#EAGLE3
20 related articles
·4 min
Disaster and Glory of the Apollo Program: The History We Must Revisit Before Returning to the Moon
From the fatal Apollo 1 fire to Apollo 8's daring lunar orbit to Apollo 11's successful landing—revisiting the disasters, fears, and compromises of the Apollo program and their lessons for today's return to the Moon.
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·2 min
DSpark: DeepSeek Partners with Peking University to Open-Source Inference Acceleration, Boosting Speed by Up to 85%
DeepSeek partners with Peking University to open-source DSpark, an inference acceleration tech boosting single-user speed by 57%-85% under high concurrency. Learn its three core designs and the DSpec framework.
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·2 min
DSpark: DeepSeek and Peking University Open-Source Inference Acceleration Tech with Up to 85% Speed Boost
DeepSeek and Peking University open-source DSpark, an inference acceleration tech boosting single-user generation speed by 57%-85% under high concurrency. Learn its 3 core designs and the DSpec framework.
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·2 min
D-Flash: How Diffusion Drafting Delivers 3.5x Faster LLM Inference
D-Flash solves the autoregressive drafter latency bottleneck in speculative decoding via fast diffusion parallel drafting and target feature KV injection. 16 tokens in just 6ms, up to 3.5x speedup on HumanEval, beating EAGLE3 and MTP.
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·3 min
D-Flash: The Secret Behind 3.5x LLM Inference Speedup with Diffusion Drafting
D-Flash uses fast diffusion parallel drafting and target feature KV injection to solve the autoregressive Drafter latency bottleneck in speculative decoding. 16 tokens in just 6ms, up to 3.5x speedup on HumanEval, surpassing EAGLE3 and MTP.
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·3 min
DeepSeek Open-Sources DeepSpec: A Full-Stack Speculative Decoding Library with 60–85% Inference Speedup
DeepSeek open-sources DeepSpec, a full-stack speculative decoding library delivering 60–85% inference speedup and up to 661% throughput gains in production. MIT license, 9 checkpoints, 9 benchmarks.
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·3 min
Codex in Action: A Complete Guide to Building a WeChat Mini Program with AI — No Coding Experience Required
A complete walkthrough of building and launching a WeChat Mini Program using OpenAI Codex and ChatGPT — from AI prototyping to ICP filing. MVP delivered in 5 days, no coding required.
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·3 min
Musk vs. OpenAI: A Full Legal Breakdown of the Two-Hour Jury Verdict
Musk's lawsuit against OpenAI and CEO Sam Altman ended in a two-hour jury defeat. A full legal breakdown: from OpenAI's founding, its for-profit pivot, to the statute of limitations that proved fatal.
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·4 min
DSpark Open Source: DeepSeek's Inference Acceleration Tech That Doubles LLM Speed
DeepSeek and Peking University open-source DSpark, an inference acceleration technology using semi-autoregressive architecture and dynamic scheduling to boost LLM speed by 50%+ and double GPU concurrency without quality loss.
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·3 min
DeepSeek Open-Sources DSpark: 50%–400% LLM Inference Speedup Without Retraining
DeepSeek open-sources DSpark, delivering 50%–400% LLM inference speedup with no retraining or quantization, via semi-autoregressive drafting and confidence-scheduled verification.
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·4 min
Quantum Optimization with QAOA + Elastic Net: A Practical Look at Genomic Variant Selection
An in-depth look at Q-FH Explorer's latest iteration: replacing XGBoost with Elastic Net for high-dimensional genomic data and adding QAOA quantum optimization for variant selection, reaching R²=0.655.
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·2 min
Deep Dive into Tencent Hunyuan Hy3: How a 295B MoE Model Cracks the Agent Deployment Challenge
Tencent Hunyuan Hy3 launches with a 295B MoE architecture activating just 21B params and 256K context. Hallucination cut from 12.5% to 5.4%, MRCR nearly doubled, with MTP and EAGLE decoding and Day-0 SGLang support.
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·5 min
DeepSeek Boosts Inference Speed by 85%: How Speculative Decoding Is Reshaping the AI Speed Race
DeepSeek and Peking University's DS Spark paper boosts AI inference speed by up to 85% via confidence scheduling and semi-autoregressive speculative decoding — no model or GPU changes.
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·5 min
DeepSeek DSpec Hands-On: How Speculative Decoding Accelerates LLM Inference by 6x
Hands-on report on DeepSeek's open-source inference acceleration toolkit DSpec: draft model + smart scheduling delivers lossless speedup, hitting acceptance length 6 on GSM8K and reproducing official data.
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·3 min
DeepSeek Open-Sources DiSpark: Up to 85% Faster AI Inference Without Changing Hardware
DeepSeek and Peking University release DiSpark, an open-source framework that speeds up LLM inference by 60–85% using speculative decoding and hierarchical verification — no hardware changes or retraining required.
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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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Tutorials·3 min
DeepSeek V4 Flash MTP Speculative Decoding Real-World Test: A Guide to 20% Faster Local Inference
Real-world testing of DeepSeek V4 Flash with MTP speculative decoding: ~20% speedup for code generation, minimal gains for text. Covers memory overhead, accuracy differences, Q4 vs Q3 quantization, and full deployment tutorial.
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Tech Frontiers·3 min
Google Introduces AI Assistant in Job Interviews, OpenAI Launches Cybersecurity-Specific Model GPT-5.5 Cyber
Google introduces Gemini AI assistant in hiring to assess AI proficiency, OpenAI launches GPT-5.5 Cyber for critical infrastructure defense, Anthropic nears trillion-dollar valuation, Mozilla fixes 271 Firefox bugs with AI in two months.
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Tech Frontiers·1 min
RNDA Data Protocol Explained: How 256-Byte Encoding Makes Raw Data Disappear Forever
Deep dive into the RNDA data protocol: 256-byte encoding permanently destroys raw data across 31 data types including genomics and quantum circuits.
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Product Reviews·2 min
ZeroClaw vs OpenClaw In-Depth Comparison: How to Choose Between Lightweight AI Agent Frameworks
In-depth comparison of ZeroClaw vs OpenClaw AI Agent frameworks: Rust static binary vs Node.js runtime, 5MB vs 2GB memory, installation experience, and ideal use cases.
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