Author: Ricardo

Agentic AI AI Agents

Google DeepMind Releases GenAI Processors: A Lightweight Python Library that Enables Efficient and Parallel Content Processing
ByRicardo July 13, 2025

Google DeepMind recently released GenAI Processors, a lightweight, open-source Python library built to simplify the orchestration of generative AI workflows—especially those involving real-time multimodal content. Launched last week, and available under an Apache‑2.0 license, this library provides a high-throughput, asynchronous stream framework for building advanced AI pipelines. Stream‑Oriented Architecture At the heart of GenAI Processors…

Read More Google DeepMind Releases GenAI Processors: A Lightweight Python Library that Enables Efficient and Parallel Content Processing
Artificial Intelligence Editors Pick

Meta AI Introduces UMA (Universal Models for Atoms): A Family of Universal Models for Atoms
ByRicardo July 13, 2025

Density Functional Theory (DFT) serves as the foundation of modern computational chemistry and materials science. However, its high computational cost severely limits its usage. Machine Learning Interatomic Potentials (MLIPs) have the potential to closely approximate DFT accuracy while significantly improving performance, reducing computation time from hours to less than a second with O(n) versus O(n³)…

Read More Meta AI Introduces UMA (Universal Models for Atoms): A Family of Universal Models for Atoms
Agentic AI Artificial Intelligence

Moonshot AI Releases Kimi K2: A Trillion-Parameter MoE Model Focused on Long Context, Code, Reasoning, and Agentic Behavior
ByRicardo July 12, 2025

Kimi K2, launched by Moonshot AI in July 2025, is a purpose-built, open-source Mixture-of-Experts (MoE) model—1 trillion total parameters, with 32 billion active parameters per token. It’s trained using the custom MuonClip optimizer on 15.5 trillion tokens, achieving stable training at this unprecedented scale without the typical instabilities seen in ultra-large models. Unlike traditional chatbots, K2 is architected…

Read More Moonshot AI Releases Kimi K2: A Trillion-Parameter MoE Model Focused on Long Context, Code, Reasoning, and Agentic Behavior
Artificial Intelligence Editors Pick

From Perception to Action: The Role of World Models in Embodied AI Systems
ByRicardo July 11, 2025

Introduction to Embodied AI Agents Embodied AI agents are systems that exist in physical or virtual forms, such as robots, wearables, or avatars, and can interact with their surroundings. Unlike static web-based bots, these agents perceive the world and act meaningfully within it. Their embodiment enhances physical interaction, human trust, and human-like learning. Recent advances…

Read More From Perception to Action: The Role of World Models in Embodied AI Systems
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

Author: Ricardo

Google DeepMind Releases GenAI Processors: A Lightweight Python Library that Enables Efficient and Parallel Content Processing

Meta AI Introduces UMA (Universal Models for Atoms): A Family of Universal Models for Atoms

Moonshot AI Releases Kimi K2: A Trillion-Parameter MoE Model Focused on Long Context, Code, Reasoning, and Agentic Behavior

From Perception to Action: The Role of World Models in Embodied AI Systems

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

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