What do tech pioneers think about the AI revolution? – BBC World Service

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Three leading engineers discuss the impact of the AI revolution.

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Intelligent machines are remaking our world. The speed of their improvement is accelerating fast and every day there are more things they can do better than us. There are risks, but the opportunities for human society are enormous.

Three engineers at the forefront of that revolution come to London to join Caroline Steel and a public audience at the Great Hall of Imperial College.

Regina Barzilay from MIT created a major breakthrough in detecting early stage breast cancer. She also led the team that used machine learning to discover Halicin, the first new antibiotic in 30 years.

David Silver is Principal Research Scientist at Google DeepMind. He led the AlphaGo team that built the AI to defeat the world’s best human player of Go.

Paolo Pirjanian founded Embodied, and is a pioneer in developing emotionally intelligent robots to aid child development.

Producer: Charlie Taylor

00:00 Introduction
02:10 How AI could be used to detect cancer early
03:47 Gaming and reinforcement learning
05:42 Robot companions
07:08 What can AI do to detect cancer that humans can’t?
08:12 Can computers learn to be intuitive?
09:45 How robots can build emotional bonds
10:42 The first AI influenced antibiotic
12:26 Narrow AI vs Artificial general intelligence
13:43 Why isn’t AI used in medicine more?
15:05 Can “emotional” AI help humanity to be come better?
16:23 Should we use AI to create art and culture?
17:43 Audience questions
18:15 Should you have to understand the consequences of AI before using it?
20:09 Are robots going to take all our jobs?
21:39 Can AI help with sport performance?
22:59 Will depending on AI stop humans from learning?

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22 Comments

  1. I'm personally wondering if we need AGI at all, because humans, IMO, are "jack of all trades, master of none" kind of things. For example, our arms are able to perform a wide range of tasks, yet for every subset of those there's a simpler solution that also happens to work better. In other words, won't it be more useful to build a wide range of specialized lightweight ai tools instead of one generalized that needs to be run in a huge data center and requires a nuclear power plant to power itself?

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