Ahead of OpenAI CEO Sam Altman’s four days in exile, several staff researchers sent the board of directors a letter warning of a powerful artificial intelligence discovery that they said could threaten humanity, two people familiar with the matter told Reuters.
Many of the building blocks of computing come from complex abstractions built on top of less complex abstractions built on top of even simpler concepts in algebra and arithmetic. If Q* can pass middle school math, then building more abstractions can be a big leap.
Huge computing resources only seem ridiculous, unsustainable, and abstract until they aren’t anymore. Like typing messages a bending glass screens for other people to read…
With middle school math you can fairly straightforwardly do math all the way to linear algebra. Calculus requires a bit of a leap, but this still leaves a lot of the math world available.
The thing is, in general computing it was humans who figured out how to build the support for complex abstractions up from support for the simplest concepts, whilst this would have to not just support the simple concepts but actually figure out and build support for complex abstractions by itself to be GAI.
Training a neural network to do a simple task (such as addition) isn’t all that hard (I get the impression that the “breaktrough” here is that they got an LLM - which is a very specific kind of NN, for language - to do it), getting it to by itself build support for complex abstractions from support for simpler concepts is something else altogether.