461–470 of 1001 posts
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I feel like if I attempted this, the bike frame would look fine and everything else would be completely unrecognizable. After all, a basic bike frame is just straight lines arranged in a fairly simple shape. It's really surprising that models find it so difficult, but they can make a pelican with panache.
Humans are also famously bad at drawing bicycles from memory https://www.gianlucagimini.it/portfolio-item/velocipedia/
This model is great at long horizon tasks, and Codex now has heartbeats, so it can keep checking on things. Give it your hardest problem that would take hours with verifiable constraints, you will see how good this is:) *I work at OAI.
It's genuinely so great at long horizon tasks! GPT-5.5 solved many long-horizon frontier challenges, for the first time for an AI model we've tested, in our internal evals at Canva :) Congrats on the launch!
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Worst case? I dunno, maybe the world's oldest profession becomes the world's only profession? Something along those lines.
> the world's oldest profession becomes the world's only profession Until the sexbots come out the other side of the uncanny valley, that is.
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…
Do it, I'm game! You nerdsniped me immediately and my brain went "That sounds easy, I'm sure I could do that in a night" so I'm surely not alone in being almost triggered by what you wrote. I bet I could even do it with a local model!
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Well, they obviously are going to say that, they have vested interest in OpenAI and thus Nvidia stock price growing. Also, I honestly can’t believe the 10x mantra is being still repeated.
> Also, I honestly can’t believe the 10x mantra is being still repeated. I'm sure in 20 years we'll all be programming via neural interfaces that can anticipate what you want to do before you even finished your thoughts, but I'm confident we'll still have blog posts about how some engineers are 10x while others are just "normal programmers".
https://www.nytimes.com/2026/04/23/technology/openai-new-model.html
However, this same-day article came out before people really looked at it. It seems largely intended to contrast OpenAI with Anthropic's caution, before there has been any evidence that the new model has cyber-security implications.
It's not at all clear that the broader discourse is helping, if even the NY Times is itself producing slop just to stoke questions.
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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…
How are you handing the cube state to the model?
Earlier quoted context omitted.
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…
How are you handing the cube state to the model?
Opus 4.6 got the cross and started to get several pieces on the correct faces. It couldn't reason past this. You can see the prompts and all the turn messages.
https://gist.github.com/adam-s/b343a6077dd2f647020ccacea4140...
edit: I can't reply to message below. The point isn't can we solve a Rubik's Cube with a python script and tool calls. The point is can we get an LLM to reason about moving things in 3 dimensions. The prompt is a puzzle in the way that a Rubik's Cube is a puzzle. A 7 year old child can learn 6 moves and figure out how to solve a Rubik's Cube in a weekend, the LLM can't solve it. However, can, given the correct prompt, a LLM solve it? The prompt is the puzzle. That is why it is fun and interesting. Plus, it is a spatial problem so if we solve that we solve a massive class of problems including huge swathes of mathematics the LLMs can't touch yet.
> 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…
> 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…
One might argue that it’s not too too different from higher level abstractions when using libraries. You get things done faster, write less code, library handles some internal state/memory management for you. 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 g…
When you use abstractions you are still deterministically creating something you understand in depth with individual pieces you understand.
When you vibe something you understand only the prompt that started it and whether or not it spits out what you were expecting.
Hence feeling lost when you suddenly lose access to frontier models and take a look at your code for the first time.
I’m not saying that’s necessarily always bad, just that the abstraction argument is wrong.