Jonathan Frankle is the Chief AI Scientist at Databricks ($43B), which he joined through the acquisition of MosaicML in July 2023. Databricks has over 12,000 customers on the cutting edge of AI; Jonathan works to anticipate their needs and offer solutions even as the tech is rapidly evolving.

[0:00] Intro

[0:52] Incentives and Team Motivation at Databricks

[2:40] The Evolution of AI Models: Transformers vs. LSTMs

[5:27] Mosaic and Databricks: A Strategic Merger

[7:31] Guidance on AI Model Training and Fine-Tuning

[11:11] Building Effective AI Evaluations

[16:02] Domain-Specific AI Models and Their Importance

[19:37] The Future of AI: Challenges and Opportunities

[25:07] Ethical Considerations and Human-AI Interaction

[29:13] Customer Collaboration and AI Implementation

[30:45] Navigating AI Tools and Techniques

[35:41] The Role of Open Source Models

[36:46] AI Infrastructure and Partnerships

[48:27] Academia's Role in AI Research

[52:09] Ethics and Policy in AI

[57:47] Quickfire

With your co-hosts:

@jacobeffron

- Partner at Redpoint, Former PM Flatiron Health

@patrickachase

- Partner at Redpoint, Former ML Engineer LinkedIn

@ericabrescia

- Former COO Github, Founder Bitnami (acq’d by VMWare)

@jordan_segall

- Partner at Redpoint

Ep 47: Chief AI Scientist of Databricks Jonathan Frankle on Why New Model Architectures are Unlikely, When to Pre-Train or Fine Tune, and Hopes for Future AI Policy 01:04:25 Share

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Ep 47: Chief AI Scientist of Databricks Jonathan Frankle on Why New Model Architectures are Unlikely, When to Pre-Train or Fine Tune, and Hopes for Future AI Policy