Comment by mjburgess
4 years ago
sure, but co-pilot is mostly just copying code (see, for example, the issue with it producing quake source code).
If you think of AI as a dial from sample(data) to mean(data), then as the dial is turned towards the mean() you get more "generic" results, but also more garbled ones.
Copilot is more like a search engine, having turned the dial more towards sample().
The real invention of the NN is simply to provide that dial in a trainable way.
The only change to the "state of the art" is the size of the weights, and how long they take to train. This "advancement" is no more impressive than google indexing more webpages.
There has been no step-change advancement in AI in, perhaps, 50 years. All we see today is a product of hardware, in GPU/CPUs able to compress TBs of data into c. 300GB of weights. And likewise, the internet to provide it and SSDs to hold it.
The "magic" of AI is no more the magic of wikipida, here: copilot is good only because million+ programmers made github good.
It's still little more than a fancy search.
> It's all just passable garbled nonesense that the reader (goes to lengths) to interept based on their prior knowledge, which is not expressed in the syntax of what these systems output.
> It's still little more than a fancy search.
I feel like the goalposts have been moved between your two comments. CoPilot is obviously not producing garbled nonsense, and it's also not just printing the top result from StackOverflow. It is producing code that references my variables, does the right thing 50% of the time, and usually compiles.
One of the nice little things is error messages- when I type `if (!foo) { throw ... ` CoPilot is able to complete a nicely formatted and descriptive error message from its understanding of my code. It's not garbled nonsense, and it's not just a search engine.
Does AI deserve the hype it sometimes gets? Not yet. But I think you're going to have to start digging a little deeper for your commentary.
As someone who uses co-pilot daily - it often does print garbled nonsense (semantic nonsense, not syntactic nonsense - if you get my meaning).
Even if AI got to the point of perfectly passing every expert-level Turing test your degree of rigor as to what "thinking" is would never truly permit any belief of AI having struck the golden nugget of intelligence.
Imagine if we were all self-replicating computers, and certain members of this silicon race began experimenting with making creatures with carbon macro-molecules to create organic intelligence, you could make the same claim in the other direction:
"There has been no step-change advancement in Organic Intelligence in, perhaps, 50 years. All we see today is a product of cell count, in neurotransmitter chemistry able to compress TBs of experiences into c. 300B neurons."
I think you are missing the conditional, contextual nature of language models. They mix things in coherent ways, they adapt to the request. Google doesn't create new things when they don't exist, and the pre-written code examples on the internet will never adapt to your needs.
But I agree with you that everything they do seems intelligent because 'intelligence' was in the training data. Not much different from us, if you raise a human removed from society (take his intelligent training data away) he will not accomplish almost anything on his own.