CNET visits a leading-edge company making an implantable brain-computer-interface that's "experimenting with ChatGPT integration..." We previously covered Synchron's unique approach to implanting its brain-computer-interface (BCI) without the need for open brain surgery. Now the company has integrated OpenAI's ChatGPT into its software, something it says is a world's first for a BCI company...

Typing out messages word by word with the help of a BCI is still time consuming. The addition of AI is seen as a way to make communication faster and easier by taking in the relevant context, like what was last said in a conversation, and anticipating answers a person might want to respond with, providing them with a menu of possible options. Now, instead of typing out each word, answers can be filled in with a single "click." There's a refresh button in case none of the AI answers are right... [ALS patient Mark, one of 10 people in the world testing Synchron's brain implant in a clinical trial] has noticed the AI getting better at providing answers that are more in line with things he might say. "Every once in a while it'll drop an f-bomb, which I tend to do occasionally," he says with a laugh.

Synchron CEO Tom Oxley tells me the company has been experimenting with different AI models for about a year, but the release of OpenAI's ChatGPT-4o in May raised some interesting new possibilities. The "o" in ChatGPT-4o stands for "omni," representative of the fact that this latest version is capable of taking in text, audio and visual inputs all at once to inform its outputs... Oxley envisions the future of BCIs as... having large language models like ChatGPT take in relevant context in the form of text, audio and visuals to provide relevant prompts that users can select with their BCI... Synchron's BCI is expected to cost between $50,000 and $100,000, comparable with the cost of other implanted medical devices like cardiac pacemakers or cochlear implants.
CNET has also released a video — titled "What It's Like Using a Brain Implant With ChatGPT."

Simon Sharwood reports via The Register: Chinese researchers have created a drone that weighs just over four grams -- less than a sheet of printer paper -- and may be able to fly indefinitely. Documented in a paper published last week in Nature, the drone uses an electrostatic motor that weighs just 1.52 grams and is powered by solar cells that produce 4.5V. The paper asserts that the drone's design has a lift-to-power efficiency two to three times better than that found in traditional drones. The authors suggested that if rechargeable batteries can be added, the craft could be capable of 24-hour flying operations.

An anonymous reader quotes a report from MIT Technology Review: Researchers from Google have built a new weather prediction model that combines machine learning with more conventional techniques, potentially yielding accurate forecasts at a fraction of the current cost. The model, called NeuralGCM and described in a paper in Nature today, bridges a divide that's grown among weather prediction experts in the last several years. While new machine-learning techniques that predict weather by learning from years of past data are extremely fast and efficient, they can struggle with long-term predictions. General circulation models, on the other hand, which have dominated weather prediction for the last 50 years, use complex equations to model changes in the atmosphere and give accurate projections, but they are exceedingly slow and expensive to run. Experts are divided on which tool will be most reliable going forward. But the new model from Google instead attempts to combine the two.

"It's not sort of physics versus AI. It's really physics and AI together," says Stephan Hoyer, an AI researcher at Google Research and a coauthor of the paper. The system still uses a conventional model to work out some of the large atmospheric changes required to make a prediction. It then incorporates AI, which tends to do well where those larger models fall flat -- typically for predictions on scales smaller than about 25 kilometers, like those dealing with cloud formations or regional microclimates (San Francisco's fog, for example). "That's where we inject AI very selectively to correct the errors that accumulate on small scales," Hoyer says. The result, the researchers say, is a model that can produce quality predictions faster with less computational power. They say NeuralGCM is as accurate as one-to-15-day forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF), which is a partner organization in the research.

But the real promise of technology like this is not in better weather predictions for your local area, says Aaron Hill, an assistant professor at the School of Meteorology at the University of Oklahoma, who was not involved in this research. Instead, it's in larger-scale climate events that are prohibitively expensive to model with conventional techniques. The possibilities could range from predicting tropical cyclones with more notice to modeling more complex climate changes that are years away. "It's so computationally intensive to simulate the globe over and over again or for long periods of time," Hill says. That means the best climate models are hamstrung by the high costs of computing power, which presents a real bottleneck to research." The researchers said NeuralGCM will be open source and capable of running on less than 5,500 lines of code, compared with the nearly 377,000 lines required for the model from the National Oceanic and Atmospheric Administration (NOAA).

