Talk

Inioluwa Deborah Raji is a Nigerian-Can

This talk will present Basil, a new transactional Byzantine Fault Tolerant database. Basil leverages ACID transactions to scalably implement the abstraction of a trusted shared log in the presence of Byzantine actors.

Recent breakthroughs in Artificial Intelligence (AI) have produced a new class of neural networks called Large Language Models (LLMs) that demonstrate a remarkable capability to generate fluent, plausible responses to prompts posed in natural language.

Recent breakthroughs in Artificial Intelligence (AI) have produced a new class of neural networks called Large Language Models (LLMs) that demonstrate a remarkable capability to generate fluent, plausible responses to prompts posed in natural language.

In this talk, I will explore three elements of designing next-generation machine learning systems: congestion control, network topology, and computation frequency.

Predicting a protein’s structure from its primary sequence has been a grand challenge in biology for the past 50 years, holding the promise to bridge the gap between the pace of genomics discovery and resulting structural characterization.

In the era of big biological data, there is a pressing need for methods that visualize, integrate and interpret high-throughput high-dimensional data to enable biological discovery. There are several major challenges in analyzing high-throughput biological data.

We have promised social scientists a data revolution, but it hasn’t arrived.  What stands between practitioners and the data-driven insights they want?

Many computational challenges in machine learning involve the three problems of optimization, integration, and fixed-point computation. These three can often be reduced to each other, so they may also provide distinct vantages on a single problem.