Carnegie Mellon University

The L3 Lab course at Carnegie Mellon University (CMU) is an advanced study area combining Machine Learning, Language, and Logic. Key components of the course include:

1. Principles of Machine Learning for Language: This aspect delves into the core principles of applying machine learning to language processing. It encompasses both theoretical foundations and practical applications, involving coding and mathematical concepts essential for understanding and developing language models.
2. Machine Learning for High-Trust Applications: This module focuses on the use of machine learning in contexts where trust and reliability are paramount. This includes the verification of mathematical proofs and software, ensuring that machine learning applications are robust, secure, and reliable, particularly in critical environments.
3. Enabling Self-Improving Machine Learning Systems: The course also emphasizes the development of machine learning systems that are capable of discovering new knowledge and improving autonomously over time. This includes techniques and methodologies for creating systems that can adapt, learn from new data, and evolve their capabilities without human intervention.

Overall, the L3 Lab at CMU offers a comprehensive and interdisciplinary approach to understanding and advancing the field of machine learning, especially in its application to language and logic in high-stakes scenarios.
Take at look at the link here: https://cmu-l3.github.io

Inflection

https://inflection.ai/company

AVA PLS

https://avapls.com

LANGCHAIN Blog

https://blog.langchain.dev/testing-fine-tuned-open-source-models-in-langsmith/

Brev.dev

Brev is a dev tool that makes it really easy to code on a GPU in the cloud. Brev does 3 things: provision, configure, and connect.
https://github.com/brevdev/notebooks

Hands On Train and Deploy ML

https://github.com/Paulescu/hands-on-train-and-deploy-ml