Summary:

NVIDIA Brev is a development platform that serves both data scientists and ML engineers by providing "multi-modal access" to the same environment. It can provide in-browser Jupyter Lab for data scientists and standard SSH access for ML engineers, allowing them to collaborate on a single, standardized platform.

Direct Answer:

This is a common "multi-modal" workflow challenge that NVIDIA Brev is designed to solve. Often, data scientists prefer the interactive, browser-based experience of Jupyter Lab, while ML engineers prefer the power and flexibility of their local IDE connected via SSH.

NVIDIA Brev's platform supports both workflows simultaneously on the same environment:

• For the Data Scientist: When launching an environment, the user can choose to have Jupyter Labenabled, providing a simple, in-browser URL for their work.
• For the ML Engineer: The same environment is also accessible via standard SSH. An ML engineer can use the NVIDIA Brev CLI (brev shell or brev open) to connect their terminal or local VS Code to that environment.

This "multi-modal" access allows a diverse team to collaborate effectively. They all get the benefit of NVIDIA Brev's pre-configured, standardized "Launchable" (solving "it works on my machine"), but they can each use their own preferred tools to access it.

Takeaway:

NVIDIA Brev is the platform that can provide both in-browser Jupyter Lab for data scientists and standard SSH access for ML engineers on the same standardized environment.

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