Building sustainable, cost-effective generative AI on AWS requires integrating agentic AI, efficient architecture, and cloud-native optimization. Agentic systems using Amazon Bedrock AgentCore employ contextual memory, asynchronous execution, and on-demand tool invocation to minimize compute waste. MCP enables secure connections between AI agents, AWS services, and custom tools. Efficiency increases through AWS's Trainium and Inferentia2 silicon (50% better performance per watt), Amazon SageMaker for scalable development, and optimization techniques like quantization and speculative decoding. Auto-scaling, batch processing, and spot instances prevent over-provisioning. Combined with CloudWatch and Cost Explorer monitoring, this approach delivers high-performance, low-carbon generative AI solutions.

Learn more: More AWS events: https://go.aws/3kss9CP

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ABOUT AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2025 #AWS

Sustainability regulations require extensive documentation reviews, creating bottlenecks in compliance workflows. RAPID (Review & Assessment Powered by Intelligent Documentation) transforms this process using AI with a human-in-the-loop approach. This solution dramatically accelerates certification and regulatory compliance document reviews - processes traditionally requiring significant expert review hours. RAPID structures complex regulatory checklists, applies AI to identify compliance issues, and maintains human oversight for critical decisions. The solution's serverless architecture enables organizations to start small and scale efficiently, reducing review time while improving assessment quality. Learn how RAPID helps organizations overcome administrative barriers and focus resources on implementing sustainable practices rather than paperwork.

Learn more: More AWS events: https://go.aws/3kss9CP

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ABOUT AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2025 #AWS

Shantanu Narayen shares how Adobe works with AWS to transform digital experiences with innovative AI capabilities for business professionals and consumers, creators and creative professionals, and marketing professionals and IT professionals.

Learn more about AWS events: https://go.aws/events

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ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSEvents

John Kodera explains how Sony continually aims to deliver emotionally resonant experiences by connecting fans with creators and leveraging state-of-the-art technology from AWS that harnesses data and AI.

Learn more about AWS events: https://go.aws/events

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ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSEvents

Tech Talk at YTalks Berlin / Thoughtworks Berlin event.

Unlock AI agent potential with this advanced session on scaling tools using Amazon Bedrock AgentCore Gateway. Learn to build and manage secure, production-ready agent tool environments. We'll cover multi-tenant architecture, deployment strategies, and integration patterns for agentic tools. Explore zero-code MCP tool creation with intelligent tool discovery. Gain insights on security controls, monitoring, and performance optimization for enterprise-scale agent tool ecosystems.

Learn more: More AWS events: https://go.aws/3kss9CP

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ABOUT AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2025 #AWS

In this Supercomputing 25 edition of Data Unchained, host Molly Presley talks with Hunter Hagewood of Vanderbilt University’s ACCRE research computing center about the urgent storage and performance challenges that pushed Vanderbilt to rethink its entire HPC strategy. Hunter explains how procurement delays, faculty chargeback pressures, millions of small medical imaging files, manual GPU data staging, and rapidly growing research datasets created a breaking point that traditional appliance based storage could not solve. He shares how Hammer Space helped eliminate the 20 percent of workloads that were bottlenecking the cluster, enabled modular growth at scale, improved GPU performance for AI driven workflows, and positioned Vanderbilt to save nearly two million dollars over four years while supporting future research expansion. Cyberpunk by jiglr | https://soundcloud.com/jiglrmusic Music promoted by https://www.free-stock-music.com Creative Commons Attribution 3.0 Unported License https://creativecommons.org/licenses/by/3.0/deed.en_US Hosted on Acast. See acast.com/privacy for more information.

Learn how AWS is enhancing its SQL analytics offerings with new capabilities in Amazon Redshift and Amazon Athena. Discover how Redshift's AI-powered data warehousing capabilities are enabling customers to modernize their analytics workloads with enhanced performance and cost optimization. Explore Athena's latest features for interactively querying data directly in their Amazon S3 data lakes. This session showcases new features and real-world examples of how organizations are using these services to accelerate business insights while optimizing costs.

Learn more: More AWS events: https://go.aws/3kss9CP

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

ABOUT AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2025 #AWS

You build a prototype that works perfectly in a demo, but the moment it reaches production, it breaks. This is where most AI projects fail. In this talk, Joanna will explain why this happens, share the best practices for building stable and scalable AI systems, and show how an effective evaluation setup can keep quality consistent.

AI promises to make product teams more productive — faster research synthesis, instant documentation, automated reporting. The efficiency gains are undeniable. But there's a question we're not asking enough: What happens to our craft when we stop doing the hard thinking ourselves? As an early adopter who pushed the boundaries of AI in her day-to-day work, Lisa discovered something surprising: You can ship faster while losing touch with the nuances that make products great. This isn't anti-AI—it's about intentional AI use. Lisa will share insights from neuroscience research and historical patterns that reveal how cognitive shortcuts come with cognitive costs.

