The one thing that I learned when talking to chatGPT or any other AI on a technical subject is you have to ask the AI to cite its sources. Because AIs can absolutely bullshit without knowing it, and asking for the sources is critical to double checking.
I consider myself very average, and all my average interactions with AI have been abysmal failures that are hilariously wrong. I invested time and money into trying various models to help me with data analysis work, and they can’t even do basic math or summaries of a PDF and the data contained within.
I was impressed with how good the things are at interpreting human fiction, jokes, writing and feelings. Which is really weird, in the context of our perceptions of what AI will be like, it’s the exact opposite. The first AI’s aren’t emotionless robots, they’re whiny, inaccurate, delusional and unpredictable bitches. That alone is worth the price of admission for the humor and silliness of it all, but certainly not worth upending society over, it’s still just a huge novelty.
It makes HAL 9000 from 2001: A Space Odyessy seem realistic. In the movie he is a highly technical AI but doesn’t understand the implications of what he wants to do. He sees Dave as a detriment to the mission and it can be better accomplished without him… not stopping to think about the implications of what he is doing.
I mean, leave it up the one of the greatest creative minds of all time to predict that our AI will be unpredictable and emotional. The man invented the communication satellite and wrote franchises that are still being lined up to make into major hollywood releases half a century later.
I’ve found questions about niche tools tend to get worse answers. I was asking if some stuff about jpackage and it couldn’t give me any working suggestions or correct information. Stuff I’ve asked about Docker was much better.
The ability of AI to write things with lots of boilerplate like Kubernetes manifests is astounding. It gets me 90-95% of the way there and saves me about 50% of my development time. I still have to understand the result before deployment because I’m not going to blindly deploy something that AI wrote and it rarely works without modifications, but it definitely cuts my development time significantly.
The one thing that I learned when talking to chatGPT or any other AI on a technical subject is you have to ask the AI to cite its sources. Because AIs can absolutely bullshit without knowing it, and asking for the sources is critical to double checking.
I consider myself very average, and all my average interactions with AI have been abysmal failures that are hilariously wrong. I invested time and money into trying various models to help me with data analysis work, and they can’t even do basic math or summaries of a PDF and the data contained within.
I was impressed with how good the things are at interpreting human fiction, jokes, writing and feelings. Which is really weird, in the context of our perceptions of what AI will be like, it’s the exact opposite. The first AI’s aren’t emotionless robots, they’re whiny, inaccurate, delusional and unpredictable bitches. That alone is worth the price of admission for the humor and silliness of it all, but certainly not worth upending society over, it’s still just a huge novelty.
It makes HAL 9000 from 2001: A Space Odyessy seem realistic. In the movie he is a highly technical AI but doesn’t understand the implications of what he wants to do. He sees Dave as a detriment to the mission and it can be better accomplished without him… not stopping to think about the implications of what he is doing.
I mean, leave it up the one of the greatest creative minds of all time to predict that our AI will be unpredictable and emotional. The man invented the communication satellite and wrote franchises that are still being lined up to make into major hollywood releases half a century later.
I’ve found questions about niche tools tend to get worse answers. I was asking if some stuff about jpackage and it couldn’t give me any working suggestions or correct information. Stuff I’ve asked about Docker was much better.
The ability of AI to write things with lots of boilerplate like Kubernetes manifests is astounding. It gets me 90-95% of the way there and saves me about 50% of my development time. I still have to understand the result before deployment because I’m not going to blindly deploy something that AI wrote and it rarely works without modifications, but it definitely cuts my development time significantly.
Well that is obvious why, isn’t it!?
Microsoft LLM whatever the name is gives sources, or at least it did to me yesterday.