Songkick Co-Founder Ian Hogarth on the Emerging Geopolitics of AI | BoF VOICES
The Business of Fashion Podcast
The Business of Fashion
4.6 • 770 Ratings
🗓️ 11 March 2019
⏱️ 17 minutes
🧾️ Download transcript
Summary
Angel investor and co-founder of Songkick Ian Hogarth explores how the race to develop the most sophisticated artificial intelligence will define geopolitics in the coming decades.
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Transcript
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| 0:00.0 | Hi, I'm Imran Ahmed, founder and CEO of the Business of Fashion. Welcome to the BOF podcast. |
| 0:08.9 | One of the things we learned about at Voices 2018 was the growing power of mega technology companies. |
| 0:15.0 | And one area in which they are all competing is the field of artificial intelligence. |
| 0:19.7 | Could this growing arms race and AI create a |
| 0:23.3 | whole new kind of geopolitics? This was something that Ian Hogarth spoke about at Voices 2018. |
| 0:30.1 | Ian believes that machine learning will transform the economy and the military so unrecognizably |
| 0:36.1 | that it will create instability at the national and international level, |
| 0:40.5 | requiring further government intervention. |
| 0:43.4 | Ian is an angel investor in over 40 startups, where the main focus of his investing is an applied machine learning. |
| 0:50.0 | Previously, he co-founded Songkick, the concert service used by 17 million music fans every month to discover live events. |
| 0:58.4 | So here's Ian Hogarth on the emerging geopolitics of AI at Voices 2018. |
| 1:06.9 | So, yeah, I wrote an essay on this topic. |
| 1:09.5 | There was 6,600 words long because it turns out that AI and geopolitics are quite big topics. So I'm going to try and do the 10-minute version for you now. So I'll be talking maybe a little bit quicker than some of the other speakers. So the central prediction that I want to make to you is that continued rapid progress in machine |
| 1:29.9 | learning is driving a new kind of geopolitics called AI nationalism. |
| 1:36.0 | And the last few years have seen pretty amazing developments in machine learning, and I wanted |
| 1:39.6 | to sort of just start off by recapping what's happened and why I think we're going through a period of profound |
| 1:44.9 | change. So firstly, as a few examples of research and machine learning, image recognition |
| 1:50.6 | by machines has started to achieve human level accuracy at very complex pattern recognition |
| 1:56.5 | tasks, for example, skin cancer classification. We've also seen big steps forward in things like |
| 2:02.5 | machine translation where Microsoft system has achieved human parity in translation of news articles |
| 2:10.1 | from Chinese to English. And those are examples of a technique called Deep Learning, which was |
| 2:15.9 | invented a while back but has started to really work with the amount of data and computing power we now have. Another technique that has |
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