1/ The first generation of enterprise AI borrowed human infrastructure. Service accounts. API keys. User credentials. That worked while AI was mostly assisting people. It becomes much harder once agents act independently across systems.

Inference Labs @inference_labs ·

更多来自 @inference_labs

  1. #1

    From fuel leaks to smoke and fire, many airport risks are visual before they become operational problems. @hudsongrae_me is showing how Sertn can train models to detect these anom…

    Inference Labs @inference_labs ·
    视频封面
  2. #2

    1/ Airports already have cameras covering stands, baggage halls, terminals, and airfield movement. The opportunity is not always adding more hardware. It is turning existing foota…

    Inference Labs @inference_labs ·
    1/ Airports already have cameras covering stands, baggage halls, terminals, and…
  3. #3

    Long-horizon AI is making outputs much larger and workflows much harder to inspect. The challenge is no longer only whether a model can finish the task, but whether the path there…

    Inference Labs @inference_labs ·
  4. #4

    In a factory, airport, or logistics site, the physical event may last seconds. The model output may trigger a workflow immediately. Sertn is useful because evidence can be created…

    Inference Labs @inference_labs ·
  5. #5

    NVIDIA now describes physical AI safety as something that has to span hardware, software, models, sensors, and deployment. That is important. A safe robot is not just a good model…

    Inference Labs @inference_labs ·
  6. #6

    Confidential computing protects workloads while they run. Verification answers a different question: did the expected workload actually run, and can we establish that continuously…

    Inference Labs @inference_labs ·

查看 @inference_labs 的全部帖子