Attentive outsider and acquaintance of a couple people who are or were employed there. Nothing I'm saying is particularly inside baseball, though, it's pretty well covered by all the blogs and podcasts.
Machine Learning Street Talk and Dwarkesh are excellent. Various discord communities, forums, and blogs downstream of the big podcasts, and following researchers on X keeps you in the loop on a lot of these things, and then you can watch for random interviews and presentations on youtube when you know who the interesting people and subjects are.
Most serious researchers want to work on interesting problems like reinforcement learning or robotics or RNN or dozen other avant-garde subjects. None want to work on "boring" LLM technology, requiring significant engineering effort and huge dataset wrangling effort.
This is true - Ilya got an exit and is engaged in serious research, but research is by its nature unpredictable. Meta wanted a product and to compete in the AI market, and JEPA was incompatible with that. Now LeCun has a lab and resources to pursue his research, and Meta has refocused efforts on LLMs and the marketplace - it remains to be seen if they'll be able to regain their position. I hope they do - open models and relatively open research are important, and the more serious AI labs that do this, the more it incentivizes others to do the same, and keeps the ones that have committed to it honest.
Attentive outsider and acquaintance of a couple people who are or were employed there. Nothing I'm saying is particularly inside baseball, though, it's pretty well covered by all the blogs and podcasts.
What podcast?
Machine Learning Street Talk and Dwarkesh are excellent. Various discord communities, forums, and blogs downstream of the big podcasts, and following researchers on X keeps you in the loop on a lot of these things, and then you can watch for random interviews and presentations on youtube when you know who the interesting people and subjects are.
Most serious researchers want to work on interesting problems like reinforcement learning or robotics or RNN or dozen other avant-garde subjects. None want to work on "boring" LLM technology, requiring significant engineering effort and huge dataset wrangling effort.
This is true - Ilya got an exit and is engaged in serious research, but research is by its nature unpredictable. Meta wanted a product and to compete in the AI market, and JEPA was incompatible with that. Now LeCun has a lab and resources to pursue his research, and Meta has refocused efforts on LLMs and the marketplace - it remains to be seen if they'll be able to regain their position. I hope they do - open models and relatively open research are important, and the more serious AI labs that do this, the more it incentivizes others to do the same, and keeps the ones that have committed to it honest.