The Stanford AI Lab Blog

APRIL 25, 2022

We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that’s happening at Stanford!

Neural Network 40

Neural Network Robotics Continuous Learning AI 40

The Stanford AI Lab Blog

DECEMBER 6, 2021

We’re excited to share all the work from SAIL that’s being presented at the main conference , at the Datasets and Benchmarks track and the various workshops , and you’ll find links to papers, videos and blogs below. Smith, Scott W.

Neural Network 40

Neural Network Deep Learning Machine Learning AI 40

Mlearning.ai

MARCH 2, 2023

This blog post promises to be easier to understand than the underlying research paper, especially for readers not that familiar with the field. In the ablation studies, the authors can demonstrate that this approach yields performance improvements over classical ones.

BERT 52

BERT NLP Deep Learning Neural Network 52

Sebastian Ruder

JANUARY 24, 2022

Consequently, 2021 saw much discussion of best practices and ways in which we can reliably evaluate such models going forward, which I cover in this blog post. An art scene emerged around the most recent generation of generative models (see this blog post for an overview). von Arx, S., … Liang, P. H., … Zhang, Y.

NLP 52

NLP ML BERT Computational Linguistics 52

deepsense.ai

FEBRUARY 28, 2024

Apart from implementing the models, the authors of llama.cpp came up with their own quantization algorithm, called k-quants and often referred to as GGUF (after the format in which llama.cpp models are served). If you want to know more about the topic, feel free to check out our previous blog post.

Generative AI 88

Generative AI LLM Neural Network Algorithm 88