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Scotland's public prosecution service has warned 300 staff that their personal information may have been caught up in a cyberattack on one of its suppliers. The Crown Office and Procurator Fiscal Service (COPFS) disclosed the incident on Thursday, saying an unnamed third-party supplier detected suspicious activity on August 5 and subsequently launched an investigation. COPFS said its own systems were not compromised and that the incident involves information provided for an online data maturity assessment completed by the prosecution service last year. The Scottish government organized the assessment, which was managed by the affected supplier. COPFS said the potentially exposed information is limited to employment-related data submitted for the exercise, including staff names, roles, and work email addresses. In a statement to The Register, a COPFS spokesperson said: "COPFS is aware that a Scottish Government partner has been subject to a data security breach. We understand that this has affected around 300 COPFS colleagues who participated in a public sector data maturity survey. "This is unconnected to casework and did not involve sensitive or confidential case information. There is no impact on the work of the prosecution service. "Colleagues have been reminded of guidance on responding to any phishing or scam attempts which may arise from this third-party breach." According to COPFS, the supplier has taken steps to secure its systems and is still investigating how the intrusion happened and precisely what information may have been accessed. COPFS said it would provide further updates if "significant new information" emerges. It is unclear whether the incident is connected to the recent exploitation of a zero-day vulnerability in business intelligence platform Metabase. The Scottish government did not answer our question about whether the affected supplier used the software. Metabase disclosed this month that attackers had exploited a previously unknown vulnerability in its cloud service, potentially allowing them to gain administrator access and reach connected databases. As we reported earlier this week, modular laptop maker Framework was among those affected. For now, the supplier breach leaves plenty of questions and few answers about who got in or what they accessed. ®

**ChatGPT si nově může pamatovat, co jste dělali na počítači. **Funkce Computer History sleduje aktivitu v aplikacích a na webech. **Díky tomu dokáže lépe navázat na vaši práci.

ChatGPT si nově může pamatovat, co jste dělali na počítači. • Funkce Computer History sleduje aktivitu v aplikacích a na webech. • Díky tomu dokáže lépe navázat na vaši práci.

A former data analyst contractor for Brightly Software has been sentenced to two years in prison for targeting his employer in a $2.5 million extortion scheme. [...]

Po zvyšování cen DRAM, NAND Flash / SSD, mechanických pevných disků, grafických karet, zdrojů i licencí Windows 11, rostou i ceny monitorů…

The China-linked threat actor known as Jewelbug has been observed carrying out cyber espionage operations targeting governments and militaries, while simultaneously engaging in cryptocurrency fraud. "Both missions are administered from a single control panel, XG-Web, a browser-centric remote-access and information-stealing framework that turns a victim's browser into a full remote-control Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

Qualcomm upřesnil specifikace nového čipu Snapdragon C, který představil letos v květnu a kterým chce proniknout do lowendových pater počítačů – desktopů i notebooků. Stále ještě neznáme datum uvedení takových strojů, ale nabízí se září, kdy by mohli výrobci prezentovat nová PC na berlínském ...

Nákladní Boeing 737 se patrně po poruše navigace zřítil do Arabského moře • Černé skříňky leží v hloubce tři tisíce metrů a nejspíš už nevysílají signál • Vyšetřovatelé nevydali předběžnou zprávu a příčina nehody zůstává neznámá

O procesorech Diamond Rapids se mluví již šest let. Jejich architektura i výbava se však opakovaně nejednou měnila a dlouho to vypadalo, že půjde o 256 jader Panther Cove, z nichž bude aktivních 192…

Na všech herních platformách je každou chvíli nějaká slevová akce. Každý týden proto vybíráme ty nejatraktivnější, které by vám neměly uniknout. Pokud chcete získat hry zdarma nebo s výhodnou slevou, podívejte se na aktuální přehled akcí!

