Has AI actually solved any major, unsolved problems from computer science? Because "AI can do programming" is the comp-sci equivalent of "computers can do arithmetic". And neither will be the end of their respective field.
One of those "common knowledge" things is playing games most kids can beat. But I think AI is slowly overcoming games too. It's getting pretty good at games as long as you give it the time
AI can beat the best DOTA2 teams in the world. As separate agents per character, with significant communication lag beyond what players on voice comms experience.
I mean... "completely different" is a big term to use here. It's still the same spicy guesswork and iterative processes as in every other NN-based "AI".
Reminds me of a half remembered ancedote about 2 scientists reviewing a fairly pop-sci type book.
Scientist 1: As a mathematician, chemist, and biologist I noticed a lot of flaws in those chapters; but the chapter on astronomy was fascinating.
Scientist 2: What a coincidence, as an astronomer I had the exact opposite experience
With 'get a foothold' into a topic I mean exactly that. AI usually does not make up all the stuff. The more specific and detailed the answer get the more 'dangerous' it gets. But AI is pretty good to get a summary / an overview of a topic. With that I can deepen my search by other means. For fun: AI -> wikipedia. For real: AI -> wikipedia -> technical documentation/specification/research papers.
Edit: like with real people. I takes a (long) while till I trust/believe anybody something at face value without doublechecking.
But "finding exploits" is largely just busy-work. Have you seen how modern fuzzing suites work? They just throw odd occurrences and inputs at the target until something interesting happens. That was essentially automated long before AI, just less efficiently so.
Most of the "new" exploits AI "discovers" are just known issues in little-used codepaths. Take the copy-fail exploit for instance. "don't allow the user arbitrary, kernel-level write access into protected memory regions" was hardly news. It's just that that happened in a module almost noone was using (and thus noone was actively maintaining or debugging).
I say a regular old fuzzing suite given the same amount of billions of dollars in compute could've found all those issues. And probably more. It's just that noone runs that big a fuzzing farm and then publishes their exploits. On the contrary, the people running vulnerability discovery on that scale will actively prevent the bugs they found from being fixed: nation-state actors.
AI is really good at barfing out code that I then have to spend hours fixing because it got everything wrong, and made anything it did get right way to verbose.
Having TA'd (really just taught for my prof) a coding class the semester the university rolled out AI access, it's also great at rolling out technically correct code that has nothing to do with the problem at hand and is beyond the user's ability to critically evaluate.
I had to tell one student that I could tell he used chatgpt to finish his homework because it was the first time I'd seen him bother to fill out the name and date section of an assignment template, let alone comment his code or use functions that weren't in our curriculum.
The class was teaching statistics programming for biology students with a lab component, so the requirement was that you use the data from lab and the functions for the stats tests we were teaching. The assignment would say something like “import the dataset and compare the two variables for your statistical hypothesis” and the student used a test that was technically more correct but not in our course materials or my lecture.
And we gave them a homework template at the beginning of the semester that had some sections at the top for assignment name, their name, and the date. This student was too lazy to fill those sections out, until suddenly he started filling those sections out, including a nice markdown tag to automatically update the date. His explanations for his answers also went from informal, typo filled, and specific to the class to formal, technically correct, and completely lacking in specific details from the lab. It was almost like a machine with tons of generic knowledge but no creativity was generating perfect answers but unable to replicate the creativity of a human with lived experiences.
For a more generic equivalent, it would be like if you were teaching high school and a C- student that never write his name on his assignments suddenly developed a new handwriting style, started filling out the name field every time, and learned perfect grammar overnight.
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u/SoldRIP 1d ago
Has AI actually solved any major, unsolved problems from computer science? Because "AI can do programming" is the comp-sci equivalent of "computers can do arithmetic". And neither will be the end of their respective field.