Language models have shown great capabilities across various tasks. However, complex reasoning remains challenging as it often requires additional computational resources and specialized techniques. This challenge has motivated the development of inference-time compute (ITC) scaling methods, which allocate additional computational…

The pretraining efficiency and generalization of large language models (LLMs) are significantly influenced by the quality and diversity of the underlying training corpus. Traditional data curation pipelines often treat quality and diversity as separate objectives, applying quality filtering followed by…

Proteins are the workhorses that keep our cells running, and there are many thousands of types of proteins in our cells, each performing a specialized function. Researchers have long known that the structure of a protein determines what it can…

While early language models could only process text, contemporary large language models now perform highly diverse tasks on different types of data. For instance, LLMs can understand many languages, generate computer code, solve math problems, or answer questions about images and…

A Knowledge Graph Memory Server allows Claude Desktop to remember and organize information about a user across multiple chats. It can store things like user preferences, past conversations, and personal details. Because the information is saved as a knowledge graph,…

Biology is never simple. As researchers make strides in reading and editing genes to treat disease, for instance, a growing body of evidence suggests that the proteins and metabolites surrounding those genes can’t be ignored. The MIT spinout ReviveMed has…