replying to executives on slack with shit like “well said Michael” and “Spot on” like a good millennial
so many blatently incorrect statements in this episode (e.g. micron does not trade at 2-3x earnings). no clue how this will all shake out but i would highly bet against whatever these guys say and increasingly seems being 'ai-pilled' is just a euphanism for overconfident midwit
Had a lot of fun chatting again with my twin brother @dylan522p
We went through lab economics over the next few years - the shift from inference to training as RSI draws near; and how Anthropic and OpenAI are on track to control most of the world’s usable FLOPs within the next few years (because they can monetize compute better and thus outbid everyone).
And then we discuss whether the >$10T of total AI capex we’ll see by the end of the decade will cause a sovereign debt crisis, where hyperscaler debt raises interest rates, drives non-AI exposed countries into bankruptcy, and crashes non-AI equities.
One question we weren’t able to resolve is whether there’s anything that can counter all the forces barrelling towards centralization in this industry - the economies of scale in training, the scarcity of compute, and eventually continual learning and RSI.
0:00:00 – Two labs will soon control most of the world’s compute
0:07:01 – $6 billion in fab capex enables $1t+ of end revenue
0:13:08 – Compute prices will rise if the labs outbid everyone
0:18:22 – Which layer will capture most of the surplus?
0:25:40 – Will datacenter regulation slow down AI?
0:29:43 – Labs are shifting compute from inference to R&D
0:33:27 – China gets less than 10% of new compute, but its labs need less
0:48:48 – Will AI cause a sovereign debt crisis?
1:07:52 – Will the world's future workforce belong to a few companies?
the more i learn about Aschenbrenner (active in german green party as a teen, asked ross douthat to officiate his wedding), the more it seems like his entire persona is dedicated to being zoomer Thiel
man this story delivers wsj.com/tech/ai/situational-…
is the point of this guys 'hedge-fund advisory firm' just to advise how to create record setting blow ups??
“what important truth do very few people agree with you on?”
it might actually be totally fine for dogs to have chocolate and the idea that it’s not safe for them was fabricated by some conspiratorial anti dog qualia cabal
its interesting (but i guess somewhat expected) how much the stylistic choices seem to change for an LLM based on the project domain. specifically anything financial, the var names or code quality in general read like 2015-esque python
dont think ive ever run into a "talent sourcer" who uses the correct acronym for daylight/standard time
if you ever presented a classifier this bad as a Data Scientist/ML engineer, you would be fired from most jobs
making an outdoor plant stand and realizing if i wasn’t using scrap wood, it’s cheaper to just buy one online than to make it myself is my equivalent $28 lunch blackpill moment











