Gemini 4 Argon: our next era of frontier intelligence
Gemini 4 Argon: our next era of frontier intelligence
October 01, 2026
Gemini 4 Argon: our next era of frontier intelligence
Introducing SynthID Bio
Disrupting a coordinated model-distillation campaign
Helping small businesses put AI to work
DevDay 2026 Recap
Introducing GPT-6.1 Sol
Introducing dots
How we will do better for Australia
Towards safety cases for frontier AI training
The Lenfest Institute grows landmark program with expanded OpenAI support
$\textit{BlockFormer}$ : Transformer-based inference from genomic contact maps
$D^2$-Monitor: Dynamic Safety Monitoring for Diffusion LLMs via Hesitation Signals
3D Software Synthesis Driven by Constraint-Expressive Intermediate Representation
A 3GPP-Compliant Benchmark Dataset for RIS-Aided Beyond 5G Networks
A Competing-Hazards Systematization of Loss of Control in Autonomous Agents
A Comprehensive Benchmark of Source-Free Universal Domain Adaptation on Time Series Representations
A Data-Free Physics-Informed Neural Operator for Level-Set Interface Advection
A differentiability framework for zigzag persistent homology via linear interpolation
A Dynamical Theory of LoRA in Continual Learning
A Flow Matching Algorithm for Many-Shot Adaptation to Unseen Distributions
Deep learning perturbation models can outperform baselines on calibrated metrics
Shifting from knowledge retrieval to evidence exploration and synthesis
Times are changing but order matters: transferable prediction of small-molecule liquid chromatography retention times
Function-preserving watermarking of AI-generated proteins
Secret watermark labels proteins as ‘made by AI’
This award-winning microscopy image used AI — igniting controversy in a prestigious competition
WeedNet: a foundation model-based global-to-local AI approach for weed species identification and classification
AI can widen science — but only if institutions stop rewarding the already measurable
AI-powered medical devices must be tested in real-world settings
Phylogeny-agnostic strain-level prediction of phage–host interactions from genomes using machine learning