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While most eyes remain on familiar AI giants, China’s Alibaba and DeepSeek are unveiling open‑source video and inference models that run on consumer GPUs, sparking a regulatory scramble and threatening the dominance of closed‑source AI, heralding a rapid, disruptive shift across the industry.
Alibaba Mama’s advertising platform migrated from a monolithic Flink‑Kafka pipeline to a layered Paimon lakehouse, adding DWS upsert support and multi‑layer storage, which delivers minute‑level data freshness, cuts latency by 2.5 hours, reduces resource use over 40 %, halves development effort and achieves ≥99.9 % availability.
Alibaba has released the open‑source Qwen QwQ‑32B model, a 32‑billion‑parameter LLM that matches DeepSeek‑R1's performance while being deployable on consumer‑grade GPUs, and the announcement is accompanied by extensive promotional offers for AI‑related products and services.
Apple’s new Apple Intelligence platform, unveiled at WWDC24, will incorporate Alibaba’s Qwen 2.5 Max model to create China‑specific AI features for iPhone users, with a custom dataset and regulatory submission, marking a shift from overseas ChatGPT reliance to a domestic partnership.
Apple’s recent decision to partner with Alibaba as its AI collaborator in China reflects the iPhone’s sales slump, regulatory pressures, and Alibaba’s superior large‑model performance, cloud infrastructure, and compliance expertise, a move that could boost Apple’s market share while propelling Alibaba Cloud’s revenue and showcasing China’s rising AI capabilities.
Apple’s steep sales decline in China has driven it to partner with Alibaba’s Qwen AI platform, a move that blends cutting‑edge large‑model technology, cloud scalability, and local compliance to revive iPhone market share and showcase China’s rising AI prowess.
This article introduces the basic concepts of supervised and unsupervised machine learning, explains the core mechanisms of large language models such as Transformers, and provides a step‑by‑step guide with code to build a simple chatbot using Alibaba's Tongyi LLM via Spring Boot.
The cloud‑native large‑scale cloud‑edge collaborative computing platform jointly developed by Alipay, Zhejiang University, Xieyun Technology and Alibaba Cloud won the 2023 Zhejiang Science and Technology Progress First Prize, showcasing breakthroughs in unified resource scheduling, million‑node management, patents, papers and open‑source contributions.
On May 18, 2024, CCF and Alibaba Mama will unveil the CCF‑Alibaba Mama Technology Fund—a global academia‑industry platform targeting next‑generation AI algorithms and large‑model research through ten projects in e‑commerce, knowledge‑enhanced generation, and legal AI, with a livestreamed forum featuring a keynote by Prof. Zhang Qi on boosting task performance.
On May 18 in Ningbo, CCF and Alibaba Mama unveiled the CCF‑Alibaba Mama Technology Fund—a global academia‑industry platform targeting next‑generation AI algorithms and large‑model research through ten projects in e‑commerce, tool generation, and legal services—accompanied by a keynote on boosting large‑model task performance and open registration for scholars.
This article presents Alibaba's enterprise knowledge recommendation system, detailing its role in digital transformation, the challenges of long‑document recommendation, the multi‑layer architecture spanning feature, engine, ranking, and functional layers, various recall strategies, progressive ranking models, and the integration and evaluation of large language models for improved recommendation performance.
The paper introduces a real‑time controllable, multi‑objective re‑ranking framework for Taobao’s feed recommendation that combines actor‑critic reinforcement learning with hypernetworks to instantly adjust objective weights, handling diverse media and cold‑start constraints while delivering higher click‑through, diversity, and cold‑start ratios with only 20‑25 ms latency.
This article presents a comprehensive study of a scenario‑adaptive and self‑supervised multi‑scenario recommendation model (SASS) for Taobao, detailing its motivation, adaptive multi‑scenario architecture, two‑stage pre‑training and fine‑tuning, experimental validation, deployment in the recall stage, and practical challenges addressed through Q&A.
The 2023 AIGC Year-End Summit highlighted the integration of AI in the insurance industry, with Alibaba's CTO announcing the open-source release of their AI code assistant tool DevPilot to foster industry collaboration.
In November 2023, Alibaba Cloud suffered a massive outage that disrupted client, web, and mobile access for nearly eight hours, affecting a wide range of Alibaba products, over 300,000 enterprise customers, and numerous global data centers, highlighting the fragility of large-scale cloud services.
This article presents Alibaba's experience in addressing large‑scale data stability challenges by outlining common problems, governance principles, baseline monitoring, team collaboration methods, practical implementations, and proactive measures to ensure reliable and accurate data production on the DataWorks platform.
Taobao’s IPv6 journey, from early mobile‑internet growth through five development stages, culminated in a full end‑to‑end architecture that now delivers over 95 % IPv6 traffic, 11 % latency reduction and billion‑user scale, while pioneering innovations such as precise stack detection, multi‑channel competition and future APN6/BIERv6 extensions.
In this event, a senior Alibaba Taobao Tech engineer introduces LangChain—a framework for large language models—explaining its core concepts, diverse applications, and future directions, and shows attendees how to leverage the platform to boost AI capabilities within their own businesses.
This article presents a comprehensive case study of Taobao's data model governance, detailing the background challenges, the four‑pillar solution framework, specific governance practices such as invalid table decommissioning, data handover, public layer operations, incremental control, productization, future plans, and a Q&A session.
This article presents a comprehensive overview of applying causal inference to Alibaba’s Business Intelligence platform, detailing fundamental concepts, the merchant intelligent diagnosis system architecture, key technologies such as hybrid causal network discovery (HCM) and deep attribution, and showcases the resulting operational impact.