According to investigative reporter Will Evans, Amazon recently backed out of a commitment to make 50% of its shipments net-zero carbon by 2030. "Amazon said (PDF) in a statement that it would roll this goal into a broader Climate Pledge to reach net-zero carbon across all its operations by 2040," reports Insider. "That's a decade later than the 50% goal, which was called 'Shipment Zero' at the time." From the report: "As we examined our work toward The Climate Pledge, we realized that it no longer made sense to have a separate and more narrow Shipment Zero goal that applied to only one part of our business, so we've decided to eliminate it," Amazon wrote in the statement.

The investigative reporter Will Evans squeezed this information from Amazon and tweeted about it Thursday. Last year, Evans uncovered a study that said the company had drastically undercounted its carbon footprint. At the time, an Amazon spokesman reiterated the company's commitment to cutting emissions, including ordering a fleet of electric delivery vans and buying renewable energy for its electricity needs.

Dropping the specific shipment pledge is noteworthy because Amazon's ecommerce operation relies on vast fleets of vehicles and aircraft to deliver packages to consumers quickly. Most of this activity chews up vast quantities of fossil fuels and spews out greenhouse gases. However, fast delivery is a key selling point for shoppers and the main reason millions subscribe to the company's Prime program. Amazon announced the Shipment Zero initiative in a blog a few years ago. The company has since deleted the post. However, through the magic of the Internet Archive's Wayback Machine, large corporations cannot rewrite online history. Here's a version of the blog.

Michael Larabel, reporting at Phoronix: AMD engineers have been working out many quirks and oddities in system suspend/resume handling to make it more reliable on their hardware particularly around Ryzen laptops. In addition to suspend/resume reliability improvements and suspend-to-idle (s2idle) enhancements, one of their engineers also discovered an easy one-liner as a small step to speeding up system resume time. AMD engineer Basavaraj Natikar realized a missing check in the USB XHCI driver can avoid an extra 120ms delay during system resume time. It's only 120 ms, but it's a broad win given it's for the XHCI driver code and part of their larger effort of improving the AMD Ryzen platform on Linux and this 120ms savings is from altering one line of code.

An anonymous reader shared this report from the Verge: Meta is building its first custom chip specifically for running AI models, the company announced on Thursday. As Meta increases its AI efforts — CEO Mark Zuckerberg recently said the company sees "an opportunity to introduce AI agents to billions of people in ways that will be useful and meaningful" — the chip and other infrastructure plans revealed Thursday could be critical tools for Meta to compete with other tech giants also investing significant resources into AI.

Meta's new MTIA chip, which stands for Meta Training and Inference Accelerator, is its "in-house, custom accelerator chip family targeting inference workloads," Meta VP and head of infrastructure Santosh Janardhan wrote in a blog post... But the MTIA chip is seemingly a long ways away: it's not set to come out until 2025, TechCrunch reports.
Meta has been working on "a massive project to upgrade its AI infrastructure in the past year," Reuters reports, "after executives realized it lacked the hardware and software to support demand from product teams building AI-powered features."

As a result, the company scrapped plans for a large-scale rollout of an in-house inference chip and started work on a more ambitious chip capable of performing training and inference, Reuters reported...

Meta said it has an AI-powered system to help its engineers create computer code, similar to tools offered by Microsoft, Amazon and Alphabet.
TechCrunch calls these announcements "an attempt at a projection of strength from Meta, which historically has been slow to adopt AI-friendly hardware systems — hobbling its ability to keep pace with rivals such as Google and Microsoft."

Meta's VP of Infrastructure told TechCrunch "This level of vertical integration is needed to push the boundaries of AI research at scale." Over the past decade or so, Meta has spent billions of dollars recruiting top data scientists and building new kinds of AI, including AI that now powers the discovery engines, moderation filters and ad recommenders found throughout its apps and services. But the company has struggled to turn many of its more ambitious AI research innovations into products, particularly on the generative AI front. Until 2022, Meta largely ran its AI workloads using a combination of CPUs — which tend to be less efficient for those sorts of tasks than GPUs — and a custom chip designed for accelerating AI algorithms...

The MTIA is an ASIC, a kind of chip that combines different circuits on one board, allowing it to be programmed to carry out one or many tasks in parallel... Custom AI chips are increasingly the name of the game among the Big Tech players. Google created a processor, the TPU (short for "tensor processing unit"), to train large generative AI systems like PaLM-2 and Imagen. Amazon offers proprietary chips to AWS customers both for training (Trainium) and inferencing (Inferentia). And Microsoft, reportedly, is working with AMD to develop an in-house AI chip called Athena.

