
自三年前ChatGPT横空出世以来,分析师和技术专家——甚至包括谷歌(Google)的一位工程师及该公司前CEO——都曾断言,谷歌在这场关乎未来的人工智能竞赛中处于下风。但如今,情况已发生改变。
这家互联网巨头已推出新的AI软件,并达成多项协议,包括与Anthropic PBC的芯片合作协议。这些举措让投资者相信:谷歌不会轻易输给ChatGPT的开发公司OpenAI及其他竞争对手。谷歌最新发布的多模态模型Gemini 3甫一亮相,便因其在推理、编程以及其他AI聊天机器人“失足”的复杂任务上表现出色而广受好评。谷歌曾一度落后的云业务,也在全球开发AI服务的热潮和算力需求暴增的推动下稳步增长。
有迹象表明,企业对谷歌专研AI芯片的需求正在上升,而它们正是目前少数能替代英伟达(Nvidia Corp.)主导性芯片的产品之一。周一有报道称,Meta Platforms正在洽谈采用谷歌芯片的合作,这一消息推动其母公司Alphabet股价大涨。在巴菲特三季度斥资49亿美元建仓,以及华尔街对其AI战略普遍看好情绪的助推下,自10月中旬以来,Alphabet的市值已增长1万亿美元。
因市场担心OpenAI将面临来自谷歌Gemini的竞争,其主要投资方软银集团(SoftBank Group)的股价在周二跌至两个月低点。英伟达股价当日一度下跌5.51%,市值蒸发2,430亿美元。
对位研究(Counterpoint Research)分析师兼联合创始人尼尔·沙阿表示:“从某种意义上说,谷歌一直是这场AI竞赛中的黑马。如今,这位沉睡的巨人已经完全醒来。”
多年来,谷歌高管一直认为,高成本的深度研发能帮助公司抵御竞争对手,守住其在搜索领域的主导地位,并打造下一代计算平台。直到ChatGPT的出现,给谷歌搜索带来了多年来第一波实质性威胁——尽管谷歌才是OpenAI聊天机器人底层技术的率先研发者。不过,谷歌拥有大量OpenAI所不具备的资源:用于训练与优化AI模型的海量现成数据;源源不断的利润;以及自有的计算基础设施。
谷歌及Alphabet的首席执行官桑达尔·皮查伊在上季度对投资者表示:“我们在AI领域采取了完整、深入、全栈式的布局。而且事实证明,这一布局正在发挥作用。”
关于谷歌可能会受到监管拖累的担忧也正在消散。该公司近期在美国一桩反垄断案件中避免了最严重的后果,即业务拆分,部分原因是监管机构认为AI新势力的崛起对谷歌的竞争威胁足够大。此外,这家搜索巨头在核心业务之外推行多元化的长期努力也取得了一些进展。Alphabet旗下无人驾驶公司Waymo正进入更多城市,并刚刚将高速路驾驶场景纳入其无人出租车服务,这项突破得益于谷歌的大量研发和投资。
谷歌的优势部分源于其经济结构。它是业内少数几家能够打造所谓计算“全栈”的公司之一:既开发直面用户的AI应用(例如广受欢迎的Nano Banana图像生成器),也自研软件模型、云计算架构以及底层芯片。此外,公司还掌握着一座构建AI模型所需的数据宝库,这些数据来自其搜索索引、Android设备、YouTube,且只供自家使用。这意味着,理论上谷歌对AI产品的技术方向拥有更强掌控力,也无需像OpenAI那样依赖外部供应商。
包括微软(Microsoft Corp.)和OpenAI在内的多家科技公司,均已谋划通过自研芯片或建立合作关系来降低对英伟达畅销产品的依赖。多年来,谷歌自研的处理器——张量处理单元(TPU)——实际上仅服务于自身需求。这款芯片最初设计于十多年前,用于加速搜索结果的生成,后经调整用于处理复杂的AI任务。如今,这一局面正在改变:AI初创公司Anthropic在10月宣布,将在一项价值数百亿美元的交易中使用多达100万块谷歌TPU。
周一,科技媒体The Information报道称,Meta计划在2027年将谷歌芯片用于其数据中心。谷歌没有回应具体计划,但表示其云业务对自研TPU与英伟达GPU的需求均在“加速增长”。公司发言人在声明中写道:“多年来,我们一直致力于同时支持这两类芯片。”
