Mastering Parallel Agent Mode in Cursor 2.0
Parallel Agent Mode in Cursor 2.0 lets you run up to eight AI agents at once, each on its own branch. This speeds up feature delivery, reduces merge conflicts, and keeps your codebase clean.
Kimi K2.5: The New Open-Weight AI Model Shaping the Future
Kimi K2.5 is the first open‑weight AI model with 15 trillion tokens. It offers a hybrid architecture that balances speed and accuracy, making it ideal for content creation, code generation, and research.
SenseNova‑MARS: The First Open‑Source Agentic Vision‑Language Model
SenseNova‑MARS is the first open‑source agentic vision‑language model that can see, reason, and act. Built on a hybrid transformer‑Mamba architecture, it offers low memory usage, fast inference, and built‑in policy controls for secure deployment.
Sora 2 & Veo 3.1: Build Video Apps with Playcode.io
This guide shows how to use Sora 2 and Veo 3.1 AI video models with Playcode.io to build responsive React/Tailwind web apps. It includes code snippets, styling tips, and best practices for prompt design and caching.
AI‑native IDEs: Google Antigravity and the Future of Coding
Artificial intelligence is no longer just a buzzword. It’s becoming a real part of the tools we [Read more]
Local 4K AI Video
A practical guide to creating 4K video locally using GPUs, Ollama, and AI tools. Includes workflow steps, troubleshooting, and resource links.
Falcon‑H1R 7B: Hybrid Transformer‑Mamba Model Explained
Falcon‑H1R 7B is a new hybrid AI model that blends Transformer and Mamba. It offers fast, accurate performance for writing, coding, and customer support.
DeepSeek MODEL1 Architecture: Memory‑Efficient LLMs
DeepSeek MODEL1 is a new large‑language‑model architecture that reduces GPU memory usage by 30 % and speeds up inference. It uses a new KV cache layout, sparsity handling, and FP8 decoding.
Self‑Adapting Language Models Explained
Self‑adapting language models can learn from real‑world use, generate their own training data, and keep improving without full retraining. This article explains how they work, their benefits, and the challenges they face.
DeepSeek V4 Architecture: Hyper‑Connections Explained
DeepSeek V4 architecture introduces manifold‑constrained hyper‑connections, a new way to keep long‑range context in transformer models. This design makes the model lighter, faster, and more accurate for code generation and multi‑step reasoning.