Hello everyone! For many years, I have been coding every once in a while and actually learned a lot. I especially liked C and C-Like languages and building useless stuff just for fun and for the sake of the intellectual challenge that came with it, but since when AI became decent enough, it just kinda ruined the passion for programming and computers as a whole. Thing is, I am in university now and need to go back to using C and program regularly, but now that AI does everything 20000 times better than I ever will I always either cede to temptation to use it (thus nullifying learning) or just get bored so quickly I just turn off the computer to do something different.

is there a way to revive the interest for programming and building projects? I am doing my best to stop using AI but heck I really am self-indulging. please help!

  • FizzyOrange@programming.dev
    13·
    7 days ago

    It is not known how much AI can be improved

    I didn’t say it was. But at this point it would be a pretty wild prediction to think it’s not going to continue to rapidly improve.

          • FizzyOrange@programming.dev
            11·
            5 days ago

            A few reasons:

            1. The evidence so far seems to be that AI capability scales with compute, and compute continues to advance. Including with crazy AI hardware like Cerebras and Taalas. There are still a ton of AI hardware startups that have yet to tape out.
            2. There’s an enormous amount of research into algorithmic and infrastructure improvements, which also show no signs of slowing down.
            3. Empirically, it has been getting better continuously for several years now. There appears to be no reason to suspect any blockers.

            In other words: why not?

            To steel man, the main reasons I would counter with are:

            1. Moore’s law is pretty much dead… Except that we still have a ton of headroom with custom AI-focused chips. E.g. I know of at least two startups working on DRAM stacked on the compute chip instead of next to it, which gives dramatically higher memory bandwidth.
            2. There are still a couple of architectural issues, e.g. context length is limited, AI can’t really remember/learn things on-line, hallucination is not solved. But… in practice those problems seem to not matter too much and also hallucinations seem less common the more capable the model is, so maybe it doesn’t need an architectural solution at all.
            • agentlangdon@infosec.pubEnglish
              11·
              5 days ago

              “dram stacked on the compute chip” is the amd x3d design which has been out for gaming PCs for years now.

              The rest of your statements seem clueless and completely based on AI company marketing.

              • FizzyOrange@programming.dev
                1·
                5 days ago

                amd x3d design which has been out for gaming PCs for years now.

                That’s SRAM, not DRAM. But sure, I’m the clueless one.