For centuries, members of the B’doul Bedouin tribe lived in the caves around the ancient city of Petra, Jordan. Then, in the 1980s, the government forced the tribe to move in the name of preserving the geological site for tourists. But if the residents are forced to leave, and if their heritage has been permanently changed, then what exactly is being preserved? SHOW NOTES: Meet The Man Living in The Lost City Carved in Stone Jordan: Petra's tourism authority cracks down on Bedouin cave dwellers The tribes paying the brutal price of conservation “There is no future for Umm Sayhoun” Jordan’s Young Bedouins Are Documenting Their Traditions on TikTok Check out Sami's company Jordan Inspiration Tours Learn about your ad choices: dovetail.prx.org/ad-choices…
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Streaming Ecosystem Complexities and Cost Management // Rohit Agrawal // #302
Manage episode 475231637 series 3241972
محتوای ارائه شده توسط Demetrios. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Demetrios یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
Streaming Ecosystem Complexities and Cost Management // MLOps Podcast #302 with Rohit Agrawal, Director of Engineering at Tecton.
Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter
// Abstract
Demetrios talks with Rohit Agrawal, Director of Engineering at Tecton, about the challenges and future of streaming data in ML. Rohit shares his path at Tecton and insights on managing real-time and batch systems. They cover tool fragmentation (Kafka, Flink, etc.), infrastructure costs, managed services, and trends like using S3 for storage and Iceberg as the GitHub for data. The episode wraps with thoughts on BYOC solutions and evolving data architectures.
// Bio
Rohit Agrawal is an Engineering Manager at Tecton, leading the Real-Time Execution team. Before Tecton, Rohit was the a Lead Software Engineer at Salesforce, where he focused on transaction processign and storage in OLTP relational databases. He holds a Master’s Degree in Computer Systems from Carnegie Mellon University and a Bachelor’s Degree in Electrical Engineering from the Biria Institute of Technology and Science in Pilani, India.
// Related Links
~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Rohit on LinkedIn: /agrawalrohit10
425 قسمت
اشتراک گذاریManage episode 475231637 series 3241972
محتوای ارائه شده توسط Demetrios. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Demetrios یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
Streaming Ecosystem Complexities and Cost Management // MLOps Podcast #302 with Rohit Agrawal, Director of Engineering at Tecton.
Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter
// Abstract
Demetrios talks with Rohit Agrawal, Director of Engineering at Tecton, about the challenges and future of streaming data in ML. Rohit shares his path at Tecton and insights on managing real-time and batch systems. They cover tool fragmentation (Kafka, Flink, etc.), infrastructure costs, managed services, and trends like using S3 for storage and Iceberg as the GitHub for data. The episode wraps with thoughts on BYOC solutions and evolving data architectures.
// Bio
Rohit Agrawal is an Engineering Manager at Tecton, leading the Real-Time Execution team. Before Tecton, Rohit was the a Lead Software Engineer at Salesforce, where he focused on transaction processign and storage in OLTP relational databases. He holds a Master’s Degree in Computer Systems from Carnegie Mellon University and a Bachelor’s Degree in Electrical Engineering from the Biria Institute of Technology and Science in Pilani, India.
