IMO the top people I know and who are likely to write the future of AI are:
* not making 100M+ in panic-driven reorgs
* not in in the GenAI/ASI org of a BigCo™️
* mostly L5-L6
* not active bloggers or super well-followed tweeters
* pretty low-ego people
Munger had a friend that carried a big stack of index cards.
Whenever this friend heard someone feel sorry for themselves, he would sarcastically give them one that read:
“Your story has touched my heart, never have I heard of anyone with as many misfortunes as you”.
Don't leave AI to the STEM folks.
They are often far worse at getting AI to do stuff than those with a liberal arts or social science bent. LLMs are built from the vast corpus human expression, and knowing the history & obscure corners of human works lets you do far more with AI
when you hear someone say:
“Oh, [I/my company] has been using ai for *decades*”
that is a reliable signal that you’re about to hear some terrible opinions about LLMs and the dynamics of modern ai
ai is a newcomer’s game.
"actually it's all just pattern matching!" he screams as his peers develop intelligence capable of finding security vulnerabilities in the linux kernel
kids, always remember that money has log(money) utility, not linear utility.
and almost all careers offer [10^n, 10^n+1] money, but rarely exceed some bound.
ex: quant may be the best way to make 10 million, but the worst way to make 100.
ChatGPT and others:
2022: Cool toy! Fun to play with.
2023: Don't use it much.
2024: Use it a few times a week.
2025: Use it ~ every hour.
Anyone else like this?
I have noticed more excitement about AI tools from technical generalists filling in knowledge gaps vs hyper-specialists that don't feel the tools are good enough to help them much within their zone of expertise.
new from me: what went wrong with the Alan Turing Institute?
I dive into the failures in institutional design, focus, and leadership that led the UK's national AI institute to become irrelevant. It's a story of drift, stakeholderism, and wasted potential. 🧵
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