#tensor processing unit
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Tutorials·3 min
Review of a 648-Episode Complete Python Tutorial: Is It Worth Learning from Zero to AI Applications?
In-depth review of a 648-episode Python tutorial on Bilibili, analyzing its three-stage course structure, resource quality, and learning effectiveness with practical study tips for beginners.
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Tutorials·2 min
Tutorial: Deploying a PD-Disaggregated SGLang Multi-Node Inference Cluster on AMD GPUs
Learn how to deploy a PD-disaggregated SGLang inference cluster on AMD GPUs using a single config file, boosting LLM throughput and latency performance.
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Tech Frontiers·2 min
SGLang v0.5.12.post1 Released: DeepSeek V4 Stability Fixes and Blackwell Adaptation
SGLang v0.5.12.post1 stability patch details: 12 critical fixes covering DeepSeek V4 garbled text and crashes, NIXL PD disaggregated inference logic, Blackwell B300 adaptation, and cold start optimization.
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Industry Insights·2 min
AMD MI355X Beats B200: Full-Stack Optimization Breakdown for 5% Lower TCO on DeepSeek-R1 Inference
AMD Instinct MI355X achieves 5% lower TCO than NVIDIA B200 on DeepSeek-R1 disaggregated inference via SGLang+MoRI full-stack optimization with 1.25x per-GPU throughput.
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Tech Frontiers·1 min
SGLang Hosts Agent Loops Office Hour, Focusing on Agentic Loop Architecture Optimization
SGLang team hosts an Agent Loops Office Hour exploring inference optimization for agentic loops, covering KV Cache reuse, low-latency multi-turn dialogue, and tool calling techniques.
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Industry Insights·3 min
Deep Dive into Three Major LLM Career Paths: Requirements, Tech Stacks, and Career Prospects
Deep analysis of three core LLM roles—Application Engineer, Development Engineer, and Algorithm Engineer—covering technical requirements, salary thresholds, and career prospects including RAG, fine-tuning, and inference deployment.
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Tutorials·2 min
Learning AI Large Language Models from Scratch: A Guide to Learning Paths, Hardware, and Programming Languages
A beginner's guide to learning AI large language models — covering learning paths, hardware requirements, Python essentials, and cloud services for learners at every level.
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Tech Frontiers·2 min
Meta Muse Spark Released: A Comprehensive Analysis of the Native Multimodal Reasoning Model
Meta Superintelligence Labs releases Muse Spark, a native multimodal reasoning model supporting visual chain of thought, tool-use, and multi-agent orchestration. Deep dive into its capabilities and competitive positioning.
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Tutorials·2 min
Coze Beginner's Guide: A Complete Tutorial for Building AI Agents with Zero Code
A detailed guide to Coze AI development platform's core features including agent building, workflow orchestration, knowledge base setup, and plugins — build custom AI apps with zero code.
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Tech Frontiers·2 min
DeepSeek OCR2, Kimi K2.5, and Microsoft Maia 200 All Launched on the Same Day
DeepSeek releases OCR2 replacing CLIP with an LLM as visual encoder; Moonshot AI launches Kimi K2.5 with 100+ sub-agent cluster mode; Microsoft deploys 3nm Maia 200 chip; Alibaba releases Qwen3 Max Thinking.
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Tutorials·3 min
Getting Started with AI Full-Stack Development: A Knowledge Framework from Machine Learning to Large Language Models
A systematic guide to the relationships between AI, machine learning, deep learning, and large language models, helping developers build a clear knowledge framework and find an efficient learning path.
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Tutorials·3 min
Decoding LLM Naming Conventions: Parameter Counts, Quantization Formats & VRAM Requirements Quick Reference
Decode LLM naming conventions, understand 32B parameters & AWQ/GGUF quantization formats, with 4-bit VRAM estimation formulas, MOE model pitfalls, and model selection by GPU tier.
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Industry Insights·2 min
NVIDIA Blackwell Sets New STAC-AI Records for Financial LLM Inference
NVIDIA Blackwell GPU sets new LLM inference records in STAC-AI financial benchmark. Explore Blackwell architecture advantages, TensorRT-LLM co-optimization, and LLM applications in trading and risk management.
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Tutorials·3 min
Efficient PyTorch Learning: A Source Code-Driven Methodology
A proven PyTorch learning method: spend 2-3 days on basics, then advance rapidly by reading U-Net and ViT source code line by line. Master PyTorch through source code-driven learning.
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Tech Frontiers·2 min
Google I/O 2025 Gemini Updates Roundup: Model Upgrades, Multimodal Interaction, and AI Agent Deep Dive
A comprehensive breakdown of Gemini updates at Google I/O 2025: next-gen model upgrades, multimodal interaction, AI Agent capabilities, and competitive analysis against ChatGPT and Copilot.
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Tutorials·1 min
NVIDIA CUDA Tile: A Detailed Look at the New Tile-Based GPU Programming Paradigm
In-depth analysis of NVIDIA's new CUDA Tile programming model: how tile-based GPU kernel development integrates with C++, optimizes data locality, and accelerates Tensor Core computation for HPC, deep learning, and AI inference.
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Tutorials·2 min
Python for Absolute Beginners: A Complete Guide to Language Features and Applications
A beginner's guide to Python covering its core features—readability, simplicity, and extensibility—plus key applications in AI, web development, data analysis, and web scraping, with version selection advice.
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Tech Frontiers·2 min
Anthropic's Compute Expansion Explained: How More Chips Make Claude Stronger and Faster
Anthropic announces a massive compute expansion with "More chips, more Claude." This article analyzes the impact on user experience, service capacity, response speed, and next-gen models.
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Product Reviews·3 min
Ara: An Open-Source Computer Use Tool as a Multi-Agent Automation Alternative to OpenClaw
Ara is an open-source Computer Use tool and OpenClaw alternative that uses multi-AI-agent collaboration to automate tasks. Explore its architecture, use cases, and competitive landscape.
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Product Reviews·2 min
ElevenCreative Flows: In-Depth Review of a Node-Based Multimodal AI Creative Collaboration Tool
In-depth analysis of ElevenCreative Flows, a node-based AI creative pipeline tool supporting image, video, voice, and music generation with Figma-style real-time collaboration for brand marketing and design teams.
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