There's been substantial effort put into designing and running benchmarks for these models. You know which one they don't report any more? Chess ELO.

Watt for watt, every one of these models loses to stockfish. There is no possible scenario where we need to be afraid of "rogue superintelligence" when the intelligence in question cannot reason or plan well enough to play chess.

Lecun has the correct approach. Mock these people relentlessly for their attention-seeking doomerism.

If chess ELO is the best proxy for general intelligence, then surely, even Deep Blue was smarter than any human alive?

You can also claim that the best proxy for general intelligence is being able to multiply large numbers. In which case both humans and LLMs lose resoundingly to an old Casio.

Pick a piss poor metric - get a piss poor result.

Also, LeCun is a fool and his "world model" approach has consistently failed to yield any advantages over either the "pure imitation learning" or modern "imitation learning annealed by RL", but that's an aside.

It doesn't really matter if it will be an LLM or Lecuns world model. Lecuns world model, if its the right architecture, will be retrained by google, anthropic and co with the massive amount of compute they have and the massive amount of data.

Also i'm pretty sure Lecun didn't get his money from thin air so big companies are invested in this one way or the other.

And an LLM can easily, today, just rebuild a chess engine and beat whatever they need to beat. It doesn't make sense to ask a random LLM for a next chess move. Would you ask a random human to beat a chess master?

We have reached peak learning. Its probalby now cheaper to teach 1 LLM something new than teaching it to 100.000 people.

Blender support got a lot better just this month. So much better that its quesitonable if anyone new/young wants to learn blender today.