MLOps.community

Join Benjamin Rogojan, a seasoned data engineering consultant, along with Gable's Chad Sanderson, NAO's CTO Christophe Blefari, and Acryl Data's Maggie Hays for a lively discussion on the ever-evolving world of data. They delve into their diverse career journeys and transformative experiences in data engineering. Expect insights on the rise of modern data tools, personal anecdotes about creating data lakes, and the emerging challenges in data governance. Discover how shared ownership of data models enhances collaboration and drives business value!

Jelmer Borst, analytics and machine learning leader at Picnic, and Daniela Solis Morales, machine learning lead, delve into the dynamics of building effective ML teams. They discuss shifting from decentralized to centralized structures and the challenges of recruiting the right talent. The pair explores the complexities of demand forecasting in online grocery delivery and stresses the importance of collaboration between data scientists and business teams. They also highlight the need for lightweight, scalable ML infrastructure and the evolving roles within data science to meet business goals.

In this discussion, Francisco Ingham, an LLM consultant and founder of Pampa Labs, delves into what it means to be LLM-native for companies. He emphasizes the integration of large language models into business functions, balancing productivity with a human touch. The conversation also highlights the importance of tracking optimization in engineering experiments and strategic integration of LLMs within system architecture. Additionally, Ingham explores the complexities of retrieval-augmented generation techniques and their application in enhancing user experiences.

Simba Khadder, the founder and CEO of Featureform and a machine learning expert, dives deep into the evolution of feature stores and their intersection with vector stores. He explains the significance of embeddings for recommender systems and discusses how personalization enhances user experiences with large language models. Simba also addresses the challenges in managing feature pipelines and the trade-offs between system complexity and reliability. Tune in to learn about the latest innovations shaping the MLOps landscape!

Stefano Bosisio, an MLOps Engineer with a PhD in chemistry, shares his inspiring journey from academia to the tech industry. He discusses the challenges of building ML platforms in finance while emphasizing the importance of soft skills. Topics include the strategic choices behind building vs. buying tech solutions and how MLOps can enhance financial operations. Stefano also delves into auto-scaling in data engineering and introduces his new MLOps course, designed to equip future engineers with essential skills in a hands-on way.

Gottam Sai Bhrath, a Senior Machine Learning Engineer, and Cole Bailey, an ML Platform Engineering Manager at Delivery Hero, dive into the intricacies of optimizing machine learning practices across their global operations. They discuss the evolution of feature stores, balancing centralized and decentralized models, and overcoming technological integration challenges in a diverse organization. The conversation highlights their collaborative approach to building a Global Feature Store, addressing real-time data processing and strategies to maintain data integrity in a complex environment.

In this engaging discussion, Adam Kamor, co-founder of Tonic, shares his expertise in creating mock data while ensuring data privacy. He highlights the significance of high-quality data for Retrieval-Augmented Generation (RAG) systems, tackling challenges like data documentation and chunking. Adam emphasizes innovative strategies for managing sensitive information and maintaining accuracy in retrieval. Listeners will gain valuable insights into building effective data pipelines and the critical role of database tools in today’s AI landscape.

In this engaging discussion, Jonathan Rioux, Managing Principal of AI Consulting at EPAM Systems, shares insights on the evolving landscape of MLOps. He highlights the critical balance between technical prowess and business alignment needed for successful AI products. Rioux also navigates the misconceptions surrounding MLOps, emphasizing its true role beyond just technical execution. The conversation touches on the importance of user-friendly tech solutions, measuring ROI in chatbot technology, and innovative approaches to tackling challenges in generative AI.

Shiva Bhattacharjee, Co-founder and CTO of TrueLaw, leverages his 20 years of tech experience to revolutionize legal workflows with bespoke models. He dives into the necessity of fine-tuning versus prompting in AI, emphasizing real-world applications in law. The discussion highlights retrieval-augmented generation and the complexities of prompt crafting for improved legal info retrieval. Additionally, he shares insights on optimizing embedding models and making strategic build vs. buy decisions in tech solutions for enhanced operational efficiency.

Vikram Rangnekar, an open-source software developer known for simplifying LLM integration, discusses his innovative work with LLMClient, a TypeScript library. He shares insights on crafting complex workflows using prompt tuning and composable prompts. The conversation delves into effective LLM prompting techniques and the challenges faced in building applications with LLMs. Vikram also explores the use of personas to enhance workflow efficiency and the need for improved frameworks to unlock the full potential of LLMs.