AI/ML Techniques

Using a Transformer Model: From Training to Inference

This chapter is divided into four parts; they are: • Autoregressive Generation • Prefill and Decode • A Simple KV…

6 hours ago

Decoding Strategies and Output Control

This chapter is divided into nine parts; they are: • Reading Logits from a Model • Greedy Decoding • Temperature…

6 hours ago

The End-to-End Agentic AI Pipeline

In this article, you will learn the seven architectural components that separate a production-grade agentic AI system from a demo…

4 days ago

Ollama vs. LM Studio vs. llama.cpp: Which Local AI Runtime Should You Use in 2026?

In this article, you will learn how Ollama, LM Studio, and llama.cpp differ across the dimensions that matter most to…

5 days ago

From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon

Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied instruction-for-instruction.…

5 days ago

5 Architectural Patterns for Persistent Memory and State in AI Agents

Memory & State For AI Agents Building an AI agent can be tricky. Keeping it on track over a six-month…

1 week ago

Teaching LLMs to Update Beliefs for Efficient Long-Horizon Interaction

Overview of ABBEL compared to traditional recursive summarization. Beliefs replace the full interaction history as the agent’s working context, and…

1 week ago

Stateful vs. Stateless Agent Design: Tradeoffs for Scalable Agentic Systems

In this article, you will learn how an agent's approach to managing state — stateless or stateful — shapes both…

1 week ago

An Introduction to Loop Engineering

It's tempting to treat loop engineering as something invented in a single week in June, but the mechanics behind it…

2 weeks ago

The Current State of Agentic AI

In this article, you will learn how agentic AI architecture has evolved by mid-2026, including the shift away from orchestrated…

2 weeks ago