U.S. Military Takes Generative AI Out for a Spin

Based on previous experience,  can see this as useful.   With cautions. 

ACM TECHNEWS

U.S. Military Takes Generative AI Out for a Spin

By Bloomberg, July 10, 2023

A service member with the 175th Cyber Operations monitors cyberattacks during Exercise Southern Strike at Camp Shelby, MS.

Dozens of companies, including Palantir Technologies Inc. and Anduril Industries Inc., are developing AI-based decision platforms for the Pentagon.

Credit: Staff Sgt. Renee Seruntine/U.S. Army National Guard

The U.S. Department of Defense is testing five large language models (LLMs) as part of an effort to develop data integration and digital platforms for military use.

U.S. Air Force Col. Matthew Strohmeyer said one experiment using a LLM to perform a military task was "highly successful" and "very fast."

However, Strohmeyer said, "That doesn't mean it's ready for primetime right now."

The exercises involve feeding classified operational information into the LLMs, with the ultimate goal of using AI-enabled data in decision-making, sensors, and firepower.

Specifically, the LLMs are being tasked with helping plan a military response to an escalating global crisis, with a focus on the Indo-Pacific region.

From Bloomberg

View Full Article - May Require Paid Subscription

Accelerating Optical Communications with AI

 Accelerating Optical Communications with AI     By Chris Edwards

Communications of the ACM, July 2023, Vol. 66 No. 7, Pages 13-15  10.1145/3595957

Photonic computing has seen its share of research breakthroughs and deep research winters, much like the history of artificial intelligence (AI). Now, with the resurgence of AI, the huge amounts of energy today's large neural-network models need when running on electronic computers is reawakening interest in uniting the two.

More than 30 years ago, during one of the booms in research into artificial neural networks, Demetri Psaltis and colleagues at the California Institute of Technology demonstrated how techniques from holography could perform rudimentary face recognition. The team members showed they could store as many as one billion weights for a two-layer neural network using the core elements from a liquid-crystal display. Similar spatial light modulators became the foundation of several attempts to commercialize optical computing technology, including those by U.K.-based startup Optalysys, which has focused in recent years on applying the technology to accelerating homomorphic encryption to support secure remote computing.

Though some groups are using spatial light modulators for AI, they represent just one category of optical computer suitable for the job. There are also decisions as to which form of neural networks best suits optical computing. Some techniques focus on the matrix-arithmetic operations of mainstream deep learning pipelines, while others focus squarely on emulating the spike trains of biological brains.

What all the proposed systems have in common is the possibility that, by using photons to communicate and calculate, they will deliver major advantages in density and speed over systems based purely on electrical signaling. A 2021 study of inferencing based on matrix arithmetic by Mitchell Nahmias, now CTO of startup Luminous Computing, and colleagues at Princeton University argued the theoretical efficiency of AI inferencing in the optical domain could far surpass that of conventional accelerators based on existing electronics-only architectures.

The key issue for machine learning is the amount of energy needed to move data around accelerators. Electronic accelerators often employ strategies to cache as much data as possible to reduce this overhead, with major trade-offs concerning whether temporary results or weights are held in the cache depending on the model's structure. However, the energy cost of delivering photons over distances larger than the span of a single chip is far lower than it is for electrical signaling.

A second potential advantage of photonic AI comes from the ease with which it can handle complex operations in the analog domain, though the power savings achievable here are less certain than for communications. Whereas matrix arithmetic relies on highly parallelized hardware circuits for performance in conventional systems, simply passing photons through an optical component such as a Mach-Zehnder interferometer (MZi) or micro-ring resonator will perform arithmetic requiring hundreds or even thousands of logic gates in a digital circuit.

In the MZi, coherent beams of light pass through a succession of couplers and phase shifters. At each coupling point, the interference between the beams results in phase shifts that can be interpreted as part of a matrix multiplication. A 4x4 matrix operation requires just four inputs that feed into six coupling elements, with four output ports providing the result. The speed of the operations is limited only by the rate at which coherent pulses can be passed through the array.

