An excerpt has surfaced from the AI2027 podcast with siskind and the ex AI researcher, where the dear doctor makes the case for how an AGI could build an army of terminators in a year if it wanted.
It goes something like: OpenAI is worth as much as all US car companies (except tesla) combined, so it could buy up every car factory and convert it to a murderbot factory, because that's kind of like what the US gov did in WW2 to build bombers, reaching peak capacity in three years, and AGI would obviously be more efficient than a US wartime gov so let's say one year, generally a completely unassailable syllogism from very serious people.
Even /r/ssc commenters are calling him out about the whole AI doomer thing getting more noticeably culty than usual edit: The thread even features a rare heavily downvoted siskind post, -10 at the time of this edit.
The latter part of the clip is the interviewer pointing out that there might be technological bottlenecks that could require upending our entire economic model before stuff like curing cancer could be achieved, positing that if we somehow had AGI-like tech in the 1960s it would probably have to use its limited means to invent the entire tech tree that leads to late 2020s GPUs out of thin air, international supply chains and all, before starting on the road to becoming really useful.
Siskind then goes "nuh-uh!" and ultimately proceeds to give Elon's metaphorical asshole a tongue bath of unprecedented depth and rigor, all but claiming that what's keeping modern technology down is the inability to extract more man hours from Grimes' ex, and that's how we should view the eventual AGI-LLMs, like wittle Elons that don't need sleep. And didn't you know, having non-experts micromanage everything in a project is cool and awesome actually.
Wonder how many people stopped being AI-doomers after this. I use the same argument against ai-doom.
Others as in specifically his co-writer for AI2027 Daniel Kokotlajo, the actual ex-OpenAI researcher.
Pay no attention to this thing we just spent two hours exhaustively discussing, it's not really relevant context.
Also the title is inflammatory only in the context of already knowing him for a ridiculous AI doomer, otherwise it's fine. Inflammatory would be calling the video economically illiterate bald person thinks evaluations force-buy car factories, China having biomedicine research is like Elon running SpaceX .
Here's a couple:
LLM agents can beat Pokemon... if you give them enough customized tools and prompting that with the same number of lines of instruction you could just directly code a bot that beats Pokemon without an LLM in the first place. And you don't mind the LLM agent playing much much worse than literal children.
Kind of knew that after Claude plays pokemon went semi viral, it was going to immediately get goodhart'd. i also saw the usual doomers be like BY END OF YEAR AGENTS WILL BEAT POKEMON, which I thought was a severe underestimate at the time- they were undoubtably basing their projection based off the Anthropic people who posted a little chart showing how far each version of Claude made it, waiting for pokemon playing skill to emerge from larger and larger models, instead of thinking, hmm they are iteratively refining the customized tools as it gets stuck. Then after Gemini 'beat' the game I read a disappointed response from an RL guy that said after trying to replicate the results, they concluded Googe's set up was basically 90% harness for the model, 10% model despite the Google team basically implying it was raw pixels-to-action.
Yep. If you're looking for a snappy summary of this situation, this reddit comment had a nice summary. An open source LLM Pokemon harness/scaffold has 4.8k lines of python, and is missing features essential to Gemini's harness. Whereas an open source LUA script to play Pokemon is 7.2k lines, was written in 2014, and it consistently speed runs the game in under two hours.