New Zealand’s Security Intelligence Service (NZSIS) has claimed Chinese companies are building space facilities in the nation to gather military intelligence. Director-general of security Andrew Hampton yesterday made that allegation in the SIS’s annual threat environment assessment. The document points out that New Zealand’s space sector is booming, because the nation’s location makes it “an ideal place to install Ground Based Space Infrastructure (GBSI) … to track satellites and space debris, as well as for collecting a range of other scientific data.” The NZSIS has also found that GBSI is “attractive for foreign states seeking to advance military capabilities and intelligence operations.” The report offers a case study of a China-based organization called “Purple Mountain Observatory” that has “close links” to Beijing and tried to install GBSI in New Zealand. “They worked with a local company that was likely unaware of the equipment’s capability to collect intelligence of military value and would have no idea who was receiving the data,” the report states, before noting that Chinese laws mean Purple Mountain could be compelled to provide information to China’s government. The intelligence agency believes Purple Mountain “would have … willingly passed on” data it collected. “NZSIS, working with other agencies was able to disrupt this activity, but it was not the first time this organisation has attempted to install its own GBSI in New Zealand and is unlikely to be the last.” The report rates China as the only country targeting New Zealand at scale, based on activity NZSIS has been able to observe. “We have observed increased targeting of professional networking sites and online job platforms for espionage purposes by China’s military intelligence services,” the assessment finds. "PRC (People’s Republic of China) intelligence officers, or their affiliates, use an aggressive strategy where they pose as consultants or employees of think tanks, or recruitment firms. They place online job advertisements looking for analysts in foreign policy, international relations, defence or security,” the document states. “Candidates are then vetted by PRC intelligence to determine what information they have had access to and whether they would divulge it. The job offers are lucrative, but the intelligence officers often encourage their candidates to keep their government jobs both to keep the information tap running and to open up opportunities to recruit their colleagues.” The report also observes that some recent cyber-attacks were probably the work of state-backed groups trying to destabilize New Zealand. “Looking for the sharpest needle in endless giant stacks of needles” The document also addresses domestic threats, especially violent extremism. “Part of our job is to work out whether someone’s vitriolic and violent online pronouncements have any link to New Zealand,” the report states. “This is a narrow focus but the pool of information and intelligence we are working with is vast.” “We used to describe our work as finding a needle in a haystack. However, the internet has changed. Large volumes of toxic content, widespread anonymity, and hidden locations mean our job is now like looking for the sharpest needle in endless giant stacks of needles.” “Extremist rhetoric, particularly online, has become more mainstream, a development which has made it even more challenging to differentiate between genuine support for violent extremism, hateful language designed to shock, or online content created simply to drive engagement or ‘likes’.” NZSIS also has to keep an eye on encrypted messaging services and even gaming platforms, to counter violent online communities. “Algorithms on various social media platforms can link non-violent content to progressively more extreme material,” the report states. “The gateway subject matter can quickly expose people to violent extremist content that can support radicalisation.” Kiwis aren’t just recipients of this vile material. “NZSIS has observed New Zealand violent extremists use encrypted messaging systems, social media and online gaming platforms to circulate violent material including weapon tutorials and objectionable content. Their presence on these platforms, many of which are mainstream, also helps them to find like-minded individuals or supporters.” ® Bootnote: Readers interested in New Zealand’s intelligence services might enjoy 2026 comedy series New Zealand Spy, a deadpan delight.

One of AI vendor DeepSeek’s biggest selling points has been its ultra-low price point, but that party’s about to end.

The Chinese model provider is raising API pricing for its V4 model family by notable margins, in some cases by more than 1,100%. The increases may not be that dramatic for all, though; the company is encouraging “more flexible workload scheduling,” with peak rates and half-price off-peak rates.

The news was tucked into the announcement of the general availability (GA) of DeepSeek V4-Pro and upgrades to VR-Flash. The new pricing takes effect for most parts of the world on August 16.

