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There's a huge price difference between o3-mini and o1 ($4.40 vs $60 per million output tokens), what trade-offs in performance would justify such a large price gap? Are there specific use cases where o1's higher cost is justified anymore?
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LLMs give programmers an extraordinary productivity boost, but are much less effective for people who don't have a programming mindset.
It might help more people gain that mindset, but ai welcome that: it's not like there's any shortage of problems in the world that benefit from being automated by computers.
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I've seen enough now that I no longer worry that LLMs getting better at code will threaten my job. LLMs give programmers an extraordinary productivity boost, but are much less effective for people who don't have a programming mindset. It might help more people gain that mindset, but ai welcome that: it's not like there's any shortage of problems in the world that benefit from being automated by computers.
The smart thing to do as programmers is to keep trying to automate more of our work, but there's no guarantee that it will be like this in the future.
A lot of this post resonated with me: https://youtubetranscriptoptimizer.com/blog/05_the_short_cas... It doesn't argue that demand for video cards will be exhausted, but that it won't be as white hot as it is now. I can see the same with the top tier of programming talent. There isn't any shortage of problems that you could throw compute at and it's the same for top-tier programming talent, but does the market need it right away at any cost?
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Earlier quoted context omitted.
I've seen enough now that I no longer worry that LLMs getting better at code will threaten my job. LLMs give programmers an extraordinary productivity boost, but are much less effective for people who don't have a programming mindset. It might help more people gain that mindset, but ai welcome that: it's not like there's any shortage of problems in the world that benefit from being automated by computers.
That reads like an OpenAI talking point. The smart thing to do as programmers is to keep trying to automate more of our work, but there's no guarantee that it will be like this in the future. A lot of this post resonated with me: https://youtubetranscriptoptimizer.com/blog/05_the_short_cas... It doesn't argue that demand for video cards will be exhausted, but that it won't be as white hot as it is now. I can see the…
There's a huge price difference between o3-mini and o1 ($4.40 vs $60 per million output tokens), what trade-offs in performance would justify such a large price gap? Are there specific use cases where o1's higher cost is justified anymore?
Long tail stuff perhaps. Most stuff doesn't resemble a programming benchmark. A newer model thrives despite being small when there is a lot of training data, and with programming benchmarks, like with chess, there is a lot of training data, in part because high quality training data can be synthesized.
Earlier quoted context omitted.
That reads like an OpenAI talking point. The smart thing to do as programmers is to keep trying to automate more of our work, but there's no guarantee that it will be like this in the future. A lot of this post resonated with me: https://youtubetranscriptoptimizer.com/blog/05_the_short_cas... It doesn't argue that demand for video cards will be exhausted, but that it won't be as white hot as it is now. I can see the…
if you check GP, you might agree he is very helpful. Btw, he is the author of the article posted.