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Today, the key challenge in AI isn’t only how to build better models; it’s how to build evaluation systems that can keep up. Search-augmented AI systems can now produce deep research reports — long, polished syntheses of many sources that increasingly resemble expert analysis. But those reports are useful only if their claims are supported by the underlying literature. Most exis...

Routing in today’s data centers is usually governed by a data structure called a “fat tree”, which is similar to a corporate organizational chart, with nodes in each layer connecting to multiple nodes in the layer below. Here, however, the nodes of the bottom layer represent routers that want to send messages to each other, and the layers above them contain extra routers that si...

Amazon Research Awards (ARA) provides unrestricted funds and AWS Promotional Credits to academic researchers investigating various research topics in multiple disciplines. This cycle, ARA received many excellent research proposals from across the world and today is publicly announcing 68 award recipients who represent 49 universities in 11 countries. This announcement includes a...

Large language models (LLMs) are pretrained on huge volumes of unlabeled data, but afterward, they’re typically post-trained on specific tasks such as instruction following, avoiding harmful outputs, and reasoning, or providing justifications for the outputs they generate. Parallel reasoning — in which multiple, diverse reasoning paths are generated and compared for the same pro...

Large language models (LLMs) keep getting bigger and better. But the cost of running them — generating text, answering questions, powering real-time applications — is scaling up, too. Obviously, model accuracy is important, but for real-time AI-based web applications, it can’t come at the expense of efficiency. In a paper we presented at the International Conference on Learning ...