ОБ ЭТОМ ЭПИЗОДЕ
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/
английский
США
РАСШИФРОВКА 🔗
Are you the producer of this podcast?
Add a podcast transcript
Need Audio-to-Text?
Transcribe with Listen411 in Just 60 Seconds
ПОИСК ПРОШЛЫХ ЭПИЗОДОВ
Искать прошлые эпизоды Data Brew by Databricks.
ДРУГИЕ ЭПИЗОДЫ В ЭТОМ ПОДКАсте
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 ethica…
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 effecti…
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 re…
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-t…
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 enha…
Отказ от ответственности: Подкаст и иллюстрации, встроенные в эту страницу, взяты из Databricks, который является собственностью его владельца и не связан или не одобрен Listen Notes, Inc.
ИЗМЕНИТЬ
Спасибо, что помогаете поддерживать базу подкастов актуальной.
