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This is a bit over-hyped and not exactly a breakthrough. It’s not doing true weather prediction but rather extrapolating the movement of radar images. This is n

by JCM9 5y ago

This is a bit over-hyped and not exactly a breakthrough. It’s not doing true weather prediction but rather extrapolating the movement of radar images. This is nothing new. I remember as far back as the 1990s TV weathermen would draw a line across a line of moving rain and the computer would predict which town it would get to and when. Slapping “AI” on this 25 years later is an good example of the whole present PR move of labeling things as “AI” that are just rather basic data analytics.

donjuan7331 5y ago
yep, I was researching precipitation nowcasting i.e. extrapolating radar images years ago using "AI"
Jabbles 5y ago
AI doing something that humans used to do but better is pretty much the whole point of AI. The chasm between drawing a line on a map and this system is enormous, and represents 30 years of research. It doesn't have to be a breakthrough to be in the news, it's a routine advancement of the state-of-the art.
- JCM9 5y ago
  No. Drawing the line on the map was just used to decide where you wanted to show the prediction for. The forward looking prediction models themselves have been around for decades.
- ekianjo 5y ago
  You did not need Black box neural networks to do statistics before.
  - spywaregorilla 5y ago
    You don't need a black box neural network to do statistics now. But it might be a good tool nonetheless. And it might be much less of a black box than you imagine.
    - ekianjo 5y ago
      As far as i know the understanding of how multi layered neural networks actually work is a hot research topic.
      - spywaregorilla 5y ago
        It is, but in many cases its still pretty easy to figure out. It depends on how complicated the problem is. If it's truly an incomprehensible nonlinear cesspool, then its pretty much impossible. If it's secretly a linear regression with a few forks and inflection points, its easy. The problems neural nets are used for do tend to fall into the former, but the techniques to unravel it are getting better.
sailingparrot 5y ago
That sounds like petty criticism to me. What exactly is "true weather prediction" then? Using a crystal ball? And yes, extrapolation is not new, but deep learning is just much better at it. > labeling things as “AI” that are just rather basic data analytics They are using a GAN to do this, you can't get more AI than this. If this is not AI, then what is? Getting accurate short term predictions is very valuable for e.g. prediction of solar panels energy production to avoid starting coal peaker plants, or to predict flooding. I get that it's popular to dunk on anything called AI to show that you have not fallen prey to the PR bullshit machine, but in that case, it's 100% unwarranted in my opinion.
- dr-detroit 5y ago
  the point is that when academics and private entities start throwing around the word "AI" for anything digital they are cashing in on other people's hard work and diluting the positive effects of actual AI research.
- scoopertrooper 5y ago
  I generally agree with your points, but nowcasting is definitely the less exciting problem for ML to solve. Also, applying a GAN to nowcasting is definitely not a novel idea. You'd hope that given that modern ML methods can handle crazy high dimensional data that someone would be able to do something with weather forecasting beyond current models. However, there are many factors that render this a 'hard' problem. I guess, starting off with nowcasting is a neat way for DeepMind to become acquainted with the topic matter, but I'd hope they have their ambitions set a little higher. Here's an interesting paper on this topic: https://royalsocietypublishing.org/doi/10.1098/rsta.2020.0097 https://royalsocietypublishing.org/doi/10.1098/rsta.2020.009...
  - sailingparrot 5y ago
    Sure, that might not be a Nobel prize worthy breakthrough, but it is still very much AI, and it is still very much "true" weather prediction. I just don't understand where the gatekeeping on both point is coming from.

by JCM9 5y ago

donjuan7331 5y ago

yep, I was researching precipitation nowcasting i.e. extrapolating radar images years ago using "AI"

Jabbles 5y ago

AI doing something that humans used to do but better is pretty much the whole point of AI. The chasm between drawing a line on a map and this system is enormous, and represents 30 years of research. It doesn't have to be a breakthrough to be in the news, it's a routine advancement of the state-of-the art.

JCM9 5y ago
No. Drawing the line on the map was just used to decide where you wanted to show the prediction for. The forward looking prediction models themselves have been around for decades.
ekianjo 5y ago
You did not need Black box neural networks to do statistics before.
- spywaregorilla 5y ago
  You don't need a black box neural network to do statistics now. But it might be a good tool nonetheless. And it might be much less of a black box than you imagine.
  - ekianjo 5y ago
    As far as i know the understanding of how multi layered neural networks actually work is a hot research topic.
    - spywaregorilla 5y ago
      It is, but in many cases its still pretty easy to figure out. It depends on how complicated the problem is. If it's truly an incomprehensible nonlinear cesspool, then its pretty much impossible. If it's secretly a linear regression with a few forks and inflection points, its easy. The problems neural nets are used for do tend to fall into the former, but the techniques to unravel it are getting better.

sailingparrot 5y ago

That sounds like petty criticism to me. What exactly is "true weather prediction" then? Using a crystal ball? And yes, extrapolation is not new, but deep learning is just much better at it. > labeling things as “AI” that are just rather basic data analytics They are using a GAN to do this, you can't get more AI than this. If this is not AI, then what is? Getting accurate short term predictions is very valuable for e.g. prediction of solar panels energy production to avoid starting coal peaker plants, or to predict flooding. I get that it's popular to dunk on anything called AI to show that you have not fallen prey to the PR bullshit machine, but in that case, it's 100% unwarranted in my opinion.

dr-detroit 5y ago
the point is that when academics and private entities start throwing around the word "AI" for anything digital they are cashing in on other people's hard work and diluting the positive effects of actual AI research.
scoopertrooper 5y ago
I generally agree with your points, but nowcasting is definitely the less exciting problem for ML to solve. Also, applying a GAN to nowcasting is definitely not a novel idea. You'd hope that given that modern ML methods can handle crazy high dimensional data that someone would be able to do something with weather forecasting beyond current models. However, there are many factors that render this a 'hard' problem. I guess, starting off with nowcasting is a neat way for DeepMind to become acquainted with the topic matter, but I'd hope they have their ambitions set a little higher. Here's an interesting paper on this topic: https://royalsocietypublishing.org/doi/10.1098/rsta.2020.0097 https://royalsocietypublishing.org/doi/10.1098/rsta.2020.009...
- sailingparrot 5y ago
  Sure, that might not be a Nobel prize worthy breakthrough, but it is still very much AI, and it is still very much "true" weather prediction. I just don't understand where the gatekeeping on both point is coming from.