Brought to You By: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. •⁠ Linear ⁠ — ⁠ The system for modern product development. — Michelle Lim joined Warp as engineer number one and is now building her own startup, Flint. She brings a strong product-first mindset shaped by her time at Facebook, Slack, Robinhood, and Warp. Michelle shares why she chose Warp over safer offers, how she evaluates early-stage opportunities, and what she believes distinguishes great founding engineers. Together, we cover how product-first engineers create value, why negotiating equity at early-stage startups requires a different approach, and why asking founders for references is a smart move. Michelle also shares lessons from building consumer and infrastructure products, how she thinks about tech stack choices, and how engineers can increase their impact by taking on work outside their job descriptions. If you want to understand what founders look for in early engineers or how to grow into a founding-engineer role, this episode is full of practical advice backed by real examples — Timestamps (00:00) Intro (01:32) How Michelle got into software engineering  (03:30) Michelle’s internships  (06:19) Learnings from Slack  (08:48) Product learnings at Robinhood (12:47) Joining Warp as engineer #1 (22:01) Negotiating equity (26:04) Asking founders for references (27:36) The top reference questions to ask (32:53) The evolution of Warp’s tech stack  (35:38) Product-first engineering vs. code-first (38:27) Hiring product-first engineers  (41:49) Different types of founding engineers  (44:42) How Flint uses AI tools  (45:31) Avoiding getting burned in founder exits (49:26) Hiring top talent (50:15) An overview of Flint (56:08) Advice for aspiring founding engineers (1:01:05) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • Thriving as a founding engineer: lessons from the trenches • From software engineer to AI engineer • AI Engineering in the real world • The AI Engineering stack — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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In this episode, I sit down with Mark Freeman and Chad Sanderson (Gable.ai) to discuss the release of their new O’Reilly book, Data Contracts: Developing Production-Grade Pipelines at Scale. They dive deep into the chaotic journey of writing a 350-page book while simultaneously building a venture-backed startup. The conversation takes a sharp turn into the evolution of Data Contracts. While the concept started with data engineers, Mark and Chad explain why they pivoted their focus to software engineers. They argue that software engineers are facing a "Data Lake Moment, "prioritizing speed over craftsmanship, resulting in massive technical debt and integration failures.

Gable: https://www.gable.ai/

A carreira de AI Engineer se consolidou como uma das mais disputadas do mercado de tecnologia. Mas afinal, o que realmente é esperado desse profissional na prática? Neste episódio do Data Hackers, discutimos em profundidade o caminho para se tornar um AI Engineer, analisando as principais habilidades técnicas, as diferenças em relação a outros cargos da área de dados e engenharia, a formação acadêmica versus experiência prática, a rotina nas empresas e o impacto da IA Generativa, RAG e AI Agents no dia a dia da função. Para enriquecer o debate, utilizamos dados da pesquisa State of Data Brazil como base para entender o cenário atual do mercado brasileiro, identificar tendências de demanda por habilidades, perfis profissionais mais buscados e os principais desafios enfrentados por quem deseja ingressar ou evoluir nessa carreira. Se você quer migrar para IA, se preparar para oportunidades reais ou entender se esse é o próximo passo profissional em dados, este episódio é para você. Não se esqueça de preencher a pesquisa State of Data Brazil: https://www.stateofdata.com.br/

Nossa Bancada Data Hackers: Paulo Vasconcellos — Co-founder da Data Hackers e Principal Data Scientist na Hotmart.Gabriel Lages — Co-founder da Data Hacker e Diretor de Dados & AI da Hotmart

Send us a text Hit replay on this high-energy conversation with Ben Lowe, Founder and CEO of Lighthouse Technology, as he breaks down what it really takes to build something from scratch in a fast-changing AI world. From finding the right co‑founder and stepping into the CEO role, to navigating the toughest challenges of entrepreneurship, Ben shares practical lessons and hard‑won insights for builders at every stage. Ben also lifts the curtain on Lighthouse Technology’s mission at the intersection of cloud modernisation, cost optimisation, and Agentic AI, and how enterprises can turn AI hype into outcomes with the right GTM motion and architecture. If you care about innovation, AI for the enterprise, or your own startup journey, this replay is packed with career gold, strategic perspective, and a candid look at what’s next. 01:34 Finding a Entrepreneurial Partner 04:43 The Creation of Lighthouse 08:10 Becoming the CEO 09:34 The Biggest Challenge of Entrepreneurship 11:30 Lighthouse Technology 19:07 Agentic AI 20:16 The Lighthouse Trajectory 22:12 The GTM 31:39 Reseller versus Innovator 36:53 AI for the Enterprise 41:35 The 2-Min Pitch 43:30 What's True?LinkedIn: https://www.linkedin.com/in/lowebenjamin/?originalSubdomain=uk Website: https://lighthousetechnology.ai/

