summarized as swapping labor for capital, in the form of automation. Despite the availability of ever-more-sophisticated machinery at ever-lower cost, in many situations a more attractive alternative is to use digital and analytics technologies to support people rather than supplant them.

Even today, labor-intensive sectors can include everything from toys, apparel, and jewelry to medical devices, consumer-electronic products, electrical goods, and automotive components. These sectors are a critical force in emerging economies, providing employment that reduces poverty and strengthens social stability.

Where labor is so instrumental in creating value, managing a workforce becomes a matter of strategic importance. Companies that perform better at hiring, retaining, and—most crucial of all—engaging their workers can build a substantial advantage over their competitors. To do so, they must overcome a host of challenges, some of which became even more vexing under COVID-19. Ensuring that workers feel safe must, of course, be the highest priority. But providing a protective environment may not be enough to persuade every worker to come into factories—particularly workers juggling responsibilities to care for children and families that may have been disproportionately affected by the pandemic.

Companies that perform better at hiring, retaining, and—most crucial of all—engaging their workers can build a substantial advantage over their competitors. ... '  ( 6 pages) 

Training for Brain on a Chip Using SNN

First I had heard of this detailed. Probably worth a look.

Brain-on-a-Chip Would Need Little Training  in CNN

KAUST Discovery (Saudi Arabia), April 20, 2021

Researchers at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia used a spiking neural network (SNN) on a microchip as a foundation for developing more efficient hardware-based artificial intelligence systems. KAUST's Wenzhe Guo said SNNs mimic the biological nervous system and can process information faster and more efficiently than artificial neural networks. The researchers created a brain-on-a-chip using a standard FPGA microchip and a spike-timing-dependent plasticity model, which allowed the neuromorphic computing system to learn real-world data patterns without training. Compared to other neural network platforms, the brain-on-a-chip was more than 20 times faster and 200 times more energy efficient. Guo said, "Our ultimate goal is to build a compact, fast and low-energy brain-like hardware computing system.".... ' 

Pandemic Eviction Modeling

 More models accurately done, with the right data, address the results of specific decisions.

Modeling Shows Pandemic Eviction Bans Protect Entire Communities From Covid-19 Spread

Johns Hopkins Medicine Newsroom

April 19, 2021

Researchers at institutions including Johns Hopkins University and the University of Pennsylvania used computer modeling to determine that eviction bans during the Covid-19 pandemic lowered infection rates, shielding entire communities from the virus. The scientists said they used simulations to predict additional virus infections in major U.S. cities if bans were not authorized in fall 2020. The team initially calibrated its model to reproduce the most common epidemic patterns observed in major cities last year, accounting for infection-rate changes due to public health measures. Another iteration factored in the lifting of eviction bans, determining that people who are evicted or who live in a household that hosts evictees are 1.5 to 2.5 times more likely to become infected than with such bans in place.  .... '

Saturday, April 24, 2021

Plane Paradox: More Creativity for Complex Automation

 Operating complex automated systems needs more training to be creative, rather than more training about very the details complex systems.  Or do we just need more training to deal with surprises in automated systems?   Wordering.  

The Plane Paradox: More Automation Should Mean More Training   in Wired

Today's highly automated planes create surprises pilots aren't familiar with. The humans in the cockpit need to be better prepared for the machine's quirks.

SHORTLY AFTER A Smartlynx Estonian Airbus 320 took off on February 28, 2018, all four of the aircraft’s flight control computers stopped working. Each performed precisely as designed, taking themselves offline after (incorrectly) sensing a fault. The problem, later discovered, was an actuator that had been serviced with oil that was too viscous. A design created to prevent a problem created a problem. Only the skill of the instructor pilot on board prevented a fatal crash.

Now, as the Boeing 737 MAX returns to the skies worldwide following a 21-month grounding, flight training and design are in the crosshairs. Ensuring a safe future of aviation ultimately requires an entirely new approach to automation design using methods based on system theory, but planes with that technology are 10 to 15 years off. For now we need to train pilots how to better respond to automation’s many inevitable quirks.   ..." 