Meta周一晚间拒绝就该报道置评。
英伟达发言人周二在声明中表示:“我们为谷歌的成功感到高兴。他们在AI领域取得了重大进展,而我们也会继续向谷歌供货。”该发言人补充道:“英伟达仍领先行业整整一代,我们是唯一能在所有计算场景下运行所有AI模型的平台。”
分析师将Meta的消息视为谷歌成功的重要信号。Quilter Cheviot科技研究主管本·巴林杰在一封邮件中写道:“许多公司都在自研芯片的道路上折戟,但显然,谷歌在此领域为自己增添了新的筹码。”
谷歌也是通过不断冒险才走到今天。2023年初,公司将旗下的AI业务全面整合,由伦敦AI实验室DeepMind负责人戴密斯·哈萨比斯统一领导。此次重组过程并非一帆风顺,最明显的问题是一款图像生成产品的发布出现了失误。多年来,DeepMind专注于蛋白质折叠等研究领域,这些研究虽催生了新的商业策略并斩获诺贝尔奖,但对谷歌的营收贡献微乎其微。重组之后,该AI部门几乎将全部精力都集中在基础模型的研发上,以跟上OpenAI、微软等竞争对手的节奏。
哈萨比斯是业内公认的计算机科学专家,面对竞争对手百万美元的重金挖角,他帮助公司成功留住了核心AI工程师。而他的上司皮查伊在人才投入上也从不吝啬。
Gemini 3 Pro已登上LMArena和Humanity’s Last Exam等备受关注的AI排行榜榜首。OpenAI创始成员安德烈·卡帕西称其“无疑是一款顶级大语言模型”。谷歌在宣传这款模型时强调,它能解决复杂的科学和数学难题,也能处理常见的棘手问题,例如在生成带有文字的图像时出现拼写错误,这些痛点可能会阻碍企业更大规模地采用AI服务。
消费者端的反馈则更难判断。谷歌上周表示,其Gemini应用的用户规模已达到6.5亿。OpenAI近期称,ChatGPT每周的使用人数达到8亿。研究机构Sensor Tower的数据显示,截至10月,Gemini应用的月下载量为7,300万次,低于ChatGPT的9,300万次。
谷歌虽是一家广告巨头,但在探索其他商业模式方面历来步履维艰。其云业务第三季度营收为152亿美元,同比增长34%。尽管如此,谷歌云仍位列行业第三,落后于微软和亚马逊(Amazon)的云服务——这两家公司的云业务收入在最新季度均超过谷歌的两倍。对位研究的沙阿指出,在企业级AI应用落地上,谷歌仍落后于微软和Anthropic。
与此同时,OpenAI正通过向企业销售ChatGPT的高级版本及相关软件来追求盈利。该公司正与博通(Broadcom Inc.)、超微半导体(Advanced Micro Devices Inc.)以及英伟达等芯片厂商达成合作,以支撑其在AI领域的雄心。
AI初创公司Doubleword的CEO梅里耶姆·阿里克表示,谷歌的TPU主要吸引的是少数几家计算量巨大的公司,例如Meta和Anthropic。
巴林杰则认为,芯片行业“并不是只有一个赢家的零和竞争”。
AI开发者只能通过谷歌自家的云服务访问TPU;相比之下,英伟达的GPU使用起来更灵活。阿里克表示:“一旦使用TPU,就等于被锁定在谷歌的云生态中。”
过去,企业往往会尽量避免依赖单一供应商。但如今,凭借在AI领域的巨大进展,谷歌让这种顾虑成为过去。
弗雷斯特研究公司(Forrester)分析师托马斯·哈森表示:“完全可以说,凭借Gemini 3,谷歌已重回竞争行列。套用马克·吐温的那句名言:关于谷歌衰落的报道,不仅被严重夸大,更纯属无稽之谈。”(*)
译者:刘进龙
审校:汪皓
自三年前ChatGPT横空出世以来,分析师和技术专家——甚至包括谷歌(Google)的一位工程师及该公司前CEO——都曾断言,谷歌在这场关乎未来的人工智能竞赛中处于下风。但如今,情况已发生改变。
