Intuition and other forms of knowledge are stock quantities while calibration and instructions are types of flows which change the stock. I'd love to know if there a better word for learning through trial and evaluation than calibration.

Seems like they already built this capability.

Sql server hekaton punted this problem in a seemingly effective way by requiring the client to use stored procedures to get full native compilation. Not sure though if they recompile if the table statistics indicate a different query plan is needed.

https://willus.com/mingw/colinp/win32/resources/menu.html

I dispute the search space problem for something like folding clothes. Like a lot of human actions in space, folding clothes and other motor tasks are hierarchical sequences of smaller tasks that are strung together, similar to a sentence or paragraph of text.

We can probably learn things from each other from few examples because we are leaning on a large library of subtasks that all have learned or which are innate, and the actual novel learning of sequencing and ordering is relatively small to get to the new reward.

I expect soon we'll get AIs that have part of their training be unsupervised rl in a physics simulation, if it's not being done already.

This is probably true for some words and concepts but not others. I think we find that llms make inhuman mistakes only because they don't have the embodied senses and inductive biases that are at the root of human language formation.

If this hypothesis is correct, it suggests that we might be able to train a more complete machine intelligence by having them participate in a physics simulation as one part of the training. I.e have a multimodal ai play some kind of blockworld game. I bet if the ai is endowed with just sight and sound, it might be enough to capture many relevant relationships.

The point is not that she predicted the gender of the child. She predicts what gender the parents expect the child to be without being explicitly told.

She didn't tell me anything about the success rate. Instead she told what factors she used to make her guess. She can tell if she was right or wrong right away because the parents can say what they are expecting.

Most of the times situations are a complete cypher, but in more unisual cases when observing groups of people who know each other, you can tell how they feel from analyzing the behaviors.

This author is clearly in a privileged position in the wedding group. She's in the background with the specific job of looking at everyone and capturing their feelings. They don't try to hide their behavior or respond to her, and the usual western taboo against staring at strangers doesn't apply.

This was definitely a good read!

I wonder if there's a way to make this set of techniques less brittle and more applicable to any language. I guess you're looking at a new backend or some enhancements to one of the parser generator tools.