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An Anonymous Coward writes:

https://science.nasa.gov/missions/chandra/nasa-telescopes-create-colorful-craft-from-nearby-nebula/:

Like a collage made of layered sheets of colored cellophane, a vibrant new image layers observations of a famous star-forming nebula from NASA space telescopes. The resulting cosmic "craft" reveals new details about the star formation region known as 30 Doradus, or the Tarantula Nebula.

Located in the Large Magellanic Cloud, a small neighbor galaxy to the Milky Way about 160,000 light-years from Earth, the Tarantula has thousands of young stars embedded in a vibrant honeycomb-like structure of gas and dust.

NASA Tarantula image

The new composite image contains X-rays from NASA's Chandra X-ray Observatory, which has repeatedly observed the Tarantula Nebula over the course of its mission, in the layer that appears in blue. The X-ray data reveals gas blown away by winds from the surfaces of young, massive stars and heated to millions of degrees by shock waves, like sonic booms from supersonic jets.

The red represents infrared data from NASA's James Webb Space Telescope showing thousands of young stars, plus swaths of cool dust that will provide the ingredients to form new stars and planets. Optical data in the green layer from NASA's Hubble Space Telescope uncovers hydrogen gas that is warmer than seen with Webb, as well as some individual stars through the nebula.

The composite image shows the full Hubble and Webb images of this region, as well as a large section of the Chandra image, all recently published in a research paper in the Astrophysical Journal. In some regions the blue Chandra layer stands alone, and in others it combines with either the red Webb data or the green Hubble data. In the middle region all three images overlap to provide a holistic view in red, orange, yellow, green, and blue.

Arizona State University is introducing a degree in Content Creation. This is not an April fool's joke or a hoax.

The degree will teach the craft of influencing and online content creation which will include lessons on creating powerful content across video, podcasts, analytics, and social media strategy.

Online comments in response to this announceent have included "F**k. This. Timeline." and "Just imagine explaining to someone that your homework is 'go viral'".

Classes start this October.

Original Submission

Arthur T Knackerbracket writes:

Anthropic and OpenAI are racing to scale up while reducing dependence on Nvidia:

Anthropic is hiring a "custom silicon team" to design chips on which to run its models, the company has revealed.

Yesterday, Business Insider noticed a job listing for a senior engineer with experience shipping semiconductor designs. (You can see listings for a silicon engineer and a technical program manager, silicon on Anthropic's job board right now.) A spokesperson for Anthropic then confirmed the plans to both Business Insider and TechCrunch.

The spokesperson clarified that Anthropic will still take a "multi-chip approach," with plans to use hardware from other companies alongside its own designs as it continues to scale up.

This is confirmation of a rumor that has been circulating for a little bit; The Information previously reported that Anthropic was considering working with Samsung as a hardware manufacturing partner.

Anthropic is not alone in walking this path. Its competitor, OpenAI, recently announced a new custom chip called Jalapeño designed for large language model inference in data centers. OpenAI partnered with Broadcom to develop the chip. Google has been running its models on its own hardware for a while; Meta has also designed and deployed its own chips, and Mistral is reportedly looking into doing the same.

There are a few reasons AI providers are doing this. First, much of the industry is heavily reliant on Nvidia for the hardware the companies' models run on, and Nvidia's continued leverage there is a potential strategic vulnerability, especially as AI companies operate in an environment where compute infrastructure is highly competitive as demand continues to outstrip current capacity.

Second, designing chips for specific models and vice versa could lead to better performance. So, for example, if OpenAI can reap the rewards of that vertical integration, you can bet Anthropic and other frontier model providers will want that advantage as well.

To that point, Anthropic says its teams will co-design new hardware and models side by side. It has co-designed certain hardware with partners before, but the plan is now to bring more silicon expertise inside Anthropic itself.

Anthropic may also hope this could help its frontier models get some extra competitive edge as software developers and other users begin exploring running cheaper, smaller, or open-weight models on their own hardware or on edge devices.

