The errors that quantum computers make are holding the technology back. But recent progress in quantum error correction has ...

As AI systems began acing traditional tests, researchers realized those benchmarks were no longer tough enough. In response, nearly 1,000 experts created Humanity’s Last Exam, a massive 2,500-question ...

Farming is changing from manual, experience-led observation to data-driven decision-making powered by advanced sensing systems and artificial intelligence. A new research paper titled “Fast Forward ...

Sarvam’s open-sourced Indic-focused reasoning models signal India’s AI ambition, but missing tooling, ecosystem gaps and ...

DeepMind’s AlphaProof system solved four out of six problems at the 2024 International Mathematical Olympiad, generating ...

The introduction of AI into mathematics represents a seismic shift in what it means to do math. When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works.

Valued at $1.6 billion, a tiny start-up called Axiom is building A.I. systems that can check for mistakes. Axiom Math’s founder and chief executive, Carina Hong, right, and the chief technology ...

People are increasingly using AI auto-complete features when writing. Unbeknownst to them, that feature may change how they think.

Erdos, explores what researchers call autoformalization, the process of converting traditional mathematical proofs into formats machines can verify using tools such as Lean and Coq.

People and computers perceive the world differently, which can lead AI to make mistakes no human would. Researchers are working on how to bring human and AI vision into alignment.

Abstract: The pathfinding problem in a graph has been solved using several classical algorithms, notably Dijkstra’s and A* algorithms. However, most classical algorithms are most effective on static ...

Within the STRUCTURES Cluster of Excellence, two research teams at the Interdisciplinary Center for Scientific Computing (IWR) have refined a computing process, long held to be unreliable, such that ...