SF Tensor YC 申请
SF Tensor 在 Fall 2025 批次的 Y Combinator 中作为一家 B2B 公司进行过。以下是：公司做什么、谁创立了它，以及其 YC 申请，按照真实 YC 表格逐题重建。
- YC 批次
- Fall 2025
- 行业
- B2BInfrastructure
- 团队规模
- 6
- 状态
- Active
- 已发布
- 2025
创始人
Ben KoskaFounder
Luk KoskaFounder
Tom KoskaFounder
SF Tensor 做什么
AI researchers should be pushing the boundaries of what's possible with new architectures and training methods. Instead, they waste weeks configuring cloud infrastructure, debugging distributed systems, and optimizing their GPU code. We know because we lived it: While training our own models across thousands of GPUs earlier this year, we spent more time fighting our infrastructure than doing actual research. That's why we're building two things. First, Elastic Cloud: a managed platform that automatically finds the cheapest GPUs across all providers, handles spot instance preemption, and cuts compute costs by up to 80%. Second, automatic kernel optimization that makes training code run faster by modeling hardware topology, often beating hand-tuned implementations. The problem is that getting high performance across different hardware is genuinely hard. NVIDIA's CUDA moat exists because writing fast kernels requires deep expertise. Most teams either accept vendor lock-in or hire expensive kernel engineers. Our goal is to break the CUDA moat. The compute bottleneck is the biggest constraint on AI progress. NVIDIA can't manufacture enough GPUs, and their monopoly keeps prices astronomical. Meanwhile, AMD, Google, and Amazon are shipping capable alternative hardware that nobody uses because the software is too hard. We're breaking that moat. If we succeed, anyone will be able to train state-of-the-art models without thinking past their PyTorch code.
SF Tensor 的 YC 申请，重建版
Y Combinator 申请
SF Tensor，Fall 2025 期。来自公开数据的真实申请问题解答。
- Founders2
- Company7
- Progress7
- Idea4
- Equity3
- Curious2
- Batch Preference1
Company
SF Tensor
Infrastructure for AI labs to focus on research
We're building two core products. First, Elastic Cloud, a managed platform that automatically finds the cheapest GPUs across cloud providers, handles spot instance interruptions, and cuts compute costs by up to 80%. Second, automatic kernel optimization that models hardware topology to speed up training code, often surpassing hand-tuned implementations. Our goal is to remove infrastructure friction so AI researchers can spend more time experimenting and less time on system ops.
We do not have a set company location; our team is distributed. We expect to remain remote after YC.
Because our work is mostly software infrastructure targeting global AI labs, we do not depend on location. Remote lets us access talent and collaborate with AI researchers worldwide.
21 更多回答 在完整申请中
Founders, Progress, Idea, Equity, Curious, Batch Preference 包含在完整版中。创建免费账户即可在 YC Insights 中打开，紧邻每个其他 YC 批次。
常见问题解答
这是 SF Tensor 的真实 YC 申请吗？
不是。Y Combinator 对提交的申请保密。这是重建版：使用 SF Tensor 的公开数据（发布笔记、创始人背景、产品描述）回答真实的 YC 表格问题。它展示了像 SF Tensor 这样的公司会如何向 YC 自我介绍，而不是他们提交的文本。
SF Tensor 是哪个 YC 批次的？
SF Tensor 是 Y Combinator Fall 2025 批次的成员。
谁创立了 SF Tensor？
SF Tensor 由 Ben Koska, Luk Koska, Tom Koska 创立。
SF Tensor 做什么？
Infrastructure for AI labs to focus on research.
如何阅读完整的重建申请？
创建免费的 Round Funded 账户。YC Insights 中包含 SF Tensor 的完整 26 个问题的版本，以及其他所有 YC 批次的公司信息。
