emtel

Your comment is nothing but supposition

A lot of the commenters here are still living in early 2026. Late 2026 AI can absolutely demolish this kind of job. It can clone photoshop! You think this is going to be harder than that?

I don’t know why you’re getting downvoted. One of my coworkers who was constantly touting Chinese models a few months ago now only uses opus 5.5. It is a huge difference.

Unless new data has come out, we don’t know if they are losing money on subscriptions. We know that there is a big difference between subscription and API costs per token, but that alone doesn’t mean much. Subscriptions may be underutilized, or margins on API tokens may be very high. Both are probably true.

This debate conflates two senses of the word deterministic:

1. Repeatable: the same inputs always lead to the same outputs 2. Algorithmic: the answer is arrived at by a set of steps that can clearly be shown to produce output with some desired property.

(2 is not a textbook definition of deterministic that I’ve ever heard, but I think it’s what people mean here)

LLMs don’t usually satisfy definition 1. They could, in principle, but it wouldn’t matter if they did. It wouldn’t tell you anything about whether the outputs are trustworthy.

What people seem to want is 2, but 2 is, I think, a contradiction. There cannot be an algorithmic process that can turns a natural language prompt into a working program, because natural language is too ambiguous to specify an output.

Nevertheless I agree with the main point of the article. Non-algorithmic processes (like intelligence) can produce algorithmic processes (like software). After all that’s what human programmers do!

It means that NNs don't (as previously thought) smoosh unrelated concepts together into the same neurons, which would have made interpretability very difficult.

For instance, if you had a single neuron that fires for "puppies" and "murder", it would be much more difficult to tell if the model is thinking something nice or something not so nice.

I’m not entirely unsympathetic to this view, but man. AI is here. It’s not going away. You may as well lament the fact that people use cars instead of horses.

The better use of your time is to start thinking about what new opportunities have opened up because of this. With AI coding your only limit is your imagination. Don’t waste it by sitting around and whining.

No evidence other than the fact that this has been happening steadily in all areas for many years?

You might have a point if the goal was to have LLMs that spit out a correct proof without chain of thought or tool use. LLMs + agent harnesses are more than capable of self verification and course correction.

There’s a small cottage industry of people who now have careers built on telling people that AI is a grift. Bender, Ed Zitron, Gary Marcus, etc. And there is a large audience who wants to hear this message.

What is troubling to me is I can’t think of a single prominent AI skeptic who has changed their mind. Are there any?

Are you serious? Lots of people disagree with what you are saying.

Today’s current problems were all hypothetical several years ago. At that time people claimed that the “real pressing problems” were misinformation and DEI issues. If we pretend that hypothetical problems can be safely ignored because there’s “no evidence” that they are real, we will keep getting surprised.

As far as I can tell, neither of the frontier US labs have referred to distillation as "stealing", but someone please provide a link if I'm wrong.

They do claim that it violates their ToS, which we can assume is simply correct, since they get to put whatever they want in their ToS.

Given all that, I don't know what the fuss is. Are they supposed to not use the advances that were openly published by Chinese labs? The entire industry is built on a discovery made at Google, which was published openly. Should Chinese labs therefore not use transformers? Should US labs not try to prevent distillation of their models?

You’re technically correct, but the vast majority of software has never been built to the kinds of standards you are describing. LLMs are not displacing that kind of work!

There is no limited supply of batteries. Production is growing and prices are declining rapidly.

Do you think people should continue developing AI up until the point that there is evidence that AI is facilitating biological weapons development?

I think we should stop before then. But that necessarily means that there will not be evidence at the time that we stop.