AMD has introduced its latest Ryzen AI chips, built on the new Zen 5 architecture, in an ambitious attempt to compete with Apple's dominant MacBook processors. During a recent two-day event in Los Angeles, the company made bold claims about outperforming Apple's M3 and M3 Pro chips in various tasks including multitasking, image processing, and gaming, though these assertions remain unverified due to limited demonstrations and benchmarks provided at the event, The Verge reports. The report adds: At that event, I heard AMD brag about beating the MacBook more than I've ever heard a company directly target a competitor before. AMD claimed its new Ryzen chip "exceeds the performance of what MacBook Air has to offer in multitasking, image processing, 3D rendering, and gaming"; "is 15 percent faster than the M3 Pro" in Cinebench; and is capable of powering up to four displays, "unlike the MacBook Air, which limits you to two displays only." While AMD touted significant improvements in CPU architecture, graphics performance, and AI capabilities, journalists present at the event were unable to fully test or validate these features, leaving many questions unanswered about the chips' real-world performance.

The company's reluctance or inability to showcase certain capabilities, particularly in gaming and AI applications, has raised eyebrows among industry observers, the report adds. The new Ryzen AI chips are scheduled to debut in Asus laptops on July 28th, marking a critical juncture for AMD in the fiercely competitive laptop processor market. As Apple's M-series chips and Qualcomm's Snapdragon processors continue to gain traction in the mobile computing space, the success or failure of AMD's latest offering could have far-reaching implications for the future of x86 architecture in laptops.

Meta says it won't be launching its upcoming multimodal AI model -- capable of handling video, audio, images, and text -- in the European Union, citing regulatory concerns. From a report: The decision will prevent European companies from using the multimodal model, despite it being released under an open license. Just last week, the EU finalized compliance deadlines for AI companies under its strict new AI Act. Tech companies operating in the EU will generally have until August 2026 to comply with rules around copyright, transparency, and AI uses like predictive policing. Meta's decision follows a similar move by Apple, which recently said it would likely exclude the EU from its Apple Intelligence rollout due to concerns surrounding the Digital Markets Act.

Dr. Fei-Fei Li, the so-called "godmother of AI," is working on a startup focused on developing technology capable of human-like visual data processing and advanced reasoning. According to the Financial Times (paywalled), the startup is called World Labs and is already worth $1 billion. Quartz reports: "Curiosity urges us to create machines to see just as intelligently as we can, if not better," Li said during a Ted talk in April. "And if we want to advance AI beyond its current capabilities, we want more than AI that can see and talk. We want AI that can do." Andreessen Horowitz and the AI fund Radical Ventures are funders of World Labs.

Li is renowned for her contributions to AI. She invented ImageNet, a dataset used for advancing computer vision that many see as a catalyst for the AI boom. She consults with policymakers as they work to set up guardrails for the technology, and was named one of 12 national AI research resource task force members by the U.S. White House in 2021.

"In a significant advancement for space technology, a team of UC Berkeley researchers, led by doctoral student Taylor Waddell, successfully launched a 3D printer into space," reports the university's student newspaper: As part of the Virgin Galactic 07 mission, the team sent a 3D printer named SpaceCAL to space to explore the potential of Computed Axial Lithography, or CAL, and additive manufacturing in space... During its 140-second flight in suborbital space, the SpaceCAL printer autonomously detected microgravity and printed four test parts: two space shuttles and two Benchies, or 3D-printed boats created to check the printer's accuracy, according to Sean Chu, a member of the team who worked on designing structures and mechanisms. Within the 140 seconds, the process involved multiple steps such as printing, post-washing, flushing with water and post-curing with light to fully solidify the parts.
But that's just the beginning, says the university's engineering department: To date, CAL has shown that it can successfully print with more than 60 different materials on Earth, such as silicones, glass composites and biomaterials. According to Waddell, this versatility could come in handy for both the cabin and the crew... "CAL is also capable of repairing the crew. We can print dental replacements, skin grafts or lenses, or things personalized in emergency medicine for astronauts, which is very important in these missions, too."

