311–320 of 392 posts
https://meta.ai/share/pe4HxOfv2Bp Finding a little bit tricky to evaluate because the harness is unfortunately very, very bad (e.g. search is awful). Can't wait to try this in some real external services where we can see how it performs for real. Definitely getting ordinary high-quality results, overall. But hard to test agentic behavior and hard to test prose quality, even, when just working off of the default chat…
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What people seem to miss is that they don't need to get the investment back from people, they will get it from machines.
Could you explain how you think that's going to work? Because to me it seems that until machines have bank accounts, there's no money for them to get.
Comes impressively close to GPT 5.4 / Gemini 3.1 Pro / Opus 4.6! Mostly behind OpenAI on coding/agentic benchmarks, behind Google on text reasoning, behind Anthropic on Humanity's Last Exam with tools (surprisingly the only benchmark where Anthropic leads currently). Meta hasn’t fully caught up, but they came close and I think can solidly claim to be a frontier lab again. I’d call it a 3.5 horse race right now, and h…
Unfortunately with LLMs everything is based off your use case, domain and the context you give it. I also use Grok daily for health questions as the other models are too afraid to give input on medical matters
This really reinforces the idea that the AI race and the Railroad Mania of the 19th century are very similar. So many different companies are going to have similarly powerful ai that there will be no moat around it and it will be cheap. They will never earn their investment back.
> Muse Spark is a natively multimodal reasoning model with support for [...] visual chain of thought [...]. Do they mean "the chain of thought is visible to the user" (ie. not hidden like ChatGPT), or "the medium of the chain of thought is not text, but visuals" (ie. thinking in images). I'd guess the former, since it wouldn't be economical to generate transient images, just for thinking. But I'm not sure why they'd…