Meta says that it created the first generation of the MTIA — MTIA v1 — in 2020, built on a 7-nanometer process. It can scale beyond its internal 128 MB of memory to up to 128 GB, and in a Meta-designed benchmark test — which, of course, has to be taken with a grain of salt — Meta claims that the MTIA handled "low-complexity" and "medium-complexity" AI models more efficiently than a GPU. Work remains to be done in the memory and networking areas of the chip, Meta says, which present bottlenecks as the size of AI models grow, requiring workloads to be split up across several chips. (Not coincidentally, Meta recently acquired an Oslo-based team building AI networking tech at British chip unicorn Graphcore.) And for now, the MTIA's focus is strictly on inference — not training — for "recommendation workloads" across Meta's app family...

If there's a common thread in today's hardware announcements, it's that Meta's attempting desperately to pick up the pace where it concerns AI, specifically generative AI... In part, Meta's feeling increasing pressure from investors concerned that the company's not moving fast enough to capture the (potentially large) market for generative AI. It has no answer — yet — to chatbots like Bard, Bing Chat or ChatGPT. Nor has it made much progress on image generation, another key segment that's seen explosive growth.

If the predictions are right, the total addressable market for generative AI software could be $150 billion. Goldman Sachs predicts that it'll raise GDP by 7%. Even a small slice of that could erase the billions Meta's lost in investments in "metaverse" technologies like augmented reality headsets, meetings software and VR playgrounds like Horizon Worlds.

Designers are using Unreal Engine to create virtual renditions of architectural projects that were never fully realized, such as the Hillside Sample Project by Neoscape and Safdie Architects, showcasing Moshe Safdie's original vision for Montreal's Habitat 67 housing complex. The interactive 3D models offer exceptional detail of the structures and highlight the potential of real-time 3D renditions for pitching architectural concepts. Engadget reports: A young Safdie designed Habitat 67 for Montreal's 1967 World's Fair, also known as Expo 67. It was meant to combine the advantages of suburbia (such as gardens and multi-level housing) with the affordability and density of apartments. The affordability didn't pan out, and Safdie ended up producing a smaller-scale version for the fair. Habitat 67 ultimately launched Safdie's career, though, and it's still one of the better-known landmarks in the city.

You have a few options for exploring the complex. You can watch a video if you just want a quick overview, but you can also navigate a 3D space using either Google Chrome or a downloadable app. The interactive models let you either roam freely or have Safdie guide you through the project with narration at key points.

Amazon CTO Werner Vogels, writes in a blog post: Software architectures are not like the architectures of bridges and houses. After a bridge is constructed, it is hard, if not impossible, to change the way it was built. Software is quite different, once we are running our software, we may get insights about our workloads that we did not have when it was designed. And, if we had realized this at the start, and we chose an evolvable architecture, we could change components without impacting the customer experience. My rule of thumb has been that with every order of magnitude of growth you should revisit your architecture, and determine whether it can still support the next order level of growth.

A great example can be found in two insightful blog posts written by Prime Video's engineering teams. The first describes how Thursday Night Football live streaming is built around a distributed workflow architecture. The second is a recent post that dives into the architecture of their stream monitoring tool, and how their experience and analysis drove them to implement it as a monolithic architecture. There is no one-size-fits-all. We always urge our engineers to find the best solution, and no particular architectural style is mandated. If you hire the best engineers, you should trust them to make the best decisions.

I always urge builders to consider the evolution of their systems over time and make sure the foundation is such that you can change and expand them with the minimum number of dependencies. Event-driven architectures (EDA) and microservices are a good match for that. However, if there are a set of services that always contribute to the response, have the exact same scaling and performance requirements, same security vectors, and most importantly, are managed by a single team, it is a worthwhile effort to see if combining them simplifies your architecture.

Evolvable architectures are something that we've taken to heart at Amazon from the very start. Re-evaluating and re-architecting our systems to meet the ever-increasing demands of our customers. You can go all the way back to 1998, when a group of senior engineers penned the Distributed Computing Manifesto, which put the wheels in motion to move Amazon from a monolith to a service-oriented architecture. In the decades since, things have continued to evolve, as we moved to microservices, then microservices on shared infrastructure, and as I spoke about at re:Invent, EDA.

An anonymous reader quotes a report from Gizmodo: Microsoft issued a Windows update that broke a Chrome feature, making it harder to change your default browser and annoying Chrome users with popups, Gizmodo has learned. An April Windows update borked a new button in Chrome -- the most popular browser in the world -- that let you change your default browser with a single click, but the worst was reserved for users on the enterprise version of Windows. For weeks, every time an enterprise user opened Chrome, the Windows default settings page would pop up. There was no way to make it stop unless you uninstalled the operating system update. It forced Google to disable the setting, which had made Chrome more convenient.