“On paper, at peak, against the right comparator, DeepSeek’s price advantage does disappear, and in places inverts,” said Sanchit Vir Gogia, chief analyst at Greyhound Research. But in practice, “the schedule’s own clock and cache hand most of it back to any buyer paying attention.”

How Flash and Pro compare now

The new API pricing structure is as follows:

• Flash is now $0.22 per million input tokens (cache miss) and $0.66 per million output tokens off-peak; and $0.44 per million input tokens (cache miss) and $1.32 per million output tokens at peak.
  This is up from the flat rate of $0.14 for inputs (cache miss), representing a 57% to 214% increase, and $0.28 per million tokens for outputs, a 136% to 371% increase.
•  Pro is now $0.66 per million input tokens (cache miss) and $1.98 per million output tokens off-peak; and $1.32 per million input tokens (cache miss) and $3.96 per million output tokens at peak.
  This represents an input increase of between 51% and 203% (up from $0.435) and output increase between 127% and 355% (up from $0.87).

Inputs with cache hits, when apps reuse stored prompts rather than processing similar requests from scratch, have even more dramatic pricing increases of 52% to 1,100%.

Mark Tauschek, VP of research fellowships and distinguished analyst at Info-Tech Research Group, pointed out that the increase does eliminate the price advantage that 4.0 Flash has over OpenAI 5.6 Luna at peak pricing, but not at off-peak pricing, as OpenAI has dropped Luna API pricing by 80%, off-peak.

It also doesn’t eliminate Deepseek 4.0 Pro’s price advantage over Terra, OpenAI’s GPT-5.6 mid-tier reasoning model, even at peak pricing, nor its advantage over GPT-5.6 Sol released in July, Tauschek said.

Greyhound Research’s Gogia noted that, off-peak, V4 Flash is “marginally more expensive” on input and 45% cheaper on output than Luna. Pro at peak, meanwhile, runs close to 5x Luna’s price on a representative coding-agent workload.

DeepSeek’s roughly 98% cache-hit discount, against an industry norm nearer to 90%, is the mechanism that has kept its measured cost per task at about 60% below Luna, even after Luna’s cost cut, he said.

“The schedule re-prices exactly that mechanism,” Gogia said. Flash’s edge over Luna decreases from roughly sevenfold to threefold off-peak, and 1.4 times at peak. “The cache is where the advantage genuinely erodes.”

Encouraging users to rethink their schedules

DeepSeek’s V4-Pro is now generally available, and V4-Flash is in beta. Both models have new flexible reasoning capabilities (low, high, max) and ‘thinking modes’ that use chain-of-thought (CoT) reasoning to improve answer accuracy. V4 Pro is now available on app, web, and via API, and users can try it using “Expert Mode.” V4 Flash is now in beta.

The general availability “completes a two-tier structure in which Flash serves volume and Pro is priced for complexity,” Gogia noted.

DeepSeek’s peak/off-peak pricing is a means to “allocate resources more reasonably,” the company said, to encourage users to “schedule their tasks based on actual usage.”

Gogia pointed out that with the new model, 17 of every 24 hours stay at half price, so timing becomes an economic variable, and work that can wait moves into the cheap hours. In fact, the new pricing schedule hits DeepSeek’s home market hardest and its export market lightest; Western buyers largely pay the off-peak rates.

“Usage is following economics at least as much as capability, and economics can change by schedule,” Gogia noted.

Simple supply and demand

Reading between the lines provides a more nuanced picture, Tauschek noted. “While it’s alarming to see the headlines saying DeepSeek is raising API pricing by 50%-1100%, it doesn’t really tell the whole story.”

Part of that story is demand, which is increasing exponentially. DeepSeek can’t keep up with compute requirements, and Anthropic also had a price increase for the same reason in April. And, while third-party providers have not yet reflected that trend, they’ll eventually have to, Tauschek said.

“This isn’t unexpected at all,” he noted. “It’s simple supply and demand: when demand goes up, pricing goes up, because supply becomes constrained.”

