Open source AI models have become key drivers of innovation and collaboration. An increasing number of developers and end users are leveraging open source technologies. There is immense potential in the long-term impact of open source AI.

In this episode, we are releasing a conversation on the future of open source AI between Wei Lien Dang (Unusual Ventures), and Reynold Xin (Databricks) and Vipul Ved Prakash (Together).

Join us as we discuss:
3:16: The rise of open source LLMs and foundation models

7:23 Building open source AI platforms to serve customers

10:35 Why Together and Databricks decided to build with open source

13:33 LLMs and the need for standardization

21:09 The role of academia in AI research and innovation

26:57 Innovations in training data

30:55 Making the decision to choose open source models

36:52 Growing Accessibility of Machine Learning with LLMs

40:31 How the open source ecosystem will evolve in the future

47:18 Best practices for parameterizing LLMs over time
Wei Lien Dang is a General Partner at Unusual Ventures and leads investments in infrastructure software, security, and developer tool. Wei was a co-founder of StackRox, a cloud-native security company prior to its acquisition by Red Hat. He can be reached at wei@unusual.vc and

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Vipul Ved Prakash is the co-founder and CEO of Together. He was also the founder of Topsy and Cloudmark.

Reynold Xin is the co-founder of Databricks. Last valued at $43B, Databricks has been a juggernaut data infrastructure business built on Apache Spark analytics engine. They recently launched multiple AI products including Lakehouse AI and their own open source LLM — Dolly.

Unusual Ventures is a seed-stage venture capital firm designed from the ground up to give a distinct advantage to founders building the next generation of software companies. Unusual has invested in category-defining companies like Webflow, Arctic Wolf Networks, Carta, Robinhood, and Harness. Learn more about us at https://www.unusual.vc/.
Further reading from Unusual Ventures:

Why the future of AI-native infrastructure will be open

How good is your LLM? Nobody know yet

What AI builders should know about data protection and privacy

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