Why does an LLM need to produce human readable code at all? Especially in a language optimized around preventing humans from making human mistakes. For now, sure, we're in the transitional period, but in the long run? Why?
Why does an LLM need to produce human readable code at all? Especially in a language optimized around preventing humans from making human mistakes. For now, sure, we're in the transitional period, but in the long run? Why?
"It has been lost in AI money-grabbing frenzy but a few years ago we were talking a lot about AIs being “legible”, that they could explain their actions in human-comprehensible terms. “Running code we can examine” is the highest grade of legibility any AI system has produced to date. We should not give that away.
"We will, of course. The Number Must Go Up. We aren’t very good at this sort of thinking.
"But we shouldn’t."
If we do enough passes of synthetic or goal-based training of source code generation, where the models are trained to successfully implement things instead of imitating success, then we may see new programming paradigms emerge that were not present in any training data. The "new language" would probably not be a programming language (because we train on generating source FOR a language, not giving it the freedom to generate languages), but could be new patterns within languages.
Assuming that after the transitional period it will still be humans working with ai tools to build things where humans actually add value to the process. Will the human+ai where the ai can explain what the ai built in detail and the human leverages that to build something better, be more productive that the human+ai where the human does not leverage those details?
That 'explanation' will be/can act as the human readable code or the equivalent. It does not need to be any coding language we know today however. The languages we have today are already abstractions and generalizations over architectures, OSs, etc and that 'explanation' will be different but in the same vein.
If you take your question and look into the future, you might consider the existence of an LLM specifically trained to take high-level language inputs and produce machine code. Well, we already have that technology: we call it a compiler. Compilers exist, are (frequently) deterministic, and are generally exceedingly good at their job. Leaving this behind in favor of a complete English -> binary blob black box doesn't make much sense to me, logically or economically.
I also think there is utility in humans being able to read the generated output. At the end of the day, we're the conscious ones here, we're the ones operating in meatspace, and we're driving the goals, outputs, etc. Reading and understanding the building blocks of what's driving our lives feels like a good thing to me. (I don't have many well-articulated thoughts about the concept of singularity, so I leave that to others to contemplate.)