For enterprises that do use DeepSeek (many in the US do not, or can not), the new pricing is not likely to change anything, he said. Cost increases will mostly impact developers, but it will still be less expensive than most alternatives.

He pointed out that enterprises are adapting to model routing, which is critical for developers using agentic workloads. Just a few months ago, organizations were paying per-seat pricing and running up usage as a matter of course, but the market move to usage-based pricing has resulted in sticker shock akin to that of the early cloud days.

“Pricing will continue to be a big deal because CFOs are starting to ask what they’re getting for the massive AI spend,” Tauschek said.

DeepSeek pricing doesn’t change the need for compatibility, multi-modality

CIOs should read the schedule with “relief and unease,” Gogia noted. Relief because the bill is largely schedulable; unease because “a supplier that has learned to price the clock has learned something about its own leverage.”

Going forward, he predicted, Flash keeps the volume usage, Pro handles complexity, and interface compatibility lowers the cost of adoption and departure. The real question becomes whether lower economic floors, open weights, and compatible interfaces, when taken together with multi-model routing, make foundation model intelligence materially easier to substitute.

Capable inference can be produced “far below the price structures that once surrounded frontier AI,” Gogia noted, and open weights mean model developers become one of just several parties able to serve inference requirements. “The traditional software dependency changes shape when that happens,” he said.

The vendor still matters, as do capability and support, but once a workload can move between providers, and enterprises manage their own orchestration and governance, the vendor no longer owns the whole dependency, Gogia said.

The most lasting effect of DeepSeek is unlikely to be that it stayed cheapest, he noted. “It is that every provider must now explain why intelligence should command a premium once near-equivalent capability is available through several technical and commercial routes.”

This article originally appeared on InfoWorld.

NVIDIA na konci ledna vydala v beta verzi nativního linuxového klienta své cloudové herní služby GeForce NOW. Včera oznámila ukončení beta verze a oficiální podporu Linuxu.

You're not alone if you just received an "Apple Threat Notification" saying it detected a "mercenary spyware attack targeted at your iPhone." [...]

Sugar damage in the body was thought to be irreversible. But the new enzyme made 75-year-old tissue look chemically like a 30-year-old’s.

The scent of fresh bread straight from the oven is intoxicating. As sugars and proteins react under heat, they create compounds that give golden-brown crusts their rich aroma. Called advanced glycation end products (AGEs), these molecules also form inside us. Our bodies are essentially ovens running at around 98 degrees Fahrenheit, and AGEs slowly build up over decades. They stiffen bouncy, elastic tissues and trigger lasting inflammation.

One of the hallmarks of aging, AGEs drive a range of age-related problems, increasing the risk of heart disease, diabetes, and eye and kidney troubles. In theory, clearing them out could turn back the clock. But previous attempts have failed, leading some scientists to suspect that the damage is irreversible. Once AGEs form, they stay.

Or maybe not.

A team at Revel Pharmaceuticals in San Francisco and colleagues took a new approach: They designed a synthetic version of an enzyme found inside microbes that targeted the most abundant type of AGE in several human tissues. In tissue from a 75-year-old donor, the enzyme reduced AGE levels to those seen in a 30-year-old, potentially giving the cells and their surrounding scaffold a chance to repair and rebuild.

“This work establishes that damage to aging proteins previously thought to be irreversible can be repaired,” wrote the team. Study author and Revel CEO Aaron Cravens added in a press release: “More work is needed, but these results alter the starting assumption for how we think about this fundamental aspect of the aging process.”

Rusting Away

AGEs are often nicknamed the body’s rust. They coat structural proteins, and like rust eating away at a car, gradually damage them. Scientists discovered AGEs in the 1980s and have sought ways to scrub them away ever since.

