overfeed

> It's been well reported the number of drones/missiles Iran fired has consistently decreased.

One way of interpreting that statistic is that they are running out of munitions. Another way is to consider that stockpiles are not running low, but the initial response was a collection of high-burn, uncoordinated, decentralized tactical actions after an attempted decapitation-strike disrupted top-down C&C. Now that the fog of war has cleared, and communication has been restored, a more strategic regime is now in effect.

> This still feels like a step in the wrong direction, though, especially with OpenAI making so much progress with the efficiency of their models

Gemini also had modest increase before this - don't be surprised when OpenAI also has a "modest increase" with its next release. Cartel-like behaviour doesn't require direct communication when none of the participants are interested in participating in a margin-destroying price-war. All one needs to do is raise their price and watch how the competition react.

Such a scheme (and resulting high margins) would be imperilled by the existence of frontier open-weight models in the market, which may be why the reaction to Chinese models may be particularly shrill.

> This is precisely what the people worried about AI risk and job displacement want, so they should be strongly in favor of open weights then, right?

I'm getting a "gotcha" vibe from how you worded the question, but the answer -unironically - is "Yes." Anyone who is not a closed-weight AIaaS provider[0] will have their lot significantly improved by equally capable, open-weight models.

0. Or their investors. I'm surprised to see Y Combinator signed this letter sering their holding in OpenAI is worth billions and hasn't IPO'd yet. I suspect they crunched some numbers first before signing.

Edit: I realized another group that may be unhappy with frontier open-weight models are those who believe LLMs are inchoate super-intelligences; not only do I disagree with them, but if they are correct, I don't see why we should trust trillion-dollar corporations and their out-of-touch CEOs with that responsibility, when countless CEOs have shown time and time again, that they are not aligned with humanity's interests.

I don't understand the excited tone of the reporting - yes, it is sci-fi, but in a Torment Nexus sense. Imagine other "unconventional" solutions these amoral LLMs could come up with, when given a goal of optimizing the cost of labor in a factory, or making the social security solvent.

Downvoters: if someone indignantly announces they are leaving a service in a manner that suggests its a loss for the service, finding out if they are a paying customer - and in this case, one that can vote on the subject at hand - adds to the discussion.

Were you paying for the service?

> How does Codeberg handle the diverse mix of politics within it and manage its influence

They don't have to.

> Overall, again I feel this is a self-own to project idealogue this hard since you flavor it in a specific way that is not inclusive.

D.E.I. is out right now. Fortunately, Codeberg helpfully funds Forgejo, so all the non-eligible projects can benefit from self-hosting.

A fear of competition causing a failure to recoup the trillions invested in AI via sky-high margins, and starting a (short) chain-reaction that causes the bubble to pop (or fizzle). A lot of people have a lot riding on the AI bubble not popping.

> But the more interesting question is whether labs like Moonshot can be a real competitor to OpenAI/Anthropic.

The answer depends on whether you think the AI researchers at Chinese labs are (or can be) as smart, motivated, and as good at math as those working at US labs - a not-insignificant proportion of whom are Chinese nationals.

Strives to minimize =/= completely eliminates

Math strives to minimize ambiguity, which other fields don't do as much. Non-math fields tend to reuse regular words as jargon (i.e. with specificity of meaning that may fly over the laymen's heads). Social sciences and humanities are most notorious for this, often resulting in non-practitioners not realizing they are out of their depth because they are not looking at symbols from non-Roman alphabets.

> Hugging Face’s security team and agents detected and stopped the activity on their infrastructure and had already begun containment.

Won't even name the model that successfully mounted the defense, huh? Fortunately, Hugging Face has publicly identified GLM 5.2 as the foil against OpenAI's next-gen frontier model's offensive-capabilities.

This announcement feels like rearguard action against a successfully deployed self-hosted open-weight model, and Hugging Face's original recommendations to have an open-weight model you control on standby before an incident.

> ...when is fast a good tradeoff for quality?

When it is cheaper, and the "lower quality" model is adequate for the task at hand.

Plenty of problems have a low(er) skill/intelligence floor, anyone who uses the dual-mode agent paradigm (plan, then act) figures out the second phase can be completed by a less capable model. Even when disregarding costs - speed is important here because the agent can rapidly iterate without human supervision, based on compiler errors, lint and test failures

So that's just an appeal to authority (longevity?) not anchored in reality. Just because you've been doing something for longer doesn't mean you're the best at it; Google has been shipping AI/ML models years before the founding of OpenAI and Anthropic, but it's playing catch-up on LLMs.

That the author doesn't acknowledge the relentless R&D efforts DeepSeek has been plowing into optimization, and giving a default win to OpenAI/Anthropic on the supposition that they've been serving models for longer is a black mark against the article.

I appreciate the transparency in explicitly stating their motivation for writing the article (a response to what the author saw as an overreaction to Chinese models), but I feel the article goes too far the other direction, with multiple unsupported leaps of logic, and overstating the stickiness of AI client products.

