Right now #ai seems like magic bullet to all solutions. Preliminary success indicators also help the narrative. Its only when instead of teaching how to use ai you use it then you realize its shortcomings just like every other software in existence. Treating ai as yet another software more importantly as a solution still looking for right problem set is imho the way we need to look at things.

There are use-cases still but do they justify the compute power resources and cost. That is where the real rubber meet the road scenarios come into picture.

At this point everyone is squeezing all other funds to create or enlarge funds for r&d and use that for cloud or hardware for ai. This is the part which will hurt the most once people put it in prod and realise the true cost.

#randomrambling #aidisillusions #technology #itsecurity

@anant

I have tried few PoCs and used these so called AI apps.

• None of these apps live up to their hype. What is not informed is the number of times a prompt is modified to arrive at a solution. Or the manual intervention needed for the final output.
• As you say the operational cost is enormous. It is not discussed anywhere. So CEOs (and managers who attend these conferences and virtual demos) think they are fire all their employees and AI tools will do all the jobs. When IT / Dev team gets back with actual results, they are termed as incompetent. Frustration everywhere.

As Seth Godwin once named his book - “All marketers are liars” 😀

@anant This twitter thread seems to sum up this discussion: https://x.com/ChrisAlvino/status/1804823161076080887
Chris Alvino (@ChrisAlvino) on X

I still can't get over how bad AI has become. And this is coming from a computer scientist who spent over a decade studying and programming AI. I fucking LOVE AI, but here are 10 reasons I absolutely fucking hate it now, a 🧵 ...

X (formerly Twitter)