// Related Links
~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Rohit on LinkedIn: /agrawalrohit10
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Real-Time Forecasting Faceoff: Time Series vs. DNNs // MLOps Podcast #305 with Josh Xi, Data Scientist at Lyft. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractIn real-time forecasting (e.g. geohash level demand and supply forecast for an entire region), time series-based forecasting methods are widely adopted due to their simplicity and ease of training. This discussion explores how Lyft uses time series forecasting to respond to real-time market dynamics, covering practical tips and tricks for implementing these methods, an in-depth look at their adaptability for online re-training, and discussions on their interpretability and user intervention capabilities. By examining these topics, listeners will understand how time series forecasting can outperform DNNs, and how to effectively use time series forecasting for dynamic market conditions and decision-making applications. // BioJosh is a data scientist from the Marketplace team at Lyft, working on forecasting and modeling of marketplace signals that power products like pricing and driver incentives. Josh got his PHD in Operations Research in 2013, with minors in Statistics and Economics. Prior to joining Lyft, he worked as a research scientist in the Operations Research Lab at General Motors, focusing on optimization, simulation and forecasting modeling related to vehicle manufacturing, supply chain and car sharing systems. // Related LinksWebsite: https://www.lyft.com/ ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Josh on LinkedIn: /joshxiaominxi…
1 We're All Finetuning Incorrectly // Tanmay Chopra // #304 1:00:30
1:00:30 
پخش در آینده 
پخش در آینده 
لیست ها 
پسندیدن 
دوست داشته شد1:00:30
پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شدWe're All Finetuning Incorrectly // MLOps Podcast #304 with Tanmay Chopra, Founder & CEO of Emissary. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract Finetuning is dead. Finetuning is only for style. We've all heard these claims. But the truth is we feel this way because all we've been doing is extended pretraining. I'm excited to chat about what real finetuning looks like - modifying output heads, loss functions and model layers, and it's implications on quality and latency. Happy to dive deeper into how DeepSeek leveraged this real version of finetuning through GRPO and how this is nothing more than a rediscovery of our old finetuning ways. I'm sure we'll naturally also dive into when developing and deploying your specialized models makes sense and the challenges you face when doing so. // Bio Tanmay is a machine learning engineer at Neeva, where he's currently engaged in reimagining the search experience through AI - wrangling with LLMs and building cold-start recommendation systems. Previously, Tanmay worked on TikTok's Global Trust&Safety Algorithms team - spearheading the development of AI technologies to counter violent extremism and graphic violence on the platform across 160+ countries.Tanmay has a bachelor's and master's in Computer Science from Columbia University, with a specialization in machine learning. Tanmay is deeply passionate about communicating science and technology to those outside its realm. He's previously written about LLMs for TechCrunch, held workshops across India on the art of science communication for high school and college students, and is the author of Black Holes, Big Bang and a Load of Salt - a labor of love that elucidated the oft-overlooked contributions of Indian scientists to modern science and helped everyday people understand some of the most complex scientific developments of the past century without breaking into a sweat! // Related Links ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Tanmay on LinkedIn: /tanmayc98…
From Shiny to Strategic: The Maturation of AI Across Industries // MLOps Podcast #303 with David Cox, VP of Data Science; Assistant Director of Research at RethinkFirst; Institute of Applied Behavioral Science. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract Shiny new objects are made available to artificial intelligence(AI) practitioners daily. For many who are not AI practitioners, the release of ChatGPT in 2022 was their first contact with modern AI technology. This led to a flurry of funding and excitement around how AI might improve their bottom line. Two years on, the novelty of AI has worn off for many companies but remains a strategic initiative. This strategic nuance has led to two patterns that suggest a maturation of the AI conversation across industries. First, conversations seem to be pivoting from "Are we doing [the shiny new thing]" to serious analysis of the ROI from things built. This reframe places less emphasis on simply adopting new technologies for the sake of doing so and more emphasis on the optimal stack to maximize return relative to cost. Second, conversations are shifting to emphasize market differentiation. That is, anyone can build products that wrap around LLMs. In competitive markets, creating products and functionality that all your competitors can also build is a poor business strategy (unless having a particular thing is industry standard). Creating a competitive advantage requires companies to think strategically about their unique data assets and what they can build that their competitors cannot. // Bio Dr. David Cox can formally lay claim to being a bioethicist (master's degree), a board-certified behavior analyst at the doctoral level, a behavioral economist (post-doc training), and a full-stack data scientist (post-doc training). He has worked in behavioral health for nearly 20 years as a clinician, academic researcher, scholar, technologist, and all-around behavior science junky. He currently works as the Assistant Director of Research for the Institute of Applied Behavioral Science at Endicott College and the VP of Data Science at RethinkFirst. David also likes to write, having published 60+ peer-reviewed articles, book chapters, and a few books. When he's not doing research or building tools at the intersection of artificial intelligence and behavioral health, he enjoys spending time with his wife and two beagles in and around Jacksonville, FL. // Related Links ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with David on LinkedIn: /coxdavidj…
Streaming Ecosystem Complexities and Cost Management // MLOps Podcast #302 with Rohit Agrawal, Director of Engineering at Tecton. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract Demetrios talks with Rohit Agrawal, Director of Engineering at Tecton, about the challenges and future of streaming data in ML. Rohit shares his path at Tecton and insights on managing real-time and batch systems. They cover tool fragmentation (Kafka, Flink, etc.), infrastructure costs, managed services, and trends like using S3 for storage and Iceberg as the GitHub for data. The episode wraps with thoughts on BYOC solutions and evolving data architectures. // Bio Rohit Agrawal is an Engineering Manager at Tecton, leading the Real-Time Execution team. Before Tecton, Rohit was the a Lead Software Engineer at Salesforce, where he focused on transaction processign and storage in OLTP relational databases. He holds a Master’s Degree in Computer Systems from Carnegie Mellon University and a Bachelor’s Degree in Electrical Engineering from the Biria Institute of Technology and Science in Pilani, India. // Related Links ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Rohit on LinkedIn: /agrawalrohit10…
Building Trust Through Technology: Responsible AI in Practice // MLOps Podcast #301 with Rafael Sandroni, Founder and CEO of GardionAI. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractRafael Sandroni shares key insights on securing AI systems, tackling fraud, and implementing robust guardrails. From prompt injection attacks to AI-driven fraud detection, we explore the challenges and best practices for building safer AI. // BioEntrepreneur and problem solver. // Related LinksGardionAI LinkedIn: https://www.linkedin.com/company/guardionai/ ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Rafael on LinkedIn: /rafaelsandroni Timestamps:[00:00] Rafael's preferred coffee[00:16] Takeaways[01:03] AI Assistant Best Practices[03:48] Siri vs In-App AI[08:44] AI Security Exploration[11:55] Zero Trust for LLMS[18:02] Indirect Prompt Injection Risks[22:42] WhatsApp Banking Risks[26:27] Traditional vs New Age Fraud[29:12] AI Fraud Mitigation Patterns[32:50] Agent Access Control Risks[34:31] Red Teaming and Pentesting[39:40] Data Security Paradox[40:48] Wrap up…
Beyond the Matrix: AI and the Future of Human Creativity // MLOps Podcast #300 with Fausto Albers, AI Engineer & Community Lead at AI Builders Club. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract Fausto Albers discusses the intersection of AI and human creativity. He explores AI’s role in job interviews, personalized AI assistants, and the evolving nature of human-computer interaction. Key topics include AI-driven self-analysis, context-aware AI systems, and the impact of AI on optimizing human decision-making. The conversation highlights how AI can enhance creativity, collaboration, and efficiency by reducing cognitive load and making intelligent suggestions in real time. // Bio Fausto Albers is a relentless explorer of the unconventional—a techno-optimist with a foundation in sociology and behavioral economics, always connecting seemingly absurd ideas that, upon closer inspection, turn out to be the missing pieces of