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248 articles · Page 3 of 3
Architects' Tech Alliance
Architects' Tech Alliance
Apr 25, 2024 · Industry Insights

What China’s AI Labs Learned from Scaling Domestic Large‑Model Training

The article analyzes the computational characteristics and system challenges of training large AI models on domestic platforms, examines framework parallelism and future algorithms, and proposes six strategic measures—including scaling compute, improving data management, building a national R&D team, and boosting AI‑chip investment—to accelerate China’s AI leadership.

AI infrastructuredomestic AIlarge models
0 likes · 5 min read
What China’s AI Labs Learned from Scaling Domestic Large‑Model Training
DataFunSummit
DataFunSummit
Mar 31, 2024 · Artificial Intelligence

Challenges and Techniques in Distributed Training of Large Language Models

This article reviews the rapid development of large language models since 2019, outlines the historical background, identifies key challenges such as massive compute demand, memory constraints, and system complexity, and then details distributed training technologies—including data parallelism, pipeline parallelism, and advanced optimization strategies—while also discussing future research directions and answering common questions.

AI infrastructureDeepSpeedDistributed Training
0 likes · 23 min read
Challenges and Techniques in Distributed Training of Large Language Models
Architects' Tech Alliance
Architects' Tech Alliance
Mar 27, 2024 · Industry Insights

Why AI Large‑Model Training Needs Ultra‑High‑Bandwidth, Low‑Latency Networks

The rapid growth of AI model sizes has created unprecedented demands on network bandwidth, latency, stability, and automation, making efficient RDMA‑based interconnects, advanced congestion control, and intelligent deployment essential for scaling distributed training clusters to thousands of GPUs.

AI infrastructureAI trainingDistributed Computing
0 likes · 11 min read
Why AI Large‑Model Training Needs Ultra‑High‑Bandwidth, Low‑Latency Networks
Bilibili Tech
Bilibili Tech
Mar 15, 2024 · Artificial Intelligence

Hardware Resource Estimation and Bottleneck Analysis for Large Language Models (LLMs)

The article analyzes the compute, memory, and communication resources required to train and run large language models, quantifies bottlenecks such as the massive FLOP demand, terabyte‑scale GPU memory, and high‑bandwidth interconnect needs, and evaluates parallelism strategies and bandwidth estimates to guide hardware and software design for scaling LLMs.

AI infrastructureHardwareLLM
0 likes · 53 min read
Hardware Resource Estimation and Bottleneck Analysis for Large Language Models (LLMs)
DataFunSummit
DataFunSummit
Mar 14, 2024 · Artificial Intelligence

Multi‑Level Efficiency Challenges and Emerging Paradigms for Large AI Models

The article examines how large AI models are moving toward a unified, low‑knowledge‑density paradigm that raises computational efficiency challenges across model, algorithm, framework, and infrastructure layers, while also highlighting NVIDIA's GTC 2024 China AI Day sessions that showcase practical solutions and upcoming training opportunities.

AI conferencesAI infrastructureLarge Language Models
0 likes · 10 min read
Multi‑Level Efficiency Challenges and Emerging Paradigms for Large AI Models
Baidu Geek Talk
Baidu Geek Talk
Mar 6, 2024 · Artificial Intelligence

How Baidu’s BCCL Boosts Large‑Model Training with Real‑Time Observability and Fault Diagnosis

The article explains why collective communication is critical for distributed large‑model training, outlines the new requirements for system reliability, and introduces Baidu’s Collective Communication Library (BCCL), detailing its enhanced observability, fault‑diagnosis, stability, and performance optimizations that raise effective training time to 98 % and bandwidth utilization to 95 %.

AI infrastructureDistributed TrainingFault diagnosis
0 likes · 11 min read
How Baidu’s BCCL Boosts Large‑Model Training with Real‑Time Observability and Fault Diagnosis
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Mar 1, 2024 · Artificial Intelligence

How Baidu’s BCCL Boosts Distributed AI Training with Real‑Time Observability and Fault Diagnosis

Baidu’s Collective Communication Library (BCCL) enhances large‑model distributed training by improving real‑time bandwidth monitoring, fault diagnosis, network stability, and performance, leveraging RDMA networks and GPU‑specific optimizations to increase effective training time to 98% and bandwidth utilization to 95%.

