Chris Alexiuk has a simple rule about open source AI: If you believe in it, be loud about it.

“We should be shouting about this technology from the rooftops,” said Alexiuk, a Toronto-based senior product research engineer in deep learning at NVIDIA who specializes in making open large language models (LLMs) practical for working developers.

Alexiuk’s preferred “rooftop” is YouTube, where he’s built a following teaching curious thousands how to build, fine-tune, evaluate and ship production LLM applications and agents.

“I think the people who will most help us understand how to build and apply AI likely haven’t even heard of it yet,” he said. “Trying to get knowledge and information out to as many people as humanly possible is what continues to drive me.”

Having spent years teaching developers to build with open models, Alexiuk has concluded that transparency isn’t a feature of good AI; it’s the precondition for it.

“Fully open source AI is necessary for the democratization of intelligence,” he said. “You should have access to the weights, the data that went into it, the training recipes, everything.”

That’s why, on his LinkedIn profile, Alexiuk styles himself “No. 1 Nemotron Fan,” referring to the NVIDIA Nemotron family of open source, multimodal models built for long-running, self-evolving and specialized AI agents.

“I think Nemotron is the most important project that exists,” said Alexiuk, who also uses the pseudonym “Joe Nemotron” across social media. “I’m a firm believer that openness is a very important thing to undertake, so I’m going to be the No.

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