<feed xmlns="http://www.w3.org/2005/Atom"> <id>https://pramodith.github.io/</id><title>Pramodith Dissects</title><subtitle>Pramodith Dissects is a blog covering AI, Tech, Startups and other musings.</subtitle> <updated>2026-03-24T23:36:47+00:00</updated> <author> <name></name> <uri>https://pramodith.github.io/</uri> </author><link rel="self" type="application/atom+xml" href="https://pramodith.github.io/feed.xml"/><link rel="alternate" type="text/html" hreflang="en" href="https://pramodith.github.io/"/> <generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator> <rights> © 2026 </rights> <icon>/assets/img/favicons/favicon.ico</icon> <logo>/assets/img/favicons/favicon-96x96.png</logo> <entry><title>Gated Delta Net Attention: A Deep Dive into the Linear Attention Mechanism Powering Qwen3.5</title><link href="https://pramodith.github.io/posts/gated-delta-net/" rel="alternate" type="text/html" title="Gated Delta Net Attention: A Deep Dive into the Linear Attention Mechanism Powering Qwen3.5" /><published>2026-03-25T00:00:00+00:00</published> <updated>2026-03-25T00:00:00+00:00</updated> <id>https://pramodith.github.io/posts/gated-delta-net/</id> <content type="text/html" src="https://pramodith.github.io/posts/gated-delta-net/" /> <author> <name>Pramodith B</name> </author> <category term="LLM" /> <category term="AI" /> <category term="Inference Optimization" /> <category term="ML" /> <category term="Qwen3.5" /> <summary>A deep dive into the Gated Delta Net Attention mechanism, a linear attention technique powering Qwen3.5.</summary> </entry> <entry><title>Speculative Decoding Tutorial</title><link href="https://pramodith.github.io/posts/speculative-decoding/" rel="alternate" type="text/html" title="Speculative Decoding Tutorial" /><published>2025-12-01T00:00:00+00:00</published> <updated>2025-12-01T12:03:24+00:00</updated> <id>https://pramodith.github.io/posts/speculative-decoding/</id> <content type="text/html" src="https://pramodith.github.io/posts/speculative-decoding/" /> <author> <name>Pramodith B</name> </author> <category term="LLM" /> <category term="AI" /> <category term="Inference Optimization" /> <category term="ML" /> <summary>A tutorial on implementing speculative decoding, an inference optimization technique for LLMs, using PyTorch and Hugging Face Transformers.</summary> </entry> <entry><title>The Math Behind Online Softmax</title><link href="https://pramodith.github.io/posts/online-softmax/" rel="alternate" type="text/html" title="The Math Behind Online Softmax" /><published>2025-11-24T00:00:00+00:00</published> <updated>2025-11-24T06:32:54+00:00</updated> <id>https://pramodith.github.io/posts/online-softmax/</id> <content type="text/html" src="https://pramodith.github.io/posts/online-softmax/" /> <author> <name>Pramodith B</name> </author> <category term="LLM" /> <category term="AI" /> <category term="Kernels" /> <category term="GPU" /> <category term="ML" /> <summary>Understanding the mathematical principles behind online softmax, an optimization technique used in Flash Attention to efficiently compute softmax in chunks.</summary> </entry> <entry><title>The One Big Beautiful Blog on Group Relative Policy Optimization (GRPO)</title><link href="https://pramodith.github.io/posts/grpo-trainer/" rel="alternate" type="text/html" title="The One Big Beautiful Blog on Group Relative Policy Optimization (GRPO)" /><published>2025-06-04T11:00:00+01:00</published> <updated>2025-11-24T06:32:54+00:00</updated> <id>https://pramodith.github.io/posts/grpo-trainer/</id> <content type="text/html" src="https://pramodith.github.io/posts/grpo-trainer/" /> <author> <name>Pramodith B</name> </author> <category term="LLM" /> <category term="AI" /> <category term="RLHF" /> <category term="Reasoning Models" /> <category term="GRPO" /> <category term="PPO" /> <summary>A step-by-step tutorial to code up your own GRPO Trainer.</summary> </entry> <entry><title>Do LLMs recognize Medical Definitions?</title><link href="https://pramodith.github.io/posts/medical-definition-understanding/" rel="alternate" type="text/html" title="Do LLMs recognize Medical Definitions?" /><published>2025-05-12T11:00:00+01:00</published> <updated>2025-11-24T06:32:54+00:00</updated> <id>https://pramodith.github.io/posts/medical-definition-understanding/</id> <content type="text/html" src="https://pramodith.github.io/posts/medical-definition-understanding/" /> <author> <name>Pramodith B</name> </author> <category term="LLM" /> <category term="AI" /> <category term="Explaniable AI" /> <category term="Factual Understanding" /> <category term="Medical AI" /> <summary>Figure: Do LLMs recognize Medical Definitions? There’s been a never-ending debate about whether LLMs understand the data they process, so much so that people have started to debate what understanding something actually means. While some argue that LLMs are mere statistical machines that capture patterns of when and where different words are used, others claim that LLMs do indeed have a sense ...</summary> </entry> </feed>
