The Importance of Reproducibility and Data Provenance

Hugo speaks with Omoju Miller, a machine learning guru and founder and CEO of Fimio, where she is building 21st century dev tooling. In the past, she was Technical Advisor to the CEO at GitHub, spent time co-leading non-profit investment in Computer Science Education for Google, and served as a volunteer advisor to the Obama administration’s White House Presidential Innovation Fellows.

We need open tools, open data, provenance, and the ability to build fully reproducible, transparent machine learning workflows. With the advent of closed-source, vendor-based APIs and compute becoming a form of gate-keeping, developer tools are at the risk of becoming commoditized and developers becoming consumers.

We’ll talk about how ideas for escaping these burgeoning walled gardens. We’ll dive into

• What fully reproducible ML workflows would look like, including git for the workflow build process,
• The need for loosely coupled and composable tools that embrace a UNIX-like philosophy,
• What a much more scientific toolchain would look like,
• What a future open sources commons for Generative AI could look like,
• What an open compute ecosystem could look like,
• How to create LLMs and tooling so everyone can use them to build production-ready apps,

And much more!

LINKS

• The livestream on YouTube
• Omoju on Twitter
• Hugo on Twitter
• Vanishing Gradients on Twitter
• Lu.ma Calendar that includes details of Hugo's European Tour for Outerbounds
• Blog post that includes details of Hugo's European Tour for Outerbounds