Google Earth Becomes a (Selective) Time Machine

Quite an interesting development.    Look forward to testing it soon.   Always have been a fan of Google Earth and how it has changed geography.    But do understand the data you are seeing over time and location is selectively chosen by Google.  By what criterion I do not know.  Most likely is cost, availability, needs ...   This selectivity occurs even in non-time lapse Google data.   Data from big cities is gathered in much more detail than that from out in the country.   Some of our own tests showed this.  Why?  Because more people want the detailed city data.  The specific availability will vary over time based on new sources.  But the statistics of your data may be insufficient for hoped for conclusions.  Not criticizing, just pointing  this out.   - FAD 

Google puts 20 petabytes of historical satellite data into the Google Earth globe.   By Ron Amadeo  in ArsTechnica

Google has pushed out what it says is Google Earth's "biggest update since 2017" with a new 3D time-lapse feature. Entering the new "Timelapse" mode of Google Earth will let you fly around the virtual globe with a time slider, showing you satellite imagery from the past 37 years. Google Earth Timelapse has been around for years as part of Google Earth Engine (which is a totally separate interface from Google Earth; it's a weird Google branding thing), but it was previously only available in 2D. Now, Google has mapped all this data across the 3D Google Earth globe, where you can watch cities being built, forests being cut down, and glaciers receding.

Google Earth Timelapse isn't just a huge amount of data; properly mapping it across the globe means correcting the images for artifacts and problems. The company had to get clouds out of the way, correct images for perspective, and ensure seamless transitioning through zoom levels. Luckily, Google happens to have some really big computers to handle the load.  ... " 

Law, Rule of Law and Computer Science

Lots to consider here, and it seems we are not close to understanding the implications.  The pressure to automate lots of this is very strong. 

Understanding Law and the Rule of Law: A Plea to Augment CS Curricula,  By Mireille Hildebrandt

Communications of the ACM, May 2021, Vol. 64 No. 5, Pages 28-31   10.1145/3425779

Some people think they are above the law. In a constitutional democracy this cannot be the case. Neither the head of state nor the doctor or the police are above the law. They should all be enabled to do their work, but we do not buy the claim that they could act as they wish. In 18th century Europe we replaced the authoritarian rule by law with a rule of law, to mitigate uninhibited power, and to ensure that those in power can be held to account in a court of law. Whereas rule by law is rule by persons (law as an instrument of control), rule of law implies a division of powers where those who enact the rules do not get the last word on their interpretation.13

This also refers to the difference between law and ethics. Replacing rule by law with rule of law means we do not want to depend on the ethical inclinations of those who rule us. Instead, we can send them home if we don't agree with the rules they impose (democracy) and we can contest their interpretation of those rules in court (rule of law). As a thought experiment I ask the reader how this would apply to the rules computing systems impose: Can we send home the developers (and/or those who implement these systems to gain a profit or to engage in public administration)? Can we contest their rules in a court of law when they impact our choice architecture?

Law and the rule of law have been implemented by way of intricate checks and balances that safeguard the contestability of legally relevant decision making, thus preparing the ground for robust, legitimate, and binding decisions. This is how we create and sustain societal trust: not by cherishing the illusion of an ideal world where power plays no role, but by creating and sustaining countervailing powers. Simultaneously, law is about coordinating human interaction, making sure that governments treat their citizens with equal respect and concern,5 thus providing for legal certainty and justice. That is why it is imperative that nobody is above the law.

This also goes for the architects of our computational environments, who increasingly design and engineer the space we inhabit. Computer scientists, Web developers, roboticists, and software engineers must understand both when and how the law applies to them, and insofar as they develop modules, systems or applications for specific use cases, they should be sensitized about how and when the law may apply. This goes for issues of privacy and data protection, cybercrime, intellectual property rights and private law liability (for example, tort), but also for issues of jurisdiction (what law applies) and international law (how national legal systems interact at the global level). It goes even more for the idea of the rule of law that should inform our understanding of the law.

Based on many years of teaching law to master's students of computer science,8 I have come to believe that by teaching them about law I am not only helping them to comply with current law, but also offering them a unique opportunity to engage with the foundations and implications of their own 'trade' (precisely because computing systems also produce rules that affect human behavior).   ....  ' 

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?

ACM NEWS

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

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

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 

MIC LISTEN TO THE PODCAST:

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."... '