#deep learning
123 related articles
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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Research·2 min
Meta Muse Spark Technical Deep Dive: How Three-Dimensional Scaling Achieves 10x Compute Reduction
Meta reveals Muse Spark technical details: three-dimensional scaling across pre-training, RL, and test-time inference achieves over 10x compute reduction versus Llama 4 Maverick.
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Industry Insights·2 min
The EU AI Fund Controversy: Why GPU Subsidies Fail to Reach Real Entrepreneurs
The EU AI Fund aims to provide GPU compute for startups, but entrepreneurs question resource allocation citing cronyism. Analysis of EU AI subsidy challenges vs. US market-driven models.
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Product Reviews·3 min
ZhiHu AI Digital Human Live Streaming Review: Dual-Person Co-Frame and Full-Posture Features Tested
In-depth review of ZhiHu AI's digital human streaming software: dual co-frame streaming, full-posture multi-scene support, timed host switching, smart script rewriting across 14 platforms with OEM options.
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Tech Frontiers·2 min
Qwen Core Team Turmoil, OpenAI and Google Release New Models in Rapid Succession | AI Daily
Multiple core leaders depart Alibaba's Qwen team amid metric disputes. Same day: MiniMax Music 2.5+, OpenAI GPT 5.3 Instant, Google Gemini 3.1 Flashlight, and Seedance 2.0 pricing announced.
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Tutorials·3 min
Complete Breakdown of Andrew Ng's Agent Course: A Practical Guide to the Five Core Modules of AI Agent Development
Deep dive into Andrew Ng's viral AI Agent course covering five core modules: Reflection, Planning, Tool Use, Multi-Agent Collaboration, and Memory, with practical learning paths for LLM agent development.
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Tutorials·3 min
Frontend Engineers Leveling Up to AI Agents: LangGraph.js Architecture Design & Practical Guide
How can frontend engineers advance into AI Agent development? This guide covers LangGraph.js core architecture (state, nodes, edges), LangChain comparison, and workflow agent design with practical examples.
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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
Getting Started with LLM Application Development from Scratch: A Complete Guide to Learning Paths and Career Directions
A complete beginner's guide to LLM application development: learn the three key directions (API calling, RAG, Agent), master frameworks like LangChain, and follow a step-by-step learning path to become an AI application developer.
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Tutorials·3 min
Learning LLM Application Development from Scratch: A Complete Roadmap from RAG to Agent
How to start LLM application development from scratch? A complete roadmap covering Python basics, RAG knowledge bases, and Agent development with LangChain.
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Tutorials
Decoding LLM Naming Conventions: Param…
·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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Tutorials
Running AI Models on a P106 Mining GPU…
·3 min
Running AI Models on a P106 Mining GPU: Build a Local AI Workstation for Under $10
Build a local AI workstation with a P106 mining GPU for under $10. Run Live Portrait and other AI models locally with full privacy, zero marginal cost, and incredible value.
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Tutorials
AI Code Explanation: Quickly Understan…
·2 min
AI Code Explanation: Quickly Understand Someone Else's C# Code
Learn how AI code explanation helps C# developers quickly understand others' code. A 3-step demo with Tongyi Lingma for code handoffs, Code Review, and legacy system maintenance.
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Tutorials
Efficient PyTorch Learning: A Source C…
·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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Tutorials
PyTorch Beginner Tutorial: A Complete …
·3 min
PyTorch Beginner Tutorial: A Complete Guide to Tensor Operations and Neural Network Construction
A detailed PyTorch beginner guide covering tensor operations, dynamic computational graphs, GPU acceleration, and building your first neural network with nn.Module, with learning path recommendations and code examples.
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Tutorials
Getting Started with Vibe Coding: A Ze…
·3 min
Getting Started with Vibe Coding: A Zero-to-One Guide for Product Managers
Vibe Coding lets product managers build product prototypes by describing requirements in natural language—no programming needed. Learn the core concepts, setup steps, and why PMs have a natural edge.
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Tutorials·2 min
Deep Dive into OpenAI Codex Plugin System: Architecture, Installation, and Hands-On Development
Deep dive into OpenAI Codex plugin system architecture (Skills, Apps, MCP Server), four installation methods, and a macOS app development case study showing how plugins boost AI coding efficiency.
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Product Reviews·3 min
DLSS 4.5 Deep Integration with UE5 and Multilingual AI Characters: Major NVIDIA RTX Game Development Update
NVIDIA releases major RTX update with DLSS 4.5 deep UE5 integration for frame generation performance leaps and multilingual AI characters supporting dynamic dialogue with real-time speech synthesis.
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Deep Dives
Neural Networks for Beginners: From Fu…
·1 min
Neural Networks for Beginners: From Fundamentals to Handwritten Digit Recognition
Understand neural networks from scratch. Learn input layers, hidden layers, forward propagation, backpropagation, gradient descent, with a handwritten digit recognition example.
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Tutorials·4 min
AI-Powered Research in Practice: From LLM Selection to Building Automated Workflows with N8N
A deep dive into AI-driven research methodology: LLM selection, Python automation, Zotero reference management, Overleaf writing, local LLM deployment, and N8N workflow automation.
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