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Since its beginning in the 1950s, the field of artificial intelligence has vacillated between periods of optimistic predictions and massive investment and periods of disappointment, loss of confidence, and reduced funding. Even with today’s seemingly fast pace of AI breakthroughs, the development of long-promised technologies such as self-driving cars, housekeeping robots, and conversational companions has turned out to be much harder than many people expected. Professor Melanie Mitchell thinks one reason for these repeating cycles is our limited understanding of the nature and complexity of intelligence itself.
YT vid- https://www.youtube.com/watch?v=A8m1Oqz2HKc
Main show kick off [00:26:51]
Panel: Dr. Tim Scarfe, Dr. Keith Duggar, Letitia Parcalabescu (https://www.youtube.com/c/AICoffeeBreak/)
By Machine Learning Street Talk (MLST)4.7
8585 ratings
Since its beginning in the 1950s, the field of artificial intelligence has vacillated between periods of optimistic predictions and massive investment and periods of disappointment, loss of confidence, and reduced funding. Even with today’s seemingly fast pace of AI breakthroughs, the development of long-promised technologies such as self-driving cars, housekeeping robots, and conversational companions has turned out to be much harder than many people expected. Professor Melanie Mitchell thinks one reason for these repeating cycles is our limited understanding of the nature and complexity of intelligence itself.
YT vid- https://www.youtube.com/watch?v=A8m1Oqz2HKc
Main show kick off [00:26:51]
Panel: Dr. Tim Scarfe, Dr. Keith Duggar, Letitia Parcalabescu (https://www.youtube.com/c/AICoffeeBreak/)

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