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.  ... ' 

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;

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.  .... '

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.   ..."