Most aging research has focused on keeping cells healthy. The scaffolding surrounding those cells has received far less attention, even though it makes up roughly 70 percent of the body. These structural materials are especially long-lived. It takes the body 15 years to replace half of its collagen, for example. That longevity comes with a price. The longer these proteins stick around, the more likely they’ll incur damage from accumulating AGEs. The result isn’t just loose skin, weakened tendons, and creaky joints. The heart, kidneys, brain, and eyes also suffer.

Scientists have developed drugs to intervene. Some are able to stop new AGEs from forming but fail to clear those already embedded in tissue or restore damaged proteins. Attempts to develop enzymes that could cut them apart have also been unsuccessful, largely because there aren’t obvious natural enzymes in the body to use as a starting point for protein engineering.

The authors of the new study looked outside the body, starting with an unusual idea. Human remains, including AGE-laden proteins, are eventually decomposed by microbes. The team reasoned these bugs may harbor enzymes that can be engineered to clean up the molecular debris while we’re still alive.

Needle in a Haystack

For the search, the team focused on CML, the most abundant type of AGE.

CML is both notoriously stubborn and detrimental to our health. It triggers cells to release inflammatory molecules that stiffen tissues and damage microglia, the brain’s immune cell guardians, contributing to cognitive decline during aging.

“We believe you can remove [CML damage] enzymatically, by going in and developing these lawnmower enzymes that can just cut and clip these changes off of the proteins,” Cravens told The Scientist.

The team screened DNA sequences from over 50,000 microbes with AI and predicted the structures of the enzymes they encoded. They narrowed the candidates by looking for those capable of reaching CML buried within larger proteins like collagen. The winner came from a type of bacteria that thrives in geothermal hot springs.

The enzyme could cleave CML molecules, but barely. To boost its effectiveness, the team turned to directed evolution, a Nobel Prize-winning technique that mimics natural evolution at breakneck speed. After five evolutionary rounds and more than 500 million variants, they landed on CMLase, an engineered enzyme over 10 times more efficient than its ancestor.

To test its activity, the team created CML-laden versions of several proteins, including collagen, retinal proteins, and hemoglobin, which carries oxygen in blood. Initial test-tube experiments showed the enzyme worked as expected. It stripped away the chemical modification and restored the proteins’ original structures, as if they had never reacted with sugar. Think Rust-Oleum, but for damaged proteins.

But does it work in actual tissues?

Mice might seem like the obvious next test, but their short lifespans make them poor models for decades of accumulated molecular damage. Instead, the team tested CMLase on thin slices of donated human tissue.

In aortic tissue—the aorta is the body’s largest blood vessel—from a 75-year-old donor, the enzyme slashed CML by roughly 70 percent, bringing levels down to those seen in a 30-year-old. Skin and eye lens proteins from a 64-year-donor also showed significant reductions.

“We were pretty floored,” said Cravens.

Chemical reversal, however, isn’t the same as tissue rejuvenation. It’s still unknown if stripping away CML can actually restore tissue. But the finding challenges a decades-long assumption this kind of molecular damage can’t be treated. It also highlights long-ignored structural proteins as a crucial part of damage repair during aging, paving the way for new treatments.

An enzyme like CMLase could, in theory, be formulated as eye drops to clear CML from the lens or be used to plump up the skin’s protective barrier or restore hearts and kidneys. It would be especially valuable for people with type 2 Diabetes, who accumulate these compounds faster than usual.

Plenty of roadblocks remain. Safety is a concern. Because CMLase evolved from a bacterial protein, the body could label it foreign and launch immune attacks (especially with repeated doses). The body’s own enzymes could also break it down before it has a chance to work. And the enzymes will have to tunnel through a dense protective biological sheath that surrounds organs to reach their target. Work is underway to improve its activity, stability, and safety.

But the team is already looking beyond CMLase. Engineered enzymes could potentially erase other forms of molecular damage once considered permanent. CML is just one member of the AGE family. If the approach works, other targets could follow and one by one, they might chip away at the molecular scars of time.

