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Engineering MLOps // Emmanuel Raj // MLOps Meetup #69
Manage episode 313294438 series 3241972
Content provided by Demetrios. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Demetrios or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
MLOps community meetup #69! Last Wednesday we talked to Emmanuel Raj, Senior Machine Learning Engineer at TietoEvry.
//Abstract
The talk focuses on simplifying/demystifying MLOps, encourages others to take steps to learn this powerful SE method. We also talked about Emmanuel's journey in ML engineering, the evolution of MLOps, daily life, and SE problems, and what's next in MLOps (fusion of AIOps, EU AI regulations impact on MLOps workflow, etc).
//Bio
Emmanuel Raj is a Finland-based Senior Machine Learning Engineer. He is a passionate ML Researcher, Software engineer, speaker, and author. He is also a Machine Learning Engineer at TietoEvry and a Researcher at Arcada University of Applied Sciences in Finland. With over 6+ years of experience building ML solutions in the industry, he has worked on multiple domains such as Healthcare, Manufacturing, Finance, Retail, e-commerce, aviation, etc.
Emmanuel is passionate about democratizing AI and bringing state-of-the-art research to the industry. He has a keen interest in R&D in technologies such as Edge AI, Blockchain, NLP, MLOps, and Robotics. He believes the best way to learn is to teach and he is passionate about teaching about new technologies, that's one reason for writing a book and making an online course on MLOps.
Emmanuel is the author of the book "Engineering MLOps". The book covers industry best case practices and hands-on implementation to Rapidly build, test, and manage production-ready machine learning life cycles at scale. There is a big evolution happening in Data science for good, and we are moving away from notebooks and models sharing to a collaborative way of working via MLOps. We will discuss this big evolution of DevOps, MLOps, Data Engineering, Data Science, and Data-Driven business in the meetup.
----------- Connect With Us ✌️-------------
Join our Slack community: https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register
Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Emmanuel on LinkedIn: https://www.linkedin.com/in/emmanuelraj7/
// Other Links:
www.emmanuelraj.com
https://www.youtube.com/watch?v=m32k9jcY4pY
https://www.youtube.com/watch?v=1sGECHbc9zg
438 episodes
ShareManage episode 313294438 series 3241972
Content provided by Demetrios. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Demetrios or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
MLOps community meetup #69! Last Wednesday we talked to Emmanuel Raj, Senior Machine Learning Engineer at TietoEvry.
//Abstract
The talk focuses on simplifying/demystifying MLOps, encourages others to take steps to learn this powerful SE method. We also talked about Emmanuel's journey in ML engineering, the evolution of MLOps, daily life, and SE problems, and what's next in MLOps (fusion of AIOps, EU AI regulations impact on MLOps workflow, etc).
//Bio
Emmanuel Raj is a Finland-based Senior Machine Learning Engineer. He is a passionate ML Researcher, Software engineer, speaker, and author. He is also a Machine Learning Engineer at TietoEvry and a Researcher at Arcada University of Applied Sciences in Finland. With over 6+ years of experience building ML solutions in the industry, he has worked on multiple domains such as Healthcare, Manufacturing, Finance, Retail, e-commerce, aviation, etc.
Emmanuel is passionate about democratizing AI and bringing state-of-the-art research to the industry. He has a keen interest in R&D in technologies such as Edge AI, Blockchain, NLP, MLOps, and Robotics. He believes the best way to learn is to teach and he is passionate about teaching about new technologies, that's one reason for writing a book and making an online course on MLOps.
Emmanuel is the author of the book "Engineering MLOps". The book covers industry best case practices and hands-on implementation to Rapidly build, test, and manage production-ready machine learning life cycles at scale. There is a big evolution happening in Data science for good, and we are moving away from notebooks and models sharing to a collaborative way of working via MLOps. We will discuss this big evolution of DevOps, MLOps, Data Engineering, Data Science, and Data-Driven business in the meetup.
