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LeCun has "zero concerns" about AI wiping out humanity, recent "rogue" incidents

403 points · 757 comments · Anon84

lukewarm707 · 1791068851 · focus · HN ↗
Per <a href="https://trace.manifund.org/" rel="nofollow">https://trace.manifund.org/ a total of $2,846,125,859 USD has been wired into 'ai safety' causes, many involving ai consciousness and p(doom).
The outcome of this 'safety' is restricting public access to AI and giving a monopoly of access to the industry. This is the ai nonprofit-industrial complex actively concentrating monopoly power in Anthropic in particular as creator, interpreter and safety regulator of AI.
Much of the $2.8bn listed is indirectly, from Anthropic and EA. Three of the four people who participated in the $125m Anthropic Series A are now folding their 1000x Anthropic return into AI 'safety'. Some is from FTX/Alameda, which invested 86% of the Series B.
Dustin Moskovitz: Facebook/Asana/Anthropic Series A, funds EA Good Ventures, transferred to Coefficient Giving, then $1.5bn into ai safety. $500m of Anthropic into an unknown foundation. Funding: $160m to Resolution (alignment research), $93m to Epoch AI (investigating the trajectory of AI), $63m to Redwood Research (oai report), $67m to MATS ( EA type alignment and security researchers), Institute for AI Policy and Strategy, Fund for Alignment Research, $53m to Kairos (building talent infrastructure for AI safety), $32m to Bluedot (online safety courses), $15m to MIRI (Yudkowsky).
Jaan Tallinn: Led the Series A, now $10bn in Anthropic. Funds $199m (85%) of the Survival and Flourishing Fund, then $161m to AI safety including $14m to lightcone (Lesswrong, Lighthouse). $10m to BERI (existential risks), Palisade Research (studying AI capabilities to prevent loss of control.) PauseAI, MIRI, METR etc. Much of what Coefficient funds.
Eric Schmidt: Anthropic Series A, $72m to AI safety via Schmidt Sciences. Over $1m per individual AI2050 researcher.
FTX: Led the Anthropic Series B, bankruptcy estate sold $884m of Anthropic in 2024; $40m to AI Safety. Same orgs, Redwood, Lightcone, etc.
Ruairí Donnelly (Chief of Staff FTX): FTX tokens plus assorted donors, $91m to AI safety via Macroscopic Ventures. $15m to Cooperative AI (currently whitewashing openai under 'multiagent safety')
1. api · 1791070467 · focus · HN ↗
  There's absolutely no way these companies can justify their insane valuations unless they can legislate a barrier to entry and create an oligopoly.
  There's no moat. I can literally sit here in Zed or Pi or any other third party harness and switch models in the middle of a task and it's typically fine. Sometimes a model will get stuck and that's just what I'll do.
  Combined with competition and open weights models, that means the price is going to go to fall until AI tokens cost a small premium over the cost of the hardware and electricity.
  That's assuming improvements in algorithms and specialized silicon doesn't eventually lead to an efficient accelerator that can run a frontier model locally. It'll be a while but I don't see any fundamental barrier. High bandwidth flash storage is coming, and that'll radically cut the RAM side of that cost. Pair that with a pipelined TPU accelerator and you're cooking.
  Now look at Anthropic's proposed IPO valuation. It's insane unless they can own the market or share it with a cartel of maybe 1-2 other behemoths, and this is the only way they can do that.
  1. ItsMattyG · 1791075821 · focus · HN ↗
    To me it seems the opposite. There's a few companies in the world that have enough compute to train and serve frontier models.
    As the frontier gets smarter and more useful prices will only go up, as they are set to replace jobs being paid six or seven figures a year - the demand for as much inference on these models for as long as possible will be astronomical, but compute starting in 2030 will not be keeping up.
    Eventually prices will fall for assistants but the frontier will be the most profitable thing in the world, and the top companies basically already have oligopolies due to their ridiculously expensive compute investments.
    api · 1791080665 · focus · HN ↗
    > There's a few companies in the world that have enough compute to train and serve frontier models.
    Train: yes, for now.
    Host: depends on the scale. At a small scale a wealthy individual could easily build a rig in their basement to host one of these things. At larger scale any cloud company could do it, and many already have the compute on site. At large scale this is true... again, for now.
    What you say only holds (in the absence of a state oligopoly) if two conditions are met: (1) AI performance does not asymptote any time soon due to running out of training data or other scaling limitations, and (2) these companies are able to stay at the frontier.
    There's little to no moat, so staying at the frontier will be a game of investing massively in compute, talent, and R&D, and they can never stop.
    rubikscube09 · 1791080937 · focus · HN ↗
    what suggests that we will hit an asymptote any time soon? Agree with you on the second part. The ever elusive frontier will probably always be changing hands after some point.

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