Daniel & Chris chat with Demetrios Brinkmann, 'the funniest guy in AI', about the MLOps Community survey results and the AI Quality Conference. They discuss RAG models, the fusion of traditional ML with generative AI, the 'Hacker Mindset' book, trade-offs between RAG and fine-tuning, the release of the Common Corpus dataset, limitations of transformers in AI, and future visions in the field.

Discover how Demetrios Brinkmann transitioned from teaching to founding the MLOps Community. Explore the role of MLOps in the ML lifecycle and the debate between specialized vs generalizing language models. Learn about the business implications of relying on OpenAI and the activities of the MLOps Community, including live events, podcasts, and new courses on generative AI.

Demetrios Brinkmann, AI strategist at Uber, discusses the evolution of Michelangelo platform at Uber, from basic ML predictions to deep learning and generative AI. Covering challenges faced in early versions and improvements in Michelangelo 2.0 and 3.0 like Pytorch support, enhanced model training, and integration of technologies like Nvidia’s Triton and Kubernetes. The platform now includes features like a Genai gateway, compliance guardrails, and model performance monitoring to streamline AI operations.

Worlds are colliding! This week we join forces with the hosts of the MLOps.Community podcast to discuss all things machine learning operations. We talk about how the recent explosion of foundation models and generative models is influencing the world of MLOps, and we discuss related tooling, workflows, perceptions, etc. Join the discussionChangelog++ members save 2 minutes on this episode because they made the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with extended episodes, make the ads disappear, and increment your audio quality with higher bitrate mp3s. Let’s do this! Featuring:Demetrios Brinkmann – XMihail Eric – Website, GitHub, XChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes:MLOps.Community Something missing or broken? PRs welcome!

Worlds are colliding! This week we join forces with the hosts of the MLOps.Community podcast to discuss all things machine learning operations. We talk about how the recent explosion of foundation models and generative models is influencing the world of MLOps, and we discuss related tooling, workflows, perceptions, etc. Join the discussionChangelog++ members save 2 minutes on this episode because they made the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with extended episodes, make the ads disappear, and increment your audio quality with higher bitrate mp3s. Let’s do this! Featuring:Demetrios Brinkmann – TwitterMihail Eric – Twitter, GitHub, WebsiteChris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes:MLOps.Community Something missing or broken? PRs welcome!

Demetrios Brinkmann, Chief Happiness Engineer at MLOps Community, leads a lively discussion with expert guests: Erica Greene from Yahoo News, Matar Haller of ActiveFence, Mohamed Elgendy from Kolena, and freelance data scientist Catherine Nelson. They dive into the intricacies of ML model testing, particularly around hate speech detection. The conversations reveal the unique challenges of AI quality assurance compared to traditional software, the importance of tiered testing, and strategies for balancing swift AI product releases with safety measures.

Daniel & Chris chat with 'the funniest guy in AI', Demetrios Brinkmann, discussing results of the MLOps Community survey and the upcoming AI Quality Conference. Topics include RAG models, generative AI workloads, transformer architecture, and neuromorphic computing.

Demetrios Brinkmann, co-founder of the global MLOps Community, shares insights on separating AI hype from reality. He discusses building an expansive tech network during the pandemic and the importance of shared learning in machine learning. The conversation dives into the transformative role of AI agents in software development, highlighting cost reductions and accessibility. Brinkmann also addresses the ethical implications of AI in business and HR, and the need for authenticity in vendor-community relationships to foster genuine engagement.

Demetrios Brinkmann, a notable member of the MLOps Community, joins for a lively and humorous dissection of the 2024 Gartner Hype Cycle for AI. They discuss the amusing mismatch between AI's hype and practical uses, touching on topics like quantum and ethical AI. The guys delve into small AI models and wearable tech, playfully introducing concepts like 'Trinket AI'. They also explore the spectrum of AI sustainability, revealing public sentiment and the quirks of customer service communication, all while keeping the tone light and engaging.

Demetrios Brinkmann, an MLOps expert, shares insights on MLOps, LLMOps, and DevOps. He discusses developing an online MLOps community, using third-party APIs, and building online communities. The episode also covers tools like LlamaIndex and Ollama for scaling LLMs, as well as guidance on data pipeline engineering using Kubernetes and YAML files.