Demonstrate–Search–Predict Framework | Data Brew | Episode 32

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Andrew Stein: Living with Lions 46:39

8 dagen geleden46:39

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Vind ik leuk

Leuk

46:39

“If we march into that village and we start trying to persecute people for using poison, something that's very illegal, nobody's going to talk to us. We're not going to find out where the poison came from. We're not going to be able to shut anything down. We should take the approach that people are using poison because they're desperate, because they see no other alternative.” – Andrew Stein Andrew Stein is a wildlife ecologist who spent the past 25 years studying human carnivore conflict from African wild dogs and lions in Kenya and Botswana to leopards and hyenas in Namibia. His work has long focused on finding ways for people and predators to coexist. He is the founder of CLAWS , an organization based in Botswana that's working at the intersection of cutting-edge wildlife research and community driven conservation. Since its start in 2014 and official launch as an NGO in 2020, CLAWS has been pioneering science-based, tech-forward strategies to reduce conflict between people and carnivores. By collaborating closely with local communities, especially traditional cattle herders, CLAWS supports both species conservation and rural livelihoods—making coexistence not just possible, but sustainable.…

2 jaar geleden 33:14

MP3•Thuis aflevering

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.

42 afleveringen

#Databricks #Data Analytics #Apache Spark #Delta Lake #Machine Learning #Data Engineering #Artificial Intelligence #Tech #Data Science #Science #Lifestyle #Podcasting Education

Demonstrate–Search–Predict Framework | Data Brew | Episode 32

Data Brew by Databricks

71 subscribers

published 2 jaar geleden

MP3•Thuis aflevering

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.

42 afleveringen

#Databricks #Data Analytics #Apache Spark #Delta Lake #Machine Learning #Data Engineering #Artificial Intelligence #Tech #Data Science #Science #Lifestyle #Podcasting Education

Alle afleveringen

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SWE-bench & SWE-agent | Data Brew | Episode 44 36:22

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Enterprise AI: Research to Product | Data Brew | Episode 43 38:03

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Multimodal AI | Data Brew | Episode 42 42:14

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Age of Agents | Data Brew | Episode 41 40:47

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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, including error handling and software quality. - The growing role of AI in entrepreneurship and business automation. - Why 2025 could be the year of AI agents and what’s next for the industry.…

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Reward Models | Data Brew | Episode 40 39:58

29 dagen geleden39:58

39:58

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Retrieval, rerankers, and RAG tips and tricks | Data Brew | Episode 39 45:22

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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 retrieval systems with embeddings and fine-tuning techniques. - Enhancing search results using re-rankers and retrieval diagnostics. - Applying RAG strategies in enterprise AI for domain-specific improvements.…

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The Power of Synthetic Data | Data Brew | Episode 38 42:28

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Secret to Production AI: Tools & Infrastructure | Data Brew | Episode 37 37:14

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Mixture of Memory Experts (MoME) | Data Brew | Episode 36 41:24

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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 inaccuracies and hallucinations. - Lessons learned from deploying AI applications, including insights from GitHub Copilot’s rollout. Connect with Sharon Zhou and Lamini: https://www.linkedin.com/in/zhousharon/ https://x.com/realsharonzhou https://www.lamini.ai/…

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Mixed Attention & LLM Context | Data Brew | Episode 35 39:11

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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 mechanisms, including mixed attention strategies. - Practical applications of Mamba architectures and their trade-offs with traditional transformers.…

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43:27

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LLMs: Internals, Hallucinations, and Applications | Data Brew | Episode 33 38:50

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38:50

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, Databricks) on the best practices around LLM use cases, prompt engineering, and how to adapt MLOps for LLMs (i.e., LLMOps).…

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Demonstrate–Search–Predict Framework | Data Brew | Episode 32 33:14

2 years geleden33:14

33:14

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.…

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34:38

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John Snow Labs & SparkNLP | Data Brew | Episode 30 43:17

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43:17

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Data Brew Season 4 Episode 6: Professional Athletes 35:49

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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 and how they combine their passion for sports with the Dreamcatcher Foundation. See more at databricks.com/data-brew…

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Data Brew Season 4 Episode 5: Public Health: Education, Access, and Policy 34:39

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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 databricks.com/data-brew…

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Data Brew Season 4 Episode 4: 1283 Days of Running (and Counting) 35:54

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35:54

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Data Brew Season 4 Episode 3: Last Man Standing 41:20

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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-brew…

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Data Brew Season 4 Episode 2: NBA Analytics 30:16

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30:16

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Data Brew Season 4 Episode 1: Reducing Injury & Increasing Retention of Industrial Athletes 33:58

3 years geleden33:58

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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 devices to reduce workplace injury and increase retention of industrial athletes. See more at databricks.com/data-brew…

Data Brew by Databricks

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Data Brew Season 3 Episode 6: Open Source 33:49

