Join us for a fascinating deep dive with Ali Benfettoum, AWS Principal Product Manager and Physical AI expert, as we explore the revolutionary world of agentic twins and the foundations of physical AI.

Ali brings over 15 years of expertise in IoT, Applied AI, and Digital Twins, including his groundbreaking work as creator of the open-source Garnet Framework.

Discover how AI is evolving beyond digital realms into physical applications, transforming everything from smart cities to industrial systems. Learn about the intersection of IoT and AI, the power of knowledge graphs in creating context-aware solutions, and how digital twins are enabling intelligent, responsive environments across major cities and global enterprises.

Get insider insights on semantic data modeling, context management strategies, and the practical implementation of living digital twins. Ali shares his unique perspective bridging mathematics, physics, and cutting-edge AI technology, offering a comprehensive view of where Physical AI is heading and how it's reshaping our interaction with the physical world.

Don't miss this technical exploration where we uncover real-world applications of agentic systems and the infrastructure powering the next generation of intelligent physical environments.

Garnet Framework: https://garnet-framework.tech/

Learn more: https://aws.amazon.com/iot/

Chapters:

0:00:00 : Episode Introduction

0:02:37 : Ali's Journey to Physical AI and IoT

0:05:35 : From smart territory framework to physical AI

0:08:00 : The Garnet Framework : From data silos to insights

0:12:02 : Building with the garnet framework

0:14:58 : AI Agents as Data Consumers

0:18:02 : Knowledge graphs for true context aware AI

0:22:12 : NGSI-LD specification

0:24:20 : Sustainable AI foundations for the future

0:26:57 : Physical AI : perceive reason act in real world

0:29:35 : Use Cases with the most impact

0:32:48 : Maximizing ROI of using physical AI.

0:39:09 : Next generation of automated industry

0:40:08 : Panama Success Stories

0:42:30 : City of Madrid Success Story

0:43:43 : From digital twins to agentic twins

0:47:06 : Training world models , nvidia omniverse

0:50:47 : Build today for tomorrow’s innovations on AWS

0:55:15 : Future Trends in Agentic Systems

0:58:46 : Final Thoughts

1:00:02 : Closing Remarks

Join us for an enlightening conversation with Anton Alexander, AWS's Senior Specialist for Worldwide Foundation Models, as we delve into the complexities of training and scaling large foundation models. Anton brings his unique expertise from working with the world's top model builders, along with his fascinating journey from Trinidad and Tobago to becoming a leading AI infrastructure expert.

Discover practical insights on managing massive GPU clusters, optimizing distributed training, and handling the critical challenges of model development at scale. Learn about cutting-edge solutions in GPU failure detection, checkpointing strategies, and the evolution of inference workloads. Get an insider's perspective on emerging trends like GRPO, visual LLMs, and the future of AI model development.

Don't miss this technical deep dive where we explore real-world solutions for building and deploying foundational AI models, featuring discussions on everything from low-level infrastructure optimization to high-level AI development strategies.

Learn more: http://go.aws/47yubYq

Amazon SageMaker HyperPod : https://aws.amazon.com/fr/sagemaker/ai/hyperpod/

The Llama 3 Herd of Models paper : https://arxiv.org/abs/2407.21783

Chapters:

00:00:00 : Introduction and Guest Background

00:01:18 : Anton Journey from Caribbean to AI

00:05:52 : Mathematics in AI

00:07:20 : Large Model Training Challenges

00:09:54 : GPU failures : Lama Herd of models

00:13:40 : Grey failures

00:15:05 : Model training trends

00:17:40 : Managing Mixture of Experts Models

00:21:50 : Estimate how many GPUs you need.

00:25:12 : Monitoring loss function

00:27:08 : Crashing trainings

00:28:10 : SageMaker Hyperpod story

00:32:15 : How we automate managing grey failures

00:37:28 : which metrics to optimize for

00:40:23 : Checkpointing Strategies

00:44:48 : USE Utilization, Saturation, Errors

00:50:11 : SageMaker Hyperpod for Inferencing

00:54:58 : Resiliency in Training vs Inferencing workloads

00:56:44 : NVIDIA NeMo Ecosystem and Agents

00:59:49 : Future Trends in AI

01:03:17 : Closing Thoughts

Join us as we sit down with AWS Solutions Architect Mirabela Dan for a journey into the world of generative AI for developers. Whether you're a seasoned developer or just getting started, this episode is your gateway to staying ahead in the AI revolution.

Discover: the game-changing shift from "vibe coding" to spec-driven development and learn about the latest AWS AI tools that can supercharge your productivity. Get real-world insights on how AI is reshaping the developer landscape and plan essential strategies to future-proof your development career

Don't miss this power-packed episode where we demystify the intersection of AI and modern development practices. Get ready to transform the way you build with AWS's innovative AI solutions!

Learn more: https://aws.amazon.com/ai/ and https://kiro.dev/

Connect with Mirabela: https://www.linkedin.com/in/carmenmirabeladan/

Chapters

0:00:00 : Introduction and Guest Background

0:02:48 : Mirabela's Journey at AWS

0:05:38 : Working with Different Customer Types

0:08:52 : Shift from Infrastructure to AI

0:09:35 : Evolution of Developer Role with AI

0:15:49 : Challenges in Developing with AI

0:20:06 : AI for Code Generation vs Maintenance

0:28:33 : Spec-Driven Development Approach

0:39:30 : Balancing Planning vs Rapid Delivery

0:42:23 : Kiro - AWS AI-Powered IDE

0:44:46 : MCP Integration

0:46:10 : Agent Steering and Hooks

0:54:43 : Code Transformation with AI

0:55:57 : Future of Developer Role

0:59:55 : Consuming AI/Tech Updates

1:00:17 : Personal Learning Methods

1:01:30 : Optimism for Future of Development

1:02:34 : Closing Remarks

In this episode of AWS for AI, we sit down with Akshat Prakash, CTO and co-founder of Camb.ai, to explore how this Dubai-based startup is revolutionizing content localization through AI. From making sports accessible in 140+ languages to preserving indigenous cultures with fewer than 600 speakers, discover how they're breaking down global language barriers.

