make3

Do you want companies to have incentives to pay researchers even if NDAs and non competes are basically unenforceable? Do you want any communication of knowledge from corporations? Should companies not be allowed to benefit from sometimes huge investments in research?

I think talent would definitely take a startup that publishes more seriously, and it would be a smaller risk for top research talent to go somewhere where they can also publish than have to bear the full risk of their work at a no name startup not going anywhere

It's harder for them to argue you were actively destroying evidence; you could say that you had written the wipe pin there for a legitimate use case like both your wallet and your phone get stolen

creating a convincing and actually safe innocuous mode is probably harder than it sounds in practice

Your argument about not successfully competing doesn't hold because distillation is essentially model stealing. The situation is like trying to compete on effort in school on an exam against someone who's copying your answers. Of course the person copying your answer will always have to study fewer hours.

I sympathize with the argument saying that they ripped the whole Internet and books first though of course.

The Zirgs they call them (I'm kidding)

Not arguing for the morality of it, but if we're going by the law because that's what you're using in your comment ("don't I own" which only matters wrt the law), then you explicitly accepted a Terms of Use which excludes distillation as a use case.

Now of course they themselves trained on the whole Internet for free, etc.

no argument from me here

There's no real way to compete with someone who gets the output of your own work for almost free in comparison.

I sympathize with the argument saying that they ripped the whole Internet and books first though

You can also get it to think in the output tokens pretty easily, eg "Here's a math problem, I want your reasoning first, then the answer" which is what I assume they're doing.

It's about the claim of whether these companies could develop a similarly powerful model without larger companies building their own first, which is an important point, and it's likely not the case.

It's also about the larger companies explaining why they can't be as efficient, of course they can't, they're not just ripping the outputs of another model that someone else invested billions to train.

Distillation requires training

The most concerning is the use of these tools to detect cheaters in schools.

are the other devices waterproof

Not if it's going to keep dropping, which I think is fair to assume as people wake up to the fundamentals after the hype is done (not financial advice)

wow that's kind of crazy impressive that it can do that honestly, VLMs have gone so far, can't imagine the crazy amount of annotations they had to create to get to that level

Second group essentially is how you have to think of it

They need to sell like 300+ per single Nvidia B100 GPU lol I'm not sure they'll quite fund themselves with this

no, last stage is removing you completely from the equation

I'm sure 99% don't? Unless your abuser is a CS major

I don't expect that Mamdani will cave in to real estate lobbyists lol. What you're describing is exactly why Establishment Democrats are losing to Mamdani and his ilk (DSA)

Yes, I really don't think that such a high fraction of people get purchased for fucking 15M after one year lol

Yes, exactly this. Migrant workers, under the threat of being deported if they don't work enough, obviously can be forced to accept much worse work conditions and work-life balance.

Every drug indeed has a huge burden of proof before it is distributed to humans, including the 3 levels of FDA clinical drug trials that cost billions of dollars, as well as all the internal testing we do beforehand.

there's no benefit to anyone for being so reductive, from whichever side you're on.

As a progressive person, the constructive thing is to try to see how to harness it for good or how to fight it, it's not to pretend that it's weak. It's not weak.

I professionally use it to design pharmaceutical drugs, essentially I do my best to harness the good sides of it

"the code is not quite detail oriented enough to be AI", times are changing

Efficiency is an angle of research that's quite active, see quantization, MoE, speculative decoding, QKV cache optimizations, sparse attention, etc

the thing went from the transformer paper in 2017 to basically doing your job for you in 2026

I don't think that people relying on the tools too much is the first sign I would identify to mean the bubble is popping