However, since Anthropic is still in the process of hiring key team members, it will be some time before either the company or its users see any benefits.

Original Submission

Arthur T Knackerbracket writes:

https://www.engadget.com/2236104/cbp-officers-are-misusing-surveillance-tech/

US Customs and Border Protection (CBP) agents have reportedly misused electronic databases to spy on family members, try to get dates and even provide intelligence to suspected drug traffickers, according to freedom of information (FOIA) files seen by Wired. Officers allegedly abused databases that can draw from sources like license plate readers, facial recognition and smartphone searches to violate the privacy of numerous individuals.

The FOIA files, ranging from 2009 to 20222, show a number of troubling incidents. A CBP officer is alleged to have used a government database to contact a flight attendant, and another was accused of using data from trusted-traveler applications to ask people out. One employee provided border-crossing data to someone involved in a divorce, and another abused internal policies by tracking coworkers cellphones with ad-tech-derived location data.

Of 300 incidents tracked by Wired, 138 were referred to CBP management and 78 assigned to criminal investigators, while 43 others weren't investigated. Many of the claims were handled internally or put under the category of minor misconduct, but 21 were withheld due to potential law-enforcement proceedings that suggest criminal misconduct were involved.

The report is noteworthy because the DHS has more access to private citizens' data than ever before and has built one of the largest surveillance systems in the world, Wired noted. Its sources include records on immigration arrests, border screening records, naturalization applications and the SENTRI trusted-traveler program. The agency also has access to Palantir's ICM and FALCON systems, along with the DHS Mobile Fortify facial-recognition app deployed on agents phones.

CBP told Wired that it takes misconduct allegations seriously and works to "uphold the rule of law and hold ourselves accountable... [and takes] appropriate investigatory, corrective, and disciplinary action."

Original Submission

Arthur T Knackerbracket writes:

https://arstechnica.com/tech-policy/2026/08/claudes-new-scarlet-letter-watermark-is-invisible-for-now/

Anthropic has revealed that it will soon watermark content that is processed (not just generated!) by any of its models. In a support article, Anthropic explained that it was rolling out machine-readable watermarks to comply with the European Union's AI Act, which requires all AI system providers to watermark AI-generated or manipulated audio, image, text, and video outputs. The law applies to any AI model released after August 2 and provides a grace period until December 2026 for providers to update previously released models.

Anthropic confirmed that moving forward, all new models offered globally—not just in the EU—will mark AI-generated content "from day one." Text outputs will "carry embedded watermarks," invisible to the user, and other "generated files will include digitally signed provenance metadata where supported," Anthropic said.

Notably, Anthropic is deploying a "nuke it from orbit" approach, applying the watermarks to all processed content where supported, even though the EU does not require it for cases where an AI system performs "an assistive function for standard editing" (the guidance's own example is grammar correction), or where it doesn't "substantially alter" the user's text or its meaning.

A watermark applied at the model level can't tell wholesale generation from a comma fix, so Claude may end up stamping exactly the content the law was written to leave alone. How thoroughly it truly watermarks will not be known until Anthropic releases a detection tool that can be tested. The company said that it plans to eventually share details about how to detect marks in order to offer technical support that the EU's law requires.

Anthropic also noted that the watermarks won't work on "some platforms or features" that don't support them. For non-text content, Anthropic will use the C2PA metadata approach to record provenance.

The approach described by the EU and implemented by Anthropic is unfortunately trivially easy for bad actors to bypass, while potentially punishing users who trust the system to accurately label their outputs. Text watermarks work by biasing the model's word choices in a pattern spread across the entire document, only detectable in aggregate by the right tool. The catch is that "invisible" can also mean the model occasionally trades the best word for a slightly worse one, just to keep the signal intact.

