Data Brew by Databricks
Data Brew by Databricks is hosted by Denny and Brooke. The series explores topics in the data and AI community and interviews subject matter experts in data engineering and data science. The first season focuses on lakehouses, combining data warehouse features like ACID transactions with the scalability of data lakes against low-cost object stores. Listeners are invited to join with their morning brew and dive deep into data and AI.
Episodes
Reinforcement Fine-Tuning and the Future of Specialized AI Models
What if building a custom AI model for your business was as simple as giving feedback—no massive labeled datasets required? In this episode, we sit down with Travis Addair, CTO and Co-Founder of Predibase, creators of the first reinforcement fine-tuning platform, to explore the future of specialized AI.Discover how reinforcement fine-tuning is revolutionizing model customization, enabling you to s
Benchmarking Domain Intelligence | Data Brew | Episode 45
In this episode, Pallavi Koppol, Research Scientist at Databricks, explores the importance of domain-specific intelligence in large language models (LLMs). She discusses how enterprises need models tailored to their unique jargon, data, and tasks rather than relying solely on general benchmarks.Highlights include:- Why benchmarking LLMs for domain-specific tasks is critical for enterprise AI.- An
SWE-bench & SWE-agent | Data Brew | Episode 44
In this episode, Kilian Lieret, Research Software Engineer, and Carlos Jimenez, Computer Science PhD Candidate at Princeton University, discuss SWE-bench and SWE-agent, two groundbreaking tools for evaluating and enhancing AI in software engineering.Highlights include:- SWE-bench: A benchmark for assessing AI models on real-world coding tasks.- Addressing data leakage concerns in GitHub-sourced be
Enterprise AI: Research to Product | Data Brew | Episode 43
In this episode, Dipendra Kumar, Staff Research Scientist, and Alnur Ali, Staff Software Engineer at Databricks, discuss the challenges of applying AI in enterprise environments and the tools being developed to bridge the gap between research and real-world deployment.Highlights include:- The challenges of real-world AI—messy data, security, and scalability.- Why enterprises need high-accuracy, fi
Multimodal AI | Data Brew | Episode 42
In this episode, Chang She, CEO and Co-founder of LanceDB, discusses the challenges of handling multimodal data and how LanceDB provides a cutting-edge solution. He shares his journey from contributing to Pandas to building a database optimized for images, video, vectors, and subtitles.Highlights include:- The limitations of traditional storage systems like Parquet for multimodal AI.- How LanceDB
Age of Agents | Data Brew | Episode 41
In this episode, Michele Catasta, President of Replit, explores how AI-driven agents are transforming software development by making coding more accessible and automating application creation.Highlights include:- The difference between AI agents and copilots in software development.- How AI is democratizing coding, enabling non-programmers to build applications.- Challenges in AI agent development
Reward Models | Data Brew | Episode 40
In this episode, Brandon Cui, Research Scientist at MosaicML and Databricks, dives into cutting-edge advancements in AI model optimization, focusing on Reward Models and Reinforcement Learning from Human Feedback (RLHF).Highlights include:- How synthetic data and RLHF enable fine-tuning models to generate preferred outcomes.- Techniques like Policy Proximal Optimization (PPO) and Direct Preference
Retrieval, rerankers, and RAG tips and tricks | Data Brew | Episode 39
In this episode, Andrew Drozdov, Research Scientist at Databricks, explores how Retrieval Augmented Generation (RAG) enhances AI models by integrating retrieval capabilities for improved response accuracy and relevance.Highlights include:- Addressing LLM limitations by injecting relevant external information.- Optimizing document chunking, embedding, and query generation for RAG.- Improving retrie
The Power of Synthetic Data | Data Brew | Episode 38
In this episode, Yev Meyer, Chief Scientist at Gretel AI, explores how synthetic data transforms AI and ML by improving data access, quality, privacy, and model training.Highlights include:- Leveraging synthetic data to overcome AI data limitations.- Enhancing model training while mitigating ethical and privacy risks.- Exploring the intersection of computational neuroscience and AI workflows.- Add
Secret to Production AI: Tools & Infrastructure | Data Brew | Episode 37
In this episode, Julia Neagu, CEO & co-founder of Quotient AI, explores the challenges of deploying Generative AI and LLMs, focusing on model evaluation, human-in-the-loop systems, and iterative development.Highlights include:- Merging reinforcement learning and unsupervised learning for real-time AI optimization.- Reducing bias in machine learning with fairness and ethical considerations.- Le
Mixture of Memory Experts (MoME) | Data Brew | Episode 36
In this episode, Sharon Zhou, Co-Founder and CEO of Lamini AI, shares her expertise in the world of AI, focusing on fine-tuning models for improved performance and reliability.Highlights include:- The integration of determinism and probabilism for handling unstructured data and user queries effectively.- Proprietary techniques like memory tuning and robust evaluation frameworks to mitigate model i
Mixed Attention & LLM Context | Data Brew | Episode 35
In this episode, Shashank Rajput, Research Scientist at Mosaic and Databricks, explores innovative approaches in large language models (LLMs), with a focus on Retrieval Augmented Generation (RAG) and its impact on improving efficiency and reducing operational costs.Highlights include:- How RAG enhances LLM accuracy by incorporating relevant external documents.- The evolution of attention mechanism
Kumo AI & Relational Deep Learning | Data Brew | Episode 34
In this episode, Jure Leskovec, Co-founder of Kumo AI and Professor of Computer Science at Stanford University, discusses Relational Deep Learning (RDL) and its role in automating feature engineering. Highlights include:- How RDL enhances predictive modeling.- Applications in fraud detection and recommendation systems.- The use of graph neural networks to simplify complex data structures.
