Alibaba’s Qwen AI Releases Compact Dense Qwen3-VL 4B/8B (Instruct & Thinking) With FP8 Checkpoints
Do you actually need a giant VLM when dense Qwen3-VL 4B/8B (Instruct/Thinking) with FP8 runs in low VRAM yet retains 256K→1M context and the full capability surface? Alibaba’s Qwen team…
Andrej Karpathy Releases ‘nanochat’: A Minimal, End-to-End ChatGPT-Style Pipeline You Can Train in ~4 Hours for ~$100
Andrej Karpathy has open-sourced nanochat, a compact, dependency-light codebase that implements a full ChatGPT-style stack—from tokenizer training to web UI inference—aimed at reproducible, hackable LLM training on a single multi-GPU…
A Coding Implementation of Advanced PyTest to Build Customized and Automated Testing with Plugins, Fixtures, and JSON Reporting
In this tutorial, we explore the advanced capabilities of PyTest, one of the most powerful testing frameworks in Python. We build a complete mini-project from scratch that demonstrates fixtures, markers,…
NVIDIA Researchers Propose Reinforcement Learning Pretraining (RLP): Reinforcement as a Pretraining Objective for Building Reasoning During Pretraining
Why this matters technically: unlike prior “reinforcement pretraining” variants that rely on sparse, binary correctness signals or proxy filters, RLP’s dense, verifier-free reward attaches position-wise credit wherever thinking improves prediction,…
7 LLM Generation Parameters—What They Do and How to Tune Them?
Tuning LLM outputs is largely a decoding problem: you shape the model’s next-token distribution with a handful of sampling controls—max tokens (caps response length under the model’s context limit), temperature…
ServiceNow AI Research Releases DRBench, a Realistic Enterprise Deep-Research Benchmark
ServiceNow Research has released DRBench, a benchmark and runnable environment to evaluate “deep research” agents on open-ended enterprise tasks that require synthesizing facts from both public web and private organizational…
Meta’s ARE + Gaia2 Set a New Bar for AI Agent Evaluation under Asynchronous, Event-Driven Conditions
Meta AI has introduced Agents Research Environments (ARE), a modular simulation stack for creating and running agent tasks, and Gaia2, a follow-up benchmark to GAIA that evaluates agents in dynamic,…
Ivy Framework Agnostic Machine Learning Build, Transpile, and Benchmark Across All Major Backends
In this tutorial, we explore Ivy’s remarkable ability to unify machine learning development across frameworks. We begin by writing a fully framework-agnostic neural network that runs seamlessly on NumPy, PyTorch,…
Microsoft AI Debuts MAI-Image-1: An In-House Text-to-Image Model that Enters LMArena’s Top-10
Microsoft AI introduced MAI-Image-1, its first image generation model developed entirely in-house at Microsoft. The model has debuted in the Top-10 of the LMArena text-to-image leaderboard (as of Oct 13,…
How to Evaluate Your RAG Pipeline with Synthetic Data?
Evaluating LLM applications, particularly those using RAG (Retrieval-Augmented Generation), is crucial but often neglected. Without proper evaluation, it’s almost impossible to confirm if your system’s retriever is effective, if the…
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