We present Amazon Nova Premier, our most capable multimodal foundation model and teacher for model distillation.
In experiments involving real quantum devices and algorithms, automated-reasoning-based method for mapping quantum computations onto quantum circuits is 26 times as fast as predecessors.
A new multimodal foundation model that unifies speech and text processing in a single architecture, delivering frontier voice intelligence and industry-leading price performance.
Novel training procedure and decoding mechanism enable model to outperform much larger foundation model prompted to perform the same task.
Customer-obsessed science
Research areas
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February 27, 2025Prototype is the first realization of a scalable, hardware-efficient quantum computing architecture based on bosonic quantum error correction. -
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The submission period will open March 19 and close May 7.
Inaugural global university competition focused on advancing secure, trusted AI-assisted software development.
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Led by David Luan and Pieter Abbeel, the lab will focus on developing new foundational capabilities for enabling useful AI agents.
The company's new state-of-the-art foundation models deliver frontier intelligence and industry-leading price performance.
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2025The training and fine-tuning of large language models (LLMs) often involve diverse textual data from multiple sources, which poses challenges due to conflicting gradient directions, hindering optimization and specialization. These challenges can undermine model generalization across tasks, resulting in reduced downstream performance. Recent research suggests that fine-tuning LLMs on carefully selected,
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As the demand for online A/B testing continues to rises for tech companies, the opportunity cost of conducting these experiments becomes increasingly significant. Consequently, there is a rising need for an efficient continuous monitoring system capable of early terminating experiments when necessary. Existing literature and tools primarily focuses on early terminating experiments with evidently significant
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2025The instruction hierarchy, which establishes a priority order from system messages to user messages, conversation history, and tool outputs, is essential for ensuring consistent and safe behavior in language models (LMs). Despite its importance, this topic receives limited attention, and there is a lack of comprehensive benchmarks for evaluating models’ ability to follow the instruction hierarchy. We bridge
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Tabular data is one of the most common data formats found in the web and used in domains like finance, banking, e-commerce and medical. Although deep neural networks (DNNs) have demonstrated outstanding performance on homogeneous data such as visual, audio, and textual data, tree ensemble methods such as Gradient Boosted Decision Trees (GBDTs) are often the go-to choice for supervised machine learning problems
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2025Retrieval-Augmented Generation (RAG) systems have shown promise in enhancing the performance of Large Language Models (LLMs). However, these systems face challenges in effectively integrating external knowledge with the LLM’s internal knowledge, often leading to issues with misleading or unhelpful information. This work aims to provide a systematic study on knowledge checking in RAG systems. We conduct
Academia
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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.