In analog architectures, noise presents a significant hurdle. Work by numerous groups on accelerating inference operations has shown that deep neural networks can work successfully at an effective resolution of 4 bits, but hardware overhead and energy rise quickly as resolution increases. These effects may limit the practical energy advantage of photonic designs.

Estimates by Alexander Tait, assistant professor at Queen's University, Ontario, found the potential power-savings easily eroded by the practical limitations of today's optical devices. Tait calculated just 500 micro-ring resonators acting as neurons in a fully connected layout could fit onto a single 1cm2 die using early 2020s technology. But operating at 10GHz, it would require a kilowatt of power. Tait stresses the example shows the impact of the current need for heaters to tune optical properties. Scaling and design changes could bring the energy down dramatically. "The heaters are certainly a solvable problem," he says.  .... ' 

Can Generative AI Bots Be Trusted?

Full article required sign into ACM.

Can Generative AI Bots Be Trusted?

By Peter J. Denning

Communications of the ACM, June 2023, Vol. 66 No. 6, Pages 24-27   10.1145/3592981

In November 2022, OpenAI released ChatGPT, a major step forward in creative artificial intelligence. ChatGPT is OpenAI's interface to a "large language model," a new breed of AI based on a neural network trained on billions of words of text. ChatGPT generates natural language responses to queries (prompts) on those texts. In bringing working versions of this technology to the public, ChatGPT has unleashed a huge wave of experimentation and commentary. It has inspired moods of awe, amazement, fear, and perplexity. It has stirred massive consternation around its mistakes, foibles, and nonsense. And it has aroused extensive fear about job losses to AI automation.

Where does this new development fit in the AI landscape? In 2019, Ted Lewis and I proposed a hierarchy of AI machines ranked by learning power (see the accompanying table).2 We aimed to cut through the chronic hype of AI5 and show AI can be discussed without ascribing human qualities to the machines. At the time, no working examples of Creative AI (Level 4) were available to the public. That has changed dramatically with the arrival of "generative AI"—creative AI bots that generate conversational texts, images, music, and computer code.a  ... '   ( sign in) 

Quantum Advantage

 Quantum Advantage

Disentangling Hype from Practicality: On Realistically Achieving Quantum Advantage

By Torsten Hoefler, Thomas Häner, Matthias Troyer

Communications of the ACM, May 2023, Vol. 66 No. 5, Pages 82-87    10.1145/3571725

Operating on fundamentally different principles than conventional computers, quantum computers promise to solve a variety of important problems that seemed forever intractable on classical computers. Leveraging the quantum foundations of nature, the time to solve certain problems on quantum computers grows more slowly with the size of the problem than on classical computers—this is called quantum speedup. Going beyond quantum supremacy,2 which was the demonstration of a quantum computer outperforming a classical one for an artificial problem, an important question is finding meaningful applications (of academic or commercial interest) that can realistically be solved faster on a quantum computer than on a classical one. We call this a practical quantum advantage, or quantum practicality for short.

There is a maze of hard problems that have been suggested to profit from quantum acceleration: from cryptanalysis, chemistry and materials science, to optimization, big data, machine learning, database search, drug design and protein folding, fluid dynamics and weather prediction. But which of these applications realistically offer a potential quantum advantage in practice? For this, we cannot only rely on asymptotic speedups but must consider the constants involved. Being optimistic in our outlook for quantum computers, we identify clear guidelines for quantum practicality and use them to classify which of the many proposed applications for quantum computing show promise and which ones would require significant algorithmic improvements to become practical and relevant.

To establish reliable guidelines, or lower bounds for the required speedup of a quantum computer, we err on the side of being optimistic for quantum and overly pessimistic for classical computing. Despite our overly optimistic assumptions, our analysis shows a wide range of often-cited applications is unlikely to result in a practical quantum advantage without significant algorithmic improvements. We compare the performance of only a single classical chip fabricated like the one used in the NVIDIA A100 GPU that fits around 54 billion transistors15 with an optimistic assumption for a hypothetical quantum computer that may be available in the next decades with 10,000 error-corrected logical qubits, 10μs gate time for logical operations, the ability to simultaneously perform gate operations on all qubits and all-to-all connectivity for fault tolerant two-qubit gates .... 

