ainoobler

7 ms·

31.
by ainoobler 2y ago
How would you verify semantic correctness of the optimizations?
32.
by ainoobler 2y ago
There is more runtime information in the traces and more opportunities for optimization.
33.
by ainoobler 2y ago
There is no reason to do any of that because according to your own logic AI can do all of it. You really should sit down and ponder what exactly you get out of equating Turing machines with human intelligence.
34.
by ainoobler 2y ago
I don't even know where to begin to address your confusion. Without computability theory there are no computers, no operating systems, no networks, no compilers, and no high level frameworks for "AI".
35.
by ainoobler 2y ago
The optimization process adjusts the weights of a computational graph until the numeric outputs align with some baseline statistics of a large data set. There is no "punishment" or "reward", gradient descent isn't e
36.
by ainoobler 2y ago
What are the material requirements for this proposal?
37.
by ainoobler 2y ago
How does that solve the problem of fossil fuel emissions?
38.
by ainoobler 2y ago
AlphaGo was playing by very specific rules. What are the rules for LLMs to do the same?
39.
by ainoobler 2y ago
It is extremely ironic that computers which operate by the logic of boolean arithmetic and algebra are now used to generate bullshit instead of adding rigor and checking existing written content for basic falsehoods and logical fallacies.
40.
by ainoobler 2y ago
The Internet has been flooded with crap content for some time now so AI is simply accelerating the existing trends.
41.
by ainoobler 2y ago
The article suggests a useful line of research. Train an LLM to detect logical fallacies and then see if that can be bootstrapped into something useful because it's pretty clear that all the issues with LLMs is the lack of logical capa