据报道，Meta 正在构建人工智能驱动的搜索引擎来与 Google 和 Bing 竞争

据报道，Meta（纳斯达克股票代码：META）正在开发一款人工智能驱动的搜索引擎，他们希望该引擎能够与谷歌（纳斯达克股票代码：GOOGL）和必应（Bing）竞争。

Meta (NASDAQ:META) is reportedly building an AI-driven search engine that they hope will rival Google (NASDAQ:GOOGL) and Bing.

据报道，Meta（纳斯达克股票代码：META）正在开发一款人工智能驱动的搜索引擎，他们希望该引擎能够与谷歌（纳斯达克股票代码：GOOGL）和必应（Bing）相媲美。

Similar to Google’s AI Overview, Meta’s search engine would deliver AI-generated summaries of current events through the Meta AI chatbot. The company’s team has allegedly been working on this project for over eight months, with the goal of reducing Meta’s reliance on Google, which it currently uses as its primary search reference for Meta AI.

与谷歌的人工智能概述类似，Meta 的搜索引擎将通过 Meta AI 聊天机器人提供人工智能生成的当前事件摘要。据称，该公司的团队已经在这个项目上工作了八个多月，目标是减少 Meta 对谷歌的依赖，目前 Meta AI 的主要搜索参考是谷歌。

While AI is widely touted as a game-changer for everything from workplace productivity to societal efficiency, in reality, most consumers primarily use AI chatbots as glorified search engines. This effectively turns these AI chatbots into alternative search engines, saving users time from piecing together answers from multiple sources as they need to do in conventional search engines.

尽管人工智能被广泛吹捧为从工作场所生产力到社会效率等各个方面的游戏规则改变者，但实际上，大多数消费者主要将人工智能聊天机器人用作美化的搜索引擎。这有效地将这些人工智能聊天机器人转变为替代搜索引擎，从而节省了用户在传统搜索引擎中需要从多个来源拼凑答案的时间。

When these chatbots became popular, traditional search engines actually started losing market share to these up-and-coming AI chatbots that were answering search queries more efficiently for their users.

当这些聊天机器人变得流行时，传统搜索引擎实际上开始失去市场份额，而这些新兴的人工智能聊天机器人正在为用户更有效地回答搜索查询。

Leading search providers like Google quickly noticed this shift and infused AI into their search processes, allowing users to receive AI-generated summaries without leaving the traditional search interface—and apparently, it’s paying off.

像谷歌这样的领先搜索提供商很快就注意到了这一转变，并将人工智能融入到他们的搜索过程中，允许用户在不离开传统搜索界面的情况下接收人工智能生成的摘要——显然，它正在得到回报。

In its recent Q3 earnings call, Google reported a 35% year-over-year revenue increase to $11.4 billion, attributing its AI infrastructure and generative AI features as driving forces for revenue growth. Even though these AI tools don’t directly generate revenue, their presence enhances the user experience and attracts more users, ultimately driving revenue through channels like ad placements.

在最近的第三季度财报电话会议中，谷歌报告收入同比增长 35%，达到 114 亿美元，将其人工智能基础设施和生成式人工智能功能视为收入增长的驱动力。尽管这些人工智能工具并不直接产生收入，但它们的存在增强了用户体验并吸引了更多用户，最终通过广告投放等渠道增加收入。

Meta, whose revenue model heavily relies on advertising, could likely achieve similar results by building its own AI-powered search platform.

Meta 的收入模式严重依赖广告，它很可能通过构建自己的人工智能搜索平台来实现类似的结果。

OpenAI eyes in-house chip production

OpenAI着眼于内部芯片生产

Amid a global shortage of high-performance chips, OpenAI is reportedly working to design and produce its own specialized chips for AI processing, reducing its reliance on third-party suppliers like NVIDIA (NASDAQ:NVDA) and AMD (NASDAQ:AMD).

据报道，在全球高性能芯片短缺的情况下，OpenAI 正在致力于设计和生产自己的人工智能处理专用芯片，以减少对 NVIDIA（纳斯达克股票代码：NVDA）和 AMD（纳斯达克股票代码：AMD）等第三方供应商的依赖。

OpenAI is working with semiconductor designer, developer, manufacturer, and supplier Broadcom to design these custom chips that will be used primarily for inference rather than training. Inference is the process in which an AI model, having already been trained on vast amounts of data, analyzes new data and makes predictions, which ultimately manifest themselves as outputs.

