1954 related articles

Complete guide to deploying production-grade LLM inference on Kubernetes, covering GPU scheduling, vLLM engine selection, autoscaling, observability, and cost optimization.

Facing GPU fragmentation on edge devices, the PostSlate team used ncnn's Vulkan backend for cross-platform ML inference, achieving 10× speedup on RTX 4070 with half the model size and zero runtime installation.

Complete guide to DeepSeek-OCR from vLLM inference deployment and Unsloth model loading to fine-tuning, covering cloud server setup, GPU selection, and code examples — all on a single 4090 GPU.

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.

Agent A1 is a 35B MoE open-source model from Shanghai's Intern Science, activating only 3B params. Hits 95 tok/s on M4 Mac Studio. Supports 256K context, tool calling, and free local deployment via Ollama.

A deep dive into vLLM's five core features — KV cache management, continuous batching, and distributed inference — plus a full setup guide for deploying DeepSeek on a cloud server.
Java Local LLM Inference: Low-Latency …
Learn how Java and OpenJDK Panama FFM API enable local LLM inference. Explore the technical foundations, JVM ecosystem benefits, and low-latency AI deployment in enterprise Java systems.

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.

A deep dive into distributed AI systems engineering: data/model/tensor parallelism for training, KV cache, quantization, elastic scaling for inference, and cloud deployment with Kubernetes, Ray, and DeepSpeed.

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.

Deep dive into Firebase AI Logic: server-side prompt templates to prevent leakage, Cloud Function triggers, four-layer security defense, AI monitoring with context caching for cost control, and cross-platform hybrid inference.

Google Hybrid Inference now supports iOS, adds Gemma 4 on Android, and Chrome local Web inference nears GA. A deep dive into hybrid inference technology, cross-platform advantages, and developer opportunities.

Google Hybrid Inference officially supports iOS, adds Gemma 4 on Android, and Chrome local Web inference nears GA. A deep dive into hybrid inference technology, cross-platform advantages, and developer opportunities.
TutorialsComplete guide to ONNX neural network exchange format: PyTorch and TensorFlow model export, ONNX Runtime inference, MNIST classifier deployment, and HuggingFace model downloads with runnable code examples.
Deep DivesDeep dive into pipeline friction in AI model deployment from training to production, covering TensorRT automated optimization, ONNX export, and Triton Inference Server best practices.

Exploring how to synthesize 190° fisheye driving videos based on camera calibration parameters, analyzing how geometric consistency impacts ADAS perception model training, and the opportunities and domain gap challenges of synthetic data in surround view systems.

Deep dive into how Tokens evolved from a technical concept in LLMs to the core unit of measurement in the AI economy. Exploring Token consumption explosion, cost optimization, and Token economics.

A deep dive into the complete workflow of training a 1.3B parameter LLM from scratch, covering Transformer architecture design, data preparation, and distributed training optimization.

An Ollama Max paid user's account was banned with a 403 error just two weeks after subscribing, with no support response in three days. Analysis of causes and practical appeal solutions.