MIT to Reconcile Data Sharing with EU AI Regulations

Proposed regulations constraining AI proposed by the EU are over 100 pages long.  What is MIT's view?   Note some other  things also include  'subliminal behavior manipulation', I assume specifying exactly how this differs from clever advertising,  and 'Social Credit Scoring'. 

AI Weekly: MIT aims to reconcile data sharing with EU AI regulations  In VentureBeat By Kyle Wiggers, @Kyle_L_Wiggers

This week, the European Union (EU) unveiled regulations to govern the use of AI across the bloc’s 27 member states. The first-of-its-kind proposal spans more than 100 pages    and will take years to implement, but the ramifications are far-reaching. It imposes a ban — with some exceptions — on the use of biometric identification systems in public, including facial recognition. Other prohibited applications of AI include social credit scoring, the infliction of harm, and subliminal behavior manipulation.

The regulations are emblematic of an increased desire on the part of consumers for privacy-preserving, responsible implementations of AI and machine learning. A study by Capgemini found that customers and employees will reward organizations that practice ethical AI with greater loyalty, more business, and even a willingness to advocate for them — and in turn, punish those that don’t. And 87% of executives told Juniper in a recent survey that they believe organizations have a responsibility to adopt policies that minimize the negative impacts of AI  ..."

Many Simple Small Robots,

Robot work at Ga Tech, which we visited a number times.   Always liked the idea of small,  multiple and cooperative problem solving doing tasks.  Bur even without collaboration can have value.  Gathering data, especially can be a good example. 

Simple robots, smart algorithms   by Georgia Institute of Technology

Anyone with children knows that while controlling one child can be hard, controlling many at once can be nearly impossible. Getting swarms of robots to work collectively can be equally challenging, unless researchers carefully choreograph their interactions—like planes in formation—using increasingly sophisticated components and algorithms. But what can be reliably accomplished when the robots on hand are simple, inconsistent, and lack sophisticated programming for coordinated behavior?

A team of researchers led by Dana Randall, ADVANCE Professor of Computing and Daniel Goldman, Dunn Family Professor of Physics, both at Georgia Institute of Technology, sought to show that even the simplest of robots can still accomplish tasks well beyond the capabilities of one, or even a few, of them. The goal of accomplishing these tasks with what the team dubbed "dumb robots" (essentially mobile granular particles) exceeded their expectations, and the researchers report being able to remove all sensors, communication, memory and computation—and instead accomplishing a set of tasks through leveraging the robots' physical characteristics, a trait that the team terms "task embodiment."

The team's BOBbots, or "behaving, organizing, buzzing bots" that were named for granular physics pioneer Bob Behringer, are "about as dumb as they get," explains Randall. "Their cylindrical chassis have vibrating brushes underneath and loose magnets on their periphery, causing them to spend more time at locations with more neighbors." The experimental platform was supplemented by precise computer simulations led by Georgia Tech physics student Shengkai Li, as a way to study aspects of the system inconvenient to study in the lab.  ... ' 

How and Why to Share Scientific Code

Rarely done this consistently, but it is a useful approach to follow.   Add it to a review and follow up of results.   Plans for maintaining models.  

How and why to share scientific code

A simple guide to reproducible research without becoming a software engineer

By Nathan C. Frey

When you do an experiment, whether that’s in a lab or on a computer, you generate data that needs to be analyzed. If your analysis involves new methods, algorithms, or simulations, you probably wrote some code along the way. Scientific code is designed to be quick to write, easy for the writer to use, and never looked at again after the project is complete (maybe designed is a strong word).

For many scientists, packaging their code involves a lot of work and no reward. I want to share a few obvious benefits and some that are hopefully non-obvious. After that, I’ll give some tips for how to share your code as painlessly as possible without detouring into becoming a software engineer. If you want a simple example of what the finished product will look like, check out my repos for Python Topological Materials or Positive and Unlabeled Materials Machine Learning.

