Artwork

Player FM - Internet Radio Done Right

71 subscribers

Checked 9d ago
Đã thêm cách đây bốn năm
Nội dung được cung cấp bởi Databricks. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Databricks hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.
Player FM - Ứng dụng Podcast
Chuyển sang chế độ ngoại tuyến với ứng dụng Player FM !
icon Daily Deals

Data Brew Season 2 Episode 2: Data Ethics

25:47
 
Chia sẻ
 

Manage episode 291217673 series 2814833
Nội dung được cung cấp bởi Databricks. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Databricks hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.

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

  continue reading

39 tập

Artwork

Data Brew Season 2 Episode 2: Data Ethics

Data Brew by Databricks

71 subscribers

published

iconChia sẻ
 
Manage episode 291217673 series 2814833
Nội dung được cung cấp bởi Databricks. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Databricks hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.

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

  continue reading

39 tập

Tất cả các tập

×
 
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.…
 
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 Optimization (DPO) for enhancing response quality. - The role of reward models in improving coding, math, reasoning, and other NLP tasks. Connect with Brandon Cui: https://www.linkedin.com/in/bcui19/…
 
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.…
 
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. - Addressing licensing and legal considerations in synthetic data usage. - Unlocking private datasets for broader and safer AI applications.…
 
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. - Lessons from large-scale AI deployments on scalability and feedback loops. - Automating workflows with AI through successful business examples. - Best practices for managing AI pipelines, from data collection to validation.…
 
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/…
 
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.…
 
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.…
 
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).…
 
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.…
 
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 discuss generative AI, the trends toward embracing LLMs, and how the surface area for vulnerabilities in generative AI is much bigger.…
 
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 artificial intelligence in healthcare, and responsible AI.…
 
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…
 
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…
 
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…
 
Loading …

Chào mừng bạn đến với Player FM!

Player FM đang quét trang web để tìm các podcast chất lượng cao cho bạn thưởng thức ngay bây giờ. Đây là ứng dụng podcast tốt nhất và hoạt động trên Android, iPhone và web. Đăng ký để đồng bộ các theo dõi trên tất cả thiết bị.

 

icon Daily Deals
icon Daily Deals
icon Daily Deals

Hướng dẫn sử dụng nhanh

Nghe chương trình này trong khi bạn khám phá
Nghe