这家互联网巨头已推出新的AI软件,并达成多项协议,包括与Anthropic PBC的芯片合作协议。这些举措让投资者相信:谷歌不会轻易输给ChatGPT的开发公司OpenAI及其他竞争对手。谷歌最新发布的多模态模型Gemini 3甫一亮相,便因其在推理、编程以及其他AI聊天机器人“失足”的复杂任务上表现出色而广受好评。谷歌曾一度落后的云业务,也在全球开发AI服务的热潮和算力需求暴增的推动下稳步增长。
有迹象表明,企业对谷歌专研AI芯片的需求正在上升,而它们正是目前少数能替代英伟达(Nvidia Corp.)主导性芯片的产品之一。周一有报道称,Meta Platforms正在洽谈采用谷歌芯片的合作,这一消息推动其母公司Alphabet股价大涨。在巴菲特三季度斥资49亿美元建仓,以及华尔街对其AI战略普遍看好情绪的助推下,自10月中旬以来,Alphabet的市值已增长1万亿美元。
因市场担心OpenAI将面临来自谷歌Gemini的竞争,其主要投资方软银集团(SoftBank Group)的股价在周二跌至两个月低点。英伟达股价当日一度下跌5.51%,市值蒸发2,430亿美元。
对位研究(Counterpoint Research)分析师兼联合创始人尼尔·沙阿表示:“从某种意义上说,谷歌一直是这场AI竞赛中的黑马。如今,这位沉睡的巨人已经完全醒来。”
多年来,谷歌高管一直认为,高成本的深度研发能帮助公司抵御竞争对手,守住其在搜索领域的主导地位,并打造下一代计算平台。直到ChatGPT的出现,给谷歌搜索带来了多年来第一波实质性威胁——尽管谷歌才是OpenAI聊天机器人底层技术的率先研发者。不过,谷歌拥有大量OpenAI所不具备的资源:用于训练与优化AI模型的海量现成数据;源源不断的利润;以及自有的计算基础设施。
谷歌及Alphabet的首席执行官桑达尔·皮查伊在上季度对投资者表示:“我们在AI领域采取了完整、深入、全栈式的布局。而且事实证明,这一布局正在发挥作用。”
关于谷歌可能会受到监管拖累的担忧也正在消散。该公司近期在美国一桩反垄断案件中避免了最严重的后果,即业务拆分,部分原因是监管机构认为AI新势力的崛起对谷歌的竞争威胁足够大。此外,这家搜索巨头在核心业务之外推行多元化的长期努力也取得了一些进展。Alphabet旗下无人驾驶公司Waymo正进入更多城市,并刚刚将高速路驾驶场景纳入其无人出租车服务,这项突破得益于谷歌的大量研发和投资。
谷歌的优势部分源于其经济结构。它是业内少数几家能够打造所谓计算“全栈”的公司之一:既开发直面用户的AI应用(例如广受欢迎的Nano Banana图像生成器),也自研软件模型、云计算架构以及底层芯片。此外,公司还掌握着一座构建AI模型所需的数据宝库,这些数据来自其搜索索引、Android设备、YouTube,且只供自家使用。这意味着,理论上谷歌对AI产品的技术方向拥有更强掌控力,也无需像OpenAI那样依赖外部供应商。
包括微软(Microsoft Corp.)和OpenAI在内的多家科技公司,均已谋划通过自研芯片或建立合作关系来降低对英伟达畅销产品的依赖。多年来,谷歌自研的处理器——张量处理单元(TPU)——实际上仅服务于自身需求。这款芯片最初设计于十多年前,用于加速搜索结果的生成,后经调整用于处理复杂的AI任务。如今,这一局面正在改变:AI初创公司Anthropic在10月宣布,将在一项价值数百亿美元的交易中使用多达100万块谷歌TPU。
周一,科技媒体The Information报道称,Meta计划在2027年将谷歌芯片用于其数据中心。谷歌没有回应具体计划,但表示其云业务对自研TPU与英伟达GPU的需求均在“加速增长”。公司发言人在声明中写道:“多年来,我们一直致力于同时支持这两类芯片。”
Meta周一晚间拒绝就该报道置评。