This petty chapter of the browser wars started in July 2022 when Google quietly rolled out a new button in Chrome for Windows. It would show up near the top of the screen and let you change your default browser in one click without pulling up your system settings. For eight months, it worked great. Then, in April, Microsoft issued Windows update KB5025221, and things got interesting. "Every time I open Chrome the default app settings of Windows will open. I've tried many ways to resolve this without luck," one IT administrator said on a Microsoft forum. A Reddit user noticed that the settings page also popped up any and every time you clicked on a link, but only if Chrome was your default browser. "It doesn't happen if we change the default browser to Edge," the user said. Others made similar complaints on Google support forums, some saying that entire organizations were having the issue. Users quickly realized the culprit was the operating system update.

For people on the regular consumer version of Windows, things weren't quite as bad; the one-click "Make Default" button just stopped working. Gizmodo was able to replicate the problem. In fact, we were able to circumvent the issue just by changing the name of the Chrome app on a Windows desktop. It seems that Microsoft threw up the roadblock specifically for Chrome, the main competitor to its Edge browser. [...] In response, Google had to disable its one-click default button; the issue stopped after it did. In other words, Microsoft seems to have gone out of its way to break a Chrome feature that made life easier for users. Google confirmed the details of this story, but declined to comment further.

The low-profile firm that has become crucial to a half-trillion-dollar global industry. From a report: In 1984, Martin van den Brink, a young Dutch engineer, joined a newly created venture in a quiet corner of the Netherlands. Little did he know then that about 40 years on the company would be so crucial to the $580 billion semiconductor industry that it would be the epicenter of a US-China chip war. ASML Holding NV, where Van den Brink is now the chief technology officer, practically owns the market for a critical piece of equipment needed to produce the brains of everything that makes modern life possible -- from cars and smartphones to computers, microwaves and airplanes. With the company's high-end machines churning out chips that can also go into state-of-the-art weapons and artificial intelligence devices, ASML is effectively being treated as critical infrastructure for US national security and has become a target of industrial espionage for China. "I never expected to be where we are today," said Van den Brink.

Over his nearly four decades at the company, ASML has gone from a bit player competing with the likes of Nikon, Canon and Ultratech to the world's only maker of very high-end semiconductor lithography equipment. Its ascent has made it Europe's most valuable technology company, with a market capitalization of over $247 billion -- more than twice that of its customer Intel. In an industry where devices typically cost $10 million, ASML commands about $180 million for its current top-end machine. And although the chip market has softened recently, ASML is still growing and its long-term outlook seems intact, thanks to the insatiable demand for computing power.

"This is a company that the world can't exist without," said Jon Bathgate, a fund manager at NZS Capital in Denver, which has about $2 billion under management, with ASML as one of its biggest holdings. "They've got a 20-year head start... Investors have clearly realized how important ASML is as a company and how difficult it would be to replicate. It's a natural monopoly with secular growth winds. That's unique." As chips become for geopolitics in the 21st century what oil was in the last one, ASML's singular success has thrust it squarely in the crosshairs of the intensifying tensions between the US and China. With the US focused on the strategic importance of semiconductors, Presidents Donald Trump and Joe Biden have done everything to ensure that China is a couple of generations behind in chips. No company is more critical to that effort than ASML.

An anonymous reader quotes a report from TechCrunch: In pursuit of "safer" text-generating models, Nvidia today released NeMo Guardrails, an open source toolkit aimed at making AI-powered apps more "accurate, appropriate, on topic and secure." Jonathan Cohen, the VP of applied research at Nvidia, says the company has been working on Guardrails' underlying system for "many years" but just about a year ago realized it was a good fit for models along the lines of GPT-4 and ChatGPT. "We've been developing toward this release of NeMo Guardrails ever since," Cohen told TechCrunch via email. "AI model safety tools are critical to deploying models for enterprise use cases."

Guardrails includes code, examples and documentation to "add safety" to AI apps that generate text as well as speech. Nvidia claims that the toolkit is designed to work with most generative language models, allowing developers to create rules using a few lines of code. Specifically, Guardrails can be used to prevent -- or at least attempt to prevent -- models from veering off topic, responding with inaccurate information or toxic language and making connections to "unsafe" external sources. Think keeping a customer service assistant from answering questions about the weather, for instance, or a search engine chatbot from linking to disreputable academic journals. "Ultimately, developers control what is out of bounds for their application with Guardrails," Cohen said. "They may develop guardrails that are too broad or, conversely, too narrow for their use case."