The benefits of sharing scientific code

Encourage reproducibility. As soon as a method has more than one step (click the big red button) or a data analysis pipeline is more complex than “we divided all the numbers by this number,” it becomes unlikely that other scientists will be able to really explore what you did. If you developed a set of instructions to process or generate your data, you wrote a program, whether you wrote it down in code or not. It’s much more natural to share that program than to only write out what you did in your paper.  ... " 

Overview of Graph Databases

Overview of Graph DBs and their uses.  From the CACM.  Below the intro, more at the link. 

Understanding NoSQL Database Types: Graph Databases     By Alex Williams  in CACM

While originating as a subset of NoSQL or "Not Only SQL," graph databases represent a sharp closing of SQL and NoSQL demarcations. Graph technologies are exploding in its market size as more companies and developers take up their hybrid flexibility offerings. Those offerings: Intuitivity plus scalability with a high connection and robust data pattern.

While I won't go into depth on the formation of the 'SQL vs NoSQL' debate, you could quite accurately say that SQL represents data stored in rows and tables, while high-growth NoSQL is data stores arranged via nested documents as columnar schemas or key-value pairs. One is relational, the other not so much.

Graph databases are formed from nodes, properties, and relationships—all in a very interlinked data structure. And yet it supports advanced, rich querying with scalability. In this model, relationships matter just as much as the data itself. In a sense, it combines the querying power of relational databases with the intuitive flexibility of columnar non-relational databases—supporting agile development while also letting you gain deep insights.

Why use graph databases: The benefits

The graph model is a general-purpose data technology. While many know it for its social media implementations—this 'emerging shape', as it's known amongst data scientists due to being a non-typical dataset, has become most popular with social media companies for performing social network analyses, and for creating social graphs via companies like Facebook and Twitter who are particularly focused on the Six Degrees of Separation concept—graph databases are actually found in a large variety of industries, ranging from finance to healthcare, to emergency-response networks.

The principal benefit of graph databases is using its ability to assign values to links or connections. If your data has connections, whether for offline machine learning systems or online mobile applications, implementing this emerging shape will likely be beneficial.

In short: Build high-fidelity, highly interconnected networks made of bite-sized, scalable patterns (ie. great for CI/CD dev) that can together service, query, and manage sophisticated problem domains.  ... ' 

Perspective Brain Hack

Good thought, but not always.

Perspective Taking: A Brain Hack That Can Help You Make Better Decisions

Mar 22, 2021 Opinion North America

Supports K@W's Innovation Content

In business and in life, many of our interactions benefit from perspective taking, or our ability to put ourselves in someone else’s shoes. In a unique corporate partnership with SEB, a leading Swedish corporate bank, The Wharton Neuroscience Initiative, explores the neural basis of perspective taking and its effects on collaboration and business outcomes. In this piece, Wharton marketing professor and neuroscientist Michael Platt, Vera Ludwig, Elizabeth Johnson and Per Hugander shed light on the neural basis of perspective taking and why it may lead to more innovation and better business outcomes. 

According to Martin Lorentzon, co-founder of Spotify and Tradedoubler, “The value of your company is equal to the sum of the problems you are able to solve.” But how can we build this problem-solving capability into our organizations? Neuroscience suggests that one key strategy may be taking the perspective of others. Not only does this crucial skill provide us with additional information about complex situations, it also activates brain regions linked with creativity and innovation.

Indeed, many frameworks and tools for solving tough and complex problems are centered around the ability to take the perspective of others. Innovation frameworks start with taking the customer’s perspective; collaboration and negotiation frameworks are centered around understanding others’ viewpoints; and dialogue models recommend postponing judgment in order to take different perspectives for solving numerous challenges from business issues to marital problems.

When considering how often perspective taking appears in the problem-solving literature, it is surprising that so few leaders invest time and effort in developing this skill. Even though organizations frequently use the aforementioned tools and frameworks, including the well-known approach of Design Thinking, the results may be suboptimal if individuals are not skilled in perspective taking itself.... " 

Friday, April 23, 2021

New Small Drone Rules in US

How full will the skies ultimately become,  with more drone-like and autonomous devices?  Expect it. Note remote ID requirements.

