Yudkowsky previously expected AI progress to involve more distinct discoveries, rather than scaling an existing architecture.

Judged as of 2023-03; the claim concerns Yudkowsky's own earlier expectations. True: Yudkowsky's earlier writings (for example the Hanson–Yudkowsky FOOM debate of 2008, or posts and papers before 2020) show he expected AI progress to come mainly from multiple distinct conceptual discoveries or insights, rather than from scaling an existing architecture such as transformers. Mostly true: his earlier writings mainly stress insights over scale, with some minor acknowledgment of the role of compute or scaling. Mixed: his earlier writings are about evenly split between expecting distinct discoveries and expecting scale or compute to dominate. Mostly false: his earlier writings mostly predicted that scaling would be important, with only occasional emphasis on discoveries. False: his documented earlier views clearly predicted progress driven by scaling an existing architecture.

Set before the research began.

1. E1 Intelligence Explosion Microeconomics Machine Intelligence Research Institute (author: Eliezer Yudkowsky) Own record

   “I no longer think that Moore’s Law will play much of a role in the intelligence explosion, partially because I expect returns on algorithms to dominate, and partially because I would expect an AI to prefer ways to scale itself onto more existing hardware rather than waiting for a new generation of chips to be produced in Intel-style factories.”

2. E2 Intelligence Explosion Microeconomics Machine Intelligence Research Institute (author: Eliezer Yudkowsky) Own record

   “I identify the key issue as returns on cognitive reinvestment—the ability to invest more computing power, faster computers, or improved cognitive algorithms to yield cognitive labor which produces larger brains, faster brains, or better mind designs.”

3. E3 Intelligence Explosion Microeconomics Machine Intelligence Research Institute (author: Eliezer Yudkowsky) Own record

   “Although I used to go around asking, “If Moore’s Law says that computing speeds double every eighteen months, what happens when computers are doing the research?””

In his MIRI paper Intelligence Explosion Microeconomics, Yudkowsky writes that he expects "returns on algorithms to dominate" over hardware trends such as Moore's Law (E1). That fits an earlier expectation that progress would come from insights rather than scale. The same paper still lists more computing power and faster computers as channels alongside better algorithms (E2), and he says he once framed AI progress around Moore's Law (E3), so compute and scaling are acknowledged. The evidence is undated and does not directly contrast "distinct discoveries" with scaling a single architecture, so the claim fits the "mostly true" level of the criteria.