[beyarkay]

Given that AI couldn't even speak English 6 years ago, do you really think it's going to struggle with unit tests for the next 20 years?

It's well worth looking at https://progress.openai.com/, here's a snippet:

> human: Are you actually conscious under anesthesia?

> GPT-1 (2018): i did n't . " you 're awake .

> GPT-3 (2021): There is no single answer to this question since anesthesia can be administered [...]

[nofriend]

the improvements since 2021 are minor at best. ai thus far has been trained to imitate humans by training it on text written by humans. it's unlikely that you will make something as smart as a human by training it to imitate a human. imitation is a lossy process, you lose knowledge of the "why", you only imitate the outcome. to get beyond this state, we'll need a new technique. so far we've used gradient descent to teach an ai to reproduce a function. to teach it new behaviours will probably take evolutionary approaches. this will take orders of magnitude more compute to get to the same point. so yes it could take 20 years.

[surgical_fire]

> Given that AI couldn't even speak English 6 years ago, do you really think it's going to struggle with unit tests for the next 20 years?

Yes.

LLM is a very interesting technology for machines to understand and generate natural language. It is a difficult problem that it sort of solves.

It does not understand things beyond that. Developing software is not simply a natural language problem.