neural network – Page 4 – Andrew Fairless, Ph.D.

What I Read: diffusion distillation

By Andrew Fairless on May 13, 2024March 11, 2024

https://sander.ai/2024/02/28/paradox.html The paradox of diffusion distillationSander DielemanFebruary 28, 2024 “…let’s take a closer look at the various ways in which the number of sampling steps required to get good resultsContinue readingWhat I Read: diffusion distillation

What I Read: Mamba, Easy Way

By Andrew Fairless on May 9, 2024March 7, 2024

https://jackcook.com/2024/02/23/mamba.html Mamba: The Easy WayJack CookFebruary 23, 2024 “Mamba appears to outperform similarly-sized Transformers while scaling linearly with sequence length…. If… you’re looking for a higher-level overview of Mamba’s bigContinue readingWhat I Read: Mamba, Easy Way

What I Read: Mamba

By Andrew Fairless on May 1, 2024March 7, 2024

https://jameschen.io/jekyll/update/2024/02/12/mamba.html Mamba No. 5 (A Little Bit Of…)James ChenFeb 12, 2024 “…I attempt to provide a walkthrough of the essence of the Mamba state space model architecture, occasionally sacrificing someContinue readingWhat I Read: Mamba

What I Read: Structured State Space Sequence Models

By Andrew Fairless on April 30, 2024March 7, 2024

https://cnichkawde.github.io/statespacesequencemodels.html Beyond Transformers: Structured State Space Sequence ModelsChetan NichkawdeJanuary 22, 2024 “A new paradigm is rapidly evolving within the realm of sequence modeling that presents a marked advancement over theContinue readingWhat I Read: Structured State Space Sequence Models

What I Read: Forgetting Can Help AI Learn

By Andrew Fairless on April 29, 2024March 1, 2024

https://www.quantamagazine.org/how-selective-forgetting-can-help-ai-learn-better-20240228/ How Selective Forgetting Can Help AI Learn BetterAmos Zeeberg2/28/24 10:38 AM “Erasing key information during training results in machine learning models that can learn new languages faster and moreContinue readingWhat I Read: Forgetting Can Help AI Learn

What I Read: Scaling ChatGPT, Engineering Challenges

By Andrew Fairless on April 18, 2024March 1, 2024

https://newsletter.pragmaticengineer.com/p/scaling-chatgpt Scaling ChatGPT: Five Real-World Engineering ChallengesGergely OroszFeb 20, 2024 “Just one year after its launch, ChatGPT had more than 100M weekly users. In order to meet this explosive demand,Continue readingWhat I Read: Scaling ChatGPT, Engineering Challenges

What I Read: High-Quality Human Data

By Andrew Fairless on April 17, 2024March 1, 2024

https://lilianweng.github.io/posts/2024-02-05-human-data-quality/Thinking about High-Quality Human DataLilian WengFebruary 5, 2024 “High-quality data is the fuel for modern data deep learning model training.”

What I Read: How Quickly LLMs Learn Skills?

By Andrew Fairless on April 10, 2024March 1, 2024

How Quickly Do Large Language Models Learn Unexpected Skills?Stephen Ornes2/13/24 10:32 AM “A new study suggests that so-called emergent abilities actually develop gradually and predictably, depending on how you measureContinue readingWhat I Read: How Quickly LLMs Learn Skills?

What I Read: LoRA from Scratch

By Andrew Fairless on April 4, 2024March 1, 2024

https://lightning.ai/lightning-ai/studios/code-lora-from-scratch Code LoRA from ScratchSebastian Raschka “LoRA, which stands for Low-Rank Adaptation, is a popular technique to finetune LLMs more efficiently,,,. This Studio explains how LoRA works by coding itContinue readingWhat I Read: LoRA from Scratch

What I Read: Artificial, Biological Intelligence

By Andrew Fairless on April 1, 2024March 1, 2024

https://medium.com/@begus.gasper/artificial-and-biological-intelligence-humans-animals-and-machines-142bc3c4b304 Artificial and Biological Intelligence: Humans, Animals, and MachinesGasper BegusSep 19, 2023 “…a highly promising direction in AI research is to use artificial intelligence to better understand biological intelligence, andContinue readingWhat I Read: Artificial, Biological Intelligence

Tag: neural network