New Rules Allowing Small Drones to Fly Over People in U.S. Take Effect

Reuters, David Shepardson, April 21, 2021

Final rules from the U.S. Federal Aviation Administration that permit small drones to fly over people and at night took effect April 21. The rules also allow drones to fly over moving vehicles in some instances. To address security concerns, remote identification technology (Remote ID) will be required in most cases so drones can be identified from the ground. Drone manufacturers have been given 18 months to begin production of drones with Remote ID, and an additional year has been granted to operators to provide Remote ID. The rules do not require drones to be connected to the Internet to transmit location data, but they must use radio frequency (RF) broadcasting to transmit remote ID messages. U.S. Transportation Secretary Pete Buttigieg called the rules "an important first step in safely and securely managing the growing use of drones in our airspace."

More on Amazon's Palm Scanning System

Amazon Bringing Palm-Scanning Payment System to Whole Foods Stores

CNBC, Annie Palmer, April 21, 2021

Amazon's palm-scanning payment system will be rolled out to a Whole Foods store in Seattle's Capitol Hill neighborhood before expanding to seven other Whole Foods stores in the area in the coming months. About a dozen Amazon physical stores already offer the Amazon One payment system, which allows shoppers who have linked a credit card to their palm print to pay for items by holding their palm over a scanning device. Amazon says the palm-scanning system is "highly secure" and more private than facial recognition and other biometric systems. The company says thousands of people have signed up to use the system at the Amazon stores.... '

Apple Supplier Targeted with Ransomware

Even Apple suppliers are vulnerable.  Note in particular theft of corporate data and plans.

 Apple Targeted in $50-Million Ransomware Hack of Supplier Quanta

Bloomberg, Kartikay Mehrotra, April 21, 2021

Taiwan-based Apple contract manufacturer Quanta Computer suffered a ransomware attack apparently by Russian operator REvil, which claimed to have stolen the blueprints of Apple's latest products. A user on the cybercrime forum XSS posted Sunday that REvil was about to declare its "largest attack ever," according to an anonymous source. REvil named Quanta its latest victim on its "Happy Blog" site, claiming it had waited to publicize the breach until Apple's latest product launch because Quanta had refused to pay its ransom demands. By the time the launch ended, REvil had posted schematics for a new laptop, including the workings of what seems to be a Macbook designed as recently as March. ... '

EU to Constrain Certain AI Uses?

To be expected reaction from EU regulators.

Facial Recognition, Other 'Risky' AI Set for Constraints in EU

Bloomberg, Natalia Drozdiak, April 21, 2021

The European Commission has proposed new rules constraining the use of facial recognition and other artificial intelligence applications, and threatening fines for companies that fail to comply. The rules would apply to companies that, among other things, exploit vulnerable groups, deploy subliminal techniques, or score people’s social behavior. The use of real-time remote biometric identification systems by law enforcement also would be prohibited unless used specifically to prevent a terror attack, find missing children, or for other public security emergencies. Other high-risk applications, including for self-driving cars and in employment or asylum decisions, would have to undergo checks of their systems before deployment. The proposed rules need to be approved by the European Parliament and by individual member-states before they could become law.   ... " 

Thursday, April 22, 2021

AI Centered Product Design

Had not heard of the concept as stated, worth a look:

How is AI-Centered Product Design Different?

By Amanda Linden  in TowardsDataScience

People who are interested in AI often ask me what an AI designer is, and I’ve attempted to answer that question in this article. I wanted to go a step further, by helping designers and product teams understand how designing AI-based product experiences is different from traditional product design. Here is what I’ve learned over the last two years of managing AI design & innovation teams, about how AI-first product thinking is evolving the traditional product design process. ....  " 

Related earlier article:  

Wharton: Planning for AI Risk Governance

Useful thoughts on the concept of governance of AI in the paper linked to below.