The Power of Low-Power GPS Receivers for Nanosats

From The New Yorker   View Full Article

Home/Magazine Archive/November 2022 (Vol. 65, No. 11)/Technical Perspective: The Power of Low-Power GPS.../Abstract

RESEARCH HIGHLIGHTS

Technical Perspective: The Power of Low-Power GPS Receivers for Nanosats

By Karthik Dantu   Communications of the ACM, November 2022, Vol. 65 No. 11, Page 13210.1145/3559769

Technical Advancements in embedded systems, sensing technology, and an understanding of the Earth's atmosphere have allowed us to deploy satellites for various applications. A more recent phenomenon is the use of low-Earth (<2,000km from Earth) and medium-Earth (between 2,000km and 35,000km from Earth) orbits to deploy smaller satellites called nanosats to perform applications such as surveillance, mapping, estimating sea levels and areas of forests and lakes. Most of these satellites use GPS to localize themselves. A unique challenge at the scale of a nanosat is that the size, weight, and energy required to run a typical GPS receiver might be more than what is affordable for long-term operation.

The work explored in the following paper focuses on the energy consumption of a typical GPS receiver and its operational challenges in a nanosat setting. The challenges include: power draw of a typical GPS receiver could be as high as 20% of overall power consumption; high-speed travel of nanosatellites (~7.8km/s) and relative speed to the GPS satellites (which themselves travel at 3.8km/s) makes getting a fix with a GPS satellite very challenging with high Doppler shift; lack of attitude control (typical of low power satellites) results in loss of GPS signal and corresponding loss in a fix; and, small delays result in large error requiring precise computation at low power.  ... ' 

A Cuddly Human Interface

 Interesting look at new user interfaces, from the ACM, which has long looked at Human Consumer Interfaces (HCI) 

Featured ACM Member: Yuta Sugiura

Yuta Sugiura is an Associate Professor at Keio University in Yokohama, Japan. His research interests include human-computer interaction, ubiquitous computing, and medical informatics. He has served as a program committee member for various international conferences, including ACM UIST, TEI, and SIGGRAPH ASIA E-Tech.

Sugiura was the recipient of the Information Processing Society of Japan (IPSJ/ACM) Award for Early Career Contributions to Global Research. He was recognized for his pioneering work in user interfaces and ubiquitous computing and for his recent focus on medical-engineering collaboration.

How did you initially become interested in human-computer interaction and, specifically, in user interfaces?

Human-computer interaction (HCI) is a multidisciplinary field of study. Unlike other technologies, HCI has been solving visible and tangible problems related to people and exploring how technology can be better applied to people. This is very interesting to me, and I can think of myself as a designer who has the power to use technology to develop interesting systems that solve real-life problems that people encounter.

Since the birth of the mouse and keyboard, people have become familiar with user-interface technology to interact with machine systems. As the only bridge between machine systems and humans, the user interface has great significance in the entire field of human-computer interaction. Research to promote the development of user interface technology enables more people to enjoy the benefits of technological advances.

Your work with Cuddly User Interface (Cuddly UI) focuses on finding new ways for computers to understand human physical gestures. How will this area of research shape smart homes in the future? What are some important technical challenges that need to be overcome in this area?

The Cuddly UI focuses on the application of soft interface technology. I proposed combining soft objects around the user (e.g., sofa, pillow, etc.) with sensor technology to build a friendlier and ubiquitous interaction interface. In addition, using soft objects also improves the user's acceptance of the interface and we can enable the soft materials to make a display. For example, we can use the robotic device to change the direction of the fiber on the carpet to show the graphics.