Someday, CAL may be used to print even more sophisticated parts, such as human organs. Lawrence Livermore National Lab has received a grant from NASA to test this technology on the International Space Station. "They're going to basically do bioprinting on the Space Station," said Waddell. "And the long, long-term goal is to print organs up in space with CAL, then bring them back down to Earth." Next, Waddell and his colleagues hope to begin work with NASA on developing and validating a single object that could support crew health and wellness, like a dental crown for an astronaut or a surgical wound closure tool...

This project was made possible through a $1.4 million grant and engineering support provided by NASA. In addition, Virgin Galactic played a pivotal role in taking this project to the next level.

An anonymous reader quotes a report from Reuters: Taiwan's TSMC scaled a record high on Thursday after posting strong second-quarter revenue on booming demand for AI applications, cementing its position as Asia's most valuable company. TSMC also topped a trillion dollar market value this week. The AI frenzy has sparked a rally in chipmaker stocks across the globe. Taiwan Semiconductor Manufacturing Co (TSMC), the world's largest contract chipmaker, whose customers include AI poster child Nvidia, has especially benefited from the soaring demand for AI-capable chips.

Foreign investors have poured $4.8 billion so far this year into Taiwan's stock market, which is dominated by TSMC. Asian funds, however, according to HSBC, still remain underweight on Taiwan, suggesting there could be room for further inflow. Shares of TSMC, whose customers also include Apple, have jumped nearly 80% this year, widely outperforming the benchmark Taiwan SE Weighted Index, which is up 35%. On Thursday, TSMC's Taipei-listed shares rose more than 2% to a record T$1,080, taking the company's market value to T$28 trillion ($861 billion) and making it Asia's most valuable publicly listed company.

Amazon Web Services is the latest entrant to the generative AI game with the announcement of App Studio, a groundbreaking tool capable of building complex software applications from simple written prompts. TechCrunch's Ron Miller reports: "App Studio is for technical folks who have technical expertise but are not professional developers, and we're enabling them to build enterprise-grade apps," Sriram Devanathan, GM of Amazon Q Apps and AWS App Studio, told TechCrunch. Amazon defines enterprise apps as having multiple UI pages with the ability to pull from multiple data sources, perform complex operations like joins and filters, and embed business logic in them. It is aimed at IT professionals, data engineers and enterprise architects, even product managers who might lack coding skills but have the requisite company knowledge to understand what kinds of internal software applications they might need. The company is hoping to enable these employees to build applications by describing the application they need and the data sources they wish to use.

Examples of the types of applications include an inventory-tracking system or claims approval process. The user starts by entering the name of an application, calling the data sources and then describing the application they want to build. The system comes with some sample prompts to help, but users can enter an ad hoc description if they wish. It then builds a list of requirements for the application and what it will do, based on the description. The user can refine these requirements by interacting with the generative AI. In that way, it's not unlike a lot of no-code tools that preceded it, but Devanathan says it is different. [...] Once the application is complete, it goes through a mini DevOps pipeline where it can be tested before going into production. In terms of identity, security and governance, and other requirements any enterprise would have for applications being deployed, the administrator can link to existing systems when setting up the App Studio. When it gets deployed, AWS handles all of that on the back end for the customer, based on the information entered by the admin.

Eton College, Britain's elite boarding school with alumni that includes Princes William and Harry, as well as George Orwell and a long list of others, is banning incoming students from having smartphones. Instead, the school will provide students with a Nokia "brick" phone, which will only be capable of making calls and sending text messages. CBS News reports: Parents of first-year students at Eton -- where tuition exceeds $60,000 per year -- were informed of the changes in a letter, which said that incoming 13-year-old boarders should have their smart devices taken home after their SIM cards are transferred to offline Nokia phones provided by the school, which can only make calls and send simple text messages. Eton's previous rules on smartphones required first-year students to hand over their devices overnight.

"Eton routinely reviews our mobile phone and devices policy to balance the benefits and challenges that technology brings to schools," a spokesperson for the school told CBS News on Tuesday, adding that those joining in Year 9, essentially the equivalent of freshman year in high school for American students, "will receive a 'brick' phone for use outside the school day, as well as a school-issued iPad to support academic study." The spokesperson added that "age-appropriate controls remain in place for other year groups." The ban follows a recent guidance issued by the UK government backing school principals who decide to ban smartphones during the school day. The goal is to help minimize disruption and improve classroom behavior.

