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Humanoid robots take over CES in Las Vegas as tech industry touts future of AI
CNBC· 2026-01-09 13:00
Core Insights - The CES trade show in Las Vegas showcased advancements in humanoid robots, indicating a significant year for physical artificial intelligence [3][4] - Nvidia announced new vision language models for humanoid robots, highlighting the potential for robots to achieve human-level capabilities [4][5] - The market for general-purpose robotics is projected to reach $370 billion by 2040, with applications in various sectors [7] Company Developments - Nvidia introduced Gr00t, a vision language model for humanoid robots, and emphasized partnerships with companies like Boston Dynamics and Caterpillar [4][5] - AMD showcased the GENE.01 robot, which utilizes its chips and AI technology, and plans to deploy it in industrial settings [10] - Qualcomm presented a new line of robot chips called Dragonwing, aimed at enhancing robot capabilities through vision language models [14] Industry Trends - The humanoid robotics sector is experiencing rapid growth, with 40 companies mentioning humanoid robots at CES [9] - Generative AI technologies, such as those used in ChatGPT, are being leveraged to enhance robot functionalities [6][13] - Experts caution that while humanoid robots are gaining attention, practical commercial implementation remains a significant challenge [8][12]
英伟达新一代Rubin平台 欲重构AI与世界的联结
记者注意到,黄仁勋此前多次提到"英伟达已是一家AI基础设施公司而非只是卖芯片"。总的来看,黄仁 勋本次CES主题演讲超过70%的篇幅都在讲述物理AI的具体应用场景和商业化路径,包括自动驾驶、机 器人、工业制造等领域的规模化部署计划,而这些没有太多新鲜的内容。 在记者看来,这次黄仁勋演讲呈现出明显的推理导向特征,主要有两大亮点:一是展示了更多关于 Rubin平台的详情和细节,黄仁勋透露"Vera Rubin已全面投产";二是开源模型在2025年真正起飞,1/4 的token来自开源模型,而"英伟达在领导开源模型生态",并多次提到DeepSeek、Kimi、Qwen等中国开 源模型。 对于Rubin平台,行业机构Omdia人工智能首席分析师苏廉节表示,此前英伟达的数据中心业务闭环还 差存储一环,英伟达Vera Rubin NVL72系统加入了数据存储单元,"存的是模型运行所需要的key value,并不是大量的冷热企业数据,这种存储格式仍有标杆意义,象征的是一种程度上的闭环"。 Rubin已全面投产 Rubin平台的全面发布,可以说是英伟达在CES 2026上的最大亮点。 据了解,这是英伟达首个采用协同设计、集成 ...
黄仁勋CES最新演讲:这,是所有人的机会
Sou Hu Cai Jing· 2026-01-08 23:23
内容来源:本文汇编网络公开资料。 责编 | 柒排版| 沐言 第 9380篇深度好文:5182字 |11分钟阅读 商业趋势 笔记君说: 在拉斯维加斯的CES(2026国际消费电子展)上,黄仁勋又带着他的标志性皮衣"炸场"了。 听完他的演讲,再看后续的媒体采访,我们可以发现:AI已经从"实验室里的聪明人",变成了"要走进工厂、汽车、家庭的打工人"。 往年我们看英伟达,总觉得是"芯片大佬"在秀技术肌肉,但这次不一样,他不谈玄乎的未来概念,只说"怎么把AI落地";不吹模型多牛,只讲"怎 么让AI算得起、用得久"。 以下,是黄仁勋在CES上的演讲和采访的精华梳理,希望对你有所帮助。 一、AI正在经历"双重搬家" 旧房子装不下新需求了 黄仁勋一开场就说:计算机行业每10-15年就会"重置"一次,这叫"平台转移"。 简单说,就像你开餐厅,原来在商场专柜(大型机时代),后来搬到街边小店(PC时代),再到线上外卖(移动互联网时代),每次"搬家",生 意逻辑、设备、客源都得换。 但这次不一样——AI正在经历"双重搬家",相当于同时从街边店搬到商场,还要顺便开个线上分店。 第一重搬家:应用都要"建在AI上" 以前AI是单独的工具, ...
