EVOLVE26期间的预期：10月27日加入CUBE
跨企业运行人工智能agents需要的不仅仅是获取计算电源。 公司还需要管理整个云层和地上系统的数据安全、治理和业绩，特别是在代理工作流程进入生产过程中。
在去年的EVOLVE25活动中，Cloudera Inc. 将自己定位为混合工作量的平台，采用“任何地方的AI”方法，涵盖边缘、基础设施和云层。 现在，公司希望兑现这一承诺，因为企业让代理AI在日益复杂的数据环境中工作，据CUBE研究的主要分析师Paul Nashawaty说。
" 去年的叙述是建立一个混合的，" 任何地方的AI " 基金会。 “今年，人们期望对话将推动这一愿景的实现。 重点已从抽象潜力转向大规模运行生产级AI的机械，证明企业数据架构能够处理代理工作流程的硬度。”
在纽约市Cloudera EVOLVE26,CUBE将报道公司如何将其混合AI战略转化为生产能力，包括数据治理的进步，代理工作流程和AI在分布式环境中的部署。 CUBE独家报导10月27日播出，(* 下文披露。 )
Cloudera 以 " AI Wherewhere " 方法为基础
Cloudera曾经缓慢地拥抱公共云，现在已将混合基础设施作为其AI战略的核心。 8月，Cloudera Anywhere Cloud平台发布公司，旨在支持AI应用软件在公共云层和前提环境中的部署和管理。 该平台还为各组织提供了一种途径，在系统之间不移动敏感信息的情况下将AI能力带入专有数据。
" Cloudera Anywhere Cloud反映了向`AI wherewhere, ' 的战略成熟，从仅仅获得数据转变为有能力在数据所在的地方部署agents。 " “它突出了一种建筑结构的转变，即计算转向数据而不是替代数据，这对于减少延迟和维持分布式企业环境中的治理至关重要。”
这一转变解决了企业面临的一个实际障碍：AI agents需要获得商业数据，但是在环境之间移动信息可能会带来安全风险、合规问题和额外费用。 Cloudera Anywhere Cloud旨在让各组织在支持现有基础设施的应用和在分布式环境中保持连贯一致的治理的同时，对AI的工作量进行更大的控制。
这一方法也反映了Cloudera为使混合人工智能部署更具可控性所做的努力，因为各组织已经超越了试点项目。 该平台不要求企业在一个单一的环境中整合数据，而是支持现有基础设施的人工智能工作量。
称 Cloudera的首席产品官Leo Brunnick。 “云云带来的云速和灵活性直接提供给企业数据，使客户能够加快AI举措，同时保持对它的完全所有权，并优化基础设施和信物的成本。”
进入EVOLVE26的问题是，这一方法如何能够有效地支持AI生产。 除了部署agents之外，企业还必须考虑工作量业绩、基础设施成本以及管理分布环境中的自主系统所需的控制。
Mistral伙伴关系推进主权AI能力。
数据主权是Cloudera混合AI策略的另一部分。 对于跨国经营或受管制行业的企业来说，使用专有信息而不将其转让给外部AI服务的能力可以影响它们采用的模型和平台。
Cloudera正在将其管理的数据架构定位为这些部署的基础，使各组织能够管理人工智能工作量，同时保留对敏感信息的控制。 根据Nashawaty的说法，该公司的做法也将其与主要侧重于计算能力的基础设施供应商区分开来。
“Cloudera的竞争优势是它能够弥合存储数据与移动数据之间的差距，” “虽然其他云基础设施提供者提供原始计算，但Cloudera正在通过提供一个开放的、有管理的、在混合环境中始终一致的数据层来区分自己。 不只是存储，而是提供AI应用程序需要的可信数据基础
该战略在9月份又获得了另一个组成部分，当时Cloudera 宣布与法国AI开发商Mistral AI SAS建立了伙伴关系。 合作的宣布领先圣保罗的EVOLVE26事件，带来 Mistral的AI模型和定制能力更接近通过Cloudera平台管理的企业数据。 它为客户在不向外部环境发送专有信息的情况下开发专门的AI应用程序提供了另一个选项。
一个重要要素是Mistral Forge，它允许企业使用自己的数据自定义AI模型。 根据NAND Research首席分析师Steve McDowell的说法，这种能力对数据居住要求严格的组织或对披露知识产权的关切特别重要。
Mistral Forge是这项公告中最令人信服的部分，“能够使用企业数据创建和微调 Mistral模型而不移动该数据是极其强大的。 它带来是一个已知实体支持的已知模型，它可以吸引对开放量级模型起源感兴趣的企业，这些模型大多在中国开发。 这比OpenAI、Anthropic和Google更灵活
该伙伴关系还将是纽约EVOLVE26对话的一部分，Cloudera和Mistral AI计划参加侧重于部署企业AI应用的实践讲座。 程序将解决将代理工作流程转移到生产过程中的实际挑战，同时保持对企业数据的控制。
对Cloudera来说，更大的挑战是表明其混合AI架构可以简化部署而不需要企业牺牲灵活性或控制。 CUBE的覆盖范围将提供更多的视角，说明这些能力是如何运用的，以及各组织在扩大AI规模时继续遇到哪些障碍。
CUBE 事件实时流
别错过CUBE10月27日EVOLVE26的报导。 此外，您可在活动结束后按要求访问 CUBE 的独家内容。
如何观看CUBE访谈
我们为各位提供各种方式来观看CUBE对EVOLVE26的报导，包括CUBE的专用网站和YouTube频道。 您也可在SiliconANGLE上获得今年事件的所有报道。
CUBE播客
SiliconANGLE的"TheCUBE Pod"可以在Apple Podcasts,Spotify和YouTube上获得，你可以在上路时享受。 SiliconANGLE的John Furrier和Dave Vellante讨论企业技术的最大趋势
SiliconANGLE还制作了我们的每周"Breaking Analysis"节目，Vellante在节目中考察了企业技术方面的主要发展，将CUBE的见解与企业技术研究的支出数据结合起来，在Apple Podcasts,Spotify和YouTube上可以获得。
来宾
在EVOLVE26期间，CUBE将专访行业高管、技术领袖和专家，讨论Cloudera的最新创新、缩放代理AI的挑战以及跨混合环境的数据治理日益重要。
(*披露：CUBE是EVOLVE26的付费媒体合作伙伴。 CUBE活动报道的主办方对CUBE或SiliconANGLE上的内容没有编辑控制。 )
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What to expect during EVOLVE26: Join theCUBE on Oct. 27
