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Updated 2025-12-28T23:11:02+00:00

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Product · 4d ago

Intelligent Document Processing (IDP) transforms how organizations handle…

Programmatically creating an IDP solution with Amazon Bedrock Data Automation

Intelligent Document Processing (IDP) transforms how organizations handle unstructured document data, enabling automatic extraction of valuable information from invoices, contracts, and reports.

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Intelligent Document Processing (IDP) transforms how organizations handle unstructured document data, enabling automatic extraction of valuable information from invoices,…

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  1. 4d ago Product

    Intelligent Document Processing (IDP) transforms how organizations handle unstructured…

    Programmatically creating an IDP solution with Amazon Bedrock Data Automation

    Intelligent Document Processing (IDP) transforms how organizations handle unstructured document data, enabling automatic extraction of valuable information from invoices, contracts, and reports.
  2. 4d ago Product

    Enterprise organizations increasingly rely on web-based applications for critical…

    AI agent-driven browser automation for enterprise workflow management

    Enterprise organizations increasingly rely on web-based applications for critical business processes, yet many workflows remain manually intensive, creating operational inefficiencies and…
  3. 4d ago Product

    Quality assurance (QA) testing has long been the backbone of software development, but…

    Agentic QA automation using Amazon Bedrock AgentCore Browser and Amazon Nova Act

    Quality assurance (QA) testing has long been the backbone of software development, but traditional QA approaches haven’t kept pace with modern development cycles and complex UIs.
  4. 4d ago Product

    The rise of powerful large language models (LLMs) that can be consumed via API calls has…

    Optimizing LLM inference on Amazon SageMaker AI with BentoML’s LLM- Optimizer

    The rise of powerful large language models (LLMs) that can be consumed via API calls has made it remarkably straightforward to integrate artificial intelligence (AI) capabilities into applications.
  5. 5d ago Product

    At Amazon, our culture, built on honest and transparent discussion of our growth…

    Exploring the zero operator access design of Mantle

    At Amazon, our culture, built on honest and transparent discussion of our growth opportunities, enables us to focus on investing and innovating to continually raise the standard on our ability to…
  6. 5d ago Product

    Building intelligent agents to handle complex, real-world tasks can be daunting

    AWS AI League: Model customization and agentic showdown

    Building intelligent agents to handle complex, real-world tasks can be daunting.
  7. 5d ago Product

    This post is co-written by Thomas Capelle and Ray Strickland from Weights & Biases (W&B)

    Accelerate Enterprise AI Development using Weights & Biases and Amazon Bedrock AgentCore

    This post is co-written by Thomas Capelle and Ray Strickland from Weights & Biases (W&B).
  8. 5d ago Product

    dLocal , Uruguay’s first unicorn, has established itself as a pioneer in cross-border…

    How dLocal automated compliance reviews using Amazon Quick Automate

    dLocal , Uruguay’s first unicorn, has established itself as a pioneer in cross-border payments since its founding in 2016.
  9. 5d ago Product

    This post is cowritten with Dr

    Advancing ADHD diagnosis: How Qbtech built a mobile AI assessment Model Using Amazon SageMaker AI

    This post is cowritten with Dr.
  10. 5d ago Product

    Marketing teams face increasing pressure to create engaging campaigns quickly while…

    Accelerating your marketing ideation with generative AI – Part 1: From idea to generation with the Amazon Nova foundation models

    Marketing teams face increasing pressure to create engaging campaigns quickly while maintaining brand consistency and creative quality.
  11. 5d ago Paper 2 sources

    Research breakthroughs of the year

    Google's year in review: 8 areas with research breakthroughs in 2025

    Google 2025 recap: Research breakthroughs of the year
  12. 5d ago Product

    This post is cowritten with Sangeetha Bharath and Seemal Zaman from Visa

    Introducing Visa Intelligent Commerce on AWS: Enabling agentic commerce with Amazon Bedrock AgentCore

    This post is cowritten with Sangeetha Bharath and Seemal Zaman from Visa.
  13. 5d ago Product

    AprielGuard: A Guardrail for Safety and Adversarial Robustness in Modern LLM Systems

    AprielGuard: A Guardrail for Safety and Adversarial Robustness in Modern LLM Systems

    Hugging Face Blog: AprielGuard: A Guardrail for Safety and Adversarial Robustness in Modern LLM Systems
  14. 6d ago Product

    As organizations scale their generative AI implementations, the critical challenge of…

    Move Beyond Chain-of-Thought with Chain-of-Draft on Amazon Bedrock

    As organizations scale their generative AI implementations, the critical challenge of balancing quality, cost, and latency becomes increasingly complex.
  15. 6d ago Product

