Technology is the core driver of Ant's future creation.
Leveraging a proprietary “large model + optimization” approach, Alibaba’s Ant Group and East China Normal University built a constraint-aware multi-agent framework that secured first place in the Original OS track and second in the DSL track of the IJCAI-2025 Autonomous Travel Planning Competition.
Alipay’s trusted deep defense architecture, built on security parallel slices and trusted computing, was selected as a flagship case for the 2025 Important Industry Security Protection list, demonstrating zero‑false‑positive, zero‑miss, and zero‑business‑disruption protection against advanced threats such as 0‑day and APT attacks during high‑traffic events like Double 11.
The Ring-1T model, a trillion-parameter AI system released as open source, leverages advanced reinforcement learning techniques, extensive benchmark evaluations, and custom training frameworks to deliver balanced performance across math, code, reasoning, and creative tasks while highlighting current limitations and future development plans.
Ant Group's open‑source dInfer framework dramatically speeds up diffusion language model inference—achieving more than a ten‑fold boost over Fast‑dLLM, surpassing autoregressive baselines, and delivering 1011 tokens per second on HumanEval—by tackling computational cost, KV‑cache invalidation, and parallel decoding challenges through modular system‑level innovations.
Ling-1T, a trillion‑parameter flagship non‑thinking model, combines 50 billion active parameters per token, 128 K context, Evo‑CoT reasoning, and FP8 mixed‑precision training to achieve state‑of‑the‑art performance on complex reasoning, code generation, and multimodal tasks while outlining its architecture, benchmarks, limitations, and future roadmap.
The ICCV 2025 live session will deep‑dive into two cutting‑edge papers—PixTrace with CopyNCE for precise image copy detection and Skip‑Vision for dramatically faster training and inference of vision‑language models—showcasing their methods, results, and real‑world impact.
Ant Insurance’s tech team leveraged reinforcement learning, focused data selection, and a multi‑dimensional reward system to dramatically reduce hallucinations in LLMs, achieving top‑rank performance on the HHEM leaderboard and robust improvements across instruction‑following and reasoning‑enhanced models.
Since 2016, Alipay's security team has built the Alipay‑SDL 1.0 framework and now integrates AI and large‑model technologies to automate risk identification, enhance security tools, and streamline operations across the entire software development lifecycle, addressing rising business complexity and engineer workload.
At the ACM CCS 2025 live paper showcase, three groundbreaking studies—Gibbon’s fast secure two‑party GBDT training, Panther’s efficient private approximate nearest‑neighbor search on a single server, and PromeFuzz’s knowledge‑driven LLM approach to fuzzing harness generation—are presented, highlighting significant performance and security advances.
Ant Group’s award‑winning ‘Aspect Fusion Intelligence’ system, unveiled at the 2025 Zhejiang Cybersecurity Promotion Week, leverages AI, large models, blockchain and zero‑trust principles to tackle trillion‑scale data, rapid threat response, and financial‑grade reliability, setting new standards for intrusion detection.
