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evanthebouncy OP t1_isbui1j wrote

I read all of your blog.

I loved this reference

"""The physicist David Deutsch proposes a single criterion to judge the quality of explanations. He says good explanations are those that are hard to vary, while still accounting for observations. """

You write really well! I followed you on twitter. I Think you have thought about the relationship between explaining data and probablistic programming deeper and longer than I have so i cant say much of surprising cool things to you.

I think my work "communicating natural programs to humans and machines" will entertain you for hours. Give it a go.

It's my belief that we should program computers using natural utterances such as language, demonstration, doodles, ect. These "programs" are fundamentally probablistic and admits multiple interpretations/executions.

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yldedly t1_isecsiy wrote

>I think my work "communicating natural programs to humans and machines" will entertain you for hours. Give it a go.

I will, looks super interesting. I'm so jealous of you guys at MIT working on all this fascinating stuff :D

>It's my belief that we should program computers using natural utterances such as language, demonstration, doodles, ect. These "programs" are fundamentally probablistic and admits multiple interpretations/executions.

That's an ambitious vision. I can totally see how that's the way to go if we want "human compatible" AI, in Stuart Russell's sense where AI is learning what the human wants to achieve, by observing their behavior (including language, demonstrations, etc).

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evanthebouncy OP t1_iseg25n wrote

Yaya thanks! My belief is that for most part, people know exactly what they want from computers, and can articulate it well enough so that a developer (with knowledge of computers) can implement it successfully. In this process the first person need not code at all, in the traditional sense.

All we need is the technology to replace the dev with AI haha

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evanthebouncy OP t1_isq1rru wrote

Yo.

Foundation Posteriors for Approximate Probabilistic Inference

Read this on arxiv

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