a bigger puzzle. He thrives in paradox: he overcomplicates the simple, oversimplifies the complex, and yet somehow lands on solutions that feel inevitable in hindsight. He believes that true innovation exists in the tension between chaos and structure—too much of either, and you’re stuck.His career has been anything but linear. He’s owned and operated successful restaurants, served high-stakes cocktails while juggling bottles on London’s bar tops, and later traded spirits for code—designing digital waiters, recommender systems, and AI-driven accounting tools. Now, he leads the AI Builders Club Amsterdam, a fast-growing community where AI engineers, researchers, and founders push the boundaries of intelligent systems.Ask him about RAG, and he’ll insist on specificity—because, as he puts it, discussing retrieval-augmented generation without clear definitions is as useful as declaring that “AI will have an impact on the world.” An engaging communicator, a sharp systems thinker, and a builder of both technology and communities, Fausto is here to challenge perspectives, deconstruct assumptions, and remix the future of AI. // Related Links Website: aibuilders.club ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~ Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Fausto on LinkedIn: /stepintoliquid…
Building Trust Through Technology: Responsible AI in Practice // MLOps Podcast #299 with Animesh Singh, Executive Director, AI Platform and Infrastructure of LinkedIn. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractAnimesh discusses LLMs at scale, GPU infrastructure, and optimization strategies. He highlights LinkedIn's use of LLMs for features like profile summarization and hiring assistants, the rising cost of GPUs, and the trade-offs in model deployment. Animesh also touches on real-time training, inference efficiency, and balancing infrastructure costs with AI advancements. The conversation explores the evolving AI landscape, compliance challenges, and simplifying architecture to enhance scalability and talent acquisition. // BioExecutive Director, AI and ML Platform at LinkedIn | Ex IBM Senior Director and Distinguished Engineer, Watson AI and Data | Founder at Kubeflow | Ex LFAI Trusted AI NA Chair Animesh is the Executive Director leading the next-generation AI and ML Platform at LinkedIn, enabling the creation of the AI Foundation Models Platform, serving the needs of 930+ Million members of LinkedIn. Building Distributed Training Platforms, Machine Learning Pipelines, Feature Pipelines, Metadata engines, etc. Leading the creation of the LinkedIn GAI platform for fine-tuning, experimentation and inference needs. Animesh has more than 20 patents and 50+ publications. Past IBM Watson AI and Data Open Tech CTO, Senior Director, and Distinguished Engineer, with 20+ years experience in the Software industry, and 15+ years in AI, Data, and Cloud Platform. Led globally dispersed teams, managed globally distributed projects, and served as a trusted adviser to Fortune 500 firms. Played a leadership role in creating, designing, and implementing Data and AI engines for AI and ML platforms, led Trusted AI efforts, and drove the strategy and execution for Kubeflow, OpenDataHub, and execution in products like Watson OpenScale and Watson Machine Learning. // Related LinksComposable Memory for GPU Optimization // Bernie Wu // Pod #270 - https://youtu.be/ccaDEFoKwko ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Animesh on LinkedIn: /animeshsingh1 Timestamps:[00:00] Animesh's preferred coffee[00:16] Takeaways[02:12] What is working? [07:00] What's not working?[13:40] LLM vs Rexis Efficiency[21:49] GPU Utilization and Architecture[27:32] GPU reliability concerns[36:50] Memory Bottleneck in AI[41:06] Optimizing LLM Checkpointing[46:51] Checkpoint Offloading and Platform Design[54:55] Workflow Divergence Points[58:41] Wrap up…
Building Trust Through Technology: Responsible AI in Practice // MLOps Podcast #298 with Allegra Guinan, Co-founder of Lumiera. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractAllegra joins the podcast to discuss how Responsible AI (RAI) extends beyond traditional pillars like transparency and privacy. While these foundational elements are crucial, true RAI success requires deeply embedding responsible practices into organizational culture and decision-making processes. Drawing from Lumiera's comprehensive approach, Allegra shares how organizations can move from checkbox compliance to genuine RAI integration that drives innovation and sustainable AI adoption. // BioAllegra is a technical leader with a background in managing data and enterprise engineering portfolios. Having built her career bridging technical teams and business stakeholders, she's seen the ins and outs of how decisions are made across organizations. She