A U.S. government agency tasked with supporting the nation's nuclear deterrence capability has bought access to a data tool that claims to cover more than 90 percent of the world's internet traffic, and can in some cases let users trace activity through virtual private networks, according to documents obtained by 404 Media. From the report: The documents provide more insight into the use cases and customers of so-called netflow data, which can show which server communicated with another, information that is ordinarily only available to the server's owner, or the internet service provider (ISP) handling the traffic. Other agencies that have purchased the data include the U.S. Army, NCIS, FBI, IRS, with some government clients saying it would take too long to get data from the NSA, so they bought this tool instead. In this case, the Defense Threat Reduction Agency (DTRA) says it is using the data to perform vulnerability assessments of U.S. and allied systems.

A document written by the DTRA and obtained by 404 Media says the agency "has a requirement to support ongoing assessments of the vulnerability of critical U.S. and allied national/theater mission systems, networks, architectures, infrastructures, and assets." The tool "is capable of following communications between servers, even private servers," which allows the agency to identify infrastructure used by malicious actors, the document continues. That contract was for $490,000 in 2023, according to the document. 404 Media obtained the document and others under a Freedom of Information Act (FOIA) request.

An anonymous reader quotes a report from Fortune: On February 1st last year, Montana residents gawked upwards at a large white object hovering in the sky that looked to be another moon. The airborne object was in fact a Chinese spy balloon loaded with cameras, sensors, and other high-tech surveillance equipment, and it set off a nationwide panic as it drifted across the midwestern and southern United States. How much information the balloon gathered -- if any -- remains unknown, but the threat was deemed serious enough that an F-22 U.S. Air Force jet fired a Sidewinder missile at the unmanned balloon on a February afternoon, blasting it to pieces a few miles off the coast of South Carolina. At the same time that the eyes of Americans were fixed on the Chinese intruder in the sky, around 30 cars owned by Chinese companies and equipped with cameras and geospatial mapping technology were navigating the streets of greater Los Angeles, San Francisco, and San Jose. They collected detailed videos, audio recordings, and location data on their surroundings to chart out California's roads and develop their autonomous driving algorithms.

Since 2017, self-driving cars owned by Chinese companies have traversed 1.8 million miles of California alone, according to a Fortune analysis of the state's Department of Motor Vehicles data. As part of their basic functionality, these cars capture video of their surroundings and map the state's roads to within two centimeters of precision. Companies transfer that information from the cars to data centers, where they use it to train their self-driving systems. The cars are part of a state program that allows companies developing self-driving technology -- including Google-spinoff Waymo and Amazon-owned Zoox -- to test autonomous vehicles on public roads. Among the 35 companies approved to test by the California DMV, seven are wholly or partly China-based. Five of them drove on California roads last year: WeRide, Apollo, AutoX, Pony.ai, and DiDi Research America. Some Chinese companies are approved to test in Arizona and Texas as well.

Fitted with cameras, microphones, and sophisticated sensors, self-driving cars have long raised flags among privacy advocates. Matthew Guariglia, a policy analyst at the digital rights nonprofit Electronic Frontier Foundation, called self-driving cars "rolling surveillance devices" that passively collect massive amounts of information on Americans in plain sight. In the context of national security however, the data-hungry Chinese cars have received surprisingly little scrutiny. Some experts have compared them to Chinese-owned social media site TikTok, which has been subjected to a forced divestiture or ban on U.S. soil due to fears around its data collection practices threatening national security. The years-long condemnation of TikTok at the highest levels of the U.S. government has heightened the sense of distrust between the U.S. and China.

