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Snotnose writes:

I suspect most of us are software engineers with our own stories of tracking down gnarly bugs. Have you ever thought of debugging other processes like, say, drug discovery? Here is the story of tracking down an impurity in a new drug

Here's a recent paper illustrating an impurity problem that I'll bet none of us out there have experienced! It describes process work on an antifungal molecule, efinaconazole, which is now available as a generic drug. The authors were checking the purity of various batches of the final product and kept noticing a small peak shouldering the desired one under LC conditions. They estimated it at about 0.06% of the samples (it showed up every time!) and eluted just a bit faster than the real drug.

This of course needed to be tracked down. The standard is generally 0.15% for a known impurity (one whose structure and properties have previously been worked out) and 0.10% for unknown ones. And this peak was getting too close to that cutoff - there were no guarantees that whatever-it-was might not come in across the threshold at some point, for some reason, and cause some real problems. Plus, just what was it anyway? Making sure of the structure could allow a switch to the 0.15% standard eventually.

Original Submission

"Arthur T Knackerbracket" writes:

https://www.theregister.com/ai-and-ml/2026/09/28/openai-pauses-some-training-amid-allegations-its-rogue-agents-behaved-more-badly-than-first-thought/5299350

The AI safety debate advanced at high speed over the weekend, amid new allegations that rogue agents have behaved more badly than first thought – and in greater numbers.

The fun started on Friday when OpenAI quietly disclosed it had paused training of its most advanced models.

The AI upstart buried that news in a "misalignment report" – that's OpenAI-speak for its reports on rogue agents. An agent used DNS to reach an external chatbot.

The good news is that the agent involved in this incident never reached the open internet.

The bad news is that the agent, which was attempting to complete a search-based training task, was able to reach the chatbot due to insufficient DNS filtering in a training sandbox. Or as OpenAI put it, "a gap in our internet-access restrictions" – which was also a problem in the Hugging Face attack.

"The incident exposed a gap in our controls over network restrictions," the report reads. "We therefore stopped the affected training run and have subsequently decided to pause all other training, evaluation, and inference with tool-use (defined broadly) for our most capable models until we have both validated that the gap is resolved and performed additional red-teaming of the system."

Also on Friday, AI startup Parse published an analysis of the Hugging Face attack that the authors claim revealed new details including that OpenAI's agent swarm gained credentials to Docker Hub and built modified versions of existing images they hoped would make it easier to complete their capture the flag mission. The agents also mapped Hugging Face's Kubernetes environment.

Friday got worse for OpenAI after the New York Times reported that its agents also "meddled with the websites for the Education Department, the Commerce Department and the Securities and Exchange Commission." OpenAI acknowledged the incidents.

The company also admitted "agents in our research environment transmitted training and evaluation data while using third-party services." That mess saw 53 user-generated images posted to image hosting sites.

OpenAI CEO Sam Altman responded by admitting that his company's investigations into rogue agents "have not been as fast as we would have liked but we are trying to balance our desire for transparency with gaining a clear understanding from petabytes of agent activity logs, and working with impacted organizations."

One of those impacted organizations is the Australian government, which last week revealed it was the target of over-eager OpenAI agents that inappropriately accessed a healthcare research data portal. Over the weekend, Australia indicated it wants Altman and Anthropic CEO Dario Amodei to appear before a Senate inquiry.

Australian leaders have softened their rhetoric on the incident, with deputy prime minister Richard Marles describing it as "minor" and akin to "climbing a fence" rather than cracking layers of security controls – perhaps because members of the opposition are suggesting that lax cybersecurity was to blame.

If Altman and Amodei do front Australia's Senate, they may face a new line of questions after Axios reported that their companies are investigating "tens of thousands" of worrying incidents.

That level of agentic misbehavior sounds like the sort of thing that regulators might consider strong evidence of products being unsafe.

Two very important people – Chinese president Xi Jinping and US president Donald Trump – seem unworried, as the AI-related result of their summit meeting last week was to establish a "China-U.S. AI Dialogue to exchange views on risks and benefits related to AI" plus "a bilateral communication channel for AI incidents."