LLMs: Internals, Hallucinations, and Applications | Data Brew | Episode 33
Our fifth season dives into large language models (LLMs), from understanding the internals to the risks of using them and everything in between. While we're at it, we'll be enjoying our morning brew.In this session, we interviewed Chengyin Eng (Senior Data Scientist, Databricks), Sam Raymond (Senior Data Scientist, Databricks), and Joseph Bradley (Lead Production Specialist - ML, Databri
Demonstrate–Search–Predict Framework | Data Brew | Episode 32
We will dive into LLMs for our fifth season, from understanding the internals to the risks of using them and everything in between. While we’re at it, we’ll be enjoying our morning brew.In this session, we interviewed Omar Khattab - Computer Science Ph.D. Student at Stanford, creator of DSP (Demonstrate–Search–Predict Framework), to discuss DSP, common applications, and the future of NLP.
Generative AI Risks | Data Brew | Episode 31
We will dive into LLMs for our fifth season, from understanding the internals to the risks of using them and everything in between. While we’re at it, we’ll be enjoying our morning brew.In this session, we interviewed Yaron Singer, CEO of Robust Intelligence, Professor of Computer Science at Harvard University, and guest of Data Brew Season 3 (our first repeat guest!). In this session, we discus
John Snow Labs & SparkNLP | Data Brew | Episode 30
We are back and we will dive into LLMs from understanding the internals to the risks of using them and everything in between. While we’re at it, we’ll be enjoying our morning brew.In this session, we interviewed David Talby who is the CTO at John Snow Labs; they help healthcare & life science companies put AI to good use. David's interests include natural language processing, applied arti
Data Brew Season 4 Episode 6: Professional Athletes
For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.Shayna Powless and Eli Ankou, professional cyclist for L39ion of Los Angeles and defensive tackle for the Buffalo Bills, respectively, provide valuable insight on how professional athletes leverage data to improve their performance an
Data Brew Season 4 Episode 5: Public Health: Education, Access, and Policy
For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.Matt Willis, Marin County Public Health Officer, shares the three pillars of public health: education, access, and policy, and the critical role data plays in addressing the COVID-19 pandemic & opioid epidemic. See more at databri
Data Brew Season 4 Episode 4: 1283 Days of Running (and Counting)
For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.Running the length of the US every year, Alexandra Matthiesen shares her motivational secrets for running 1,283 consecutive days (and counting!) and redefining physical and mental limits. See more at databricks.com/data-brew
Data Brew Season 4 Episode 3: Last Man Standing
For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.Winner of the infamous Last Man Standing race (running 246 miles in 59 hours), Guillaume merges the world of competitive long-distance running with data science to push the boundaries of body and mind. See more at databricks.com/data
Data Brew Season 4 Episode 2: NBA Analytics
For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.Alexander Powell chronicles the evolution of sports analytics and how professional sports teams use data as a competitive advantage. See more at databricks.com/data-brew
Data Brew Season 4 Episode 1: Reducing Injury & Increasing Retention of Industrial Athletes
For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.Globally, 38,000 people get hurt on the job every hour. In the United States alone, over $250 billion dollars is spent on workplace injury annually. Sean Petterson, founder and CEO of StrongArm Tech, discusses the role of wearable dev
Data Brew Season 3 Episode 6: Open Source
For our third season, we focus on how leaders use data for change. Whether it’s building data teams or using data as a constructive catalyst, we interview subject matter experts from industry to dive deeper into these topics.For our season 3 finale, Nithya Ruff discusses the open-source ecosystem, ways to contribute to open-source projects (hint: it’s not just about the code), and how businesses c
Data Brew Season 3 Episode 5: Sustainability & Sake
For our third season, we focus on how leaders use data for change. Whether it’s building data teams or using data as a constructive catalyst, we interview subject matter experts from industry to dive deeper into these topics.We interview Junta Nakai in our most unique location yet - Brooklyn Kura - the first non-Japanese sake distillery in New York. In this episode, Junta shares the philosophical,
Data Brew Season 3 Episode 4: Executive Education
For our third season, we focus on how leaders use data for change. Whether it’s building data teams or using data as a constructive catalyst, we interview subject matter experts from industry to dive deeper into these topics.Did you know that the average tenure of a board member is longer than the average tenure of a marriage in the United States? In this episode, Coco Brown discusses the benefits
Data Brew Season 3 Episode 3: 3 T’s to Securing AI Systems: Tests, tests, and more tests
For our third season, we focus on how leaders use data for change. Whether it’s building data teams or using data as a constructive catalyst, we interview subject matter experts from industry to dive deeper into these topics.What does it mean to make your machine learning system “production-ready”? Yaron Singer walks us through the infrastructure, testing procedures, and more that help make ML sys
Data Brew Season 3 Episode 2: Data Culture Outside ‘The Valley’
