721–730 of 960 posts
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Did Google actually train a new model? The cutoff dates for Gemini 3 and 2.5 are the same.
I think this simply suggests the same (or very similar) training corpora.
I can't imagine it making sense to purposefully neglect to keep a model as up-to-date as possible!
Last week there we had a customer request that landed in our support on a feature that I partially wrote and wrote a pile of public documentation on. Support engineer ran customer query through Claude (trained on our public and internal docs) and it very, very confidently made a bunch of stuff up in the response. It was quite plausible sounding and it would have been great if it worked that way, but it didn't. While…
Or did you just misuse basic terminology about LLMs and are now saying it misbehaved, likely because your org did something very bad with?
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It's not a rumor, it's confirmed by OpenAI. All "models" since 4o are actually just optimizations in prompting and a new routing engine. The actual -model- you are using with 5.1 is 4. Nothing has been pre-trained from scratch since 4o. Their own press releases confirm this. They call 5 their best new "ai system", not a new model https://openai.com/index/introducing-gpt-5/
New AI system doesn't preclude new models. I thought when GPT 5 launched and users hated it the speculation was GPT 5 was a cost cutting model and the routing engine was routing to smaller, specialized dumber models that cost less on inference? It certainly was much dumber than 4o on Perplexity when I tried it.
That this was part of it was stated outright, except maybe that they "cost less" which was left for you to infer (sorry), in their launch announcement.
Paying for pro, and setting it to thinking all the time, I saw what seemed like significant improvements, but if your requests got (mis-)routed to one of the dumber models, it's not surprising if people were disappointed.
I think they made a big mistake in not clearly labelling the responses with which of the models responded to a given request, as it made people complain about GPT 5 in general, instead of complaining about the routing.
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The SemiAnalysis article that you linked to stated: "OpenAI’s leading researchers have not completed a successful full-scale pre-training run that was broadly deployed for a new frontier model since GPT-4o in May 2024, highlighting the significant technical hurdle that Google’s TPU fleet has managed to overcome." Given the overall quality of the article, that is an uncharacteristically convoluted sentence. At the ris…
This is misleading. They had 4.5 which was a new scaled up training run. It was a huge model and only served to pro users, but the biggest models are always used as teacher models for smaller models. Thats how you do distillation. It would be stupid to not use the biggest model you have in distillation and a waste since they have the weights. The would have taken some time to calculate the efficiency gains of pretrai…
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It's not a rumor, it's confirmed by OpenAI. All "models" since 4o are actually just optimizations in prompting and a new routing engine. The actual -model- you are using with 5.1 is 4. Nothing has been pre-trained from scratch since 4o. Their own press releases confirm this. They call 5 their best new "ai system", not a new model https://openai.com/index/introducing-gpt-5/
I can believe this, Deepseek V3.2 shows that you can get close to "gpt-5" performance with a gpt-4 level base model just with sufficient post-training.
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It's not a rumor, it's confirmed by OpenAI. All "models" since 4o are actually just optimizations in prompting and a new routing engine. The actual -model- you are using with 5.1 is 4. Nothing has been pre-trained from scratch since 4o. Their own press releases confirm this. They call 5 their best new "ai system", not a new model https://openai.com/index/introducing-gpt-5/
Maybe this is just armchair bs on my part, but it seems to me that the proliferation of AI-spam and just general carpet bombing of low effort SEO fodder would make a lot of info online from the last few years totally worthless. Hardly a hot take. People have theorized about the ouroboros effect for years now. But I do wonder if that’s part of the problem
I have (rather, had) a paid subscription to ChatGPT. I work at my home in the Sierra foothills, and on alternate weeks in my office in San Jose. Last month, I used ChatGPT while in SJ. I needed a function that's only available to paying customers, and which had worked well from my home. ChatGPT refused to recognize me as a paid-up customer. I had correct login creds + ancillary identifying info, but no go. Over the c…
How do you handle family obligations and a super commute like that?
It averages 3.25hrs one way, or about 13 hrs/month, given my every other week schedule. It's a little tiring, but doable.
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I can believe this, Deepseek V3.2 shows that you can get close to "gpt-5" performance with a gpt-4 level base model just with sufficient post-training.
Deepseek scores Gold at IMO and IOI while GPT-5 scores Bronze. OpenAI now has to catch up to china.
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I am a novice programmer -- I have programmed for 35+ years now but I build and lose the skills moving between coder to manager to sales -- multiple times. Fresh IC since last week again :) I have coded starting with Fortran, RPG and COBOL and I have also coded Java and Scala. I know modern architecture but haven't done enough grunt work to make it work or to debug (and fix) a complex problem. Needless to say sometim…
> I was more prepared and asked it to improve class by class, and for whatever reasons I got better answers There is a learning curve with all of the LLM tools. It's basically required for everyone to go through the trough of disillusionment when you realize that the vibecoding magic isn't quite real in the way the influencers talk about it. You still have to be involved in the process, steer it in the right directio…
In other areas, it is as you say and you need to be on top of it constantly.
You're absolutely right re: the learning curve, and you're much more likely to hit an area where you need to be on top of it than one that it can do autonomously, at least without a lot of scaffolding in the form of sub-agents, and rules to follow, and agent loops with reviews etc., which takes a lot of time to build up, and often include a lot of things specific to what you want to achieve. Sorting through how much effort is worth it for those things for a given project will take time to establish.
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SemiAnalysis said it last week and AFAIK it wasn't denied. https://newsletter.semianalysis.com/p/tpuv7-google-takes-a-s...
The SemiAnalysis article that you linked to stated: "OpenAI’s leading researchers have not completed a successful full-scale pre-training run that was broadly deployed for a new frontier model since GPT-4o in May 2024, highlighting the significant technical hurdle that Google’s TPU fleet has managed to overcome." Given the overall quality of the article, that is an uncharacteristically convoluted sentence. At the ris…