----------- Connect With Us ✌️-------------
Join our Slack community: https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register
Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Emmanuel on LinkedIn: https://www.linkedin.com/in/emmanuelraj7/
// Other Links:
www.emmanuelraj.com
https://www.youtube.com/watch?v=m32k9jcY4pY
https://www.youtube.com/watch?v=1sGECHbc9zg
438 episodes
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MLOps.community
1 Getting AI Apps Past the Demo // Vaibhav Gupta // #319 50:29
50:29 
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Play Later Play Later Lists Like LikedGetting AI Apps Past the Demo // MLOps Podcast #319 with Vaibhav Gupta, CEO of BoundaryML. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract It's been two years, and we still seem to see AI disproportionately more in demos than production features. Why? And how can we apply engineering practices we've all learned in the past decades to our advantage here? // Bio Vaibhav is one of the creators of BAML and a YC alum. He spent 10 years in AI performance optimization at places like Google, Microsoft, and D.E. Shaw. He loves diving deep and chatting about anything related to Gen AI and Computer Vision! // Related Links Website: https://www.boundaryml.com/ ~~~~~~~~ ✌️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 Vaibhav on LinkedIn: /vaigup Timestamps: [00:00] Vaibhav's preferred coffee [00:38] What is BAML [03:07] LangChain Overengineering Issues [06:46] Verifiable English Explained [11:45] Python AI Integration Challenges [15:16] Strings as First-Class Code [21:45] Platform Gap in Development [30:06] Workflow Efficiency Tools [33:10] Surprising BAML Insights [40:43] BAML Cool Projects [45:54] BAML Developer Conversations [48:39] Wrap up…
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MLOps.community
1 Building Out GPU Clouds // Mohan Atreya // #317 47:57
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Play Later Play Later Lists Like LikedDemetrios and Mohan Atreya break down the GPU madness behind AI — from supply headaches and sky-high prices to the rise of nimble GPU clouds trying to outsmart the giants. They cover power-hungry hardware, failed experiments, and how new cloud models are shaking things up with smarter provisioning, tokenized access, and a whole lotta hustle. It's a wild ride through the guts of AI infrastructure — fun, fast, and full of sparks! Big thanks to the folks at Rafay for backing this episode — appreciate the support in making these conversations happen! // BioMohan is a seasoned and innovative product leader currently serving as the Chief Product Officer at Rafay Systems. He has led multi-site teams and driven product strategy at companies like Okta, Neustar, and McAfee. // Related LinksWebsites: https://rafay.co/ ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~ Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore MLOps Swag/Merch: [https://shop.mlops.community/] Connect with Demetrios on LinkedIn: /dpbrinkm Connect with Mohan on LinkedIn: /mohanatreya Timestamps: [00:00] AI/ML Customer Challenges [04:21] Dependency on Microsoft for Revenue [09:08] Challenges of Hypothesis in AI/ML [12:17] Neo Cloud Onboarding Challenges [15:02] Elastic GPU Cloud Automation [19:11] Dynamic GPU Inventory Management [20:25] Terraform Lacks Inventory Awareness [26:42] Onboarding and End-User Experience Strategies [29:30] Optimizing Storage for Data Efficiency [33:38] Pizza Analogy: User Preferences [35:18] Token-Based GPU Cloud Monetization [39:01] Empowering Citizen Scientists with AI [42:31] Innovative CFO Chatbot Solutions [47:09] Cloud Services Need Spectrum…
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MLOps.community
1 A Candid Conversation Around MCP and A2A // Rahul Parundekar and Sam Partee // #316 SF Live 1:04:42
1:04:42 Play Later Play Later Lists Like Liked1:04:42
Play Later Play Later Lists Like LikedDemetrios, Sam Partee, and Rahul Parundekar unpack the chaos of AI agent tools and the evolving world of MCP (Model Context Protocol). With sharp insights and plenty of laughs, they dig into tool permissions, security quirks, agent memory, and the messy path to making agents actually useful. // Bio Sam Partee Sam Partee is the CTO and Co-Founder of Arcade AI. Previously a Principal Engineer leading the Applied AI team at Redis, Sam led the effort in creating the ecosystem around Redis as a vector database. He is a contributor to multiple OSS projects including Langchain, DeterminedAI, LlamaIndex and Chapel amongst others. While at Cray/HPE he created the SmartSim AI framework which is now used at national