This article covers three new papers related to instruction finetuning and parameter-efficient finetuning with LoRA in large language models (LLMs). I work…
This is an overview of the LLM development process. This one-hour talk focuses on the essential three stages of developing an LLM: coding the architecture…
What a month! We had four major open LLM releases: Mixtral, Meta AI’s Llama 3, Microsoft’s Phi-3, and Apple’s OpenELM. In my new article, I review and…
The AI revolution drove frenzied investment in both private and public companies and captured the public’s imagination in 2023. Transformational consumer products like ChatGPT are powered by Large Language Models (LLMs) that excel at modeling sequences of tokens that represent words or parts of words [2]. Amazingly, structural
What are the different ways to use and finetune pretrained large language models (LLMs)? The three most common ways to use and finetune pretrained LLMs…
It’s another month in AI research, and it’s hard to pick favorites. This month, I am going over a paper that discusses strategies for the continued…
Exploring the utility of large language models in autonomous driving: Can they be trusted for self-driving cars, and what are the key challenges?
‘Vec2text’ can serve as a solution for accurately reverting embeddings back into text, thus highlighting the urgent need for revisiting security protocols around embedded data.
Once again, this has been an exciting month in AI research. This month, I’m covering two new openly available LLMs, insights into small finetuned LLMs, and…
Low-rank adaptation (LoRA) is a machine learning technique that modifies a pretrained model (for example, an LLM or vision transformer) to better suit a…