The hero image on the linked page, which consists of a muted teal background with the words "Introducing Muse Spark", weighs in at 3,5MB. I don't even...
complaining about sand on the beach
It's not sand on the beach, it's garbage on the beach.
Muse Spark: Scaling towards personal superintelligence
151–160 of 392 posts
Re: Muse Spark: Scaling towards personal superintelligence
#152Earlier quoted context omitted.
I’m not sure. If it was open source, certainly. But 4th place doesn’t really matter if you have nothing different to add.
Fourth place means you're not reliant on any of the external providers for internal AI use, which is important for organizational health and negotiating with those other providers.
I’m not sure it’s useful for negotiating, the capex to build it was surely orders of magnitude more than it would cost to just use one of the other frontier models.
It’s like someone negotiating by saying, “I’ll waste even MORE money to build something worse if you don’t give me a deal.”
I’m not discounting there may be other advantages to doing it. I just don’t think negotiating is one.
Re: Muse Spark: Scaling towards personal superintelligence
#153This would have been an amazing release 6 months ago. But the industry moves so fast, this is a trite release. Maybe it’s best for Meta to sell their superintelligence division. I don’t think Zuck’s vision is particularly compelling.
I never understood why meta decided to join the race. They don’t sell compute like Google or Microsoft. Why not let others do the hard work and integrate their LLMs in your systems if needed? I assume it’s because they have Instagram, Facebook, WhatsApp, Thread data and feel they should be the ones using them for training, but it’s really not obvious how having a frontier AI lab benefits their business
> I never understood why meta decided to join the race.
I can think of at least two reasons. Price and customizability. If they train their own models on their own data, they potentially have a better model at a better price, and they're not at the mercy of Anthropic's decisions when they decide to raise prices. Additionally, if you use someone else's model, you use it the way they create it and permit you to use it. In a couple years, who has any idea how these models are used. Arguably, a company the size of Meta should be in control of their AI models.
Re: Muse Spark: Scaling towards personal superintelligence
#154This would have been an amazing release 6 months ago. But the industry moves so fast, this is a trite release. Maybe it’s best for Meta to sell their superintelligence division. I don’t think Zuck’s vision is particularly compelling.
I never understood why meta decided to join the race. They don’t sell compute like Google or Microsoft. Why not let others do the hard work and integrate their LLMs in your systems if needed? I assume it’s because they have Instagram, Facebook, WhatsApp, Thread data and feel they should be the ones using them for training, but it’s really not obvious how having a frontier AI lab benefits their business
Only thanks to Meta we have competitive local LLMs. Without LLama nothing decent would have been released. Commoditize your complements in action.
Re: Muse Spark: Scaling towards personal superintelligence
#155The hero image on the linked page, which consists of a muted teal background with the words "Introducing Muse Spark", weighs in at 3,5MB. I don't even...
lol it literally took me 2s to google search "optimize image for website" and 10s to upload and get a smaller sized image. The result for that specific image is: 500kb. 85% decrease in size
You can even automatically do that on your CDN/delivery/web server layer. Or as part of your web deployment pipeline.
Re: Muse Spark: Scaling towards personal superintelligence
#156Saying nothing about the actual performance of this model, it does strike me how .... minimal(?) this announcement is. Their safety section is like 2 paragraphs about bioweapons. Go look at the reports for OpenAI and Anthropic's model releases. It's like 50+ pages of tests, examples, reports, and benchmarks across a bunch of safety and wellfare metrics. If Meta wants to be seen as a cutting edge massive lab they need…
Rumor on the ground is that they expected a much stronger model than this one.
Re: Muse Spark: Scaling towards personal superintelligence
#157Earlier quoted context omitted.
They really weren't horrible. They were ~gpt4o, with the added benefit that you could run them on premise. Just "regular" models, non "thinking". Inefficient architecture (number of active out of total) but otherwise "decent" models. They got trashed online by bots and chinese shills (I was online that weekend when it happened, it's something to behold). Just because they were non-thinking when thinking was clearly t…
Nah I remember how disgusted I felt trying llama 4 maverick and scout. They were both DOA.. couldn't even beat much smaller local models.
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% the cost.
They shouldn't have released it on a Saturday.
They should have spent a month with it in private prerelease, working with providers.[1]
The rushed launch and ensuing quality issues got rolled into the hypebeast narrative of "DeepSeek will take over the world"
I bet it was super fucking annoying to talk to due to LMArena maxxing.
[1] my understanding is longest heads up was single-digit days, if any. Most modellers have arrived at 2+ weeks now, there's a lot between spitting out logits and parsing and delivering a response.
Re: Muse Spark: Scaling towards personal superintelligence
#158NOTHING about this is personal! No weights were released!
Re: Muse Spark: Scaling towards personal superintelligence
#159Earlier quoted context omitted.
I never understood why meta decided to join the race. They don’t sell compute like Google or Microsoft. Why not let others do the hard work and integrate their LLMs in your systems if needed? I assume it’s because they have Instagram, Facebook, WhatsApp, Thread data and feel they should be the ones using them for training, but it’s really not obvious how having a frontier AI lab benefits their business
LLMs/Chat-based systems will reach a point where Facebook, WhatsApp, Threads, Instagram, etc. are all unnecessary. The idea of opening a browser or a specific app to do a thing will seem antiquated. You can do it all with your chat-based agent. Meta wants to be part of that.
Sure but they have the platforms, they don’t need their own frontier models for that
Re: Muse Spark: Scaling towards personal superintelligence
#160Earlier quoted context omitted.
the models were objectively horrible
They really weren't horrible. They were ~gpt4o, with the added benefit that you could run them on premise. Just "regular" models, non "thinking". Inefficient architecture (number of active out of total) but otherwise "decent" models. They got trashed online by bots and chinese shills (I was online that weekend when it happened, it's something to behold). Just because they were non-thinking when thinking was clearly t…
Wrote longer comment steel-manning this, posted it to a reply, then realized you might like to know they had a reasoning model on deck ready for release in the next 2-4 weeks.
Got shitcanned due to bad PR & Zuck God-King terraforming the org, so there'd be a year delay to next release.
Real tragi-comedy, and you have no idea how happy it makes me to see someone in the wild saying this. It sounds so bizarre to people given the conventional wisdom, but, it's what happened.