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Sholto Douglas
Scaling RL @AnthropicAI, ex @DeepMind - working towards intelligence too cheap to meter
smh my ranking is below my best ever fencing world ranking (43rd), I've got some work to do

TBPNJul 30, 2025
Introducing The Metis List: a live leaderboard of 100 top AI researchers, ranked by their peers.
We include:
- Education
- Citation count
- Current company
- # of Dwarkesh appearances
- Notable work
Check it out at MetisList dot com

89.79K
smh my ranking is below my best ever fencing world ranking (43rd), got some work to do

TBPNJul 30, 2025
Introducing The Metis List: a live leaderboard of 100 top AI researchers, ranked by their peers.
We include:
- Education
- Citation count
- Current company
- # of Dwarkesh appearances
- Notable work
Check it out at MetisList dot com

282
Also notable that both the peptides and the robots are manufactured in China - we’ve forgotten how to build things!

Sholto DouglasJul 7, 2025
“Where did you meet the bootleg peptide dealer?”
“At the underground robot boxing ring”
Visceral future-shock
42.22K
Sholto Douglas reposted
My job? I'm a rare token hunter. I track down dead languages in Tibetan monasteries, decrypt Tesla's private journals, chase whispers of pre-contact Amazonian dialects. The AIs pay top credit for tokens they've never tasted, you know. Work is work, even if it's for the machines.

302.61K
Sholto Douglas reposted
Morning. Here are our guest call-ins today:
- @shaunmmaguire (Sequoia)
- @jackgwhitaker (Stanford)
- @AarushSelvan (Google)
- @olivercameron (Odyssey)
- @mignano (Lightspeed)
- @markchen90 (OpenAI)
- @_sholtodouglas (Anthropic)
- @eshear (Softmax)
- @jeff_weinstein (Stripe)
- @arakharazian (Ramp)
- @walden_yan (Cognition)
- @mikeknoop (Ndea)
See you all on the stream.
67.44K
Sholto Douglas reposted
AGI timelines are very bimodal. It's either by 2030 or bust.
AI progress over the last decade has been driven by scaling training compute of frontier systems (3.55x a year, 160x over 4 years).
This simply cannot continue beyond this decade, whether you look at chips, power, even fraction of raw GDP used on training.
After 2030, AI progress has to mostly come from algorithmic progress. But even there the low hanging fruit will be plucked (at least under the deep learning paradigm).
So the yearly probability of AGI craters. And we're plausibly looking at 2040+ timelines.
I discuss this dynamic with @_sholtodouglas and @TrentonBricken:
181.56K
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