In this episode of the "MLOps Weekly" podcast, host Simba Khadder talks with Paul Iusztin, a Senior ML and MLOps Engineer at Decoding ML, about his journey from software engineering to MLOps. They discuss the integration of software engineering principles in ML, the challenges of writing tests for ML applications, and the key differences between software and ML engineering. Paul shares insights on building scalable and reproducible MLOps platforms, emphasizing the importance of decoupling feature, training, and inference pipelines. They also explore the convergence of MLOps and LLMOps, highlighting the unique aspects of prompt engineering. The conversation underscores the importance of robust engineering practices and continuous adaptation in the rapidly evolving AI landscape.

For the latest episode of the MLOps Weekly Podcast, join host Simba Khadder as he chats with Gautam Krishnamurthi, partner at Great Point Ventures, about the rapidly evolving world of AI and its impacts on the future of venture capital investing. They also discuss the latest trends in large language models (LLMs), venture valuations, and the impact of rising interest rates on the public markets. Gautam provides his expertise on identifying real enterprise use cases, distinguishing valuable startups amidst the noise, and the critical role of infrastructure in the machine learning landscape. Lastly, you’ll learn about the transformative power of AI, how it's reshaping industries, and what investors seek in the next wave of groundbreaking companies.

In this podcast, Ketan Umare, CEO of Union and former leader of the ETA models team at Lyft, discusses the evolution of ML platforms. Topics include the importance of collaboration in AI, challenges of using Airflow in ML operations, building ML platforms with correctness and collaboration, and the future of AI workflows. Insights on navigating the changing landscape of AI and building scalable infrastructures are shared.

This episode of our MLOps Weekly Podcast features Simba Khadder, Featureform’s CEO, where he unravels the true meaning of “real-time” machine learning. The discussion breaks down real-time ML into three core aspects: latency, online serving, and real-time features. Simba also covers:How latency impacts the speed of ML systemsThe distinctions between online and offline modelsReal-time features and the importance of a balance between data freshness and latencyThis podcast will give listeners a better understanding of these concepts and apply them to their own ML projects.

The podcast delves into the evolution of ML and AI infrastructure, highlighting Metaflow's impact at Netflix. It explores tailored solutions for ML workflows, the seamless development process with Metaflow, and successful ML integration in business operations. The discussion also covers the significance of MLOps in enhancing productivity and the future of AI tools and platforms.

This episode of the MLOps Weekly Podcast delves into the intricate journey from academic research in AI to its practical application in industry, highlighting the challenges of bridging theoretical concepts with real-world solutions. CEO and founder of Manot, Chinar Movsisyan, and Featureform CEO Simba Khadder discuss the evolution of MLOps practices, emphasizing the importance of collaboration across diverse teams to innovate and scale AI technologies. Through engaging stories and insights, listeners are offered a deep dive into the strategies for deploying, managing, and improving machine learning models, showcasing the critical role of MLOps in advancing AI's impact in various sectors.

In this episode, we delve into the evolving landscape of AI with Sahil Agarwal, Enkrypt AI's CEO, focusing on the paramount importance of security, privacy, and governance. Through a discussion rich with insights, we uncover the strategies and challenges faced by organizations in safeguarding data and ethical considerations in AI deployment. The conversation highlights innovative solutions and the critical need for robust frameworks to navigate the complexities of AI integration in our digital age, emphasizing the balance between innovation and ethical responsibility.

In this episode of MLOps Weekly, host Simba Khadder engages with Eero Laaksonen, CEO of Valohai, to explore the intricacies of end-to-end MLOps platforms. They discuss the challenges and solutions in machine learning operations, delving into topics like proprietary vs. open-source tools, operational efficiency, and the evolving role of large language models in the MLOps domain.

Maxim Lukichev, Co-founder and CTO at Telmai, discusses the importance of proactive data quality, improving collaboration on data teams, treating data as a product, data governance, and the impact of data on analytics, ML, and AI.

For Episode 22 of the MLOps Weekly Podcast, Simba sits down with Demetrios Brinkmann, Founder of MLOps Community. They dive deep into the world of embeddings, vector databases, and why AI sometimes feels like ordering too much avocado toast. Tune in for a blend of MLOps wisdom, a sprinkle of humor, and a dash of existential AI crisis!