93 related articles
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.

Why do CNNs and RNNs fail on unordered matrix data? Learn about permutation invariance, Deep Sets, and Set Transformer to pick the right architecture for set-based classification.

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.

A deep dive into two frontier dense retrieval works: Hobbit uses gradient analysis to automatically construct hard batches; Disco replaces single-document competition with submodular collaborative coverage, reshaping Top-K retrieval.

A deep dive into building verifiable, self-evolving Agent automation loops with Claude Code and Codex — covering Loop Contracts, four trigger types, three-phase execution architecture, and Evolve Loops.

Semantic caching uses vector embeddings to match similar queries and avoid redundant LLM calls, cutting AI app costs by up to 50%. Learn how it works, how to set thresholds, and when to use it.

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.

OpenAI merges ChatGPT and Codex into a super app and releases three new GPT-5.6 models: Sol, Terra, and Luna. A deep dive into four hands-on workflows—Computer Use, Loops, and multi-threading—for the AI agent era.

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.

Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.

A deep dive into the five genuinely tough challenges of production MLOps: fault-tolerant training on Spot instances, cross-team GPU scheduling, data reproducibility, model observability, and inference cost optimization.

SlickToken is a GPU fleet and agentic workflow planning tool for AI teams, supporting offline simulation, load testing, and capacity planning—no internet required to protect enterprise data.

Just 12 days after a rival launch, OpenAI released GPT-5.6, scoring 91.9% on Terminal-Bench 2.1 to surpass competitors. Ultra mode supports multi-agent collaboration, inference hits 750 tokens/sec.
Local Coding Agents in Practice: A Com…
An in-depth look at local coding agents—core concepts, advantages, and real challenges. Compare against Claude Code and learn to build a zero-subscription, private AI coding workflow with open-weight models.

OpenAI released three GPT-5.6 models—Sol, Terra, and Luna—covering everything from flagship reasoning to lightweight speed. A deep dive into their positioning, performance differences, pricing, and industry signals.

An in-depth look at why CPU and GPU utilization is low in RL training, covering vectorized environment parallelism, distributed Actor-Learner architectures, GPU-side simulation (Isaac Gym/Brax), and Ray RLlib practice.

An in-depth analysis of the vLLM inference framework's core principles: from the meaning of throughput (tokens/s), to the bottlenecks of autoregressive generation, to KV Cache, PagedAttention, and continuous batching.

GPT-5.6 Sol or Grok 4.5 — both at $20/month, but which delivers more value? We break down use cases, intelligence benchmarks, and ecosystem tradeoffs to help you decide.

MosiAI open-sources MOSS-Transcribe-Diarize-0.9B: unified speech transcription and speaker diarization, 128K context for 90-min audio, hotword boosting, SGLang Day-0 support, edge-deployable.