What Are Diffusion Language Models, and Why Are They Different From GPT?
Then you train the neural network to reverse this process, commonly using a mean squared error objective.
Attention Variants and Memory Efficiency
Overview This post is divided into eight parts; they are: • The Checkpoint Fixes the Attention Architecture • A Closer Look at Attention Memory • Multi-Head Attention • Multi-Query and Grouped-Query Attention • Sliding-Window and Mixed Attention • Multi-Head Latent Attention • What the Inference Runtime Can Change • From Cache Size to Serving Capacity …
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….
BAIR at CoRL 2026
The Conference on Robot Learning (CoRL) takes place November 9–12, 2026, in Austin, Texas. BAIR faculty, postdocs and students will be presenting research at various sessions, including an Early Career Keynote from Professor Negar Mehr. See below for the full schedule of sessions with BAIR members, including papers co-authored with collaborators at other universities and …
Floating-Point Precision and Its Effects to Model Inference
Overview This post is divided into five parts; they are: • How Floating-Point Numbers Work • Common Precision Formats • Loading a Model at a Different Precision • Mixed Precision and Sensitive Operations • Measuring the Result How Floating-Point Numbers Work A floating-point number contains a sign, an exponent, and a significand (often called the …
Read more “Floating-Point Precision and Its Effects to Model Inference”
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…
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…
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…
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…
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…