Ant Group shares its practical experience in big data governance, outlining five key focus areas—architecture, security, compliance, quality, and value—through four structured sections and detailed discussions on data quality and storage governance, while also exploring future challenges and the economics of data.
The article presents Ant Group’s Ray‑based Ragent framework, detailing its background, motivation behind unified AI serving, and the four core modules—Profile, Memory, Planning, and Action—that together enable large‑language‑model agents for financial applications.
This article introduces Ant Group’s Ragent, a Ray‑based distributed AI agent framework, covering its background, motivation in the large‑model era, and a four‑module design (Profile, Memory, Planning, Action) that enables scalable LLM‑driven agents.
This article introduces Ant Group’s new Ray‑based distributed agent framework Ragent, outlines its background and motivation, and details the four core modules—Profile, Memory, Planning, and Action—that together enable sophisticated LLM‑driven AI agents for large‑scale applications.
This article introduces Ant Group’s Ragent, a Ray‑based distributed AI‑agent framework, covering its background, motivation, design and implementation, and detailing the four core modules—Profile, Memory, Planning, and Action—that enable large‑language‑model agents at massive scale.
This article introduces Ant Group’s Ragent, a Ray‑based distributed AI Agent framework, detailing its background, motivations, and design, and explains the four essential modules—Profile, Memory, Planning, and Action—that enable scalable large‑language‑model agents for real‑world applications.
This article introduces Ant Group’s Ragent, a Ray‑based distributed agent framework, covering its background, motivation, and design—including core modules like Profile, Memory, Planning, and Action—that enable large‑language‑model agents to operate at massive scale.
This article introduces Ant Group’s Ray‑based distributed agent framework Ragent, outlines its background, motivation, and design, and details the four essential modules—Profile, Memory, Planning, and Action—that power large‑language‑model agents in large‑scale AI serving.
This article explains how Ant Group’s Ragent framework leverages Ray to create scalable, multi‑tenant AI agents, detailing its background, motivation, and design while outlining the core modules—Profile, Memory, Planning, and Action—that power large‑language‑model agents.
This article introduces Ant Group’s Ray‑based distributed agent framework Ragent, outlines its background, motivation, and design, and breaks down the four essential modules—Profile, Memory, Planning, and Action—that enable large‑language‑model agents to operate in real‑world scenarios.
Ant Group’s Ant Financial Science released Agentar‑Fin‑R1, a finance‑focused large model that claims expert‑level knowledge, efficient training, and continuous self‑evolution, outperforming open‑source rivals on benchmarks like FinEval1.0, FinanceIQ and Finova, while supporting industry standards through a collaborative AI alliance.
Ant Group’s “Aspect‑Fusion Intelligence” system, recognized as an outstanding cybersecurity case at the 2025 Beijing Cybersecurity Conference, leverages large‑model AI and expert knowledge to enhance threat detection, lower false positives, and improve explainability in large‑scale intrusion detection.
An award‑winning joint project by Shanghai Jiao Tong University and Ant Group unveils a multimodal foundation model and advanced detection techniques that dramatically improve AI‑driven content risk governance across massive online services.
At the second Wuhan Cybersecurity Innovation Forum, Ant Group unveiled its AI‑powered "parallel security slice" approach for threat detection, detailing a multi‑layer defense system that leverages a DKCF framework, large‑model reasoning, and knowledge graphs to improve accuracy, reduce false alarms, and uncover unknown threats in complex digital enterprises.
The International Symposium on Computer Architecture (ISCA) 2025 accepted two Ant Group research papers—FAST and Neo—detailing novel fully homomorphic encryption accelerators that combine cryptographic optimizations with hardware design to achieve significant performance gains for privacy‑preserving computation.
The InclusionAI open‑source community, initiated by Ant Group, will showcase the latest advances of its reinforcement‑learning framework AReaL and multi‑agent framework AWorld at the ICLR 2025 conference in Singapore, highlighting performance breakthroughs, open‑source contributions, and industry‑focused AI research.
The ISO/IEC JTC 1/SC 27 plenary meeting in Virginia approved the ISO/IEC 25330 Part 3 standard on Oblivious Transfer Extension, a cryptographic protocol standardized by Ant Group with contributions from Chinese researchers, aiming to improve OT efficiency and interoperability for secure multi‑party computation.
