My mainline prediction scenario for the next decades.

My mainline prediction * :

• LLMs will not scale to AGI. They will not spawn evil gremlins or mesa-optimizers. BUT Scaling laws will continue to hold and future LLMs will be very impressive and make a sizable impact on the real economy and science over the next decade. EDIT: since there is a lot of confusion about this point. BY LLM I mean the paradigm of pre-trained transformers. This does not include different paradigms that follow pre-trained transformers but are still called large language models.  EDIT2: since I'm already anticipating confusion on this point: when I say scaling laws will continue to hold that means that the 3-way relation between model size, compute, data will probably continue to hold. It has been known for a long time that amount of data used by gpt-4 level models is already within perhaps an OOM of the maximum. ]
• there is a single innovation left to make AGI-in-the-alex sense work, i.e. coherent, long-term planning agents (LTPA) that are effective and efficient in data sparse domains over long horizons.
• that innovation will be found within the next 10-15 years
• It will be clear to the general public that t