DeepMind’s program AlphaGo beat Fan Hui, the European Go champion, five times out of five in tournament conditions, the firm reveals in research published in Nature on 27 January. It also defeated its silicon-based rivals, winning 99.8% of games against the current best programs. The program has yet to play the Go equivalent of a world champion, but a match against South Korean professional Lee Sedol, considered by many to be the world’s strongest player, is scheduled for March. “We’re pretty confident,” says DeepMind co-founder Demis Hassabis.
The technique is deep recurrent learning with neural networks.
Distributed Solar: The Democratizaton of Energy
Blogroll
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- Woods Hole Oceanographic Institution (WHOI)
- The Keeling Curve: its history
- AP Statistics: Sampling, by Michael Porinchak
- GeoEnergy Math
- Professor David Draper
- Mertonian norms
- All about models
- Dominic Cummings blog
- Harvard's Project Implicit
climate change
- ATTP summarizes all that stuff about Committed Warming
- Isaac Held's blog
- Professor Robert Strom's compendium of resources on climate change
- Reanalyses.org
- Mrooijer's Global Temperature Explorer
- "Impacts of Green New Deal energy plans on grid stability, costs, jobs, health, and climate in 143 countries" (Jacobson, Delucchi, Cameron, et al)
- "Betting strategies on fluctuations in the transient response of greenhouse warming"
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- weather blocking patterns
- Mathematics and Climate Research Network
Archives
Jan Galkowski
ecoquant
