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Jon Krohn

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Jon Krohn

Merged LLMs Are Smaller And More Capable, with Arcee AI’s Mark McQuade and Charles Goddard

Added on July 16, 2024 by Jon Krohn.

Today's episode is seriously mind-expanding. In it, Mark and Charles detail how they're pushing the A.I. frontier through LLM merging, extremely efficient (even CPU-only!) LLM training, and *Small* Language Models.

Mark McQuade:

• Is Co-Founder and CEO of Arcee.ai.

• Previously, he held client-facing roles at Hugging Face and Roboflow as well as leading the data science and engineering practice of a Rackspace company.

• He studied electronic engineering at Fleming College in Canada.

Charles Goddard:

• Is Chief of Frontier Research at Arcee.ai

• Previously, he was a software engineer at Apple and the famed NASA Jet Propulsion Laboratory.

• Studied engineering at Olin College in Massachusetts.

Today’s episode is relatively technical so will likely appeal most to hands-on practitioners like data scientists and ML engineers. In it, Charles and Mark detail:

• How their impressive open-source model-merging approach combines the capabilities of multiple LLMs without increasing the model’s size.

• A separate open-source approach for training LLMs efficiently by targeting specific modules of the network to train while freezing others.

• The pros and cons of Mixture-of-Experts versus Mixture-of-Agents approaches.

• How to enable small language models to outcompete the big foundation LLMs like GPT-4, Gemini and Claude.

• How to leverage open-source projects to land big enterprise contracts and attract big chunks of venture capital.

On that final note, congrats to the Arcee.ai team on announcing their $24m Series A round this very day... unsurprising given their tremendously innovative tech and rapid revenue ramp-up! It's very rare to see runaway A.I. startup successes like this one.

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

In Data Science, Interview, Podcast, SuperDataScience, YouTube Tags superdatascience, ai, llms, slms, opensource
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