minor update

Author: ModiShi

public/OpenGO1/index.html

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                         Open-sourcing GO-1: <br>The Bitter Lessons of Building VLA Systems at Scale
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-                        However, once these models are deployed as the robots' “brain,” the reality looks different. Prediction accuracy only influences how well an action might succeed, a matter of percentages. The pipeline itself, especially the parts beyond algorithms or model design that are often overlooked by researchers, determines whether an action succeeds at all. This is a <b class="text-white font-black">strict zero-or-one outcome</b>.
+                        However, once these models are deployed as the robots' "brain", the reality looks different. Prediction accuracy only influences how well an action might succeed, a matter of percentages. The pipeline itself, especially the parts beyond algorithms or model design that are often overlooked by researchers, determines whether an action succeeds at all. This is a <b class="text-white font-black">strict zero-or-one outcome</b>.
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-                        Here's a problem that keeps robotics researchers up at night: the random noise in your testing setup is often larger than the actual improvements you're trying to measure. You spend weeks developing what you think is a breakthrough, but when you test it on real hardware, the measurement uncertainty is so high that you can't tell if your method actually works. The same model tested in the morning versus afternoon can show completely different success rates just because the lighting changed or someone moved an object slight
+                        Here's a problem that keeps robotics researchers up at night: the random noise in your testing setup is often larger than the actual improvements you're trying to measure. You spend weeks developing what you think is a breakthrough, but when you test it on real hardware, the measurement uncertainty is so high that you can't tell if your method actually works. The same model tested in the morning versus afternoon can show completely different success rates just because the lighting changed or someone moved an object slightly.
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