Perivitta Rajendran

Large Language ModelsRetrieval-Augmented GenerationAI AgentsFine-TuningDiffusion ModelsMixture of Experts Large Language ModelsRetrieval-Augmented GenerationAI AgentsFine-TuningDiffusion ModelsMixture of Experts

Updated daily

AI Model Leaderboard

Top language models ranked by benchmark performance — refreshed daily.

See full rankings

1 Loading… —

From the archive

Browse all →

Jun 10, 2026 blogpost

Edge AI: Running LLMs on Your Phone Without the Cloud

LLMs no longer require a data center. Phi-3, Gemma, and Apple Intelligence run directly on device, with no data leaving your phone....

blogpost· 25 mins read ·Beginner
Jun 9, 2026 blogpost

AI Coding Assistants in 2026: Cursor, GitHub Copilot, and the Future of Software Development

AI coding assistants have moved well beyond tab-completion. Cursor edits across files, GitHub Copilot reviews pull requests, and Devin claims to handle...

blogpost· 25 mins read ·Beginner
Jun 8, 2026 blogpost

Context Engineering: The New Skill That Is Replacing Prompt Engineering

Prompt engineering is giving way to something deeper: context engineering. How you structure what goes into the context window, what you include,...

blogpost· 26 mins read ·Intermediate
Jun 7, 2026 ai-engineering

Vision Language Models (VLMs): How GPT-4o, Claude, and LLaVA Understand Images

Vision Language Models bridge the gap between pixels and language. This post covers how CLIP encodes images, how visual tokens are projected...

ai-engineering· 45 mins read ·Advanced
Jun 6, 2026 ai-engineering

Mixture of Experts (MoE): The Architecture Behind GPT-4, Mixtral, and Grok

Mixture of Experts scales model capacity without scaling compute. Instead of activating all parameters for every token, MoE routes each token to...

ai-engineering· 47 mins read ·Advanced
Jun 5, 2026 blogpost

Diffusion Models Explained: The Math-Free Guide to How Stable Diffusion and DALL-E Work

Diffusion models generate images by learning to reverse a noise process. No math required. Here is the intuition behind Stable Diffusion, DALL-E,...

blogpost· 34 mins read ·Beginner
Jun 4, 2026 blogpost

AI Agent Memory: Short-Term Context, Long-Term Storage, and Episodic Recall

Stateless LLMs forget everything when the context window closes. Building agents that actually remember requires understanding four distinct memory types and when...

blogpost· 29 mins read ·Intermediate
Jun 3, 2026 blogpost

Reasoning Models Explained: How o1, o3, and DeepSeek R1 Think Before They Answer

Reasoning models like o1, o3, and DeepSeek R1 don't just predict the next token. They think through problems step by step before...

blogpost· 27 mins read ·Intermediate
Jun 2, 2026 ai-engineering

LoRA and QLoRA: Fine-Tuning LLMs on a Single GPU

Full fine-tuning a 7B parameter model requires 112 GB of VRAM and costs thousands of dollars. LoRA reduces trainable parameters by 99%...

ai-engineering· 24 mins read ·Advanced
Jun 1, 2026 ai-engineering

Graph RAG: When Knowledge Graphs Beat Vector Search

Standard vector RAG fails on multi-hop questions that require connecting information across multiple documents. Graph RAG solves this by building a knowledge...

ai-engineering· 24 mins read ·Advanced

Perivitta Rajendran

Recent writing

Decision Trees: A Complete Guide with Hand-Worked Examples

Knowledge Distillation: How Small Models Learn from Big Ones

LLM as Judge: How to Evaluate AI Models Automatically at Scale

AI Model Leaderboard

From the archive

Edge AI: Running LLMs on Your Phone Without the Cloud

AI Coding Assistants in 2026: Cursor, GitHub Copilot, and the Future of Software Development

Context Engineering: The New Skill That Is Replacing Prompt Engineering

Vision Language Models (VLMs): How GPT-4o, Claude, and LLaVA Understand Images

Mixture of Experts (MoE): The Architecture Behind GPT-4, Mixtral, and Grok

Diffusion Models Explained: The Math-Free Guide to How Stable Diffusion and DALL-E Work

AI Agent Memory: Short-Term Context, Long-Term Storage, and Episodic Recall

Reasoning Models Explained: How o1, o3, and DeepSeek R1 Think Before They Answer

LoRA and QLoRA: Fine-Tuning LLMs on a Single GPU

Graph RAG: When Knowledge Graphs Beat Vector Search

Recent writing

Decision Trees: A Complete Guide with Hand-Worked Examples

Knowledge Distillation: How Small Models Learn from Big Ones

LLM as Judge: How to Evaluate AI Models Automatically at Scale

Not sure where to start? Just ask.

AI Model Leaderboard

From the archive

Edge AI: Running LLMs on Your Phone Without the Cloud

AI Coding Assistants in 2026: Cursor, GitHub Copilot, and the Future of Software Development

Context Engineering: The New Skill That Is Replacing Prompt Engineering

Vision Language Models (VLMs): How GPT-4o, Claude, and LLaVA Understand Images

Mixture of Experts (MoE): The Architecture Behind GPT-4, Mixtral, and Grok

Diffusion Models Explained: The Math-Free Guide to How Stable Diffusion and DALL-E Work

AI Agent Memory: Short-Term Context, Long-Term Storage, and Episodic Recall

Reasoning Models Explained: How o1, o3, and DeepSeek R1 Think Before They Answer

LoRA and QLoRA: Fine-Tuning LLMs on a Single GPU

Graph RAG: When Knowledge Graphs Beat Vector Search