Essentially that trying to utilize multiple sensors cripples any progress (given that resources will never be infinite).
For example, if your lidar sensor is 99.999% percent sure there is an obstacle in front of you, surely it's helpful to take that information into account, even if it is a tiny bit uncertain/noisy.
More data in any situation where bandwidth is already maximized will lead to entropy and noise. However, if the capabilities were there to process all of that data in low latency scenarios with headroom to spare, surely adding additional sensors and data points would lead to a more complete model of spatial awareness for the car.
That's all hypothetical and reliant on ignoring the realities of running a business and tech development lol
Fusion is hard. As hard as getting humans to agree. Been there. In both situations.
And of course you can concentrate on improving one echo chamber, err single sensor. But you can never come past its fundamental limitations.