Andrew Fairless – Page 18 – Andrew Fairless, Ph.D.

What I Read: SciPy builds for Python 3.12

By Andrew Fairless on January 25, 2024November 20, 2023

https://labs.quansight.org/blog/building-scipy-with-flang The ‘eu’ in eucatastrophe – Why SciPy builds for Python 3.12 on Windows are a minor miracleAxel ObermeierPublished November 8, 2023 “…behind the ordinary-seeming “SciPy released builds compatible withContinue readingWhat I Read: SciPy builds for Python 3.12

What I Read: Density Kernel Depth for Outlier Detection

By Andrew Fairless on January 24, 2024November 20, 2023

https://www.kdnuggets.com/density-kernel-depth-for-outlier-detection-in-functional-data Density Kernel Depth for Outlier Detection in Functional DataKulbir SinghNovember 8, 2023 “The Density Kernel Depth (DKD) method provides a nuanced approach to detect outliers in functional data…”

What I Read: Helping AI See

By Andrew Fairless on January 23, 2024November 20, 2023

https://www.quantamagazine.org/the-computing-pioneer-helping-ai-see-20231024/ The Computing Pioneer Helping AI SeeSusan D’AgostinoOctober 24, 2023 ““Patches of color and brightness require us to connect what we’re seeing now to our memory…”… machines see what isContinue readingWhat I Read: Helping AI See

What I Read: Unify Batch and ML Systems

By Andrew Fairless on January 18, 2024November 7, 2023

https://www.kdnuggets.com/2023/09/hopsworks-unify-batch-ml-systems-feature-training-inference-pipelines Unify Batch and ML Systems with Feature/Training/Inference PipelinesBy Jim Dowling, Co-Founder & CEO, HopsworksSeptember 27, 2023 “This article introduces a unified architectural pattern for building both Batch and Real-TimeContinue readingWhat I Read: Unify Batch and ML Systems

What I Read: vectorize wide PyTorch expressions

By Andrew Fairless on January 16, 2024November 7, 2023

https://probablymarcus.com/blocks/2023/10/19/vectorizing-wide-pytorch-expressions.html What happens when you vectorize wide PyTorch expressions?Marcus Lewis19 October 2023 “So we see that vectorization has three effects:It lets us keep the GPU busy even when inputs areContinue readingWhat I Read: vectorize wide PyTorch expressions

What I Read: GPU Computing

By Andrew Fairless on January 15, 2024November 7, 2023

https://codeconfessions.substack.com/p/gpu-computing What Every Developer Should Know About GPU ComputingAbhinav UpadhyayOct 18, 2023 “GPUs have become incredibly important because of their pervasive use in deep learning. Today, it is essential forContinue readingWhat I Read: GPU Computing

What I Read: Enterprise AI, RAG + Fine Tuning

By Andrew Fairless on January 11, 2024November 20, 2023

https://www.montecarlodata.com/blog-the-moat-for-enterprise-ai-is-rag-fine-tuning/ The Moat for Enterprise AI is RAG + Fine Tuning – Here’s WhyLior GavishUpdated Nov 09 2023 “Data needs to be secure and private; LLM deployment needs to beContinue readingWhat I Read: Enterprise AI, RAG + Fine Tuning

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

Author: Andrew Fairless