It has progressed. The tech is just expensive and heavy and... all sorts of tradeoffs. Meta had a prototype (Boba) with a 180 horizontal and 120 vertical FoV
But it of course is large and heavy like the quest pro and expensive most likely. Things that when you market to consumers don't pan out.
So they are optimizing on the other dimension (weight) which of course trades of many other dimensions.
All anthropic launches are like this. They just post it and don't particularly put out the PR sprint that OpenAI does with videos, livestreams or whatever.
(Except for of course Mythos and whatnot when they want to push the whole "safety" thing)
Small quirks can quickly add up in posttraining if not caught. Although TBH with how obvious Claude language is, I do feel like this is something Anthropic probably noticed and just assumed people would not care about. Now that people have obviously cared, they're probably actively looking to alleviate it
But also effectively this is a classification model. It excels at specific certain types of workloads, and obviously will fail at others. Not really sure how one benchmarks this tbf. I can see their argument on why this requires a novel specific eval for whatever your usecase is. A consistent "global" benchmark might be hard to do
You're fooling yourself if the quest provides any advertising data value, let alone 600$ The device is simply just being sold for as a loss and is not a data harvesting operation.
Some quick googling shows the ARPU of a meta user is approx 57$ a year, and ~65$ in NA. Even if the quest provided useful advertising data (it doesn't) it would never come close to 600$ over the lifetime of a user.
I don't even understand what you mean by "biometric data" for advertising purposes. What biometric data is the quest collecting? How in the world is biometric data useful for advertising?
There's a reason why Meta is tens of billions of dollars in the hole for reality labs. It's not to subsidize for advertising that's for sure.
Eh I mean this is common default no? If you inspect element on many sites it links to the career page. Reddit, discord, etc.
Maybe a little distasteful since I suppose since these WordPress sites are not owned by WordPress, but I wouldn't really say it's unique or necessarily poaching
You should use their harness. They trained it on multiple harnesses but have specifically optimized it for their harness. Cline also did an independent experiment w spark 1.2 where using the native harness makes it use fewer tokens / turns to accomplish tasks
> Co-trained with the harness. Muse Code was in the training loop from day one, so tool calls succeed and plans execute cleanly. Crucially, we trained across multiple harnesses, so while the model is at its best in Muse Code, it still generalizes to other coding agents you already use.
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