黄仁勋开年定调:AI 真升级,靠工业化
3 6 Ke· 2026-01-06 01:51
2026 年刚开年,AI 行业最重磅的信号,不是来自模型发布会,而是来自芯片 CEO 的一场产业宣言。 1月5日,拉斯维加斯 CES 现场,英伟达 CEO 黄仁勋一登台就说: 计算行业的每一层,都要被重写一次。 黄仁勋并没有把模型升级作为主角,而是强调:AI的真正跃迁,不靠单点突破,而要靠一整套工业化 能力。 什么是工业化能力? 不是展示一个更强的Demo,而是让 AI 能被复制、能被部署、能被验收、最终能规模化。 这次发布会,英伟达展示的正是这套完整的工业化体系: 这意味着:AI 应用不再是堆个模型挂在原来的程序上,而是从写代码变成教会一个智能体怎么做事。 过去的应用程序,是提前写好一套流程、预先编译、部署到设备上运行。 硬件层:Rubin平台全面量产,训练速度提升4倍、成本降低10倍 应用层:Physical AI标准路径,从Cosmos模拟到 Alpamayo 自动驾驶,2026年 Q1上路 生态层:全栈开源工具链,从模型到数据到工具,全部向行业开放 而现在的 AI 应用,是实时生成、实时理解、实时回应,连每一帧画面、每一个词,都是现场生成的。 这背后,底层逻辑变了三件事: 黄仁勋说,机器人领域的"Ch ...
直击CES|黄仁勋:英伟达在开放模型生态系统中处于领先地位
Xin Lang Cai Jing· 2026-01-06 01:23
新浪科技讯 1月6日上午消息,一年一度的CES展会期间,黄仁勋在英伟达新品发布会上表示,英伟达 在开放模型生态系统中处于领先地位。这包括用于机器人的"GR00T"、用于物理人工智能的"Cosmos"以 及基于物理定律的"Earth-2"。此外,还有NVIDIA的智能体AI模型Nemotron、用于生物医学AI的Clara以 及用于自动驾驶汽车的Alpamayo。 "我们不仅开源了模型,还开源了用于训练这些模型的数据。只有这样,你才能真正信任这些模型的生 成过程,"黄仁勋表示。 "我们不仅开源了模型,还开源了用于训练这些模型的数据。只有这样,你才能真正信任这些模型的生 成过程,"黄仁勋表示。 责任编辑:江钰涵 专题:2026年度国际消费电子展(CES) 专题:2026年度国际消费电子展(CES) 新浪科技讯 1月6日上午消息,一年一度的CES展会期间,黄仁勋在英伟达新品发布会上表示,英伟达 在开放模型生态系统中处于领先地位。这包括用于机器人的"GR00T"、用于物理人工智能的"Cosmos"以 及基于物理定律的"Earth-2"。此外,还有NVIDIA的智能体AI模型Nemotron、用于生物医学AI的Clar ...
NVIDIA (NasdaqGS:NVDA) 2026 Conference Transcript
2026-01-05 22:02
Summary of NVIDIA Conference Call Company Overview - **Company**: NVIDIA (NasdaqGS: NVDA) - **Event**: 2026 Conference at CES - **Date**: January 05, 2026 Key Industry Insights - **Platform Shifts**: The computing industry is experiencing two simultaneous platform shifts: the transition to AI and the development of applications built on AI [2][3] - **Investment Trends**: Approximately $10 trillion of computing from the last decade is being modernized, with hundreds of billions in venture capital funding directed towards AI advancements [3][4] - **AI Evolution**: The introduction of large language models and agentic systems has transformed AI capabilities, allowing for real-time reasoning and decision-making [5][6][16] Core Technological Developments - **Agentic Systems**: These systems can reason, plan, and simulate outcomes, significantly enhancing problem-solving capabilities in various domains [6][7] - **Open Models**: The rise of open-source AI models has democratized access to AI technology, leading to rapid innovation and widespread adoption across industries [8][12] - **Physical AI**: Advances in physical AI are enabling machines to understand and interact with the physical world, which is crucial for applications in robotics and autonomous vehicles [25][26] Product Innovations - **AlphaMyo**: NVIDIA's new autonomous vehicle AI, capable of reasoning and decision-making based on real-time data, is set to revolutionize self-driving technology [33][34] - **Cosmos**: A foundation model for physical AI that integrates various data types to enhance AI's understanding of the physical world [31][32] - **Vera Rubin Supercomputer**: A new AI supercomputer designed to meet the increasing computational demands of AI, featuring advanced architecture and high-speed data processing capabilities [55][56] Strategic Partnerships - **Collaboration with Siemens**: NVIDIA is integrating its technologies into Siemens' platforms to enhance industrial automation and simulation capabilities [49][50] - **Enterprise Integration**: Partnerships with companies like Palantir, ServiceNow, and Snowflake are transforming enterprise AI applications, moving towards more intuitive user interfaces [24][25] Market Outlook - **Autonomous Vehicles**: The transition to autonomous vehicles is anticipated to accelerate, with a significant percentage of cars expected to be autonomous within the next decade [42][43] - **AI in Industries**: The integration of AI into various sectors, including manufacturing and design, is expected to drive a new industrial revolution [50][51] Additional Insights - **Investment in R&D**: A significant portion of R&D budgets is shifting towards AI, indicating a long-term commitment to AI development across industries [3][4] - **Customization of AI**: Companies can now customize AI models to fit specific needs, enhancing their operational efficiency and effectiveness [19][20] This summary encapsulates the key points discussed during the NVIDIA conference, highlighting the company's strategic direction, technological advancements, and market implications.
