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Designing High-Performance GPU Kernels with TileLang: Tensor-Core GEMM, Fused Softmax, FlashAttention, and Autotuning
1+ hour, 45+ min ago (764+ words) Explore TileLang, a high-level Python domain-specific language that simplifies the design of high-performance GPU kernels. This tutorial provides a step-by-step approach to implementing complex workloads—including tiled tensor-core GEMM, fused softmax, and FlashAttention—while letting the compiler handle intricate thread…...
Meet Gigatoken: A Rust BPE Tokenizer that Encodes Text at 24.53 GB/s, up to 989x Faster than HuggingFace Tokenizers
2+ day, 11+ hour ago (426+ words) Tokenization is the one part of the language modeling stack that almost nobody profiles. Gigatoken, released by Marcel Rød (a PhD student from Stanford) under an MIT license, argues that this was a mistake. The library encodes text at gigabytes…...
Unsloth vs Axolotl vs TRL vs LLaMA-Factory: A Fine-Tuning Framework Comparison on Speed, VRAM, and Multi-GPU
3+ day, 10+ hour ago (1264+ words) Four open source projects dominate LLM fine-tuning today. Unsloth, Axolotl, TRL, and LLaMA-Factory all wrap the same underlying PyTorch and Hugging Face stack. They diverge on where they spend engineering effort. Unsloth rewrites kernels. Axolotl composes parallelism strategies. TRL defines…...
Poolside Releases Laguna S 2.1, an Open-Weight Agentic Coding Model Punching Above Its Weight Class on SWE-Bench Multilingual
3+ day, 19+ hour ago (455+ words) Poolside has released Laguna S 2.1, a 118B-parameter open-weight model built for agentic coding. It is a Mixture-of-Experts (MoE) model with 8B activated parameters per token. It supports a context window of up to 1M tokens in both thinking and no-thinking modes. The…...
Validating Distributed LLM Serving Benchmarks with NVIDIA srt-slurm, SLURM Recipes, Parameter Sweeps, and Pareto Analysis
4+ day, 3+ hour ago (719+ words) In this tutorial, we explore NVIDIA’s srt-slurm framework and learn how we use srtctl to convert declarative YAML configurations into reproducible SLURM benchmark workflows for distributed LLM serving. We set up the project in Google Colab, inspect its internal architecture,…...
10 Open-Source No-Code AI Platforms for Building LLM Apps, RAG Systems, and AI Agents
6+ day, 14+ hour ago (1157+ words) Building an LLM application no longer requires wiring orchestration code by hand. A class of open-source platforms now exposes retrieval, agents, and workflows through visual canvases, web UIs, and plain-English prompts. These tools let developers prototype in minutes and self-host…...
Fine-Tuning Qwen3 with LoRA Using NVIDIA NeMo AutoModel: A Complete Single-GPU Google Colab Workflow Tutorial
6+ day, 18+ hour ago (288+ words) We import the core Python libraries required for file handling, process execution, path management, and formatted output. We define the repository, working, and checkpoint directories used throughout the workflow. We also create a reusable shell-command function that streams command output…...
Sakana AI's Error Diffusion Trains Dale-Compliant Dual-Stream Networks, Reaching 96.7% MNIST and 61.7% CIFAR-10 Without Backpropagation
1+ week, 13+ hour ago (147+ words) A biologically plausible learning rule reaches 96.7% on MNIST and a 61.7% CIFAR-10 baseline, then extends to reinforcement learning with PPO — all while keeping weights non-negative. Backpropagation dominates deep learning, yet it uses a mechanism the brain likely cannot. Specifically, the backward…...
Zyphra Releases ZUNA1.1: An Apache 2.0 EEG Foundation Model With Variable-Length Inputs From 0.5 To 30 Seconds
1+ week, 22+ hour ago (510+ words) This week, Zyphra released ZUNA1.1 under the Apache 2.0 license. The EEG foundation model reconstructs, denoises, and upsamples data across arbitrary channel layouts. It builds on ZUNA1, the Zyphra’s earlier open EEG foundation model. The main change is flexibility, not a jump in…...
NVIDIA AI Releases Nemotron 3 Embed: An Open Embedding Collection Whose 8B Checkpoint Ranks #1 on RTEB
1+ week, 1+ day ago (539+ words) Embedding models decide which passages an agent ever sees. NVIDIA released Nemotron 3 Embed model to work on that layer. It targets production-scale RAG, agentic retrieval, code retrieval, and agent memory. All three are transformer encoders trained with bidirectional attention masking....