Comment by mkl
1 day ago
All of that stuff takes time and resources. Self-improvement may not be easy, e.g. if they end up in a local maximum that doesn't extend, and it probably won't be cheap or fast (if it's anything like frontier LLMs it could be months of computation on enormous numbers of cutting-edge devices, costing hundreds of millions or billions, or it may not even be possible without inventing and mass-manufacturing better hardware). Another company achieving a slightly different form of AGI within a few years will probably be at least competitive, and if they have more resources or a better design they could overtake.
All the major companies are setting up to have all the hardware necessary to leverage an AGI-level system when it does emerge. The entire purpose of Starbase for OpenAI or the memphis supercomputer for X.ai is such that there would be very little delay between hitting the right marks on an AGI-capable model and deploying its capabilities en masse towards the highest-leverage aims. Certainly there will be bottlenecks, but the advantages will significantly accelerate progress.