https://www.aidancooper.co.uk/how-to-beat-proprietary-llms How to Beat Proprietary LLMs With Smaller Open Source ModelsAidan CooperApr 26, 2024 “…we explore the unique advantages of open source LLMs, and how you can leverage them to
What I Read: LLM Chatbots, Browser
https://www.kdnuggets.com/2023/05/webllm-bring-llm-chatbots-browser.html Web LLM: Bring LLM Chatbots to the BrowserBala Priya CMay 22, 2023 “Wouldn’t it be cool if you can run LLMs and LLM chatbots natively in your browser?”
What I Read: Dataset Distillation
https://ai.googleblog.com/2021/12/training-machine-learning-models-more.html Training Machine Learning Models More Efficiently with Dataset DistillationWednesday, December 15, 2021Posted by Timothy Nguyen1, Research Engineer and Jaehoon Lee, Senior Research Scientist, Google Research“For a machine learning (ML)
What I Read: Why Deep Learning Works
https://moultano.wordpress.com/2020/10/18/why-deep-learning-works-even-though-it-shouldnt/ Why Deep Learning Works Even Though It Shouldn’tRyan Moulton’s ArticlesRyan Moulton “Stop talking about minima…. Nobody ever trains their model remotely close to convergence…. What really needs further research
What I Read: Do Wide and Deep Networks Learn the Same Things?
https://ai.googleblog.com/2021/05/do-wide-and-deep-networks-learn-same.html Do Wide and Deep Networks Learn the Same Things?Tuesday, May 4, 2021Posted by Thao Nguyen, AI Resident, Google Research
What I Read: Ensemble, knowledge distillation, and self-distillation
https://www.microsoft.com/en-us/research/blog/three-mysteries-in-deep-learning-ensemble-knowledge-distillation-and-self-distillation/ Three mysteries in deep learning: Ensemble, knowledge distillation, and self-distillationPublished January 19, 2021By Zeyuan Allen-Zhu , Senior Researcher Yuanzhi Li , Assistant Professor, Carnegie Mellon University “…besides this small