Personally I define AI as software that you "train" rather than "program". In the sense that neural nets and other ML tools function as black boxes rather than explicit logic.
By that definition, AI is a real thing—it's built on top of programming that uses compilers and languages and ones and zeros—but it's different and it's valuable.
To say it's all bullshit, I feel, is to cut yourself off from new skills. Kind of like "compilers are all bullshit—it's opcodes at the bottom anyway."
AI carries a set of connotations in popular imagination that a) don't comport with the actual capabilities of what we term 'AI' in the computer science world, and b) are being exploited by marketing teams at IBM and plenty of other companies to sell technologies that aren't particularly new or interesting. The kernel of truth in 'AI is bullshit' is really that the discourse around AI is bullshit, which I think is a pretty fair assessment, and this is coming from someone who's work gets labeled as AI on a regular basis.
>I define AI as software that you "train" rather than "program".
I like this definition. It covers things that are AI but not ML, like DSS / rules engines. I've built two fairly sophisticated DSS before but haven't messed with ML much. It seems interesting, but I haven't had the time.
By that definition, AI is a real thing—it's built on top of programming that uses compilers and languages and ones and zeros—but it's different and it's valuable.
To say it's all bullshit, I feel, is to cut yourself off from new skills. Kind of like "compilers are all bullshit—it's opcodes at the bottom anyway."