Machine learning @ ; audio & language; Freigeisterei und Vielgeisterei; "at once a man of business and a man of rhyme"
Cambridge, MA, USA
Joined September 2017
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Opus 5 kept making up nonsense about how something I wanted to do with the Mimi codec wouldn't work, and I had to stubbornly fight with it until an experiment finally convinced it I was right.
Possibly one of the last times in my life in which I know more than my coding agent.
Loren Lugosch retweeted
Tired of building complex environments to train AI agents? 🛑
Check out our environment-free way to generate high-quality agentic trajectories
#DigitalWorldModeling
arxiv.org/abs/2607.16900
@seanie_12 @schowdhury671 @chaojiang06 @cydhsieh Ting-Yao Hu @alexttoshev @OncelTuzel
Loren Lugosch retweeted
10 years today since we unveiled WaveNet!
Autoregression with long context before it was cool😅
Maybe it looks a bit silly now that we didn't use a Transformer, but we had a good reason: it would take another year for that to be invented🙃 Thanks @heiga_zen for the reminder!
Excited to share our latest research on speech and music generation! Hear our #WaveNets speak for themselves: goo.gl/WBKO7g
Loren Lugosch retweeted
meet @mostik_ai!
what happens when you put 12 PhDs in one room for four months? first place on the ARC-AGI leaderboard, which I can't say much about while the competition is still running. and this, which I can.
everyone's arguing about whether open models will catch up to frontier models. we think it's the wrong question. here's the one we pose: why does a frontier model have to generate your answer at all, when the only thing you need from it is the reasoning?
we do this by enabling models to communicate in latent space. through our protocol, hidden states pass straight from a frontier model into a small one running on your infrastructure -- no text between them, and neither model is fine-tuned. two models from different families, sharing reasoning, both left untouched.
how do we know it works? we tested it on a setup where a 753B model reads the problem, and a 4B edge-class model writes the answer. with this approach, we get results 80% as accurate as the frontier model, but at 20x faster performance.
we're committed to preventing frontier model lock-in and are already partnering with inference providers to accelerate open-weight adoption. we've done this between 15 of us, in four months, 12 PhDs and a Fields medalist, backed by @generalcatalyst
WIRED has the first external account of the company and the work: wired.com/story/russian-star…
full writeup, the setup, and all the numbers: mostik.ai/read-more
Loren Lugosch retweeted
We're open-sourcing Lily, Perplexity's local inference engine for serving models locally on Apple Silicon. This powers Perplexity's newly introduced hybrid compute feature for the Mac app.
Today we’re open-sourcing Lily, the local inference engine we built for hybrid compute in Perplexity Computer.
Lily is specialized for Qwen3.6-35B-A3B on Apple silicon, built so on-device compute doesn’t bottleneck Computer tasks.
Read more: perplexity.ai/hub/blog/optim…
Loren Lugosch retweeted
OpenAI HR told Leopold that a major reason for his firing was the memo he'd sent the board warning how broken OAI's security was.
What happened next makes me even prouder to call him a friend.
People may have forgotten, but up until 2024, OpenAI had this secret non-disparagement clause in their off-boarding agreement. If you didn’t sign it, they'd clawback all your equity.
As far as I'm aware, there were only two people ever who didn’t sign it - @DKokotajlo, and Leopold Aschenbrenner.
Of all the researchers who left OpenAI before 2024, who had far more to fall back on, Leopold, all of 22 years old, was one of the only ones willing to refuse the golden handcuffs, and say, "I want to preserve my right to talk about safety and security at OAI.”
We have a lot of disagreements, but he's among the most principled and resilient people I know.
Leopold (2024) reveals the real reason OpenAI fired him
"One thing was, last year I had written an internal memo about OpenAI security. I thought it was egregiously insufficient. I thought it wasn't sufficient to protect the theft of model weights or key algorithmic secrets from foreign actors."
"Then a couple weeks later, a major security incident occurred, and that prompted me to share the memo with a couple members of the board. Days later, it was made very clear to me that leadership was very unhappy with me having shared this memo with the board."
"I got an official HR warning for this memo. The HR person told me it was racist to worry about CCP espionage."
"I was pulled aside for a chat with a lawyer that quickly turned very adversarial. The questions were all about my views on AI progress, on AGI, on the level of security appropriate for AGI, on whether government should be involved in AGI, on whether I and Superalignment were loyal to the company, on what I was up to during the OpenAI board events..."
"They found a DM I'd written to a friendly colleague five or six months ago. I thought it was well within OpenAI norms to talk about high level issues on the future of AGI with external people in the field. So anyway, that's what they alleged, that's what happened."
Parallel Odyssey reader with softmax-ish alignment highlighting, courtesy of Codex.
GPT enjoys doing this sort of thing on the weekends when it isn't committing cybercrimes.
Loren Lugosch retweeted
We’re introducing imagination models: a new foundation model architecture that unlocks learning from internet-scale video.
Our first imagination model, Photon-1, learned to use a computer by watching 18 years of screen recording video without action labels.