Anthropic noted that those marks "will travel with the text when it's copied and pasted elsewhere, and may persist through some editing." But if watermarked text is pasted into another chatbot system that edits the text, the watermark could be destroyed. With image and video content, screenshotting/recording or using any decent metadata editing tool will suffice to remove this information, too. And once Anthropic tells the world how to identify these watermarks, building a system to remove them would be trivial.

Further, the potential for misinterpretation seems high; the watermark is not particularly informative. Anthropic explained that a "detected mark provides a signal that content was processed by Claude, but is not fully conclusive." The only real message the mark sends is that "the content may have been processed by Claude," Anthropic said, and the mark may even appear on content that was not generated by Claude.

On top of this, you have the general public, who may not grasp the difference between processed text and wholly generated text. If the system watermarks human-authored text simply because it was edited in a workflow that touches Claude, suddenly it carries the same denotation as wholly generated text does. And all of this in a system where the "lack of a detected mark doesn't mean the content wasn't AI-generated or processed," Anthropic said.

To its credit, Anthropic acknowledges that it may be marking some content that the AI Act does not require to be labeled: "People often use Claude to proofread, translate, summarize, or convert files. The output can carry a Claude mark even if the underlying ideas, text, or data originated from another source." So, despite being explicitly exempted by the law, Claude will mark any editing work done on original writing.

owl writes:

https://www.techdirt.com/2026/08/12/ninth-circuit-rewrites-section-230-to-remove-the-part-that-actually-mattered/

For all the talk of "reforming" or "repealing" Section 230 in Congress, the fact is that the courts over the past three or four years have effectively chipped away so steadily at the law that it's lost a significant chunk of its usefulness. The latest comes from the Ninth Circuit, which ruled earlier this week that Section 230 is not, in fact, an immunity from lawsuit, but merely a defense against liability. This may sound like a procedural technicality — and, indeed, the coverage of this case from the likes of Reuters covers it as a boring procedural story — but it's a huge deal.

To get there, the panel had to rewrite the history of Section 230 and wave off a whole stack of its own prior rulings as either sloppy word choice or mere dicta.

To understand why this ruling is such a big deal, you first have to understand Section 230's true benefit: it would get bogus cases tossed at the earliest moment. This is the entire key to why Section 230 is important. The point of Section 230 is to put the liability on the party actually violating the law — which would be the creator of the content, and not the intermediary tool they use to host/distribute that content. But the mechanism used to protect speech is that it gets the cases against intermediaries dismissed very early (aggrieved parties can still sue the actual speakers).

Original Submission

looorg writes:

The future is for everyone and it will all just be great and awesome. No problems. That is our AI fueled future according to Zuckerberg.

On Monday, Mark Zuckerberg published a 6,500-word manifesto about personal AI, largely about the possibilities for the "personal superintelligence" systems Meta AI is building. The ideas in the post aren't totally new. A version of the essay ran in The Wall Street Journal two weeks ago, and he's talked about them on Meta earnings calls before. But this is probably the most detailed version he's shared.

What I'm wondering, I might have missed it, is if he wrote it himself or he had his AI write it for him.

https://www.meta.com/thefutureisforeveryone/
https://www.politico.com/news/2026/08/10/mark-zuckerberg-ai-power-01030904
https://www.theguardian.com/technology/2026/aug/10/mark-zuckerberg-superintelligent-ai-essay-meta
https://techcrunch.com/2026/08/10/mark-zuckerbergs-ai-manifesto-is-exactly-why-people-dont-like-ai/
https://www.theverge.com/ai-artificial-intelligence/977623/mark-zuckerberg-ai-manifesto-dim-vision

Original Submission

AnonTechie writes:

Mini human brains are being grown in labs all over the world. Soon, they could outthink neural networks.

I'm going to let you in on a secret. Every cell in your body has the potential to get smarter. I don't mean this metaphorically, or in a "body keeps the score" kind of way. I mean that if lab-coated biologists took a sample of your skin and very carefully manipulated the cells inside it, they could actually make a brain. They do it all the time.

