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The open-source AI landscape has a new entry worth paying attention to. The Qwen team at Alibaba has released Qwen3.6-35B-A3B, the first open-weight model from the Qwen3.6 generation, and it is making a compelling argument that parameter efficiency matters far more than raw model size. With 35 billion total parameters but only 3 billion activated […]
Drug discovery is one of the most expensive and time-consuming endeavors in human history. It takes roughly 10 to 15 years to go from target discovery to regulatory approval for a new drug in the United States. Most of that time is spent not in breakthrough moments, but in painstaking analytical work — sifting through
The intersection of many-body physics and deep learning has opened a new frontier: Neural Quantum States (NQS). While traditional methods struggle with high-dimensional frustrated systems, the global attention mechanism of Transformers provides a powerful tool for capturing complex quantum correlations. In this tutorial, we implement a research-grade Variational Monte Carlo (VMC) pipeline using NetKet and
Building Transformer-Based NQS for Frustrated Spin Systems with NetKet Read More »
The dominant recipe for building better language models has not changed much since the Chinchilla era: spend more FLOPs, add more parameters, train on more tokens. But as inference deployments consume an ever-growing share of compute and model deployments push toward the edge, researchers are increasingly asking a harder question — can you scale quality
In this tutorial, we build a universal long-term memory layer for AI agents using Mem0, OpenAI models, and ChromaDB. We design a system that can extract structured memories from natural conversations, store them semantically, retrieve them intelligently, and integrate them directly into personalized agent responses. We move beyond simple chat history and implement persistent, user-scoped
How to Build a Universal Long-Term Memory Layer for AI Agents Using Mem0 and OpenAI Read More »
Google just announced the release of Skills in Chrome, a new feature built into Gemini in Chrome that lets users save frequently used AI prompts as reusable, one-click workflows called Skills. The rollout begins April 14, 2026, targeting Mac, Windows, and ChromeOS users who have their Chrome language set to English-US. If you’ve been paying
In this tutorial, we build a complete and practical Crawl4AI workflow and explore how modern web crawling goes far beyond simply downloading page HTML. We set up the full environment, configure browser behavior, and work through essential capabilities such as basic crawling, markdown generation, structured CSS-based extraction, JavaScript execution, session handling, screenshots, link analysis, concurrent
AI agents struggle with tasks that require interacting with the live web — fetching a competitor’s pricing page, extracting structured data from a JavaScript-heavy dashboard, or automating a multi-step workflow on a real site. The tooling has been fragmented, requiring teams to stitch together separate providers for search, browser automation, and content retrieval. TinyFish, a
AI agents struggle with tasks that require interacting with the live web — fetching a competitor’s pricing page, extracting structured data from a JavaScript-heavy dashboard, or automating a multi-step workflow on a real site. The tooling has been fragmented, requiring teams to stitch together separate providers for search, browser automation, and content retrieval. TinyFish, a
Understanding audio has always been the multimodal frontier that lags behind vision. While image-language models have rapidly scaled toward real-world deployment, building open models that robustly reason over speech, environmental sounds, and music — especially at length — has remained quite hard. NVIDIA and the University of Maryland researchers are now taking a direct swing
