Periodic lab Tuesday came out of the stealth at the base of the $ 300 million as a seed round, with a technology industry’s Hu Huovits, DST, Nvidia, Axel, Elad Gill, Jeff Dean, Eric Shamidt and Jeff Bezos.
Period labs founded Ekin Dogas Cube and Liam Fedas. The cubes led the Google Brain and Dipmind Materials and Chemistry teams, where he had a project, for example, an AI equipment called Genome. That equipment Invented more than 2 million new crystals in 2023One day materials that can use the power of technology to the new generation, researchers say.
Former VP of the Fedas OpenAI study, and a researcher who helped create ChatzPT. He is also the leadership of the party he created The first trillion-parameter neural networkThe
Its small groups are similarly full of researchers who have worked on the AI of Microsoft’s Microsoft, Microsoft, from OpenAI’s Agent Operator Building to Microsoft, from working on AI of LLM material science to other major AI and material science projects.
The company says that the goal of periodic labs is no less than scientific discovering, creating AI scientists, the company said. This means that the robots made of robots where robots do physical examination, collect data, repeat and try again, learn and improve them.
The first goal of the lab is to discover new supercondctors that hope that performing better than existing supercondacting materials and probably less energy. However, the good startup is expected to find other new materials.
Another goal is to collect data all the physical worlds that produce and heat up with its AI scientists and otherwise manipulate the various energy and raw materials in search of something new.
TechCrunch event
San Francisco
|
October 27-29, 2025
“Now, scientific AI progress comes from the Internet trained models” and LLMS has “tired” the Internet as a source that can be consumed, the company has said in an onset blog post. “In periodic time, we are making AI scientists and autonomous laboratories to manage them.”
It is hoped that only labs will not discover the next generation of materials, but they will create invaluable fresh data that AI models can consume to continue their evolution.
Although it can be one of the impressive groups of researchers to combine a startup for this purpose, this is not the only AI scientists working on. Chemistry Discovery has been AI as AI to Automatic tools Subject to academic research since at least 2023The It follows small startups like Tetsuwan Scientific, as well as ineligible profit Future And the University of Toronto Acceleration consortiumThe