AI

Boost cold-start recommendations with vLLM on AWS Trainium

Cold start in recommendation systems goes beyond just new user or new item problems—it’s the complete absence of personalized signals at launch. When someone first arrives, or when fresh content appears, there’s no behavioral history to tell the engine what they care about, so everyone ends up in broad generic segments. That not only dampens

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Robot, know thyself: New vision-based system teaches machines to understand their bodies

In an office at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), a soft robotic hand carefully curls its fingers to grasp a small object. The intriguing part isn’t the mechanical design or embedded sensors — in fact, the hand contains none. Instead, the entire system relies on a single camera that watches the robot’s

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Benchmarking Amazon Nova: A comprehensive analysis through MT-Bench and Arena-Hard-Auto

Large language models (LLMs) have rapidly evolved, becoming integral to applications ranging from conversational AI to complex reasoning tasks. However, as models grow in size and capability, effectively evaluating their performance has become increasingly challenging. Traditional benchmarking metrics like perplexity and BLEU scores often fail to capture the nuances of real-world interactions, making human-aligned evaluation

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Pedestrians now walk faster and linger less, researchers find

City life is often described as “fast-paced.” A new study suggests that’s more true that ever. The research, co-authored by MIT scholars, shows that the average walking speed of pedestrians in three northeastern U.S. cities increased 15 percent from 1980 to 2010. The number of people lingering in public spaces declined by 14 percent in

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New machine-learning application to help researchers predict chemical properties

One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule’s properties, such as its boiling or melting point. Once researchers can pinpoint that prediction, they’re able to move forward with their work yielding discoveries that lead to medicines, materials, and more. Historically, however, the traditional methods of unveiling

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Customize Amazon Nova in Amazon SageMaker AI using Direct Preference Optimization

At the AWS Summit in New York City, we introduced a comprehensive suite of model customization capabilities for Amazon Nova foundation models. Available as ready-to-use recipes on Amazon SageMaker AI, you can use them to adapt Nova Micro, Nova Lite, and Nova Pro across the model training lifecycle, including pre-training, supervised fine-tuning, and alignment. In this

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Multi-tenant RAG implementation with Amazon Bedrock and Amazon OpenSearch Service for SaaS using JWT

In recent years, the emergence of large language models (LLMs) has accelerated AI adoption across various industries. However, to further augment LLMs’ capabilities and effectively use up-to-date information and domain-specific knowledge, integration with external data sources is essential. Retrieval Augmented Generation (RAG) has gained attention as an effective approach to address this challenge. RAG is

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