英伟达发言人周二在声明中表示:“我们为谷歌的成功感到高兴。他们在AI领域取得了重大进展,而我们也会继续向谷歌供货。”该发言人补充道:“英伟达仍领先行业整整一代,我们是唯一能在所有计算场景下运行所有AI模型的平台。”
分析师将Meta的消息视为谷歌成功的重要信号。Quilter Cheviot科技研究主管本·巴林杰在一封邮件中写道:“许多公司都在自研芯片的道路上折戟,但显然,谷歌在此领域为自己增添了新的筹码。”
谷歌也是通过不断冒险才走到今天。2023年初,公司将旗下的AI业务全面整合,由伦敦AI实验室DeepMind负责人戴密斯·哈萨比斯统一领导。此次重组过程并非一帆风顺,最明显的问题是一款图像生成产品的发布出现了失误。多年来,DeepMind专注于蛋白质折叠等研究领域,这些研究虽催生了新的商业策略并斩获诺贝尔奖,但对谷歌的营收贡献微乎其微。重组之后,该AI部门几乎将全部精力都集中在基础模型的研发上,以跟上OpenAI、微软等竞争对手的节奏。
哈萨比斯是业内公认的计算机科学专家,面对竞争对手百万美元的重金挖角,他帮助公司成功留住了核心AI工程师。而他的上司皮查伊在人才投入上也从不吝啬。
Gemini 3 Pro已登上LMArena和Humanity’s Last Exam等备受关注的AI排行榜榜首。OpenAI创始成员安德烈·卡帕西称其“无疑是一款顶级大语言模型”。谷歌在宣传这款模型时强调,它能解决复杂的科学和数学难题,也能处理常见的棘手问题,例如在生成带有文字的图像时出现拼写错误,这些痛点可能会阻碍企业更大规模地采用AI服务。
消费者端的反馈则更难判断。谷歌上周表示,其Gemini应用的用户规模已达到6.5亿。OpenAI近期称,ChatGPT每周的使用人数达到8亿。研究机构Sensor Tower的数据显示,截至10月,Gemini应用的月下载量为7,300万次,低于ChatGPT的9,300万次。
谷歌虽是一家广告巨头,但在探索其他商业模式方面历来步履维艰。其云业务第三季度营收为152亿美元,同比增长34%。尽管如此,谷歌云仍位列行业第三,落后于微软和亚马逊(Amazon)的云服务——这两家公司的云业务收入在最新季度均超过谷歌的两倍。对位研究的沙阿指出,在企业级AI应用落地上,谷歌仍落后于微软和Anthropic。
与此同时,OpenAI正通过向企业销售ChatGPT的高级版本及相关软件来追求盈利。该公司正与博通(Broadcom Inc.)、超微半导体(Advanced Micro Devices Inc.)以及英伟达等芯片厂商达成合作,以支撑其在AI领域的雄心。
AI初创公司Doubleword的CEO梅里耶姆·阿里克表示,谷歌的TPU主要吸引的是少数几家计算量巨大的公司,例如Meta和Anthropic。
巴林杰则认为,芯片行业“并不是只有一个赢家的零和竞争”。
AI开发者只能通过谷歌自家的云服务访问TPU;相比之下,英伟达的GPU使用起来更灵活。阿里克表示:“一旦使用TPU,就等于被锁定在谷歌的云生态中。”
过去,企业往往会尽量避免依赖单一供应商。但如今,凭借在AI领域的巨大进展,谷歌让这种顾虑成为过去。
弗雷斯特研究公司(Forrester)分析师托马斯·哈森表示:“完全可以说,凭借Gemini 3,谷歌已重回竞争行列。套用马克·吐温的那句名言:关于谷歌衰落的报道,不仅被严重夸大,更纯属无稽之谈。”(*)
译者:刘进龙
审校:汪皓
Since the launch of ChatGPT three years ago, analysts and technologists — even a Google engineer and the company’s former chief executive — have declared Google behind in the high-stakes race to develop artificial intelligence. Not anymore.
