111 related articles

Deep dive into building a YOLO26n object detection inference engine from scratch using ARM64 assembly and C, covering NEON SIMD, Winograd convolution, GEMM micro-kernels, and cache tiling optimizations.

An AI practitioner tests Opus 5: powerful capabilities but painfully slow inference. Deep analysis of how LLM competition is shifting from intelligence to inference speed.

A maker builds a DIY companion robot with NVIDIA Jetson Orin and 4S LiPo battery. Explore the full development journey from first power-up to AI interaction, including edge computing, power design, and companion robot trends.
Intelligent Model Routing: The Core Te…
Intelligent Model Routing is becoming key AI infrastructure. This article explores its principles, solution types, technical challenges, and implementation considerations to help developers balance cost, latency, and quality.

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.

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.

Set up an AI coding workstation on NVIDIA Jetson using VS Code + Claude Code. Covers JetPack NVIDIA Skills, token budget management, headless SSH dev, and coding agent best practices.
Moonshine: A Low-Latency Speech Engine…
Moonshine is an open-source, C++-based low-latency speech engine combining STT, intent recognition, and TTS for building voice agents. 9,400+ GitHub Stars.
NVIDIA DeepStream 9.1 Multi-Camera 3D …
A deep dive into NVIDIA DeepStream 9.1 multi-camera 3D tracking: cross-camera Re-ID, 3D coordinate fusion, GPU-accelerated pipelines, and real-world deployments in retail, warehousing, and security.
Apple M7 Ultra Leaked: Can 1.5TB Unifi…
Apple's M7 Ultra chip rumored to feature 1.5TB unified memory targeting NVIDIA Blackwell-level AI performance. A deep dive into UMA advantages, what "matching Blackwell" really means, and Apple's AI strategy.
Fine-Tuning Cosmos Models in One Day w…
NVIDIA uses Autonomous Coding Agents and Agent Skills with TAO to fine-tune Cosmos visual reasoning models in one day, achieving over 90% accuracy.

How should a CS+Stat junior efficiently prep for data/ML internships? We break down the real market gap, skill priorities, and a focused 3-month strategy.

OpenAI removes the controversial 5-hour usage limit and raises subscription quotas. As competition with Anthropic, Google, and others intensifies, users are winning big in the AI arms race.
4 Alternatives for Running CUDA on Non…
A deep dive into running CUDA on non-NVIDIA hardware (AMD, Intel): comparing ROCm/HIP, ZLUDA, SYCL/oneAPI, and OpenCL across principles, use cases, and limitations.
CUDA Kernel Fusion: A Practical Guide …
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.
How NVIDIA BioNeMo Breaks Through Co-F…
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.
Computer Vision Career Paths: A Guide …
Is Computer Vision worth pursuing as a career? This guide covers CV job market realities, master's vs. industry tradeoffs, edge deployment skills, and how to transition toward multimodal AI engineering.

A comprehensive decision framework for production LLM deployment: model selection (open-source vs. API), GPU VRAM configuration, and inference engine comparison including vLLM and TensorRT-LLM.

SentinelCV is an open-source YOLOv8-based fall detection system that works with existing CCTV and IP cameras. Get real-time alerts via Telegram — no new hardware needed.

A deep dive into Distributed AI Systems: a new book distilling 10 years of AI engineering experience covering distributed training, inference optimization, and production model serving.