#Router Replay
14 related articles
·3 min
Stickblade Arena: A New Benchmark That Pits LLMs Against Each Other in a Physics-Based Combat Arena
Stickblade Arena is a physics-engine-based LLM benchmark where models battle in a 2D arena, testing spatial reasoning and dynamic decision-making while avoiding training data leakage. Its six-axis Elo system reveals fine-grained capability differences.
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·3 min
Why We Abandoned Our LLM Router: Lessons in Over-Engineering
An in-depth analysis of why teams are abandoning LLM routers, exploring hidden complexity costs, outdated cost assumptions, and how to avoid over-engineering in AI systems.
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·3 min
Is LLM Inference Actually Profitable? Breaking Down the Cost Structure and Business Logic of Large Model Inference
A deep dive into LLM inference cost structure and profitability models—from GPU throughput, MoE architecture, and KV Cache to scale effects—revealing the business logic behind API price wars.
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·3 min
Chinese Open-Source AI Conquers Silicon Valley: The Industry Upheaval Behind a 58% Compute Share
Chinese open-source AI models surged from under 10% to 58% of U.S. AI consumption. Kimi K3, DeepSeek, and Qwen are reshaping AI cost structures as DoorDash, Airbnb, and other Silicon Valley giants adopt them at scale.
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·5 min
Will Chinese Open-Source Models Burst the US AI Bubble? A Deep Dive into the Transmission Chain
Chinese open-source models like Kimi K3 and DeepSeek approach US closed-source performance at a fraction of the cost. This deep dive analyzes the transmission chain from price competition to valuation reassessment.
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·3 min
Chinese Open-Source AI Conquers Silicon Valley: The Industry Upheaval Behind a 58% Compute Share
Chinese open-source AI models surged from under 10% to 58% of U.S. market share. Kimi K3, DeepSeek, and Qwen are being adopted by DoorDash, Airbnb, and other Silicon Valley giants, reshaping AI costs and competition.
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·7 min
OpenClaw vs Hermes: An In-Depth Comparison and Selection Guide for AI Agent Tools
An in-depth comparison of OpenClaw and Hermes Agent, covering skill management, memory mechanisms, security, and gateway configuration to help you find the right AI agent solution.
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·7 min
The Prompt is the Platform: How AI Agents Deeply Participate in System Design and Specification
Resonate's founder proposes "The Prompt is the Platform": as AI agents generate production-grade implementations from abstract specs, engineers' value shifts to specification. A deep dive into deterministic simulation and forbidden-fruit debugging.
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·4 min
Building an AI Agent Framework from Scratch: Deep Dive into Tool Calling, Memory, and Dual-Model Scheduling
Build an AI Agent from scratch — no frameworks. Deep dive into Function Call schema design, MCP remote mirroring, dual-model routing, and short-term memory management.
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·4 min
AirDrop and Quick Share Security Vulnerabilities: Hidden Risks in Wireless Transfer Protocols
A deep dive into AirDrop and Quick Share wireless transfer protocol security — covering device discovery, handshake auth, data parsing attack surfaces, and practical defense recommendations.
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·6 min
Claude Team Edition Launches as Encrypted Reasoning Controversy Sparks AI Transparency Debate
Anthropic launches Claude for team collaboration while encrypted reasoning controversy erupts. Plus Sakana AI's routing model and OpenAI's alignment research breakthroughs.
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·3 min
StepFun STEP3.7 Flash Tops AA Benchmark — Multimodal Reasoning Speed Takes Off
StepFun STEP3.7 Flash tops Artificial Analysis benchmark in speed, cost-efficiency, and multimodal. AI safety leaders call for legislation, embodied AI gets 300K-home training ground, Huawei Cloud unveils Agentic Infra.
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Research·3 min
Inside Cursor Composer 2 Training: A Complete Breakdown of Its Distributed Reinforcement Learning Architecture
Deep dive into how Cursor trained Composer 2 on Fireworks: async pipeline architecture, MoE numerical precision challenges, Router Replay, and global distributed GPU coordination.
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Research·2 min
Technical Breakdown of Cursor Composer 2's Distributed RL Training
Deep dive into how Cursor trained Composer 2 via distributed RL, covering async pipelines, MoE numerical alignment, global weight sync, and more.
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