The post Designer Enzyme Strips Decades of ‘Rust’ From Aging Human Tissue appeared first on SingularityHub.

Byla vydána nová verze 3.5.0 nástroje pro inkrementální kopírování souborů rsync (Wikipedie). Přehled oprav a vylepšení v souboru NEWS. Řešeno je 33 zranitelností.

If you want to record whatever you do on a computer, send those records to OpenAI, use more ChatGPT tokens, and increase your vulnerability to prompt injection, then OpenAI has something for you. It's called Computer History, an opt-in way to record your computer interactions across apps and websites as memories organized on a timeline. Why would you want to do so? Maybe you found Chronicle, the predecessor of Computer History which compiled similar histories using screenshots, a bit too intrusive but don't mind Computer History's approach – recording input events and storing them unencrypted locally for 48 hours (or more), with a brief visit to OpenAI's servers. Maybe you're not bothered by the warning OpenAI includes in its documentation: "Computer History files can contain sensitive information. They are not encrypted by Computer History, and other programs running as your macOS user may be able to access them." Perhaps, having given OpenAI's Codex and GPT Work the run of your computer, you're already sold on the suggestion that storing your computer activity in memory files and arranging those interactions in a timeline will improve ChatGPT responses, surface opportunities for automation, and make it easier to resume prior work. Computer History is, to put it bluntly, a keylogging and event capture system. There was a time before eyeglass cameras, license plate readers, surveillance capitalism, and police drones when such snooping might have provoked an outcry from privacy advocates. But the tech industry has found it can outsource surveillance to its own customers and in so doing make the panopticon harder to protest once it becomes a personal choice. "Computer History creates an interaction-event stream from allowed apps and websites," OpenAI's documentation explains. "Events can include clicks, typing, keyboard shortcuts, app switches, and context that macOS exposes through its accessibility system. Computer History periodically turns these events into text summaries and local memory files." The AI biz makes a point of noting that Computer History does not capture screen images, microphone input, or system audio. Nor does it capture private-mode browsing. Off by default, Computer History is available for ChatGPT Pro, Business, and Enterprise users in the ChatGPT desktop app on macOS. Pro users can enable it individually; Business and Enterprise users need an admin to approve it. It's not available currently in the European Economic Area (EEA), Switzerland, or the United Kingdom or to those accessing ChatGPT via API key or Amazon Bedrock. There are circumstances in which OpenAI suggests Computer History users might want to suspend the service if they have some scruples about capturing user activity in apps and websites without permission. "Turn it off during communications with other people unless you have their prior express consent," the company advises, perhaps in acknowledgement of legal risk. "Consider pausing it or excluding apps that contain sensitive health, financial, or personal information." Computer History interaction events are supposed to be saved locally for up to 48 hours before being deleted by ChatGPT and Codex. Events, however, get sent to OpenAI servers to generate memories, and those may be stored locally for longer periods of time and may be used in future chats that get passed back to OpenAI. "OpenAI does not retain those event files after processing unless required by law and does not use them for training," the company says. While it has opposed demands for chat logs, it has nonetheless provided chat logs in response to legal process. Computer History adds cost because it uses tokens during the summarization of activities and the creation of memory data. It also expands the prompt injection attack surface. "Computer History increases the risk of prompt injection from content in apps and websites," the company says. "For example, if you visit a website containing malicious instructions, ChatGPT or Codex might follow those instructions." But at least you get a nice timeline of your recent activity. ®

Organizace Apache Software Foundation (ASF) vydala verzi 31 integrovaného vývojového prostředí a vývojové platformy napsané v Javě NetBeans (Wikipedie). Přehled novinek na GitHubu. Instalovat lze také ze Snapcraftu a Flathubu.

Astronomové zaznamenali jednu z nejvzácnějších událostí spojených s černými dírami. Objevili dosud nejpřesvědčivější důkaz toho, že Betelgeuse má společníka. Elektrická pole fungují jako fyzikální přepínač proteinů.