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I agree that self-driving had/have been overhyped over the previous few years. The problem is harder than many people realize. The difference between the curre

I agree that self-driving had/have been overhyped over the previous few years. The problem is harder than many people realize. The difference between the current AI renaissance and the past pre-winter AI ecosystems is the level of economic gain realized by the technology. The late 80s-early 90s AI winter, for example, resulted from the limitations of expert systems which were useful but only in niche markets and their development and maintenance costs were quite high relative to alternatives. The current AI systems do something that alternatives, like Mechanical Turks, can only accomplish with much greater costs and may not even have the scale necessary for global massive services like Google Photos or Youtube autocaptioning. The spread of computing infrastructure and connectivity into the hands of billions of global population is a key contributing factor.

felippee 8y ago
> The difference between the current AI renaissance and the past pre-winter AI ecosystems is the level of economic gain realized by the technology I would argue this is well discounted by level of investment made against the future. I don't think the winter depends on the amount that somebody makes today on AI, rather on how much people are expecting to make in the future. If these don't match, there will be a winter. My take is that there is a huge bet against the future. And if DL ends up bringing just as much profit as it does today, interest will die very, very quickly.
- nopinsight 8y ago
  Because there is a dearth of experts and a lack of deep technical knowledge among many business people, there are still a great many companies that have not yet started investing in deep learning or AI despite potential profits based on current technology. Non-tech sectors of the economy are probably underinvesting at the moment. This is analogous to the way electricity took decades to realize productivity gains in the broad economy. That said, the hype will dial down. I am just not sure the investment will decrease soon.
  - sanxiyn 8y ago
    While I agree there is underinvestment in non-tech sectors, I don't see why that would change and they will use deep learning. There are lots of profitable things in non-tech sectors that can be done with linear regression but not done.
    - cm2187 8y ago
      There are lots of things in the non-tech sector that can be automated with simple vanilla software but isn't. To use AI instead, you need to have 1) sophisticated devs in place, 2) a management that gets the value added, 3) lots of data in a usable format, 4) willingness to invest & experiment. Lots of non-tech businesses are lacking one if not all of these.
    - xamuel 8y ago
      This. And at the end of the day, deep learning is just a more sophisticated version of linear regression. (To listen to some people talking, you'd think if a machine just curve-fits enough data-points, it'll suddenly wake up and become self-aware or something? The delusion is just unbelievable!)
- sgt101 8y ago
  Just like it did for ecommerce? Expectations we're wildly inflated, there was a bust, the market re adjusted and value was created
  - rusk 8y ago
    Only after the dot-com bust killed off all the weaklings ... there was a brief "cold-snap" after 2001 ... then Web 2.0 happened. So I guess we're waiting for something similar to happen with AI and then get AI 2.0?
Yaggo 8y ago
> I agree that self-driving had/have been overhyped over the previous few years. The problem is harder than many people realize. The current road infrastructure (markings, signs) has been designed for humans. Once it has been modernized to better aid the self-driving systems, we don't probably need "perfect" AI.
- dx034 8y ago
  But current signs designed for humans work well. They're machine readable (traffic sign detection is available from basically all manufacturers) and can (usually) be understood without prior knowledge and don't need much change over decades. I think there are few examples where messages were designed for computers but are easy to understand independent of the system, manufacturer. ASCII encoded text files are the only thing that come to mind.

felippee 8y ago

> The difference between the current AI renaissance and the past pre-winter AI ecosystems is the level of economic gain realized by the technology I would argue this is well discounted by level of investment made against the future. I don't think the winter depends on the amount that somebody makes today on AI, rather on how much people are expecting to make in the future. If these don't match, there will be a winter. My take is that there is a huge bet against the future. And if DL ends up bringing just as much profit as it does today, interest will die very, very quickly.

nopinsight 8y ago
Because there is a dearth of experts and a lack of deep technical knowledge among many business people, there are still a great many companies that have not yet started investing in deep learning or AI despite potential profits based on current technology. Non-tech sectors of the economy are probably underinvesting at the moment. This is analogous to the way electricity took decades to realize productivity gains in the broad economy. That said, the hype will dial down. I am just not sure the investment will decrease soon.
- sanxiyn 8y ago
  While I agree there is underinvestment in non-tech sectors, I don't see why that would change and they will use deep learning. There are lots of profitable things in non-tech sectors that can be done with linear regression but not done.
  - cm2187 8y ago
    There are lots of things in the non-tech sector that can be automated with simple vanilla software but isn't. To use AI instead, you need to have 1) sophisticated devs in place, 2) a management that gets the value added, 3) lots of data in a usable format, 4) willingness to invest & experiment. Lots of non-tech businesses are lacking one if not all of these.
  - xamuel 8y ago
    This. And at the end of the day, deep learning is just a more sophisticated version of linear regression. (To listen to some people talking, you'd think if a machine just curve-fits enough data-points, it'll suddenly wake up and become self-aware or something? The delusion is just unbelievable!)
sgt101 8y ago
Just like it did for ecommerce? Expectations we're wildly inflated, there was a bust, the market re adjusted and value was created
- rusk 8y ago
  Only after the dot-com bust killed off all the weaklings ... there was a brief "cold-snap" after 2001 ... then Web 2.0 happened. So I guess we're waiting for something similar to happen with AI and then get AI 2.0?

Yaggo 8y ago

> I agree that self-driving had/have been overhyped over the previous few years. The problem is harder than many people realize. The current road infrastructure (markings, signs) has been designed for humans. Once it has been modernized to better aid the self-driving systems, we don't probably need "perfect" AI.

dx034 8y ago
But current signs designed for humans work well. They're machine readable (traffic sign detection is available from basically all manufacturers) and can (usually) be understood without prior knowledge and don't need much change over decades. I think there are few examples where messages were designed for computers but are easy to understand independent of the system, manufacturer. ASCII encoded text files are the only thing that come to mind.