    Mistral AI’s Voxtral models combine text and audio processing capabilities in a single…

    Deploy Mistral AI’s Voxtral on Amazon SageMaker AI

    Mistral AI’s Voxtral models combine text and audio processing capabilities in a single framework.
  16. 6d ago Product

    Extracting structured information from unstructured data is a critical first step to…

    Enhance document analytics with Strands AI Agents for the GenAI IDP Accelerator

    Extracting structured information from unstructured data is a critical first step to unlocking business value.
  17. 6d ago Product

    Predictive maintenance is a strategy that uses data from equipment sensors and advanced…

    Build a multimodal generative AI assistant for root cause diagnosis in predictive maintenance using Amazon Bedrock

    Predictive maintenance is a strategy that uses data from equipment sensors and advanced analytics to predict when a machine is likely to fail, ensuring maintenance can be performed proactively to…
  18. 6d ago Paper

    Look back on Google AI news in 2025 across Gemini, Search, Pixel and more products

    60 of our biggest AI announcements in 2025

    Look back on Google AI news in 2025 across Gemini, Search, Pixel and more products.
  19. 6d ago Product

    More than one million customers around the world now use OpenAI to empower their teams and…

    One in a million: celebrating the customers shaping AI’s future

    More than one million customers around the world now use OpenAI to empower their teams and unlock new opportunities.
  20. 6d ago Product

    OpenAI is strengthening ChatGPT Atlas against prompt injection attacks using automated…

    Continuously hardening ChatGPT Atlas against prompt injection

    OpenAI is strengthening ChatGPT Atlas against prompt injection attacks using automated red teaming trained with reinforcement learning.
  21. Dec 19 Product

    Today, we are excited to introduce a new feature for SageMaker Studio : SOCI (Seekable Open…

    Introducing SOCI indexing for Amazon SageMaker Studio: Faster container startup times for AI/ML workloads

    Today, we are excited to introduce a new feature for SageMaker Studio : SOCI (Seekable Open Container Initiative) indexing.
  22. Dec 19 Paper

    Learn more about the AI tips and tools Google shared in 2025

    40 of our most helpful AI tips from 2025

    Learn more about the AI tips and tools Google shared in 2025.
  23. Dec 19 Paper

    Today, Google Cloud dropped its 2026 AI Agent Trends Report

    5 ways AI agents will transform the way we work in 2026

    Today, Google Cloud dropped its 2026 AI Agent Trends Report.
  24. Dec 18 Product

    This post is co-written with Ranjit Rajan, Abdullahi Olaoye, and Abhishek Sawarkar from…

    Build and deploy scalable AI agents with NVIDIA NeMo, Amazon Bedrock AgentCore, and Strands Agents

    This post is co-written with Ranjit Rajan, Abdullahi Olaoye, and Abhishek Sawarkar from NVIDIA.
Research papers (35)
  1. 4d ago Paper

    Masked Diffusion Models (MDMs) offer flexible, non-autoregressive generation, but this…

    Optimizing Decoding Paths in Masked Diffusion Models by Quantifying Uncertainty

    Masked Diffusion Models (MDMs) offer flexible, non-autoregressive generation, but this freedom introduces a challenge: final output quality is highly sensitive to the decoding order.
  2. 4d ago Paper

    Computational point-of-care (POC) sensors enable rapid, low-cost, and accessible…

    Autonomous Uncertainty Quantification for Computational Point-of-care Sensors

    Computational point-of-care (POC) sensors enable rapid, low-cost, and accessible diagnostics in emergency, remote and resource-limited areas that lack access to centralized medical facilities.
  3. 4d ago Paper

    We present C2LLM - Contrastive Code Large Language Models, a family of code embedding…

    C2LLM Technical Report: A New Frontier in Code Retrieval via Adaptive Cross-Attention Pooling

    We present C2LLM - Contrastive Code Large Language Models, a family of code embedding models in both 0.5B and 7B sizes.
  4. 4d ago Paper

    Separating signal from noise is central to experimental science

    Measuring all the noises of LLM Evals

    Separating signal from noise is central to experimental science.
  5. 4d ago Paper

    We propose Parallel Token Prediction (PTP), a universal framework for parallel sequence…

    Parallel Token Prediction for Language Models

    We propose Parallel Token Prediction (PTP), a universal framework for parallel sequence generation in language models.
  6. 4d ago Paper

    Minimizing PDE-residual losses is a common strategy to promote physical consistency in…

    Variationally correct operator learning: Reduced basis neural operator with a posteriori error estimation

