I'll be impressed when they can create an entire cell from scratch and it will start to divide. They can create all the needed precursors, bypassing millions of years of random permutation. Because until you have an entire working cell with replication, you have no retained benefit.
Like the way slime molds solve mazes: explore every possible path in parallel, and push growth in all areas with greater nutrient gradients. Not by sensing any gestalt clues, like symmetries in the maze design.
With all the people saying that you're going to have problems because the LLM is not good at refactoring or large code bases or OOP, etc. the point may be that if you're working to develop skills, an LLM herder might be a good one. Even if the models are almost, but not quite, good enough yet - they will be.
When looking for a career move you might want to focus on the trajectory more than the current state.
this is the pitch - it's open source, run it yourself. But >99% of people will not have the hardware needed to run these models at a high enough quality to be close to SOTA. So they will run the open-source models on CCP systems for a good price.
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