AI infrastructureDistributed TrainingFault diagnosis
0 likes · 11 min read
How Baidu’s BCCL Boosts Distributed AI Training with Real‑Time Observability and Fault Diagnosis
JD Retail Technology
JD Retail Technology
Jan 30, 2024 · Artificial Intelligence

Next-Generation Multi‑GPU Synchronous Training Architecture for Large‑Scale Sparse Recommendation Models

The article details JD Retail's evolution from TensorFlow‑based sparse training to a custom high‑performance parameter server and a fully GPU‑accelerated, multi‑node, multi‑card synchronous training framework that leverages GPU‑RDMA, two‑level CPU‑DRAM/GPU‑HBM caching, and pipeline parallelism to overcome storage, I/O, and compute challenges of trillion‑parameter recommendation systems.

AI infrastructureGPU Accelerationparameter server
0 likes · 12 min read
Next-Generation Multi‑GPU Synchronous Training Architecture for Large‑Scale Sparse Recommendation Models
DataFunSummit
DataFunSummit
Jan 22, 2024 · Artificial Intelligence

Improving Efficiency of Large‑Scale AI Model Training, Fine‑tuning, and Deployment with Colossal‑AI

This article introduces Colossal‑AI, an open‑source platform that tackles the challenges of training, fine‑tuning, and deploying massive AI models by leveraging efficient memory management, N‑dimensional parallelism, and high‑performance inference to dramatically reduce cost and improve scalability across thousands of GPUs.

AI infrastructureColossal-AIDistributed Training
0 likes · 21 min read
Improving Efficiency of Large‑Scale AI Model Training, Fine‑tuning, and Deployment with Colossal‑AI
Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
Nov 11, 2023 · Cloud Computing

Alibaba Cloud Executive Discusses IPv6 Deployment, Global Collaboration, and AI‑Driven Network Evolution at the 2023 Wuzhen Internet Forum

In a detailed interview at the 2023 Wuzhen Internet Forum, Alibaba Cloud’s infrastructure lead Cai Dezhong outlines the three‑phase IPv6 rollout, highlights organizational and technical innovations, stresses the need for global cooperation, and explains how IPv6 underpins the next generation AI infrastructure and predictable high‑performance networking.

AI infrastructureGlobal CollaborationHigh-performance networking
0 likes · 9 min read
Alibaba Cloud Executive Discusses IPv6 Deployment, Global Collaboration, and AI‑Driven Network Evolution at the 2023 Wuzhen Internet Forum
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Oct 10, 2023 · Artificial Intelligence

How AI Infrastructure Fuels High‑Quality Digital Economy Growth

The article summarizes a Baidu Cloud Intelligence conference speech and whitepaper, explaining how AI foundations and large‑model infrastructure reshape applications, boost enterprise digital transformation, and drive regional economic development, offering a roadmap for high‑quality digital economy advancement.

AI infrastructuredigital economyenterprise transformation
0 likes · 11 min read
How AI Infrastructure Fuels High‑Quality Digital Economy Growth
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Sep 21, 2023 · Artificial Intelligence

How Baidu Cloud Integrates AI and Cloud to Accelerate Autonomous Driving

At the 2023 Baidu Cloud Intelligence Conference, Baidu AI Cloud outlined a comprehensive, four‑layer solution—spanning distributed cloud infrastructure, AI‑focused compute, data compliance, and end‑to‑end toolchains—to address the challenges of electric, intelligent vehicles, large‑model deployment, and regulatory compliance in autonomous driving.

AI infrastructureCloud Computingautonomous driving
0 likes · 12 min read
How Baidu Cloud Integrates AI and Cloud to Accelerate Autonomous Driving
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Sep 19, 2023 · Artificial Intelligence

BladeLLM: Ultra‑Long Context LLM Inference via RaggedAttention & AutoTuner

BladeLLM, Alibaba Cloud’s large‑model inference engine, pushes the limits of LLMs by supporting ultra‑long context lengths up to 70 K tokens, leveraging novel RaggedAttention and a DNN‑based AutoTuner to deliver superior performance, memory efficiency, and low‑latency inference across diverse workloads.