The article presents the abstracts, publication types, links, and research areas of seventeen Ant Group papers accepted at ICLR 2025, covering topics such as embodied robot co‑design, efficient distributed training for large language models, optimization via LLMs, character animation, interactive frame interpolation, KV‑cache management, and privacy‑preserving Transformers.
Two Ant Group papers accepted at AAAI 2025—one presenting a human‑feedback‑driven evaluation framework for product image background inpainting using EfficientSAM and a new HFPC‑44k dataset, and the other proposing a Bagging‑Expert Network to mitigate expert polarization in multi‑gate mixture‑of‑experts for multi‑task learning.
This article shares Ant Group's practical experience and evolution of data architecture, covering theoretical foundations, analysis of current challenges, proposed upgrade solutions based on domain‑driven design, and future outlook through complex network theory to improve scalability, governance, and resilience of large‑scale data systems.
Ant Group’s AIGC security detection system was evaluated by the China Information and Communication Research Institute, achieving the highest "Excellent" rating with a 0.99 F1 score across image, video, and audio modalities, while also releasing large‑scale detection datasets for the research community.
In his MEET2025 keynote, Ant Group’s Wang Xu explains how generative AI models are reshaping traditional database‑centric architectures, driving a new LAMP stack, accelerating AI agent frameworks, and prompting fundamental shifts in infrastructure, security, and developer productivity.
This article presents a curated overview of fifteen Ant Group research papers accepted at NeurIPS 2024, covering topics such as large language models, knowledge graphs, recommendation systems, privacy-preserving inference, and multimodal learning, with abstracts, paper types, links, and key contributions highlighted.
Ant Group will showcase three flagship papers at NeurIPS 2024—AMOR for adaptable modular knowledge agents, PaRO for efficient data‑parallel training of large language models, and LLMDFA for code data‑flow analysis using LLMs—highlighting novel methods, experimental results, and upcoming live discussions.
The article details Ant Group’s AI‑driven security parallel plane and intelligent threat detection system, its DKCF‑based architecture, key modules for data correlation, unknown threat discovery, alarm reduction, and knowledge‑graph integration, and its recognition in the 2024 AI Pioneer Case Collection.
The CNCC2024 roundtable highlighted how enterprises can effectively run technology research institutes by focusing on future‑oriented, value‑creating AI and data initiatives, acting as bridges between academia and industry, and adopting long‑term assessment practices, with Ant Group’s institute serving as a prime example.
Ant Group’s cryptography lab introduced Coral, a new maliciously secure multi‑party computation framework that leverages a reverse multiplication‑friendly embedding (RMFE) to efficiently handle packed and mixed circuits, enhancing security from semi‑honest to fully malicious models and delivering practical performance improvements.
The 2024 CCF Technology Achievement Awards honored Ant Group’s two projects—complex behavior modeling for digital inclusive finance security and Alipay terminal intelligent technology—highlighting their AI‑driven risk control, edge inference innovations, extensive research output, and large‑scale real‑world deployments.
At the CNCC2024 conference in Hangzhou, Ant Group and the China Computer Federation announced third‑phase research funds for green computing and privacy computing, committing tens of millions of yuan to support AI‑infra, model algorithms, trusted confidential computing, and related academic collaborations across leading universities.
On September 5 at the 2024 Inclusion·Bund Conference, Ant InTech announced its first ten award-winning young scholars from top Chinese universities, highlighting their research in artificial intelligence, data processing, cloud computing, security, and related fields, each receiving a 200,000‑RMB grant.
From August 26‑30, 2024, Ant Group showcased eight papers—including seven oral presentations—at the VLDB 2024 conference in Guangzhou, covering advances in knowledge‑graph warehouses, graph analytics, joint clustering and imputation, secure multi‑party queries, distributed logging, deep recommendation model training, cloud autoscaling, and LLM‑driven database interaction.
The article presents a curated collection of Ant Group's research papers accepted at KDD2024, summarizing each paper's title, type, link, source, relevant fields, and abstract, covering topics such as graph mining, large language models, fraud detection, recommendation systems, and multimodal medical AI.
This article introduces causal debiasing techniques for Ant Group's marketing recommendation systems, detailing background biases, causal graph analysis, a meta‑learning data‑fusion model (MDI), backdoor‑adjustment methods, extensive experiments on public and internal datasets, and real‑world deployment results.
Ant Group’s cryptography team, leveraging the open‑source Tongsuo project and its proprietary Ant Card, has obtained a Level 2 commercial cryptography product certification under GM/T 0028, demonstrating compliance with China’s national cryptographic standards and offering a hybrid software‑hardware security solution for enterprises.
