The open source OpenAI models are finally here, and oh boy were these worth the wait...
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Hackers Hijacked Google’s Gemini AI With a Poisoned Calendar Invite to Take Over a Smart Home
For likely the first time ever, security researchers have shown how AI can be hacked to create real world havoc, allowing them to turn off lights, open smart shutters, and more.
OpenAI’s new open weight (Apache 2) models are really good
The long promised OpenAI open weight models are here, and they are very impressive. They’re available under proper open source licenses—Apache 2.0—and come in two sizes, 120B and 20B. OpenAI’s …
LLMs have unlocked powerful new capabilities, but the dominant pattern for using them, writing increasingly desperate prompts, is fragile, unscalable, and of...
Design, customize, and manage AI applications and agents with Azure AI Foundry. Deploy secure, enterprise-grade AI solutions using unified tools and APIs.
Using an LLM to call tools in a loop is the simplest form of an agent. This architecture, however, can yield agents that are “shallow” and fail to plan and act over longer, more complex tasks. Applications like “Deep Research”, “Manus”, and “Claude Code” have gotten around this limitation by implementing a combination of four things: a planning tool, sub agents, access to a file system, and a detailed prompt.
Acknowledgements: this exploration was primarily inspired by Claude Code and reports o
It is wild to think that it has been only a handful of weeks.
Claude Code has considerably changed my relationship to writing and maintaining code at scale. I still write code at the same level of quality, but I feel like I have a new freedom of expression which is hard to fully articulate.
Claude Code has decoupled myself from writing every line of code, I still consider myself fully responsible for everything I ship to Puzzmo, but the ability to instantly create a whole scene instead of going line by line, word by word is incredibly powerful.
The old timers who built the early web are coding with AI like it's 1995. Think about it: They gave blockchain the sniff test and walked away. Ignored crypto (and …
Everyone's debating whether AI is a bubble while missing the real story. Two things are true: there's a massive AGI fantasy bubble built on geopolitical panic, AND a genuine ML revolution happening at ground level.
Trying out Qwen3 Coder Flash using LM Studio and Open WebUI and LLM
Qwen just released their sixth model(!) for this July called Qwen3-Coder-30B-A3B-Instruct—listed as Qwen3-Coder-Flash in their chat.qwen.ai interface. It’s 30.5B total parameters with 3.3B active at any one time. This means …
Contextualizing ancient texts with generative neural networks - Nature
Aeneas, a generative neural network trained on ancient texts, helps historians contextualize inscriptions and perform epigraphic tasks, offering an improved starting point for historical research.
Bay.Area.AI: DSPy: Prompt Optimization for LM Programs, Michael Ryan
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference DSPy: Prompt Optimization for LM Programs
Michael Ryan, Stanford
It has never been easier to build amazing LLM powered applications. Unfortunately engineering reliable and trustworthy LLMs remains challenging. Instead, practitioners should build LM Programs comprised of several composable calls to LLMs which can be rigorously tested, audited, and optimized like other software systems. In this talk I will introduce the idea of LM Programs in DSPy: The library for Programming — not Prompting LMs. I will demonstrate how the LM Program abstraction allows the creation of automatic optimizers for LM Programs which can optimize both the prompts and weights in an LM Program. I will conclude with an introduction to MIPROv2: our latest and highest performing prompt optimization algorithm for LM Programs.
Michael Ryan is a masters student at Stanford University working on optimization for Language Model Programs in DSPy and Personalizing Language Models. His work has been recognized with a Best Social Impact award at ACL 2024, and an honorable mention for outstanding paper at ACL 2023. Michael co-lead the creation of the MIPRO & MIPROv2 optimizers, DSPy’s most performant optimizers for Language Model Programs. His prior work has showcased unintended cultural and global biases expressed in popular LLMs. He is currently a research intern at Snowflake.
LLM Embeddings Explained: A Visual and Intuitive Guide - a Hugging Face Space by hesamation
This app explains how language models transform text into meaningful representations through embeddings. It provides a visual guide to help you understand traditional and modern language model tech...
Working Effectively with AI Coding Tools like Claude Code
A practical guide to working effectively with AI coding tools like Claude Code, covering mindset shifts, quality control strategies, and team collaboration workflows for modern software development.
Your robot experience started simple. You typed a question into a chatbot… just to see. Can it answer that question? I'd be impressed if it did.
Your query was simple. A simple knowledge question that with a little effort using legacy tools like Google, you would have discovered yourself, but the r
VS Code AI Customization - Learn to use custom instructions, prompt files, and custom chat modes to personalize AI code generation, reviews, and chat responses.