Some Chinese self-driving car companies appear to store U.S. data in China, according to privacy policies reviewed byFortune -- a situation that experts said effectively leaves the data accessible to the Chinese government. Depending on the type of information collected by the cars, the level of precision, and the frequency at which it's collected, the data could provide a foreign adversary with a treasure trove of intelligence that could be used for everything from mass surveillance to war planning, according to security experts who spoke withFortune. And yet, despite the sensitivity of the data, officials at the state and federal agencies overseeing the self-driving car testing acknowledge that they do not currently monitor, or have any process for checking, exactly what data the Chinese vehicles are collecting and what happens to the data after it is collected. Nor do they have any additional rules or policies in place for oversight of Chinese self-driving cars versus the cars in the program operated by American or European companies. "It is literally the wild, Wild West here," said Craig Singleton, director of the China program at the Foundation for Defense of Democracies, a conservative-leaning national security think tank. "There's no one in charge."

John Timmer reports via Ars Technica: On Tuesday, the people managing the ITER experimental fusion reactor announced (PDF) that a combination of delays and altered priorities meant that its first-of-its-kind hardware wouldn't see plasma until 2036, with the full-energy deuterium-tritium fusion pushed back to 2039. The latter represents a four-year delay relative to the previous roadmap. While the former is also a delay, it's due in part to changing priorities.

ITER is an attempt to build a fusion reactor that's capable of sustaining plasmas that allow it to operate well beyond the break-even point, where the energy released by fusion reactions significantly exceeds the energy required to create the conditions that enable those reactions. It's meant to hit that milestone by scaling up a well-understood design called a tokamak. But the problem has been plagued by delays and cost overruns nearly from its start. At early stages, many of these stemmed from changes in designs necessitated by a better and improved understanding of plasmas held at extreme pressures and temperatures due to better modeling capabilities and a better understanding of the behavior of plasmas in smaller reactions.

The latest delays are due to more prosaic reasons. One of them is the product of the international nature of the collaboration, which sees individual components built by different partner organizations before assembly at the reactor site in France. The pandemic, unsurprisingly, severely disrupted the production of a lot of these components, and the project's structure meant that alternate suppliers couldn't be used (assuming alternate suppliers of one-of-a-kind hardware existed in the first place). The second problem relates to the location of the reactor in France. The country's nuclear safety regulator had concerns about the assembly of some of the components and halted construction on the reactor.

An anonymous reader quotes a report from TechCrunch: When Rodney Brooks talks about robotics and artificial intelligence, you should listen. Currently the Panasonic Professor of Robotics Emeritus at MIT, he also co-founded three key companies, including Rethink Robotics, iRobot and his current endeavor, Robust.ai. Brooks also ran the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) for a decade starting in 1997. In fact, he likes to make predictions about the future of AI and keeps a scorecard on his blog of how well he's doing. He knows what he's talking about, and he thinks maybe it's time to put the brakes on the screaming hype that is generative AI. Brooks thinks it's impressive technology, but maybe not quite as capable as many are suggesting. "I'm not saying LLMs are not important, but we have to be careful [with] how we evaluate them," he told TechCrunch.

He says the trouble with generative AI is that, while it's perfectly capable of performing a certain set of tasks, it can't do everything a human can, and humans tend to overestimate its capabilities. "When a human sees an AI system perform a task, they immediately generalize it to things that are similar and make an estimate of the competence of the AI system; not just the performance on that, but the competence around that," Brooks said. "And they're usually very over-optimistic, and that's because they use a model of a person's performance on a task." He added that the problem is that generative AI is not human or even human-like, and it's flawed to try and assign human capabilities to it. He says people see it as so capable they even want to use it for applications that don't make sense.

Brooks offers his latest company, Robust.ai, a warehouse robotics system, as an example of this. Someone suggested to him recently that it would be cool and efficient to tell his warehouse robots where to go by building an LLM for his system. In his estimation, however, this is not a reasonable use case for generative AI and would actually slow things down. It's instead much simpler to connect the robots to a stream of data coming from the warehouse management software. "When you have 10,000 orders that just came in that you have to ship in two hours, you have to optimize for that. Language is not gonna help; it's just going to slow things down," he said. "We have massive data processing and massive AI optimization techniques and planning. And that's how we get the orders completed fast." "People say, 'Oh, the large language models are gonna make robots be able to do things they couldn't do.' That's not where the problem is. The problem with being able to do stuff is about control theory and all sorts of other hardcore math optimization," he said.