For our third season, we focus on how leaders use data for change. Whether it’s building data teams or using data as a constructive catalyst, we interview subject matter experts from industry to dive deeper into these topics.Have you ever had a spam call automatically blocked for you? You can thank First Orion for that - in one day they blocked or scam tagged over 108 million calls - just on T-Mob
Data Brew Season 3 Episode 1: Disrupt: Challenge your Business Assumptions
For our third season, we focus on how leaders use data for change. Whether it’s building data teams or using data as a constructive catalyst, we interview subject matter experts from industry to dive deeper into these topics. In this season opener, Elena Donio shares her experience using data and domain knowledge to disrupt the traditional service and sales compensation model. She also discusses h
Data Brew Season 2 Episode 9: Data Driven Software
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.We branch, version, and test our code, but what if we treated data like code? Tim Hunter joins us to discuss the open-sou
Data Brew Season 2 Episode 8: Feature Engineering
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.Is there ever a “one-size fits all” approach for feature engineering? Find out this and more with Amanda Casari and Alice
Data Brew Season 2 Episode 7: Interpretable Machine Learning
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.What does it mean for a model to be “interpretable”? Ameet Talwalkar shares his thoughts on IML (Interpretable Machine Le
Data Brew Season 2 Episode 6: AutoML
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.Erin LeDell shares valuable insight on AutoML, what problems are best solved by it, its current limitations, and her thou
Data Brew Season 2 Episode 5: ML Applications
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.Good machine learning starts with high quality data. Irina Malkova shares her experience managing and ensuring high-fidel
Data Brew Season 2 Episode 4: Hyperparameter and Neural Architecture Search
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.Liam Li is a leading researcher in the fields of hyperparameter optimization and neural architecture search, and is the a
Data Brew Season 2 Episode 3: Infrastructure for ML
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more. Adam Oliner discusses how to design your infrastructure to support ML, from integration tests to glue code, the importan
Data Brew Season 2 Episode 2: Data Ethics
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.Have you ever wondered how your purchasing behavior may reveal protected attributes? Or how data scientists and business
Data Brew Season 2 Episode 1: ML in Production
For our second season, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.In the season opener, Matei Zaharia discusses how he entered the field of ML, best practices for productionizing ML pipelines, leverag
Data Brew Season 1 Episode 6: Journey of Big Data
Jules Damji and Tathagata Das guide us through their journey in big data and the evolution of data architecture in the past 30 years. They discuss some of the biggest changes in industry they’ve seen, as well as trends to look forward to in the coming years. This is a fun episode connecting all four authors of the Learning Spark, 2nd Edition book.See more at databricks.com/data-brew
Data Brew Season 1 Episode 5: Combining Machine Learning and MLflow with your Lakehouse
Ellissa Verseput, ML Engineer at Quby, joins Denny and Brooke to discuss how Quby leverages ML to extract additional value from their data lake and how they manage this process.See more at databricks.com/data-brew
Data Brew Season 1 Episode 4: BI on Data Lakes - Making it Real for Retail
In this session, we discuss the lessons learned with Lara Minor, Senior Enterprise Data Manager at Columbia Sportswear, on how her team achieved a 70% reduction in pipeline creation time. This had reduced ETL workload times from four hours with previous data warehouses to minutes enabling near real-time analytics. Her team migrated from multiple legacy data warehouses, run by individual lines of b
Data Brew Season 1 Episode 3: Demystifying Delta Lake
Delta Lake is an open source storage layer that brings reliability to data lakes. Delta Lake offers ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. It runs on top of your existing data lake and is fully compatible with Apache Spark APIs. For our “Demystifying Delta Lake” session, we will interview Michael Armbrust - committer and PMC member of Apache
Data Brew Season 1 Episode 2: Welcome to Lakehouse
Legacy approaches have failed to deliver on the promise of a single data architecture that can support every downstream use case from BI to AI. Lakehouse aspires to address this by combining the best of data warehouses and data lakes. Ali Ghodsi, Co-Founder and CEO of Databricks, and David Meyer, SVP of Product at Databricks, explain how. See more at databricks.com/data-brew
Data Brew Season 1 Episode 1: From data warehousing to data lakes in 40 minutes
In our inaugural episode, we’d like to welcome data warehouse luminaries Barry Devlin, Susan O’Connell, and Donald Farmer to discuss the evolution of data warehouses, data lakes, and lakehouses.See more at databricks.com/data-brew
Recommended
The Bread and Banter Podcast
The Church of What's Happening Now: The New Testament
Busted Open
Deadline: White House
Crickets Corner
History of the Earthquake and Fire in San Francisco
Fox news
K-Drama Obsessed Mamas | Beyond “Just One More Episode!”
True Crime Classics
The Healer Revolution
Becoming: HER with Nikki Spoelstra
Booked, Blonde & Busy w/ Olivia Ponton
