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Deep Learning is only a small part of AI research. A big part of the rest of machine learning & AI research has been pioneered in the US. However, there have b

by screye 9y ago

Deep Learning is only a small part of AI research. A big part of the rest of machine learning & AI research has been pioneered in the US. However, there have been some huge contributions by UK and Canada throughout the growth of AI.

deepnotderp 9y ago
Dupe from my other reply, but the general sentiment is the same: Again, I was assuming this is talking about deep learning. I understand that hating on deep learning is popular, but the current AI boom, including AlphaGo (which triggered the Chinese interest in AI according to this article) is driven by deep learning.
- abrichr 9y ago
  Also Reinforcement Learning, pioneered by Rich Sutton's group at the University of Alberta.
  - screye 9y ago
    Would just like to put in a mention for Andy Barto (Sutton's pHD advisor) who has contributed as much as Sutton to reinforcement learning. Although Barto is retired now, Barto's lab at UMass Amherst is still alive and kicking (led by another of his pHD and incoming UMass asst. professor in Phil Thomas).
- deleted 9y ago
  [deleted]
tanilama 9y ago
> AI research Prior to Deep Learning, Machine Learning community don't really associated themselves with Artificial Intelligence very often. The AI at the time, if I recall correctly, related more to 70s symbolism and heuristic search approach. Now DL have became the dominant focus, people start to put AI/DL in every places possible, to ride the along the hype. For me it is deep learning that really leads the AI buzzword trend at this point.
- tnecniv 9y ago
  > Prior to Deep Learning, Machine Learning community don't really associated themselves with Artificial Intelligence very often. The AI at the time, if I recall correctly, related more to 70s symbolism and heuristic search approach. It's more complicated than that. First, the AI community had periodic tendencies that oscillated between philosophies and approaches. Every once in a while, someone would make a big contribution, that approach would bloom, then progress would slow for a number of years. There were previous periods where ANNs and other statistical methods were in vogue. Second, it depends on what you define as the AI community and the ML community. For example, speech recognition people have been using Hidden Markov Models for years, which is a statistical/learning method. Is that AI? Is that ML?
- kilburn 9y ago
  General AI conferences such as IJCAI [1] and AAAI [2] have been publishing machine learning papers forever, just as they have been publishing constraint satisfaction-related papers, logics-related papers, multi-agent stuff papers, etc.. Of course non-generalist conferences such as ICML, UAI, AAMAS, etc. focus on more specific topics, and those are considered of the same level (A+) than IJCAI/AAAI. Their existence does not mean that anyone in those fields doesn't think they are not doing AI. In fact, pretty much everyone agrees they are doing AI. If anyone does not agree on that, it is (part of) the pro-"symbolic reasoning" crowd, which sometimes claim only their "strong AI" approach is actual AI and everything else is just little more than mathematical tricks. [1] https://aaai.org/Library/conferences-library.php https://aaai.org/Library/conferences-library.php [2] https://www.ijcai.org/past_proceedings https://www.ijcai.org/past_proceedings

by screye 9y ago

deepnotderp 9y ago

Dupe from my other reply, but the general sentiment is the same: Again, I was assuming this is talking about deep learning. I understand that hating on deep learning is popular, but the current AI boom, including AlphaGo (which triggered the Chinese interest in AI according to this article) is driven by deep learning.

abrichr 9y ago
Also Reinforcement Learning, pioneered by Rich Sutton's group at the University of Alberta.
- screye 9y ago
  Would just like to put in a mention for Andy Barto (Sutton's pHD advisor) who has contributed as much as Sutton to reinforcement learning. Although Barto is retired now, Barto's lab at UMass Amherst is still alive and kicking (led by another of his pHD and incoming UMass asst. professor in Phil Thomas).
deleted 9y ago
[deleted]

tanilama 9y ago

> AI research Prior to Deep Learning, Machine Learning community don't really associated themselves with Artificial Intelligence very often. The AI at the time, if I recall correctly, related more to 70s symbolism and heuristic search approach. Now DL have became the dominant focus, people start to put AI/DL in every places possible, to ride the along the hype. For me it is deep learning that really leads the AI buzzword trend at this point.

tnecniv 9y ago
> Prior to Deep Learning, Machine Learning community don't really associated themselves with Artificial Intelligence very often. The AI at the time, if I recall correctly, related more to 70s symbolism and heuristic search approach. It's more complicated than that. First, the AI community had periodic tendencies that oscillated between philosophies and approaches. Every once in a while, someone would make a big contribution, that approach would bloom, then progress would slow for a number of years. There were previous periods where ANNs and other statistical methods were in vogue. Second, it depends on what you define as the AI community and the ML community. For example, speech recognition people have been using Hidden Markov Models for years, which is a statistical/learning method. Is that AI? Is that ML?
kilburn 9y ago
General AI conferences such as IJCAI [1] and AAAI [2] have been publishing machine learning papers forever, just as they have been publishing constraint satisfaction-related papers, logics-related papers, multi-agent stuff papers, etc.. Of course non-generalist conferences such as ICML, UAI, AAMAS, etc. focus on more specific topics, and those are considered of the same level (A+) than IJCAI/AAAI. Their existence does not mean that anyone in those fields doesn't think they are not doing AI. In fact, pretty much everyone agrees they are doing AI. If anyone does not agree on that, it is (part of) the pro-"symbolic reasoning" crowd, which sometimes claim only their "strong AI" approach is actual AI and everything else is just little more than mathematical tricks. [1] https://aaai.org/Library/conferences-library.php https://aaai.org/Library/conferences-library.php [2] https://www.ijcai.org/past_proceedings https://www.ijcai.org/past_proceedings