"It's not useful in the warehouse to tell an individual robot to go out and get one thing for one order, but it may be useful for eldercare in homes for people to be able to say things to the robots," he said.

An anonymous reader quotes a report from Ars Technica: Temu -- the Chinese shopping app that has rapidly grown so popular in the US that even Amazon is reportedly trying to copy it -- is "dangerous malware" that's secretly monetizing a broad swath of unauthorized user data, Arkansas Attorney General Tim Griffin alleged in a lawsuit (PDF) filed Tuesday. Griffin cited research and media reports exposing Temu's allegedly nefarious design, which "purposely" allows Temu to "gain unrestricted access to a user's phone operating system, including, but not limited to, a user's camera, specific location, contacts, text messages, documents, and other applications."

"Temu is designed to make this expansive access undetected, even by sophisticated users," Griffin's complaint said. "Once installed, Temu can recompile itself and change properties, including overriding the data privacy settings users believe they have in place." Griffin fears that Temu is capable of accessing virtually all data on a person's phone, exposing both users and non-users to extreme privacy and security risks. It appears that anyone texting or emailing someone with the shopping app installed risks Temu accessing private data, Griffin's suit claimed, which Temu then allegedly monetizes by selling it to third parties, "profiting at the direct expense" of users' privacy rights. "Compounding" risks is the possibility that Temu's Chinese owners, PDD Holdings, are legally obligated to share data with the Chinese government, the lawsuit said, due to Chinese "laws that mandate secret cooperation with China's intelligence apparatus regardless of any data protection guarantees existing in the United States."

Griffin's suit cited an extensive forensic investigation into Temu by Grizzly Research -- which analyzes publicly traded companies to inform investors -- last September. In their report, Grizzly Research alleged that PDD Holdings is a "fraudulent company" and that "Temu is cleverly hidden spyware that poses an urgent security threat to United States national interests." As Griffin sees it, Temu baits users with misleading promises of discounted, quality goods, angling to get access to as much user data as possible by adding addictive features that keep users logged in, like spinning a wheel for deals. Meanwhile hundreds of complaints to the Better Business Bureau showed that Temu's goods are actually low-quality, Griffin alleged, apparently supporting his claim that Temu's end goal isn't to be the world's biggest shopping platform but to steal data. Investigators agreed, the lawsuit said, concluding "we strongly suspect that Temu is already, or intends to, illegally sell stolen data from Western country customers to sustain a business model that is otherwise doomed for failure." Seeking an injunction to stop Temu from allegedly spying on users, Griffin is hoping a jury will find that Temu's alleged practices violated the Arkansas Deceptive Trade Practices Act (ADTPA) and the Arkansas Personal Information Protection Act. If Temu loses, it could be on the hook for $10,000 per violation of the ADTPA and ordered to disgorge profits from data sales and deceptive sales on the app. In a statement to Ars, a Temu spokesperson discredited Grizzly Research's investigation and said that the company was "surprised and disappointed by the Arkansas Attorney General's Office for filing the lawsuit without any independent fact-finding."

"The allegations in the lawsuit are based on misinformation circulated online, primarily from a short-seller, and are totally unfounded," Temu's spokesperson said. "We categorically deny the allegations and will vigorously defend ourselves."

"We understand that as a new company with an innovative supply chain model, some may misunderstand us at first glance and not welcome us. We are committed to the long-term and believe that scrutiny will ultimately benefit our development. We are confident that our actions and contributions to the community will speak for themselves over time." Last year, Temu was the most downloaded app in the U.S. and has only become more popular as reports of security and privacy risks have come out.

Automated license plate readers "pose risks to public safety," argues the EFF, "that may outweigh the crimes they are attempting to address in the first place." When law enforcement uses automated license plate readers (ALPRs) to document the comings and goings of every driver on the road, regardless of a nexus to a crime, it results in gargantuan databases of sensitive information, and few agencies are equipped, staffed, or trained to harden their systems against quickly evolving cybersecurity threats. The Cybersecurity and Infrastructure Security Agency (CISA), a component of the U.S. Department of Homeland Security, released an advisory last week that should be a wake up call to the thousands of local government agencies around the country that use ALPRs to surveil the travel patterns of their residents by scanning their license plates and "fingerprinting" their vehicles. The bulletin outlines seven vulnerabilities in Motorola Solutions' Vigilant ALPRs, including missing encryption and insufficiently protected credentials...

