内容来源：https://aibusiness.com/agentic-ai/sambanova-s-strategic-move-in-ai-market

内容总结：

AI芯片市场新动向：SambaNova联手英特尔 押注“智能体推理”新赛道

在生成式AI浪潮中，企业如何迈出第一步？行业观点指出，应优先关注能改善人类信息交互体验的领域。与此同时，AI芯片市场正经历一场从“通用”到“智能体”推理的关键转变，这为新兴厂商创造了差异化竞争的窗口。

近日，独立AI芯片制造商SambaNova Systems发布了新一代SN50芯片，并宣布与科技巨头英特尔建立合作伙伴关系，共同聚焦快速增长的“智能体AI推理”市场。该公司声称，SN50芯片在速度上超越竞品，并具备高内存容量和高效的“代币经济”设计，能通过软件优化的可重构数据流处理器，将AI模型图映射至芯片，从而优化推理性能。

所谓“智能体推理”，指的是AI模型进行多步骤理解与行动的复杂推理过程，这不同于早期的通用型推理任务。随着市场转向要求AI执行更复杂、多步骤的任务，对高性价比、高效率推理硬件的需求日益凸显。SambaNova此举正是为了抓住这一市场机遇，展示其作为生成式AI推理创新者的技术能力。

行业分析师指出，SambaNova长期以来擅长快速运行小型模型，而近期智能体应用的兴起，正使其架构优势得以发挥。然而，挑战依然严峻：智能体推理市场尚处早期阶段，SambaNova不仅需要面对Cerebras、Groq等强劲的专业竞争对手，还需挑战英伟达在AI芯片市场的绝对主导地位。

分析人士强调，要在市场中获得吸引力，“硬件性能只是基础，企业同样看重方案的灵活性、集成度以及厂商的开发者生态系统。”在此背景下，与英特尔的合作被视为SambaNova的关键助力。英特尔庞大的市场覆盖面有望为其带来支撑，但英特尔自身也需在AI应用领域找回增长节奏，应对来自AMD和Arm的竞争压力。

对于密切关注AI硬件市场的企业用户而言，专家的建议是保持灵活与开放。未来几年，市场将出现更多针对特定场景的优化解决方案，这是一个持续演进的领域，过早“将一切固化”并非明智之举。市场格局远未定型，变化必将持续发生。

中文翻译：

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如何选择首个生成式AI应用场景
要开启生成式AI之旅，首先应关注能够优化人类信息交互体验的领域。

随着市场向更复杂、多步骤推理需求转变，SambaNova与英特尔合作，致力于提供高性价比的AI推理系统。
在快速迭代的AI市场中进展缓慢的独立AI芯片制造商SambaNova Systems，近日发布新款芯片并与英特尔达成合作，以应对日益增长的智能体AI推理需求。

2月24日，SambaNova发布了号称速度超越竞品的最新AI芯片SN50。这家硬件供应商与英特尔的合作（据悉英特尔去年曾考虑收购SambaNova）将专注于提供高性能、高性价比的AI推理产品。

这家成立于2017年的初创公司透露已融资3.5亿美元，但未披露市场估值。该公司上一轮融资发生在2021年4月，通过D轮融资获得6.76亿美元。

据SambaNova介绍，新芯片具备高内存容量和高效的"代币经济学"机制。代币经济学（原为区块链领域术语）指AI模型处理与生成数据时涉及的计算单元经济体系。SN50芯片采用软件优化、可重构的数据流处理器，能将AI模型图映射至芯片以优化推理效能。

新芯片面世之际，正值AI市场焦点从通用推理转向智能体推理。
推理是AI技术中模型将所学应用于新数据的阶段。智能体推理则涉及多步骤推理过程，要求智能体具备理解与执行能力。这种推理类型的转变意味着部分硬件供应商正着力帮助企业通过高性价比芯片实现降本增效。专注推理领域的供应商正吸引主流厂商关注，例如Cerebras与OpenAI的合作，就在探索如何脱离英伟达GPU实现低成本推理。

对SambaNova而言，当前智能体AI推理市场需求攀升正是展示其技术实力的良机。
Futurum Group分析师Brendan Burke指出："SambaNova长期定位于生成式AI推理创新者，擅长快速运行小型模型。"他补充道，虽然该公司仍需寻找理想应用场景，但智能体推理可能成为其差异化优势。

"智能体工具的应用场景与SambaNova的架构高度契合，"Burke表示，"近期智能体的发展意味着规模化推广此技术正当其时——此前市场过度聚焦大模型，并未充分重视小型模型的加速性能优势。"

