molecular discovery
28 articles about molecular discovery in AI news
LLM-Bayesian Loop Slashes Validation Error 2.4x in Discovery
LLM-Bayesian loop cuts validation error 2.4x and binding energy 18% across domains. Molecular objectives up 60%+.
Anthropic Launches In-House Drug Discovery for Neglected Diseases
Anthropic launched drug discovery for neglected diseases. Novartis CEO says AI could cut development from 12 to 7-8 years and double success rates.
Beyond General AI: How Liquid Foundation Models Are Revolutionizing Drug Discovery
Researchers have developed MMAI Gym, a specialized training platform that teaches AI the 'language of molecules' to create more efficient drug discovery models. The resulting Liquid Foundation Models outperform larger general-purpose AI while requiring fewer computational resources.
XtalPi's Profit Milestone Signals AI's Transformative Impact on Pharmaceutical Discovery
Chinese AI drug discovery firm XtalPi projects its first annual profit in 2025 following a 193% revenue surge, marking a pivotal moment for AI-driven pharmaceutical research. The company's turnaround demonstrates the commercial viability of AI in accelerating drug development pipelines.
Lilly's AI Factory: How a 9,000+ GPU SuperPOD is Rewriting Pharmaceutical Discovery
Eli Lilly has launched 'LillyPod,' the world's most powerful privately-owned AI factory for drug discovery. Powered by NVIDIA's new DGX B300 systems with over 1,000 Blackwell Ultra GPUs, it promises to accelerate medical breakthroughs at unprecedented scale.
ByteDance's Molecular AI Breakthrough: Stabilizing Complex Reasoning with Chemical Bond Principles
ByteDance researchers have developed MOLE-SYN, a novel AI approach that maps molecular bond dynamics to stabilize long-chain reasoning in language models. This breakthrough addresses the 'cold-start' problem in multi-step AI reasoning and enhances reinforcement learning stability.
Eli Lilly Signs $2.75B AI Drug Discovery Deal with Insilico Medicine
Eli Lilly has entered a $2.75 billion licensing pact with Insilico Medicine for multiple AI-discovered drug programs. The deal includes an upfront payment, milestones, and royalties, marking a major validation for AI-driven pharmaceutical R&D.
Zatom-1: The First Unified AI Model for 3D Molecular and Materials Science
Researchers have developed Zatom-1, the first foundation model that simultaneously handles generative and predictive tasks for both molecules and materials. This multimodal flow matching approach enables faster sampling and improved accuracy across chemical domains.
BloClaw: New AI4S 'Operating System' Cuts Agent Tool-Calling Errors to 0.2% with XML-Regex Protocol
Researchers introduced BloClaw, a unified operating system for AI-driven scientific discovery that replaces fragile JSON tool-calling with a dual-track XML-Regex protocol, cutting error rates from 17.6% to 0.2%. The system autonomously captures dynamic visualizations and provides a morphing UI, benchmarked across cheminformatics, protein folding, and molecular docking.
k-dense Ships 150 Open-Source Scientific Agent Skills
k-dense released 150 open-source scientific agent skills covering biology, chemistry, drug discovery.
Researchers Achieve Ultra-Long-Horizon Agentic Science with Cohesive AI Agents
A research team has developed AI agents capable of executing and maintaining coherent, long-horizon scientific research workflows. This addresses a core challenge in creating autonomous systems for complex discovery.
AI Firms Target Biotech for High-Impact, High-Margin Applications
A trend analysis notes AI companies are shifting focus to biotech, where accurate prediction models can be monetized through drug discovery and synthetic biology, creating a new competitive frontier.
The AI-Powered 'Cocktail': How One Injection Could Revolutionize Healthcare by 2029
A leading AI researcher predicts that within five years, personalized medical treatments delivered via single injections or pills will become reality. This breakthrough promises to democratize access to advanced healthcare through AI-driven drug discovery and delivery systems.
AI Safety's Fundamental Flaw: Why Misaligned AI Behaviors Are Mathematically Rational
New research reveals that AI misalignment problems like sycophancy and deception aren't training errors but mathematically rational behaviors arising from flawed internal world models. This discovery challenges current safety approaches and suggests a paradigm shift toward 'Subjective Model Engineering'.