AI infrastructureAutoTunerLLM inference
0 likes · 11 min read
BladeLLM: Ultra‑Long Context LLM Inference via RaggedAttention & AutoTuner
Efficient Ops
Efficient Ops
Jun 11, 2023 · Artificial Intelligence

Why Network Bandwidth Is the Real Bottleneck for AIGC and How DDC Solves It

The article explains how AIGC models demand massive GPU compute, why network bandwidth and latency become the critical limiting factors, and how the Distributed Disaggregated Chassis (DDC) architecture addresses these challenges with scalable, high‑throughput networking solutions.

AI infrastructureAIGCDDC
0 likes · 13 min read
Why Network Bandwidth Is the Real Bottleneck for AIGC and How DDC Solves It
Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
May 19, 2023 · Artificial Intelligence

Immersion Liquid Cooling Forum on AI Infrastructure: Key Insights and Industry Perspectives

The May 15 Beijing forum gathered experts from leading tech firms and research institutes to discuss immersion liquid cooling as a vital solution for AI infrastructure's growing compute and thermal challenges, presenting current trends, technical designs, material research, and future sustainable development directions.

AI infrastructureData Centerimmersion cooling
0 likes · 7 min read
Immersion Liquid Cooling Forum on AI Infrastructure: Key Insights and Industry Perspectives
Baidu Tech Salon
Baidu Tech Salon
May 11, 2023 · Artificial Intelligence

Inside Baidu’s High‑Performance GPU Cluster: Powering the Next‑Gen AI Models

The article details Baidu's development of a massive high‑performance GPU/IB cluster, its architectural design, the challenges of training trillion‑parameter models, and how the integrated AI stack—spanning hardware, framework, and resource management—overcomes compute, memory, and communication bottlenecks to accelerate large‑model training.

AI infrastructureBaidu AI BaseDistributed Training
0 likes · 17 min read
Inside Baidu’s High‑Performance GPU Cluster: Powering the Next‑Gen AI Models
Amap Tech
Amap Tech
May 11, 2023 · Artificial Intelligence

A 20‑Year Review of AI Infrastructure Milestones

Over the past two decades, AI infrastructure has evolved from early distributed storage and MapReduce to GPU programming, modern package managers, in‑memory processing, deep‑learning frameworks, parameter servers, AI compilers, synthetic data pipelines, open‑source model hubs, and today’s large‑scale Kubernetes‑based clusters, forming the essential foundation for every breakthrough.

AI CompilersAI infrastructureBig Data
0 likes · 29 min read
A 20‑Year Review of AI Infrastructure Milestones
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
May 9, 2023 · Artificial Intelligence

How Baidu’s High‑Performance GPU Cluster Powers the Next Generation of Large‑Scale AI Models

This article explains how Baidu built a massive, high‑performance GPU/IB cluster, optimized its architecture and software stack, and integrated AI frameworks and resource management to overcome compute, memory, and communication bottlenecks, enabling efficient training of trillion‑parameter large models.

AI infrastructureCloud ComputingDistributed Training
0 likes · 19 min read
How Baidu’s High‑Performance GPU Cluster Powers the Next Generation of Large‑Scale AI Models
DataFunSummit
DataFunSummit
Apr 27, 2023 · Artificial Intelligence

Baidu's Interoperability Solutions for Federated Learning: Principles, JinKe Alliance, and the Open‑Source HIGHFLIP Protocol

The article presents Baidu's comprehensive approach to federated‑learning interoperability, covering the underlying principles, the JinKe Alliance bottom‑layer solution, the high‑level HIGHFLIP protocol, and a comparative discussion of white‑box, gray‑box, and black‑box integration strategies.

AI infrastructureBaiduHIGHFLIP
0 likes · 11 min read
Baidu's Interoperability Solutions for Federated Learning: Principles, JinKe Alliance, and the Open‑Source HIGHFLIP Protocol
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Apr 24, 2023 · Artificial Intelligence

How Alibaba’s TePDist Automates Distributed Deep Learning for Large Models

Alibaba Cloud’s PAI platform unveils TePDist, an HLO‑based automatic distributed deep‑learning system that decouples strategy search from model code, offers client/server architecture, supports SPMD and pipeline parallelism, delivers high performance on GPT, MoE and other models, and is now open‑source.