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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 can balance community and company interests. With 95% of open-source contributions coming from men, Nithya also educates us on how to improve diversity & inclusion in the open-source community. See more at databricks.com/data-brew…

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Data Brew Season 3 Episode 5: Sustainability & Sake 32:26

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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, economic, and tactical approaches to sustainability and ESG, as well as the secrets to brewing sake in the US. See more at databricks.com/data-brew…

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Data Brew Season 3 Episode 4: Executive Education 38:46

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Data Brew Season 3 Episode 3: 3 T’s to Securing AI Systems: Tests, tests, and more tests 35:01

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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 systems ready for the real world in this episode of Data Brew. See more at databricks.com/data-brew…

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Data Brew Season 3 Episode 2: Data Culture Outside ‘The Valley’ 35:39

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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-Mobile alone! In this episode, we have the pleasure to chat with Charles Morgan and Kent Welch, CEO and CDO, respectively, of First Orion to discuss Arkansan data culture, First Orion’s one hundred day program, and team culture. See more at databricks.com/data-brew…

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Data Brew Season 3 Episode 1: Disrupt: Challenge your Business Assumptions 29:45

4 years geleden29:45

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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 how to build companies that scale, manage corporate cultural evolution, and the influence of corporate boards. See more at databricks.com/data-brew…

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Data Brew Season 2 Episode 9: Data Driven Software 31:12

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Data Brew by Databricks

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Data Brew Season 2 Episode 8: Feature Engineering 31:17

4 years geleden31:17

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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 Zheng, co-authors of the Feature Engineering for Machine Learning book. See more at databricks.com/data-brew…

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Data Brew Season 2 Episode 7: Interpretable Machine Learning 37:07

4 years geleden37:07

37:07

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 Learning), how it relates to data privacy and fairness, and his research in this field. See more at databricks.com/data-brew…

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Data Brew Season 2 Episode 6: AutoML 35:55

4 years geleden35:55

35:55

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 thoughts on the future of AutoML. We also discuss founding and growing the Women in Machine Learning and Data Science (WiMLDS) non-profit. See more at databricks.com/data-brew…

Data Brew by Databricks

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Data Brew Season 2 Episode 5: ML Applications 32:40

4 years geleden32:40

32:40

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-fidelity data, developing custom metrics to satisfy business needs, and discusses how to improve internal decision making processes. See more at databricks.com/data-brew…

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1
Data Brew Season 2 Episode 4: Hyperparameter and Neural Architecture Search 33:25

4 years geleden33:25

33:25

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 author of the seminal Hyperband paper. In this session, Liam discusses the evolution of hyperparameter optimization techniques and illustrates how every data scientist can benefit from neural architecture search. See more at databricks.com/data-brew…

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1
Data Brew Season 2 Episode 3: Infrastructure for ML 30:34

4 years geleden30:34

30:34

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 importance of iteration, and centralized vs decentralized data science teams. He provides valuable advice for companies investing in ML and crucial lessons he’s learned from founding two companies. See more at databricks.com/data-brew…

Data Brew by Databricks

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Data Brew Season 2 Episode 2: Data Ethics 25:47

4 years geleden25:47

25:47

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 play a role in combating bias? We discuss with Diana Pfeil recommendations to reduce bias and improve fairness, from SHAP to adversarial debiasing. See more at databricks.com/data-brew…

Data Brew by Databricks

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Data Brew Season 2 Episode 1: ML in Production 30:49

4 years geleden30:49

30:49

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, leveraging MLflow & the Lakehouse architecture for reproducible ML, and his current research in this field. See more at databricks.com/data-brew…

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1
Data Brew Season 1 Episode 6: Journey of Big Data 40:16

4 years geleden40:16

40:16

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…

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Data Brew Season 1 Episode 5: Combining Machine Learning and MLflow with your Lakehouse 36:00

4 years geleden36:00

36:00

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 by Databricks

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Data Brew Season 1 Episode 4: BI on Data Lakes - Making it Real for Retail 29:05

4 years geleden29:05

29:05

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 business, to a single scalable, reliable, performant data lake. See more at databricks.com/data-brew…

Data Brew by Databricks

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Data Brew Season 1 Episode 3: Demystifying Delta Lake 25:51

4 years geleden25:51

25:51

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 Spark™ and the original creator of Spark SQL. He currently leads the team at Databricks that designed and built Structured Streaming and Delta Lake. See more at databricks.com/data-brew…

Data Brew by Databricks

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Data Brew Season 1 Episode 2: Welcome to Lakehouse 26:10

4 years geleden26:10

26:10

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 by Databricks

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Data Brew Season 1 Episode 1: From data warehousing to data lakes in 40 minutes 44:48

4 years geleden44:48

44:48

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

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Demonstrate–Search–Predict Framework | Data Brew | Episode 32