Alexander Long @_AlexanderLong
Founder @PluralisHQ | ML PhD Protocol Learning: Multi-participant, low-bandwidth model parallel Pluralis.ai Joined July 2023-
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Last few months has been this with the additional complexity of supporting multi-party training + running over a noisy fabric of decentralised compute we don't control. Required re-writing large portions of the distributed training stack. Not easy. Done now though.
Last few months has been this with the additional complexity of supporting multi-party training + running over a noisy fabric of decentralised compute we don't control. Required re-writing large portions of the distributed training stack. Not easy. Done now though.
People think about pretraining runs as single long monolithic loss curves but they're not like that even in the centralised case. You run stuff, move it through different data stages, go back and fork off a checkpoint, change some norm somewhere etc. etc.
People think about pretraining runs as single long monolithic loss curves but they're not like that even in the centralised case. You run stuff, move it through different data stages, go back and fork off a checkpoint, change some norm somewhere etc. etc.
perps on god
Obsessing over the SWE-bench chart is one of the most mid-curve things I've ever seen. Take a second and absorb what's actually been achieved here. Understandable to not like OpenAI since they're destroying your whole identity but don't pretend its the chart that's the issue.
Every single datapoint pointing towards GPT-5 being really really good.
Every single datapoint pointing towards GPT-5 being really really good.
pretraining is an elegant science, done by mathematicians who sit in cold rooms writing optimization theory on blackboards, engineers with total absorb of distributed systems of titanic scale posttraining is hair raising cowboy research where people drinking a lot of diet coke…
Missing the point that it'll be a system who's behaviour is controlled by a few people, in companies that don't have the best track record when it comes to this kind of thing. It's fundamentally a level of power that's never existed before it's that simple.
Missing the point that it'll be a system who's behaviour is controlled by a few people, in companies that don't have the best track record when it comes to this kind of thing. It's fundamentally a level of power that's never existed before it's that simple.
Thats a wrap for ICML2025. Incredible to watch the space go from "What are you talking about" to "That's impossible" to "Hmmm thats very interesting" in just over a year. @tha_ajanthan @hmdolatabadi
Jack Dorsey says AI must be permissionless because constraint kills innovation. Five CEOs shouldn't dictate what brings humanity forward. Open source is the answer. To protect ourselves, we have to race ahead. Eliminating single points of failure before they become…
If you claim to have seen this coming, you better have the manifold P&L to back it up
Noam tends to not exaggerate.
Welcome to DeAI Summer. My op ed in @CoinDesk on the progress we're making in decentralized AI. coindesk.com/opinion/2025/0…
Totally agree - Flower labs another group actively publishing great stuff and now squarely focused on decentralised training. Should be a major datapoint for everyone still skeptical of the area - flower team is as legitimate as it gets and Nic Lane is pretty much top of the…
Totally agree - Flower labs another group actively publishing great stuff and now squarely focused on decentralised training. Should be a major datapoint for everyone still skeptical of the area - flower team is as legitimate as it gets and Nic Lane is pretty much top of the…
Pluralis + Prime Intellect + Ambient flips Ethereum by 2030
From my experience, getting a paper on decentralized DL accepted to top-level conferences can be quite tough. The motivation is not familiar to many reviewers, and standard experiment settings don't account for the problems you aim to solve. Hence, I'm very excited to see…
From my experience, getting a paper on decentralized DL accepted to top-level conferences can be quite tough. The motivation is not familiar to many reviewers, and standard experiment settings don't account for the problems you aim to solve. Hence, I'm very excited to see…
Feel like meta closing models was very predictable. I explicitly said this would happen last year and explained why (from blog.pluralis.ai/p/article-2-pr…).
Feel like meta closing models was very predictable. I explicitly said this would happen last year and explained why (from blog.pluralis.ai/p/article-2-pr…). https://t.co/VQkbescnx7
Hidden in the article "Furthermore, there have been some billion dollar offers that were not accepted by researcher/engineering leadership at OpenAI." I believe if @dylan522p wrote it that its true... but how can that be possible?
Hidden in the article "Furthermore, there have been some billion dollar offers that were not accepted by researcher/engineering leadership at OpenAI." I believe if @dylan522p wrote it that its true... but how can that be possible?
Spoke 50 minutes straight to a packed room of cracked AI researchers at ICML, presenting work by @akashnet_, @PrimeIntellect, @gensynai, @NousResearch, @PluralisHQ, and @GoogleDeepMind. There is now an enormous interest in DeAI. Mission (Partially) Accomplished.
Spoke 50 minutes straight to a packed room of cracked AI researchers at ICML, presenting work by @akashnet_, @PrimeIntellect, @gensynai, @NousResearch, @PluralisHQ, and @GoogleDeepMind. There is now an enormous interest in DeAI. Mission (Partially) Accomplished.
People forget Policy Gradient based RL is the most data-inefficient form of training. Going to be major algorithmic advances in RL'ing the base models, probably using something like artificial curiosity (arxiv.org/pdf/1705.05363). But the current methods are not there.
People forget Policy Gradient based RL is the most data-inefficient form of training. Going to be major algorithmic advances in RL'ing the base models, probably using something like artificial curiosity (arxiv.org/pdf/1705.05363). But the current methods are not there.
For people not familiar with AI publishing; there are 3 main conferences every year. ICML, ICLR and NeurIPS. These are technical conferences and the equivalent of journals in other disciplines - they are the main publishing venue for AI. The competition to have papers at these…
For people not familiar with AI publishing; there are 3 main conferences every year. ICML, ICLR and NeurIPS. These are technical conferences and the equivalent of journals in other disciplines - they are the main publishing venue for AI. The competition to have papers at these…
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