While companies like Zapier are using Guardrails to add a layer of safety to their generative models, Nvidia acknowledges that the toolkit isn't imperfect; it won't catch everything, in other words. Cohen also notes that Guardrails works best with models that are "sufficiently good at instruction-following," a la ChatGPT, and that use the popular LangChain framework for building AI-powered apps. That disqualifies some of the open source options out there. And -- effectiveness of the tech aside -- it must be emphasized that Nvidia isn't necessarily releasing Guardrails out of the goodness of its heart. It's a part of the company's NeMo framework, which is available through Nvidia's enterprise AI software suite and its NeMo fully managed cloud service. Any company can implement the open source release of Guardrails, but Nvidia would surely prefer that they pay for the hosted version instead.

Reddit moderators say they already see an increase in spam and that the future will "require a lot of human labor." From a report: In December last year, the moderators of the popular r/AskHistorians Reddit forum noticed posts popping up that appeared to carry the hallmarks of AI-generated text. "They were pretty easy to spot," said Sarah Gilbert, one of the forum's moderators and a postdoctoral associate at Cornell University. "They're not in-depth, they're not comprehensive, and they often contain false information." The team quickly realized their little corner of the internet had become a target for ChatGPT-created content. When ChatGPT launched last year, it set off a seemingly never-ending carousel of hype. According to evangelists, the tech behind ChatGPT may eradicate hundreds of millions of jobs, exhibit "sparks" of singularity-esque artificial general intelligence, and quite possibly destroy the world, but in a way that means you must buy it right now. The less glamorous impacts, like unleashing a tidal wave of AI-produced effluvium on the internet, haven't garnered the same attention so far.

The two-million-strong AskHistorians forum allows non-expert Redditors to submit questions about history topics, and receive in-depth answers from historians. Recent popular posts have probed the hive mind on whether the stress of being "on time" is a modern concept; what a medieval scribe would've done if the monastery cat left an inky paw print on their vellum; and how Genghis Khan got fiber in his diet. Shortly after ChatGPT launched, the forum was experiencing five to 10 ChatGPT posts per day, says Gilbert, which soon ramped up as more people found out about the tool. The frequency has tapered off now, which the team believes may be a consequence of how rigorously they've dealt with AI-produced content: even if the posts aren't being deleted for being written by ChatGPT, they tend to violate the sub's standards for quality.

In the 1970s, Bob Metcalfe helped develop the primary technology that lets you send email or connect with a printer over an office network. From a report: In June 1972, Bob Metcalfe, a 26-year-old engineer fresh out of graduate school, joined a new research lab in Palo Alto, Calif., as it set out to build something that few people could even imagine: a personal computer. After another engineer gave up the job, Dr. Metcalfe was asked to build a technology that could connect the desktop machines across an office and send information between them. The result was Ethernet, a computer networking technology that would one day become an industry standard. For decades, it has connected PCs to servers, printers and the internet in corporate offices and homes across the globe.

For his work on Ethernet, the Association for Computing Machinery, the world's largest society of computing professionals, announced on Wednesday that Dr. Metcalfe, 76, would receive this year's Turing Award. Given since 1966 and often called the Nobel Prize of computing, the Turing Award comes with a $1 million prize. When Dr. Metcalfe arrived at the Palo Alto Research Center -- a division of Xerox nicknamed PARC -- the first thing he did was connect the lab to the Arpanet, the wide-area network that later morphed into the modern internet. The Arpanet transmitted information among about 20 academic and corporate labs across the country. But as PARC researchers designed their personal computer, called the Alto, they realized they needed a network technology that could connect personal computers and other devices within an office, not over long distances. Further reading: Ethernet Creator Makes the Inventors Hall of Fame (2007).

Codon is a new "high-performance Python compiler that compiles Python code to native machine code without any runtime overhead," according to its README file on GitHub. Typical speedups over Python are on the order of 10-100x or more, on a single thread. Codon's performance is typically on par with (and sometimes better than) that of C/C++. Unlike Python, Codon supports native multithreading, which can lead to speedups many times higher still.
Its development team includes researchers from MIT's Computer Science and Artificial Intelligence lab, according to this announcement from MIT shared by long-time Slashdot reader Futurepower(R): The compiler lets developers create new domain-specific languages (DSLs) within Python — which is typically orders of magnitude slower than languages like C or C++ — while still getting the performance benefits of those other languages. "We realized that people don't necessarily want to learn a new language, or a new tool, especially those who are nontechnical. So we thought, let's take Python syntax, semantics, and libraries and incorporate them into a new system built from the ground up," says Ariya Shajii SM '18, PhD '21, lead author on a new paper about the team's new system, Codon. "The user simply writes Python like they're used to, without having to worry about data types or performance, which we handle automatically — and the result is that their code runs 10 to 100 times faster than regular Python. Codon is already being used commercially in fields like quantitative finance, bioinformatics, and deep learning."