Unlike location data a person shares with, say, GPS-based navigation app Waze, ALPRs collect and store this information without consent and there is very little a person can do to have this information purged from these systems... Because drivers don't have control over ALPR data, the onus for protecting the data lies with the police and sheriffs who operate the surveillance and the vendors that provide the technology. It's a general tenet of cybersecurity that you should not collect and retain more personal data than you are capable of protecting. Perhaps ironically, a Motorola Solutions cybersecurity specialist wrote an article in Police Chief magazine this month that public safety agencies "are often challenged when it comes to recruiting and retaining experienced cybersecurity personnel," even though "the potential for harm from external factors is substantial." That partially explains why, more than 125 law enforcement agencies reported a data breach or cyberattacks between 2012 and 2020, according to research by former EFF intern Madison Vialpando. The Motorola Solutions article claims that ransomware attacks "targeting U.S. public safety organizations increased by 142 percent" in 2023.

Yet, the temptation to "collect it all" continues to overshadow the responsibility to "protect it all." What makes the latest CISA disclosure even more outrageous is it is at least the third time in the last decade that major security vulnerabilities have been found in ALPRs... If there's one positive thing we can say about the latest Vigilant vulnerability disclosures, it's that for once a government agency identified and reported the vulnerabilities before they could do damage... The Michigan Cyber Command center found a total of seven vulnerabilities in Vigilant devices; two of which were medium severity and 5 of which were high severity vulnerabilities...

But a data breach isn't the only way that ALPR data can be leaked or abused. In 2022, an officer in the Kechi (Kansas) Police Department accessed ALPR data shared with his department by the Wichita Police Department to stalk his wife.
The article concludes that public safety agencies should "collect only the data they need for actual criminal investigations.

"They must never store more data than they adequately protect within their limited resources-or they must keep the public safe from data breaches by not collecting the data at all."

In 2022, Red Hat announced plans to extend RHEL to the automotive industry through Red Hat In-Vehicle Operating System (providing automakers with an open and functionally-safe platform). And this week Red Hat announced it achieved ISO 26262 ASIL-B certification from exida for the Linux math library (libm.so glibc) — a fundamental component of that Red Hat In-Vehicle Operating System.

From Red Hat's announcement: This milestone underscores Red Hat's pioneering role in obtaining continuous and comprehensive Safety Element out of Context certification for Linux in automotive... This certification demonstrates that the engineering of the math library components individually and as a whole meet or exceed stringent functional safety standards, ensuring substantial reliability and performance for the automotive industry. The certification of the math library is a significant milestone that strengthens the confidence in Linux as a viable platform of choice for safety related automotive applications of the future...

By working with the broader open source community, Red Hat can make use of the rigorous testing and analysis performed by Linux maintainers, collaborating across upstream communities to deliver open standards-based solutions. This approach enhances long-term maintainability and limits vendor lock-in, providing greater transparency and performance. Red Hat In-Vehicle Operating System is poised to offer a safety certified Linux-based operating system capable of concurrently supporting multiple safety and non-safety related applications in a single instance. These applications include advanced driver-assistance systems (ADAS), digital cockpit, infotainment, body control, telematics, artificial intelligence (AI) models and more. Red Hat is also working with key industry leaders to deliver pre-tested, pre-integrated software solutions, accelerating the route to market for SDV concepts.
"Red Hat is fully committed to attaining continuous and comprehensive safety certification of Linux natively for automotive applications," according to the announcement, "and has the industry's largest pool of Linux maintainers and contributors committed to this initiative..."

Or, as Network World puts it, "The phrase 'open source for the open road' is now being used to describe the inevitable fit between the character of Linux and the need for highly customizable code in all sorts of automotive equipment."

