MachineLearning
Atinary announces their latest research on Multi-fidelity Optimization (MFBO), a machine learning technique that optimizes several information sources with different fidelities.
Atinary reaches a major milestone: 5️⃣ years working to transform how science and R&D are done. Happy anniversary Atinary! 🎈
Atinary sponsors the “LLM Hackathon for Applications in Materials Science & Chemistry” at EPFL, Lausanne. Congratulations to our 2 award-winning projects!
In Episode 2 of Atinary's Webinar series, we discussed the capabilities of Atinary SDLabs and IBM's RoboRXN in accelerating chemical reaction optimization.
🔬🚀 Our latest article, a collaboration between Atinary & IBM Research, was published in the May 2024 issue of Chemical Science from the Royal Society of Chemistry!
Atinary announces partnership with the Danish research center dedicated to the discovery of sustainable materials for green transition.
As a machine learning expert, Prof. Hernández-Lobato joins Atinary's advisory board as the company continues to bring the SDLabs technology AI solutions to R&D labs.
Atinary releases the first commercial self-driving lab at Future Labs. Atinary's AI no-code SDLabs platform executes formulation experiments in full autonomy.
Atinary announces collaboration with the group of Prof. Alfredo Alexander-Katz, Laboratory for Soft Materials at Massachusetts Institute of Technology (MIT).
🔬🚀 Our latest article describes a framework and lay out the key technologies to accelerate R&D and optimize experiment planning.
