tensor processing units (TPUs)

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Prediction: These Supercharged Growth Stocks Will Soar by 2028
The Motley Fool· 2025-09-27 09:20
These three stocks have huge growth opportunities ahead.Growth stocks continue to lead the market higher, and with artificial intelligence (AI) still in its early innings, that looks like the strong growth could continue over the next few years. Even though the market is trading near all-time highs, there are still plenty of stocks with good upside from here.Let's look at three stocks with huge growth opportunities still in front of them that could soar by 2028. 1. BroadcomAs the AI market starts to shift t ...
It isn't your imagination; Google Cloud is flooding the zone
TechCrunch· 2025-09-25 04:41
The $100 billion partnership between Nvidia and OpenAI, announced Monday, represents – for now – the latest mega-deal reshaping the AI infrastructure landscape. The agreement involves non-voting shares tied to massive chip purchases and enough computing power for more than 5 million U.S. households, deepening the relationship between two of AI’s most powerful players.Meanwhile, Google Cloud is placing a different bet entirely. While the industry’s biggest players cement ever-tighter partnerships, Google is ...
Google is going 'all in' on AI: It's part of a troubling trend in big tech
TechXplore· 2025-05-31 01:40
谷歌AI战略 - 谷歌推出"AI mode"新功能 将作为搜索引擎的新选项在美国推出 该功能类似于与专家对话 [2] - 公司采取"all-in"全面投入AI的战略 不仅将AI技术整合到不同应用中 还提供覆盖整个AI供应链的产品 实现垂直整合 [3] - 垂直整合涵盖从AI芯片到用户界面(如谷歌地图和Gmail)的全链条 [3] AI行业垂直整合趋势 - 除谷歌外 OpenAI收购苹果前设计师联合创立的硬件初创公司 将硬件开发集中化 [4] - 亚马逊采取类似策略 拥有云计算平台 定制芯片 设备计划 并在产品中整合更多AI服务 [4] - 这可能是大型科技公司垂直整合趋势的开端 对用户和公司都有重大影响 [5] 谷歌AI技术栈 - 硬件层:开发自有AI芯片TPU 声称比通用处理器具有更优性能和效率 [6] - 基础设施层:使用自有云基础设施满足计算能力 网络和存储需求 [8] - 模型开发层:利用内部研究能力推动产品开发 包括机器学习 机器人 语言模型和计算机视觉 [8] - 数据层:从所有谷歌平台持续获取用户数据 包括搜索引擎 地图和邮箱 [9] 垂直整合的影响 - 加剧市场力量失衡 少数主导公司可对商品服务收取更高溢价 滥用在线广告行为 [10] - 集中AI技术栈各层于单一公司 提高小公司进入壁垒 大公司将一切内部化 [11] - 减少创新动力 消除通常推动创新的商业竞争 [12] - 数据依赖使谷歌等行业巨头获得更大权力 通过多平台持续获取数据流 [12] 垂直整合的脆弱性 - 成功依赖于内部集中最佳知识和专业知识 导致知识囤积 [13] - 知识囤积减少社会学习 加大市场"赢家"和"输家"差距 造成行业整体脆弱 [14] - 集中化导致缺乏韧性 因为故障点集中 [14] - 减少与外部供应商互动 消除外部审查 可能导致公司采取更高风险行为 [15] 监管与透明度问题 - 当前AI放松监管趋势扩大技术发展与监管间差距 [16] - 大型科技公司变得日益不透明 缺乏透明度引发对组织实践(特别是数据实践)的担忧 [16] - AI领域垂直整合趋势将进一步增加不透明性 加剧现有透明度问题 [16]