The general models tackle generic tasks. There is a very long tail of highly specialized tasks that you have never even heard of and the generic AI won't pick u

The general models tackle generic tasks. There is a very long tail of highly specialized tasks that you have never even heard of and the generic AI won't pick up the necessary knowledge by reading books3 and watching YouTube. Just one example would be material fatigue analysis on CT scans of airliner wings. How much such data will be included in the GPT-6 that addresses such a use case? This is just one example that I've heard about the other day when talking to an ML engineer. The world consists of so so many diverse things that are not well documented, and the knowledge is closed off in a few companies globally. Things like pharma, physical engineering things, oil and gas, agriculture. There are companies for stuff like muzzle-based cattle identification systems or pig weight estimation from videos etc. Do you think these will become features in Gemini anytime soon? Most of the world works on very niche things. People who build generic consumer apps have a very distorted view of what's actually making the world run.