labs around the country to integrate HPC simulations like climate models with AI. Rahul Parundekar Rahul Parundekar is the founder of AI Hero. He graduated with a Master's in Computer Science from USC Los Angeles in 2010, and embarked on a career focused on Artificial Intelligence. From 2010-2017, he worked as a Senior Researcher at Toyota ITC working on agent autonomy within vehicles. His journey continued as the Director of Data Science at FigureEight (later acquired by Appen), where he and his team developed an architecture supporting over 36 ML models and managing over a million predictions daily. Since 2021, he has been working on AI Hero, aiming to democratize AI access, while also consulting on LLMOps(Large Language Model Operations), and AI system scalability. Other than his full time role as a founder, he is also passionate about community engagement, and actively organizes MLOps events in SF, and contributes educational content on RAG and LLMOps at learn.mlops.community. // Related Links Websites: arcade.dev aihero.studio~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~ Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore MLOps Swag/Merch: [https://shop.mlops.community/] Connect with Demetrios on LinkedIn: /dpbrinkm Connect with Rahul on LinkedIn: /rparundekar Connect with Sam on LinkedIn: /samparteeTimestamps:[00:00] Agents & Tools, Explained (Without Melting Your Brain) [09:51] MVP Servers: Why Everything’s on Fire (and How to Fix It) [13:18] Can We Actually Trust the Protocol? [18:13] KYC, But Make It AI (and Less Painful) [25:25] Web Automation Tests: The Bugs Strike Back [28:18] MCP Dev: What Went Wrong (and What Saved Us) [33:53] Social Login: One Button to Rule Them All [39:33] What Even Is an AI-Native Developer? [42:21] Betting Big on Smarter Models (High Risk, High Reward) [51:40] Harrison’s Bold New Tactic (With Real-Life Magic Tricks) [55:31] Async Task Handoffs: Herding Cats, But Digitally [1:00:37] Getting AI to Actually Help Your Workflow [1:03:53] The Infamous Varma System Error (And How We Dodge It)…
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MLOps.community
1 AI in M&A: Building, Buying, and the Future of Dealmaking // Kison Patel // #315 55:32
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Play Later Play Later Lists Like LikedAI in M&A: Building, Buying, and the Future of Dealmaking // MLOps Podcast #315 with Kison Patel, CEO and M&A Science at DealRoom . Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractThe intersection of M&A and AI, exploring how the DealRoom team developed AI capabilities and the practical use cases of AI in dealmaking. Discuss the evolving landscape of AI-driven M&A, the factors that make AI companies attractive acquisition targets, and the key indicators of success in this space. // Bio Kison Patel is the Founder and CEO of DealRoom, an M&A lifecycle management platform designed for buyer-led M&A and recognized twice on the Inc. 5000 Fastest Growing Companies list. He also founded M&A Science, a global community offering courses, events, and the top-rated M&A Science podcast with over 2.25 million downloads. Through the podcast, Kison shares actionable insights from top M&A experts, helping professionals modernize their approach to deal-making. He is also the author of *Agile M&A: Proven Techniques to Close Deals Faster and Maximize Value*, a guide to tech-enabled, adaptive M&A practices. Kison is dedicated to disrupting traditional M&A with innovative tools and education, empowering teams to drive greater efficiency and value. // Related LinksWebsite: https://dealroom.nethttps://www.mascience.com ~~~~~~~~ ✌️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 Kison on LinkedIn: /kisonpatel…
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MLOps.community
1 AI, Marketing, and Human Decision Making // Fausto Albers // #313 49:40
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Play Later Play Later Lists Like LikedAI, Marketing, and Human Decision Making // MLOps Podcast #313 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 Demetrios and Fausto Albers explore how generative AI transforms creative work, decision-making, and human connection, highlighting both the promise of automation and the risks of losing critical thinking and social nuance. // 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 Moravec's paradox: https://en.wikipedia.org/wiki/Moravec%27s_paradox?utm_source=chatgpt.com Behavior Modeling, Secondary AI Effects, Bias Reduction & Synthetic Data // Devansh Devansh // #311: https://youtu.be/jJXee5rMtHI ~~~~~~~~ ✌️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 Fausto on LinkedIn: /stepintoliquid Timestamps:[00:00] Fausto's preferred coffee[00:26] Takeaways[01:18] Automated Ad Creative Generation[07:14] AI in Marketing Workflows[13:23] MCP and System Bottlenecks[21:45] Forward Compatibility vs Optimization[29:57] Unlocking Workflow Speed[33:48] AI Dependency vs Critical Thinking[37:44] AI Realism and Paradoxes[42:30] Outsourcing Decision-Making Risks[46:22] Human Value in Automation[49:02] Wrap up…
