OpenMed 1.7.0 brings multimodal de-identification, OCR, FHIR and HL7 helpers, signed audit evidence, Transformers.js browser export, 1,000 open-source healthcare LLM models, and Swift-native OpenMedKit.

a walkthrough of how LLMs work

The process for fine-tuning LLMs Locally without third-party APIs and platform fees. Before starting to fine-tune a model, make sure you actually need to! Fine-tuning LLMs can be a lengthy process and computationally expensive. It is a good idea to test the model’s performance on your task-specific data and try other less-demanding methods such as In-Context-Learning (ICL). It is also a good practice to fine-tune with smaller batches of data and record the improvement (i.e., output accuracy and validation loss) at each step, before increasing the number of training data examples.

Interactive AI timeline tracking 194 Large Language Models from 2017 to 2026. Explore the history of ChatGPT, GPT-4, Claude, Gemini, LLaMA, Mistral, DeepSeek and every major LLM ever released.

This weblog features the work of developer Simon Willison, primarily focusing on the latest developments in AI, large language models (LLMs), prompt injection vulnerabilities, coding agents, and related software and security topics.

AINews is a daily newsletter and archive by smol.ai that summarizes the top discussions and developments from major AI communities (Discord, Reddit, X/Twitter) to help engineers and enthusiasts keep up with the latest in AI models, agents, infrastructure, and research.

Extracting structured text from GI Bill index cards for JDoc 2023 paper - ICPSR/gi-bill

Really heartfelt piece that cuts through the noise imo. It deals with it quite fairly.