How Can Financial Institutions Prepare for AI Risks?

Apr 13, 2021 Analytics Wharton Research North America

Artificial intelligence (AI) technologies hold big promise for the financial services industry, but they also bring risks that must be addressed with the right governance approaches, according to a white paper  by a group of academics and executives from the financial services and technology industries, published by Wharton AI for Business. 

Wharton is the academic partner of the group, which calls itself Artificial Intelligence/Machine Learning Risk & Security, or AIRS. Based in New York City, the AIRS working group was formed in 2019, and includes about 40 academics and industry practitioners. ..." 

Book: End-to-end Encrypted Messaging

Continue to make my way through this excellent and detailed book.    Rolf Oppliger's site describes this book and others he has written.   Plus his company's ongoing research and work.   Order it below.

End-to-End Encrypted Messaging Hardcover – April 30, 2020   by Rolf Oppliger  (Author)

This exciting resource introduces the core technologies that are used for Internet messaging. The book explains how Signal protocol, the cryptographic protocol that currently dominates the field of end to end encryption (E2EE) messaging, is implemented and addresses privacy issues related to E2EE messengers. The Signal protocol and its application in WhatsApp is explored in depth, as well as the different E2EE messengers that have been made available in the last decade are also presented, including SnapChat. It addresses the notion of self-destructing messages (as originally introduced by SnapChat) and the use of metadata to perform traffic analysis.

Uses of AI for Small Business

 Fairly obvious, but the stats show you that small business understands the needs and possibilities.

The Growing Importance of AI for Small Businesses

AI has become enormously important for small businesses in recent years.  Posted By Gaurav Sharma

Artificial intelligence (AI) is no more confined to big businesses. As the technology matures and becomes more affordable, it has found a place in startups and small businesses as well.

A survey of 1,467 CEOs of small and mid-sized businesses (SMBs) found that out of all the current technologies, AI has had the maximum impact on their business.   ... " 

Wednesday, April 21, 2021

CPG Costs Rise in Pandemic

Seems like a need for analytical modeling of costs.  My former employer needs to step up to the  problem.

Price hikes on the horizon for P&G as material costs rise

In Reuters: 

Procter & Gamble Co (PG.N) said on Tuesday it would raise prices of certain products in the United States to offset rising costs that were already weighing on its fourth quarter, after reporting a better-than-expected quarterly result.

The Cincinnati-based company joins a growing list of consumer product makers hiking prices this year as they battle increasing costs for everything from transport to pulp and resin or edible oils and nuts.

P&G said since it gave its initial guidance for fiscal 2021 last year, costs had risen by $400 million, including after tax costs of $125 million for commodities that will largely hit the fourth quarter and $200 million in higher freight costs.... " 

Palm Swipe Scanning at Whole Foods

 We experimented with a number of ID/payment methods.   From Iris to thumbprint to Face.   But not palm swipe scanning, installed at Wholefoods now. Contact-less.

Amazon to let Whole Foods shoppers pay with a swipe of their palm   By Jeffrey Dastin

 (Reuters) - Amazon.com Inc said it is rolling out biometric technology at its Whole Foods stores around Seattle starting on Wednesday, letting shoppers pay for items with a scan of their palm.

The move shows how Amazon is bringing some of the technology already in use at its namesake brick-and-mortar Go and Books stores to the grocery chain it acquired in 2017.

The system, called Amazon One, lets customers associate a credit card with their palm print. It offers a contact-less alternative to cash and card payments, Amazon said.  .... " 

Need for Continuous and Dynamic Threat Modeling

Well done post from Cisco, with useful explanatory visuals. Strongly agree. Using and applying specific risk models.

By Sujata Ramamoorthy

This blog is co-authored by Mohammad Iqbal and is part four of a four-part series about DevSecOps.

The trend towards accelerated application development, and regular updates to an architecture through an agile methodology, reduces the efficacy and effectiveness of point-in-time threat modeling. This recognition led us to explore and strategize ways to continuously, and dynamically, threat model an application architecture during runtime.