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MLOps.community
1 MLOps with Databricks // Maria Vechtomova // #314 52:43
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Play Later Play Later Lists Like LikedMLOps with Databricks // MLOps Podcast #314 with Maria Vechtomova, MLOps Tech Lead | Founder at Ahold Delhaize | Marvelous MLOps. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract The world of MLOps is very complex as there is an endless amount of tools serving its purpose, and it is very hard to get your head around it. Instead of combining various tools and managing them, it may make sense to opt for a platform instead. Databricks is a leading platform for MLOps. In this discussion, I will explain why it is the case, and walk you through Databricks MLOps features. // Bio Maria is an MLOps Tech lead with over 10 years of experience in Data and AI. For the last 8 years, Maria has focused on MLOps and helped to establish MLOps best practices at large corporations. Together with her colleague, she co-founded Marvelous MLOps to share knowledge on MLOps via training, social media posts, and blogs. // Related Links Website: marvelousmlops.io MLOps Course discount code: MLOPS100 for the podcast listeners - https://maven.com/marvelousmlops/mlops-with-databricks?promoCode=MLOPS100 ~~~~~~~~ ✌️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 Maria on LinkedIn: /maria-vechtomovaTimestamps: [00:00] Maria's preferred coffee[00:42] Takeaways[02:48] Why Databricks for MLOps[09:56] Platform Adoption vs Procurement Pain[12:56] Databricks Best Practices[16:57] Feature Store Overview[22:00] Managed system trade-offs[29:15] Databricks Developments and Trends[44:31] Insider Info and Summit[45:47] Data Ownership Pros and Cons[48:08] Data Contracts and Challenges[51:25] MLOps Databricks Book Guide[52:19] Wrap up…
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MLOps.community
1 Making AI Reliable is the Greatest Challenge of the 2020s // Alon Bochman // #312 1:01:37
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Play Later Play Later Lists Like LikedMaking AI Reliable is the Greatest Challenge of the 2020s // MLOps Podcast #312 with Alon Bochman, CEO of RagMetrics. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter Huge shout-out to @RagMetrics for sponsoring this episode! // Abstract Demetrios talks with Alon Bochman, CEO of RagMetrics, about testing in machine learning systems. Alon stresses the value of empirical evaluation over influencer advice, highlights the need for evolving benchmarks, and shares how to effectively involve subject matter experts without technical barriers. They also discuss using LLMs as judges and measuring their alignment with human evaluators. // Bio Alon is a product leader with a fintech and adtech background, ex-Google, ex-Microsoft. Co-founded and sold a software company to Thomson Reuters for $30M, grew an AI consulting practice from 0 to over $ 1 Bn in 4 years. 20-year AI veteran, winner of three medals in model-building competitions. In a prior life, he was a top-performing hedge fund portfolio manager.Alon lives near NYC with his wife and two daughters. He is an avid reader, runner, and tennis player, an amateur piano player, and a retired chess player. // Related Links Website: ragmetrics.ai ~~~~~~~~ ✌️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 Alon on LinkedIn: /alonbochman Timestamps: [00:00] Alon's preferred coffee[00:15] Takeaways[00:47] Testing Multi-Agent Systems[05:55] Tracking ML Experiments[12:28] AI Eval Redundancy Balance[17:07] Handcrafted vs LLM Eval Tradeoffs[28:15] LLM Judging Mechanisms[36:03] AI and Human Judgment[38:55] Document Evaluation with LLM[42:08] Subject Matter Expertise in Co-Pilots[46:33] LLMs as Judges[51:40] LLM Evaluation Best Practices[55:26] LM Judge Evaluation Criteria[58:15] Visualizing AI Outputs[1:01:16] Wrap up…
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MLOps.community
1 Behavior Modeling, Secondary AI Effects, Bias Reduction & Synthetic Data // Devansh Devansh // #311 1:01:35
