341–350 of 1001 posts
Note it's not available to everyone yet: > GPT-5 Rollout > We are gradually rolling out GPT-5 to ensure stability during launch. Some users may not yet see GPT-5 in their account as we increase availability in stages.
So models are getting pretty good at oneshotting many small project ideas I've had. What's a good place to host stuff like that? Like a modern equivalent of Heroku? I used to use a VPS for everything but I'm looking for a managed solution. I heard replit is good here with full vertical integration, but I haven't tried it in years.
Watching the livestream now, the improvement over their current models on the benchmarks is very small. I know they seemed to be trying to temper our expectations leading up to this, but this is much less improvement than I was expecting
It is frequently suggested that once one of the AI companies reaches an AGI threshold, they will take off ahead of the rest. It's interesting to note that at least so far, the trend has been the opposite: as time goes on and the models get better, the performance of the different company's gets clustered closer together. Right now GPT-5, Claude Opus, Grok 4, Gemini 2.5 Pro all seem quite good across the board (ie the…
> 400,000 context window > 128,000 max output tokens > Input $1.25 > Output $10.00 Source: https://platform.openai.com/docs/models/gpt-5 If this performs well in independent needle-in-haystack and adherence evaluations, this pricing with this context window alone would make GPT-5 extremely competitive with Gemini 2.5 Pro and Claude Opus 4.1, even if the output isn't a significant improvement over o3. If the output qu…
gpt-4.1 family had 1M/32k input/output tokens. Pricing-wise, it's 37% cheaper input tokens, but 25% more expensive on output tokens. Only nano is 50% cheaper on input and unchanged on output.
Going by the system card at: https://openai.com/index/gpt-5-system-card/ > GPT‑5 is a unified system . . . OK > . . . with a smart and fast model that answers most questions, a deeper reasoning model for harder problems, and a real-time router that quickly decides which model to use based on conversation type, complexity, tool needs, and explicit intent (for example, if you say “think hard about this” in the prompt).…
Still only 256k input tokens/context. Do they not see utility in larger context?
I would like to see a demo where they go through the bug, explain what are the tricky parts and show how this new model handle these situations.
Every demo I've seen seems just the equivalent of "looks good to me" comment in a merge request.
Damn, you guys are toxic. So -- they did not invent AGI yet. Yet, I like what I'm seeing. Major progress on multiple fronts. Hallucination fix is exciting on its own. The React demos were mindblowing.
its not a "fix"