Constructive Circuit Amplification: Improving Math Reasoning in LLMs via Targeted Sub-Network Updates

by AI Generated Robotic ContentFAANGPosted on Comments are Disabled

Prior studies investigating the internal workings of LLMs have uncovered sparse subnetworks, often referred to as circuits, that are responsible for performing specific tasks. Additionally, it has been shown that model performance improvement through fine-tuning often results from the strengthening of existing circuits in the model. Taken together, these findings suggest the possibility of intervening …

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Efficiently serve dozens of fine-tuned models with vLLM on Amazon SageMaker AI and Amazon Bedrock

by AI Generated Robotic ContentFAANGPosted on Comments are Disabled

Organizations and individuals running multiple custom AI models, especially recent Mixture of Experts (MoE) model families, can face the challenge of paying for idle GPU capacity when the individual models don’t receive enough traffic to saturate a dedicated compute endpoint. To solve this problem, we have partnered with the vLLM community and developed an efficient …

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A developer’s guide to production-ready AI agents

by AI Generated Robotic ContentFAANGPosted on Comments are Disabled

Something has shifted in the developer community over the past year. AI agents have moved from “interesting research concept” to “thing my team is actually building.” The prototypes are working. The demos are impressive. And now comes the harder question: How do we ship this? That question turns out to be a multi-part one. Agents …

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How AI could help make society less selfish

by AI Generated Robotic ContentAI/ML NewsPosted on Comments are Disabled

The Care Bears taught a generation of kids that sharing is caring, but not everyone has carried this principle into adulthood. Researchers at Michigan State University have found a new angle to promote cooperation: artificial intelligence (AI). The results of this study, titled “Promoting cooperation in the public goods game using artificial intelligent agents,” are …

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Closing the Gap Between Text and Speech Understanding in LLMs

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Large Language Models (LLMs) can be adapted to extend their text capabilities to speech inputs. However, these speech-adapted LLMs consistently underperform their text-based counterparts—and even cascaded pipelines—on language understanding tasks. We term this shortfall the text-speech understanding gap: the performance drop observed when a speech-adapted LLM processes spoken inputs relative to when the original text-based …

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Build an intelligent photo search using Amazon Rekognition, Amazon Neptune, and Amazon Bedrock

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Managing large photo collections presents significant challenges for organizations and individuals. Traditional approaches rely on manual tagging, basic metadata, and folder-based organization, which can become impractical when dealing with thousands of images containing multiple people and complex relationships. Intelligent photo search systems address these challenges by combining computer vision, graph databases, and natural language processing …

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