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Play Later Play Later Lists Like LikedBehavior Modeling, Secondary AI Effects, Bias Reduction & Synthetic Data // MLOps Podcast #311 with Devansh Devansh, Head of AI at Stealth AI Startup. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractOpen-source AI researcher Devansh Devansh joins Demetrios to discuss grounded AI research, jailbreaking risks, Nvidia’s Gretel AI acquisition, and the role of synthetic data in reducing bias. They explore why deterministic systems may outperform autonomous agents and urge listeners to challenge power structures and rethink how intelligence is built into data infrastructure. // BioThe best meme-maker in Tech. Writer on AI, Software, and the Tech Industry. // Related Links Subscribe to Artificial Intelligence Made Simple: https://artificialintelligencemadesimple.substack.com/https://www.linkedin.com/pulse/alternative-ways-build-ai-models-taoist-devansh-devansh-z9iff/?trackingId=TKvUBldml6rOQUjqam%2B7lA%3D%3D ~~~~~~~~ ✌️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 Devansh on LinkedIn: /devansh-devansh-516004168 Timestamps:[00:00] Devansh's preferred coffee[01:23] Jailbreaking DeepSeek[02:24] AI Made Simple [07:16] Leveraging AI for Data Insights[10:42] Synthetic Data and LLMs[19:29] AI Experience Design[22:20] Synthetic Data Bias Reduction[26:33] Data Ecosystem Insights[29:50] Moving Intelligence to Data Layer[36:37] Minimizing Model Responsibility[40:04] Workflow vs Generalized Agents[49:24] AI Second-Order Effects[55:26] AI Experience vs Efficiency[1:01:10] Wrap up…
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MLOps.community
1 GraphBI: Expanding Analytics to All Data Through the Combination of GenAI, Graph, & Visual Analytics // Paco Nathan & Weidong Yang // #310 1:14:01
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Play Later Play Later Lists Like LikedGraphBI: Expanding Analytics to All Data Through the Combination of GenAI, Graph, & Visual Analytics // MLOps Podcast #310 with Paco Nathan, Principal DevRel Engineer at Senzing & Weidong Yang, CEO of Kineviz. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractExisting BI and big data solutions depend largely on structured data, which makes up only about 20% of all available information, leaving the vast majority untapped. In this talk, we introduce GraphBI, which aims to address this challenge by combining GenAI, graph technology, and visual analytics to unlock the full potential of enterprise data. Recent technologies like RAG (Retrieval-Augmented Generation) and GraphRAG leverage GenAI for tasks such as summarization and Q&A, but they often function as black boxes, making verification challenging. In contrast, GraphBI uses GenAI for data pre-processing—converting unstructured data into a graph-based format—enabling a transparent, step-by-step analytics process that ensures reliability. We will walk through the GraphBI workflow, exploring best practices and challenges in each step of the process: managing both structured and unstructured data, data pre-processing with GenAI, iterative analytics using a BI-focused graph grammar, and final insight presentation. This approach uniquely surfaces business insights by effectively incorporating all types of data. // BioPaco NathanPaco Nathan is a "player/coach" who excels in data science, machine learning, and natural language, with 40 years of industry experience. He leads DevRel for the Entity Resolved Knowledge Graph practice area at Senzing.com and advises Argilla.io, Kurve.ai, KungFu.ai, and DataSpartan.co.uk, and is lead committer for the pytextrank and kglab open source projects. Formerly: Director of Learning Group at O'Reilly Media; and Director of Community Evangelism at Databricks. Weidong YangWeidong Yang, Ph.D., is the founder and CEO of Kineviz, a San Francisco-based company that develops interactive visual analytics based solutions to address complex big data problems. His expertise spans Physics, Computer Science and Performing Art, with significant contributions to the semiconductor industry and quantum dot research at UC, Berkeley and Silicon Valley. Yang also leads Kinetech Arts, a 501(c) non-profit blending dance, science, and technology. An eloquent public speaker and performer, he holds 11 US patents, including the groundbreaking Diffraction-based Overlay technology, vital for sub-10-nm semiconductor production. // Related LinksWebsite: https://www.kineviz.com/Blog: https://medium.com/kinevizWebsite: https://derwen.ai/pacohttps://huggingface.co/pacoidhttps://github.com/ceterihttps://neo4j.com/developer-blog/entity-resolved-knowledge-graphs/ ~~~~~~~~ ✌️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 Weidong on LinkedIn: /yangweidong/Connect with Paco on LinkedIn: /ceteri/…