AI infrastructureDistributed Deep LearningHLO IR
0 likes · 4 min read
How Alibaba’s TePDist Automates Distributed Deep Learning for Large Models
DataFunSummit
DataFunSummit
Apr 20, 2023 · Artificial Intelligence

SenseTime Unveils Multimodal ‘SenseNova’ Large Model System and Its Industry Applications

SenseTime introduced its visual‑centric multimodal large‑model platform SenseNova, detailing model scaling, extensive AI infrastructure, diverse industry deployments such as autonomous driving and generative content, and the challenges of compute efficiency and data acquisition in the race for advanced AI.

AI infrastructurecomputer visionlarge models
0 likes · 13 min read
SenseTime Unveils Multimodal ‘SenseNova’ Large Model System and Its Industry Applications
DataFunTalk
DataFunTalk
Mar 31, 2023 · Artificial Intelligence

Estimating the Resource and Cost Requirements for Large Language Model Training and Inference

The article analyses the computational resources, hardware costs, and human investment needed to train and serve large language models such as GPT‑3, discusses practical cost calculations, highlights the challenges faced by Chinese AI teams, and argues for sustained, long‑term funding to achieve meaningful breakthroughs.

AI infrastructureChina AIcost estimation
0 likes · 14 min read
Estimating the Resource and Cost Requirements for Large Language Model Training and Inference
21CTO
21CTO
Mar 31, 2023 · Artificial Intelligence

How ColossalChat Replicates ChatGPT with a Complete Open‑Source RLHF Pipeline

ColossalChat, an open‑source project built on LLaMA, offers a full RLHF pipeline—including supervised fine‑tuning, reward‑model training, and reinforcement learning—enabling low‑cost, bilingual ChatGPT‑like models with 4‑bit quantized inference, detailed code, dataset, and performance optimizations.

AI infrastructureColossalAIRLHF
0 likes · 12 min read
How ColossalChat Replicates ChatGPT with a Complete Open‑Source RLHF Pipeline
Tencent Cloud Developer
Tencent Cloud Developer
Mar 22, 2023 · Artificial Intelligence

How AngelPTM Cuts Large Model Training Costs with ZeRO-Cache Optimizations

This article analyzes Tencent's AngelPTM framework, detailing its ZeRO-Cache strategy, unified storage management, multi‑stream async execution, SSD tiered storage, and performance benchmarks that show up to 95% larger model capacity and over 44% speedup compared to community solutions.

AI infrastructureGPU AccelerationLarge model training
0 likes · 12 min read
How AngelPTM Cuts Large Model Training Costs with ZeRO-Cache Optimizations
Baidu Geek Talk
Baidu Geek Talk
Mar 21, 2023 · Artificial Intelligence

Infrastructure Challenges and Solutions for Large‑Scale AI Model Training

The article explains how the massive compute and storage demands of today’s large language models create a “compute wall” and “storage wall,” and describes Baidu Intelligent Cloud’s four‑layer full‑stack infrastructure—combining advanced parallelism techniques, optimized GPU networking, static‑graph compilation, and cost‑model‑driven placement—to train trillion‑parameter models efficiently.

AI infrastructureCost ModelDistributed Training
0 likes · 27 min read
Infrastructure Challenges and Solutions for Large‑Scale AI Model Training
Python Programming Learning Circle
Python Programming Learning Circle
Mar 21, 2023 · Artificial Intelligence

Why Replicating ChatGPT in China Demands Massive AI Infrastructure and Cloud Computing

The article explains that reproducing ChatGPT in China is not just a matter of funding but requires extensive expertise in large‑scale language model training, massive compute resources, optimized cloud infrastructure, and deep AI research, as demonstrated by Alibaba's DAMO Academy efforts.

AI infrastructureChatGPTCloud Computing
0 likes · 10 min read
Why Replicating ChatGPT in China Demands Massive AI Infrastructure and Cloud Computing
Hulu Beijing
Hulu Beijing
Mar 16, 2023 · Artificial Intelligence

Inside Hulu’s Distributed Training Platform: Architecture, Challenges, and Solutions

This article explores Hulu’s five‑year‑old machine‑learning training platform, detailing its three‑layer architecture, the shift from single‑node to distributed training, and the technical solutions—including parameter servers, Ring AllReduce, Kubernetes, Volcano, and Horovod—that enable scalable AI workloads across GPU, CPU, and storage resources.

