411–420 of 473 posts
Attempts to litigate any license violation are going to get precisely nowhere I bet, but I find the actual license violation argument persuasive. This is an excellent example of how the AI singularity/revolution/whatever is a total distraction and that a much bigger and more serious issue is how AI is becoming so effective at turning the output of cheap/free human mental labour into capital. If AI keeps getting bette…
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> Part of me wants to tell him to try selling it as a machine learning model and just obfuscate the fact that the model was carefully hand written rather than back propagated. How many models are back-propagated first and then hand-tuned?
That's a great question. I had assumed that the workflow of an ML engineer consisted of managing the data and a relatively high level set of parameters around a search space of layers and connectivity, as the whole shtick of ML is that the hyperparameter space of the tensors themselves is too complex to grok or tweak when generated from training. But I only have a passing knowledge of the subject, pretty much just en…
Two examples I can think of are doing linear regression on the square of your input. For deep learning, people have improved visual representation by taking samples of the colors at various frequencies. [1]
Attempts to litigate any license violation are going to get precisely nowhere I bet, but I find the actual license violation argument persuasive. This is an excellent example of how the AI singularity/revolution/whatever is a total distraction and that a much bigger and more serious issue is how AI is becoming so effective at turning the output of cheap/free human mental labour into capital. If AI keeps getting bette…
Earlier quoted context omitted.
That's a great question. I had assumed that the workflow of an ML engineer consisted of managing the data and a relatively high level set of parameters around a search space of layers and connectivity, as the whole shtick of ML is that the hyperparameter space of the tensors themselves is too complex to grok or tweak when generated from training. But I only have a passing knowledge of the subject, pretty much just en…
I'm no data scientist but many statistical methods rely on prior knowledge and even computed inputs. Two examples I can think of are doing linear regression on the square of your input. For deep learning, people have improved visual representation by taking samples of the colors at various frequencies. [1] [1]: https://arxiv.org/pdf/2003.08934.pdf
gonna develop my own linux-like kernel soon, with my own AI model trained on public repositories wanna see the source code of my AI model? oh, it's closed source it's just coincidence that nearly 100% of my future linux-like kernel code looks the same as linux the kernel, bear in mind that my closed-source AI model takes inspiration from GitHub Copilot, there is no way that it will copy any source code
Nothing is closed-source to the courts.
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> When AI inevitably outperforms humans on almost all tasks Correct me if I’m wrong, but is that even possible? I kind of thought that AI is just set of fancy statistical models that requires some (preferably huge) data set in order to infer the best fit. These models can only outperform humans in scenarios where the parameters are well defined. Many (most?) tasks humans regularly perform don’t have clean and well de…
> Correct me if I’m wrong, but is that even possible? Why should it be impossible? Arguing that it's impossible for an AI to outperform a human on almost all tasks is like arguing that it's impossible for flying machines to outperform birds. There's nothing magical going on in our heads. It's just a set of chemical gradients and electrical signals that result in us doing or thinking particular things. Why can't we de…
I think the key word in that sentence might be "we". That is, you could hypothesize that while it's possible in principle for such a computer to exist, it might be beyond what humans and human civilization are capable of in this era. I don't know if this is true or not, but it's kind of intuitively plausible that it's difficult for a designer to design something as complex as the designer themselves, and the space of AI we can design is smaller than the space of theoretically conceivable AI.
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Whilst I absolutely agree that writing code fast enough isn't the bottleneck, it's always nice to have tools that reduce repeat code writing. I use the React plugin for Webstorm to avoid having to write the boilerplate for FCs. Maybe in the future Copilot will replace that usage.
To me that - and really any form of common boilerplate - is just evidence that we're lacking abstractions. If your editor is generating code for you, that means that the 'real' programming language you're using 'in your head' has some metaprogramming facilities emulated by your IDE. I think we should strive to improve our programming languages to make less of this boilerplate necessary, not to make generating boiler…
I really like your point on symptoms of insufficient abstraction. I do worry that we always see abstraction as belonging in language. Which in turn we treat as a precious singleton, and fight about.
At least in my own hacking, I'm surprised how infrequently I see programmers write programs that write programs. I'm surprised how infrequently I see programmers programming their shell, editor, or IDE.
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Whilst I absolutely agree that writing code fast enough isn't the bottleneck, it's always nice to have tools that reduce repeat code writing. I use the React plugin for Webstorm to avoid having to write the boilerplate for FCs. Maybe in the future Copilot will replace that usage.
To me that - and really any form of common boilerplate - is just evidence that we're lacking abstractions. If your editor is generating code for you, that means that the 'real' programming language you're using 'in your head' has some metaprogramming facilities emulated by your IDE. I think we should strive to improve our programming languages to make less of this boilerplate necessary, not to make generating boiler…
Attempts to litigate any license violation are going to get precisely nowhere I bet, but I find the actual license violation argument persuasive. This is an excellent example of how the AI singularity/revolution/whatever is a total distraction and that a much bigger and more serious issue is how AI is becoming so effective at turning the output of cheap/free human mental labour into capital. If AI keeps getting bette…
First in was lands, then other means of productions, and for the past 150 years, capitalists have turned many types of intellectual creations into exclusively owned capital (art, inventions). Now some want to turn personal data into capital (the “right to monetize” personal data advertised by some is nothing else) and this aims to turn publicly available code into capital. This is simply the history of capitalism goi…
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I don't understand how your example relates to "launder intellectual property violations". What you're saying is that your grandfather hand wrote some feature extractors that look similar to the neurons that ML models have learned from backpropagation. There's no stealing of IP there at all.
He has a set of patents on certain types of highlighting frequency domain patterns in MRIs. In a lot of ways recurrent neural networks can be frequency domain feature extractors as the backwards data flows create sort of delay line memories tapped at interesting periods. The MRI manufacturers after refusing to license his patents, heavily invested in ML models that focus on using recurrent networks for frequency doma…