W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...
https://ernie.baidu.com/blog/publication/PaddleOCR-VL_Technical_Report.pdf ...
What QeRL changes in the Reinforcement Learning (RL) loop? Most RLHF/GRPO/DAPO pipelines spend the bulk of wall-clock time in rollouts (token generation). QeRL shifts the policy’s weight path to NVFP4 ...
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 ...
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 has expanded ...
Michal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data ...
In the traditional cascade modeling approach, automatic speech recognition (ASR) first produces a single text string, which is then passed to retrieval. Small transcription errors can change query ...
ACE positions “context engineering” as a first-class alternative to parameter updates. Instead of compressing instructions into short prompts, ACE accumulates and organizes domain-specific tactics ...
xAI introduced Grok-4-Fast, a cost-optimized successor to Grok-4 that merges “reasoning” and “non-reasoning” behaviors into a single set of weights controllable via system prompts. The model targets ...
Alibaba’s Tongyi Lab has open-sourced Tongyi-DeepResearch-30B-A3B, an agent-specialized large language model built for long-horizon, deep information-seeking with web tools. The model uses a ...
What Do We Mean by “Physical AI”? Artificial intelligence in robotics is not just a matter of clever algorithms. Robots operate in the physical world, and their intelligence emerges from the co-design ...
Deep-learning throughput hinges on how effectively a compiler stack maps tensor programs to GPU execution: thread/block schedules, memory movement, and instruction selection (e.g., Tensor Core MMA ...
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