Join us for a fascinating deep dive with Ali Benfattoum, 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 in-depth conversation with Dr. Zuhair Khayat, CTO and co-founder of Lucidya, a groundbreaking AI company revolutionizing customer experience in the Middle East. From his journey through academia at KAUST to pioneering Arabic language AI solutions, Dr. Khayat shares invaluable insights on building technology for Arabic markets. Discover how Lucidya is tackling unique challenges in Arabic language processing, managing customer experience across dialects, and leveraging AI for brand management in the MENA region. Learn how Lucidya is transforming social listening and customer intelligence through advanced AI. From sophisticated sentiment analysis to real-time brand monitoring across multiple dialects, discover the future of customer experience management. Learn more: http://go.aws/47yubYq Lucidya Website: http://go.aws/4846zeH Dr. Khayat's Research: https://scholar.google.com/citations?... Chapters: 00:00 - Introduction 02:27 - Lucidya's Origin Story 05:20 - AI startup vision before GenAI 07:30 - From Saudi Arabia to the world. 08:11 - Lucidya’s Long Term Mission 08:59 - What is Customer Experience ? 10:55 - Lucidya’s Value Proposition 12:18 - Use Cases : Brand Managment 17:20 - Use Cases : Customer Support 19:14 - Use Cases : Market Research 20:43 - Use Cases : Marketing Optimization 21:52 - Building Products in GenAI Era 25:58 - Keeping up with the AI innovations 26:45 - Product bundles from Research to Support 28:50 - Evolution of Challenges for Building AI Models 30:18 - ASAD - Arabic Sentiment Analysis Data 31:22 - Navigating Ambiguity in Human Communications 33:40 - Managing Biases in Data with agents 38:02 - Arabic Dialects Support 40:41 - Split Learning, Collaborative Training on Private Data on the Cloud. 47:10 - Opportunities for Split Learning in Regulated Industries 49:35 - U shape Learning as a Collaborative Framework for Privacy 50:12 - a CTO’s advise for AI startups 53:20 - Choosing the right architecture on AWS for your team 55:45 - The Future of AI. 58:06 - 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 

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