Comments URL: https://news.ycombinator.com/item?id=49224054

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See e.g. corporate green and rainbow washing, Amazon marketplace, organic food.

> Astra, a new model that OpenAI is testing internally, is amazing. No denying that.

"it isn't clear whether generative AI actually provides much business value at all"

"cannot seem to find a product that people will pay for, in part because the results are so mediocre"

"Last week, we got our first real, definitive glimpse of what’s around that corner that future. And boy, was it underwhelming."

"OpenAI claims that o1 “performs similarly to PhD students on challenging benchmark tasks in physics, chemistry, and biology.” Just not in geography, it seems. Or basic elementary-level English language tests. Or math. Or programming. "

"Worse still, it's kind of hard to explain why anybody should give a shit about o1."

"o1 shows that OpenAI is both desperate and out of ideas."

"the software is not becoming more useful"

Honestly, every other line is quotable in this context.

For sight and sound, the sensory input layer for AIs is much, much richer in terms of bitrate, though is redundant.

> AIs do get linked to cameras though and could improve a lot in those directions.

Video is an interesting one, as most AI systems use the full pixel information of a scene, while human vision is much more temporal, focusing primarily on logistic deltas rather than raw pixels. That's not inherent to hardware (e.g. see event or "neuromorphic" cameras), but it's a significant difference. My more sympathetic reading of embodiment is that the relative paucity of the human sensory stream is part of what makes us work better than current AI in many domains, in that it forces us to form richer, temporal world models from a low bitrate stream of salient events instead of relying on shallow responses to rich sensory data.

This ends up driving most hard sci fi to current understanding of physics, with maybe one tweak. If you diverge more from that, it's difficult or impossible to establish the rules and their implications early on, and so choices about them later end up serving the narrative.

Though, a certain irony: hard sci-fi doesn't seem to offer much predictive insight about the future compared to other subgenres. The 20th century sci-fi genre that seems to offer the most insight into our current moment is probably the one with the wildest imaginings: cyberpunk.

Though, mostly by abandoning the field and moving to Anthropic.

The phrase to describe it is anti-AI psychosis. Which isn't about providing thoughtful critiques of AI, which are good and we need more of. But anytime an LLM does anything--prove a major math problem, create a successful hack against multiple corporations simultaneously--people feel compelled to start minimizing it in ridiculous terms. It's just a script kiddy; it's just a marketing scam OpenAI cooked up; the Jacobian conjecture counterexample was something anyone could have done in a weekend; etc. It has to just be a stochastic parrot, because it's scary to imagine a non-anthropocentric world. And it's rightly scary, and we should slow down and try to better prepare for it. But blanket denial is not a strategy that will lead to success, and people who rely on it are sorely ill-prepared for the next couple years.