Reactive Machines

Boost cold-start recommendations with vLLM on AWS Trainium

Boost cold-start recommendations with vLLM on AWS Trainium

[ad_1] Cold start in recommendation systems goes beyond just new user or new item problems—it’s the complete absence of personalized…
Benchmarking Amazon Nova: A comprehensive analysis through MT-Bench and Arena-Hard-Auto

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

[ad_1] Large language models (LLMs) have rapidly evolved, becoming integral to applications ranging from conversational AI to complex reasoning tasks.…
On the way to llm to make your own preference: learning to remember users' chats

On the way to llm to make your own preference: learning to remember users' chats

[ad_1] The paper was welcomed at workshop on a large language in model (L2M2) 2025. Large models of language (llms)…
Customize Amazon Nova in Amazon SageMaker AI using Direct Preference Optimization

Customize Amazon Nova in Amazon SageMaker AI using Direct Preference Optimization

[ad_1] At the AWS Summit in New York City, we introduced a comprehensive suite of model customization capabilities for Amazon…
In geometry databases and implementation of Iterative in Model Compression: Operator performance

In geometry databases and implementation of Iterative in Model Compression: Operator performance

[ad_1] The growing parameter prices are increasingly growing deep learning models that require effective attack strategies by sending for the…
Multi-tenant RAG implementation with Amazon Bedrock and Amazon OpenSearch Service for SaaS using JWT

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

[ad_1] In recent years, the emergence of large language models (LLMs) has accelerated AI adoption across various industries. However, to…
Aspera: A recycled nature of the test of the murder of a complex action

Aspera: A recycled nature of the test of the murder of a complex action

[ad_1] This work evaluates the power of the largest Model Modes (LLMS) in the power of digital adversaries cannot be…
Beyond accelerators: Lessons from building foundation models on AWS with Japan’s GENIAC program

Beyond accelerators: Lessons from building foundation models on AWS with Japan’s GENIAC program

[ad_1] In 2024, the Ministry of Economy, Trade and Industry (METI) launched the Generative AI Accelerator Challenge (GENIAC)—a Japanese national…
Streamline deep learning environments with Amazon Q Developer and MCP

Streamline deep learning environments with Amazon Q Developer and MCP

[ad_1] Data science teams working with artificial intelligence and machine learning (AI/ML) face a growing challenge as models become more…
To direct advanced spaces

To direct advanced spaces

[ad_1] Discretion of all languages are desirable in large multilingual models (MLMS), as alignment can improve performance in the Cross-Lingual…
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