OpenAI 正在与半导体设计师、开发商、制造商和供应商 Broadcom 合作设计这些定制芯片，这些芯片将主要用于推理而不是训练。推理是人工智能模型经过大量数据训练后，分析新数据并做出预测的过程，最终表现为输出。

One reason OpenAI may be pursuing in-house chip production is to mitigate operating costs and navigate ongoing supply chain challenges. The chip shortage has hit AI companies particularly hard, with high demand for GPUs and other specialized hardware driving up prices and making it difficult for companies to secure the hardware they need. By designing and manufacturing chips internally, OpenAI would gain greater control over its supply chain, similar to how Apple (NASDAQ:AAPL) did when it began designing its own processors for iPhones and Macs.

OpenAI 寻求内部芯片生产的原因之一是降低运营成本并应对持续的供应链挑战。芯片短缺对人工智能公司的打击尤其严重，对 GPU 和其他专用硬件的高需求推高了价格，并使公司难以获得所需的硬件。通过内部设计和制造芯片，OpenAI 将对其供应链获得更大的控制权，类似于苹果公司（纳斯达克股票代码：AAPL）开始为 iPhone 和 Mac 设计自己的处理器时的做法。

Bringing chip production in-house could also lead to significant long-term cost savings for OpenAI. As the company moves toward vertical integration, it could decrease dependency on external suppliers, who have raised prices due to the high demand and limited supply of AI hardware.

将芯片生产引入内部还可以为 OpenAI 带来显着的长期成本节省。随着公司走向垂直整合，它可能会减少对外部供应商的依赖，由于人工智能硬件的高需求和有限供应，外部供应商提高了价格。

Elon Musk’s xAI pursues new fundraising round

埃隆·马斯克 (Elon Musk) 的 xAI 正在进行新一轮融资

On the heels of OpenAI’s $6.6 billion funding round at a $157 billion valuation, Elon Musk’s AI company, xAI, has announced that it is in discussions for another funding round that would push xAI’s valuation over $40 billion. This follows a recent $6 billion raise that valued the company at $24 billion just months earlier, underscoring the fact that AI remains a hot sector for investment in what is otherwise a venture capital drought.

继 OpenAI 以 1570 亿美元估值完成 66 亿美元融资后，埃隆·马斯克 (Elon Musk) 的人工智能公司 xAI 宣布正在讨论另一轮融资，这将使 xAI 的估值超过 400 亿美元。几个月前，该公司刚刚完成了 60 亿美元的融资，估值达到 240 亿美元，这突显了这样一个事实：在风险资本匮乏的情况下，人工智能仍然是投资的热门领域。

These major fundraising rounds highlight the unusually large capital needs in artificial intelligence, particularly for companies developing and scaling advanced models. AI development requires substantial investments in computing infrastructure, with some companies spending multiple billions on data centers and GPUs to support training and inference for their AI models. Even top AI companies like OpenAI have acknowledged that profitability remains elusive, with OpenAI not expecting to turn a profit until at least 2029.

这些主要融资轮凸显了人工智能领域异常庞大的资本需求，特别是对于开发和扩展先进模型的公司而言。人工智能开发需要对计算基础设施进行大量投资，一些公司在数据中心和 GPU 上花费数十亿美元，以支持其人工智能模型的训练和推理。即使像 OpenAI 这样的顶级人工智能公司也承认，盈利能力仍然难以捉摸，OpenAI 预计至少要到 2029 年才能实现盈利。

This high-cost environment reflects the unique economics of AI. Companies need high-performance computing environments, vast datasets, and specialized hardware to train and run large language models and other advanced AI systems. However, these items are very expensive. For companies like xAI and OpenAI to remain competitive and continue innovating, they have ever-increasing capital needs to sustain growth and scale their businesses, which is why most AI companies raise money at every chance they can.

这种高成本环境反映了人工智能独特的经济学。公司需要高性能计算环境、大量数据集和专用硬件来训练和运行大型语言模型和其他高级人工智能系统。然而，这些物品非常昂贵。对于像 xAI 和 OpenAI 这样的公司来说，为了保持竞争力并持续创新，他们需要不断增加的资本来维持增长和扩大业务，这就是为什么大多数人工智能公司会抓住一切机会筹集资金。

US tightens AI restrictions on China

美国收紧对中国人工智能的限制

This week, the U.S. Department of the Treasury issued a final rule restricting American investments in China, Hong Kong, and Macau, specifically within areas like AI, semiconductors, microelectronics, and quantum information technologies. The rule prohibits U.S. companies and investors from engaging in certain transactions with entities based in these regions.

本周，美国财政部发布了一项最终规则，限制美国在中国、香港和澳门的投资，特别是在人工智能、半导体、微电子和量子信息技术等领域。该规则禁止美国公司和投资者与这些地区的实体进行某些交易。

“This Final Rule takes targeted and concrete measures to ensure that U.S. investment is

“该最终规则采取了有针对性的具体措施，以确保美国投资