In a new study, researchers from Google DeepMind have created an AI system that is capable of generating creative chess puzzles, some of which impressed experts in chess compositions.

Leading evolutionary theorists and philosophers come together to understand how organisms persist, even as they’re riddled with internal conflict, from cancer cells to selfish genes.How does a vast me...

The rapid adoption of autonomous AI agents is giving rise to a new economic layer where agents transact and coordinate at scales and speeds beyond direct human oversight. We propose the "sandbox econo...

npj Complexity - Self-organizing systems: what, how, and why?

Neural development and brain circuit evolution converged in birds and mammals

Course Web site: http://timroughgarden.org/f13/f13.html (includes lecture notes and homeworks). Course description: Broad survey of topics at the interface o...

YouTube video by AI4All

YouTube video by AI4All

Have you registered for MEXA's next Virtual Hackathon, 𝙈𝙚𝙣𝙩𝙖𝙡 𝙃𝙚𝙖𝙡𝙩𝙝 𝙖𝙣𝙙 𝘼𝙄: 𝙄𝙣𝙩𝙚𝙧𝙫𝙚𝙣𝙩𝙞𝙤𝙣? Now is the time!⏰ Join us in…

While large language models perform well on a range of complex tasks (e.g., text generation, question answering, summarization), robust multi-step planning and reasoning remains a considerable challen...

This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement learning and sequential decision making, covering value-based RL, policy-gradient methods, model-based met...

Virtual Event - An overview of Google's efforts to develop flexible machine learning tools to help understand biodiversity through sounds recordings

YouTube video by FIDE chess

In this essay, we take a tour of how AI is transforming scientific disciplines from genomics to computer science to weather forecasting. Some scientists are training their own AI models, while...

LLM-based programming assistants offer the promise of programming faster but with the risk of introducing more security vulnerabilities. Prior work has studied how LLMs could be maliciously fine-tuned...

We examine multi-task benchmarks in machine learning through the lens of social choice theory. We draw an analogy between benchmarks and electoral systems, where models are candidates and tasks are vo...

Language models have shown impressive performance on tasks within their training distribution, but often struggle with novel problems requiring complex reasoning. We investigate the effectiveness of t...