When it comes to smart homes, current intelligent home systems still use an explicit way to interact (e.g., remote control, voice control, etc.). Using Cuddly UIs can bring more implicit interactions to the user. This interaction with the Cuddly User Interface can be a more convenient, ubiquitous, and low-cost way to learn to interact with the computer system. For example, we can expect remote communication using the Cuddly UI. A person operates the soft objects (e.g., a toy or cushion) in their home, and the other can receive the toy’s movement. In addition, it is common and natural for people to come into contact with soft interfaces. It may also record many users' mood states invisibly. For example, a person may hammer the sofa when angry or hug a pillow tightly when watching a horror movie. These behaviors can be recorded by the intelligent Cuddly UI, which can analyze the emotional state to change its morphology (e.g., hardness) into feedback for the user.

Interaction with the Cuddly UI is still highly dependent on sensor technology and machine-learning techniques. Following a basic development paradigm, the system design must follow data collection and classifier training processes. The degree of user customizability is low. Therefore, the next step to focus on is reducing the system’s development cost to increase the user’s customizability so that each user can rely on their habits to design the interaction.  ...   " 

Highlights Risks of Quantum Simulation Technology

 Tech Bulletin form ACM Policy Council (TPC) 

ACM TechBrief Highlights Risks of Quantum Simulation Technology

ACM

August 2, 2022

A technical bulletin from ACM's Technology Policy Council (TPC) weighs the benefits and risks of quantum simulation technologies. The fourth TechBrief to be released by TPC, the bulletin notes media and policymakers' focus on future quantum computers' theoretical encryption-breaking capability has overshadowed quantum simulation's viability and likely impact. In response, the advisory calls for rigorous, immediate planning in order for quantum simulation to fulfill its potential, especially since quantum simulators are likely to emerge before general-purpose quantum computers. ACM TPC chair James Hendler said the TechBrief was intended "to introduce a broad audience to both the promise and peril of quantum simulation so that leaders in science, government, and policy may begin to debate and design parameters within which this technology can develop and be deployed responsibly with maximum benefit and minimum risk."

ACM Opens Doors to its Archives

 As a long time member, user, blogger, reader and  promoter ... love the idea.  Will try to find new ways to make this more useful. Thoughts?   Join me?

ACM NEWS

“The Way Things Were”: How ACM Is Opening the Doors to Its Archives   By Associations Now, July 15, 2022

The computing industry has changed significantly over the past 75 years, and the Association for Computing Machinery was there for all of it.

Over that time, the educational and scientific group representing nearly 100,000 members across 190 countries has collected a number of published works within its archives, many of which discuss fundamental work within the world of computers—for example, the first mention of UNIX, a groundbreaking operating system that has deeply influenced modern computing, in 1973, or an in-depth interview with Steve Jobs from 1989.

Once, this information—immensely valuable to historians and researchers alike—might have been locked behind a paywall. But as a part of its landmark campaign for its 75th anniversary celebrations, ACM is opening up a large portion of its archives, making the first 50 years of its published records—more than 117,500 documents dating from 1951 to 2000—accessible to the public without a login.

From Associations Now

Staffing.com Appeals for more Security leaders

 From Communications of the ACM

@CACMmag

HR and security leaders must deploy new strategies to attract, #hire, and retain #cybersecurity professionals. New #talent pools could help narrow the talent gap.

More:  https://bit.ly/3Orsr6N

Vint Cerf Invents a Company

Good process thoughts on  digital, below only an excerpt, full at the link.

Digital Synergy,  By Vinton G. Cerf

Communications of the ACM, June 2022, Vol. 65 No. 6, Page 9  10.1145/3534934

Google Vice President and Chief Internet Evangelist Vinton G. Cerf 

Imagine for a moment a company I will call ACRONYM that maintains warehouses around the world from which customer orders for a variety of products are made. Imagine further that some of the inventory is in digital form (think movies, music, ebooks) in addition to being physical in nature. ACRONYM's access to information in digital form turns out to be enormously enabling. The data is readily processed by sophisticated algorithms. This column is pure speculation on my part but inventing the imaginary ACRONYM Company helped me imagine how powerful it can be to have data available that permits fact-based analysis of business performance, projections for future business operations, and understanding of the marketplace the business serves.