AI infrastructureDistributed TrainingHulu
0 likes · 13 min read
Inside Hulu’s Distributed Training Platform: Architecture, Challenges, and Solutions
Tencent Advertising Technology
Tencent Advertising Technology
Mar 2, 2023 · Artificial Intelligence

Tencent's HunYuan‑NLP 1T Large‑Scale AI Model: Training Techniques, Optimization, and Real‑World Applications

This article details Tencent's development of the 1‑trillion‑parameter HunYuan‑NLP model, covering its MoE architecture, cost‑effective pre‑training strategies, distributed training framework, model compression toolkit, and successful deployment across advertising, gaming, and other Tencent services.

AI infrastructureMixture of Expertslarge language model
0 likes · 17 min read
Tencent's HunYuan‑NLP 1T Large‑Scale AI Model: Training Techniques, Optimization, and Real‑World Applications
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Feb 23, 2023 · Artificial Intelligence

How Baidu’s Cloud Infrastructure Tackles the Challenges of Training Massive AI Models

This article explains how Baidu's intelligent cloud overcomes the compute and storage walls of large‑scale model training by combining hardware design, network topology, and software optimizations such as pipeline, tensor, and expert parallelism, cost‑model‑driven placement, and future‑proof AI infrastructure evolution.

AI infrastructureBaidu CloudCost Model
0 likes · 28 min read
How Baidu’s Cloud Infrastructure Tackles the Challenges of Training Massive AI Models
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Nov 11, 2022 · Artificial Intelligence

Large-Scale Deep Learning Systems and Their Application at Xiaohongshu (RED)

Xiaohongshu’s in‑house LarC platform powers real‑time, multimodal recommendation, life‑search, and generative‑AI commercial content for its 200 million‑user community by processing billions of daily feedback samples, employing conflict‑free parameter servers, diversified sequence modeling, and large‑scale representation learning to deliver personalized, fresh, and diverse user experiences.

AI infrastructureMachine Learning PlatformXiaohongshu
0 likes · 13 min read
Large-Scale Deep Learning Systems and Their Application at Xiaohongshu (RED)
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Jul 13, 2022 · Artificial Intelligence

Unlocking GPU Efficiency: Baidu’s Dual‑Engine Container Virtualization for AI

This article explores Baidu’s cutting‑edge GPU container virtualization architecture, detailing the challenges of low GPU utilization in AI workloads, the dual‑engine (user‑space and kernel‑space) isolation mechanisms, various mixing strategies, performance evaluations, and best‑practice recommendations for maximizing resource efficiency in large‑scale AI deployments.

AI infrastructureGPU virtualizationMixed Scheduling
0 likes · 31 min read
Unlocking GPU Efficiency: Baidu’s Dual‑Engine Container Virtualization for AI
Baidu Geek Talk
Baidu Geek Talk
Jul 6, 2022 · Artificial Intelligence

Why Training Massive AI Models Demands New Cluster Architectures and Parallelism Strategies

The article examines the industry trend toward ever‑larger AI models, compares their parameter scale to the human brain, outlines the computational and memory challenges of training such models, and details advanced parallelism techniques and Baidu's high‑performance cluster solutions that enable efficient, stable large‑scale model training.

AI infrastructureBaiduCluster Computing
0 likes · 17 min read
Why Training Massive AI Models Demands New Cluster Architectures and Parallelism Strategies
ITPUB
ITPUB
Jun 2, 2022 · Artificial Intelligence

Why AI Needs Modular Infrastructure: Lessons from LLVM and the Future of ML Systems

The article examines how monolithic AI toolchains hinder innovation, recounts the historical fragmentation of software in the 1990s, highlights LLVM's modular architecture as a turning point, and argues for a new, composable AI infrastructure to make machine learning more accessible and scalable.

