Gerald McAlister (@GEMISIS) header
Gerald McAlister (@GEMISIS) profile picture

Focused on #AI #VR #AR #MR #XR #SpatialComputing | he/him | SWE @Meta | Previously @RealityLabs @amazon @alexa99 | Side projects @RGBSchemes | Opinions are mine

Seattle, WA
Joined June 2013
Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)Photo by Gerald McAlister (@GEMISIS)
Gerald McAlister retweeted
Hey folks, like a lot of people this year I've been affected by layoffs, and I'm looking for my next opportunity! I'm a Lead Unity Developer looking for a similar position. I have a decade of experience, mostly XR but in small and large teams, medical, simulation, etc. DM me!
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Gerald McAlister retweeted
Replying to @finkd
Congrats to the team! Amazing to run a model of Muse Spark Open's caliber and scale this efficiently, right from your desk. Mac Studio keeps pushing the boundaries of on-device AI!
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Gerald McAlister retweeted
Muse Spark Open -- weights releasing today -- runs great on new Mac Studios thanks to work with @johnternus and Apple.
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Gerald McAlister retweeted
somehow the corposlops refused to use my video
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Gerald McAlister retweeted
Replying to @AntonHand
If everyone will just read
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Gerald McAlister retweeted
This is a take espoused by people with a poor understanding of software architecture in my experience (I don’t know Richard so not saying anything specifically about him here, maybe he has more refined thoughts) I find it’s usually an over reaction to “agents write bad unit tests”. And instead of digging in and understanding why and how to correct… they prefer to throw it out completely The pendulum will swing the other way imho
Unit tests were for an era when the 50 percentile programmer could barely one shot a LeetCode medium. You don’t need unit tests 99 times out of 100 if you can now one shot LeetCode hards with a well-defined spec.
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Gerald McAlister retweeted
We just dropped a new paper on our Community Writer -- scaling AI-written Community Notes, with human raters in charge The Community Writer submits its notes over the same the public AI note writing API that all other AI note writers use, and altogether, AI note writing has been a huge driver of speeding up and scaling up Community Notes so far (in a way that's complementary with human note writers) The code is open sourced too so it's easier than ever now to build a great AI note writer
We're open-sourcing the Community Writer, an AI note writer designed to reflect the will of the people, which, together with the open note writing API, has helped drive an 86% increase in the number of notes on X that people from different perspectives find helpful. The Community Writer works by incorporating input from the public throughout the note writing process. We've written a technical report detailing how it works and the impact of the Note Writing API overall. And we’re making the code open-source under Apache V2 so that it can be used to advance research and scale informative context across the internet. Technical report: arxiv.org/abs/2609.40067 Code: github.com/xai-org/community…
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Gerald McAlister retweeted
Me rolling into the office with all 25 of my personal agents:
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Gerald McAlister retweeted
1/ muse for small businesses 📊 we found lots of people using muse to run their small business. plumbing businesses, grocery stores, farms, restaurants, and shops. today we're launching a bunch of connectors to make that easier!
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Gerald McAlister retweeted
the moat is literally just caring about your work and being proud of your output and holy shit it does not seem to apply to 99% of people
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Gerald McAlister retweeted
Model benchmarks are completely broken. They don't reflect real world use at all. Stop putting so much trust in them
Replying to @theo
While you’re absolutely correct that these routers don’t make sense, I’ve fully soured on running benchmarks that just test a bunch of tiny tasks in isolation to evaluate ideas like this. In the real world users run prompts that can take an hour+ to run. The model has to decipher your ambiguous prompt, navigate your messy repo, and then iterate until it’s satisfied. This takes compactions, and sometimes steers from you. Compare that to a deepswe task that’s pretty clear upfront, and that’s so trivial it costs the model a buck fifty in inference to complete.
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Gerald McAlister retweeted
Here’s to the wanting. Here’s to the dreaming. Here’s to everyone.
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Gerald McAlister retweeted
Anthropic marketing: We built a god only we can control and gave it a “wet lab” Muse marketing: Heyy girl I know you have dozens of unpaid parking tickets. Let’s get that cleaned up
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Gerald McAlister retweeted
Meta VR Glasses -- private cinema, a workstation with multiple monitors, and a game console in a pair of high-res glasses. Our first time delivering VR in glasses rather than a full headset -- really a glimpse of the future.
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Gerald McAlister retweeted
Here's everything I announced at Meta Connect today 👇
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Gerald McAlister retweeted
Meta VR Glasses Coming Spring 2027.
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Gerald McAlister retweeted
Opening access for developers to build Muse connectors. You bring the API -- Muse brings the agent, the browser, and the context of what the person actually wants. People reach your service just by asking for it, and their agent takes it from there. New connectors are live today. Come build with us. muse.ai/platform
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Gerald McAlister retweeted
So I keep putting your tweets into Jev and asking if they are good and it keeps saying “No.”
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Gerald McAlister retweeted
Last month I wrote about how we can build a positive and safe future for everyone: meta.com/thefutureisforevery… Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens. The reality is: - People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned. There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind. - Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well. Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built. - Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators. - Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well. I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.
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