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MLOps.community
1 AI Data Engineers - Data Engineering After AI // Vikram Chennai // #309 49:40
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Play Later Play Later Lists Like LikedAI Data Engineers - Data Engineering after AI // MLOps Podcast #309 with Vikram Chennai, Founder/CEO of Ardent AI. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractA discussion of Agentic approaches to Data Engineering. Exploring the benefits and pitfalls of AI solutions and how to design product-grade AI agents, especially in data. // BioSecond Time Founder. 5 years building Deep learning models. Currently, AI Data Engineers // Related LinksWebsite: tryardent.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 Vikram on LinkedIn: /vikram-chennai/…
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MLOps.community
1 I Am Once Again Asking "What is MLOps?" // Oleksandr Stasyk // #308 1:07:22
1:07:22 Play Later Play Later Lists Like Liked1:07:22
Play Later Play Later Lists Like LikedI am once again asking "What is MLOps?" // MLOps Podcast #308 with Oleksandr Stasyk, Engineering Manager, ML Platform of Synthesia. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractWhat does it mean to MLOps now? Everyone is trying to make a killing from AI, everyone wants the freshest technology to show off as part of their product. But what impact does that have on the "journey of the model". Do we still think about how an idea makes it's way to production to make money? How can we get better at it, maybe the answer lies in the ancient "non-AI" past... // BioFor the majority of my career I have been a "full stack" developer with a leaning towards devops and platforms. In the last four years or so, I have worked on ML Platforms. I find that applying good software engineering practises is more important than ever in this AI fueled world. // Related LinksBlogs: https://medium.com/@sashman90/mlops-the-evolution-of-the-t-shaped-engineer-a4d8a24a4042 ~~~~~~~~ ✌️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 Sash on LinkedIn: /oleksandr-stasyk-5751946b…
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MLOps.community
1 How Sama is Improving ML Models to Make AVs Safer // Duncan Curtis // #307 45:34
45:34 Play Later Play Later Lists Like Liked45:34
Play Later Play Later Lists Like LikedHow Sama is Improving ML Models to Make AVs Safer // MLOps Podcast #307 with Duncan Curtis, SVP of Product and Technology at Sama. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract Between Uber’s partnership with NVIDIA and speculation around the U.S.'s President Donald Trump enacting policies that allow fully autonomous vehicles, it’s more important than ever to ensure the accuracy of machine learning models. Yet, the public’s confidence in AVs is shaky due to scary accidents caused by gaps in the tech that Sama is looking to fill.As one of the industry’s top leaders, Duncan Curtis, SVP of Product and Technology at Sama, would be delighted to share how we can improve the accuracy, speed, and cost-efficiency of ML algorithms for AVs. Sama’s machine learning technologies minimize the risk of model failure and lower the total cost of ownership for car manufacturers including Ford, BMW, and GM, as well as four of the five top OEMs and their Tier 1 suppliers. This is especially timely as Tesla is under investigation for crashes due to its Smart Summon feature and Waymo recently had a passenger trapped in one of its driverless taxis. // Bio Duncan Curtis is the SVP of Product at Sama, a leader in de-risking ML models, delivering best-in-class data annotation solutions with our enterprise-strength, experience & expertise, and ethical AI approach. To this leadership role, he brings 4 years of Autonomous Vehicle experience as the Head of Product at Zoox (now part of Amazon) and VP of Product at Aptiv, and 4 years of AI experience as a product manager at Google where he delighted the +1B daily active users of the Play Store and Play Games. // Related Links Website: https://www.sama.com/Tesla is under investigation: https://www.cnn.com/2025/01/07/business/nhtsa-tesla-smart-summon-probe/index.htmlWaymo recently had a passenger trapped: https://www.cbsnews.com/losangeles/news/la-man-nearly-misses-flight-as-self-driving-waymo-taxi-drives-around-parking-lot-in-circles/https://coruzant.com/profiles/duncan-curtis/https://builtin.com/articles/remove-bias-from-machine-learning-algorithmsLook At Your ****ing Data :eyes: // Kenny Daniel // MLOps Podcast #292: https://youtu.be/6EMnkAHmoag ~~~~~~~~ ✌️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 Luca on LinkedIn: /duncan-curtis Timestamps:[00:00] Duncan's preferred coffee[00:08] Takeaways[01:00] AI Enterprise Focus[04:18] Human-in-the-loop Efficiency[08:42] Edge Cases in AI[14:14] Forward Combat Compatibility Failures[17:30] Specialized Data Annotation Challenges[24:44] SAM for Ring Integration[28:50] Data Bottleneck in AI[31:29] Data Connector Horror Story[33:17] Sama AI Data Annotation[37:20] Cool Business Problems Solved[40:50] AI ROI Framework[45:11] Wrap up…
