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Google AI is advancing scientific research and improving lives through innovative applications in education and healthcare. The company's machine learning technologies are accelerating discoveries and solving complex global challenges.
Learn how Faraday, an AI agent created by DeepMind alumni, can read and replicate scientific research faster than traditional methods, potentially accelerating scientific discovery.
Google's top AI researchers, including Jeff Dean, have left to found Discovery Loop, a startup focused on using AI for breakthrough discoveries in drug development, chip design, and scientific research.
Learn how to build a basic AI-powered scientific data analysis tool that demonstrates the same principles being used by OpenAI and national labs to accelerate discovery.
Synthetic Sciences has released OpenScience, an open-source, model-agnostic AI workbench for scientific research in machine learning, biology, physics, and chemistry.
Learn how to set up and use Claude Science, a multi-agent AI workbench for scientific research in genomics, proteomics, and cheminformatics.
OpenAI introduces LifeSciBench, an expert-authored benchmark for evaluating AI systems in real-world life science research tasks. The platform aims to advance AI's role in scientific discovery by providing a standardized framework for assessing AI capabilities in biomedical research.
Learn to build a data integration pipeline that unifies scattered scientific data from spreadsheets and legacy systems, mirroring Altara's approach to accelerate R&D.
Learn how a new AI startup called Mirendil is using artificial intelligence to accelerate scientific discoveries in biology and materials science. Discover what AI can do for research and why it matters for the future of science.
Learn how to implement Google's Gemini 3 Deep Think AI framework for scientific research and engineering problem-solving using Python and Google Cloud.
