Learning to code can be a valuable skill, even for those without a traditional computer science background.

"A lot of people are always kind of like, do you know how to code?"

Data analysis and quantitative skills can be applied in various industries, including finance and technology.

"I actually learned Python there. I wrote my own data pipelines there before Airflow was a thing."

Building data infrastructure is crucial for training large language models and making them scalable.

"A lot of the work originally just went into building data infrastructure, like modernizing the data infrastructure in a way where you can answer questions like that, where you can pull in data from any particular Reple to process, to make available for search and moving all of that data into a format where you can do all of this in minutes."

The vibe test is an essential aspect of evaluating large language models, focusing on the model's 'feel' and overall user experience.

"It really kind of depends on like how snappy the completion is, what the latency feels like."

Collaboration between teams and open-source projects can lead to significant advancements in technology.

"We leaned heavily on open source and our friends at Salesforce obviously were huge in that in developing these models."