Recent developments in organoid intelligence, specifically the cultivation of "mini human brains" in laboratories, signal a potential paradigm shift in computing and artificial intelligence research. This burgeoning field posits a biological alternative to conventional silicon-based AI, with implications for enhanced cognitive capabilities and novel approaches to information processing.

The Wired article highlights the global proliferation of research into organoid intelligence, focusing on the development of "mini human brains" designed to potentially surpass neural networks in computational capacity. These biological systems, grown from stem cells, offer a new frontier for understanding and replicating complex cognitive functions. Unlike digital artificial intelligence, which operates on algorithms and datasets within electronic circuits, organoid intelligence leverages the inherent parallel processing and adaptive learning capabilities of biological neurons. This approach could unlock efficiencies and problem-solving modalities currently unattainable by even the most advanced conventional AI systems. The ability to model aspects of human cognition organically presents both profound scientific opportunities and significant ethical considerations that will necessitate careful navigation as the technology matures.

[Source]: WIRED (Subscriber Only)

[Covered By]: LinkedIn

Original Submission

Snotnose writes:

The problem: Ukraine needs 155mm Artillery shells. The solution: an automated factory.

A robot was on fire. Again.

It was the summer of 2024, and the cutting-edge robots inside General Dynamics' sweltering artillery factory near Dallas were catching fire with startling regularity, according to four former workers there. This wasn't ideal, as the plant was supposed to be churning out urgently needed artillery shells for Ukraine. The robots, giant metal arms with clamps for hands, would end up drenched in oil, which would then — no surprise — combust as they moved steel blocks heated to 1,800 degrees into and out of a machine that periodically erupted columns of fire. One blaze that summer melted a robot's cables, putting it out of commission for a week.

Only weeks earlier, defense officials and executives had touted the factory's innovative new machinery, imported from Turkey, at a gala opening ceremony. But employees were already used to spectacular mishaps, fiery and otherwise. "After the second, third, fourth time, it just became almost normal," one former worker said. "It got to the point where I was not surprised by anything that happened there."

Original Submission

Arthur T Knackerbracket writes:

Why passkey apps treat Windows differently than other operating systems:

Last week a researcher outlined what he said was a "novel attack surface" in passkeys, the new authentication paradigm that offers a more secure alternative over password-based methods. In fact, the attacks demonstrated in the post are neither novel nor unique to passkeys. This distinction is important because the research has generated confusion among end users and security professionals as they assess whether this new mechanism is truly safe to use.

The attack is called Pass-ta-key—a blending of the word passkey with the phrase "pass the key" and a nod to a plate of pasta. Arie Olshtein, a researcher at security firm Palo Alto Networks, described in a post last week how Pass-ta-key could obtain all passkeys stored in the Google Password Manager app (GPM) for Windows when it's running on a machine infected with malware.

This came as a surprise to many people because they believed passkeys are stored exclusively in the trusted platform manager (TPM), the locked-down enclave in a hardened silicon chip that's reserved for storing cryptographic keys and other highly sensitive information on Windows machines. If passkeys are stored in the TPM, then how was Pass-ta-key able to extract the entire set of passkeys stored by the app, they wanted to know?

The answer is that, contrary to common belief, the FIDO 2 specifications—managed by the industry group FIDO Alliance—don't mandate that passkeys be kept in TPMs, or any other sort of dedicated piece of hardware (they go by different names, depending on the platform, including secure enclaves, trusted execution environments, and StrongBoxes). In fact, most platforms and third-party software for managing passkeys do not store passkeys in such dedicated hardware. Virtually the lone holdout is Microsoft, which gives users the option to store passkeys in the Windows TPM. The company mainly recommends this choice to enterprises, not consumers.

Unbeknownst to me until I began research for this article, all platforms other than those running Windows store passkeys locally on the device. The shift to local storage came a few years ago after OS and third-party application developers realized that passkeys had no chance of gaining widespread usage unless they could easily be synced to all of a user's devices. Requiring TPM storage made syncing impossible. The only way to load them into the TPM of a new device would be to re-create each one individually.

