chartpath

Not to mention they will need to research how to make their models faster and cheaper to run in order to fit some margin within what people are actually willing to pay.

Are there any indications that this will be possible? Consumer hardware will continue getting better but I can't see 512GB RAM in a MacBook Pro any time soon. I'm hoping linear attention techniques plus MoE will make breakthroughs in size/compression and throughput.

Sure, and OpenAI, Anthropic, Grokkk are totally self-made and profitable.

I find Mistral Medium 3.5 with OpenCode is perfectly fine if you're willing to talk to it in a more fine-grained way about actual code. For me that's fine because even with huge frontier models I don't like trying to vibe prompt like a product manager.

Yeah same company. Clearly they haven't improved their guardrails in the last couple months.

It's never the technology that's the problem, it's the owners and operators who decide how to use it.

We should pivot the culture to one that is pro-liberal arts again. These people know how to read and write better than STEMs in general.

CS as the only path to programming was always too narrow, and often people with a broader education are better at creative solutions. With AI-assisted programming I'd argue they have an even clearer advantage now.

Some much focus on fine-tuning when it can actively make performance on reasoning and planning benchmarks worse (over a baseline of already worse-than-coin-toss).

Why not give us nice things for integrating with knowledge graphs and rules engines pretty please?

Kind of a tangent but I'm really interested in why statements like:

> if you have carbon-based life forms, you will have water and CO2.

..can lead to statements like:

> it is just way more likely than any other form

I totally agree on the observation, but what is fascinating to me is why a deductive statement can be considered to indicate likelihood in probability. It seems there is a bit of abductive reasoning going on behind the scenes which neither the deductive logic or inductive probability can really capture on their own.

How is wealth distribution wrong? It sounds like you are arguing in favour of inequality.

There's a third kind, which is when unscrupulous business managers or politicians use it to make decisions that they would not be capable of auditing for a rationale when otherwise required to know why such a decision was made.

It's more of an ethics and compliance issue with the cost of BS and plausible deniability going to zero. As usual, it's what humans do with technology that has good or bad consequences. The tech itself is fairly close to neutral as long as training data wasn't chosen specifically to contain illegal substance or by way of copyright infringement (which isn't even the tech, it's the product).

$10k is nothing for rich people. Just putting them in debt for it doesn't mean nothing of value was provided.

The reverse would be true where poor people could be ruined, unless the value provided is worth significantly more than the debt created, which seems doubtful.

There is a lot of synthetic content about academic subjects on YT now, and it's very low quality. I used to search for lectures to listen to while walking or driving but now need to wade through tons of enshittified spam. Even if it's reading wikipedia or other long form articles, the voices and graphics are bad.

Actually I paid for Blinkist recently and really enjoyed it at first. They have a lot of "blinks" that state at the end that the voice was synthetic and I was legitimately surprised at the quality, having not even noticed until they told me.

This seems like a good move for YT to maintain a basic level of quality (which I'm amazed can actually get worse), but I suspect it's a pretext to avoid paying out to "illegitimate creators" for commercial reasons in a way that makes them look like they care about people.