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Artificial Intelligence Computer Vision

This AI Paper Introduces PEVA: A Whole-Body Conditioned Diffusion Model for Predicting Egocentric Video from Human Motion
ByRicardo July 11, 2025

Understanding the Link Between Body Movement and Visual Perception The study of human visual perception through egocentric views is crucial in developing intelligent systems capable of understanding & interacting with their environment. This area emphasizes how movements of the human body—ranging from locomotion to arm manipulation—shape what is seen from a first-person perspective. Understanding this…

Read More This AI Paper Introduces PEVA: A Whole-Body Conditioned Diffusion Model for Predicting Egocentric Video from Human Motion
Amazon SageMaker AI Artificial Intelligence

Advanced fine-tuning methods on Amazon SageMaker AI
ByRicardo July 11, 2025

This post provides the theoretical foundation and practical insights needed to navigate the complexities of LLM development on Amazon SageMaker AI, helping organizations make optimal choices for their specific use cases, resource constraints, and business objectives. We also address the three fundamental aspects of LLM development: the core lifecycle stages, the spectrum of fine-tuning methodologies,…

Read More Advanced fine-tuning methods on Amazon SageMaker AI
Amazon SageMaker HyperPod Announcements

Streamline machine learning workflows with SkyPilot on Amazon SageMaker HyperPod
ByRicardo July 11, 2025

This post is co-written with Zhanghao Wu, co-creator of SkyPilot. The rapid advancement of generative AI and foundation models (FMs) has significantly increased computational resource requirements for machine learning (ML) workloads. Modern ML pipelines require efficient systems for distributing workloads across accelerated compute resources, while making sure developer productivity remains high. Organizations need infrastructure solutions…

Read More Streamline machine learning workflows with SkyPilot on Amazon SageMaker HyperPod
Amazon Bedrock Amazon Bedrock Data Automation

Intelligent document processing at scale with generative AI and Amazon Bedrock Data Automation
ByRicardo July 11, 2025

Extracting information from unstructured documents at scale is a recurring business task. Common use cases include creating product feature tables from descriptions, extracting metadata from documents, and analyzing legal contracts, customer reviews, news articles, and more. A classic approach to extracting information from text is named entity recognition (NER). NER identifies entities from predefined categories,…

Read More Intelligent document processing at scale with generative AI and Amazon Bedrock Data Automation
Amazon Bedrock Amazon Bedrock Agents

Build a conversational data assistant, Part 2 – Embedding generative business intelligence with Amazon Q in QuickSight
ByRicardo July 11, 2025

In Part 1 of this series, we explored how Amazon’s Worldwide Returns & ReCommerce (WWRR) organization built the Returns & ReCommerce Data Assist (RRDA)—a generative AI solution that transforms natural language questions into validated SQL queries using Amazon Bedrock Agents. Although this capability improves data access for technical users, the WWRR organization’s journey toward truly…

Read More Build a conversational data assistant, Part 2 – Embedding generative business intelligence with Amazon Q in QuickSight
Advanced (300) Amazon Bedrock

Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents
ByRicardo July 11, 2025

What if you could replace hours of data analysis with a minute-long conversation? Large language models can transform how we bridge the gap between business questions and actionable data insights. For most organizations, this gap remains stubbornly wide, with business teams trapped in endless cycles—decoding metric definitions and hunting for the correct data sources to…

Read More Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents
Advanced (300) Amazon SageMaker

Implement user-level access control for multi-tenant ML platforms on Amazon SageMaker AI
ByRicardo July 11, 2025

Managing access control in enterprise machine learning (ML) environments presents significant challenges, particularly when multiple teams share Amazon SageMaker AI resources within a single Amazon Web Services (AWS) account. Although Amazon SageMaker Studio provides user-level execution roles, this approach becomes unwieldy as organizations scale and team sizes grow. Refer to the Operating model whitepaper for…

Read More Implement user-level access control for multi-tenant ML platforms on Amazon SageMaker AI
Amazon Bedrock Amazon Bedrock Prompt Flows

Long-running execution flows now supported in Amazon Bedrock Flows in public preview
ByRicardo July 11, 2025

Today, we announce the public preview of long-running execution (asynchronous) flow support within Amazon Bedrock Flows. With Amazon Bedrock Flows, you can link foundation models (FMs), Amazon Bedrock Prompt Management, Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, Amazon Bedrock Guardrails, and other AWS services together to build and scale predefined generative AI workflows. As customers…

Read More Long-running execution flows now supported in Amazon Bedrock Flows in public preview
Amazon SageMaker Amazon SageMaker AI

Fraud detection empowered by federated learning with the Flower framework on Amazon SageMaker AI
ByRicardo July 11, 2025

Fraud detection remains a significant challenge in the financial industry, requiring advanced machine learning (ML) techniques to detect fraudulent patterns while maintaining compliance with strict privacy regulations. Traditional ML models often rely on centralized data aggregation, which raises concerns about data security and regulatory constraints. Fraud cost businesses over $485.6 billion in 2023 alone, according…

Read More Fraud detection empowered by federated learning with the Flower framework on Amazon SageMaker AI
Amazon Bedrock Amazon Nova

Building intelligent AI voice agents with Pipecat and Amazon Bedrock – Part 2
ByRicardo July 11, 2025

Voice AI is changing the way we use technology, allowing for more natural and intuitive conversations. Meanwhile, advanced AI agents can now understand complex questions and act autonomously on our behalf. In Part 1 of this series, you learned how you can use the combination of Amazon Bedrock and Pipecat, an open source framework for…

Read More Building intelligent AI voice agents with Pipecat and Amazon Bedrock – Part 2

Posts

This AI Paper Introduces PEVA: A Whole-Body Conditioned Diffusion Model for Predicting Egocentric Video from Human Motion

Advanced fine-tuning methods on Amazon SageMaker AI

Streamline machine learning workflows with SkyPilot on Amazon SageMaker HyperPod

Intelligent document processing at scale with generative AI and Amazon Bedrock Data Automation

Build a conversational data assistant, Part 2 – Embedding generative business intelligence with Amazon Q in QuickSight

Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents

Implement user-level access control for multi-tenant ML platforms on Amazon SageMaker AI

Long-running execution flows now supported in Amazon Bedrock Flows in public preview

Fraud detection empowered by federated learning with the Flower framework on Amazon SageMaker AI

Building intelligent AI voice agents with Pipecat and Amazon Bedrock – Part 2

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