ACRONYM gets its orders online, so they are already in digital form, with information ACRONYM needs to fulfill the order. Customers provide all the information requested since, without it, ACRONYM can't or won't place the order. The fact that the data is already in machinable form means ACRONYM can (in no particular order or priority):

Track the geocentric demand for specific products, which will inform them of where to place inventory and in what quantity in its many warehouses to reduce delivery time;

Track seasonal variations in demand to create powerful forecasting tools so that long-lead items can be ordered for inventory in a timely way;

Associate demographics with product orders to further analyze and anticipate demand and inform potential advertising campaigns;

Use reinforcement and other machine learning tools to prioritize stock keeping levels in warehouses; ..... ' 

War and Technology

 Good piece on the topic and related implications. 

War and Tech (and ACM)

By Moshe Y. Vardi  Communications of the ACM, May 2022, Vol. 65 No. 5, Page 9  10.1145/3528570

As COVID-19 surged around the globe two years ago, I reflected on a fundamental lesson that we must learn from our pandemic unpreparedness. I quoted the economist William A. Galston, who asked: "What if the relentless pursuit of efficiency, which has dominated American business thinking for decades, has made the global economic system more vulnerable to shocks?" arguing that efficiency, which comes through optimal adaptation to an existing environment, can be at the expense of resilience, which requires the capacity to adapt to disruptive changes in the environment.

But in those early days of the pandemic, I grossly underestimated how much our obsession with efficiency came at the expense of resilience. At that point, the main symptoms of our fragility were the shortage of paper products and personal protective equipment. But by late 2021, we were all talking about the supply-chain crisis, described by the New York Times as "Ships stuck at sea, warehouses overflowing, trucks without drivers: the highly intricate and interconnected global supply chain is in upheaval, with little end in sight." A specific aspect of the supply-chain crisis was the global chip shortage—everything "smart" requires a chip, but demand outstrips supply. .... ' 

Pentagon Predicting Events

Long after I worked for NCSS at the Pentagon,  but you could start to hear the same questions at the time, when we were predicting events using large scale visualization of plans and events in eastern Europe.  Ultimately the same thing. 

Pentagon Wants to Predict Events Before They Occur By IEEE Spectrum, October 15, 2021

What if by leveraging today's artificial intelligence (AI) to predict events several days in advance, countries could simply avoid warfare in the first place? That's the type of visionary thinking that is driving U.S. military commanders and senior defense policymakers toward the rapid adoption of AI-enabled situational awareness platforms.

But, it's tempting ask, "What could possibly go wrong?" Leveraging AI-enabled tools to make better decisions is one thing, but using them to predict adversarial actions in order to preempt them is an entirely different ballgame. In addition to raising philosophical questions about free will and inevitability, it is unclear whether any proactive actions taken in response to predicted adversarial behavior might be perceived by the other side as aggressive and end up catalyzing the war we sought to avoid in the first place.

From IEEE Spectrum

Reimplementing Software Interfaces is Fair Use

 Somewhat surprising,  and Beyond the US?   Good overview of the technical implications.

Reimplementing Software Interfaces Is Fair Use

By Pamela Samuelson  Communications of the ACM, July 2021, Vol. 64 No. 7, Pages 24-26

10.1145/3466607

A long-standing, generally accepted norm in the computing field distinguishes between software interfaces and implementations: Programmers should have to write their own implementing code, but they should be free to reimplement other developers' program interfaces. This norm, of which Sun Microsystems, the developer of Java, was once the software industry's foremost proponent, is now the law of the land in the U.S. after the Supreme Court's decision in Google Inc. v. Oracle America, Inc., which overturned a lower court ruling that reimplementing an interface infringed copyright.