AI infrastructureLLVMML compilers
0 likes · 11 min read
Why AI Needs Modular Infrastructure: Lessons from LLVM and the Future of ML Systems
DataFunTalk
DataFunTalk
Apr 17, 2022 · Artificial Intelligence

DeepRec: Alibaba’s Sparse Model Training Engine – Architecture, Features, and Open‑Source Status

DeepRec, developed since 2016 by Alibaba, is a specialized sparse‑model training engine that addresses feature elasticity, training performance, and deployment challenges through dynamic elastic features, optimized runtimes, distributed training frameworks, incremental model export, and multi‑level storage, and is now being open‑sourced for broader industry collaboration.

AI infrastructureDeepRecruntime optimization
0 likes · 15 min read
DeepRec: Alibaba’s Sparse Model Training Engine – Architecture, Features, and Open‑Source Status
DataFunTalk
DataFunTalk
Mar 16, 2021 · Artificial Intelligence

Weibo Multimodal Content Understanding Service Architecture and GPU Heterogeneous Cluster Solutions

This article details Weibo's large‑scale multimodal content understanding platform, covering its background, data and model heterogeneity challenges, the end‑to‑end workflow, GPU‑heterogeneous cluster design, resource scheduling, performance optimization for distributed training and online inference, and comprehensive monitoring to ensure stable, low‑latency AI services.

AI infrastructureDistributed TrainingGPU clustering
0 likes · 17 min read
Weibo Multimodal Content Understanding Service Architecture and GPU Heterogeneous Cluster Solutions
DataFunTalk
DataFunTalk
Nov 24, 2020 · Artificial Intelligence

Building Next‑Generation Data Intelligence Infrastructure with Knowledge Graphs: From New Infrastructure to Cognitive AI Platforms

This presentation explains how knowledge graphs serve as the foundation for new‑infrastructure initiatives, detailing the evolution of AI from perception to cognition, the role of big‑data centers, DIKW modeling, intelligent data governance, and the construction of a cognitive AI middle‑platform for industry applications.

AI infrastructureArtificial IntelligenceBig Data
0 likes · 18 min read
Building Next‑Generation Data Intelligence Infrastructure with Knowledge Graphs: From New Infrastructure to Cognitive AI Platforms
360 Tech Engineering
360 Tech Engineering
Sep 14, 2020 · Artificial Intelligence

TensorNet: A Distributed Training Framework Optimized for Large-Scale Sparse Feature Models on TensorFlow

TensorNet is a TensorFlow‑based distributed training framework that tackles the challenges of massive data and billions of sparse parameters in advertising and recommendation systems by enabling near‑infinite sparse feature dimensions, drastically reducing synchronization overhead, and delivering up to 35% inference speed improvements.

AI infrastructureDistributed TrainingTensorFlow
0 likes · 8 min read
TensorNet: A Distributed Training Framework Optimized for Large-Scale Sparse Feature Models on TensorFlow
JD Tech Talk
JD Tech Talk
Jun 3, 2020 · Artificial Intelligence

JD Digital Science Unveils Fast Secure Federated Learning Framework and Two Industry‑First Techniques

JD Digital Science introduced its fast secure federated learning framework, highlighted two pioneering technologies—a kernel‑based nonlinear federated learning algorithm and a distributed fast homomorphic encryption method—both accepted at KDD 2020, and discussed their industrial applications, privacy benefits, and regulatory relevance.

AI infrastructureKDD2020Kernel Methods
0 likes · 6 min read
JD Digital Science Unveils Fast Secure Federated Learning Framework and Two Industry‑First Techniques
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 17, 2020 · Artificial Intelligence

How AI Engineering Powers Modern Enterprises: From Deep Learning to Cloud Infrastructure

This article explores the fundamentals and evolution of artificial intelligence, its applications in perception and decision‑making, the role of deep learning, the importance of compute power and cloud platforms, and how enterprises can strategically adopt AI and data‑driven solutions to drive business value.

AI infrastructuremachine learning
0 likes · 15 min read
How AI Engineering Powers Modern Enterprises: From Deep Learning to Cloud Infrastructure
AntTech
AntTech
Oct 17, 2019 · Artificial Intelligence

From a 30‑Year Coding Journey to AI Infrastructure: Wang Yi’s Story and the Open‑Source Projects SQLFlow and ElasticDL

The article chronicles Wang Yi’s three‑decade programming career, his moves across Tencent, Google, Baidu and Ant Financial, and explains how his open‑source AI infrastructure projects SQLFlow and ElasticDL transform model development for analysts while promoting a culture of code review and practical engineering.