The team put Codon through some rigorous testing, and it punched above its weight. Specifically, they took roughly 10 commonly used genomics applications written in Python and compiled them using Codon, and achieved five to 10 times speedups over the original hand-optimized implementations.... The Codon platform also has a parallel backend that lets users write Python code that can be explicitly compiled for GPUs or multiple cores, tasks which have traditionally required low-level programming expertise.... Part of the innovation with Codon is that the tool does type checking before running the program. That lets the compiler convert the code to native machine code, which avoids all of the overhead that Python has in dealing with data types at runtime.

"Python is the language of choice for domain experts that are not programming experts. If they write a program that gets popular, and many people start using it and run larger and larger datasets, then the lack of performance of Python becomes a critical barrier to success," says Saman Amarasinghe, MIT professor of electrical engineering and computer science and CSAIL principal investigator. "Instead of needing to rewrite the program using a C-implemented library like NumPy or totally rewrite in a language like C, Codon can use the same Python implementation and give the same performance you'll get by rewriting in C. Thus, I believe Codon is the easiest path forward for successful Python applications that have hit a limit due to lack of performance."

The other piece of the puzzle is the optimizations in the compiler. Working with the genomics plugin, for example, will perform its own set of optimizations that are specific to that computing domain, which involves working with genomic sequences and other biological data, for example. The result is an executable file that runs at the speed of C or C++, or even faster once domain-specific optimizations are applied.

An anonymous reader quotes a report from CBS News: The U.S. Postal Service's plans for a nationwide fleet of electric vehicles are getting closer to being realized. The service awarded contracts on Tuesday for 9,250 battery electric vehicles and for more than 14,000 charging stations. The vehicles purchased are Ford E-Transit Battery Electric Vehicles (BEVs), which according to USPS are "100 percent electric." It's part of the agency's plans, announced in December, to make 75% of its newly acquired vehicles, known as Next Generation Delivery Vehicles, over the next five years electric. After 2026, NGDV purchases will be 100% electric, the agency said. The goal is to have a fleet of 66,000 electric vehicles deployed by 2028.

Three suppliers were awarded contracts for more than 14,000 charging stations, as well, USPS said, to kick off its Electric Vehicle Supply Equipment (EVSE) inventory. However, the agency did note that the contracts they just awarded will not provide an immediate supply. The vehicles won't be delivered until December, assuming that the agency successfully finishes its Supplemental Environmental Impact Statement and other necessary tasks. It also remains unclear where the vehicles and charging stations will be placed, as those details have yet to be finalized, the agency said.

As such, a contract has also been awarded for the agency to acquire 9,250 commercial-off-the-shelf internal combustion engine vehicles "to fill the urgent need for vehicles." In December, the agency said that 21,000 COTS vehicles will be purchased and are "expected to be battery electric," but said that depends "on market availability and operational feasibility." In this case, the internal combustion engine vehicles will be gas-powered and made by Fiat Chrysler Automobile, a spokesperson for USPS told CBS News. They added that, unlike older USPS vehicles, these will "feature air conditioning and advanced safety technology and are more suited to modern day operational requirements." "We have an urgent need to replace some of our vehicles as soon as possible, and in those instances we will look to obtain vehicles that can be provided to us expeditiously, recognizing that there are a limited amount of BEV options currently available and that the charging infrastructure buildout will also take some time," they said in an email.

"...Today there remain routes and applications which do not support BEVs. As BEV technology matures and capabilities increase, the Postal Service will continue to review its ability to utilize and expand BEV usage."

Longtime Slashdot reader theshowmecanuck shares a report from CBS News: A 2012 trip to a Fayetteville, Arkansas, Walmart to pick up some milk turned out to be one for the history books. A giant bug that stopped a scientist in his tracks as he walked into the store and he ended up taking home turned out to be a rare Jurassic-era flying insect. Michael Skvarla, director of Penn State University's Insect Identification Lab, found the mysterious bug -- an experience that he says he remembers "vividly."

"I was walking into Walmart to get milk and I saw this huge insect on the side of the building," he said in a press release from Penn State. "I thought it looked interesting, so I put it in my hand and did the rest of my shopping with it between my fingers. I got home, mounted it, and promptly forgot about it for almost a decade."

