The meteorological industry has seen a remarkable impact from large language models in the field of artificial intelligence. The emergence of models like GPT-3 has greatly enhanced the precision and accuracy of weather forecasting. By analyzing extensive weather datasets and patterns, meteorologists can now predict weather trends with higher levels of accuracy, which has revolutionized the industry.
The use of AI in weather forecasting has transformed decision-making when it comes to public safety and disaster response. AI models can analyze extensive data in real-time, offering timely recommendations and critical interventions, resulting in better public safety. Although AI’s role in advancing weather forecasting still needs further exploration, it is clear that these models play a significant role in providing valuable insights and mitigating risks.
The potential for AI in weather forecasting is almost limitless, and the industry can continue to leverage large language models’ power to enhance public safety. It is exciting to consider where this technology will lead the industry in the future as there are enormous possibilities.
I’m sure that weather forecasting and medicine and a lot of other disciplines will be well-regulated, but in general what I prefer to call Machine Intelligence - which makes clear that it includes robotics - has the potential for self-inflicted disaster.
I remember the '70s when Edinburgh UP used to publish Max Newman and Jack Good and Donald Michie (Bletchley men) and others, when it seemed to the casual observer that the trivial goal was to get computers to graduate from playing Noughts and Crosses to playing Chess. . . and they did. But it went a lot deeper than that.
I am now of the opinion that, inadvertently, we could soon reach a situation rather like that described by Oppenheimer with his quote from the Bhagavad Vita. . .
Yes, I confess that I don’t know an awful lot about it; and no, I am not a Luddite - it’s just a gut feeling
I have to admit being a little devious with the quote. It was actually written by the AI function in some software I was testing. AI content generation is becoming mainstream!
Generally, I’m against AI for whatever purpose. Every good technology can be (and it is) used for bad purposes. I’m not sure how well GPT was generating various text, articles, etc., if people didn’t write about the same content before. This is just taking (stealing?) data and rephrasing them into new text.
Now youth do not even bother googling for content but just tell GPT to find it for them. Who will make further research, work on technological innovation, optimize hardware, etc.?
Time ago I put a label “Content without AI” on my weather page. I want my content to be authentic, not in perfect grammar and even contain human mistakes. We’re people.
I agree that the use of AI to generate content does seem to become limiting as more AI content is generated. Once it starts to feed itself who knows what is true and what isn’t. However, I was interested to see what it would say when I asked about using AI for meterological applications. The repsonse is actually quite reasonable and I must admit that had I read it without knowing where it came from I wouldn’t have suspected that it was machine generated. That’s why I wanted to see if anyone else could see that it wasn’t written by a human.
I will say that I wish my maths was better because I’d love to use AI in a meterological application. Not for generating content but for analysing weather data to look for patterns that I’d probably never see as a human observer. Imagine feeding your weather station data into a machine learning app and after looking at months (or preferably years) of data it could tell you things like “When the wind is from the NE at between 10 and 20mph, with a surface temperature between 5 and 10C and RH between 55 and 65%, then it will likely rain heavily within the next hour”. OK a made up example, but hopefully you can see what I’m getting at.
I’ve looked at this a few times in the past but I really don’t have the skills to take it on in a meaningful way. I can do the IT side but that’s the easy bit compared to trying to define the model and get it to learn.
I agree the AI could do a nice job with correlating preceding conditions with actual event. My comment was meant more general how good technology is eventually used for bad purposes.
Anyway, the AI is here but I can simply decide not to use it
The text you pasted in the original post really reads as written by human. However, if you read it carefully again, it doesn’t tell something useful. It is just a lot of text with no concrete answer how (based on what data) the AI can warn public of approaching storm or flood.
I don’t believe a word he says. He’s probably trying to get laws put in place to stop others doing what he wants to do but isn’t ready to do just yet. Then he’ll just ignore the laws when he’s ready with his own solution.
I see that, despite moving X from San Francisco, Musk supports the California AI safety bill.
Geoff Hinton does too, and is quoted as saying “Powerful AI systems bring incredible promise, but the risks are also very real and should be taken extremely seriously.”
I don’t take any notice of what Musk says. He’s extremely self-serving so if he supports something it’s only because it benefits him or his pet project to control the world.
