451–460 of 1001 posts
For a 56.7 score on the Artificial Intelligence Index, GPT 5.5 used 22m output tokens. For a score of 57, Opus 4.7 used 111m output tokens. The efficiency gap is enormous. Maybe it's the difference between GB200 NVL72 and an Amazon Tranium chip?
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This brings up an interesting philosophical point: say we get to AGI... who's to say it won't just be a super smart underachiever-type? "Hey AGI, how's that cure for cancer coming?" "Oh it's done just gotta...formalize it you know. Big rollout and all that..." I would find it divinely funny if we "got there" with AGI and it was just a complete slacker. Hard to justify leaving it on, but too important to turn it off.
It would be funny but not very flywheel so the one that gets there is more likely to get a gunner.
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Did you guys do anything about GPT‘s motivation? I tried to use GPT-5.4 API (at xhigh) for my OpenClaw after the Anthropic Oauthgate, but I just couldn‘t drag it to do its job. I had the most hilarious dialogues along the lines of „You stopped, X would have been next.“ - „Yeah, I‘m sorry, I failed. I should have done X next.“ - „Well, how about you just do it?“ - „Yep, I really should have done it now.“ - “Do X, righ…
This brings up an interesting philosophical point: say we get to AGI... who's to say it won't just be a super smart underachiever-type? "Hey AGI, how's that cure for cancer coming?" "Oh it's done just gotta...formalize it you know. Big rollout and all that..." I would find it divinely funny if we "got there" with AGI and it was just a complete slacker. Hard to justify leaving it on, but too important to turn it off.
I've found myself so deeply embedded in the Claude Max subscription that I'm worried about potentially makign a switch. How are people making sure they stay nimble enough not to get trarpped by one company's ecosystem over another? For what it's worth, Opus 4.7 has not been a step up and it's come with an enormously higher usage of the subscription Anthropic offers making the entire offering double worse.
> One engineer at NVIDIA who had early access to the model went as far as to say: "Losing access to GPT‑5.5 feels like I've had a limb amputated.” This quote is more sinister than I think was intended; it likely applies to all frontier coding models. As they get better, we quickly come to rely on them for coding. It's like playing a game on God Mode. Engineers become dependent; it's truly addictive. This matches my o…
Would one be uneasy about calling a library to do stuff than manually messing around with pointers and malloc()? For some, yes. For others, it’s a bit freeing as you can do more high-level architecture without getting mired and context switched from low level nuances.
A playable 3D dungeon arena prototype built with Codex and GPT models. Codex handled the game architecture, TypeScript/Three.js implementation, combat systems, enemy encounters, HUD feedback, and GPT‑generated environment textures. Character models, character textures, and animations were created with third-party asset-generation tools The game that this prompt generated looks pretty decent visually. A big part of th…
LLM models can not do spacial reasoning. I haven't tried with GPT, however, Claude can not solve a Rubik Cube no matter how much I try with prompt engineering. I got Opus 4.6 to get ~70% of the puzzle solved but it got stuck. At $20 a run it prohibitively expensive. The point is if we can prompt an LLM to reason about 3 dimensions, we likely will be able to apply that to math problems which it isn't able to solve cur…
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> This quote is more sinister than I think was intended; it likely applies to all frontier coding models. As they get better, we quickly come to rely on them for coding. It's like playing a game on God Mode. Engineers become dependent; it's truly addictive. What's the worst potential outcome, assuming that all models get better, more efficient and more abundant (which seems to be the current trend)? The goal of engin…
>What's the worst potential outcome, assuming that all models get better, more efficient and more abundant Complexity steadily rises, unencumbered by the natural limit of human understanding, until technological collapse, either by slow decay or major systems going down with increasing frequency.
All software has bugs already.
Earlier quoted context omitted.
> This quote is more sinister than I think was intended; it likely applies to all frontier coding models. As they get better, we quickly come to rely on them for coding. It's like playing a game on God Mode. Engineers become dependent; it's truly addictive. What's the worst potential outcome, assuming that all models get better, more efficient and more abundant (which seems to be the current trend)? The goal of engin…
>What's the worst potential outcome, assuming that all models get better, more efficient and more abundant Complexity steadily rises, unencumbered by the natural limit of human understanding, until technological collapse, either by slow decay or major systems going down with increasing frequency.
Labs still aren't publishing ARC-AGI-3 scores, even though it's been out for some time. Is it because the numbers are too embarrassing?
To be fair, there's not much to report. Isn't it pretty much at 0?
Seems meaningful even if the absolute numbers are very low. That's sort of the excitement of it.