At ICML 2024 in Vienna, Ant Group had eleven papers accepted, spanning topics such as quantization-aware secure inference for transformers, multimodal contrastive captioners, self-cognitive denoising with noisy labels, directed graph embedding, GAN improvement via score matching, and trustworthy alignment of retrieval-augmented large language models.
This article details Ant Group's research on integrating large language models into recommendation pipelines, covering background challenges, knowledge extraction, teacher‑student distillation, experimental results, and practical Q&A for improving bias, efficiency, and cold‑start performance.
At the 2024 World Artificial Intelligence Conference, Ant Group showcased seven AI-driven applications—including the Alipay Smart Assistant, AI Financial Butler, and other specialized intelligent agents—highlighting how large‑model ecosystems and professional intelligent agents are accelerating rigorous industry adoption of generative AI.
The article details Ant Group’s security parallel aspect fusion AI solution, selected as an exemplary case at the 2024 World Intelligent Industry Expo, explaining its multi‑dimensional data collection, large‑model integration, baseline construction, knowledge‑graph generation, and superior threat‑detection performance.
The IEEE CVPR2024 conference in Seattle accepted 2,719 papers out of 11,532 submissions, and Ant Group contributed 24 papers covering computer vision, deep learning, digital humans, large models, multimodal remote sensing, vision‑language distillation, federated incremental learning, model‑stealing defense, and more, with one highlighted as a highlight.
This article presents Ant Group's comprehensive data governance experience, covering data quality management, storage governance, architectural design, operational strategies, case studies, and forward‑looking thoughts on integrated lake‑warehouse governance, data value realization, and AI‑driven automation.
This article shares Ant Group's extensive experience in big data governance, detailing the overall data governance framework, data quality management, data storage governance, and future considerations, illustrated with practical cases and strategies for ensuring compliance, reliability, and cost efficiency.
The 2024 National Standards Committee AI Sub‑Committee Conference Week in Hangzhou gathered over 400 experts to discuss AI standardization and showcased Ant Group’s large‑model applications in finance and healthcare, while announcing new work‑group leadership and numerous national and industry AI standards the company has helped develop.
Under the guidance of the People’s Bank of China, the Beijing FinTech Industry Alliance has published the 'Financial Industry Privacy Computing Interconnection Platform Technical Specification', a standard co‑authored by China UnionPay, major banks, universities, tech firms and telecom operators, with Ant Group playing a key role.
At the 27th UN CSTD Annual Meeting in Geneva, the World Digital Technology Academy unveiled two pioneering international standards—one for generative AI application security testing and another for large language model security testing—crafted by experts from leading AI firms to establish a new global benchmark for AI safety.
On February 29, China’s National Information Security Standardization Technical Committee released the inaugural "Basic Requirements for Generative AI Service Security," a comprehensive guideline covering data, model, and operational safeguards, with Ant Group playing a key role in its development and implementation.
The IEEE Standards Association has published the world’s first privacy‑computing integrated‑machine standard (IEEE 3156‑2023), highlighting China’s leadership in privacy‑preserving data technologies and outlining hardware, software, and security requirements that aim to foster global adoption and reduce collaboration costs.
Ant Group introduced SkySense, a 2.06‑billion‑parameter multimodal remote‑sensing foundation model that outperformed 18 international rivals across 17 benchmark tasks, was accepted to CVPR 2024, and aims to support applications such as agriculture, urban planning, and disaster response.
This article presents Ant Group's research on causal debiasing for recommendation and marketing, covering the background of bias, common bias types, causal graph analysis, two correction approaches—data‑fusion based MDI and back‑door adjustment based DMBR—along with experimental results on public and proprietary datasets and real‑world deployment insights.
Ant Group’s mobile security parallel slice technology, recognized with the 2023 Mobile App Security Vulnerability Governance Excellent Case award, offers a low‑intrusive, configurable SDK‑based solution that decouples security from business logic, enabling real‑time threat detection, rapid response, and broad deployment across major mobile applications.
Wang Weiqiang, chief scientist of Ant Group’s Security Lab, highlighted the urgent need for both rapid detection and long‑term trustworthy safeguards for large AI models, outlining Ant’s data‑detox, guard‑rail, and detection platforms as core solutions to emerging risks such as hallucinations, bias, and data leakage.