[I]n the fall of 2020 when he was teaching an online course on insect biodiversity and evolution, Skvarla was showing students the bug and suddenly realized it wasn't what he originally thought. He and his students then figured out what it might be -- live on a Zoom call. "We were watching what Dr. Skvarla saw under his microscope and he's talking about the features and then just kinda stops," one of his students Codey Mathis said. "We all realized together that the insect was not what it was labeled and was in fact a super-rare giant lacewing." A clear indicator of this identification was the bug's wingspan. It was about 50 millimeters -- nearly 2 inches -- a span that the team said made it clear the insect was not an antlion. His team's molecular analysis on the bug has been published in the Proceedings of the Entomological Society of Washington.

theshowmecanuck captioned: "To be fair, he said he didn't know what it was so [he] just collected it and took it home, and then figured it out later. My thought that I added to the title was because of this quote in the story (which tickled my cynicism in humanity): "It could have been 100 years since it was even in this area -- and it's been years since it's been spotted anywhere near it..."

Cars aren't the only conveyances being transformed by electricity. Along with electric motorcycles and snowmobiles, personal watercraft are floating better ways to coexist with nature and neighbors. This new breed of machines brings requisite thrills to the Great Outdoors, but without fouling the atmosphere or disturbing the peace with an internal-combustion racket. From a report: The latest comes from Florida-based Pelagion, whose founder and chief executive, engineer Jamie Schlinkmann, was inspired by childhood adventures on a watersports icon: A 1973 Kawasaki Jet Ski. Schlinkmann's machine, just the 213th ever built, is still one of his prized possessions. His company's Pelagion HydroBlade is an ingenious mash-up of classic stand-up Jet Skis and modern surfboard-style "eFoils." Those electric-powered boards had a real breakthrough in 2020 when Facebook founder Mark Zuckerberg was spotted sailing over Hawaiian waters on one model. The metaverse may spring to mind the first time you see an eFoil, with its rider seeming to fly above the waves on a magic carpet. Naturally, there's no magic, only hydrodynamics. Hydrofoils work like an airplane wing, only underwater: An aerodynamic wing creates high and low pressure areas as it slices through water, generating lift with precious little drag. Add an electric motor and propeller to create thrust and you've got a hydrofoil that doesn't require surf waves, a kite, or tow boat to generate power.

There's only one problem: Powered or not, a hydrofoil takes some practice and patience to learn to ride in a standing position, especially for people with no surfing or wakeboarding experience, or so-so balance skills. To solve that, Schlinkmann's invention adds a boom-mounted canard and rudder ahead of the rider to keep the craft airborne and steady without a rider having to constantly expend energy and adjust body position. Add a trusty set of handlebars, says Schlinkmann, and the HydroBlade handles more like a vehicle with which most of us are familiar: a bicycle. Making the experience somewhat like riding a bike, he says, helps ease the intimidation factor and boost appeal for people of all ages and abilities. [...] The design began to take shape around 2020. Schlinkmann pulled the engine and other ICE guts from his old Jet Ski and studied how he could make it electric. He realized a conventional electric Jet Ski might only have a 15- or 20-minute runtime on a single charge, which wasn't good enough. But after riding a few eFoils, the idea came together. For the HydroBlade, a pair of permanent-magnet radial-flux motors drive dual propellers at a peak 16 kilowatts (21 horsepower). They're fed by two battery packs, with a combined 600 cylindrical 2170 NCM cells and a total 11 kilowatt-hours of energy -- about eight to 10 times the capacity onboard a typical eFoil. A separate 1.6-kW charger can refill batteries in about 4 hours.

An anonymous reader quotes a report from Gizmodo: A team of engineers studying the 500-year-old, backward writings of Leonardo da Vinci have found evidence that the Italian polymath was working out gravity a century before its foundations were established by Galileo Galilei. The team's findings come from a revisit of the Codex Arundel, a compilation of documents written by da Vinci that detail various experiments and personal notes taken down in the latter 40 years of his life. The codex is freely accessible online courtesy of the British Museum. The team's research is published in the MIT Press journal Leonardo. Mory Gharib, an engineer at Caltech, said he stumbled across the writings in 2017 when looking for some of da Vinci's work on flow in hearts. Though the codex was written over a long span of da Vinci's later years, Gharib suspects the gravitational musings were written sometime in the last 15-or-so years of his life. Gharib recruited co-author Flavio Noca, a researcher at the University of Applied Sciences and Arts Western Switzerland, to translate the Italian's backward writing on the subject.