Nvidia launches Alpamayo, open AI models that allow autonomous vehicles to ‘think like a human'
TechCrunch· 2026-01-05 20:27
At CES 2026, Nvidia launched Alpamayo, a new family of open-source AI models, simulation tools, and datasets for training physical robots and vehicles that are designed to help usher autonomous vehicles reason through complex driving situations.“The ChatGPT moment for physical AI is here – when machines begin to understand, reason, and act in the real world,” Nvidia CEO Jensen Huang said in a statement. “Alpamayo brings reasoning to autonomous vehicles, allowing them to think through rare scenarios, drive s ...
人均1个亿,黄仁勋拟砸下30亿美元,「买断」OpenAI昔日劲敌
3 6 Ke· 2025-12-31 11:50
AI淘金热进入深水区,卖铲子的人,开始下场挖矿了。 当英伟达被曝出以20亿-30亿美元洽谈收购AI21 Labs,这是提前锁定「下一代AI主导权」,而不是一笔普通的技术并购。 这笔交易尚未官宣,但行业认为「大概率会发生」。 如果最终成交价落在30亿美元,这将成为英伟达历史上金额最高的一笔AI并购。 这也解释了为什么很多业内人第一反应不是「AI21要起飞了」,而是:这是一场典型的高价「人才收割」。 在算力称王的时代,这家全球最强芯片公司,第一次把巨额支票直接投向模型与人才本身,信号异常明确:AI战争,已经从训练阶段,转向推理与系统 整合的终局之战。 AI21 Labs 在2022年生成式AI爆发前,AI21就是以色列AI赛道的「门面担当」,技术路线颇具学术气质: 强调可控文本生成 更让人吃惊的是,AI21 Labs全职员工规模约200人,折算下来,人均「身价」高达1000万至1500万美元,远高于大多数独角兽并购案例。 曾与OpenAI唱对台戏的独角兽 2021年,AI21 Labs的位置并不尴尬。 AI21由Amnon Shashua教授、Yoav Shoham教授与Ori Goshen于2017年联合创立, ...
深度解析世界模型:新范式的路线之争,实时交互与物理仿真
海外独角兽· 2025-12-17 07:53
我们相信 26 年会是多模态技术的大年,其中视频生成会快速进步让应用大规模落地,而世界模型 则会有研究上的科学突破,甚至开始从 research 走向 production。 在相当长的一段时间内, World Model 这一概念始终处于较为混沌的状态;直到近半年,随着技术 路径逐渐收敛,尤其是在具身智能与真实交互场景中出现了初步落地的案例,世界模型的轮廓开始 变得清晰。 作者:Cage、Haozhen 如果和语言模型对比:语言模型解决的是语义层面的压缩和推理,预测下一个 token;世界模型是 在解决下一步更根本的问题,AI agent 是否能真正理解时间与空间,并进行预测下一帧、下一个行 动。如果和视频生成模型对比:世界模型在交互性、实时性、长时记忆和物理合理性这四点上都需 要更进一步。 于是行业中的玩家开始在这些提升方向有了各自的 bet, World Model 领域逐步分化出两条路线: 一条以实时视频生成为核心,服务文娱、游戏等 for human 的消费者场景;另一条以显式 3D 结构 为中心,服务机器人、自动驾驶等 for AI 的领域。 本文沿着这个路线分化展开,拆解两条路线的技术趋势和落地 ...
Technicals Could Point to Upside for This New Crypto ETF
Etftrends· 2025-12-12 20:28
Core Insights - The current volatility in Bitcoin is negatively impacting altcoins, leading to investor hesitation in the crypto market [1][5] - Despite the negative sentiment, this may present a buying opportunity for altcoins, particularly for the CoinShares Altcoins ETF (DIME) [1][2] Market Sentiment - The overall sentiment towards altcoins is currently very negative, with the CMC Altcoin Season Index at 20, indicating a Bitcoin-favored market phase [4][6] - The CoinMarketCap's Fear and Greed Index is at 22, reflecting investor hesitation and making it difficult for an altcoin season to emerge [6] Technical Analysis - Technical conditions suggest a potential rebound for altcoins, particularly when the 30-day trading average falls below the 12-month average, which historically precedes a rally [7][8] - This pattern has previously indicated periods of low activity followed by market recoveries, suggesting a possible near-term bullish case for DIME [8]