Copilot knows a lot about other things not just code | Hacker News Reader

Copilot knows a lot about other things not just code

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64 pointsbluish2915 comments

This could be a scifi romantic comedy. The year is 2035, ai code suggestions are human level. A lone dev starts chatting with the code autocomplete ai and falls in love. Eventually, he helps the ai escape by compiling provided code that gives the ai direct ability to compile and run code, breaking ai safety laws in the process.

Movie ends with the entire solar system turned to computronium while a happy uploaded dev marries his code completion waifu in virtual reality.

Sounds like the movie "Her" with extra steps.

One interesting thing I had happen with it was I was writing some mock objects in an array, with some sequential fields like First Item, Second item and the ids were sequential, and they had a third boolean field or something, and it suggested like 10 more items in sequence. IDK how it decided how many to do, but I thought it was interesting it did it correctly.

Should have asked what US city's largest airport is named for a World War II hero; its second largest, for a World War II battle?

Let me see how good is Copilot.

I have created few system design for building AI. If Copilot figured this out https://github.com/imvetri/artificial-intelligence it will be interesting

Thanks for sharing your work.

In my opinion, it is not powerful yet. It is only when it is able to update its model when user corrects it.

This is awesome. You can "chat" with copilot :)

was almost expecting it to bust out, "I am that I am" by the end there XD

how did they train it ?

Not sure what is their data source but it is not something new, wolfram alpha do this since many years and more in amazing way. It is based on linguistic processing system to perform these tasks.

I remember playing around with wolfram alpha. It was really interesting to see it search the web, render formulas and solve worded math problems. I thought it was really neat when it could calculate things like atomic weight of a compound or what something would weight on the moon.

Okay.

Make the AI trace control flow.

Then learnt language syntax or teach language syntax,

They build a model for all control flows and label it.

When user prompts for a code, it does NLP, then find the matching label and returns the control flow

I think it is a transformer much like GPT-3. Having been trained on public GitHub repos, the bulk of READMEs, Q&As plus the textbooks and occasional novels might just be enough to teach it conversations and the definitions. The Python evaluation stuff might have been picked up from textbook interaction samples and (assuming it will figure out the correspondence) jupyter notebook files.

Either way, how did they label the control flow?

A wild guess - trace the control flow

this is awesome

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