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21专访丨安永吴晓颖:AI医疗需从“炒概念”走向“真落地”
2 1 Shi Ji Jing Ji Bao Dao· 2025-07-29 23:11
从信息化、数字化到如今的智能化,在每一轮信息革命的浪潮中,医疗健康领域始终是新技术的试验场 与先行区。当前,大模型技术正加速向多模态融合方向演进,生成式人工智能持续为医疗服务赋能。 无论是AI辅助诊断突破传统诊疗效率的瓶颈,还是加速AI药物研发中候选化合物的筛选周期,技术革 新正为全球医疗健康领域注入前所未有的创新动力。 然而,在技术迅猛发展的背后,产业落地的现实挑战也逐步显现——从数据治理到临床转化,从技术伦 理到全球普惠,医疗AI在跨越实验室与真实世界的"断层带"时,正面临多重结构性矛盾的考验。 面对这一系列挑战,究竟该如何应对?7月26日至28日,2025世界人工智能大会在上海多场馆同步拉开 帷幕。本次大会以"智能时代同球共济"为主题,涵盖会议、展览等五大板块,聚焦AI基础设施、科学智 能等十大领域。据悉,本次大会迎来800余家企业参展,3000余项前沿展品集中亮相,其中包括40余款 大模型、50余款AI终端及100余款全球首发/中国首秀新品,规模创历届之最。 在医疗AI领域从"技术可行"迈向"规模应用"的关键跨越阶段,产业亟需破解标准缺失、生态分散、转化 困难等瓶颈问题。对此,大会期间,安永大中华区生 ...
腾讯AI投入再加码 打造“好用的AI”
Huan Qiu Wang Zi Xun· 2025-05-22 03:41
Core Insights - The current industry demand for AI is extremely high, with companies eager to engage in discussions about AI applications [1] - Tencent is committed to increasing its investment in AI, aiming to transform the usability of generative AI from "quantitative change" to "qualitative change" [3] - Tencent plans to enhance AI capabilities through four key areas: large models, intelligent agents, knowledge bases, and infrastructure [3] Group 1 - Tencent's AI strategy focuses on creating "user-friendly AI" to integrate AI into various industries and everyday life [3] - The intelligent agent sector is experiencing significant growth, although it is still in its early development stages [3] - The complexity of tasks for intelligent agents requires ongoing advancements in underlying model technologies to improve their capabilities [3] Group 2 - Tencent's upgraded intelligent agent development platform allows businesses to quickly build intelligent agent applications [3] - Applications such as QQ Browser, Tencent Health, CodeBuddy, and Tencent Qidian Marketing Cloud have incorporated intelligent agent capabilities through this platform [3] - Future intelligent agents are expected to evolve into effective assistants that understand enterprise knowledge, utilize tools, and autonomously execute complex tasks [3]
加大AI投入!腾讯汤道生:加速AI大模型、智能体、知识库和基础设施建设
Xin Lang Ke Ji· 2025-05-21 03:07
Core Insights - Tencent is significantly increasing its investment in AI, aiming to enhance the usability of generative AI from "quantitative change" to "qualitative change" [1] - The company is focusing on four key areas: large models, intelligent agents, knowledge bases, and infrastructure to create "user-friendly AI" [1][3] Group 1: AI Model Development - The demand for large model APIs and computing power has rapidly increased this year, indicating a shift in generative AI towards broader usability [3] - Tencent's mixed model T1 and Turbo S have been continuously iterated, with Turbo S ranking in the top 8 globally in the Chatbot Arena, second only to DeepSeek among Chinese models [3] - The company emphasizes that models must not only think but also execute tasks, with intelligent agents expanding the value boundaries of AI [3][4] Group 2: Knowledge Management - Tencent has launched the Tencent Lexiang Enterprise AI Knowledge Base to manage knowledge effectively, addressing issues of validity, update frequency, and access permissions [4] - The company is also enhancing personal knowledge base capabilities through its IMA platform, aiming to create a more personalized AI workspace [4] Group 3: Cost Optimization and Infrastructure - The shift in AI application from training-driven to inference-dominated has made cost optimization for large-scale inference a core competitive advantage for cloud providers [4] - Tencent Cloud's AI infrastructure is optimizing response speed, latency, and cost-effectiveness in inference scenarios through collaboration between IaaS and tool layers [4]