Out of curiosity - do you think your opinion will change once on-device (i.e., power efficient) AI becomes the norm?
The capabilities and utility of contemporary LLMs are wildly overstated by many, but the claim that they are completely useless is dubious imo. Nothing they generate can be treated as fact (and shame on those who suggest you do), but I can say with certainty that it has made my life as an indie programmer much easier, and I know I’m not alone in that.
Sports are much older than the concept of a “ruling class”.
The argument that they are used as a distraction in capitalist societies does not detract from how central they are to the human condition. Hell, games aren’t even specific to humans
Hah, cool fantasy bro. GPT-9’s first output was
As an AI, I cannot predict whether humans can solve climate change. Is there anything else you would like help with?
Alignmentmaxxed
I really hope that on-device AI becomes competitive soon. It’s nice to see that on-device is the way large portions of the industry is going, but cloud AI just uses way too much energy. Not to mention the resources required to manufacture millions of large-die GPUs.
It’s probably naive to think that the corporations that created this problem will solve it, but it honestly seems like the most feasible path forward in the near term. I certainly don’t expect the world’s governments to be effective at regulating AI any time soon.
It has bad games 😎
What not playing ARMS does to a mf
Yeah I completely agree with you there. I really don’t like the way AI is being monetized and commercialized; it all just seems poised to go terribly. Ideally there shouldn’t be any incentive to overstate the capabilities of these models, as doing so just makes everything worse.
Not to be confused with Microsoft Copilot, which I have yet to find a use for. Do you not like GH Copilot either?
That GitHub Copilot and friends are useful? I would argue that their utility is rather subjective, but there are indications that it improves developer productivity.
I’m unsure if you’ve used tools like GH Copilot before, but it primarily operates through “completions” (“spicy autocorrect” in its truest form) rather than a chatbot-like interface. It’s mostly good for filling out boilerplate and code that has a single obvious solution; not game-changing intelligence by any means, but useful in relieving the programmer of various menial tasks.
May I ask, what evidence are you hoping to see in particular?
It doesn’t do that, either. LLMs retain the linguistic patterns found in textbooks, nothing more. It’s remarkable that they can do so much with this information alone, but it’s still a far cry from genuine intelligence.
I mean, it’s not shit at everything; it can be quite useful in the right context (GitHub Copilot is a prime example). Still, it doesn’t surprise me that these first-party LLM benchmarks are full of smoke and mirrors.
I guess I don’t live in a place where that happens frequently. Let me turn this around for a moment and ask you the same question you asked earlier:
How many ruined lives for this to be a concern to you?
I’m sorry?