DeepMind’s AlphaCode attains ‘average’ rating in programming competition
A team of researchers at DeepMind has tackled another difficult task—generating computer code to satisfy a natural language request. In their paper published in the journal Science, the group describes the approach they used in creating their AI app and outline how well it did when pitted against human programmers. J. Zico Kolter with Carnegie Mellon University has published a Perspective piece in the same journal issue outlining many of the issues involved in getting a computer to generate computer code and the work done by the team in London.
A team of researchers at Google's Deep Mind London project, has taught animated players how to play a realistic version of soccer on a computer screen. In their paper published in the journal Science Robotics, the group describes teaching the animated players to play as solo players and also in…
A team of researchers at Google's DeepMind, London, has found that AI can find faster algorithms to solve matrix multiplication problems. In their paper published in the journal Nature, the group describes using reinforcement learning to improve math-based algorithms. A Research Briefing has also been published in the same journal…
In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an…