The article summarizes Ant Group's twenty accepted NeurIPS 2023 papers, covering advances in generative AI, time‑series forecasting, 3D image synthesis, and other machine‑learning topics, and provides brief overviews of three highlighted works along with links to the remaining studies.
At NeurIPS 2023, Ant Group unveiled OpenASCE, the industry's first open‑source distributed full‑link causal learning system, detailing its architecture, large‑scale capabilities, and real‑world applications in credit risk, marketing, and recommendation while emphasizing its role in advancing causal AI research.
The TechTalk AI Sharing Season event on November 28 brought together nearly thirty experts from academia and industry to discuss how knowledge graphs and large language models can be integrated to enhance Ant Group's AI strategy across diverse business scenarios, highlighting collaborations, research labs, and future development directions.
The article presents Ant Group's real‑time data platform, explains its streaming graph processing architecture, and demonstrates how it powers traffic attribution, real‑time OLAP and user‑behavior intent analysis, while outlining future directions for the technology.
At the 2023 Bund Conference, Ant Group presented the Large Graph Model (LGM), a research effort that combines graph computing, graph learning, and large language models to enrich heterogeneous graph data and enable more precise insights for complex digital applications, with results accepted at WWW 2023.
At the 2023 Waibao Conference Network Security Forum in Shanghai, Ant Group and Zhejiang University introduced the Native Security Paradigm Framework v1.0, detailing its OVTP and NbSP paradigms, security parallel aspect technology, and real‑world implementations that aim to embed security directly into modern digital enterprises.
At the 2023 Bund Conference, Ant Group unveiled the Large Graph Model (LGM), a research effort that merges graph computing with large language models to enhance data representation and insight generation, marking a significant step toward advanced generative AI applications.
Ant Group announced the open-source release of Ant Graph Learning (AGL), a pioneering industrial‑grade graph learning platform that supports trillion‑scale graph data, offers ready‑to‑use algorithms, and aims to lower the barrier for large‑scale graph AI applications across industries.
This article presents Ant Group's work on knowledge graphs, covering the fundamentals, construction pipeline, fusion techniques, cognitive modeling, real‑world applications, and the emerging synergy between knowledge graphs and large language models, while highlighting technical challenges and future directions.
At the 2023 China Digital Economy Innovation Development Conference, Ant Group presented its composite data security governance framework, detailing systematic, practical approaches for safeguarding cross‑border data flows, integrating technical, managerial, and ecosystem measures to enhance data protection while supporting digital economic growth.
Ant Group’s Ant Security Tianqiong and Lightyear labs earned the prestigious Pwnie Awards’ Best Privilege Escalation prize for their VM escape research on VMware, highlighting the high‑impact nature of virtualization security breakthroughs and underscoring China’s growing prominence in global information security innovation.
This article explains the concept of Function-as-a-Service (FaaS), its rise and suitable scenarios, then details Ant Group's serverless architecture, performance‑tuning techniques, security isolation mechanisms, developer experience, and future outlook integrating AI to create a new programming paradigm.
At the 2023 World AI Conference summit, Ant Group unveiled its YinYu Open‑Source Framework 1.0 and the HyperEnclave financial‑grade TEE, detailing their technical features, industry‑wide standards contributions, and how they aim to boost the usability, security, and interoperability of privacy computing for AI applications.
The 2022 Wu Wenjun Artificial Intelligence Science and Technology Award recognized a decade‑long collaborative effort by Tsinghua University and Ant Group's security lab for breakthrough research on unconstrained human portrait perception and understanding, highlighting three core scientific discoveries, extensive academic impact, and large‑scale commercial applications in identity verification.
The article explains how Ant Group leverages blockchain‑based distributed identity authentication, detailing its technical foundations, ecosystem participants, and the advantages of privacy‑preserving, cost‑effective, and interoperable digital identity solutions for the emerging digital economy.
Beijing's National FinTech Certification Center announced that five fintech products, including AntChain MOSS and Ant Wind Tunnel multi‑party secure computation platforms, have passed the country's first national certification for multi‑party secure computation, highlighting the technology's growing importance in finance and data security.
The 2022 CCF‑Ant Green Computing research fund announced 27 selected projects from 19 universities, highlighted the fund's goals of advancing efficient AI and data computing, and described the subsequent academic exchange meeting that gathered scholars to discuss green computing trends and Ant Group's commitment to open‑source, sustainable technology development.
The article outlines the five‑generation evolution of Ant Group's risk control platforms, the technical and operational challenges faced, the shift toward data‑driven and AI‑enabled security, and the organization’s comprehensive data and network protection measures alongside emerging technologies such as graph risk, blockchain, and privacy computing.