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MLOps.community
1 Agents of Innovation: AI-Powered Product Ideation with Synthetic Consumer Testing // Luca Fiaschi // #306 1:02:23
1:02:23 Play Later Play Later Lists Like Liked1:02:23
Play Later Play Later Lists Like LikedAgents of Innovation: AI-Powered Product Ideation with Synthetic Consumer Testing // MLOps Podcast #306 with Luca Fiaschi, Partner of PyMC Labs. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract Traditional product development cycles require extensive consumer research and market testing, resulting in lengthy development timelines and significant resource investment. We've transformed this process by building a distributed multi-agent system that enables parallel quantitative evaluation of hundreds of product concepts. Our system combines three key components: an Agentic innovation lab generating high-quality product concepts, synthetic consumer panels using fine-tuned foundational models validated against historical data, and an evaluation framework that correlates with real-world testing outcomes. We can talk about how this architecture enables rapid concept discovery and digital experimentation, delivering insights into product success probability before development begins. Through case studies and technical deep-dives, you'll learn how we built an AI powered innovation lab that compresses months of product development and testing into minutes - without sacrificing the accuracy of insights. // Bio With over 15 years of leadership experience in AI, data science, and analytics, Luca has driven transformative growth in technology-first businesses. As Chief Data & AI Officer at Mistplay, he led the company’s revenue growth through AI-powered personalization and data-driven pricing. Prior to that, he held executive roles at global industry leaders such as HelloFresh ($8B), Stitch Fix ($1.2B) and Rocket Internet ($1B). Luca's core competencies include machine learning, artificial intelligence, data mining, data engineering, and computer vision, which he has applied to various domains such as marketing, logistics, personalization, product, experimentation and pricing.He is currently a partner at PyMC Labs, a leading data science consultancy, providing insights and guidance on applications of Bayesian and Causal Inference techniques and Generative AI to fortune 500 companies. Luca holds a PhD in AI and Computer Vision from Heidelberg University and has more than 450 citations on his research work. // Related Links Website: https://www.pymc-labs.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 Luca on LinkedIn: /lfiaschi…
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MLOps.community
1 Real-Time Forecasting Faceoff: Time Series vs. DNNs // Josh Xi // #305 53:41
53:41 Play Later Play Later Lists Like Liked53:41
Play Later Play Later Lists Like LikedReal-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 // Abstract In 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. // Bio Josh 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 Links Website: https://www.lyft.com/ Real-Time Spatial Temporal Forecasting @ Lyft blog: https://eng.lyft.com/real-time-spatial-temporal-forecasting-lyft-fa90b3f3ec24 ~~~~~~~~ ✌️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 Josh on LinkedIn: /joshxiaominxi…
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MLOps.community
1 We're All Finetuning Incorrectly // Tanmay Chopra // #304 1:00:30
1:00:30 Play Later Play Later Lists Like Liked1:00:30
Play Later Play Later Lists Like LikedWe'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…
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MLOps.community
1 From Shiny to Strategic: The Maturation of AI Across Industries // David Cox // #303 40:50
40:50 Play Later Play Later Lists Like Liked40:50
Play Later Play Later Lists Like LikedFrom 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…
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MLOps.community
1 Streaming Ecosystem Complexities and Cost Management // Rohit Agrawal // #302 48:51
48:51 Play Later Play Later Lists Like Liked48:51
