News

@sitepointdotcom
sitepoint.com > local-first-ai-webgpu-chrome-guide

The Complete Guide to Local-First AI: WebGPU, Wasm, and Chrome's Built-in Model

3+ hour, 49+ min ago  (737+ words) 7 Day Free Trial. Cancel Anytime. Local-first AI in the browser has crossed the threshold from experimental curiosity to production-viable technology. This guide is a deep technical walkthrough for experienced JavaScript and web developers who want to understand the architecture beneath…...

@sitepointdotcom
sitepoint.com > deepseek-r1-open-source-reasoning

DeepSeek-R1: The Open-Source Reasoning Model

4+ hour, 12+ min ago  (1102+ words) 7 Day Free Trial. Cancel Anytime. For the past two years, frontier reasoning capabilities in large language models have been locked behind closed-source walls. DeepSeek-R1 upends that dynamic'this article covers the architecture, benchmarks against GPT-4o and Claude 3.5 Sonnet, three concrete paths…...

@sitepointdotcom
sitepoint.com > definitive-guide-local-first-ai-2026

The Definitive Guide to Local-First AI

4+ hour, 13+ min ago  (942+ words) 7 Day Free Trial. Cancel Anytime. Local-first AI means running inference directly on the client device, inside the browser, with no data ever leaving the user's machine. This guide covers the full local-first AI stack, from raw WebGPU compute shaders through…...

@sitepointdotcom
sitepoint.com > definitive-guide-local-llms-2026-privacy-tools-hardware

Guide to Local LLMs in 2026: Privacy, Tools & Hardware

1+ week, 3+ day ago  (1659+ words) 7 Day Free Trial. Cancel Anytime. Before we get into specifics, one clarification matters: "local" in this article means on-device inference, where the model weights live on your machine and no data leaves it. That is distinct from "self-hosted," which might…...

@sitepointdotcom
sitepoint.com > long-context-vs-rag-1m-token-windows

Long Context vs RAG: When 1M Token Windows Replace RAG

1+ week, 4+ day ago  (1677+ words) 7 Day Free Trial. Cancel Anytime. A developer I know spent two weeks wiring up a RAG pipeline for a 200-page internal docs site. Vector database, chunking strategy, embedding model selection, retrieval evaluation harness, deployment behind an API. The whole nine…...