The internet giant has released new AI software and struck deals, such as a chip tie-up with Anthropic PBC, that have reassured investors the company won’t easily lose to ChatGPT creator OpenAI and other rivals. Google’s newest multi-purpose model, Gemini 3, won immediate praise for its capabilities in reasoning and coding, as well as niche tasks that have tripped up AI chatbots. Google’s cloud business, once an also-ran, is growing steadily, thanks in part to the global rush to develop AI services and demand for compute.
And there are signs of rising demand for Google’s specialized AI chips, one of the few viable alternatives to Nvidia Corp.’s dominant gear. A report on Monday that Meta Platforms Inc. is in talks to use Google’s chips sent shares of its parent Alphabet Inc. soaring. The stock has added nearly $1 trillion in market capitalization since mid-October, helped by Warren Buffett taking a $4.9 billion stake during the third quarter and broader Wall Street enthusiasm for its AI efforts.
SoftBank Group, one of OpenAI’s biggest backers, fell to a two-month low on Tuesday on worries about the competition from Google’s Gemini. Nvidia shares fell as much as 5.51% on Tuesday, erasing $243 billion in market value.
“Google has arguably always been the dark horse in this AI race,” said Neil Shah, analyst and cofounder at Counterpoint Research. It’s “a sleeping giant that is now fully awake.”
For years, Google executives have argued that deep, costly research would help the company fend off rivals, defend its turf as the leading search engine and invent the computing platforms of tomorrow. Then ChatGPT came along, presenting the first real threat to Google search in years, even though Google pioneered the tech underpinning OpenAI’s chatbot. Still, Google has plenty of resources that OpenAI doesn’t: a corpus of ready data to train and refine AI models; flowing profits; and its own computing infrastructure.
“We’ve taken a full, deep, full-stack approach to AI,” Sundar Pichai, chief executive officer for Google and Alphabet, told investors last quarter. “And that really plays out.”
Any concerns that Google might be held back by regulators are dying away. The company recently avoided the most severe outcome from a US anti-monopoly case — a breakup of its business — in part because of the perceived threat from AI newcomers. And the search giant has shown some progress in the longtime effort to diversify beyond its core business. Waymo, Alphabet’s driverless car unit, is coming to several new cities and just added freeway driving to its taxi service, a feat made possible by the company’s enormous research and investment.
Some of Google’s edge comes from its economics. It’s one of the few companies that produces what the industry calls the full stack in computing. Google makes the AI apps people use, like its popular Nano Banana image generator, as well as the software models, the cloud computing architecture and the chips underneath. The company also has a data goldmine for constructing AI models from its search index, Android phones and YouTube — data that Google often keeps for itself. That means, in theory, Google has more control over the technical direction of AI products and doesn’t necessarily have to pay suppliers, unlike OpenAI.
Several tech companies, including Microsoft Corp. and OpenAI, have plotted ways to develop their own semiconductors or forge ties that make them less reliant on Nvidia’s bestsellers. For years, Google was effectively its own sole customer for its homegrown processors, called tensor processing units, or TPUs, which the company first designed more than a decade ago to speed up the generation of search results and has since adapted to handle complex AI tasks. That’s changing. AI startup Anthropic said in October said it would use as many as 1 million Google TPUs in a deal worth tens of billions of dollars.
