Corporate R&D teams are there to absorb risk, innovate, disrupt, create new fields, not for doing small incremental improvements. "If we know it works, it's not research." (Albert Einstein)
I also agree with LeCun that LLMs in their current form - are a dead end. Note that this does not mean that I think we have already exploited LLMs to the limit, we are still at the beginning. We also need to create an ecosystem in which they can operate well: for instance, to combine LLMs with Web agents better we need a scalable "C2B2C" (customer delegated to business to business) micropayment infrastructure, because as these systems have already begun talking to each other, in the longer run nobody would offer their APIs for free.
I work on spatial/geographic models, inter alia, which by coincident is one of the direction mentioned in the LeCun article. I do not know what his reasoning is, but mine was/is: LMs are language models, and should (only) be used as such. We need other models - in particular a knowledge model (KM/KB) to cleanly separate knowledge from text generation - it looks to me right now that only that will solve hallucination.
Maybe at university, but not at a trillion dollar company. That job as chief scientist is leading risky things that will work to please the shareholders.
Yes but he was hired in the ZIRP era where all SV companies were hiring every opinionated academic and giving them free reign and unlimited money to burn in the hopes that maybe they'll create the next big thing for them eventually.
These are very different economic times right now, after the FED infinite money glitch has been patched out, so now people do need to adjust to them and start actually making some products of value for their seven figure costs to their employers, or end up being shown the door.
Also, like… it’s Facebook. It has a history of ploughing billions into complete nonsense (see metaverse). It is clearly not particularly risk averse.