Part of the problem is that AI doesn’t need to be an AGI to cause large society level disruption. Eg, starting a mass movement online requires a few percent of

Part of the problem is that AI doesn’t need to be an AGI to cause large society level disruption. Eg, starting a mass movement online requires a few percent of online participants to take part in the movement. That could be faked today using a lot of GPT4 agents whipping up a storm on Twitter. And this sort of stuff shapes policies and elections. With the opensource LLM community picking up steam, it’s increasingly possible for one person to mass produce this sort of stuff, let alone nation state adversaries. There’s a bunch of things like this that we need to watch out for. For our industry, within this decade we’ll almost certainly have LLMs able to handle the context size of a medium software project. I think it won’t be long at all before the majority of professional software engineering is done by AIs. There’s so much happening in AI right now. H100s are going to significantly speed up learning. Quantisation has improved massively. We have lots of papers around demoing new techniques to grow transformer context size. Stable diffusion XL comes out this month. AMD and Intel are starting to seriously invest in becoming competitors to nvidia in machine learning. (It’ll probably take a few years for PyTorch to run well on other platforms, but competition will dramatically lower prices for home AI workstations.) Academia is flooded with papers full of new methods that work today - but which just haven’t found their way into chatgpt and friends yet. As these techniques filter down, our systems will keep getting smarter. What a time to be alive.