Witness history as we discuss how Camb.ai partnered with NASCAR to become the first company to livestream a race with real-time AI dubbing. Deep dive into their groundbreaking technical solutions - from preserving context, sarcasm, and emotion in speech, to their innovative approach of separating voice identity from speech prosody, solving critical ethical challenges in voice AI.

Get exclusive insights into their MARS and BOLI models, their partnership with AWS, and learn why deep problem understanding trumps technical expertise in building successful AI solutions. Whether you're a technologist, content creator, or business leader, this episode offers valuable insights into the future of global communication.

Learn more about CAMB.AI: https://www.camb.ai/

Chapters

0:00:00 : Dubbed Introduction

00:00:17 : Episode Introduction

00:02:14 : From Siri to Camb.ai: Akshat's AI Journey

00:03:52 : Breaking Language Barriers: The Camb.ai Family Story

00:05:47 : Beyond Translation: Understanding Cultural Context

00:07:00 : The Story Behind the Name 'CAMB'

00:08:01 : The Mamba Mentality

00:10:19 : Dubai to the World: Exporting AI Innovation

00:12:43 : Making History: First Multi-Language Live Race Stream

00:14:30 : A "Man on the Moon" Moment in AI

00:15:15 : Camb.ai Technology Suite and Offerings

00:19:56 : Creating Value Across All Layers

00:22:36 : Solving Last Mile Problems in AI Localization

00:23:59 : Focus on Results: Getting the Job Done

00:24:38 : Tackling the Hardest Challenge First: Live Sports

00:28:00 : MARS Architecture: Balancing Prosody, Speed, and Performance.

00:31:01 : Understanding Auto-Regression Tradeoffs

00:31:58 : Speaker Entanglement: Core Voice Identity Challenges

00:33:42 : Ethics in Voice Identity Usage

00:35:12 : Building with Resource Constraints

00:36:48 : The Case for Small Language Models

00:42:21 : Speech-to-Speech vs. Cascading Architecture Approach

00:46:30 : Preserving Context in Cascading Architecture

00:49:29 : BOLI: Enhanced Context Through Multi-modality

00:50:59 : Inclusive AI: Supporting All Languages

00:53:12 : Managing Dialects vs Languages

00:53:49 : MBC Partnership: Advancing Arabic Understanding

00:54:56 : From Sports to Rap: Diverse Use Cases

00:59:53 : A CTO's AWS Journey

01:02:38 : Accelerating Innovation with SageMaker Hyperpod

01:03:58 : The Future of AI: Final Thoughts

01:07:24 : Closing Remarks

Explore the cutting-edge world of causal AI with Professor Kun Zhang in this enlightening episode of the AWS for AI podcast. As a leading researcher from MBZUAI and Carnegie Mellon University, Professor Zhang delves into the fundamentals of causal discovery and inference, revealing how these techniques are reshaping the landscape of artificial intelligence.

From education to finance, healthcare to climate science, discover how causal AI is revolutionizing diverse fields by answering the crucial "why" and "what if" questions that traditional machine learning often overlooks.

Professor Zhang shares his vision for a future where AI not only provides convenience and safety but also promotes human intelligence and societal harmony. He offers valuable insights on the ethical considerations of AI development and the role of cloud computing in facilitating large-scale AI research collaborations.

Whether you're an AI enthusiast, a researcher, or simply curious about the future of technology, this episode provides a fascinating glimpse into the transformative potential of causal AI. Join us for an in-depth discussion that bridges the gap between correlation and causation, paving the way for more interpretable, robust, and ethical AI systems.

Professor Kun Zhang : https://mbzuai.ac.ae/study/faculty/ku...

MBZUAI : https://mbzuai.ac.ae/

In this insightful episode, we're joined by Eduardo Ordax, Principal Specialist for Generative AI Go-to-Market at AWS and recognized as Spain's #1 most influential person in AI, and #14 worldwide.

Eduardo shares his deep expertise on the latest trends in generative AI, including the evolution of AI agents, the rise of small language models, and AWS's approach to responsible AI innovation. He offers valuable insights into AWS Nova models, the infrastructure powering enterprise AI, and practical perspectives on building AI solutions at scale.

Whether you're a developer, business leader, or AI enthusiast, this episode provides actionable insights into the current state and future direction of enterprise AI adoption. Eduardo's unique blend of technical knowledge and practical experience offers listeners a comprehensive view of how organizations can successfully implement AI while navigating key challenges around data foundations, model selection, and responsible deployment.

Learn More :

Eduardo’s Linkedin Profile: http://go.aws/4ldsLX6

Nova Models: http://go.aws/4n42nk4

Amazon Bedrock Agents: http://go.aws/3FY13P3

Amazon SageMaker HyperPod : http://go.aws/4kL0SWB

In this episode of AWS for AI, we explore the cutting-edge world of emotional AI with Moayad Rayan, Partner and Head of Technology at Virtue.

Discover how Virtue is bridging the gap between humans and machines through their innovative approach to understanding and responding to human emotions. Learn about their proprietary emotional data analysis system, real-world applications in safety and city planning, and how they're using AWS to scale their solution. From reducing human errors by 75% to creating more empathetic AI interactions, this episode reveals the future of human-centered artificial intelligence.

To learn more about Virtue : virtuedeep.tech

Ownverse : ownexperiences.com

Learn more at - https://aws.amazon.com/ai/