Play Later Play Later Lists Like LikedStreaming 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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MLOps.community
1 Fraud Detection in the AI Era // Rafael Sandroni // #301 41:19
41:19 Play Later Play Later Lists Like Liked41:19
Play Later Play Later Lists Like LikedBuilding 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…
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MLOps.community
1 Beyond the Matrix: AI and the Future of Human Creativity 55:08
55:08 Play Later Play Later Lists Like Liked55:08
Play Later Play Later Lists Like LikedBeyond 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…
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MLOps.community
1 Efficient GPU infrastructure at LinkedIn // Animesh Singh // MLOps Podcast #299 59:13
59:13 Play Later Play Later Lists Like Liked59:13
Play Later Play Later Lists Like LikedBuilding 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…
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MLOps.community
1 Building Trust Through Technology: Responsible AI in Practice // Allegra Guinan // #298 47:08
47:08 Play Later Play Later Lists Like Liked47:08
Play Later Play Later Lists Like LikedBuilding 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!…
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MLOps.community
1 Claude Plays Pokémon - A Conversation with the Creator // David Hershey // #294 46:58
46:58 Play Later Play Later Lists Like Liked46:58
Play Later Play Later Lists Like LikedI 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…
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MLOps.community
1 From Rules to Reasoning Engines // George Mathew // #296 1:05:26
1:05:26 Play Later Play Later Lists Like Liked1:05:26
Play Later Play Later Lists Like LikedFrom 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…
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1 GenAI Traffic: Why API Infrastructure Must Evolve... Again // Erica Hughberg // #296 1:06:24
1:06:24 Play Later Play Later Lists Like Liked1:06:24
Play Later Play Later Lists Like LikedGenAI 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
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1 The Unbearable Lightness of Data // Rohit Krishnan // #295 54:16
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Play Later Play Later Lists Like LikedThe 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…
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1 Kubernetes, AI Gateways, and the Future of MLOps // Alexa Griffith // #294 51:43
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Play Later Play Later Lists Like LikedKubernetes, 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…
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1 Future of Software, Agents in the Enterprise, and Inception Stage Company Building // Eliot Durbin // #293 54:26
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Play Later Play Later Lists Like LikedFuture 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…
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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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In Agents in Production [Podcast Limited Series] - Episode Four , Donné Stevenson and Paul van der Boor break down the deployment of a Token Data Analyst agent at Prosus—why, how, and what worked. They discuss the challenges of productionizing the agent, from architecture to mitigating LLM overconfidence, key design choices, the role of pre-checks for clarity, and why they opted for simpler text-based processes over complex recursive methods. Guest speakers: Paul van der Boor - VP AI at Prosus Group Donne Stevenson - Machine Learning Engineer at Prosus Group 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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Agents in Production [Podcast Limited Series] - Episode Three explores the concept of web agents—AI-powered systems that interact with the web as humans do, navigating browsers instead of relying solely on APIs. The discussion covers why web agents emerge as a natural step in AI evolution, their advantages over API-based systems, and their potential impact on e-commerce and automation. The conversation also highlights challenges in making websites agent-friendly and envisions a future where agents seamlessly handle tasks like booking flights or ordering food. Guest speakers: Paul van der Boor - VP AI at Prosus Group Chiara Caratelli - Data Scientist at Prosus Group 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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