Tessera
Folgen

Philipp Marquetand

@marquetand.bsky.social

Machine learning for different domains ranging from graphic design to chemistry.

4 Posts109 Follower185 Folgt
Claudio Zeni@claudiozeni.bsky.social · 2y ago

📢 Paper + code release 📃💻 After 2 years of work, I'm excited to announce our newest paper, MatterGen, has been published in Nature! www.nature.com/articles/s41... We are also releasing all the training data, model weights, model code, and evaluation code on GitHub! github.com/microsoft/ma...

GitHub - microsoft/mattergen: Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards...

Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c...

github.com

Microsoft Research@msftresearch.bsky.social · 2y ago

Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments. www.microsoft.com/en-us/resear...

mr. TIM@timkellogg.me · 2y ago

⚠️ Readable Paper Alert ⚠️ BLT: what if we just got rid of tokenization? Result: * text looks a lot like audio, video, PDF, it’s all just bytes * dynamically reduce compute based on difficulty * new scaling axis (patch size) ai.meta.com/research/pub...

Byte Latent Transformer: Patches Scale Better Than Tokens | Research - AI at Meta

We introduce the Byte Latent Transformer (BLT), a new byte-level LLM architecture that, for the first time, matches tokenization-based LLM performance at...

ai.meta.com