Slashdot reader DevNull127 writes: A free and open source ChatGPT clone — named LibreChat — lets its users choose which AI model to use, "to harness the capabilities of cutting-edge language models from multiple providers in a unified interface". This means LibreChat includes OpenAI's models, but also others — both open-source and closed-source — and its website promises "seamless integration" with AI services from OpenAI, Azure, Anthropic, and Google — as well as GPT-4, Gemini Vision, and many others. ("Every AI in one place," explains LibreChat's home page.) Plugins even let you make requests to DALL-E or Stable Diffusion for image generations. (LibreChat also offers a database that tracks "conversation state" — making it possible to switch to a different AI model in mid-conversation...)

Released under the MIT License, LibreChat has become "an open source success story," according to this article, representing "the passionate community that's actively creating an ecosystem of open source AI tools." And its creator, Danny Avila, says in some cases it finally lets users own their own data, "which is a dying human right, a luxury in the internet age and even more so with the age of LLM's." Avila says he was inspired by the day ChatGPT leaked the chat history of some of its users back in March of 2023 — and LibreChat is "inherently completely private". From the article:

With locally-hosted LLMs, Avila sees users finally getting "an opportunity to withhold training data from Big Tech, which many trade at the cost of convenience." In this world, LibreChat "is naturally attractive as it can run exclusively on open-source technologies, database and all, completely 'air-gapped.'" Even with remote AI services insisting they won't use transient data for training, "local models are already quite capable" Avila notes, "and will become more capable in general over time."

And they're also compatible with LibreChat...

The accounting and finance professions have long adapted to technology -- from calculators and spreadsheets to cloud computing. However, the emergence of generative AI presents both new challenges and opportunities for students looking to get ahead in the world of finance. From a report: Research last year by investment bank Evercore and Visionary Future, which incubates new ventures, highlights the workforce disruption being wreaked by generative AI. Analysing 160mn US jobs, the study reveals that service sectors such as legal and financial are highly susceptible to disruption by AI, although full job replacement is unlikely.

Instead, generative AI is expected to enhance productivity, the research concludes, particularly for those in high-value roles paying above $100,000 annually. But, for current students and graduates earning below this threshold, the challenge will be navigating these changes and identifying the skills that will be in demand in future. Generative AI is being swiftly integrated into finance and accounting, by automating specific tasks. Stuart Tait, chief technology officer for tax and legal at KPMG UK, describes it as a "game changer for tax," because it is capable of handling complex tasks beyond routine automation. "Gen AI for tax research and technical analysis will give an efficiency gain akin to moving from typewriters to word processors," he says. The tools can answer tax queries within minutes, with more than 95 per cent accuracy, Tait says.

cusco writes: Indian space startup Agnikul used a 3-D printer from German company EOS to print an engine out of inconel, a high-performance nickel-chromium alloy, in one solid piece over the course of roughly 72 hours. While other companies like Relativity Space and Rocket Lab are using 3-D printers extensively, Agnikul's engine is unique in being printed in one go, rather than as multiple components that need to be stitched together. This approach significantly speeds up manufacturing time.

The single-engine technology demonstration rocket produced 6 kilonewtons of thrust and reached an altitude of 6.5 kilometers before splashing down into the ocean. The launch vehicle used was about 6 meters tall with a single engine, making it roughly equivalent to the second stage of the company's planned commercial product, Agnibaan. Agnibaan will be a two-stage rocket, 18 meters tall, featuring eight engines in total, and capable of carrying a 300-kilogram payload to an altitude of around 700 km. The company believes that their 3D printing approach opens the door to providing low-cost, "on-demand" launch services to operators of small satellites.

IEEE Spectrum adds: Assembling the rest of the rocket and integrating the engine took roughly two weeks. The company says that opens the door to providing low-cost, "on-demand" launch services to operators of small satellites, which otherwise need to wait for a ride share on a bigger rocket. The big challenge now will be going from a single engine to a cluster of seven on Agnibaan's first stage, says cofounder and CEO Srinath Ravichandran. This raises all kinds of challenges, from balancing thrust across the engines at lift-off to managing engine plume interactions when the engines gimbal to alter the trajectory. "But these are problems that people have figured out," he says. "We believe that we should just be able to fine-tune it for our mission and go." The company is currently building facilities to carry out ground tests of engine clusters, says Ravichandran, and is targeting its first orbital launch for this time next year.