Cloudera赌注的可移植性，而不是agents，将在企业AI中将其拆分。
企业竞相走向AI自动化，发现他们的模型和数据运行的地方与模型所能做的一样重要。 监管压力、象征性成本上升和对锁定的恐惧促使公司要求对其AI工作量进行更多的控制。
这一需求正在决定数据平台提供者如何进行下一步行动。 Cloudera Inc.开始于Hadoop市场，后来移动到一个覆盖云层和地上基础设施的统一数据层。 据SiliconANGLE Media Inc公司企业编辑Paul Gillin(图，右)说
“我认为大公司早就决定了。 Gillin 称表示，“我认为Cloudera的不同之处在于，他们强烈主张建立基础设施、主权云层、公司能够随心所欲地处理工作量，并相互移动。”
吉林与CUBE的Rebecca Knight(左)在EVOLVE26的独家广播中，在CUBE,SiliconANGLE Media的现场流播室交谈。 他们讨论了AI自动化，并分析了该活动的主旨发言。
主权AI和专用制造的 agents 驱动器AI自动化
EVOLVE26主题发言中经常出现主权和私人AI。 调查指出，监管是企业希望将AI留在自己墙壁内的主要原因。 根据吉林的统计，开放量级模型给了他们一种实现的方法，已经从两年前约20%的象征性使用量增长到今天的80%以上。 Cloudera还在其数据服务中增加了代理工作流程。 他解释说，通用agents更是一种消费现象。
Gillin 称：“他们更像是办公工具，“管理工作量、优化GPU能力、真正与CIO有关的事物
仅仅拥有agent已经不再是边缘，所以Cloudera在它长期存在的多平台游戏上正在翻番。 吉林说，它正在将想要的可移植性企业从云层扩展到他们的AI模型。 他注意到，CIOs在以AI自动化方式相信投球之前，会想知道agents是如何被控制的，他们留下了什么样的审计线索，以及agent的决定如何被记录给监管者。
这与agents关系重大，“这里还是一片荒凉的西部
以及CUBE对EVOLVE26的报导：
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Cloudera bets portability, not agents, will set it apart in enterprise AI
Enterprises racing toward AI automation are finding that where their models and data run matters as much as what the models can do. Regulatory pressure, rising token costs and fear of lock-in are pushing companies to demand more control over their AI workloads.
That demand is shaping how data platform providers pitch their next act. Cloudera Inc. started out in the Hadoop market and later moved to a unified data layer that spans clouds and on-premises infrastructure. It is now positioning itself as an anywhere cloud for AI, according to Paul Gillin (pictured, right), enterprise editor of SiliconANGLE Media Inc.
“I think big companies decided a long time ago. They didn’t want to be beholden to a single cloud provider and that’s sort of baked into the landscape now,” Gillin said. “I think what’s different about Cloudera is that they’re strong proponents of on-premises infrastructure, of sovereign clouds, of companies being able to run their workloads wherever they want and move from one to another.”
Gillin spoke with theCUBE’s Rebecca Knight (left) at EVOLVE26, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed AI automation and provided analysis of the event’s keynote speech.
Sovereign AI and purpose-built agents drive AI automation
Sovereign and private AI came up frequently in the EVOLVE26 keynote. Surveys point to regulation as the main reason enterprises want to keep AI inside their own walls. Open-weight models give them a way to do it, having grown from about 20% of token use two years ago to more than 80% today, according to Gillin. Cloudera is also adding agentic workflows across its data services. General-purpose agents are more of a consumer phenomenon, he explained.
“They’re more of an office worker tool, but the Cloudera agents are tuned to managing data,” Gillin said. “To managing workloads, optimizing GPU capacity, the types of things that really concern CIOs, because they’re paying the bills for these very high training costs.”
Simply having an agent is no longer an edge, so Cloudera is doubling down on its long-standing multiplatform play. It is extending the portability enterprises wanted from their clouds to their AI models, according to Gillin. Before trusting that pitch with AI automation, CIOs will want to know how agents are controlled, what audit trails they leave behind and how agent decisions can be documented for regulators, he noted.
“This is a very big issue with agents right now,” Gillin said. “It’s still a wild west out there with agents.”
Stay tuned for the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of EVOLVE26:
Photo: SiliconANGLE
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