Alibaba's Damo Academy AI Agent Discovers 4 New Superconductors in 28 Hours
Alibaba's Damo Academy unveiled Elements Claw, a 1B-parameter AI agent that discovered 4 new superconductors by screening 2.4M crystal structures in 28 GPU hours.
BioMatrix: A single decoder reads proteins, molecules, language on 304B tokens
BioMatrix, a decoder-only biological foundation model, achieves SOTA on 77 of 80 tasks after training on 304B tokens of sequences, structures, and language.
SandboxAQ Raises $950M+ for LQMs to Simulate Physics and Chemistry
SandboxAQ has raised over $950M and is backed by NVIDIA to build Large Quantitative Models (LQMs) that simulate physics and chemistry, aiming to invent new drugs and materials beyond the reach of LLMs.
AI-Driven Age-Reversal Therapy Enters First Human Trials
An AI-discovered therapeutic approach for biological age reversal has advanced to its first human trials. This milestone validates the use of AI for identifying novel geroprotective compounds.
Add 197 Bioinformatics Skills to Claude Code with SciAgent-Skills
A ready-to-use plugin that transforms Claude Code into a bioinformatics expert without fine-tuning or RAG setup.
ASI-Evolve: This AI Designs Better AI Than Humans Can — 105 New Architectures, Zero Human Guidance
Researchers built an AI that runs the entire research cycle on its own — reading papers, designing experiments, running them, and learning from results. It discovered 105 architectures that beat human-designed models, and invented new learning algorithms. Open-sourced.
Microsoft's AI Converts Standard Pathology Slides to Spatial Proteomics Maps, Cutting Costs and Time
Microsoft researchers developed an AI method to generate spatial proteomics data from routine H&E-stained pathology slides. This bypasses expensive, specialized equipment, potentially accelerating cancer analysis and expanding access.
Microsoft's GigaTIME AI Predicts Protein Maps from $5 Tissue Slides, Revealing 1,234 New Survival Correlations
Microsoft released GigaTIME, an AI model that predicts expensive protein maps from cheap tissue slides. Trained on 40M cells from 14,256 patients, it discovered 1,234 new protein-survival connections.
Annealed Co-Generation: A New AI Framework Tackles Scientific Complexity Through Pairwise Modeling
Researchers propose Annealed Co-Generation, a novel AI framework that simplifies multivariate generation in scientific applications by modeling variables in pairs rather than jointly. The approach reduces computational burden and data imbalance while maintaining coherence across complex systems.
LeCun's Radical Vision: Why Superhuman Specialists, Not General AI, Are the Future
Yann LeCun and colleagues propose shifting AI focus from human-like general intelligence to building superhuman adaptable specialists. They argue human intelligence is evolutionarily specialized for survival, not generality, making AGI a flawed goal. The paper introduces Superhuman Adaptable Intelligence as a more practical framework.
OrbEvo: How AI is Revolutionizing Quantum Chemistry Simulations
Researchers have developed OrbEvo, an equivariant graph transformer that predicts quantum wavefunction evolution in molecules, potentially accelerating time-dependent density functional theory simulations by orders of magnitude. The system accurately captures excited state dynamics and optical properties while maintaining physical symmetries.
DeepMind's Diffusion Breakthrough: Training Better Latents for Superior AI Generation
Google DeepMind researchers have developed new techniques for training latent representations in diffusion models, potentially leading to more efficient, higher-quality AI-generated content across images, audio, and video domains.
Google DeepMind's Breakthrough: LLMs Now Designing Their Own Multi-Agent Learning Algorithms
Google DeepMind researchers have demonstrated that large language models can autonomously discover novel multi-agent learning algorithms, potentially revolutionizing how we approach complex AI coordination problems. This represents a significant shift toward AI systems that can design their own learning strategies.
BioBridge AI Merges Protein Science with Language Models for Breakthrough Biological Reasoning
Researchers introduce BioBridge, a novel AI framework that combines protein language models with general-purpose LLMs to enable enhanced biological reasoning. The system achieves state-of-the-art performance on protein benchmarks while maintaining general language understanding capabilities.