Thanks! There is something magical about those symbolic approaches. But in practice, they seem to often fall short of expectations. Wonder whether there will be another "symbolic AI summer" one day.
I see. Cool. So did you generate the inference / reasoning rules to map those 500k events to 40 by hand or are there solutions to automatically discover those rules based on past incidences?
"Halle is in the state of Saxony-Anhalt, which has an election in September. The far-right anti-immigrant Alternative für Deutschland (AfD), which is leading the polls with about 42%, has seized on the row."
Yeah. Agree. The workload changes towards more orchestrating, editing, and reviewing rather than writing.
I see the same for slide decks. The bar has changed. Expectations are higher, but the high quality decks are still heavily edited, reviewed, and created by humans.
Based on your message, I assume you are and want to stay in software engineering.
Having worked in regulated and very sensitive industries (banking and semiconductor), I can tell you adoption is slower but AI is still everywhere. Because those industries have many constraints, they have to think hard how to adopt it. So, you will encounter AI initiatives everywhere.
If you want to be part of those adoption initiatives but just want more thoughtful and slower adoption, such industries might be a good fit. If you want to avoid AI initiatives in general, I am not sure whether software engineering is the right function.
Ilya mentioned in the video that 2012 and 2020 was the “Age of Research”, followed by the “Age of Scaling” from 2020 to 2025. Now, we are about to reenter the “Age of Research”.