In this article, you will learn how to sandbox the code an AI agent writes by running it in a limited subprocess, a hardened Docker container, and a Firecracker microVM, and how to compare their safety and latency.
What Are Diffusion Language Models, and Why Are They Different From GPT?
In this article, you will learn how diffusion language models generate text by iteratively refining a masked sequence, and how this differs from the token-by-token generation of GPT-style models.
Attention Variants and Memory Efficiency
Two transformer models with the same parameter count can have very different memory requirements during inference. A major reason is the structure of their attention layers. The number of key-value heads, the representation stored for each token, and the number of earlier tokens retained by each layer determine how much KV cache a request needs. […]
Benchmarking Scikit-Ollama vs. Groq-Backed Scikit-LLM: Speed, Cost, and Accuracy
In this article, you will learn how to build a side-by-side benchmark of local and cloud LLM classifiers using Scikit-Ollama and a Groq-backed Scikit-LLM pipeline.
Floating-Point Precision and Its Effects to Model Inference
A model is a collection of numbers. The format used to store and compute with those numbers affects how much memory the model occupies, how quickly the hardware can move the numbers, and which arithmetic units can process them. Changing precision can therefore make inference faster without changing the model architecture. Lower precision is not […]
DiffusionGemma: Hands-On with Google’s Text Model That Writes All at Once
In this article, you will learn what DiffusionGemma is, how its diffusion-based text generation differs from standard autoregressive language models, and how to run it with Hugging Face Transformers and vLLM.
Free AI and Data Courses with 365 Data Science: 100% Unlimited Access until Nov 20
Sponsored Content From November 5 to November 20, 2026 (starting at 8:00 a.m. UTC), 365 Data Science will grant free access to its entire learning platform. This limited-time opportunity allows aspiring AI professionals and data enthusiasts to enhance their skills and gain practical, hands-on experience, completely free of charge. Tradition and […]
Decorators for Timing, Retries, Caching, and Validation in Python
In this article, you will learn how Python decorators work under the hood and how to build reliable ones for timing, retries, caching, and input validation.
How to Train Your own Decision Model like Jev using Unsloth
In this article, you will learn how to turn an open-weight language model into a decision model that classifies user intent, by fine-tuning Qwen3.5-4B on the CLINC150 dataset with Unsloth.
Choosing an LLM Inference Optimization Technique: A Decision-Tree Approach
In this article, you will learn how to match an LLM inference optimization technique to the actual bottleneck in your workload by working through a six-question decision tree.