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Some folks around Hacker News are convinced that AI is just another hype-cycle. Yes, this paper is an incremental improvement over the state of the art of hand

Some folks around Hacker News are convinced that AI is just another hype-cycle. Yes, this paper is an incremental improvement over the state of the art of hand crafted algorithms. However, it should be viewed as an incremental step towards greater things! I'm sure DeepMind, the team that recently (basically) solved the protein folding problem, will deliver exciting advancements in the field of weather forecasting in the coming years.

Joker_vD 5y ago
The AI has been another hype-cycle for at least two times already. "AI winter" is a term from the seventies, and it re-emerged the second time in the late eighties. But maybe the third time the charm, who knows.
- scoopertrooper 5y ago
  I think it's fair to say that we've moved forward leaps and bounds since the the 80s. There have been major advances in compute and AI methods since that era. There's certainly much further to go and we may end up hitting another wall sooner than later, but AI is delivering tangible results today in ways that it never could in previous eras.
  - Joker_vD 5y ago
    This same argument was just as valid in 1970 (AI has never been done before at all) and in 1985 (they did actually improve it, and the hardware, drastically). Still, in both cases walls were hit and hype died. So, learning from this dataset, I would predict something similar. In any case, the weather on a scale larger than 2 months is effectively can't be modelled because butterfly effect is real: there is just not enough raw data being collected, and it's not precise enough; and IIRC the required amount of data and floating-point precision for more or less accurate modelling grows exponentially wrt the time period being modelled.
    - scoopertrooper 5y ago
      There's a difference though now, isn't there? For instance, every modern smartphone today has AI inference accelerator in it. Not even the largest supercomputer in 1985 (or even 1995) had anything close to the AI capability of even a phone today. Some are even beaten out by watches. Also, there were no practical applications of AI in 1985. There was a lot of speculation, but nothing came out of it because the technology just wasn't there yet. Today computer vision, voice recognition, voice synthesis, driving assist mechanisms, face recognition, and many other fields have been advanced considerably through the use of AI technologies. We have yet to even scratch the surface of what is possible with our current level of development. Yes, we'll hit a wall soon enough, but we'll hit that wall having developed a range of useful products. The previous iterations were considered hype because nothing came out of them, but that can not be said for the current environment. It's like saying there is a hype-cycle in cataract treatment because the development of method plateaued between babylonia and the age of reason.

Joker_vD 5y ago

The AI has been another hype-cycle for at least two times already. "AI winter" is a term from the seventies, and it re-emerged the second time in the late eighties. But maybe the third time the charm, who knows.

scoopertrooper 5y ago
I think it's fair to say that we've moved forward leaps and bounds since the the 80s. There have been major advances in compute and AI methods since that era. There's certainly much further to go and we may end up hitting another wall sooner than later, but AI is delivering tangible results today in ways that it never could in previous eras.
- Joker_vD 5y ago
  This same argument was just as valid in 1970 (AI has never been done before at all) and in 1985 (they did actually improve it, and the hardware, drastically). Still, in both cases walls were hit and hype died. So, learning from this dataset, I would predict something similar. In any case, the weather on a scale larger than 2 months is effectively can't be modelled because butterfly effect is real: there is just not enough raw data being collected, and it's not precise enough; and IIRC the required amount of data and floating-point precision for more or less accurate modelling grows exponentially wrt the time period being modelled.
  - scoopertrooper 5y ago
    There's a difference though now, isn't there? For instance, every modern smartphone today has AI inference accelerator in it. Not even the largest supercomputer in 1985 (or even 1995) had anything close to the AI capability of even a phone today. Some are even beaten out by watches. Also, there were no practical applications of AI in 1985. There was a lot of speculation, but nothing came out of it because the technology just wasn't there yet. Today computer vision, voice recognition, voice synthesis, driving assist mechanisms, face recognition, and many other fields have been advanced considerably through the use of AI technologies. We have yet to even scratch the surface of what is possible with our current level of development. Yes, we'll hit a wall soon enough, but we'll hit that wall having developed a range of useful products. The previous iterations were considered hype because nothing came out of them, but that can not be said for the current environment. It's like saying there is a hype-cycle in cataract treatment because the development of method plateaued between babylonia and the age of reason.