121–130 of 1001 posts
A lot of skepticism here, but these are astonishing results! People should realize we’re reaching the point where LLMs are surpassing humans in any task limited in scope enough to be a “benchmark”. And as anyone who’s spent time using Claude 3.5 Sonnet / GPT-4o can attest, these things really are useful and smart! (And, if these results hold up, O1 is much, much smarter.) This is a nerve-wracking time to be a knowled…
Sounds great, but so does their "new flagship model that can reason across audio, vision, and text in real time" announced in May. [0] [0] https://openai.com/index/hello-gpt-4o/
after weighing multiple factors including user experience, competitive advantage, and the option to pursue the chain of thought monitoring, we have decided not to show the raw chains of thought to users.
> Therefore, after weighing multiple factors including user experience, competitive advantage, and the option to pursue the chain of thought monitoring, we have decided not to show the raw chains of thought to users.
Mentioning competitive advantage here signals to me that OpenAI believes there moat is evaporating. Past the business context, my gut reaction is this negatively impacts model usability, but i'm having a hard time putting my finger on why.
> We have found that the performance of o1 consistently improves with more reinforcement learning (train-time compute) and with more time spent thinking (test-time compute). Wow. So we can expect scaling to continue after all. Hyperscalers feeling pretty good about their big bets right now. Jensen is smiling. This is the most important thing. Performance today matters less than the scaling laws. I think everyone has…
That naming scheme... Will the next model be named "1k", so that the subsequent models will be named "4o1k", and we can all go into retirement?
The model performance is driven by chain of thought, but they will not be providing chain of thought responses to the user for various reasons including competitive advantage. After the release of GPT4 it became very common to fine-tune non-OpenAI models on GPT4 output. I’d say OpenAI is rightly concerned that fine-tuning on chain of thought responses from this model would allow for quicker reproduction of their resu…
Earlier quoted context omitted.
And Apple's product line this year? Phones. Nothing to do with fruit. Almost 50 years of lying to people. Names should mean something!
Did Apple start their company by saying they will be selling apples?
But arguments like "you wrote $x in a blog post when you founded your company" or "this is what the word in your name means" are infantile.
after weighing multiple factors including user experience, competitive advantage, and the option to pursue the chain of thought monitoring, we have decided not to show the raw chains of thought to users.
There must be some magic sauce here for guiding LLMs which boosts performance. They must think inspecting a reasonable number of chains would allow others to replicate it.
They call GPT 4 a model. But we don't know if it's really a system that builds in a ton of best practices and secret tactics: prompt expansion, guided CoT, etc. Dalle was transparent that it automated re-generating the prompts, adding missing details prior to generation. This and a lot more could all be running under the hood here.