腾讯混元Turbo S

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AI展望:NewScaling,NewParadigm,NewTAM
HTSC· 2025-06-10 01:43
证券研究报告 科技 AI 展望:New Scaling,New Paradigm,New TAM 华泰研究 2025 年 6 月 10 日│中国内地 中期策略 全球 AI 展望:New Scaling,New Paradigm,New TAM 展望全球 AI 发展趋势,1)模型端新架构正逐步探索,预训练 Scaling Law 有望呈现新起点;2)算力端训练与推理共同推动算力需求持续上行,有望 开启新 TAM,同时算力硬件设计进入新范式;3)应用端商业模式变革带来 新范式,Agent 在细分领域率先落地带来新 TAM。持续看好 AI 产业投资主 线,看好全球 AI 应用进入业绩收获期。 模型:预训练 Scaling Law 有望开启新起点 回顾近三个季度以来的大模型迭代情况,强化学习(RL)带来的后训练 test-time compute 依然是大模型的主流迭代方向。经典 transformer 架构下 模型参数规模或已达到了瓶颈,人类现有公开数据已接近被使用完。但值得 注意的是科技巨头在预训练阶段仍在继续尝试,以腾讯混元 Turbo S 与 Gemini Diffusion 为代表的大模型开始尝试在架构上进 ...
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]
财通证券:1Q2025计算机板块业绩企稳 行业投资迎来很好加仓窗口
智通财经网· 2025-05-12 03:26
Group 1 - The computer industry is experiencing a fundamental upward turning point in Q1 2025, driven by new technologies like DeepSeek's large model and increasing AI orders in specific sectors [1] - In Q1 2025, the Shenwan computer industry reported a 15.9% year-on-year increase in operating revenue and a staggering 671.5% increase in net profit attributable to shareholders [1] - The gross margin decreased by 3.4 percentage points year-on-year, while the net margin increased by 0.6 percentage points, attributed to project-based delivery and the impact of traditional orders from the previous year [1] Group 2 - The domestic AI large model sector is thriving, characterized by a "hundred schools of thought" phenomenon, with DeepSeek emerging as a leading player through algorithmic innovation [2] - Tencent's Mix Yuan Turbo S has effectively reduced training and inference costs through innovative architecture, while MiniMax has expanded linear attention mechanisms to commercial model levels [2] - Alibaba's open-source model Qwen3 has achieved performance breakthroughs with relatively low hardware resource consumption through a "mixed reasoning" approach [2] Group 3 - The AI computing power and application sectors are showing strong growth, particularly in smart driving and industrial intelligence, with domestic AI chips and server power experiencing upward trends [3] - The integration of AI productivity tools with large models is accelerating, reshaping office workflows and enhancing enterprise resilience through AI Agents [3] - The domestic low-altitude economy is experiencing accelerated development driven by policy support, significantly improving industry sentiment [3]
腾讯,重磅发布!
证券时报· 2025-02-27 12:47
Core Viewpoint - Tencent has officially launched the new generation fast-thinking model, Turbo S, which significantly improves response speed and efficiency compared to previous models [1][2]. Group 1: Model Features and Performance - Turbo S is designed to provide "instant responses," doubling the output speed and reducing the first-word latency by 44% compared to earlier models like DeepSeek-R1 and Hunyuan T1 [2]. - The model combines fast and slow thinking capabilities, allowing it to efficiently handle both intuitive and logical reasoning tasks, thus enhancing overall problem-solving intelligence [4][5]. - In various industry-standard benchmarks, Turbo S has demonstrated competitive performance against leading models such as DeepSeek-V3, GPT-4o, and Claude, particularly excelling in knowledge, mathematics, and reasoning tasks [5][6]. Group 2: Cost and Accessibility - The pricing for Turbo S has been significantly reduced, with input costs at 0.8 yuan per million tokens and output costs at 2 yuan per million tokens, making it more accessible compared to previous versions [7]. - Developers and enterprise users can access Turbo S through APIs on Tencent Cloud, while ordinary users will gradually experience it through the Tencent Yuanbao platform [2][9]. Group 3: Integration and Market Position - Tencent has integrated DeepSeek models into over ten of its products, enhancing functionalities across various applications such as WeChat, QQ Music, and Tencent Docs [10]. - The integration of DeepSeek has positioned Tencent as a key player in the AI application sector, leveraging its extensive user base and ecosystem to gain a competitive edge [11][12]. - Following the integration of DeepSeek-R1, Tencent Yuanbao quickly rose to become the second most downloaded free app in the Apple App Store in China, surpassing competitors [10]. Group 4: Strategic Implications - The emergence of DeepSeek has reshaped the competitive landscape of the AI industry, with Tencent focusing on AI applications while Alibaba leads in AI infrastructure [11]. - Tencent's strategy of combining its Hunyuan models with DeepSeek is aimed at building a robust competitive advantage in the AI application space, potentially leading to significant growth in its stock price and market valuation [11][12].