@Promptmethus@moinnadeem Get task (or imagine one) -> take action via connected tools -> evaluate performance -> change behaviour for next iteration
@Promptmethus@moinnadeem Interacting with the world is the only way to stop the infinite fractal. When a model can make decisions that effect other things and the results effect performance.
Then you have the grounds for learning because the model could self-evaluate if it performed well.
How does the coin keep score between flips?
Easy to think the flips need to even out so the aggregate looks 50/50
really your 9 flips in a row are meaningless after 1000 flips.
The growing denominator eats the variance
Large sample -> Regression to expected value
All right, look. Odds of one "heads" = 0.5. Odds of two "heads" = 0.25. Odds of three "heads" = 0.125. And so forth. By the time you get to 9 "heads", odds of an additional "head" is ~0.
"How do I make Generative AI work for my business or use case?"
I hear this question 3x a day ever since ChatGPT launched.
In this article, I've outlined the differences in maturity an enterprise will navigate as they invest in Generative AI.
https://t.co/rxpg8J0zBG
i meet a lot of smart people, but very, very few who are big minded
smart people use their mind as a coarse instrument, it is like a hammer
my impression is that they are not really interested in thoughts, they are just good at them
big minded people are different. speaking with them begets inspiration. it feels like their thought has depth
"there is room to roam in this mind,"