Low-rank adaptation, data augmentation, and chain-of-thought reasoning are among the techniques enabling accent-free polyglot outputs, improved expressiveness, and reliable synthesis.
By learning the idiosyncrasies of accumulated layers of legacy systems, AI agents can preserve institutional knowledge and provide a unified interface to a range of services.
As AI agents become more autonomous, the key challenge isn't what they can do; it's how to design the human side of the equation.
What machine learning theorists learned using AI agents to generate proofs — and what comes next.
Customer-obsessed science
Research areas
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March 20, 202615 min readSimplifying and clarifying the assembly code for core operations enabled automated optimization and verification. -
March 19, 202611 min read -
February 25, 202611 min read
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February 17, 20263 min read
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Featured news
Now open across seven research areas, including Agentic AI and Robotics. Applicants receive unrestricted funds, AWS promotional credits, and training resources. Submission deadline is May 6
Hosted by Danielle Perszyk, cognitive scientist at Amazon's AGI Lab, the podcast features conversations with leading AI researchers about the breakthroughs needed to achieve general intelligence.
Challenge pushes teams to demonstrate measurable gains in secure-coding performance while building AI agents that advance real-world utility and reliability at scale.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
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2024We present VLPG-Nav, a visual language navigation method for guiding robots to specified objects within household scenes. Unlike existing methods primarily focused on navigating the robot toward objects, our approach considers the additional challenge of centering the object within the robot’s camera view. Our method builds a visual language pose graph (VLPG) that functions as a spatial map of VL embeddings
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KDD 2024 Workshop on GenAI Evaluation2024Large language models (LLMs) can be prone to hallucinations —generating unreliable outputs that are unfaithful to their inputs, external facts or internally inconsistent. In this work, we address several challenges for post-hoc hallucination detection in production settings. Our pipeline for hallucination detection entails: first, producing a confidence score representing the likelihood that a generated
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American Journal of Qualitative Research2024Qualitative sampling in the age of Big Data requires tactful negotiation. Although qualitative research aims to explore the depth as opposed to breadth of experiences, opinions, or beliefs of individuals regarding a unique phenomenon, stakeholders or sponsors might not always be convinced that small sample sizes can yield big results. Intimate population awareness, identification of attributes of importance
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Big Data Infrastructure Technologies for Data Analytics2024This chapter discusses SageMaker - a fully managed machine learning (ML) service provided by Amazon Web Services (AWS). Being a fully managed service, means that a user does not have to deal with hardware setup, patching, management, backups etc. All this is taken care of by the service provider. The user can choose from a wide variety of computing instance types that are optimized for different tasks,
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KDD 2024 Workshop on AdKDD2024Today’s top advertisers typically manage hundreds of campaigns simultaneously and consistently launch new ones throughout the year. A crucial challenge for marketing managers is determining the optimal allocation of limited budgets across various ad lines in each campaign to maximize cumulative returns, especially given the huge uncertainty in return outcomes. In this paper, we propose to formulate budget
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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
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