Today, thanks to a robust DevOps environment, developers can deploy a complex architecture within a public cloud such as Amazon Web Services (AWS) or Google Cloud Platform without requiring support from a network or database administrator. A single developer can develop code, deploy an infrastructure through code into a public cloud, construct security groups through code, and deploy an application on the resulting environment all through a continuous integration/continuous delivery (CI/CD) pipeline. While this enables deployment velocity, it also eliminates multiple checks and balances. At Cisco, we recognized the risks introduced by such practices and decided to explore strategies to continuously evaluate how an architecture evolves in production runtime to guard against architecture drift.

Dynamic threat modeling must begin with a solid baseline threat model that is done in real-time. This can in turn be monitored for architecture drift. Our approach to obtain such a real-time view is to use dynamic techniques to allow security and ops teams to threat model live environments instead of diagraming on paper or whiteboards alone.

How Does Dynamic Threat Modeling Work?
Threat modeling is the practice of identifying data flows through systems and various constructs within an architecture that exhibit a security gap or vulnerabilities. A crucial element that enables the practice of threat modeling is generating the right kind of visual representation of a given architecture in an accurate manner. This approach can differ based on context and from one team to another.  At Cisco, we instead focused on elements and features that need to exist to allow a team to dynamically perform a threat modeling exercise. These elements include the ability:  .... " 

GE Working on Detecting COVID with a Smartphone

More detail, here from GE on their work on detecting COVID with a smartphone.

GE Scientists Developing Technology to Add COVID-19 Virus Detector to Your Mobile Device

Sensing Materials

Awarded National Institutes of Health (NIH) grant to develop tiny sensors smaller than your fingertip that can detect the presence of COVID-19 virus nano-particles on screens, tables and other surfaces

Multi-disciplinary team from GE Research will draw from years of development and commercial success with physical, environmental, gas and biosensors for industrial  monitoring

The Team’s work has been featured in journals Nature Electronics 2020 and Lab on a Chip 2021

NISKAYUNA, New York, April 8, 2021 – Building on a suite of successful sensing technologies that have resulted in field demonstrations and a commercial launch for industrial monitoring, GE Research has been awarded a 24-month NIH grant (U01AA029324) of the RADx-rad program to develop miniature sensors that can detect the presence of the COVID-19 virus nano-particles on an array of different surfaces.

“One of the first lines of defense against any virus is avoiding exposure, which is easier said than done when you can’t see it,” said Radislav Potyrailo, a principal scientist at GE Research and principal investigator on the NIH project. “Through our project with the NIH, we are developing a sensor small enough to embed in a mobile device that could detect the presence of the COVID-19 virus.”

Potyrailo added, “We all come into contact with different surfaces during any given day, from computer screens and conference tables to kiosks at the airport and of course, credit card machines at stores while running errands.  While everyone does a great job keeping these surfaces clean, we want to add an extra layer of safety by being able to detect the presence of the virus.”  ... '

Tuesday, April 20, 2021

MBRL Tuning for Partially Understood Environments

Below is very technical,  but I do like some of the background statements such as 'solving tasks in a partially understood environment ...'.    And the idea of optimizing agents to resolve elements of understanding.  (Which exemplifies the situations we are often in).    So I am not saying I understand this yet, but working through it now for broader application.  As part of my broader study of practical reinforcement learning.

The Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

Nathan Lambert, Baohe Zhang, Raghu Rajan, André Biedenkapp    Apr 19, 2021  From BAIR  Berkeley

Model-based reinforcement learning (MBRL) is a variant of the iterative learning framework, reinforcement learning, that includes a structured component of the system that is solely optimized to model the environment dynamics. Learning a model is broadly motivated from biology, optimal control, and more – it is grounded in natural human intuition of planning before acting. This intuitive grounding, however, results in a more complicated learning process. In this post, we discuss how model-based reinforcement learning is more susceptible to parameter tuning and how AutoML can help in finding very well performing parameter settings and schedules. Below, left is the expected behavior of an agent maximizing velocity on a “Half Cheetah” robotic task, and to the right is what our paper with hyperparameter tuning finds.


