In the New Space Race, Who Makes the Rules? - Freakonomics

We don’t care for others because they’re conscious. We believe they’re conscious because we care about them, argues Blaise Agüera y Arcas

We are headed toward a world of productivity without prosperity, execution without verification and capacity without constraint. But this outcome is not inevitable.

Should A.I. Move to Space? - Freakonomics

Ten Nature contributors share their current book obsessions.

A.I. labs are hiring contrarian, chin-stroking, finger-steepling sages. Who’s underemployed now?

The question of "what is life?" has challenged scientists and philosophers for centuries, producing an array of definitions that reflect both the mystery of its emergence and the diversity of discipli...

As automated reasoning systems advance rapidly, there is a growing need for research-level formal mathematical problems to accurately evaluate their capabilities. To address this, we present Formal Co...

The question of "what is life?" has challenged scientists and philosophers for centuries, producing an array of definitions that reflect both the mystery of its emergence and the diversity of discipli...

Buy your pass and choose between our FT subscriber pass ( for FT subscribers only), General, Student or Digital registration. FT Weekend Festival: NYC Edition 20 June 2026.

A leading AI researcher known for innovations such as Federated Learning and on-device machine learning. Blaise’s work spans computational imaging, privacy-respecting architectures, and exploring AI at the intersection of society, art, and ethics. Author of recent books and essays on intelligence and the future of AI. ALIFE is the world's premiere Artificial Life conference. This year’s theme is Ciphers of Life, encouraging participants to explore the many ways that life encodes information, creates internal languages, and interacts in encrypted ways with its environment. ALIFE brings together leading scientists and trailblazing companies to forge new technologies, offering attendees and sponsors alike, a front-row seat to the future!

Achieving cooperation among self-interested agents remains a fundamental challenge in multi-agent reinforcement learning. Recent work showed that mutual cooperation can be induced between "learning-aw...

A new study reveals that top models like DeepSeek-R1 succeed by simulating internal debates. Here is how enterprises can harness this "society of thought" to build more robust, self-correcting agents.

En collaborant avec d'innombrables personnes, nous avons bâti une société d'une grande complexité. Selon Blaise Agüera y Arcas, chercheur en IA chez Google, nous ferons bientôt la même chose avec des ...

We report on an astonishing ability of large language models (LLMs) to make sense of "Jabberwocky" language in which most or all content words have been randomly replaced by nonsense strings, e.g., tr...