#operator fusion
149 related articles
·3 min
Ideogram 4.0 Turbo Workflow: An AI Image Generation Solution Balancing Speed and Quality
Detailed look at the Ideogram 4.0 mixed turbo workflow: RTX 4090 tested at just 15s inference, matching Krea2 speed with up to 8K resolution output.
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·3 min
Ideogram 4.0 Turbo Workflow: An AI Image Generation Solution Balancing Speed and Quality
Detailed look at the Ideogram 4.0 mixed turbo workflow: RTX 4090 inference in just 15 seconds, rivaling Krea2 speed, with stable output up to 8K resolution.
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·4 min
Robot Valet Parking at Gatwick Airport: How the AGV Automated Parking System Works
London Gatwick launches UK's first robot valet parking using AGV technology, boosting parking capacity by 30-60%. Learn how the system works, its challenges, and the business case for automated parking.
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·4 min
Gemini API in Practice: Building AI Agents with Files
Google's official hands-on: how to go from idea to production fast with AI Studio and build AI Agents using the now-GA Interactions API. The core idea—Agents are just combinations of files.
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·6 min
AI Application Engineer Interview Guide: Core Topics on Model Quantization and Inference Deployment
A systematic guide to must-know AI application engineer interview topics: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.
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·6 min
AI Application Engineer Interview Guide: Core Topics in Model Quantization and Inference Deployment
A systematic review of must-know topics for AI Application Engineer interviews: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.
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·6 min
The AI Industrial Age Arrives: Compute Wars, Chip Reconstruction, and the GPT-5.6 Cheating Scandal Explained
Five key AI industry trends: Doubao surpasses 180 trillion daily calls, OpenAI's in-house AI chip, NVIDIA's $3-4 trillion compute forecast, China catching up, and the GPT-5.6 cheating scandal.
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Text-to-CAD: How AI Agents Are Reshapi…
·3 min
Text-to-CAD: How AI Agents Are Reshaping Hardware Design Workflows
Explore how the open-source text-to-cad project wraps CAD modeling as AI agent skills, letting engineers generate 3D models from natural language descriptions.
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CS Self-Study Guide: The 74K-Star Comp…
·2 min
CS Self-Study Guide: The 74K-Star Computer Science Learning Roadmap
A 74K-star GitHub project by Peking University students curates MIT, Stanford, and CMU open courses into a complete CS self-study roadmap covering algorithms, OS, databases, and more.
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Handwritten C/CUDA Inference Engine: P…
·2 min
Handwritten C/CUDA Inference Engine: Pushing Qwen 35B to the Limits on RTX 5090
A deep dive into a handwritten C/CUDA inference engine for Qwen 35B on RTX 5090 (Blackwell), covering quantization, FlashAttention kernels, and memory optimization.
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·4 min
OpenAI's 5% Equity Offer for Political Cover: Rescue Mission or High-Stakes Business Gamble?
OpenAI offers Trump's government a 5% stake for regulatory relief. We analyze the financial black hole, regulatory capture risks, and nationalization undercurrents behind this high-stakes equity gamble.
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·2 min
ExLlamaV3 v1.0.0 Official Release: Faster Inference, Lossless KV Quantization, and Streamlined Dependencies
ExLlamaV3 v1.0.0 releases with lossless KV cache quantization via kernel fusion, removal of flash-attention-2/xformers, major GEMM/GEMV gains, and broader tensor parallelism support.
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·3 min
Meta Muse Spark 1.1 Deep Dive: The Platform Ambitions Behind Meta's First Closed-Source Model
Meta Muse Spark 1.1 deep dive: native multimodal architecture, platform tools, social data retrieval, e-commerce vision — Meta's first closed-source API model benchmarks against Anthropic Sonnet.
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CUDA Kernel Fusion: A Practical Guide …
·2 min
CUDA Kernel Fusion: A Practical Guide to Reducing Memory Bandwidth and Launch Overhead
Learn how CUDA Kernel Fusion merges multiple GPU kernels to reduce global memory traffic and launch overhead, with real-world examples from AI inference and deep learning.
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How NVIDIA BioNeMo Breaks Through Co-F…
·2 min
How NVIDIA BioNeMo Breaks Through Co-Folding End-to-End Performance Bottlenecks
How NVIDIA BioNeMo Agent Toolkit uses agent-based orchestration to solve MSA preprocessing, pipeline scheduling, and end-to-end bottlenecks in OpenFold3 co-folding workloads for drug discovery.
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·4 min
From 50% to 92%: A Practical Methodology for Teaching AI Agents to Master Spreadsheets
An engineering team spent four months raising an AI coding agent's spreadsheet accuracy from 50% to 92%. Deep dive into REPL architecture, validation loops, and domain knowledge injection.
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Paper Reproduction as an Entry Point i…
·4 min
Paper Reproduction as an Entry Point into Scientific Machine Learning: Path Selection and Pitfall Guide
How can applied math students efficiently enter Scientific Machine Learning (SciML)? This guide covers the value and pitfalls of paper reproduction, with a layered path from numerical PDEs to research.
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·3 min
31 Companies Sign Agent Privacy Pact: Industry Self-Regulation Framework Goes into Effect
31 companies sign China's first AI agent privacy pact covering screen-reading authorization, training data restrictions, and payment caps. Plus: domestic LLM tops OpenRouter, Meta's $40B compute bet, and agent commercialization challenges.
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JAX Host Offloading: A Practical Guide…
·2 min
JAX Host Offloading: A Practical Guide to Breaking Through LLM Training Memory Bottlenecks
Memory capacity is the core bottleneck in LLM training. This guide explores JAX-based host offloading — covering optimizer state offloading, activation strategies, PCIe bandwidth trade-offs, and how it complements activation recomputation.
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·3 min
AI/ML Internship Red Flags: How to Spot and Land Internships That Actually Matter
Is paying for an internship worth it? This deep dive into AI/ML "internship commodification" exposes the real problems with pay-to-intern schemes and offers actionable alternatives — open source, cold outreach, and technical fundamentals.
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