Antioch 获 3200 万美元 A 轮,打造物理 AI 仿真测试基建

Rohan Paul · @rohanpaul_ai · X·2026-09-08 23:37·32分钟前
AI 导读

Antioch Robotics 完成 3200 万美元 A 轮融资,由 Greylock 领投,旨在让物理 AI 团队像跑软件测试套件一样测试新版本。其仿真基础设施将场景变为软件对象,可在 Isaac Sim 或 Isaac Lab 中编写测试并接入 CI/CD,使仿真成为物理 AI 的发布门禁。合作方包括 Amazon、Ring、NVIDIA Robotics 和 Nebius AI。

Rohan Paul@rohanpaul_ai
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Antioch 获 3200 万美元 A 轮,打造物理 AI 仿真测试基建

2026-09-08 23:37· 32分钟前
AI 导读

Antioch Robotics 完成 3200 万美元 A 轮融资,由 Greylock 领投,旨在让物理 AI 团队像跑软件测试套件一样测试新版本。其仿真基础设施将场景变为软件对象,可在 Isaac Sim 或 Isaac Lab 中编写测试并接入 CI/CD,使仿真成为物理 AI 的发布门禁。合作方包括 Amazon、Ring、NVIDIA Robotics 和 Nebius AI。

Physical AI teams should be able to test a new release the way software teams run a test suite.

simulation must become trustworthy enough to act as a release gate for physical AI.

@antiochrobotics just raised a $32 mn Series A to narrow that gap.

The company is building simulation infrastructure where the scenario itself becomes a software object.

You can write a test locally in Isaac Sim or Isaac Lab, define parameter distributions, then fan that scenario out across cloud GPUs. More importantly, those simulations can be connected directly to CI/CD.

In robotics, the bug may depend on a weird combination of wind, lighting, geometry, sensor noise, human traffic, or contact dynamics. Turning that exact physical state into a repeatable test is much harder.

But with simulation, when a robot fails in deployment, you can reproduce the same failure in simulation, vary the conditions around it, and keep those tests for every release after that.

AntiochToday, we’re announcing Antioch’s $32 million Series A, led by @GreylockVC with participation from @A_StarVC, @Category_VC, @BoxGroup, @IcehouseVenture, and ang...

来源:Rohan Paul· x.com