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AI Infra

7 articles · Page 1 of 1
ThinkingAgent
ThinkingAgent
Jul 19, 2026 · Artificial Intelligence

AI Infra in Practice #11: Cross‑Cut Release Governance – Full Versioning of Prompts, Models, and RAG

A real‑world incident where a tiny Prompt tweak caused a two‑day outage illustrates why AI systems need CI/CD‑style versioning and gated release for six objects—code, Prompt, model, RAG index, tool schema, and workflow—so that changes are traceable, safely rolled out, and quickly reverted.

AI InfraL7 Evaluation GateModel Registry
0 likes · 31 min read
AI Infra in Practice #11: Cross‑Cut Release Governance – Full Versioning of Prompts, Models, and RAG
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Jun 29, 2026 · Artificial Intelligence

How to Maximize Cosmos‑3 Training Throughput Without NVLink Using AI Infra Optimizations

By applying systematic AI Infra engineering—optimizing data loading, I/O pipelines, activation checkpointing, torch.compile, and multi‑node scaling—the Cosmos‑3‑Nano‑Policy‑DROID model achieved an 89× faster startup, 99.3% higher single‑node throughput, 0.42 MFU, and 98.3% scaling efficiency across 12 nodes, all without NVLink.

AI InfraActivation CheckpointingCosmos 3
0 likes · 13 min read
How to Maximize Cosmos‑3 Training Throughput Without NVLink Using AI Infra Optimizations
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
May 27, 2026 · Artificial Intelligence

Optimizing Large Model Inference Architecture for the Agent Era: Engineering Practices and Challenges

The article analyzes the architectural challenges of large‑model inference in the Agent era—such as memory‑intensive MLA structures, MoE communication overhead, exploding KV‑Cache size, and tool‑call accuracy—and presents a series of engineering solutions including hierarchical KV‑Cache pooling, sequence parallelism, offloading strategies, and chip‑level adaptations to achieve higher throughput and lower token costs.

AI InfraAgentDeepSeek
0 likes · 15 min read
Optimizing Large Model Inference Architecture for the Agent Era: Engineering Practices and Challenges
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
May 22, 2026 · Artificial Intelligence

How Baidu Baige’s Full‑Stack AI Infra Accelerates Embodied Model Iteration

The article details Baidu Baige’s end‑to‑end AI infrastructure for embodied intelligence, covering VLA and world‑model architectures, scaling challenges for medium‑sized models, cloud‑based motion‑control pipelines, open‑source integration, hardware‑aware training optimizations, and simulation‑engine improvements that together speed up model development and deployment.

AI InfraBaidu BaigeSimulation
0 likes · 13 min read
How Baidu Baige’s Full‑Stack AI Infra Accelerates Embodied Model Iteration
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Sep 26, 2024 · Artificial Intelligence

How Alibaba Cloud’s PAI Tackles Large‑Model Training and Inference Challenges in 2024

At the 2024 Yunqi Conference, Alibaba Cloud’s AI Infra experts detailed the latest challenges of large‑model deployment—such as hardware costs, resource management, and software‑hardware coordination—and introduced PAI’s new capabilities, including stability tools, automated distributed training, reinforcement‑learning frameworks, inference optimizations, and integrated big‑data AI solutions.

AI InfraDistributed Trainingbig data integration
0 likes · 14 min read
How Alibaba Cloud’s PAI Tackles Large‑Model Training and Inference Challenges in 2024
AntTech
AntTech
Jul 12, 2023 · Artificial Intelligence

Hybrid Embedding Architecture for Large‑Scale Sparse CTR Models

This article describes the Hybrid Embedding solution proposed by Ant AI Infra to address storage, resource, and feature‑governance challenges of massive sparse CTR models, detailing its multi‑layer storage design, KV‑based parameter server, and performance gains in large‑scale recommendation systems.

AI InfraCTRHybrid Embedding
0 likes · 9 min read
Hybrid Embedding Architecture for Large‑Scale Sparse CTR Models