Running artificial intelligence agents across an enterprise requires more than access to computing power. Companies also need to manage data security, governance and performance across cloud and on-premises systems, particularly as agentic workflows move into production.
At last year’s EVOLVE25 event, Cloudera Inc. positioned itself as a platform for hybrid workloads, with an “AI anywhere” approach that encompasses the edge, on-premises infrastructure and the cloud. Now, the company is looking to make good on that promise as enterprises put agentic AI to work across increasingly complex data environments, according to Paul Nashawaty, principal analyst for theCUBE Research.
“Last year, the narrative was about establishing a hybrid, ‘AI anywhere’ foundation,” he said. “This year, expect the conversation to pivot to the operationalization of that vision. The focus has moved from abstract potential to the mechanics of running production-grade AI at scale, proving that enterprise data architectures can handle the rigors of agentic workflows.”
At Cloudera EVOLVE26 in New York City, theCUBE will cover how the company is translating its hybrid AI strategy into production capabilities, including advances in data governance, agentic workflows and AI deployment across distributed environments. TheCUBE’s exclusive coverage airs Oct. 27, featuring conversations with industry leaders and experts. (* Disclosure below.)
Cloudera builds on ‘AI Anywhere’ approach
Cloudera, once slow to embrace public cloud, has now made hybrid infrastructure central to its AI strategy. In August, the company launched the Cloudera Anywhere Cloud platform, designed to support the deployment and management of AI applications across public clouds and on-premises environments. The platform also provides a way for organizations to bring AI capabilities to proprietary data without moving sensitive information between systems.
“Cloudera Anywhere Cloud reflects a strategic maturity toward ‘AI everywhere,’ moving from just having access to data to having the capability to deploy agents where the data lives,” Nashawaty said. “It highlights an architectural shift where the compute moves to the data, rather than the alternative, which is critical for reducing latency and maintaining governance in distributed enterprise settings.”
That shift addresses a practical obstacle for enterprises: AI agents need access to business data, but moving that information between environments can introduce security risks, compliance concerns and additional costs. Cloudera Anywhere Cloud is designed to give organizations greater control over where AI workloads run while supporting applications on existing infrastructure and maintaining consistent governance across distributed environments.
