New audio-processing technology is making entertainment more accessible for millions of viewers.
Reasoning models can generate seven to 10 times as many tokens as necessary on simple tasks, creating unsustainable costs at scale. Amazon's vision for metacognitive AI could fundamentally shift how models allocate computational resources.
AGI SVP Rohit Prasad on how to mix your data with Amazon's training data at every stage — deep customization without catastrophic forgetting.
How agentic systems work under the hood — and how AWS’s new AgentCore framework implements their essential components.
Competitive-agent architecture develops security protections at machine speed, reducing weeks of work to hours.
Customer-obsessed science
Research areas
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December 5, 20256 min readA multiagent architecture separates data perception, tool knowledge, execution history, and code generation, enabling ML automation that works with messy, real-world inputs. -
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November 20, 20254 min read
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Featured news
Challenge pushes teams to demonstrate measurable gains in secure-coding performance while building AI agents that advance real-world utility and reliability at scale.
Meet the 63 Amazon Research Award (ARA) recipients, who represent 41 universities in 8 countries.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
David Chang/Getty Images/iStockphoto
Led by David Luan and Pieter Abbeel, the lab will focus on developing new foundational capabilities for enabling useful AI agents.
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NeurIPS 2024 Workshop on Time Series in the Age of Large Models2024Research on neural networks for time series has mostly focused on developing models that learn patterns about the target signal without the use of additional auxiliary or exogenous information. In applications such as selling products on a marketplace, the target signal is influenced by these variables, and leveraging exogenous variables is important. In particular, knowing that a product would go into
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2024We introduce VideoLISA, a video-based multimodal large language model designed to tackle the problem of language-instructed reasoning segmentation in videos. Leveraging the reasoning capabilities and world knowledge of large language models, and augmented by the Segment Anything Model, VideoLISA generates temporally consistent segmentation masks in videos based on language instructions. Existing image-based
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NeurIPS 2024 Workshop on Intrinsically-Motivated and Open-Ended Learning2024Reinforcement Learning (RL) has achieved state-of-the-art performance in station-ary environments with effective simulators. However, lifelong and open-world RL applications, such as robotics, stock trading, and recommendation systems, change over time in adversarial ways. Non-stationary environments pose challenges for RL agents due to constant distribution shifts from the training data, leading to deteriorating
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2024Visual-Language Alignment (VLA) has gained a lot of attention since CLIP’s groundbreaking work. Although CLIP performs well, the typical direct latent feature alignment lacks clarity in its representation and similarity scores. On the other hand, lexical representation, a vector whose element represents the similarity between the sample and a word from the vocabulary, is a natural sparse representation
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Amazon Technical Reports2024
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highly capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks. Amazon Nova Lite is a low-cost multimodal model that is lightning fast for processing images, video, documents and text
Collaborations
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
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Gretchen Ertl
The program offers unrestricted funds and other resources to support research at academic institutions and non-profit organizations in areas that align with our mission.
A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and large language model coding security.
Credit: Wolfram Scheible
We partner with particular academic organizations across the world for deep and sustained collaborations in multiple research areas of mutual interest.
Courtesy of Pai-Ling Yin
We hire world-class academics to work on large-scale technical challenges, while they continue to teach and conduct research at their universities.
