Do you really need a huge VLM when a dense Qwen3-VL 4B/8B (instruction/think) with FP8 runs in low VRAM but retains 256K→1M context and full feature surface? Alibaba Qwen Team Expands its intermodal lineup...
Andrej Karpathy is open source nano chata compact, dependency-light codebase that implements the full ChatGPT-style stack (from tagger training to Web UI inference), designed for repeatable, hackable LLM training on a single multi-GPU node....
In this tutorial we will explore the following advanced features py testone of the most powerful testing frameworks in Python. We build a complete mini-project from scratch, demonstrating fixtures, markers, plugins, parameterization and custom...
Why this is technically important: Unlike the “enhanced pre-training” variant previously relied on sparse, binary Correctness signal or proxy filter, RLP dense, verifier-free Bonus accessories location credit Wherever thinking improves predictions, updates can be...
Tuning the LLM output is largely a decoding problem: you can shape the model’s next token distribution with some sampling control –Maximum number of tokens (limiting response length within the context constraints of the...
ServiceNow Research Release DRBencha benchmark and runnable environment for evaluating “deep research” agents for open enterprise tasks that require synthesizing facts from both public network and private organization data Include in properly cited reports....
In this tutorial we will explore ivyUnified capabilities for unifying machine learning development across frameworks. We start by writing a completely framework-agnostic neural network that runs seamlessly on NumPy, PyTorch, TensorFlow, and JAX. We...
Yuan artificial intelligence launched Agency Research Environment (ARE)a modular simulation stack for creating and running agent tasks, and Gaia 2a follow-up benchmark to GAIA for evaluating agents in a dynamic, writable setting. ARE provides...
Microsoft Artificial Intelligence Launched mai-image-1its first Completely developed in-house image generation model at Microsoft. This model has Debuts in the top ten LMA Arena’s text to image Ranking (as of October 13, 2025). The...
Evaluating LLM applications, especially those using RAG (Retrieval Augmentation Generation), is critical but often overlooked. Without proper evaluation, it is nearly impossible to confirm whether your system’s retriever is valid, whether the LLM’s answers...