[socketcluster]

Sounds like they got sick of if after working on it so much. It's really frustrating and tiring when you get everything essentially right but it doesn't work out because of slightly off timing or for some absurdly complex set of reasons that you can never pin down. That's the recipe for burnout.

[PaulHoule]

(1) Tried to bring back the old symbolic AI in 2010s on my own account but people kept knocking down my door because they needed help with one or another neural net. I got an autoencoder in front of customers as part of a highly successful product.

(2) Worked for a startup trying to teach RNNs to read clinical notes; people typecast me as the idealist but I would have preferred the cynical business plan of a product for medical offices to "rebill" insurance to maximize revenue, like the value is clear and nobody dies if it screws up.

(3) Worked at another startup that was training CNNs to read all sorts of documents and datasets you see in corporate environments. That summer I had a methodology I called "predictive evaluation" and a sheaf full of notes that proved that variations of the system we had wasn't really going to work (but they did get it to work enough for one at least one customer) and there was that meeting when we talked about BERT and I said "that seems to avoid all my objections" but the team was through with developing new models and my methodology would have underestimated what BERT could do because it didn't give credit for getting the right answer by the wrong method! Turned out transformers also fixed problems those RNNs had too!