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April 2025

All About The Modern Positional Encodings In LLMs
The Positional Encoding in LLMs may appear somewhat mysterious the first time we come across the concept, and for good reasons!
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Damien Benveniste
Join us for a Free LIVE Coding Event: Build The Self-Attention in PyTorch From Scratch
Next Friday, I am inviting you to join me for an exciting live coding event. It is a completely free event where I will explain the basics of the…
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Damien Benveniste
Build Production-Ready LLMs From Scratch
From Prototype to Production: Ship Scalable LLM Systems in 6 Weeks
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Damien Benveniste

March 2025

Chapter 4 of The Big Book of Large Language Models is Here!
Chapter 4 of the Big Book of Large Language Models is finally here!
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Damien Benveniste
2
Reduce AI Model Operational Costs With Quantization Techniques
A deep dive into quantization and precision levels
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Damien Benveniste
3
How To Construct Self-Attention Mechanisms For Arbitrary Long Sequences
Toward Infinite Sequence Lengths
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Damien Benveniste
How To Improve Decoding Latency With Faster Self-Attention Mechanisms
In LLMs, handling large sequences is not enough, we need to make sure the decoding process is fast.
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Damien Benveniste
How To Reduce The Memory Usage Of The Self-Attention
With a bit of magic, we take a very inefficient computation like the Self-Attention and make it super memory-optimized for the specific hardware we use…
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Damien Benveniste

February 2025

How To Linearize The Attention Mechanism!
Today, we talk about how to engineer attention mechanisms in O(n) complexity instead of O(n2).
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Damien Benveniste
Understanding The Sparse Transformers!
The First Sparse Attention: Sparse Transformers
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Damien Benveniste
Attention Is All You Need: The Original Transformer Architecture
This newsletter is the latest chapter of the Big Book of Large Language Models. You can find the preview here, and the full chapter is available in this…
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Damien Benveniste
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