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Which rate of progress are we ITT expecting from alphacode-like models? In another thread I predicted we’d see competitive programming “solved” in ten years or
by qualudeheart 5y ago
Which rate of progress are we ITT expecting from alphacode-like models?
In another thread I predicted we’d see competitive programming “solved” in ten years or less.
I didn’t rigorously explain what I meant by that in that thread, so I’ll clarify what I meant.
I expect AI to beat humans at competitive programming at the same rate as AlphaGo beats human Go players.
There could be diminshing returns soon but I don’t see what would cause them.
- Misdicorl 5y agoThe places AI excel still have very rigid rules with relatively low branching factors. It's also relatively easy to score both the final result and any intermediate stage. And all the training techniques rely on those factors tremendously. My guess is that's where the difficulties will arise.
- belter 5y agoI am willing take on your bet, as long you agree with my condition...you can't feed it with any of the millions of lines of code previously created by humans you aim to beat...;-)
- machiaweliczny 5y agoI think we need AI to learn to simplify problems because no human (at least not me) solves these problems as stated but works on limited inputs and mostly via brute-force. Then you see some generalisation and you have your solution. Are they already doing that? If not expect 2x improvement easily. Also it would be great if algos were aware where in embedding space their solution is and then try to jump between "approaches".
- machiaweliczny 5y agoOk, I've skimmed the paper and they are doing clustering grouping by tests results. Ok that's first step. Now please instead do grouping by classification of algorithm by other NN first.
- GreenWatermelon 5y agoHow would the AI learn then? Humans learn by looking at existing code and gleaning new ideas, and does the AI although it requires much more data. Give the AI as much data as it wants, if it manages to solve something, it means it's a problem worth automating (is this a cat?)
- posterboy 5y ago> Humans learn by looking at existing code and gleaning new ideas, and does the AI although it requires much more data. Actually I doubt it. There are different ways to learn, the cheapest of which is observation indeed. There's also trial and error, how most enthusiast start with little more than a description of the grammar if it's primitive enough, famously so for the BASIC varieties. Of course this leads to local minima and frustration quickly, Turing Tarpits e.g., but it also leads to independent discovery and rediscovery. At the next step of learning, I believe, it's the differentiation that makes ... all the difference – ie. learning about the development of languages and eventually of computing machines per se. At a higher order of learning it cannot be limited to calculation without a semantic interface (and vice versa). I mean, etymologies like ominous calx (Latin "pebble", cp. chalk, calcium) for calculation, and symbolical notation show the kind of "code" that we copy from. That said, I'd think at the current state of the art, the ai would have to look at the machine code as the representation of its output eventually (perhaps because I found myself wanting to do that), even if encoded through macros and programming language devices, which it could do entirely unsupervised. However, understanding the task is a more general problem, isn't it?
- qualudeheart 5y agoBelter was probably joking. A good logic programming ai could do competitive programming through purely deductive reasoning. I just don’t see good evidence that’ll be possible at a world class level in 10 year.
- red75prime 5y agoPurely deductive reasoning will crash and burn in a combinatorial explosion if there's nothing to guide it to the kind of problems it may encounter.
- meken 5y agoSure you can. You would just have to be careful not to accidentally feed it the same problem as in the competition. That would be cheating.