The Supreme Court took Google's appeal on two issues. One was whether program interfaces are protectable by copyright law. The Supreme Court declined to decide that issue, even though many amicus curiae (friend of the court) briefs filed by software developers, organizations such as the Electronic Frontier Foundation, the Center for Democracy & Technology, and the Computer & Communications Industry Association, as well as numerous intellectual property scholars, supported Google's argument that program interfaces are uncopyrightable.

A second issue was whether Google's reimplementation of 11,500 declarations from 37 Java Application Program Interface (API) packages in its Android smartphone platform was fair use or infringement. Although a jury rendered a verdict in favor of Google's fair use defense after a two-week trial, the Court of Appeals for the Federal Circuit (CAFC) overturned this verdict. The CAFC concluded that no reasonable jury could have found Google's appropriation of that many lines of computer code was fair use. This is the ruling that Supreme Court's decision reversed.

The penultimate sentence in Justice Breyer's opinion for the 6-2 majority succinctly states the Court's conclusion: "where Google reimplemented a user interface, taking only what was needed to allow users [that is, programmers] to put their accrued talents to work in a new and transformative program, Google's copying of the Sun Java API was a fair use of that material as a matter of law."

After explaining Oracle's claims against Google, this column reviews the Court's reasons for rejecting Oracle's arguments on the fair use issue.  ... ' 

Improving the Virtual Classroom

Presentation and paper on efforts at improving the virtual classroom.

How To Improve the Virtual Classroom

By University of California, San Diego, June 21, 2021

Researchers at the University of California, San Diego studied the shift to virtual learning precipitated by the COVID pandemic to better understand where remote education fell short and how it might be improved.

"'It Feels Like I am Talking into a Void': Understanding Interaction Gaps in Synchronous Online Classrooms,"   presented at ACM's 2021 CHI Conference on Human Factors in Computing Systems, examines faculty and student attitudes towards virtual classrooms and proposes several technological refinements that could improve the experience, such as flexible distribution of student video feeds and enhanced chat functions.

"We wanted to understand instructor and student perspectives and see how we can marry them," says senior author Nadir Weibel, associate professor at UC San Diego's Department of Computer Science and Engineering. "How can we improve students' experience and give better tools to instructors?"

First author on the study is Matin Yarmand. Co-authors are UC San Diego Professor Scott Klemmer and Carnegie Mellon University Ph.D. student Jaemarie Solyst.

From University of California, San Diego

Full Article

EU Post Pandemic Wallets

Wondering how far this will go, likely as good as the number of times it is asked for.  I note its use is not mandatory. 

EU Plans Digital ID Wallet for Post-Pandemic Life  By Associated Press, June 4, 2021

European Commissioner for Europe fit for the Digital Age,  Margrethe Vestager, speaking during a media conference at EU headquarters this week.

The European Union (EU) on Thursday announced plans for a post-pandemic smartphone application to enable EU residents to access services across the bloc.   Europeans would be able to store digital credentials such as driver's licenses, prescriptions, and school diplomas through the European Digital Identity Wallet, and access online and offline public/private services while keeping personal data secure.

The European Commission (EC) said the e-wallet would be available to all EU residents, although its use is not mandatory.  Dominant online platforms, however, would have to accept the wallet, in line with the EC's agenda to regulate big technology companies and their control over personal information.

From Associated Press

Thinking Federated AI

Good general idea,  further detailed at the link.

Changing How Data is Used  By Samuel Greengard,  Commissioned by CACM Staff, June 1, 2021

The ability to examine data in deep and revealing ways has fundamentally changed the world. Yet, despite enormous advances in analytics and machine learning, researchers, businesses, and governments remain hamstrung by a basic but nagging problem: a lot of data is sensitive and sharing it presents security and privacy risks.

Although numerous technologies, such as data tokenization, k-anonymity, homomorphic encryption and Trusted Execution Environments (TEE) have helped tame the beast, they do not address the fundamental problem that sensitive data is crossing undesired boundaries. Consequently, many organizations hesitate to share data that could yield remarkable insights. The problem is especially acute when organizations have trade secrets, customer data, or personally identifiable information (PII) embedded in data.