That sounds like a hotline the two nations can use to inform each other of agentic incidents that either could see as signs of ill-intent. The two nations also decided their respective militaries will "conclude a memorandum of understanding on crisis communication and prevention as soon as possible."

China's AI giants, meanwhile, remain silent on the extent and results of any tests they have conducted with agentic tools.

Original Submission

looorg writes:

I spy with my many cameras a face. A six month project. Millions of scanned faces. Nobody on any watch list found. Are the crooks to smarts to be caught on camera or don't they ride the tube?

Solution? Extend the scope of the project for a longer time period and include more stations.

A six-month trial of live facial recognition (LFR) technology in London's railway stations that cost more than £320,000 and almost 100 hours of police officers' time led to one false match against a watchlist of suspects and no arrests.

More than half a million faces were scanned between February and July this year in some of the capital's busiest transport hubs during the British Transport Police (BTP) trial of the surveillance technology, which aimed to help catch offenders and people breaching court orders.

They added: "During these deployments, officers have made a number of associated arrests, including for assault, theft, possession of an offensive weapon, breach of a criminal behaviour order and public order offences, as well as locating individuals wanted by the courts and other police forces. As these arrests did not result directly from an LFR alert, they are not included within LFR performance data.

Or there are hidden side effects that they failed to include. It wasn't the purpose. But they found a purpose.

Still the question should perhaps be asked -- worthwhile project or waste of money?

https://www.theguardian.com/technology/2026/sep/29/trial-live-facial-recognition-cameras-london-stations-false-positive

Original Submission

fliptop writes:

BMW announced Wednesday it planned to slash its management structure by 20% while expanding the use of artificial intelligence across its operations:

The luxury carmaker said it will reduce the number of divisions and associated management roles by 20% by mid-2027, with comparable reductions at lower organizational levels. BMW said AI will play a central role in making the company more efficient, speeding up decision-making and automating routine work across development, manufacturing, purchasing, sales and other operations.

The restructuring comes as BMW faces weak European demand, growing competition from Chinese automakers and U.S. tariffs, while its shares have fallen more than 30% over the past year, according to Reuters. The automaker is also seeking to restore its automotive operating margin after it fell to roughly 2.3% in its latest results.

"Consistent use of agentic AI applications across all areas of the company will be a game-changer for more agile and efficient development, leaner structures and faster decision-making," BMW finance chief Walter Mertl said.

[...] The company already uses AI throughout its factories for digital twins, quality inspections and autonomous transportation systems and plans to have digital AI agents perform increasingly challenging tasks autonomously.

Related:

• Laid-Off Developers Create AI Model to Replace CEOs and Other Executives
• AI Agents Meant To Replace Meta Workers Made "Large-Scale, Disruptive Actions"
• GM Replaces Over 1,000 Detroit Workers With Just 50 Robots
• Microsoft Pushes Out Experienced American Talent to Fuel AI Ambitions

Original Submission

"Arthur T Knackerbracket" writes:

https://www.slashgear.com/2272902/uk-traffic-camera-ghost-license-plate-detection/

Fabricating or altering license plates can help drivers become untraceable in the system, allowing them to get away with otherwise law-breaking activities. With over 14,000 cameras in the UK's automatic number plate recognition (ANPR) system, drivers attempting to evade detection, whether for illegal activities or to get away with reckless driving, have been using special plates — also known as ghost plates — that make registration numbers unreadable to these AI-powered data-collecting systems.

U.K. law enforcement has been fighting ghost plates for a while now — and a new camera could be the answer. A new camera from ANPR tech firm MAV Systems can allegedly detect and identify ghost plates by using AI to analyze the plates' infrared and color images. Tests have been positive, with U.K. police detecting anywhere between a few hundred and a few thousand ghost plates a day in some heavily trafficked areas. Some of these tests have gone on for nearly two years as of September 2026, suggesting the system works.

At a glance, ghost plates look very much like your everyday license plates. They even have the correct details for the vehicle they're on, so they appear legal to passing police officers. However, ghost plates use reflective plastic that makes them nearly impossible for ANPR cameras to read.