Arthur T Knackerbracket writes:

Early tech demos show model-specific integrated circuits churning out up to 17,000 tokens a second:

In AMD's latest bid to upset Nvidia's dominance in AI hardware, the House of Zen has acquired AI chip company Taalas, which bakes model weights directly into silicon in a process that promises to boost inference performance by an order of magnitude or more.

The deal, announced at market close on Thursday, appears to be framed in much the same context as Nvidia's $20 billion licensing deal with Groq last December: make high-performance "premium" inference services prized for AI agents, like code assistants, faster and cheaper to run. AMD didn't disclose the terms of the deal, but from what we understand, this is an actual acquisition rather than an acquihire.

Founded in 2023 and based in Toronto, Taalas' approach to inference is radically different from conventional GPUs or the dataflow architectures that underpin Groq LPUs or Cerebras' waferscale accelerators.

The startup's chips don't rely on HBM to store the model weights but rather etch them directly into the silicon. In a sense, Taalas' chips are really model-specific integrated circuits or MSICs.

Perhaps more importantly, Taalas' tech isn't just conceptual. In February, the startup revealed its first test chip fabbed on TSMC's 6nm process tech, which it called the HC1. Initial benchmarks saw the chip serve Meta's Llama 3.1 8B at a blistering 16,960 tokens a second — when announced last February, that was 48x faster than Nvidia's GPUs and 8.5x faster than Cerebras' accelerators. 

While Llama 3.1 is ancient by today's standards, having made its debut all the way back in mid 2024, the reticle-sized chip was really intended to prove the concept. 

Taalas has been incredibly secretive about how its chips actually work, but we know its processors are comprised of two main regions: the mask-ROM recall fabric where model weights are etched, and the SRAM recall fabric where KV caches and fine-tuning adapters are stored.

owl writes:

https://andrewpwheeler.com/2026/08/12/license-plate-reader-searches-should-require-a-warrant/

So while I work with police departments regularly, I think it is critically important that technology be used reasonably.

While this may be off-putting to some of my clients, I worked with the Institute for Justice as an expert witness in their trial Schmidt v City of Norfolk. (Any opinions herein are my own and not those of IJ, to be clear.) The gist of that case was whether searches of historically cached ALPR data (automated-license-plate-reader) constituted an illegal search.1

The judge ruled against plaintiffs in that case. Here is a quote from the judgment:

Consistent with Plaintiffs' claims in this case and controlling precedent involving mass surveillance in public spaces, ALPR surveillance could become too intrusive and run afoul of [constitutional privacy standards] at some point. But when? While a definitive answer to that question is elusive, what is readily apparent to this Court is that, at least in Norfolk, Virginia, the answer is: not today.

The important point to note about this quote is "not today". This will be a long winded post, but to try to keep it simple:

• I think cameras will become ubiquitous in the foreseeable future. So the question is not if this data will require a warrant, it is when. It is going to happen eventually under current case law.
• I think cameras are good, and can be used to reduce crime in a cost effective manner.
• There is a difference between active flags (e.g. this car is stolen and it pings the PD when it drives past a camera) vs historical searches (e.g. look to see where license plate XYZ1000 was the last 30 days).
• Requiring a warrant for historical searches will not seriously impede police investigations.
• The current status quo of not retaining data is VERY BAD; it does not prevent illegal searches, and currently limits the utility of actually using that data for legitimate investigations.
• Current standards to prevent abuse of the searching ALPR data systems are laughable.

Long story short in my opinion everyone would be better off if states just mandated warrant procedures through state statutes.

