106. Yang Gao - Sample-efficient AI
Historically, AI systems have been slow learners. For example, a computer vision model often needs to see tens of thousands of hand-written digits before it can tell a 1 apart from a 3. Even game-play...
8 Joulu 202149min
105. Yannic Kilcher - A 10,000-foot view of AI
There once was a time when AI researchers could expect to read every new paper published in the field on the arXiv, but today, that’s no longer the case. The recent explosion of research activity in A...
1 Joulu 20211h 3min
104. Ken Stanley - AI without objectives
Today, most machine learning algorithms use the same paradigm: set an objective, and train an agent, a neural net, or a classical model to perform well against that objective. That approach has given ...
24 Marras 20211h 6min
103. Gillian Hadfield - How to create explainable AI regulations that actually make sense
It’s no secret that governments around the world are struggling to come up with effective policies to address the risks and opportunities that AI presents. And there are many reasons why that’s happen...
17 Marras 202151min
102. Wendy Foster - AI ethics as a user experience challenge
AI ethics is often treated as a dry, abstract academic subject. It doesn’t have the kinds of consistent, unifying principles that you might expect from a quantitative discipline like computer science ...
10 Marras 202144min
101. Ayanna Howard - AI and the trust problem
Over the last two years, the capabilities of AI systems have exploded. AlphaFold2, MuZero, CLIP, DALLE, GPT-3 and many other models have extended the reach of AI to new problem classes. There’s a lot ...
3 Marras 202153min
100. Max Jaderberg - Open-ended learning at DeepMind
On the face of it, there’s no obvious limit to the reinforcement learning paradigm: you put an agent in an environment and reward it for taking good actions until it masters a task. And by last year, ...
27 Loka 202145min
99. Margaret Mitchell - (Practical) AI ethics
Bias gets a bad rap in machine learning. And yet, the whole point of a machine learning model is that it biases certain inputs to certain outputs — a picture of a cat to a label that says “cat”, for e...
20 Loka 202145min
