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Muse Spark: Scaling towards personal superintelligence

ai.meta.com

251–260 of 392 posts

Re: Muse Spark: Scaling towards personal superintelligence

#251

I would like someone to tell me how stupid I am. If I were Meta/Zuck I'd open source a great model the moment my company developed it. This just looks like a pitch to investors, otherwise.

"This just looks like a pitch to investors" The goal of public companies is generally to generate profit for their investors.

pitch to investors sounds like working for the opposite goal though - to convince investors to give more money to the company.

Re: Muse Spark: Scaling towards personal superintelligence

#253

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.

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.

Re: Muse Spark: Scaling towards personal superintelligence

#254
> 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 highight that in that case. If it were the second thing, that'd be extremely interesting. The first model not to think in text.

Re: Muse Spark: Scaling towards personal superintelligence

#255
Perhaps I'm wrong, but definitely seems to be SOTA. Although looking at it's ARC-AGI-2 score it's reasoning isn't very good. I suspect it's got the benefits of scale but lacks that human added element, understandable considering they claim to be building it from the ground up. This should come in time if they have a good team. In real life, I'd imagine one would worry about overfitting when using it.

(I'm not using it as I'm not agreeing to their ad terms).

Re: Muse Spark: Scaling towards personal superintelligence

#256

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…

It's looking rather low on reasoning and long-range problems with the approach described. For example, even with 16 agents and compaction, the HLE score is significantly below Anthropic's Mythos. Like you, I can see the release as a net Good Thing, but apples-to-apples for each org's latest models do have Meta holding steady in the middle pack.

Re: Muse Spark: Scaling towards personal superintelligence

#257
post #92

I don't get the comments trashing this. If it slightly beats or even matches Opus 4.6, it means Meta is capable of building a model competitive with the leading AI company. Sure, they spent a lot of money and will have on-going costs. But how much more work would it take to turn that into a coding agent people are willing to try (and pay for) along side their usage of a collection of agents (Claude, Codex, etc)? Also…

Because bots and trillion dollar ipos and even bigger stakes. People need to better appreciate the level of manipulation going on. Social media has an outsized impact. Bots and even people are getting paid to post and upvote/downvote narratives.

Re: Muse Spark: Scaling towards personal superintelligence

#258
post #239
post #70

Earlier quoted context omitted.

Playing with this some more and it's actively not good. Just basic mathematical errors riddling responses. Did some basic adversarial testing where its responses are analyzed by Gemini and Gemini is finding basic math errors across every relatively (relative to Opus, Gemini or GPT can handle) simple ask I make. Yikes.

Post actual results, make a blog post. Don't just say "this sucks" without tangible evidence. Otherwise you're doomed to "sample size of one" level of relevance.

I have the opposite experience: random HN/Reddit comments saying “this sucks” or “whoa this is a huge improvement” are the only benchmark that means anything. Standard benchmarks are all gamed and don’t capture the complexity of the real world.

Re: Muse Spark: Scaling towards personal superintelligence

#259

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…

It's looking rather low on reasoning and long-range problems with the approach described. For example, even with 16 agents and compaction, the HLE score is significantly below Anthropic's Mythos. Like you, I can see the release as a net Good Thing, but apples-to-apples for each org's latest models do have Meta holding steady in the middle pack.

HLE encompasses very hard problems where the larger pretraining of Mythos probably matters quite a bit. I'm not saying that Mythos is not showing some amount of genuine improvement compared to e.g. the latest Opus; just that if you're going to compare models, you should at least make sure that the overall test-time workload is in the same ballpark given how high it seems to be for Mythos.

Re: Muse Spark: Scaling towards personal superintelligence

#260

Earlier quoted context omitted.

I'll cosign what you said, simultaneously, yr interlocutor's point is also well-founded and it depresses me it's not better known and sounds so...off...due to conventional wisdom x God King Zuck's misunderstanding his own company and resulting overreaction. They beat Gemini 2.5 Flash and Pro handily on my benchmark suite. (tl;dr: tool calling and agentic coding). Llama 4 on Groq was ~GPT 4.1 on the benchmark at ~50%…

Your comments seem to imply the engineers made a great product but Zuck intervened so now it's shit

I don't know how Zuck intervening could change float32s in a trained model, so I don't think I think that, but maybe I'm parsing your words incorrectly.
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