Does any expert in the field know whether it is really the case that this intelligence we are seeing with frontier models is an "emerging" phenomena, only coming up when the architecture is scaled? Like isn't it weird that the 1 million parameter model with the same architecture can't solve basic puzzles but suddenly the 1 trillion parameter can conjure up counter-examples for the Jacobian conjecture? It's unintuitiv…
> one of the basic tenants of algorithm development was that you can't just brute-force your way towards a solution for some complex problems It's kind of sad that popular CS textbooks often focus on solving precise problems with lowest theoretical complexity bounds while ignoring more practical (but generally applicable) computation techniques. In machine learning they call it "gradient descent", which in older days…
I thought this is nowadays called gradient descent