The data from mobile phones is revolutionizing our understanding of human activity. In recent years, it has revealed commuting patterns in major cities, wealth distribution in African countries, and even reproductive strategies in western societies. That has provided unprecedented insight for economists, sociologists, and city planners among others. But this kind of advanced research is just…
Source: The Website That Visualizes Human Activity in Cities Across the World
… human experts have written a large amount of ITP code, which provides an opportunity to develop machine learning systems to imitate humans for interacting with the proof assistant. Such a combination would get us closer to fully automated human-like proofs.
Source: Learning to prove theorems via interacting with proof assistants | the morning paper
AI models can learn to perform some tasks to human or even super-human levels, but do they then perform those tasks in a human-like way? And does that even matter so long as the outcomes are good? If we’re going to hand everything over to AI and get out of the way, then maybe not. But where humans are still involved in task performance, supervision, or evaluation, then McIlroy-Young et al. make the case that this difference in approaches really does matter.
Source: Aligning superhuman AI with human behaviour: chess as a model system | the morning paper
A startup called CogitAI has developed a platform that lets companies use reinforcement learning, the technique that gave AlphaGo mastery of the board game Go. Gaining experience: AlphaGo, an AI program developed by DeepMind, taught itself to play Go by practicing. It’s practically impossible for a programmer to manually code in the best strategies for winning. Instead, reinforcement…
Source: Now any business can access the same type of AI that powered AlphaGo
David Duvenaud was collaborating on a project involving medical data when he ran up against a major shortcoming in AI. An AI researcher at the University of Toronto, he wanted to build a deep-learning model that would predict a patient’s health over time. But data from medical records is kind of messy: throughout your life, you might visit the…
Source: A radical new neural network design could overcome big challenges in AI
MultiMed Engineers