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> 1. What do our human brains do? How is that different from how a human brain may function? Our brains take large amounts of information, from all sorts of pla

> 1. What do our human brains do? How is that different from how a human brain may function? Our brains take large amounts of information, from all sorts of places, and boil it down just as Copilot tries to do. I've posted this elsewhere, but it doesn't matter what our brains do and how similar that is to how AI operates. Humans have rights that machines do not. For example I can watch a movie and not be sued for infringement because I made a copy of the movie in my head.

gjsman-1000 4y ago
> I've posted this elsewhere, but it doesn't matter what our brains do and how similar that is to how AI operates. Humans have rights that machines do not. For example I can watch a movie and not be sued for infringement because I made a copy of the movie in my head. No AI model works that way either though. Think Stability AI: It doesn't have a copy of every image that it was generated with, but has "distilled" the patterns out of images. It no longer has a copy of any specific image inside it, nor is there an ability to extract training data from it. In which case, it does not have a copy of the movie in its head either - but it does, for example, recognize the Disney look. Right now, GitHub Copilot's argument is that training AI models, on copyrighted material, is currently legal. This is also the position almost every AI startup also takes, and it is rooted in "fair use" taking the "transformative" qualities of a work into consideration. There is no doubt that AI-generated suggestions generally are "transformative," it is only about whether they are transformative enough.
- AlexandrB 4y ago
  > No AI model works that way either though. Think Stability AI: It doesn't have a copy of every image that it was generated with, but has "distilled" the patterns out of images. It no longer has a copy of any specific image inside it, nor is there an ability to extract training data from it. My point was that it doesn't matter whether AI works exactly like a human brain, humans have additional rights that an AI does not. This comment made my point better than I could: https://news.ycombinator.com/item?id=33273621 https://news.ycombinator.com/item?id=33273621 > There is no doubt that AI-generated suggestions generally are "transformative," it is only about whether they are transformative enough. I don't think even Microsoft/Github actually believes this to be the case because they choose to train on public Github repos and did not include their own proprietary codebase.
  - rented_mule 4y ago
    > I don't think even Microsoft/Github actually believes this to be the case because they choose to train on public Github repos and did not include their own proprietary codebase. There are good reasons they would not include proprietary codebases aside from this, so I don't see this as a smoking gun. Large codebases often involve elements that don't make sense outside of their immediate environment. Projects the size of Linux have this same issue, but large open source projects tend to have significant cross-pollination with the broader community so it's less of an issue. For example, one large corporate codebase I worked in had a library of ~20, strangely named, short utility functions that were called from many thousands of places. People in the broader community would not find such ubiquitous use of these functions idiomatic at all, but it formed a "dialect" within the company that was often useful given that everyone knew it. These functions caused a lot of signatures/code to be structured in ways that assumed their existence - they were painful to extract when we open sourced internal things. There also tends to be a lot of business logic in corporate code (e.g., `max_space = 100 if has_excel_license else 10`) that would make zero sense in other codebases. A real example in this case... I'd bet that many millions of lines of Microsoft's internal code still use Hungarian notation. Few users would want Copilot generating such names. I could see interest in a version of Copilot that augments the standard Copilot model with your own codebase if you have millions of lines of code in your GitHub Enterprise account.

gjsman-1000 4y ago

> I've posted this elsewhere, but it doesn't matter what our brains do and how similar that is to how AI operates. Humans have rights that machines do not. For example I can watch a movie and not be sued for infringement because I made a copy of the movie in my head. No AI model works that way either though. Think Stability AI: It doesn't have a copy of every image that it was generated with, but has "distilled" the patterns out of images. It no longer has a copy of any specific image inside it, nor is there an ability to extract training data from it. In which case, it does not have a copy of the movie in its head either - but it does, for example, recognize the Disney look. Right now, GitHub Copilot's argument is that training AI models, on copyrighted material, is currently legal. This is also the position almost every AI startup also takes, and it is rooted in "fair use" taking the "transformative" qualities of a work into consideration. There is no doubt that AI-generated suggestions generally are "transformative," it is only about whether they are transformative enough.

AlexandrB 4y ago
> No AI model works that way either though. Think Stability AI: It doesn't have a copy of every image that it was generated with, but has "distilled" the patterns out of images. It no longer has a copy of any specific image inside it, nor is there an ability to extract training data from it. My point was that it doesn't matter whether AI works exactly like a human brain, humans have additional rights that an AI does not. This comment made my point better than I could: https://news.ycombinator.com/item?id=33273621 https://news.ycombinator.com/item?id=33273621 > There is no doubt that AI-generated suggestions generally are "transformative," it is only about whether they are transformative enough. I don't think even Microsoft/Github actually believes this to be the case because they choose to train on public Github repos and did not include their own proprietary codebase.
- rented_mule 4y ago
  > I don't think even Microsoft/Github actually believes this to be the case because they choose to train on public Github repos and did not include their own proprietary codebase. There are good reasons they would not include proprietary codebases aside from this, so I don't see this as a smoking gun. Large codebases often involve elements that don't make sense outside of their immediate environment. Projects the size of Linux have this same issue, but large open source projects tend to have significant cross-pollination with the broader community so it's less of an issue. For example, one large corporate codebase I worked in had a library of ~20, strangely named, short utility functions that were called from many thousands of places. People in the broader community would not find such ubiquitous use of these functions idiomatic at all, but it formed a "dialect" within the company that was often useful given that everyone knew it. These functions caused a lot of signatures/code to be structured in ways that assumed their existence - they were painful to extract when we open sourced internal things. There also tends to be a lot of business logic in corporate code (e.g., `max_space = 100 if has_excel_license else 10`) that would make zero sense in other codebases. A real example in this case... I'd bet that many millions of lines of Microsoft's internal code still use Hungarian notation. Few users would want Copilot generating such names. I could see interest in a version of Copilot that augments the standard Copilot model with your own codebase if you have millions of lines of code in your GitHub Enterprise account.