I stopped being precious about mine after stripping and reseasoning some real gnarly ones from thrift stores. Knowing that I can always start fresh from zero made me worry less, and ironically worrying less has led to better seasoning over time.

Or tell me what it explicitly doesn't do. I like marketing that says, "We don't X"

It's very clear and not "clever"

Here's how atomic bombs work, in casual and somewhat flippant way:

If you have one, you have a seat at every negotiating table.

If you don't have one, a nation state can run special ops into your country, arrest your president and put them in a federal prison.

People who have them pinky promise to do things, shuffle around some numbers about Really Actually Existing bombs and continue to refine their programs internally.

Iff llms are analogous to nuclear weapons (ftr, I don't think they are). No world leader in their right mind would give them up. Anyone that did is as good as dead.

I’m done reading anthropic propaganda

My first impressions and thoughts on the presentation speak to the need for human mathematicians to accept, absorb, and understand new AI-generated proofs—and to the fact that it takes time to do so, as well as the increasing burden of sorting through essentially unsolicited material, which robs that same group of the time to work. Software developers are seeing this same issue with AI-generated contributions of software changes in the open-source arena. What they are seeing is a very high number of trivial submissions, which Dr. Tao points out is a propensity of AI generation. The second problem is that submissions are often not good, forcing reviewers to read hundreds if not thousands of lines of intricate yet incorrect code—and they waste their productive time doing so, making them less amenable to future consideration of such contributions. This is a real problem. As to the issue of human mathematicians needing to accept work as useful before it can enter wider consideration—now that is an interesting problem if humans are indeed unable to understand work AI creates that is useful and correct, but not understood to be so (perhaps due to the above issues), and yet we have to consider a point in time when models become more capable. Let me put it another way: how long would you spend trying to get your dog to understand calculus? AI has inexhaustible patience (unlike humans), and it will keep trying to explain its ideas and theorems to us (or our dogs) far past the point humans would be willing to listen—though our dogs, at least, are amenable to treats and used to us talking a lot while handing them cookies.

It does seem like it the last few days

“I don’t know about you, but I don’t want to live in a world where someone makes the world a better place better than we do” - Gavin Belson

Was the proof of the Cycle Double Cover Conjecture in the training data?

The overwhelming majority of websites are small projects that don't need complex tools to provide interactivity.For those websites, complexity is more likely to come from planning for complexity that will never exist.

Using a tool such as htmx is an effective way for them to solve current challenges while minimizing complexity.

Even the headline is difficult to understand for the target group.

Perhaps, soon, it will be necessary to phrase it "Zoolander" style. Maybe something like "Top 3 Shocking Reasons Why You Can't Read Good No More!"

I think the point you're trying to make is that you can always make your exposed surface area smaller

But that, of course, is not going to survive contact with reality

The difference with open weight is that everyone has access to the same weaponry

Bad example. You can do all of this with constructivism. Any constructable Cauchy sequence converges to a constructable member of the space.

What you get for the formalism around computable numbers is this. Every mathematical object in the theory is something that can be, at least in principle, actually written down. When we say that it exists, this existence is of the most tangible form that any mathematical thing could have.

I'm bitterly disappointed with the shape (aspect ratio) of that front screen, if the one on the iPhone Ultra is likely to be similar.

I got my hopes unrealistically high based on a single comment I saw somewhere here on HN, that if Apple already had a nice small screen lying around they might decide they may as well use it to make a small phone again.

I don't think there's much to be done with something that shape for the only screen on a phone.

After WWDC, I predict another flood of iPhone Mini battery replacements. Dozens!

Sorry how is that relevant to the linked article?

And despite what you claim it is the most profitable gaming platform. There are lessons you can learn from them.

> supposed to be dynamically probed to adapt to different toolchain environments

that's a bygone practice from before compilers were widely capable.

"LLMs are excellent at creating output that looks right but is nevertheless still wrong."

"Anthropic has a long history of just lying and making shit up"

Every now and then I wonder, if LLMs were created by honest people would they be more honest themselves?

That’s way more than I do with mine: hot water, nylon brush, throw it on the heat till dry, wipe with paper towel already oiled from constantly doing this.

First use is always over easy egg, which doesn’t really even dirty the pan enough to worry about if I’m going to just cook again later.

It's even worse than that. From the article:

> Open-weights models that don’t have dangerous capabilities are a public good

Oh! And, uh, what's a "dangerous capability" according to Anthropic? Let's see, according to their "Responsible Scaling Policy" [1] document:

- Being able to research energy, robotics, or AI is an unsafe capability

- Additionally, any model that's capable enough to be "used widely" by the government must de facto have unsafe capabilities.

They want to ban pretty much anything open-source that's above cat-level intelligence.

1: https://www.anthropic.com/responsible-scaling-policy

I also read that one. Though certainly I also skipped some texts in college.

Formally verified against what spec?

From TFA: “This is a tongue-in-cheek attempt to demonstrate what a human can do that an LLM cannot”

From the other comments here it seems there’s another thing humans can do that LLMs can not: choose not to read the article and respond only to the headline :-)

> I would classify D's scope exit/failure/success as RAII actually, even if D uses a GC.

D's scope exit/failure/success is built on top of RAII and has nothing to do with the GC.

> I would say exceptions should be the main mechanism in normal circumstances and for expected errors you csn use error/result types.

Come to DConf (or watch the live stream) and I hope I can change your mind, or at least challenge your conclusions!

What are the ramifications?

It is actually an interesting conundrum.

Is a non-well-aligned frontier level AI a problem? I think it is likely that it is, or at least has a high likelihood to be in the future. Two scenarios for this: Misused by some bad guys. Or the terminator scenario. Both not great.

So what do we do about it?

1) We can accept it, and hope that the good guys AI can defend.

2) We can try to limit the access to it (AI proliferation?)

3) We stop the development of it

4) We can accept the risk and do nothing.

None are particular good options. Really reminds me of nuclear proliferation, on so many levels. For that, we kinda do all three:

1) Nuclear triad / iron dome / early warning systems

2) Nuclear anti-proliferation treaties.

3) Dead Physicists

Ok, so assuming all of this is true, open weights are a problem. Don't get me wrong, I love open science, open source etc. It's great to have access to capable open models. But: Even if release open weights are well aligned and have a safety layer built in, it is likely not to difficult to abliterate that part of it.

If this is really where it is going, then even closed weight model providers will see a lot more requirements for protection of the weights.

That is not a number in constructivism.

But there are numbers in constructivism for which it is unknown whether they are zero. Some of which must remain unknown, if mathematics is consistent. This is a rather important and weird edge case.

Americans don’t get to lecture the world on authoritarianism anymore

You said that food is not meant to be enjoyable and that it's coincidental that it's tasty -- this is flat out wrong, so your attempt to argue by analogy (always a suspect process) was bogus. And your "something would be lost" is a strawman from left field that actually undermines your argument. (BTW, I enjoy Huel and they make an effort to make the taste and texture pleasurable. And people often combine kale with fruit to make tasty shakes.)

Work, unlike food, is a social construct, and while it's no doubt a bit more complex, the statement that "Jobs are not generally meant to be enjoyable (although that is a benefit if so), they are meant to get work done" is factually correct. Because work generally is "work, not fun", people get paid to do it, with competitive salaries and perks.

I won't respond further to your very bad arguments (or the absurdly out of touch elitist arguments from others here that miners enjoy their work as much as software developers do ... I'm retired and still do software development for fun; no miner does the same).