We asked the best AI researchers in the world one question: if you had the resources, how would you use AI to solve humanity's hardest problems?
Today we're sharing what came back.
Moonshots // ONE is live. 🧵 laude.org/moonshots
Journalism as a discipline needs to become as skilled at covering AI as it is at covering politics (especially as the former starts to overlap with the latter more and more). In my chat with Alex and Ellis this week we talked about how AI is progressing so fast that we AI
Databricks and Perplexity co-founder @andykonwinski has a phrase for the AI industry's current trajectory: "feudalism with better branding."
With @LaudeInstitute, he's trying to fight AI's concentration of power by incentivizing top AI researchers to do their work out in the
"The answer is not to throw the doors open. But the answer is also not to let somebody who has really good intentions hold the key. There's got to be a thing that addresses both.
We need an open AI infrastructure commons — at the intersection of academia, industry, and the
Databricks and Perplexity co-founder @andykonwinski has a phrase for the AI industry's current trajectory: "feudalism with better branding."
With @LaudeInstitute, he's trying to fight AI's concentration of power by incentivizing top AI researchers to do their work out in the
Databricks and Perplexity co-founder @andykonwinski has a phrase for the AI industry's current trajectory: "feudalism with better branding."
With @LaudeInstitute, he's trying to fight AI's concentration of power by incentivizing top AI researchers to do their work out in the
honored to be named one of @sciam's Young American Scientists!
thanks to my advisor @lateinteraction@MIT_CSAIL, and the wonderful people at @PrimeIntellect and @LaudeInstitute for supporting my research. There's a lot of work to do for open science :)
Progress in AI is driven by approaches that make weaker assumptions, which allows for better scaling
But representation learning has relied on strong assumptions like augmentations, masking, cropping, etc... until now!
🎬 Introducing Temporal Difference in Vision (TDV), a new
Is the choice really between unsafe AI and consolidated power? Laude Resident @pgasawa argues it's a false dichotomy, and that the field needs a better framework all together.
The AI community seems to increasingly be heading towards a polarized world when discussing safety and consolidated power. I see this discourse as a false dichotomy, so @profjoeyg and I wrote an essay on how we need to change the conversation (link below).
The AI community seems to increasingly be heading towards a polarized world when discussing safety and consolidated power. I see this discourse as a false dichotomy, so @profjoeyg and I wrote an essay on how we need to change the conversation (link below).
This week made something clear: it’s time to stop treating concentration of power in AI as a solution rather than a risk. Safety and centralized control are not the same thing, so let's stop talking about them like they are.
Yet scaling laws are real. The threat of AI
As expected, the next generation of models are now being evaluated for continual learning ability as a first-class attribute (via scores & traces from things like @pgasawa's recently released Continual Learning Bench).
The value I get from conferences is inversely proportional to their size. A massive hangar with 1000 posters showing completed work across every subfield of AI? meh. A few couches with 10 people discussing their half-cooked work in a particular shared niche? perfection. It's why