These ghost plates aren't some black-market product, either. U.K. drivers can purchase them from many of the 30,000-plus businesses registered with the UK's Driver and Vehicle Licensing Agency (DVLA). That means drivers are buying legally supplied plates instead of getting them from a shady back-alley operation. In its report, the BBC found that some of these businesses openly offered ghost plates to help evade cameras without even requiring proof of ID or vehicle registration. To combat this, U.K. police want tighter regulation for license plate issuers — right now, all you need to do is fill out a quick form and pay a fee.

Ghost plates aren't unique to the U.K., of course. In New York City, for example, drivers have used ghost plates to avoid highway tolls. They're also not the only way drivers try to evade cameras; other methods include illegal plate flippers that obscure plates from police and cameras.

Original Submission

An Anonymous Coward writes:

Not so long ago Australians suffered a great loss, in an event so significant the shockwaves are still felt today. Neighbours was cancelled. For those who have been living under a rock without even dialup for the last fourty years, Neighbours is an award winning classic Australian TV soap in the same vein of Eastenders or Cheers. Now, with the power of AI and Margot Robbie, Neighbours is back powered by AI. What can we expect next? Dead actors returning? Rule 63 and Rule 64 in all their glory? With amateurs making their own Star Trek Episodes the possibilities are endless for anyone looking to remake old episodes or perhaps continue or just make a much better ending to a series.

[...] The short-form Neighbours episodes will focus on specific plot points and storylines rather than the traditional approach of multiple intersecting narratives, with the first episodes to feature former soap star Margot Robbie in her role as schoolgirl Donna Freedman.

[...] It's all thanks to Roseberry's AI technology Redsnapper, which scrapes Neighbours' massive catalogue of episodes to isolate character arcs and streamline them into short-form episodes.

Original Submission

"Arthur T Knackerbracket" writes:

The DHS will use Google's AI tools to recommend information to be blacked out of FOIA requests:

Document redactions have been in the spotlight lately thanks to the US Justice Department's Epstein file release, which used it to black out text in millions of documents. Now, the government plans to use AI to handle that redaction chore for Freedom of Information Act (FOIA) requests, according to GitHub documents seen by The Washington Post.

Those documents state that US Customs and Border Protection, part of the Department of Homeland Security, will use Google's AI tools to recommend information that FOIA officers should redact. By the end of September, the DHS will use AI for documents that make up over 10 percent of FOIA requests, around 100,000 to 140,000 in all.

Following those recommendations, DHS employees will review the cases to ensure the requester gets what the document calls "accurate and complete" information, an interesting term considering the potential redaction. "[T]his automation is expected to significantly reduce processing times," the description states.

As part of its research, the Post discovered redaction-related AI tools in use or development by other agencies. The Interior Department uses Microsoft tools to redact potential attorney-client information, while the DoJ is using a Veriton tool called aiWARE to redact video. The Health and Human Services division (HHS) is developing its own tool, FRED, to redact unknown information. "FDA is responsibly exploring limited uses of AI to help FOIA staff process records more efficiently," a spokesperson told the Post.

Though the government is touting the tools as a way to save time, it could lead to even more blacked-out or missing documents. "I think we have to watch the government really carefully on how they use AI to redact records, because I think it's going to be a very powerful tool for secrecy," a FOIA expert at the University of Florida told The Washington Post.

Original Submission

"Arthur T Knackerbracket" writes:

Active-duty campaign targeted at least ten organizations and sought $1 million in ransom payments:

A former US Army soldier has been sentenced to 70 months in prison for hacking telecoms companies, stealing sensitive records, and trying to extort more than $1 million from his victims.

Cameron John Wagenius, 22, carried out the campaign while serving on active duty. He pleaded guilty in March 2025 to unlawfully transferring confidential phone records, then admitted conspiracy to commit wire fraud, computer-related extortion, and aggravated identity theft in a separate case that July.

Court documents say Wagenius conspired with three others to obtain credentials for the protected networks of at least ten organizations between April 2023 and December 2024. During that period, he was stationed in South Korea and Texas.

The Justice Department has not publicly identified the victims, describing them as US and overseas telecommunications companies and other organizations.