An emerging framework called Federated AI (artificial intelligence) Learning could change all of this, while ushering in broader changes in the way data is used, and owned. The technology has major repercussions for machine learning, security, and privacy. "It represents the future of secure machine learning," says Eliano Marques, vice president of data and AI at data security firm Protegrity.

Rethinking the Model

Federated AI takes the conventional idea of machine learning and turns it on its head. Instead of multiple groups sending data to a central cloud where the machine learning takes place, the algorithm travels to the computing device. All training is performed on the client or device, and when the algorithm determines that it is finished, it exits the device, taking the results with it. "There is no data sharing," says Jigar Mody, head of AI services at Oracle.  ... ' 

Web As We Know it Ending?

 Changing yes, but ending now.  We are too dependent on it for too many things.  No doubt using it is getting trickier.  Need to look closer at risks and Threats. 

The Worldwide Web As We Know It May Be Ending   By CNN in ACM   February 25, 2021

Over the last year, the worldwide web has started to look less worldwide.

Europe is floating regulation that could impose temporary bans on United States tech companies that violate its laws. The U.S. was on the verge of banning TikTok and WeChat. India is now at loggerheads with Twitter.

If such territorial clashes become more common, the globally-connected Internet we know will become more like what some have dubbed the "splinternet," or a collection of different Internets whose limits are determined by national or regional borders.

A combination of rising nationalism, trade disputes, and concerns about the market dominance of certain global tech companies has prompted threats of regulatory crackdowns all over the world. These forces are not just upending the tech companies that built massive businesses on the promise of a global Internet, but also the very idea of building platforms that can be accessed and used the same way by anyone anywhere in the world.

From CNN

History of the VPN

Intriguing history, now finally becoming universal.  Saw it first in the enterprise. 

Everything VPN is New Again in ACM Queue

The 24-year-old security model has found a second wind.

David Crawshaw  in 

The VPN (virtual private network) is 24 years old. The concept—cryptographically secure tunnels used as virtual wires for networking—was created for a radically different Internet from the one we know today. As the Internet grew and changed, so did VPN users and applications. The VPN had an awkward adolescence in the Internet of the 2000s, interacting poorly with other widely popular abstractions such as multiuser operating systems. In the past decade the Internet has changed again, and this new Internet offers new uses for VPNs. The development of a radically new protocol, WireGuard, provides a technology on which to build these new VPNs.

This article is a narrative history of the VPN. All narratives necessarily generalize and cannot capture every nuance, but it is a good-faith effort to (critically) celebrate some of the recent technical history of networking and to capture the mood and attitudes of software engineers and network administrators toward the VPN.  ... " 

A Review of the Semantic Web Field:

Been along follower of semantic Webs, that is webs that aim to capture and readily make usable human, corporate and systems knowledge.   It forms the background of things like a knowledge graph.   Been involved now in several attempts to mine and store the knowledge of parts of corporate knowledge and including related process knowledge.   Even a example of RPA linked process.    I have to say that none of these efforts was completely successful.   That is ending up as a ongoing way to create, store and test substantial knowledge in context.  Have talked about this frequently here.  Still we learned much.   But why not?    Still a student of the practice. Reading this piece, hopefully to better understand why.  Will try to revisit the journey here.   - FAD

A Review of the Semantic Web Field,  By Pascal Hitzler

Communications of the ACM, February 2021, Vol. 64 No. 2, Pages 76-83  10.1145/3397512

Let us begin this review by defining the subject matter. The term Semantic Web as used in this article is a field of research rather than a concrete artifact—in a similar way, say, Artificial Intelligence denotes a field of research rather than a concrete artifact. A concrete artifact, which may deserve to be called "The Semantic Web" may or may not come into existence someday, and indeed some members of the research field may argue that part of it has already been built. Sometimes the term Semantic Web technologies is used to describe the set of methods and tools arising out of the field in an attempt to avoid terminological confusion. We will come back to all this in the article in some way; however, the focus here is to review the research field.

