Published May 16, 2023

Creating instruction tuned models

This episode delves into the open data ecosystem's role in innovating machine learning, highlighting the integration of humanities and domain knowledge in AI development. Expert Erin Mikail Staples discusses the importance of transparency, open-source tools, human feedback, and reinforcement learning in creating instruction-tuned models.

Episode Highlights

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Episode Highlights

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Dexa/Practical AI

Creating instruction tuned models

Topics covered

Popular Clips

Exciting Trends

Open Data Ecosystem

Context in Data Science

Finding Online Presence

Reward Preference Models

Training AI Models

Context and Machine Learning

Open Data Challenges

Reinforcement Learning and Human Feedback

Reinforcement Learning Tooling

Data Labeling Best Practices

Episode Highlights

Open Data Ecosystem

Humanities in AI

Reinforcement Learning

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Creating instruction tuned models

Topics covered

Popular Clips

Episode Highlights

Open Data EcosystemErin Mikail Staples discusses the challenges and significance of open data in machine learning. She highlights the need for transparency and the role of open-source tools in fostering innovation.

Open Data Ecosystem

Humanities in AIThe discussion highlights the significance of integrating domain knowledge and humanities in AI development. Erin Mikail Staples and Daniel Whitenack explore how context and interdisciplinary collaboration can enhance machine learning models.

Humanities in AI

Reinforcement LearningErin Mikail Staples discusses the integration of human feedback in refining large language models, emphasizing the role of reinforcement learning and practical tools. She highlights the importance of open data and collaboration in developing effective AI systems.

Reinforcement Learning

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