combines her understanding of data value chains, passion for responsible technology, and practical experience guiding teams through complex implementations into her role as co-founder and CTO of Lumiera. // Related LinksWebsite: https://www.lumiera.ai/Weekly newsletter: https://lumiera.beehiiv.com/ ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Allegra on LinkedIn: /allegraguinan Timestamps:[00:00] Allegra's preferred coffee[00:14] Takeaways[01:11] Responsible AI principles[03:13] Shades of Transparency[07:56] Effective questioning for clarity [11:17] Managing stakeholder input effectively[14:06] Business to Tech Translation[19:30] Responsible AI challenges[23:59] Successful plan vs Retroactive responsibility[28:38] AI product robustness explained [30:44] AI transparency vs Engagement[34:10] Efficient interaction preferences[37:57] Preserving human essence[39:51] Conflict and growth in life[46:02] Subscribe to Allegra's Weekly Newsletter!…
I Let An AI Play Pokémon! - Claude plays Pokémon Creator // MLOps Podcast #295 with David Hershey, Member of Technical Staff at Anthropic. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractDemetrios chats with David Hershey from Anthropic's Applied AI team about his agent-powered Pokémon project using Claude. They explore agent frameworks, prompt optimization vs. fine-tuning, and AI's growing role in software, legal, and accounting fields. David highlights how managed AI platforms simplify deployment, making advanced AI more accessible. // BioDavid Hershey devoted most of his career to machine learning infrastructure and trying to abstract away the hairy systems complexity that gets in the way of people building amazing ML applications. // Related LinksWebsite: https://www.davidhershey.com/ ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with David on LinkedIn: /david-hershey-458ab081…
1 From Rules to Reasoning Engines // George Mathew // #296 1:05:26
1:05:26 پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شد1:05:26
پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شدFrom Rules to Reasoning Engines // MLOps Podcast #297 with George Mathew, Managing Director at Insight Partners. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractGeorge Mathew (Insight Partners) joins Demetrios to break down how AI and ML have evolved over the past few years and where they’re headed. He reflects on the major shifts since his last chat with Demetrios, especially how models like ChatGPT have changed the game. George dives into "generational outcomes"—building companies with lasting impact—and the move from rule-based software to AI-driven reasoning engines. He sees AI becoming a core part of all software, fundamentally changing business operations. The chat covers the rise of agent-based systems, the importance of high-quality data, and recent breakthroughs like Deep SEQ, which push AI reasoning further. They also explore AI’s future—its role in software, enterprise adoption, and everyday life. // BioGeorge Mathew is a Managing Director at Insight Partners focused on venture stage investments in AI, ML, Analytics, and Data companies as they are establishing product/market fit. He brings 20+ years of experience developing high-growth technology startups including most recently being CEO of Kespry. Prior to Kespry, George was President & COO of Alteryx where he scaled the company through its IPO (AYX). Previously he held senior leadership positions at SAP and salesforce.com. He has driven company strategy, led product management and development, and built sales and marketing teams. George holds a Bachelor of Science in Neurobiology from Cornell University and a Masters in Business Administration from Duke University, where he was a Fuqua Scholar. // Related LinksWebsite: https://www.insightpartners.com/ ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with George on LinkedIn: /gmathew…
1 GenAI Traffic: Why API Infrastructure Must Evolve... Again // Erica Hughberg // #296 1:06:24
1:06:24 پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شد1:06:24
پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شدGenAI Traffic: Why API Infrastructure Must Evolve... Again // MLOps Podcast #295 with Erica Hughberg, Community Advocate at Tetrate.Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter
The Unbearable Lightness of Data // MLOps Podcast #295 with Rohit Krishnan, Chief Product Officer at bodo.ai.Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractRohit Krishnan, Chief Product Officer at Bodo.AI, joins Demetrios to discuss AI's evolving landscape. They explore interactive reasoning models, AI's impact on jobs, scalability challenges, and the path to AGI. Rohit also shares insights on Bodo.AI’s open-source move and its impact on data science.// BioBuilding products, writing, messing around with AI pretty much everywhere// Related LinksWebsite: www.strangeloopcanon.comIn life, my kids. Professionally, https://github.com/bodo-ai/Bodo ... Otherwise personally, it's writing every single day at strangeloopcanon.com! ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Rohit on LinkedIn: /rkris…