    Minimizing PDE-residual losses is a common strategy to promote physical consistency in neural operators.
  7. 4d ago Paper

    This paper derives `Scaling Laws for Economic Impacts' -- empirical relationships between…

    Scaling Laws for Economic Productivity: Experimental Evidence in LLM-Assisted Consulting, Data Analyst, and Management Tasks

    This paper derives `Scaling Laws for Economic Impacts' -- empirical relationships between the training compute of Large Language Models (LLMs) and professional productivity.
  8. 4d ago Paper

    The data processing inequality is an information-theoretic principle stating that the…

    Does the Data Processing Inequality Reflect Practice? On the Utility of Low-Level Tasks

    The data processing inequality is an information-theoretic principle stating that the information content of a signal cannot be increased by processing the observations.
  9. 4d ago Paper

    Solving partial differential equations (PDEs) on shapes underpins many shape analysis and…

    Learning to Solve PDEs on Neural Shape Representations

    Solving partial differential equations (PDEs) on shapes underpins many shape analysis and engineering tasks; yet, prevailing PDE solvers operate on polygonal/triangle meshes while modern 3D assets…
  10. 4d ago Paper

    Acute Myeloid Leukemia (AML) remains a clinical challenge due to its extreme molecular…

    Transcriptome-Conditioned Personalized De Novo Drug Generation for AML Using Metaheuristic Assembly and Target-Driven Filtering

    Acute Myeloid Leukemia (AML) remains a clinical challenge due to its extreme molecular heterogeneity and high relapse rates.
  11. 4d ago Paper

    Model merging has emerged as a lightweight alternative to joint multi-task learning…

    Model Merging via Multi-Teacher Knowledge Distillation

    Model merging has emerged as a lightweight alternative to joint multi-task learning (MTL), yet the generalization properties of merged models remain largely unexplored.
  12. 4d ago Paper

    The user of Engineering Manuals (EM) finds it difficult to read EM s because they are…

    SMART SLM: Structured Memory and Reasoning Transformer, A Small Language Model for Accurate Document Assistance

    The user of Engineering Manuals (EM) finds it difficult to read EM s because they are long, have a dense format which includes written documents, step by step procedures, and standard parameter…
  13. 4d ago Paper

    The increasing integration of AI tools in education has led prior research to explore…

    Learning Factors in AI-Augmented Education: A Comparative Study of Middle and High School Students

    The increasing integration of AI tools in education has led prior research to explore their impact on learning processes.
  14. 4d ago Paper

    Methods that use Large Language Models (LLM) as planners for embodied instruction…

    LookPlanGraph: Embodied Instruction Following Method with VLM Graph Augmentation

    Methods that use Large Language Models (LLM) as planners for embodied instruction following tasks have become widespread.
  15. 4d ago Paper

    In hard-label black-box adversarial attacks, where only the top-1 predicted label is…

    Improving the Convergence Rate of Ray Search Optimization for Query-Efficient Hard-Label Attacks

    In hard-label black-box adversarial attacks, where only the top-1 predicted label is accessible, the prohibitive query complexity poses a major obstacle to practical deployment.
  16. 4d ago Paper

    Large language models (LLMs) are increasingly used in software development, but their…

    Assessing the Software Security Comprehension of Large Language Models

    Large language models (LLMs) are increasingly used in software development, but their level of software security expertise remains unclear.
  17. 4d ago Paper

    Large language models (LLMs) have revolutionized software development through AI-assisted…

    Casting a SPELL: Sentence Pairing Exploration for LLM Limitation-breaking

    Large language models (LLMs) have revolutionized software development through AI-assisted coding tools, enabling developers with limited programming expertise to create sophisticated applications.
  18. 4d ago Paper

    Large Language Models can develop reasoning capabilities through online fine-tuning with…

    MiST: Understanding the Role of Mid-Stage Scientific Training in Developing Chemical Reasoning Models

    Large Language Models can develop reasoning capabilities through online fine-tuning with rule-based rewards.
  19. 4d ago Paper

    In this work, we introduce PhononBench, the first large-scale benchmark for dynamical…

    PhononBench:A Large-Scale Phonon-Based Benchmark for Dynamical Stability in Crystal Generation

    In this work, we introduce PhononBench, the first large-scale benchmark for dynamical stability in AI-generated crystals.
  20. 4d ago Paper

    Retrieving images from natural language descriptions is a core task at the intersection…

    Leveraging Lightweight Entity Extraction for Scalable Event-Based Image Retrieval

    Retrieving images from natural language descriptions is a core task at the intersection of computer vision and natural language processing, with wide-ranging applications in search engines, media…
  21. 4d ago Paper

