Favorite EPISODE 6: How to secure AI systems “BD: Now we’re in this stage of, ‘Oh my, it works.’ Defending AI was moot 20 years ago. It didn’t do anything that was worth attacking. Now that we have AI systems that really are remarkably powerful, and that are jumping from domain to domain with remarkable…
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Episode 5: transcript
Favorite “MZ: In order to train your networks in reasonable time schedule, we need something like GPU and the GPU requires no free driver, no free firmware, so it will be a problem if Debian community wants to reproduce neural networks in our own infrastructure. If we cannot do that, then any deep learning applications…
Episode 4: transcript
Favorite “DGW: Some people just want to download the software and make porn with it. And if they don’t know how to program, and there is that restriction, that stops them. That’s a meaningful impediment. It’s a speed bump. It doesn’t stop you going down the road, but it makes it harder, it makes it…
Episode 3: transcript
Favorite [00:00:01] Connor Leahy: When a human says something, there’s all these hidden assumptions. If I tell my robot to go get me coffee, the only thing the robot wants to do is to get coffee, hypothetically. It wants to go and get the coffee as quickly as possible, so it’ll run through the wall,…
Episode 2: transcript
Favorite “AT: We know that a lot of the technological stack of AI systems is open. It’s based — funded on open code. That doesn’t solve any of the problems of the black boxes we discussed of possible harms. I think we need to take the spirit of open source, of openness, but really look…
Episode 1: transcript
Favorite [INTRODUCTION] [00:00:00] PC: We’re getting to a point of software development, where it’s not so easy to put things in buckets anymore as to what a human wrote, or what a machine wrote. The concept, may be easy, but I think the application might get really complicated. [00:00:20] SM: Welcome to Deep Dive: AI,…