Model-based reinforcement learning (MBRL) is an iterative framework for solving tasks in a partially understood environment. There is an agent that repeatedly tries to solve a problem, accumulating state and action data. With that data, the agent creates a structured learning tool – a dynamics model – to reason about the world. With the dynamics model, the agent decides how to act by predicting into the future. With those actions, the agent collects more data, improves said model, and hopefully improves future actions.  ... " 

Database of World Management Practices

This came to my attention.   Could have been useful, depending on how precise the practices were detailed, in past modeling efforts.   This effort under way for 18 years! Now if we could have working process models of each organization type to work from.   Likely much harder.  But what if we could build up from basic models?  Forecast of future practices mentioned also of interest. Note offering measurement as well.  Has to be good data here. 

The World Management Survey at 18: Lessons and the Way Forward   by Daniela Scur, Raffaella Sadun, John Van Reenen, Renata Lemos, and Nicholas Bloom  in HBSWK

With a dataset of 13,000 firms and 4,000 schools and hospitals spanning more than 35 countries, the World Management Survey provides a systematic measure of management practices used in organizations. This paper gives an overview of lessons learned and a management policy toolkit for policymakers.

Author Abstract

Understanding how differences in management “best practices” affect organizational outcomes has been a focus of both theoretical and empirical work in the fields of management, sociology, economics and public policy. The World Management Survey (WMS) project was born almost two decades ago with the main goal of developing a new systematic measure of management practices being used in organizations. The WMS has contributed to a body of knowledge around how managerial structures, not just managerial talent, relates to organizational performance. Over 18 years of research, a set of consistent patterns have emerged and spurred new questions. We will present a brief overview of what we have learned in terms of measuring and understanding management practices and condense the implications of these findings for policy. We end with an outline of what we see as the path forward for both research and policy implications of this research program. ... '

  Paper: https://www.nber.org/papers/w28524

Facebook Research Allocates Ad Funding (without AI)

Struck me because we did something similar and also quite different for advertising fund allocation very early on.    We the results of integer optimization models with montecarlo simulation, constrained to advertising agreements.   I like the fact that AI is never mentioned!  But in much later spins on this,  what could be called AI was used to check for accuracy and regulatory compliance to contractual agreements.  Nice.

Auto-placement of ad campaigns using multi-armed bandits  in Facebook Research

By: Vashist Avadhanula, Riccardo Colini Baldeschi, Stefano Leonardi, Karthik Abinav Sankararaman, Okke Schrijvers

What the research is:

We look at the problem of allocating the budget of an advertiser across multiple surfaces optimally when both the demand and the value are unknown. Consider an advertiser who uses the Facebook platform to advertise a product. They have a daily budget that they would like to spend on our platform. Advertisers want to reach users where they spend time, so they spread their budget over multiple platforms, like Facebook, Instagram, and others. They want an algorithm to help bid on their behalf on the different platforms and are increasingly relying on automation products to help them achieve it.

In this research, we model the problem of placement optimization as a stochastic bandit problem. In this problem, the algorithm is participating in k different auctions, one for each platform, and needs to decide the correct bid for each of the auctions. The algorithm is given a total budget B (e.g., the daily budget) and a time horizon T over which this budget should be spent. At each time-step, the algorithm should decide the bid it will associate with each of the k platform, which will be input into the auctions for the next set of requests on each of the platforms. At the end of a round (i.e., a sequence of requests), the algorithm sees the total reward it obtained (e.g., number of clicks) and the total budget that was consumed in the process, on each of the different platforms. Based on just this history, the algorithm should decide the next set of bid multipliers it needs to place. The goal of the algorithm is to maximize the total advertiser value with the given budget across the k platforms.   ... "    

Full paper:  https://arxiv.org/abs/2103.10246