Kubernetes, AI Gateways, and the Future of MLOps // MLOps Podcast #294 with Alexa Griffith, Senior Software Engineer at Bloomberg. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract Alexa shares her journey into software engineering, from early struggles with Airflow and Kubernetes to leading open-source projects like the Envoy AI Gateway. She and Demetrios discuss AI model deployment, tooling differences across tech roles, and the importance of abstraction. They highlight aligning technical work with business goals and improving cross-team communication, offering key insights into MLOps and AI infrastructure. // Bio Alexa Griffith is a Senior Software Engineer at Bloomberg, where she builds scalable inference platforms for machine learning workflows and contributes to open-source projects like KServe. She began her career at Bluecore working in data science infrastructure, and holds an honors degree in Chemistry from the University of Tennessee, Knoxville. She shares her insights through her podcast, Alexa’s Input (AI), technical blogs, and active engagement with the tech community at conferences and meetups. // Related LinksWebsite: https://alexagriffith.com/ Kubecon Keynote about Envoy AI Gateway https://www.youtube.com/watch?v=do1viOk8nok ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~ Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore Join our slack community [ https://go.mlops.community/slack ] Follow us on X/Twitter [ @mlopscommunity ][ https://x.com/mlopscommunity ] or LinkedIn [ https://go.mlops.community/linkedin ] Sign up for the next meetup: [ https://go.mlops.community/register ] MLOps Swag/Merch: [ https://shop.mlops.community/ ] Connect with Demetrios on LinkedIn: /dpbrinkm Connect with Alexa on LinkedIn: /alexa-griffith…
1 Future of Software, Agents in the Enterprise, and Inception Stage Company Building // Eliot Durbin // #293 54:26
Future of Software, Agents in the Enterprise, and Inception Stage Company Building // MLOps Podcast 293 with Eliot Durbin, General Partner at Boldstart Ventures.Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractKey lessons for founders that are thinking about or starting their companies. 15 years of inception stage investing from how data science companies like Yhat went to market in 2013-14 and how that's evolved, to building companies around OSS frameworks like CrewAI; Eliot share's key learnings and questions for founders starting out. // BioEliot is a General Partner @ boldstart ventures since it's founding in 2010. boldstart an inception stage lead investor for technical founders building the next generation of enterprise companies such as Clay, Snyk, BigID, Kustomer, Superhuman, and CrewAI. // Related LinksWebsite: boldstart.vc https://medium.com/@etdurbin ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore Join our slack community [https://go.mlops.community/slack] Follow us on X/Twitter [ @mlopscommunity ]( https://x.com/mlopscommunity ) or LinkedIn ( https://go.mlops.community/linkedin ) Sign up for the next meetup: [ https://go.mlops.community/register ] MLOps Swag/Merch: [ https://shop.mlops.community/ ] Connect with Demetrios on LinkedIn: /dpbrinkm Connect with Eliot on LinkedIn: /eliotdurbin…
Agents in Production [Podcast Limited Series] - Episode Five, Dmitri Jarnikov, Chiara Caratelli, and Steven Vester join Demetrios to explore AI agents in e-commerce. They discuss the trade-offs between generic and specialized agents, with Dmitri noting the need for a balance between scalability and precision. Chiara highlights how agents can dynamically blend both approaches, while Steven predicts specialized agents will dominate initially before trust in generic agents grows. The panel also examines how e-commerce platforms may resist but eventually collaborate with AI agents. Trust remains a key factor in adoption, with opportunities emerging for new agent-driven business models. Guest speakers: Dmitri Jarnikov - Senior Director of Data Science at Prosus Chiara Caratelli - Data Scientist at Prosus Group Steven Vester - Head of Product at OLX Host:Demetrios Brinkmann - Founder of MLOps Community ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~ Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore Join our slack community [https://go.mlops.community/slack] Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register] MLOps Swag/Merch: [https://shop.mlops.community/] Connect with Demetrios on LinkedIn: /dpbrinkm…
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