Difference between revisions of "History of Artificial Intelligence (AI)"
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* [http://www.techrepublic.com/article/how-china-tried-and-failed-to-win-the-ai-race-the-inside-story/ How China tried and failed to win the AI race: The inside story | Alison Rayome] | * [http://www.techrepublic.com/article/how-china-tried-and-failed-to-win-the-ai-race-the-inside-story/ How China tried and failed to win the AI race: The inside story | Alison Rayome] | ||
* [[Bio-inspired Computing]] | * [[Bio-inspired Computing]] | ||
| + | * [[Feature Exploration/Learning]] | ||
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In AI, there are four generations. | In AI, there are four generations. | ||
Revision as of 18:53, 22 May 2019
- Gaming
- History of Artificial Intelligence | Wikipedia
- Timeline of machine learning | Wikipedia
- A (Very) Brief History of Artificial Intelligence | Bruce G. Buchanan
- How China tried and failed to win the AI race: The inside story | Alison Rayome
- Bio-inspired Computing
- Feature Exploration/Learning
In AI, there are four generations.
- The first generation is the Good Old-fashioned AI, meaning that you handcraft everything and you learn nothing.
- The second generation is shallow learning — you handcraft the features and learn a classifier.
- The third generation, which a lot of people have enjoyed so far, is deep learning. Basically you handcraft the algorithm, but you learn the features and you learn the predictions, end to end. More learning than shallow learning, right?
- And the fourth generation, this is something new, what I work on, I call it “learning-to-learn.” Google Brain Research Scientist Quoc Le on Automated Machine Learning (AML) - AutoML and More
The Turk
