Google is accusing others of cloning its Gemini AI, despite its own history of scraping data without permission to train its models. This raises questions of hypocrisy as companies compete to protect their AI investments and differentiate their offerings, facing challenges like model distillation and the potential for smaller entities to compete.
An analysis of the accuracy of image search tools like Google Lens, Gemini, and Bing, highlighting that while Google Lens is the most reliable, all tools can make mistakes and should be verified. The article uses examples from Yale University architecture to demonstrate these inaccuracies.
This article details how Google SREs are leveraging Gemini 3 and Gemini CLI to accelerate incident response, root cause analysis, and postmortem creation, ultimately reducing Mean Time To Mitigation (MTTM) and improving system reliability.
An AI-powered document search agent that explores files like a human would — scanning, reasoning, and following cross-references. Unlike traditional RAG systems that rely on pre-computed embeddings, this agent dynamically navigates documents to find answers.
Simon Willison’s annual review of the major trends, breakthroughs, and cultural moments in the large language model ecosystem in 2025, covering reasoning models, coding agents, CLI tools, Chinese open‑weight models, image editing, academic competition wins, and the rise of AI‑enabled browsers.
An analysis of the current LLM landscape in 2026, focusing on the shift from 'vibe coding' to more efficient and controlled workflows for software development and data analysis. The author advocates for tools like AI Studio and OpenCode, and discusses the strengths of models like Gemini 2.5 Pro and Claude Sonnet.
An extensible Model Context Protocol (MCP) server that provides intelligent semantic code search for AI assistants. Built with local AI models using Matryoshka Representation Learning (MRL) for flexible embedding dimensions.
A review of the SearchResearch blog's 2025 posts, highlighting a shift towards AI-augmented research methods, testing AI tools, and emphasizing the importance of verification and critical thinking in online research.
This article provides a verified list of AI crawlers (GPTBot, ClaudeBot, Gemini, etc.) with user-agent strings, crawl rates, and IP verification information to help manage access and maintain inclusion in AI discovery.
Fine-tune DeepSeek models using your own markdown files as training data. Converts your notes/docs into high-quality Q&A pairs using Gemini, then trains a personalized LLM via Tinker cloud GPUs.
