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Comment Diverse double-compiling (Score 1) 131

Do you have the code for the compiler, and compile that yourself too?

If you have three different compilers for a language, and you bootstrap a compiler using all three of them, the first generation (e.g. GCC compiled with QuestionableCC, ShadyCC, or SlopCC) should be functionally identical, and the second generation (GCC compiled with GCC, which was compiled with the other compiler) should be bit-identical. See "Fully Countering Trusting Trust through Diverse Double-Compiling" by David A. Wheeler. Some people have trouble trusting Rust because only the latest stable rustc can compile the latest stable rustc.

Submission + - New tin-based solar cells trap heat 1,000 times longer, could beat 33% limit. (interestingengineering.com)

Submitted by fahrbot-bot
fahrbot-bot writes: Interesting Engineering is reporting that researchers at the University of Groningen in the Netherlands found that tin-based perovskite solar cells can slow heat loss from high-energy “hot electrons” by a factor of 1,000 and could push solar cell efficiency beyond the theoretical 33 percent limit.

When sunlight strikes a panel, photons jump-start electrons into action. The most energetic photons create super-charged hot electrons. Theoretically, these high-voltage powerhouses should generate far more electricity, but, in practice, they are fleeting. In fractions of a trillionth of a second, these high-energy particles rapidly cool, dumping their bonus energy as waste heat before ever leaving the solar cell.

“This means that the energy is lost before the hot electron exits the solar cell material,” said Jan Anton Koster, Professor of Physics of Novel Semiconductors and Devices at the University of Groningen.

Using a specialized solar cell material called tin-based perovskite, Loi’s lab performed a feat many thought impossible: she slowed the heat loss down by a factor of 1,000. Suddenly, the extra energy lingered for nanoseconds instead of vanishing in picoseconds.

The study findings were published in the journal ACS Energy Letters.

Comment Standing? (Score 0) 108

In the US, in order to file win a lawsuit, one needs standing https://en.wikipedia.org/wiki/Standing_(law), which essentially means one needs to show one has been harmed by the action in question or one is specifically given permission to sue by a specific law. I'm not a lawyer, but I'm having trouble seeing how the people suing can argue they have enough harm that is a form that matters that they'll be able to persuade a judge they have standing.

Submission + - Trump says Arch will be a military complex with weapons, drones, sniper's nest (theguardian.com)

Submitted by fahrbot-bot
fahrbot-bot writes: The Guardian is reporting, along with others, that President Donald Trump is proferring a new argument for building his triumphal arch in Washington DC: it will be converted into a “top grade military complex” replete with drone and ammunition storage space and customized sniper facilities on the roof and plaza.

In a post on his Truth Social platform on Sunday morning, Trump claimed that his new plan came at the “strong request” of the US military. He said the 250ft structure would be able to “house, store, and have the rapid ability to use large quantities of sniper ammunition in storage”. The president added, “There will be no facility like this anywhere in the world.”

This seems like a ploy to get around courts holding up the project by re-framing the project as a National Security matter, as he did with the East Wing of the White House. (Can the Kennedy Center be far behind?)

Comment Re:Migration season (Score 2) 196

by fahrbot-bot (#66343950) Attached to: US Air Force F-16 Crashes in Michigan After Pentagon Orders More Flyovers

Flying low over the central flyway during migration season might not be a good idea.
Geese are non-compressible fluids as far as jet turbines are concerned.

Probably a Canadian Geese trying to sneak into America.

Canada Geese can apparently fend off Bald Eagles, so why not Falcons (F-16s). :-)

The Full Story Behind the White House’s Eagle v Canada Goose Post

T]he official White House X account reposted a photograph of a bald eagle pinning a Canada goose ... It appeared the image was intended to symbolize American dominance over its northern neighbor ...

The full set of pictures from the incident show the bald eagle launching multiple attacks against the Canada goose over roughly 20 minutes. At several points, the goose appears pinned to the ice and in danger of being killed.

However, the goose repeatedly stands back up, spreads its wings and confronts the eagle. By the end of the encounter, the eagle gives up and leaves while the goose remains alive.

Comment Re:Jacob Coxon is a nobody (Score 1) 105

I'm not sure any of those have money at that level. Aaronson in the past when he was doing quantum computing work refused to take payment or stock from quantum computing companies, so I'd be shocked if he has any money. As for monetary concerns, Hinton explicitly quit his well-paying job at Google so he would be free to talk about AI risk. So the narrative here is the exact opposite. And when the companies talked about deliberately slowing AI growth, stock in AI related companies went down, which undermines the idea that this is anything about their investments. But there's also a serious problem here if someone like Coxon can be dismissed as not having enough knowledge or experience, but people who have been involved in the industry for a long time can be dismissed because they may have financial ties. So can absolutely anyone be dismissed as irrelevant, either lacking in expertise or being too tied in to the industry?

Comment Re: Jacob Coxon is a nobody (Score 1) 105

When LLMs have a memory longer than an hour, I will become more concerned.

I'm not sure what an hour memory here means, since context windows are measured in tokens. Even six months ago, LLMs could think for well over an hour before producing an output.

For anyone who is actually very deep in AI *in the real world*, not just heads down in foundation labs - the hyperbole is off the charts on all of this. We are NOWHERE NEAR the exponential yet. These labs can't even get AI to improve their own software reliably, let alone do other things reliably.

This seems odd at multiple levels. First, the people in the foundation labs if anything have more of an idea what is happening than the general population. They are seeing how models are made, what they contribute, and how they go run off the rails. I'm also puzzled by the claim that we're not at the exponential. Two years ago, AI systems could barely do AMC and AIMIE problems, basic high school math contests. Then the AI got to be good enough to do well on Putnam results. Then, early this year, AI got to be good enough to solve multiple open unsolved math problems, including Erdos 1196 https://www.erdosproblems.com/1196 , the Unit Distance Conjecture https://arxiv.org/abs/2605.20695 and many others, and the trends there are just continuing. That's one field, but it is one where the standards are most objective about what is happening. That certainly looks like exponential growth. I'm also puzzled by seeing the labs cannot get the AI to improve themselves is a good standard. From the perspective of a lot of people who are concerned, once that's happening, it is likely too late.

Yann is the most sane of them all because he recognizes we need some massive breakthroughs if we want to achieve real AGI

What you mean here is you agree with Yann. But the point is that lots of people who are as qualified as Yann, disagree. So if, as in your first comment, your primary problem with Coxon is lack of experinece, you should find this situation alarming. Worse, your complaint about Coxon was lack of lab experience, but in your new comment you object to people being too deep in the labs to be objective. This leads to the weird situation where no one is in a position to be relevant to listen to.

. LLM tech has hit its limit, unless someone cracks memory and continuous training.

It is possible that LLM tech has its limits. But people were saying it was hitting its limit 4 years ago, and 3 years ago, and 2 years ago, and a year ago. 4 years ago, people who were saying LLMs were limited would not have predicted they'd be solving unsolved math problems. All those predictions turned out to be wrong. Why should saying it now be more likely? And what if you are wrong here?

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