Filtered by: LLM

Assistant Professor Ambuj Varshney and his WEISER research group are building a way around this. His project, “TinyLLM: A Framework for Training and Deploying Language Models at the Edge Computers”, has been selected for the 2026 Google Awards for Machine Learning Research and Education with TPUs.

Training a large language model is not just about writing good code and pressing run. These models are spread across hundreds or thousands of processors – such as Google's Tensor Processing Units (TPUs), specialised accelerators designed to train and serve large-scale machine learning models – that must learn to work in lockstep: exchanging data, splitting tasks, staying synchronised. When something goes wrong, the whole system slows down, and expensive hardware sits idle. 

NUS Presidential Young Professor Yang You from NUS Computing's Department of Computer Science has been selected for the Google 2026 Awards for Machine Learning Research and Education with TPUs.

Explore how scalable collaborative zk-SNARKs enable fast, secure zero-knowledge proofs across multiple servers. This breakthrough improves privacy and scalability for AI verification, blockchain, and data markets, making advanced cryptography more accessible.