This article introduces and compares major privacy computing technologies—including MPC, federated learning, TEE, and proxy MPC—evaluating them across security, development cost, operational cost, accuracy, performance, participant scale, control, hardware cost, and trust, and then outlines Ant Group’s privacy computing framework, applications, and standards work.
This article explains Ant Group's privacy computing framework, covering its fundamental concepts, layered product architecture, and four concrete use‑cases in the medical sector—including insurance, hospitals, health commissions, and medical device manufacturers—demonstrating how secure multi‑party computation and federated learning enable data collaboration while preserving privacy.
Ant Group’s self‑developed open‑source cryptographic library Tongsuo, formerly BabaSSL, has become the world’s first open‑source project to obtain the national commercial cryptography product certification, confirming its compliance with GM/T 0028 security standards and its suitability for secure data storage, transmission, and privacy‑preserving applications.
This article reviews Ant Group's "thousand‑by‑thousand" model strategy for mobile AI, detailing the challenges of device compute and user heterogeneity, the engineering upgrades for offline development and online release, and the measurable business improvements achieved.
In 2022 Ant Group announced the open‑source privacy‑computing framework “YinYu”, launched OceanBase 4.0 with a single‑node distributed architecture, earned multiple AI and security awards, released AI risk‑detection platforms, open‑sourced the high‑performance graph database TuGraph, and published several papers at top AI conferences, showcasing its broad innovations across privacy, AI, and data infrastructure.
The 2022 World AI Conference in Shanghai showcased cutting‑edge research on graph computing and privacy computing, announced Ant Group’s new AI safety product “AntJian”, the “YinYu Open Platform” for trusted privacy computing, and the open‑source high‑performance graph database TuGraph, highlighting the push for secure, scalable AI technologies.
In his keynote at the 2022 Open Atom Global Open Source Summit, He Zhengyu outlined Ant Group’s open‑source strategy, highlighting over 900 repositories and key projects such as OceanBase, SOFA Mesh, MOSN, BabaSSL, Occlum, and the upcoming TuGraph, emphasizing how open core infrastructure drives industry innovation and ecosystem growth.
Ant Group announced the open‑source release of its six‑year‑old trusted privacy computing framework “YinYu,” detailing the technical challenges of data element markets, the shift to data‑in‑confidential‑state, the framework’s layered architecture, rigorous security verification, compliance considerations, and its invitation to the community for collaborative development.
This article reviews Ant Group's award‑winning mPaaS mobile security solution, detailing the current mobile app security landscape, regulatory pressures, and the four‑layer full‑chain protection architecture—including data security, privacy control, biometric authentication, and app hardening—along with practical compliance and risk‑mitigation practices.
Ant Group’s large‑scale graph computing system TuGraph recently passed the China Academy of Information and Communications Technology’s Trusted Big Data assessment, becoming one of the first graph platforms certified for basic capabilities, compatibility, management, high availability and scalability, and highlighting its critical role in financial risk control.
This article introduces GeaFlow, Ant Group’s self‑developed real‑time streaming graph engine, covering its basic concepts, technical architecture, dynamic and fusion computing capabilities, integrated DSL, and several large‑scale business use cases such as fraud detection and incremental community mining.
Ant Group partnered with CVPR 2022’s 17th IEEE Computer Society Workshop on Biometrics to host two global competitions—pet biometric recognition and image forgery detection—attracting over 1,300 teams, with top university and industry teams presenting innovative AI solutions that have been open‑sourced.
The article reviews the five‑year impact of China’s Cybersecurity Law, highlights progress in legal‑driven security governance, and details Ant Group’s advanced network and data security architectures, privacy‑preserving computing techniques, and collaborative recommendations for tackling emerging cyber threats.
The LDBC has approved the world’s first financial graph database benchmark, FinBench, a collaborative effort led by Ant Group to provide a rigorous, open‑source testing suite that simulates real‑world financial workloads and fills a critical gap in graph database evaluation.
The International Telecommunication Union (ITU) has officially adopted an Ant Group‑initiated international standard for interactive intelligent risk control, outlining technical capabilities such as interactive functions and machine‑learning abilities to enhance proactive fraud detection across the industry.
