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Submission + - Flock Has a Powerful New AI Tool for Police. We Got Its Code (archive.ph) 1

Submitted by fjo3
fjo3 writes: Vehicle surveillance giant Flock Safety has told the public for years that its technology “cannot recognize, identify, or track individuals.” It has now built a system that does both, an artificial intelligence tool for police that can identify drivers and track vehicles by their patterns of movement alone, WIRED has learned.

Submission + - New Gel Regrows Tooth Enamel (sciencedaily.com) 1

Submitted by fahrbot-bot
fahrbot-bot writes: ScienceDaily is reporting that researchers have developed a fluoride-free gel that could help rebuild damaged tooth enamel, something the body cannot naturally replace once it is lost. Inspired by the proteins that guide enamel formation in infancy, the gel fills microscopic cracks, acting as as a framework, and draws calcium and phosphate from saliva to grow a new mineral layer that closely matches healthy enamel.

The material draws calcium and phosphate ions from saliva and uses them to guide the controlled formation of new mineral crystals. This process is known as epitaxial mineralization. In simple terms, the new crystals grow in alignment with the tooth's existing structure, allowing them to connect with the natural tissue beneath them rather than forming a separate, poorly organized coating.

According to the researchers, this organized growth helps the repaired surface recover both the microscopic architecture and the physical properties of healthy enamel.

In addition, when applied to exposed dentine, the gel can grow an enamel like mineral layer over the surface. This could help reduce tooth sensitivity while also creating a stronger surface for dental restorations to bond to.

The researchers tested the regenerated material under conditions intended to reproduce the stresses teeth experience in daily life. These included repeated brushing, chewing forces, and contact with acidic foods that can gradually dissolve enamel.

The results showed that the restored tissue displayed mechanical behavior similar to that of healthy natural enamel, suggesting it may be durable enough for practical dental use.

In lab tests on human teeth using human saliva, the process took about 24 hours for the initial crystallization, reaching 80% of the enamel's original strength in 2 weeks. Human trials have recently begun.

The study is published in Nature and also discussed on Instagram.

Comment Re:Missing mass (Score 1) 18

For me the visualization of direct collapse black hole formation is that there's still a huge mass of gas falling in, at the boundary of the new black hole nearly dense enough to direct collapse itself. The blowback would compress the inflow over the density edge and you get a whole cloud of black holes.

Submission + - China-free batteries made from salt are finally here (msn.com)

Submitted by fjo3
fjo3 writes: U.S. startups are finally delivering something researchers have been working on for decades: a battery in which rare, hard-to-get elements are replaced with the same stuff found in ordinary table salt.

This tech has the potential to help every country on earth break its dependence on China for batteries, and the critical minerals that go into them.

Like any other battery, sodium-ion cells can store and release energy. They are initially being deployed where they’re needed most, in America’s power grid and fast-expanding crop of data centers. As in our homes, giving the grid or other infrastructure the ability to stockpile energy when it is cheap and plentiful, and discharge it when it is scarce, can increase reliability and lower the cost of electricity.

Submission + - New Orleans will use AI to answer 911 calls instead of a human (shreveporttimes.com)

Submitted by fjo3
fjo3 writes: If you call 911 in New Orleans, you may hear the sound of an artificial intelligence (AI) agent answering your call instead of a human voice.

The Orleans Parish Communication District (OPCD) is changing the way dispatch calls are handled in New Orleans with the implementation of new technology.

Submission + - Artificial Intelligence used to design brand new viruses (bbc.com)

Submitted by fjo3
fjo3 writes: Artificial Intelligence has been used to design brand new viruses that are fully functional and can replicate in the laboratory, say US researchers.

It is the first time whole genomes have been successfully designed by AI.

The resulting 16 novel viruses were created to infect bacteria and pose no threat to people.

The breakthrough has been labelled a "very significant turning point" in science that could unlock a new era for treating disease. But experts have also warned AI-designed viruses raise "urgent" safety and security concerns.

Submission + - An Ancient Poop Explosion Could Have Helped Complex Life Evolve (sciencealert.com)

Submitted by alternative_right
alternative_right writes: If the earliest animals hadn't been such prolific poopers, life might not have diversified into all the weird and wonderful forms we see today.

That's the conclusion reached by a new review study published in Trends in Ecology & Evolution.

The team of scientists in Australia and Germany found that the Cambrian explosion â" a period around 540 million years ago when the ancestors of most animal groups arose â" could have been partly set in motion by an explosion of feces, left by those that came before.

Submission + - A fundamental flaw leaves LLMs strikingly vulnerable to attack (technologyreview.com)

Submitted by joshuark
joshuark writes: It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conference on Machine Learning, a top AI conference, this month. The claim has huge implications for the safety of this technology.

By taking advantage of this flaw, which concerns how LLMs identify who or what is giving them instructions, the researchers were able to make popular LLMs spit out information they had been trained not to provide, such as how to synthesize cocaine and how to sabotage a commercial aircraft’s navigation system.

“There’s a real probability that this is going to be a problem that’s fundamentally unsolvable,” says Charles Ye, an independent researcher and coauthor of the ICML paper.

Companies will typically hire teams of human testers to try to come up with novel attacks that break existing guardrails, a process known as red-teaming. Model makers also use LLM super-hackers (such as OpenAI’s GPT-Red) that find and exploit weaknesses in other models to automate parts of this process. The goal is then to take those attacks and train a new model to resist them and anything that looks like them.

The problem, says Jasmine Cui, another independent researcher and coauthor of the paper, is that the approach amounts to giving the models a list of things they shouldn’t do. But no list is exhaustive. “It’s like watching The Simpsons and they have Bart writing ‘I will not say something inappropriate to my teacher’ a hundred times,” she says. “And he still does things that are pretty crass anyway.”

The ICML paper describes attacks against several of OpenAI’s models, but Cui and Ye say that they have since seen similar results with models made by Anthropic, Alibaba, and DeepSeek.

Cui and her colleagues wanted to find out why an attack like chain-of-thought forgery was so effective. They suspected it had something to do with the mechanism that LLMs use to keep track of where their instructions are coming from.

But what Cui and her colleagues discovered is that LLMs are in fact very bad at keeping track of different roles. In a series of experiments that looked at what was going on inside a handful of different models, the researchers found that LLMs seem to identify the role of a specific chunk of text not by the tags around it but by the style of that text and the words it contains.

The upshot, the researchers claim, is that all an attacker needs to do to hack an LLM is write text that spoofs a certain role. And because roles are a fundamental part of how LLMs work, no amount of training will fully solve the problem.

Ye is worried that nobody is ready for what’s coming. “There’s going to be a huge economic incentive for people to do jailbreaks and prompt injections,” he says. The best defense could be to expect the worst. Organizations shouldn’t trust LLMs, and they should expect that anything done by agents could be unsafe, he says: “That’s not a great solution, but it just might be what we have to do.”

“It’s really incredible that these things are being deployed everywhere to control super-critical systems,” he adds. “There’s been no study of the fundamental science here. We’re all doing it ad hoc.”

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