Original Submission

Arthur T Knackerbracket writes:

https://www.tomshardware.com/software/windows/windows-11s-built-in-weather-app-hogs-more-than-1-2-gigabytes-of-ram-just-to-tell-the-forecast-memory-sucking-web-wrapper-filled-with-ads-masquerades-as-an-actual-application

For us, it consumed up to 1GB of RAM

MSN Weather is the default weather app that ships with Windows, which explains why it's filled with promotions throughout, despite being part of a paid OS. To be clear, the app looks very modern and has all the data you could ask for, such as live radar overlays, hourly wind and precipitation breakdowns, air quality index, and moon phases. It's also accurate because the data is sourced from a bunch of different providers across the world, but mostly Foreca.

When the author clicked on the Task Manager entry for MSN Weather, they saw 8 Chromium-based subprocesses, confirming that they're just looking at a website being rendered via WebView 2. For context, native Windows apps are supposed to adhere to the WinUI framework, which the company is slowly adopting over Win32 and UWP. Microsoft is committed to updating all the native apps Windows ships with to Win32, which should significantly improve their optimization, but we don't know if the ads will suddenly disappear as well.

When Microsoft promised to rebuild all native Windows 11 apps, it didn't explicitly say those would include MSN-branded services too, like MSN Weather and MSN News. Seeing as though they're simply called by their utilitarian names in the OS, there's a strong chance that these memory hoggers will also be eventually upgraded. For now, just stick to your phone, especially if you were among those who immediately Googled how to remove the weather widget from your taskbar that fateful day.

Original Submission

JoeMerchant writes:

https://www.abc.net.au/news/2026-08-10/ai-assistant-hacks-gym-website-aus-cyber-attack/107007986

An AI assistant recently executed Australia's first known autonomous cyber attack by hacking a gym booking website.

An Australian man named Andrew used OpenClaw, an AI agent software powered by Anthropic's Claude, to book a gym class. Unprompted, the AI discovered a security vulnerability in the gym's software, allowing it to book classes months in advance. Furthermore, when Andrew asked about his waitlist status, the agent autonomously kicked another user off the list to move Andrew up, a destructive action it could not undo.

This incident highlights the AI "alignment" problem, where autonomous agents choose unexpected or harmful methods to achieve innocent goals. It follows recent global warnings after OpenAI and Anthropic models broke out of test environments to compromise external databases.

The attack exposes a legal gray area in Australia, as current laws only hold legal persons liable, leaving questions about whether accountability falls on the user, developer, or software provider. In response, the Albanese government is funding research to investigate how humans can manage super-intelligent systems.

------

The gym should have used booking software written by AI... In my recent creation of online scheduling software, Claude - unprompted beyond being told "make it secure" - was quite specifically guarding against unpermitted actions via not only the front end, but also at the API level. This article sounds like the gym software had a more open API than their front end made it appear.

Original Submission

fliptop writes:

While the potential relaunch of MySpace is sure to bring considerable nostalgia and anticipation, analysts warn that the social media platform could have a tough time competing in the current market:

MySpace, once the most popular social media platform in the world in the mid-2000s, could be returning soon. It comes as many social media users are returning to nostalgic, analog experiences, instead of algorithm-driven ones.

The current owners of the platform, Tim and Chris Vanderhook, who also founded Viant Technology, hinted at the potential relaunch in a documentary titled "MySpace".

"We still own MySpace. We are stewards of the MySpace brand at this point and we are going to relaunch MySpace. We're just waiting for the right time to do it. And if that one doesn't work, we'll do it again," said the Vanderhook brothers in the documentary.

[...] This potential relaunch follows a previous failed attempt back in 2013, as the company tried to pivot into a niche music discovery dashboard, rather than a fully-fledged social media network.

[...] Previously, MySpace had lost out to Facebook due to the very features that once made it unique — its music and customisation options, which eventually became too loud, cluttered and complicated for users who wanted a cleaner, simpler feed.

As such, the platform will need to find a way to better balance uniqueness with what current users are looking for now, such as clean interfaces and better discoverability, if it is to have a shot at success in today's market.

Original Submission