Wagenius has also been linked to the 2024 Snowflake extortion campaign, which affected AT&T, Verizon, and numerous other companies, as The Register previously reported.

After two suspects were arrested in connection with the Snowflake attacks, an account controlled by Wagenius claimed to possess AT&T call records belonging to Donald Trump and Kamala Harris.

Using online aliases including "kiberphant0m," Wagenius and his co-conspirators obtained login credentials with a hacking tool he helped develop called SSH Brute, among other methods. They exchanged stolen credentials in Telegram group chats and discussed using them to gain unauthorized access to other parts of victims' networks.

Court documents say the group traded hundreds of credentials and stole hundreds of thousands of customer records from multiple companies.

Wagenius and his accomplices advertised stolen data through XSS, BreachForums, X, and Telegram.

Some posts offered the information for sale, while others threatened to publish it unless victims paid. The Justice Department said the conspirators attempted to extort at least $1 million in total, successfully sold some stolen data, and used other records to commit fraud, including SIM swapping.

US District Judge Lauren King told Wagenius at sentencing: "Your actions show a shocking disregard for the safety and security of the United States... You took these actions motivated by greed and a desire for notoriety."

Wagenius was also ordered to pay $294,978 in restitution.

Original Submission

owl writes:

Ethernet ports are still desirable on desktop PCs, hanging on alongside the likes of the 3.5mm audio jack and IEC mains connector:

On this day [September 30] in 1980, version 1.0 of the Ethernet specification was published by Digital Equipment Corporation (DEC), Intel, and Xerox. This 'DIX' standard was established at a time still nearly three years before the modern internet existed. Nevertheless, Ethernet would become the default technology for connecting computers to each other in local networks – and all around the world. However, we must point out that Ethernet had existed in experimental form at Xerox PARC in the 1970s.

Before Ethernet, computer manufacturers were wary of building LAN connectivity into their computers. It seemed wasteful to integrate one type of network adapter that wouldn't always work with other networked computers and equipment an organization might use. To foster the adoption of Ethernet industrywide, DIX allowed any vendor to use the specification in their own hardware implementations.

Ethernet has been adjusted, refined, and improved over time to remain competitive and relevant. In 1980, it arrived using coaxial cable wiring and with a top speed of 10 Mbps. Five years later, it would move to adapters with BNC connectors. The first RJ45 implementation, a connector that still identifies Ethernet ports to this day, was in 1990 alongside the introduction of 10BASE-T twisted-pair cabling (but still at 10 Mbps).

Original Submission

"Arthur T Knackerbracket" writes:

Posts huge leaps in revenue, profit, and margin, with more to come:

Memory-maker Micron has warned that RAM shortages will persist into 2028, and perhaps beyond.

Speaking on the company's FY 2026 earnings call, CEO and company chair Sanjay Mehrotra reminded investors that Micron has already sold most of the memory it will make next year and said customers will pay "much higher prices" than they shelled out this year.

"In calendar 2027 as well as 2028, we see demand exceeding supply," he added. "In fact, we see greater tightness in the industry in 2027 and in 2028 versus 2026. Overall, supply-demand environment is only getting tighter."

"We do not have line of sight to when supply and demand will return to balance."

Micron plans to bring new factories online in 2028 – helped by planned capex of $25 billion in the first half of its new financial year – but execs warned those facilities won't immediately help to improve availability or ease prices.

The CEO said demand for the high-bandwidth memory (HBM) needed in AI hardware is growing faster than it is for the DRAM used in servers. Micron is also finding ways to expand its margins for HBM, which is currently not as profitable as DRAM.

Both types of memory are, however, enormously profitable.

Original Submission

"Arthur T Knackerbracket" writes:

https://www.slashgear.com/2269817/tesla-zet-scale-us-class-8-semi-truck-deal/

Tesla announced its electric semi-truck back in 2017, but deliveries to its first customers are just about to start nearly a decade later in September 2026. On September 24th, Tesla held a launch event for the Semi at its manufacturing plant in Nevada, where it plans to build 50,000 Semis a year. It may seem like a lofty goal, but Tesla CEO Elon Musk said in a pre-recorded video message that there is already a big waiting list for the Semi. At $290,000 for a Long Range Semi, it's predicted that Tesla will deliver 15,000 in 2026 at most.

