Introducing Google Antigravity

Introducing Google Antigravity 2.0

Extending single-minus amplitudes to gravitons

A new preprint extends single-minus amplitudes to gravitons, with GPT-5. 2 Pro helping derive and verify nonzero graviton tree amplitudes in quantum gravity.

Generalized Quadratic Gradient: A New Direction in Optimization via the Fusion of Positive-Definite Curvature Matrices and Gradients into A Unified Framework

arXiv:2608. 01552v1 Announce Type: cross Abstract: Quadratic Gradient (QG) is a Newton-type optimization framework that bridges first-order gradient descent and second-order optimization by incorporating curvature information into gradient updates.

Simulate real-world places with Project Genie and Street View

We’re expanding access to Google AI Ultra subscribers globally and introducing a new capability powered by Street View.

Try Deep Think in the Gemini app

We're rolling out Deep Think in the Gemini app for Google AI Ultra subscribers, and we're giving select mathematicians access to the full version of the Gemini 2. 5 Deep Think model entered into the IMO competition.

We’re launching the Google DeepMind Accelerator program in Asia Pacific to tackle environmental risks

Google's year in review: 8 areas with research breakthroughs in 2025

Google 2025 recap: Research breakthroughs of the year

Announcing our partnership with the Republic of Korea

Google DeepMind and Korea partner to accelerate scientific breakthroughs using frontier AI models

Iso-Riemannian Optimization on Learned Data Manifolds

arXiv:2510. 21033v3 Announce Type: replace-cross Abstract: We develop a theory of iso-Riemannian optimization for problems constrained to learned data manifolds, a setting in which classical Riemannian optimization - and Riemannian gradient descent in particular - can be poorly suited.

GPT-5 and the future of mathematical discovery

UCLA Professor Ernest Ryu and GPT-5 solved a key question in optimization theory, showcasing AI’s role in accelerating mathematical discovery.

The Real Challenge Limiting AI Models Today

Hint: it is not GPU speed! The post The Real Challenge Limiting AI Models Today appeared first on Towards Data Science .

A Neural Network Framework for Geodesic-Like Curve Computation on Parametric Surfaces

arXiv:2606. 18759v1 Announce Type: cross Abstract: The concept of geodesic-like curves was introduced by Chen in 2010 as a method for estimating shortest paths (geodesics) on parametric surfaces, with its convergence established theoretically.