Live data from Hacker News

Muse Spark: Scaling towards personal superintelligence

ai.meta.com

221–230 of 392 posts

Re: Muse Spark: Scaling towards personal superintelligence

#225

Meta is in a weird spot. They caught up late to the game and instead of releasing llama as a chat bot they open sourced it, precisely because they lost the mind share. They thought chatbot is not their product and I am sure they are regretting it now. Mark is obsessed with becoming the android of something and he poured billions into the metaverse thinking he is first and failed. He then open sourced llama and wanted…

> ended up enabling groq

For those reading fast, this isn't a reference to SpaceX's Grok, this is Groq.com - with its custom inference chip, and offerings like https://groq.com/blog/introducing-llama-3-groq-tool-use-mode... and https://console.groq.com/landing/llama-api

Re: Muse Spark: Scaling towards personal superintelligence

#228

Litmus test: what % of meta engineers are using muse vs Claude code? Last i heard it was mostly claude code. Tell you everything you need to know about how serious these benchmarks are.

Sure it's not as good as Claude right now but for their first model in years it's certainly not bad. I hope they continue to develop models, having another competitor in the space would be nice.

Re: Muse Spark: Scaling towards personal superintelligence

#229
post #98

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...

Someday our robot overlords will be intelligent enough to ... optimize images! (But today is not that day.)

The proper optimization in this case is to not use images at all.

Re: Muse Spark: Scaling towards personal superintelligence

#230

How is that Meta spent so much money for talent and hardware, but the model barely matches Opus 4.6? Especially, looking at these numbers after Claude Mythos, feels like either Anthropic has some secret sauce, or everyone else is dumber compared to the talent Anthropic has

Anthropic has just been focused on coding/terminal work longer mostly, and their PRO tier model is coding focused, unlike the GPT and Gemini pro tier models which have been optimized for science. Their whole "training the LLM to be a person" technique probably contributes to its pleasant conversational behavior, and making its refusals less annoying (GPT 5.2+ got obnoxiously aligned), and also a bit to its greater au…

Autonomy for agentic workflows has nothing to do with "replying more like a person", you have to refine the model for it quite specifically. All the large players are trying to do that, it's not really specific to Anthropic. It may be true however that their higher focus on a "Constitutional AI"/RLAIF approach makes it a bit easier to align the model to desirable outcomes when acting agentically.
Post reply on HN