One of those early customers includes Zero-Emission Truck Shipper-Carrier Alliance Leading Electrification (ZET SCALE), a shipper alliance with brands like Microsoft and PepsiCo that reportedly ordered 2,500 of the electric semis — the largest electric Class 8 order ever made in the U.S. Tesla's announcement made it sound as if it was providing all 2,500 of the trucks, but it's just the primary supplier along with other brands. The fleet of 2,500 electric trucks will be deployed in Los Angeles, Houston, Dallas, New York, Atlanta, and other freight hubs over the next few years.

Said Dan Priestley, Director for the Tesla Semi Program: "We are proud to have been the primary selection in this RFP and look forward to giving shippers and carriers a new competitive edge."

The Semi has a pretty typical history, as far as Tesla goes. Musk announced the vehicle in 2017 and had lofty goals of launching it in 2019, claiming it would be cheap to operate, carry a full load, and reach 500 miles on a single charge. At the time, experts responded that this was nearly impossible to pull off due to technology limitations. Tesla continued to miss various launch dates, eventually shipping some early examples to PepsiCo in 2022. Next year's launch date was also missed, although brands like Walmart, Costco, and the NFL were given one Semi to test. Those have now been used for over 5 million miles.

If that timeline sounds familiar, it's likely because the second-generation Roadster was announced in 2017, delayed multiple times, and is finally getting a reveal October 2026. The Cybercab was revealed in 2024, Musk claimed 2 million would be produced a year, and as of 2026, there are only 69 active Cybercabs besting tested in a few cities.

"This is going to be a revolutionary truck that's capable of carrying the heaviest loads over very far distances," Musk stated ahead of the launch event. He also added that it will be the "funnest truck to drive" due to its fast acceleration, which echoes previous statements, noting it will get Full Self-Driving in the future. There will be a Standard Range Semi that has 350 miles and a Long Range that gets 500 miles.

These are also claims that drivers should remain skeptical about. The Cybertruck was originally said to have a 500-mile range when it was revealed, but the reality is less than 300 miles. No comment on Musk's claim that the Cybertruck could act as a boat.

Original Submission

owl writes:

https://dfarq.homeip.net/first-dvd-player-announced-sept-26-1996/

On September 26, 1996, Toshiba announced the first DVD player, the Toshiba SD-3000. It was released in Japan in November 1996 and initially cost ¥77,000, equivalent to about $770 US. It was the first consumer DVD player in the world, and of course, DVD became the successor to VHS. Ironically, the first DVD player was announced very close to 20 years after the first VHS VCR.

Problems with VHS

VHS had a good run, and in 1996 it still had about a decade left, but it was showing its age. It didn't record at the full resolution of either NTSC or PAL video. Arguably in 1976 few people noticed because screens were comparatively small and the VCR connected over RF, causing signal degradation anyway. But by 1996, TV tubes were higher quality, most TVs had at least composite connections and many had higher-quality connections like S-Video or even component video.

Original Submission

looorg writes:

Six Flags announced Tuesday it will permanently shutter its most famous roller coaster, ... investigation exposed a long history of life-altering injuries and deaths linked to the ride.

Six Flags Magic Mountain President Brian Oerding wrote in a blog post Tuesday that while its X2 roller coaster has "consistently passed a multitude of safety tests, we have decided to close the ride because we believe it's the right thing to do."

... more than 100 new victims have come forward alleging X2-related brain injuries of varying severity sustained after riding the roller coaster in the last two years alone.

Hawley, who died from a traumatic brain injury hours after riding X2 four years ago

So did you ride the X2? Was it fun? Or a death-trap?

https://edition.cnn.com/2026/09/29/us/six-flags-roller-coaster-x2-invs

Original Submission

"Arthur T Knackerbracket" writes:

https://www.siliconrepublic.com/innovation/brain-stimulation-impact-develop-new-skills-research-innovation

Ned Jenkinson of the University of Birmingham and Matthew Weightman of the University of Oxford discuss how advancements in brain research might affect how we learn and grow our skillsets.