This review will be rather subjective, as the field is very diverse not only in methods and goals being researched and applied, but also because the field is home to a large number of different but interconnected subcommunities, each of which would probably produce a rather different narrative of the history and the current state of the art of the field. I therefore do not strive to achieve the impossible task of presenting something close to a consensus—such a thing still seems elusive. However, I do point out here, and sometimes within the narrative, that there are a good number of alternative perspectives.

The review is also very selective, because Semantic Web is a rich field of diverse research and applications, borrowing from many disciplines within or adjacent to computer science. In a brief review like this one cannot possibly be exhaustive or give due credit to all important individual contributions. I do hope I have captured what many would consider key areas of the Semantic Web field. For the reader interested in obtaining a more detailed overview, I recommend perusing the major publication outlets in the field: The Semantic Web journal,a the Journal of Web Semantics,b and the proceedings of the annual International Semantic Web Conference.c This is by no means an exhaustive list, but I believe it to be uncontroversial that these are the most central publication venues for the field.

Now that we understand that Semantic Web is a field of research, what is it about? Answers to this question are again necessarily subjective as there is no clear consensus on this in the field.

One perspective is that the field is all about the long-term goal of creating The Semantic Web (as an artifact) together with all the necessary tools and methods required for creation, maintenance, and application. In this particular narrative, The Semantic Web is usually envisioned as an enhancement of the current World Wide Web with machine-understandable information (as opposed to most of the current Web, which is mostly targeted at human consumption), together with services—intelligent agents—utilizing this information. This perspective can be traced back to a 2001 Scientific American article,1 which arguably marks the birth of the field. Provision of machine understandable information in this case is done by endowing data with expressive metadata for the data. In the Semantic Web, this metadata is generally in the form of ontologies, or at least a formal language with a logic-based semantics that admits reasoning over the meaning of the data. (Formal metadata is discussed later.) This, together with the understanding that intelligent agents would utilize the information, perceives the Semantic Web field as having a significant overlap with the field of Artificial Intelligence. Indeed, for most of the major artificial intelligence conferences held in the last 20 years ran explicit "Semantic Web" tracks.  ... " 

Anti-Patterns in Regulation

 Thoughtful piece in ACM where the notion of 'anti-pattern' is discussed, where regulation (or norms or practice)  run contrary in purpose to their original intent in design.   An specifically how the GDPR,  the European privacy law, can run contrary to modern cloud scale systems. An element of the goals of practice vs regulation or other forms of compliance.  Considerable look at the idea, largely non technical.  Anyone dealing with GDPR and other regulation  should understand the idea and implications.

GDPR Anti-Patterns  By Supreeth Shastri, Melissa Wasserman, Vijay Chidambaram

Communications of the ACM, February 2021, Vol. 64 No. 2, Pages 59-65  10.1145/3378061

The General Data Protection Regulation (GDPR)26 is a European privacy law introduced to offer new rights and protections to people concerning their personal data. While at-scale monetization of personal data has existed since the dot-com era, a systemic disregard for privacy and protection of personal data is a recent phenomenon. For example, in 2017, we learned about Equifax's negligence17 in following the security protocols, which exposed the financial records of 145 million people; Yahoo!'s delayed confession21 that three years ago, a theft had exposed all three billion of its user records; Facebook's admission33 that their APIs allowed illegal harvesting of user data, which in turn influenced the U.S. and U.K. democratic processes.

Thus, GDPR was enacted to prevent a widespread and systemic abuse of personal data. At its core, GDPR declares the privacy and protection of personal data as a fundamental right. Accordingly, it grants new rights to people, and assigns companies that collect their personal data, new responsibilities. Any company dealing with the personal data of European people is legally bound to comply with all the regulations of GDPR, or risk facing hefty financial penalties. For example, in January 2019, Google was fined6 €50M for lacking a customer's consent in personalizing advertisements across their different services.  ... "