Interesting! I agree that in the current paradigm, Foom seems very unlikely in days. But I predict that soon, we will step out of the LLM paradigm to something that works better. Take coding, GPT-4 is great at coding from only predicting code without any weight updates from experience of trial and error coding like how a human improves at it. I expect it will become possible to take a LLM base model and then train it using RL on tasks of writing full programs/apps/websites… where the feedback comes from executing the code and comparing the results with its expectation. You might be able to create a dataset of websites, for example, and give it the goal of “recreate this” so that the reward can be given autonomously. The LLM process brings common sense (according to the lead author Bubeck of the sparks of AGI paper in his YouTube Presentation), plausible idea generation, and the ability to look up other people’s idea’s online. If you add learning from trying out ideas on real tasks like coding full programs, this might go very fast upwards in capability. And in doing this you create an agentic AI that unlike Auto-GPT does learn from experience.
Interesting! I agree that in the current paradigm, Foom seems very unlikely in days. But I predict that soon, we will step out of the LLM paradigm to something that works better. Take coding, GPT-4 is great at coding from only predicting code without any weight updates from experience of trial and error coding like how a human improves at it. I expect it will become possible to take a LLM base model and then train it using RL on tasks of writing full programs/apps/websites… where the feedback comes from executing the code and comparing the results with its expectation. You might be able to create a dataset of websites, for example, and give it the goal of “recreate this” so that the reward can be given autonomously. The LLM process brings
common sense (according to the lead author Bubeck of the sparks of AGI paper in his YouTube Presentation), plausible idea generation, and the ability to look up other people’s idea’s online. If you add learning from trying out ideas on real tasks like coding full programs, this might go very fast upwards in capability. And in doing this you create an agentic AI that unlike Auto-GPT does learn from experience.