尽管面临市场机遇，SambaNova仍须应对诸多挑战。首先，智能体推理市场尚处早期阶段，SambaNova需直面Cerebras、Groq等强劲对手，以及AI芯片市场霸主英伟达的竞争压力。
J. Gold Associates总裁Jack Gold坦言："这个赛道参与者众多。"

高德纳分析师Gaurav Gupta进一步指出，该公司需强化差异化优势："要获得市场认可，仅靠硬件性能远远不够。企业选择计算方案时同样看重灵活性、集成度以及供应商的开发者生态。"

不过，SambaNova与英特尔的合作可能带来转机。Gold认为："英特尔市场影响力巨大，关键要看后续合作如何展开。"但Burke提醒，英特尔自身也需寻找理想的AI应用场景，其市场份额长期被AMD和Arm侵蚀。

"这波开源智能体浪潮与产品组合高度契合，将推动专用智能体架构发展，通过AI加速器与CPU协同高效处理各用户数据流，"Burke分析道。

对于密切关注市场动态的企业，Gold建议保持灵活性："未来几年我们将看到专业化解决方案的涌现。市场仍在演进，变革必将发生，切勿过早固化技术路线。"

英文来源：

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Partnering with Intel, SambaNova aims to deliver cost-effective AI inference systems as the market shifts toward more complex, multi-step reasoning.
Independent AI chipmaker SambaNova Systems, which has been slow to gain traction in a fast-moving AI market, launched a new chip and partnered with Intel to focus on the growing demand for agentic AI inference.
SambaNova on Feb. 24 unveiled its latest AI chip, SN50, which it claims is faster than competitive chips. The hardware provider's alliance with Intel -- which reportedly considered acquiring SambaNova as recently as last year -- involves delivering high-performance, cost-efficient AI inference products.
The 2017 startup said it also raised $350 million, though it did not disclose its market valuation. The vendor's last funding round was in April 2021, when it raised $676 million in a Series D.
The new chip has a high memory capacity and efficient "tokenomics," according to SambaNova. Tokenomics -- until recently, a term associated with blockchain technology -- is the economics of the tokens AI models use to process and generate data. The SN50 chip provides a software-optimized, reconfigurable dataflow processor that maps the AI model graph to the chip to optimize inference.
The new chip arrives amid an AI market shifting its focus from generic to agentic inference.
Inference is the stage of AI technology in which the model applies what it learns to new data. Agentic inference involves a multistep reasoning process in which agents must understand and act. This shift in the type of inference means some hardware providers are pushing to help enterprises save money by doing more with less, using more cost-efficient chips. These inference-focused vendors are attracting other mainstream vendors. For instance, Cerebras' partnership with OpenAI is a testing ground for how inference can be performed without Nvidia GPUs and at low cost.
With SambaNova, specifically, its emphasis on agentic AI inference at a time when the market demand for it is up an opportunity to showcase its technology.
"SambaNova has long positioned itself as a generative AI inference innovator, being able to run small models quickly," said Brendan Burke, an analyst at Futurum Group. He added that while the vendor still needs to find its ideal use case, agentic inference could be a differentiator for it.
"The use case of agentic tool usage is optimal for SambaNova's architecture," he said. "The growth of agents recently means that this is the right time to scale this technology when previously, the market really focused on larger models and didn't necessarily value the ability to kind of gain accelerated performance on small models."
Despite this market window, SambaNova still faces some challenges. For one, the agentic inference market is still in its early stages, so SambaNova faces many strong competitors, notably Cerebras and Groq, as well as the dominant vendor in the AI chip market, Nvidia.
"There are a lot of players," said Jack Gold, president of J. Gold Associates.
Moreover, the vendor needs to do more to differentiate, said Gaurav Gupta, an analyst at Gartner.
"It is a lot more than hardware performance that is needed to gain traction," Gupta said. He added that enterprises also choose compute for its flexibility, integration, and the vendor's developer ecosystem.
However, SambaNova's partnership with Intel could be helpful.
"Intel has a large presence; it depends on how all of this shapes out," Gold said.
However, even Intel needs to find its ideal AI application, Burke said, noting that Intel has long been losing market share to AMD and Arm.
"This new wave of open source agents offers a close alignment with the portfolio that encourages the development of agent-specific architectures, where AI accelerators and CPUs are combined to move data for each user efficiently," Burke said.
For enterprises watching the market play out, it is essential to be flexible, Gold said.
"Over the next couple of years, we're going to see optimized silos," he said. "Change will happen; it's still an evolving market. Don't put everything in cement."