I have come up with the perfect job for AI

There are some hugely useful things AI is currently doing such as in GPUs.

But the applications of AI in everything is way over done and most of it wont work.

There is one profession where AI fits in mistakes and all perfectly. Yes AI weathermen. The world wont notice the difference.

:rofl: :rofl: :rofl:

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On which planet? (put them all on Venusproblem SOLVED).

Weather forecast accuracy has improved greatly over the last 40 years, and AI might be used for further improvements. But weather is highly complex, and so the best forecaster in the near future will continue to be humans using computer tools (maybe including AI). Todays AI is clearly better than humans at chess. AI alone will not be better at weather forecasting for many years.

5G might make weather forecasts less accurate.

The quiet revolution of numerical weather prediction
As a computational problem, global weather prediction is comparable to the simulation of the human brain and of the evolution of the early Universe These scientific and technological developments have led to increas- ing weather forecast skill over the past 40 years. Importantly, this skill can be objectively and quantitatively assessed, as every day we compare the forecast with what actually occurs. For example, forecast skill in the range from 3 to 10 days ahead has been increasing by about one day per decade: todays 6-day forecast is as accurate as the 5-day forecast ten years ago, as shown in Fig. 1.
https://www.researchgate.net/publication/281516336_The_quiet_revolution_of_numerical_weather_prediction

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Lots of researchers are trying to use machine learning to improve weather forecasting.

I like this from Seifert and Rasp,

Plain Language Summary In our work, we are trying to teach a computer how rain forms in clouds. We show that computer hundreds of cases in the form of data. To be honest, the data are not real data but only results of simulations with a more complicated computer model. This complicated model can track the collisions of 10,000 of droplets, and we save all that data about the growth of the droplets into larger raindrops. This is what we then give to the simpler computer model to teach it something about clouds and rain. Afterward, it can make pretty good predictions about which clouds will rain and how long it will take them to produce the first rain. Unfortunately, the current machine learning methods are still a bit stupid because they only learn from the data but do not understand the mathematics and the physics behind the data. Therefore, the new computer model is still not as good at predicting rain as some clever mathematical formulas that were developed 20 years ago. Maybe we first have to teach the computer model more about calculus before it can learn to predict rain.

https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020MS002301

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