Vicuña, Gorilla, Chatbot Arena and Socially Beneficial LLMs, with Prof. Joey Gonzalez

Data Science

Vicuna, Gorilla and the Chatbot Arena are all critical elements of the new open-source LLM ecosystem — the extremely knowledgeable and innovative Prof. Joseph Gonzalez is behind all of them. Get the details in this SuperDataScience episode hosted by our Chief Data Scientist, Jon Krohn.

• Is an Associate Professor of Electrical Engineering and Computer Science at the University of California, Berkeley.
• Co-directs the Berkeley RISE Lab, which studies Real-time, Intelligent, Secure and Explainable systems.
• Co-founded Turi (acquired by Apple for $200m) and more recently Aqueduct.
• His research is integral to major software systems including Apache Spark, Ray (for scaling Python ML), GraphLab (a high-level interface for distributed ML) and Clipper (low-latency ML serving).
• His papers—published in top ML journals—have been cited over 24,000 times.
• Developed Berkeley’s upper-division data science class, which he now teaches to over 1000 students per semester.

This episode will probably appeal primarily to hands-on data science practitioners but we made an effort to break down technical terms so that anyone who’s interested in staying on top of the latest in open-source Generative A.I. can enjoy the episode.

In it, Prof. Gonzalez details:
• How his headline-grabbing LLM, Vicuña, came to be and how it arose as one of the leading open-source alternatives to ChatGPT.
• How his Chatbot Arena became the leading proving ground for commercial and open-source LLMs alike.
• How his Gorilla project enables open-source LLMs to call APIs making it an open-source alternative to ChatGPT’s powerful plugin functionality.
• The race for longer LLM context windows.
• How both proprietary and open-source LLMs will thrive alongside each other in the coming years.
• His vision for how A.I. will have a massive, positive societal impact over the coming decades.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at


Getting Value From A.I.

In February 2023, our Chief Data Scientist, Jon Krohn, delivered this keynote on “Getting Value from A.I.” to open the second day of Hg Capital’s “Digital Forum” in London.

read full post

The Chinchilla Scaling Laws

The Chinchilla Scaling Laws dictate the amount of training data needed to optimally train a Large Language Model (LLM) of a given size. For Five-Minute Friday, our Chief Data Scientist, Jon Krohn, covers this ratio and the LLMs that have arisen from it.

read full post

StableLM: Open-Source “ChatGPT”-Like LLMs You Can Fit on One GPU

The folks who open-sourced Stable Diffusion have now released “StableLM”, their first Language Models. Pre-trained on an unprecedented amount of data for single-GPU LLMs (1.5 trillion tokens!), these are small but mighty.

read full post