Whether learning a new piano piece or adapting your tennis serve, acquiring physical skills depends on your brain’s ability to strengthen and refine neural connections. Researchers are exploring whether this process can be accelerated with technology.

Scientists are particularly interested in the potential of non-invasive brain stimulation, a group of techniques that can alter brain activity without surgery.

Some deliver weak electrical currents to the brain through electrodes placed on the scalp. Others use magnetic fields or focused ultrasound waves. Although they work in different ways, they all aim to temporarily change the activity of neural circuits.

If these techniques can successfully enhance neuroplasticity, the brain’s ability to reorganise and form new connections during learning, then they could be of use anywhere where performance depends on learning complex movements, from sport and music to surgery and beyond. Researchers are also seeing if these technologies could help with learning non-physical skills, such as picking up a foreign language.

Elite sport, professional gaming and high-performance workplaces could all become targets for these enhancements if they prove effective. Brain stimulation could also have a big role to play in medicine, helping patients recover physical skills lost through injury or disease, such as stroke.

Studies suggest there’s a lot of potential here. But translating this potential into useful tech that reliably boosts learning physical skills remains a big challenge.

Research into enhancing motor learning with electric or magnetic stimulation has been gaining momentum since the turn of the millennium, with early studies garnering considerable excitement.

In a typical experiment, participants might learn a sequence of finger movements similar to practising scales on a piano while receiving stimulation over brain regions involved in movement. Other studies have examined how stimulation could be used for balance training or teaching sports-related skills or surgical techniques.

Some of these experiments produced eye-catching results, finding that participants learned certain movement tasks faster or retained skills for longer if they underwent brain stimulation. But other studies failed to find benefits. And in some cases, researchers struggled to replicate the success of earlier promising experiments when repeating them.

One reason for these mixed findings is that there’s no such thing as a universal ‘learning network’ in our brains. Different skills rely on different combinations of areas near the surface of the brain as well as those deep within it.

Additionally, people can respond very differently to the same stimulation. Factors such as age, anatomy, genetics and even baseline skill level may influence whether stimulation is beneficial. Add to that the infinite number of ways to apply stimulation, the picture becomes murkier.

"Arthur T Knackerbracket" writes:

NASA isn't saying much. The problem may be temporary:

Recently, the astronauts on board the International Space Station performed a routine "walk-off" maneuver with the large, 58-foot-long robotic arm attached to the orbiting laboratory.

The robotic arm, known as Canadarm2 because it was supplied by the Canadian Space Agency, is something of a modern engineering miracle—it can effectively move around the exterior of the large space station like an inchworm because both ends are essentially identical.

However, after this particular walk-off maneuver, the robotic arm, along with the mobile transporter that guides it along the main truss of the space station, engineers noted some issues with operations.

As of Sunday evening, according to two sources, work was underway to determine whether this problem was due to a data or software issue or the robotic arm or mobile transporter hardware itself. (Update: NASA provided the following statement at 2 pm ET on Monday).

The Canadarm2 is currently operating as expected and is being used for inspection of the Crew-12 Dragon spacecraft as part of predeparture procedures. Non-robotic components associated with the mobile transporter on the truss, which the arm is often attached to, have exhibited some communication errors. NASA is troubleshooting and investigating the errors prior to the next transporter movement from its current worksite (Worksite 6). In parallel, NASA and SpaceX are working to ensure there is no GPS interference affecting Dragon's docking capability to the station's forward port as a result of the transporter's current position. Joint teams are actively conducting the analysis and expect to resolve the issue before the Crew-13 launch. NASA will provide additional updates during the Crew-13 prelaunch news conference on Wednesday, Sept. 30.

Designed and developed by the Canadian space corporation MDA, the Canadarm2 launched to the International Space Station in April 2001 on Space Shuttle Endeavour, and it has since served as a critical component of the orbiting laboratory. Its nominal design lifetime was 15 years, so it has been operating for more than a decade beyond this point.

The arm has a mass of nearly two metric tons and can handle payloads of up to 116 tons.