    Embodied agents powered by vision-language models (VLMs) are increasingly capable of…

    RoboSafe: Safeguarding Embodied Agents via Executable Safety Logic

    Embodied agents powered by vision-language models (VLMs) are increasingly capable of executing complex real-world tasks, yet they remain vulnerable to hazardous instructions that may trigger unsafe…
  22. 4d ago Paper

    Attribution modelling lies at the heart of marketing effectiveness, yet most existing…

    Causal-driven attribution (CDA): Estimating channel influence without user-level data

    Attribution modelling lies at the heart of marketing effectiveness, yet most existing approaches depend on user-level path data, which are increasingly inaccessible due to privacy regulations and…
  23. 4d ago Paper

    Human infants, with only a few hundred hours of speech exposure, acquire basic units of new…

    SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation

    Human infants, with only a few hundred hours of speech exposure, acquire basic units of new languages, highlighting a striking efficiency gap compared to the data-hungry self-supervised speech models.
  24. 4d ago Paper

    Zero-shot object navigation (ZSON) requires a robot to locate a target object in a…

    Schrödinger's Navigator: Imagining an Ensemble of Futures for Zero-Shot Object Navigation

    Zero-shot object navigation (ZSON) requires a robot to locate a target object in a previously unseen environment without relying on pre-built maps or task-specific training.
  25. 4d ago Paper

    This technical note considers the sampling of outcomes that provide the greatest amount…

    Active inference and artificial reasoning

    This technical note considers the sampling of outcomes that provide the greatest amount of information about the structure of underlying world models.
  26. 4d ago Paper

    We consider the problem of ranking $n$ experts according to their abilities, based on the…

    Statistical and computational challenges in ranking

    We consider the problem of ranking $n$ experts according to their abilities, based on the correctness of their answers to $d$ questions.
  27. 4d ago Paper

    The empirical success of deep learning is often attributed to scaling laws that predict…

    Understanding Scaling Laws in Deep Neural Networks via Feature Learning Dynamics

    The empirical success of deep learning is often attributed to scaling laws that predict consistent gains as model, data, and compute grow; however, large models can exhibit training instability and…
  28. 4d ago Paper

    Diffusion models are a class of generative models that have demonstrated remarkable…

    Enhancing diffusion models with Gaussianization preprocessing

    Diffusion models are a class of generative models that have demonstrated remarkable success in tasks such as image generation.
  29. 4d ago Paper

    Modeling sparse count data, which arise across numerous scientific fields, presents…

    Learning from Neighbors with PHIBP: Predicting Infectious Disease Dynamics in Data-Sparse Environments

    Modeling sparse count data, which arise across numerous scientific fields, presents significant statistical challenges.
  30. 4d ago Paper

    A methodology is developed to extract $d$ invariant features $W=f(X)$ that predict a…

    Invariant Feature Extraction Through Conditional Independence and the Optimal Transport Barycenter Problem: the Gaussian case

    A methodology is developed to extract $d$ invariant features $W=f(X)$ that predict a response variable $Y$ without being confounded by variables $Z$ that may influence both $X$ and $Y$.
  31. 5d ago Paper

    Several performance measures are used to evaluate binary and multiclass classification tasks

    Weighted MCC: A Robust Measure of Multiclass Classifier Performance for Observations with Individual Weights

    Several performance measures are used to evaluate binary and multiclass classification tasks.
  32. 5d ago Paper

    We study the problem of subgroup discovery for survival analysis, where the goal is to find…

    Subgroup Discovery with the Cox Model

    We study the problem of subgroup discovery for survival analysis, where the goal is to find an interpretable subset of the data on which a Cox model is highly accurate.
  33. 5d ago Paper

    We present GeoTransolver, a Multiscale Geometry-Aware Physics Attention Transformer for…

    GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer

    We present GeoTransolver, a Multiscale Geometry-Aware Physics Attention Transformer for CAE that replaces standard attention with GALE, coupling physics-aware self-attention on learned state slices…
  34. Dec 19 Paper

    Plant diseases pose a significant threat to global food security, necessitating accurate…

    Interpretable Plant Leaf Disease Detection Using Attention-Enhanced CNN

    Plant diseases pose a significant threat to global food security, necessitating accurate and interpretable disease detection methods.
  35. Dec 18 Paper

    Dialogue topic segmentation supports summarization, retrieval, memory management, and…

    When F1 Fails: Granularity-Aware Evaluation for Dialogue Topic Segmentation

    Dialogue topic segmentation supports summarization, retrieval, memory management, and conversational continuity.