AI infrastructureCode ReviewElasticDL
0 likes · 12 min read
From a 30‑Year Coding Journey to AI Infrastructure: Wang Yi’s Story and the Open‑Source Projects SQLFlow and ElasticDL
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 12, 2019 · Artificial Intelligence

How Alibaba’s PAISoar Accelerates Deep Learning: 101× Speedup on 128 GPUs

Alibaba engineers detail the PAISoar distributed training framework, showing how RDMA‑optimized hardware, Ring AllReduce algorithms, and user‑friendly APIs boost deep‑learning models—like the GreenNet CNN—to 101‑fold speedups on 128 GPUs, dramatically reducing training time from days to under a day.

AI infrastructureDistributed TrainingGPU Acceleration
0 likes · 17 min read
How Alibaba’s PAISoar Accelerates Deep Learning: 101× Speedup on 128 GPUs
Didi Tech
Didi Tech
Apr 4, 2019 · Artificial Intelligence

DiDi Machine Learning Platform: From Workshop‑Style Production to Cloud‑Native Architecture

Since 2016 DiDi has evolved its machine‑learning platform from isolated, workshop‑style GPU servers to a cloud‑native, Kubernetes‑driven architecture that unifies resource management, introduces custom parameter‑server and serving frameworks, provides autotuning, external SaaS offerings such as Elastic Inference and JianShu, and aims for a 3.0 unified internal‑external AI marketplace.

AI infrastructureGPU computingKubernetes
0 likes · 19 min read
DiDi Machine Learning Platform: From Workshop‑Style Production to Cloud‑Native Architecture
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 18, 2019 · Artificial Intelligence

How Alibaba’s Open‑Source Euler Framework Powers Large‑Scale Graph Deep Learning

Euler, Alibaba's newly open‑sourced graph deep‑learning framework, combines distributed graph processing with neural network training to handle billions of nodes and edges, supports heterogeneous graphs, offers built‑in algorithms, and has already boosted advertising, fraud detection, and other industry applications.

AI infrastructureDistributed ComputingEuler framework
0 likes · 11 min read
How Alibaba’s Open‑Source Euler Framework Powers Large‑Scale Graph Deep Learning
Meituan Technology Team
Meituan Technology Team
Oct 25, 2018 · Artificial Intelligence

Deep Learning System Design and Parallel Computing Solutions at Meituan

Meituan built a custom deep‑learning platform that combines data‑parallel and hybrid parallelism across multi‑GPU/cluster hardware, uses coarse‑grained scheduling and Kaldi‑derived acoustic algorithms, and supports fast NLU model hot‑updates, achieving near‑linear GPU scaling and 6–7× speedups over traditional solutions.

AI infrastructureNLUacoustic modeling
0 likes · 13 min read
Deep Learning System Design and Parallel Computing Solutions at Meituan
Architecture Digest
Architecture Digest
Aug 15, 2017 · Artificial Intelligence

Why AI Engineers Must Understand Basic Infrastructure: From Big Data to Deep Learning

The article explains why AI engineers need foundational infrastructure knowledge—covering big‑data processing, cloud services, containerization, MapReduce, and deep‑learning platforms—to effectively solve real‑world problems, collaborate with teams, and build scalable, maintainable AI solutions.

AI infrastructureBig DataCloud Computing
0 likes · 14 min read
Why AI Engineers Must Understand Basic Infrastructure: From Big Data to Deep Learning
21CTO
21CTO
Jul 16, 2017 · Artificial Intelligence

Why Every AI Engineer Must Master Infrastructure Basics

In the AI era, engineers need more than cutting‑edge algorithms—they must understand infrastructure, deployment, scalability, and team collaboration, as illustrated by four practical reasons and Google’s architectural breakthroughs that bridge big data, machine learning, and deep learning.

AI infrastructureCloud ComputingGoogle
0 likes · 17 min read
Why Every AI Engineer Must Master Infrastructure Basics