Da Vinci understood some fundamentals of objects in motion. He wanted to make an experiment testing how the motion of a cloud would correspond to the hail it produced, if the cloud's velocity and any changes to it corresponded with the falling hail's velocity. In lieu of control of the weather, da Vinci substituted a pitcher for the cloud and sand or water for the hail. Reliable clocks weren't available until about 140 years after da Vinci's death in 1519, the researchers note, so the inventor was forced to substitute the constant of time with space: by assuming that the time it took each water/sand particle to fall from the pitcher was constant, he just kept the pitcher at the same height throughout the tests. Da Vinci's sketch shows the positions of the falling material over the course of its trajectory toward the ground. By drawing a line through the position of the material at each instance in time, da Vinci realized that a triangle could be formed, with the drawn line being the hypotenuse. By changing the acceleration of the pitcher over the course of the experiment, one would change the shape of the triangle. Leonardo knew that the falling material would accelerate and that the acceleration is downward. What he wasn't wholly certain on -- hence the experiment -- was the relationship between the falling material's acceleration and the pitcher's acceleration.

In one particular case, when the pitcher's motion was accelerated to the same rate as the falling material being affected by gravity, an equilateral triangle was formed. Literally, as Da Vinci noted, an "Equatione di Moti" or an "equalization of motions." The researchers modeled da Vinci's experiment and found that the polymath was wrong in his understanding of the relationship between the falling object and time. "What we saw is that Leonardo wrestled with this, but he modeled it as the falling object's distance was proportional to 2 to the t power [with t representing time] instead proportional to t squared," said Chris Roh, a researcher at Cornell University and a co-author of the researcher, in a Caltech release. "It's wrong, but we later found out that he used this sort of wrong equation in the correct way." The team interpreted tick marks on da Vinci's sketches as data points the polymath made based on his eyeballing of the experiment in action. In lieu of a timepiece, da Vinci found the gravitational constant to nearly 98% accuracy.

Coming to the campuses of Facebook parent Meta Platforms is a contraption that can block sound, shield workers from their peers and allow for heads-down, uninterrupted work. It's a cubicle. From a report: That is, a noise-canceling cubicle designed using some of the same principles found in soundproof, echo-free anechoic chambers. "The Cube," which the company is beginning to roll out to offices worldwide after months of development, absorbs sound from multiple directions, says John Tenanes, vice president of global real estate and facilities at Meta. "It's like a self-cocoon."

Meta's experiment comes as workplaces are in the midst of a shake-up. Like many other employers, Meta realized early in the pandemic that its open-plan arrangements would need to shift to accommodate a new hybrid era of work. In 2021, it asked 10 groups of architects, design firms and furniture manufacturers-- including MillerKnoll's Herman Miller, KI and others -- to build a new office set-up. They were given guiding principles to follow and eight weeks to do it. [...] The Cube began to take shape, in part, after one of Meta's furniture vendors brought in an early prototype of a movable screen. Engineers quickly gravitated to it, grabbing one or two at a time to essentially barricade themselves at their desks, Dr. Nagy says. Meta and its vendors refined the Cube, and its popularity became even more apparent during testing when workers began personalizing the spaces to effectively reserve them.

Several Bing users say a ChatGPT-assisted version of Bing "mysteriously appeared (and disappeared) earlier today," the Verge reported Friday: Student and designer Owen Yin reported seeing the "new Bing" on Twitter this morning. He told The Verge via Twitter DM that he has Bing set as his homepage on Microsoft's Edge browser and the new UI just loaded up. "Didn't do anything to find it," said Yin. "After a couple of minutes it stopped working ... Jaw dropped when I realized what I was looking at...!" Yin was able to briefly test the system and shared further details about the integration in a blog post on Medium. He noted that the chatbot could not only answer questions but ask them in a conversational manner.

The new Bing can also apparently cite its sources. This is an important feature, as the inability of language models like ChatGPT to describe where their information is sourced from makes them less reliable.

Yin isn't the only one who says they encountered a new Bing today either. At least two others reported receiving access to the updated search engine on Twitter before it disappeared.

Screenshots of the AI-augmented Bing show a new "chat" option appearing in the menu bar next to "search." Select it and you're taken to a chat interface that says, "Welcome to the new Bing: Your AI-powered answer engine."
The Verge adds that they were "unable to verify the authenticity of these screenshots and Microsoft declined to comment on the validity of these apparent leaks."

An anonymous reader quotes a report from Wired: Your gut has an obvious job: It processes the food you eat. But it has another important function: It protects you from the bacteria, viruses, or allergens you ingest along with that food. "The largest part of the immune system in humans is the GI tract, and our biggest exposure to the world is what we put in our mouth," says Michael Helmrath, a pediatric surgeon at Cincinnati Children's Hospital Medical Center who treats patients with intestinal diseases. Sometimes this system malfunctions or doesn't develop properly, which can lead to gastrointestinal conditions like ulcerative colitis, Crohn's disease, and celiac -- all of which are on the rise worldwide. Studying these conditions in animals can only tell us so much, since their diets and immune systems are very different from ours.

