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Into AI

Dr. Ashish Bamania
Hundreds of paid subscribers

Deep, research-driven explainers for AI engineers.

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Substack
PricingFreemiumPublishesTwice weekly
Issues234Founded3 years agoLast Issue5 days ago
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Latest Issues

PPO vs GRPO, Simply Explained

LLM training is commonly done in three stages, and each stage helps the model to become more useful. These stages are as follows:

  1. Pretraining: Teaches an LLM the basics of language and gives it foundational knowledge of the world....
5 days ago
5

On-Policy Distillation, Simply Explained

On-policy distillation (OPD) is a post-training method in which a student LLM generates its own responses, and a stronger teacher scores them token-by-token, with the student trained to minimize the reverse KL divergence between the two mod...

13 days ago
11

How to Read GPU Specs

A simple and jargon-free guide to reading GPU specs for LLM training and inference.

GPU specification sheets are packed with jargon and confusing metrics. This guide simplifies them and helps you learn how to pick the best GPUs for your LL...

18 days ago
18
Paid

9 GPU Concepts Every AI Engineer Should Know

A simple and practical guide to GPU internals that AI engineers actually need.

“This is the lesson that you need if you are new to GPUs and want to master them without getting overwhelmed.”

a month ago
49
Paid

5 LLM inference batching techniques every AI engineer should know

✨ This newsletter features new research from Pathway. ✨

BDH-CQ is a 150M-parameter reasoning model that breaks the previously reported cost-accuracy Pareto frontier in ARC-AGI-1 and sets a new state-of-the-art for benchmark cost efficiency...

a month ago
14

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    Helping engineers get 100× better in AI | Ex-CTO

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