On Monday, tech publication the Information reported that Meta planned to use Google’s chips in its data centers in 2027. Google declined to address the specific plans, but said that its cloud business is “accelerating demand” for both its custom TPUs and Nvidia’s graphics processing units. “We are committed to supporting both, as we have for years,” a spokesperson wrote in a statement.
Meta declined to comment on the report on Monday night.
“We’re delighted by Google’s success,” a spokesperson for Nvidia said in a statement Tuesday. “They’ve made great advances in AI, and we continue to supply to Google.” The spokesperson added: “Nvidia is a generation ahead of the industry – it’s the only platform that runs every AI model and does it everywhere computing is done.”
Analysts read the Meta news as a signal of Google’s success. “Many others have failed in their quest to build custom chips, but Google can clearly add another string to its bow here,” Ben Barringer, head of technology research for Quilter Cheviot, wrote in an email.
Google has taken risks to get here. In early 2023, Google consolidated its AI efforts under Demis Hassabis, the leader of its London AI lab DeepMind. The reshuffle had some bumps, most notably a botched rollout of an image-generation product. For several years, DeepMind pursued research in areas like protein-folding that led to new commercial strategies (and a Nobel prize) but contributed little to Google’s bottom line. Under the reorganization, the AI unit is focused almost squarely on foundational models that keep pace with OpenAI, Microsoft and others.
Hassabis, a renowned computer scientist, has helped retain key AI engineers despite multimillion-dollar offers from rivals. His boss, Pichai, has been willing to splurge on talent.
Gemini 3 Pro has risen to the top of closely watched AI leaderboards on LMArena and Humanity’s Last Exam. Andrej Karpathy, a founding member of OpenAI, said it’s “clearly a tier 1 LLM,” referring to large language models. Google pitched the model as one that can solve complex science and math problems, and address nagging issues — such as generating images and overlaid text with incorrect spelling — that might deter enterprise customers from adopting AI services more widely.
Consumer interest is harder to gauge. Google said last week that 650 million people use its Gemini app. OpenAI recently said ChatGPT hit 800 million weekly users. As of October, Gemini’s app had 73 million monthly downloads, well shy of ChatGPT’s 93 million monthly downloads, according to research firm Sensor Tower.
Google is an advertising behemoth, but it has historically struggled to find other commercial models. Its cloud business reported third-quarter revenue of $15.2 billion, up 34% from the prior year. Still, that remains in third-place behind Microsoft and Amazon Web Services, which posted more than double Google’s cloud sales in the most recent quarter. Counterpoint Research’s Shah said Google’s AI adoption with enterprises lags Microsoft and Anthropic.
Meanwhile, OpenAI is targeting profits by selling a premium version of ChatGPT and adjacent software to companies. It’s cutting deals with chipmakers from Broadcom Inc. to Advanced Micro Devices Inc. to Nvidia to support its AI ambitions.
Google’s TPUs are mostly attractive to a handful of companies with big computing bills, like Meta and Anthropic, said Meryem Arik, CEO of the AI startup Doubleword.
And the chip industry is “not a zero-sum game with just one winner,” said Barringer.
For one, AI developers can only access Google’s chips through the company’s own cloud service. They can use Nvidia’s graphics processing units, or GPUs, more flexibly. “As soon as you use TPUs, you’re locked into” the Google cloud ecosystem, said Arik.
Being tied to a single supplier might have been something companies avoided. That’s no longer the case for Google, thanks to its advances in AI.
“It’s definitely fair to say that Google is back in the game with Gemini 3,” said Thomas Husson, analyst at Forrester. “In fact, to paraphrase a quote attributed to Mark Twain, reports of Google’s death have been widely exaggerated, not to say irrelevant.”
