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Improving LLM Inference Speeds on CPUs with Model Quantization | by Eduardo Alvarez | Feb, 2024

Image Property of Author — Create with NightcafeDiscover how to significantly improve inference latency on CPUs using quantization techniques for mixed, int8, and int4 precisions One of the most significant challenges the AI space faces is the need for computing resources to host large-scale production-grade LLM-based applications. At scale, LLM applications require redundancy, scalability, and…

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Streamlining Giants. The Evolution of Model Compression in… | by Nate Cibik | Feb, 2024

The quest to refine neural networks for practical applications traces its roots back to the foundational days of the field. When Rumelhart, Hinton, and Williams first demonstrated how to use the backpropagation algorithm to successfully train multi-layer neural networks that could learn complex, non-linear representations in 1986, the vast potential of these models became apparent.…

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Tracking The Great Salt Lake’s Shrinkage Using Satellite Images (Python) | by Mahyar Aboutalebi, Ph.D. 🎓 | Feb, 2024

Analyzing Landsat-8 imagery (2014–2023) to create the time series of Great Salt Lake surface area using Python in Google Colab Timelapse of the Great Salt Lake area, based on cloud-free Landsat-8 images from 2014 to 2023, visualized by the author🌅 Introduction to the Great Salt Lake Shrinkage Problem 💾 Downloading Landsat-8 Images 📈 Time Series…

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What is data reconciliation?: Importance, Process, and Benefits

What is Data Reconciliation? Data reconciliation is an essential process that involves comparing multiple sets of data to identify and rectify discrepancies, ensuring data accuracy and consistency across various business operations. This process is vital for a myriad of functions, such as reconciling invoices with the general ledger, and extends to numerous other business processes…

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