IDC’s recent China Cloud‑Native Market Analysis reports that Ant Group has become one of the most comprehensive domestic cloud‑native technology providers, with widespread enterprise adoption, major investment in cluster scheduling, mixed‑deployment, and Service Mesh, and ongoing open‑source and commercial initiatives driving industry innovation.
The article explores the rapid growth of privacy computing in China, highlighting new data protection laws, a surge in patents, real‑world applications such as medical data sharing, and personal stories of Ant Group engineers who develop cutting‑edge cryptographic frameworks and champion interdisciplinary research.
The article explains how Ant Group leverages large‑scale graph computing—through its GeaBase and TuGraph platforms and a dedicated research team—to enhance real‑time fraud detection, drive industry standards, and explore future applications across finance, energy, and public services.
This article outlines Ant Group's six‑year journey in chaos engineering, describing its three generational evolutions, business‑oriented fault injection, risk‑mining, full‑lifecycle coverage, massive scale, root‑data protection, core technologies such as Awatch, simulation environments, and plans for intelligent, open‑source future development.
Ant Group's AI‑driven anti‑fraud risk perception and response system and its trusted‑execution‑environment based blockchain data privacy technology were honored with the 2021 CCF Scientific and Technological Excellence and Outstanding Awards, highlighting significant advances in proactive fraud defense, explainable AI, and on‑chain privacy protection.
This article explores how Ant Group leverages graph database technology in financial technology, detailing the evolution of fintech architecture, data‑intelligence challenges, storage and computation advancements, the GeaBase platform, real‑world use cases, standardization efforts, and future directions for graph‑driven solutions.
The Ant Group’s TitanShield Team secured the image representation track at NeurIPS ISC2021 using a self‑supervised, feature‑compatible pre‑training model that dramatically cuts labeling effort, speeds up training, and lowers image adversarial risk by 80%, highlighting AI robustness as a critical challenge for content‑security applications.
This article outlines the evolution of fintech architecture, the data‑intelligence challenges faced by Ant Group, and how their distributed graph database GeaBase addresses massive, complex financial data through advanced storage structures, real‑time computation, and industry‑wide standardization efforts.
The speech by Ant Group’s chief architect outlines how a high‑performance accounting database, a virtualization engine for complex payment networks, intelligent risk‑control strategies, and a graph‑computing platform together form an end‑to‑end intelligent middle platform that drives fintech innovation and aims for future financial auto‑driving.
The article explains how Ant Group tackles the challenge of tightly integrating multiple computing paradigms by building a Ray‑based fusion engine, detailing its architecture, features, large‑scale applications in online machine learning and parallel processing, and outlining future development and recruitment opportunities.
Ant Group’s financial intelligent AutoML system received the 2020 CCF Technology Advancement Excellence Award, highlighting its industrial‑grade automated modeling algorithms, high‑performance architecture, and large‑scale deployment that boosted AI modeling efficiency by 50% and risk discrimination by 20% in the finance sector.
The article compares shared intelligence and federated learning, examines privacy‑preserving techniques such as MPC, TEE, and differential privacy, discusses gradient‑inversion attacks and their mitigations, and presents Ant Group’s end‑to‑end system design and real‑world deployments in finance.
An interview with Ant Group senior engineer Qin Kailun reveals the inherent security flaws of Kubernetes Secrets—including plaintext storage, memory exposure, and vulnerable KMS plugins—and explains Ant Group’s TEE‑based end‑to‑end protection solution that encrypts secrets throughout their lifecycle.
This article explains the classification, value, and detailed interpretation of the first national shared intelligence standard, describes its technical background and solutions such as Trusted Execution Environments and Secure Multi‑Party Computation, and showcases real‑world applications and industry recognitions.
The article chronicles Tian Hongliang’s evolution from a Rust‑loving coder who excelled in Ant Group’s internal coding competition to a leading researcher in confidential computing, detailing his work on Intel SGX, the open‑source Occlum project, and the team’s recruitment drive for security engineers.
At AAAI 2020, Ant Group showcased six peer‑reviewed papers covering dynamic network pruning, pruning without pre‑training, video‑based auto‑insurance damage assessment, long‑short‑term sample distillation, a span‑based neural buffer for long‑range context, and cost‑effective counterfactual incentive allocation, highlighting the company’s active research in artificial intelligence.
Ant Group announced that two of its research papers—one on the Occlum secure enclave LibOS and another on the Catalyzer serverless cold‑start optimizer—were selected for presentation at the prestigious ASPLOS'20 conference, highlighting the company's contributions to confidential computing and serverless performance.