> [Anthropic/OpenAI] are serving models at a particular capability level for months before their competitors, and are simultaneously applying the best models to optimizing those costs. Second, intelligence isn’t in fact a perfect commodity, in part because applied intelligence makes itself smarter

Is he casually assuming a singularity has already happened? A regular first-mover advantage I can understand, but those have been squandered or lost many times before.

> But even in China, these AI centric hardware is not cheap

Definitely not cheap for individuals, but well within SME territory. There are countless small-town, family-owned businesses that had higher startup costs than a hypothetical Kimi-R-Us, Inc.

> Chinese labs are doing a favor to the world. But I can also say with 100% certainty that if US labs were to close shops next year, Chinese labs would immediately start charging $$.

How would do you explain the pricing of Chinese solar panels, after managing to destroy other countries' solar industries? The prices are still dropping per watt.

Could it be China's internal demand for solar is big enough, and its long-term governmental strategy on renewables result in an outcome that almost looks like largesse to the rest of the world? I suspect Chinese AI may follow a similar path.

Perhaps, but we can agree that joining the Army goes beyond that. If I were in charge, I'd call the entire Silicon Valley Detachment 201 officer corp to to active duty at some remote desert outpost.

How does yoinking outputs from from prior generation Claude model and post raining on them result in a model competitive with the latest generation? That doesn't add up - nevermind Anthropic hasbeen summarizing thinking tokens since January to counter distillation.

There is a lot of supposition going on your part and mine. IMO, Chinese labs are not dependent on OpenAI/Anthropic outputs; they definitely use the outputs, but along other training/post-training data.

Now that Anthropic hides the real thinking tokens in a way that precludes future CoT distillation, we'll find out which side is correct based on whether Chinese AI labs close the gap or not.

My bet is they'll close the gap; nothing about frontier AI is magic, once something is shown to be possible, experienced practitioners almost always figure out how to accomplish the same feat, though not always on the same way. This is why frontier US labs keep leapfrogging each other every few months.

> 3.4 million is the number of sessions Anthropic detected. The actual number of Claude sessions trained on is likely >100 million.

That's an increase of only a single order of magnitude, increasing my estimate of exfiltrated tokens from 0.05 to 0.15 trillion - a far cry from the 15 trillion required.

> They are used for post-training

Possibly - it may be too much data for post-training, unless further curation was done. However, this is not distillation; you know it, I know it, Dario knows it, but "Distillation Attack" is a short, memorable, sciencey-sounding, political sound-bite with enough malevolence to be deployed on the floors of congress, or by the usual fear-mongering newstainment talking heads.

While it sounds like a lot, do you suppose 3.4 million sessions come even close to being sufficient to train a frontier model?

Assuming each session was 10,000 words each, that's 34 billion words; lets call it 50 billion tokens (0.05 trillion) unfairly pilfered from Claude. That left Moonshot needing to scrounge for the other 14.950 trillion training tokens required for a baseline frontier model.

> We have to stop crying distillation, it’s getting embarrassing and at this point feels even a bit delusional.

It's a PR campaign - when they say its an "attack" they don't mean on Anthropic - but on America itself. What kind of American can let such a brazen attack go unanswered? At the very least, they ought to demand the dangerous, pinko, stolen models be banned in all 50 states, and pay whatever price demanded by the patriotic, freedom-loving, all-American AI labs that can never be accused of stealing.

> The Coros watches are less than half the price, have 22 days of battery life in smartwatch mode

Garmin gets almost 30% more battery life in exchange of not being as fast (30 days)

> I think you can only reach Garmin's stated time if you disable a lot of functionality.

Turning off always-on Pulse ox gets you there. Turning everything off except telling time gets you 2.5x the battery life (69-71 days)

The more expensive watches (Fenix) also have long battery lives: lasting up to a month on a battery that can fit in a watch. The processors still have to sip power.

> [...]it's pretty much a no-brainer to rewrite C in Rust, or at least to attempt it.

Thank you for proving my point. To be clear: there are a lot of legitimate reasons to not rewrite a C projects in Rust, memory safety isn't a universal trump card that supercedes all other considerations in all projects; one has to be zealot to believe that.

I suspect the majority of Rust users are rational about when Rust is appropriate (or not), but they are not going around in random bug threads demanding rewrites of multi-decade projects.

> My point is that whether there will be a crash or not is incredibly hard to predict. COVID did not come with a stock market crash

As someone who had early PUTs against the obvious industries (travel, hospitality) - what I didn't foresee was the insane amounts of government liquidity poured into the markets.

Or Demis realizes self-hosted models are a threat to frontier lab margins, and gating access to the US market is beneficial to the cartel based on whatever post-hoc arguments he can come up with.

> Truly, is that Rust's fault that sloppers are targeting it?

The "Rewrite it in Rust!", all gas, no brakes zealotry predates LLM coding agents. When you dismiss the trade-offs with no consideration, and abide no questions about the possible cost of the "one true $X", you're practicing religion, not engineering. What has changed is the zealots no longer restricted to demanding that other people adapt their preferred language, but can now automate forking projects into their ideal language. I'm hoping the next shoe to drop is the realization that the language is a small part of a projects success, when it's time to maintain their forks.