January 2024 – Page 2 – Andrew Fairless, Ph.D.

What I Read: Compiling NumPy

By Andrew Fairless on January 10, 2024November 7, 2023

https://pytorch.org/blog/compiling-numpy-code/ Compiling NumPy code into C++ or CUDA via torch.compileby Evgeni Burovski, Ralf Gommers and Mario LezcanoOctober 17, 2023 “This feature leverages PyTorch’s compiler to generate efficient fused vectorized codeContinue readingWhat I Read: Compiling NumPy

What I Read: Neural algorithmic reasoning

By Andrew Fairless on January 9, 2024November 7, 2023

https://thegradient.pub/neural-algorithmic-reasoning/ Neural algorithmic reasoningPetar Veličković14.Oct.2023 “…we will talk about classical computation… Think shortest path-finding, sorting, clever ways to break problems down… we will also investigate how to capture such computationContinue readingWhat I Read: Neural algorithmic reasoning

What I Read: SAT Solvers

By Andrew Fairless on January 8, 2024November 7, 2023

https://www.borealisai.com/research-blogs/tutorial-9-sat-solvers-i-introduction-and-applications/ Tutorial #9: SAT Solvers I: Introduction and applicationsS. PrinceNov. 10, 2020 “This tutorial concerns the Boolean satisfiability or SAT problem…. we’ll show how to fit both neural networks andContinue readingWhat I Read: SAT Solvers

What I Read: Multimodality

By Andrew Fairless on January 4, 2024November 7, 2023

https://huyenchip.com/2023/10/10/multimodal.html Multimodality and Large Multimodal Models (LMMs)Chip HuyenOct 10, 2023 “For a long time, each ML model operated in one data mode… However, natural intelligence is not limited to justContinue readingWhat I Read: Multimodality

What I Read: Finetuning LLMs with LoRA and QLoRA

By Andrew Fairless on January 3, 2024November 7, 2023

Finetuning LLMs with LoRA and QLoRA: Insights from Hundreds of Experiments Finetuning LLMs with LoRA and QLoRA: Insights from Hundreds of ExperimentsSebastian RaschkaOctober 12, 2023 “LoRA is one of theContinue readingWhat I Read: Finetuning LLMs with LoRA and QLoRA

Month: January 2024