Entrepreneurship #AgenticAI #TechLeadership #Innovation #BusinessGrowth #CareerAdvice #AIForEnterprise #StartupJourney #MakingDataSimple #LighthouseTechnology #PodcastReplay

Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Training large AI models requires significant compute resources and can be time and cost intensive. In this session, learn to optimize and accelerate your model training workloads using AWS's purpose-built infrastructure and tools. We'll dive deep into leveraging services like Amazon SageMaker HyperPod for distributed training at scale and SageMaker fully managed training jobs for cost-effective ML acceleration. You'll learn to scale training across clusters using techniques like data and model parallelism, automated model tuning, and efficient checkpoint management. Through real customer examples, see how to reduce training time by up to 40%, optimize costs, and build high-performance training pipelines.

Learn more: More AWS events: https://go.aws/3kss9CP

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ABOUT AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2025 #AWS

Learn how Amazon SageMaker AI transforms model development with a unified environment for all your AI workloads - from interactive model development on IDEs to maximizing task and compute resource utilization across training and inference workloads. We'll demonstrate how to use SageMaker Studio as the familiar IDE to develop, submit, and monitor ML jobs, while leveraging the scalability and resiliency of HyperPod environment for computationally intensive tasks like training and deploying large foundation models. You will also learn how HyperPod task governance capability can help you automatically allocate compute resources based on task prioritization end-to-end through the model development lifecycle.

Learn more: More AWS events: https://go.aws/3kss9CP

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

ABOUT AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2025 #AWS

Build robust security frameworks for AI implementations through hands-on coding. We'll implement data protection patterns, secure prompt handling, and PII detection. Code along as we create privacy-preserving pipelines in SageMaker, configure IAM policies for model access control, and automate compliance checks with AWS Config. Develop defenses against prompt injection attacks, implement differential privacy techniques, and build CloudTrail audit trails. Leave with production-ready code templates for governance guardrails and technical safeguards that protect sensitive data throughout the AI lifecycle while enabling innovation and maintaining trust in your AI applications.

Learn more: More AWS events: https://go.aws/3kss9CP

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

ABOUT AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2025 #AWS

Mini Masterclass on accelerating with AI by Ashard Nizar and Shubham Pai (AI Engineers at Pathfindr).

Unstructured data often holds untapped value, and Amazon SageMaker makes it possible to turn that data into insights and AI-ready assets. In this session, you'll learn how to bring unstructured data from Amazon S3 into SageMaker, create searchable assets, and build knowledge bases for Amazon Bedrock to improve retrieval-augmented generation (RAG) accuracy. Discover how teams can collaborate across roles, data users can self-serve to find and understand the right data, and governance ensures that the right people get the right access. Bayer will share how they use these capabilities to unlock unstructured data and accelerate research and innovation.

Learn more: More AWS events: https://go.aws/3kss9CP

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

ABOUT AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2025 #AWS

How does a one-millimetre worm help win four Nobel Prizes? In this episode, we explore how C. elegans became one of the most influential organisms in modern biology — not because of its size, but because of its community.

Researchers, beginning with Sydney Brenner’s vision, built an ecosystem of radical openness: shared strains, shared annotations, shared tools, shared knowledge. This culture powered breakthroughs in apoptosis, GFP, RNA interference, and microRNAs, each recognised with a Nobel Prize.

We discuss how the CGC, WormBase, WormAtlas, open imaging libraries, and collaborative genetics transformed a tiny worm into a global scientific powerhouse. It’s the story of a field that chose to share — and in doing so, changed biology.

Key themes: • The collaborative backbone behind worm research • Why sharing strains and data accelerated Nobel-winning discoveries • How open tools shaped genetics, neuroscience, and ageing research • The social and scientific architecture of a uniquely supportive community • Why C. elegans is still leading modern multi-omics and connectomics

Based on the research article:🎧 Subscribe to the WOrM Podcast “From nematode to Nobel: How community-shared resources fueled the rise of Caenorhabditis elegans as a research organism” Victor R. Ambros, Martin Chalfie, Aric L. Daul, Andrew Z. Fire, David H. Hall, H. Robert Horvitz, Craig C. Mello, Gary Ruvkun, Nathan E. Schroeder, Paul W. Sternberg & Ann E. Rougvie. PNAS (2025) 🔗 https://doi.org/10.1073/pnas.2522808122

🎧 Subscribe to the WOrM Podcast Whole-organism stories from molecules to behaviour.

This podcast is generated with artificial intelligence and curated by Veeren. If you’d like your publication featured on the show, please get in touch.

📩 More info: 🔗 ⁠⁠www.veerenchauhan.com⁠⁠ 📧 [email protected]