The approach also reflects Cloudera’s effort to make hybrid AI deployments more manageable as organizations expand beyond pilot projects. Rather than requiring enterprises to consolidate their data in a single environment, the platform supports AI workloads across existing infrastructure.
“Organizations shouldn’t have to choose between innovation and control,” said Cloudera’s Chief Product Officer Leo Brunnick. “Cloudera Anywhere Cloud brings the speed and flexibility of the cloud directly to enterprise data, allowing customers to accelerate AI initiatives while maintaining complete ownership of it, with optimized cost of infrastructure and tokens.”
The question heading into EVOLVE26 is how effectively that approach can support production AI at scale. Beyond deploying agents, enterprises must account for workload performance, infrastructure costs and the controls needed to manage autonomous systems across distributed environments.
Mistral partnership advances sovereign AI capabilities
Data sovereignty is another part of Cloudera’s hybrid AI strategy. For enterprises operating across national borders or in regulated industries, the ability to use proprietary information without transferring it to external AI services can influence which models and platforms they adopt.
Cloudera is positioning its governed data architecture as a foundation for those deployments, allowing organizations to manage AI workloads while retaining control over sensitive information. The company’s approach also distinguishes it from infrastructure providers focused primarily on computing capacity, according to Nashawaty.
“Cloudera’s competitive edge is its ability to bridge the gap between data-at-rest and data-in-motion,” he said. “While other cloud infrastructure providers offer raw compute, Cloudera is distinguishing itself by providing an open, governed data layer that remains consistent across hybrid environments. It isn’t just about storage; it’s about providing the trusted data foundation that AI applications require to be performant and compliant.”
That strategy gained another component in September when Cloudera announced a partnership with French AI developer Mistral AI SAS. The collaboration, announced ahead of the EVOLVE26 event in São Paulo, brings Mistral’s AI models and customization capabilities closer to enterprise data managed through Cloudera’s platform. It gives customers another option for developing specialized AI applications without sending proprietary information to external environments.
One significant element is Mistral Forge, which allows enterprises to customize AI models using their own data. That capability could be particularly important for organizations with strict data residency requirements or concerns about exposing intellectual property, according to Steve McDowell, chief analyst at NAND Research.
“Mistral Forge is the most compelling part of this announcement,” he said. “Being able to use enterprise data to create and fine-tune a Mistral model without moving that data is extremely powerful. It brings a known model backed by a known entity, which can appeal to enterprises concerned about the origins of open-weight models, most of which are developed in China. It’s a more flexible approach than we see with OpenAI, Anthropic and Google, which all require you to bring your data to them.”
The partnership will also be part of the conversation at EVOLVE26 in New York, where Cloudera and Mistral AI are scheduled to participate in hands-on sessions focused on deploying enterprise AI applications. The program will address the practical challenges of moving agentic workflows into production while maintaining control over enterprise data.
For Cloudera, the larger challenge is demonstrating that its hybrid AI architecture can simplify deployment without requiring enterprises to sacrifice flexibility or control. TheCUBE’s coverage will provide additional perspectives on how those capabilities are being applied and where organizations continue to encounter obstacles as they scale AI.
TheCUBE event livestream
Don’t miss theCUBE’s coverage of EVOLVE26 on Oct. 27. Plus, you can access theCUBE’s exclusive content on demand after the event.
How to watch theCUBE interviews
We offer you various ways to watch theCUBE’s coverage of EVOLVE26, including theCUBE’s dedicated website and YouTube channel. You can also get all the coverage from this year’s events on SiliconANGLE.
TheCUBE podcasts
SiliconANGLE’s “theCUBE Pod” is available on Apple Podcasts, Spotify and YouTube, which you can enjoy while on the go. During each podcast, SiliconANGLE’s John Furrier and Dave Vellante discuss the biggest trends in enterprise tech, including AI, cloud, cybersecurity and infrastructure, with context and analysis.
SiliconANGLE also produces our weekly “Breaking Analysis” program, where Vellante examines major developments in enterprise tech, combining insights from theCUBE with spending data from Enterprise Technology Research, available on Apple Podcasts, Spotify and YouTube.
Guests
During EVOLVE26, theCUBE will feature interviews with industry executives, technology leaders and experts discussing Cloudera’s latest innovations, the challenges of scaling agentic AI and the growing importance of data governance across hybrid environments.
(* Disclosure: TheCUBE is a paid media partner for EVOLVE26. Sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)
Photo: SiliconANGLE
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