In search of a better method, last week Helmrath and his colleagues announced in the journal Nature Biotechnology that they had transplanted tiny, three-dimensional balls of human intestinal tissue into mice. After several weeks, these spheres -- known as organoids -- developed key features of the human immune system. The model could be used to mimic the human intestinal system without having to experiment on sick patients. The experiment is a dramatic follow-up from 2010, when researchers at Cincinnati Children's became the first in the world to create a working intestine organoid -- but their initial model was a simpler version in a lab dish. A few years later, Helmrath says, they realized "we needed it to become more like human tissue." [...]

Matthew Grisham, a gastroenterologist at Texas Tech University Health Sciences Center who wasn't involved in the new study, says the findings are exciting because these structures have a "human immune cell composition very similar to that of the developing human gut." He says the organoid model will help researchers investigate the mechanisms responsible for intestinal infection, inflammation, and food allergies. The Cincinnati researchers also hope their organoids could one day be used to treat people born with genetic defects that affect their digestive systems, or those who have lost intestinal function to cancer or inflammatory bowel diseases. That these organoids can flourish in a mouse is an encouraging sign that they might be able to grow on their own if transplanted into a person. Using induced pluripotent stem cells taken from patients, scientists could perhaps one day make customized tissue patches to help heal damaged organs. In the near-term, Helmrath says his team plans on making organoids from patients' own cells to test out possible individualized therapies. "This is right around the corner," he says.

An anonymous reader quotes a report from TechCrunch: A bug in a new centralized system that Meta created for users to manage their logins for Facebook and Instagram could have allowed malicious hackers to switch off an account's two-factor protections just by knowing their phone number. Gtm Manoz, a security researcher from Nepal, realized that Meta did not set up a limit of attempts when a user entered the two-factor code used to log into their accounts on the new Meta Accounts Center, which helps users link all their Meta accounts, such as Facebook and Instagram.

With a victim's phone number, an attacker would go to the centralized accounts center, enter the phone number of the victim, link that number to their own Facebook account, and then brute force the two-factor SMS code. This was the key step, because there was no upper limit to the amount of attempts someone could make. Once the attacker got the code right, the victim's phone number became linked to the attacker's Facebook account. A successful attack would still result in Meta sending a message to the victim, saying their two-factor was disabled as their phone number got linked to someone else's account.

Manoz found the bug in the Meta Accounts Center last year, and reported it to the company in mid-September. Meta fixed the bug a few days later, and paid Manoz $27,200 for reporting the bug. Meta spokesperson Gabby Curtis told TechCrunch that at the time of the bug the login system was still at the stage of a small public test. Curtis also said that Meta's investigation after the bug was reported found that there was no evidence of exploitation in the wild, and that Meta saw no spike in usage of that particular feature, which would signal the fact that no one was abusing it.

Researchers from the University of Birmingham have developed an innovative method for existing furnaces that could reduce steelmaking's CO2 emission by nearly 90%. The Next Web reports: The iron and steel industry is a major cause of greenhouse gasses, accounting for 9% of global emissions. That's because of the inherent carbon-intensive nature of steel production in blast furnaces, which currently represent the most-widely used practice. In blast furnace steel manufacturing, coke (a type of coal) is used to produce metallic iron from ore obtained from mining -- which releases large quantities of carbon dioxide in the process. According to Dr Harriet Kildahl, who co-devised the method with Professor Yulong Ding, their technology aims to convert this carbon dioxide into carbon monoxide that can be reused in the iron ore reaction.

This is realized using a thermochemical cycle which performs chemical reactions through changes in temperature. That way, the typically damaging CO2 is turned into a useful part of the reaction, forming "an almost perfect closed carbon loop." This drastically reduces emission by the amount of coke needed and, subsequently, lowers steelmaking's emissions by up to 88%. As per the researchers, if this method was implemented in the remaining two blast furnaces in the UK, it could save 1.28 billion pounds in 5 years, all while reducing the country's overall emissions by 2.9%.

"Current proposals for decarbonizing the steel sector rely on phasing out existing plants and introducing electric arc furnaces powered by renewable electricity. However, an electric arc furnace plant can cost over 1 billion pounds to build, which makes this switch economically unfeasible in the time remaining to meet the Paris Climate Agreement," Professor Ding said. "The system we are proposing can be retrofitted to existing plants, which reduces the risk of stranded assets, and both the reduction in CO2, and the cost savings, are seen immediately." The study has been published in the Journal of Cleaner Production.