smaddox
Joined 11 years ago
Joined 11 years ago
Gold / Global M2 would be a better metric, but I haven't analyzed that yet.
Also, you don't need to solder wires to the sample. But if you want to measure the hall resistance of a thin film of a semiconductor, you can solder a glob of indium on to four corners of a 1 cm x 1 cm wafer, put it in a magnetic field, and then do basically the same measurement as four point probe, except not inline.
For that short of a run, you'll spend more time waiting for the node to come up, downloading the dataset, and compiling the model, though.
Huh? Is this something where there's multiple incremental steps in the process, and that date is just the final approval stamp, or does it actually just take more than 1.5 years?
Well, that definitely changes my opinion on how feasible/competitive camera-only autonomous driving can be.
It's not an event camera, so it's very much taking images, which are then being processed by computer vision algorithms.
Event cameras seem more viable than CMOS sensors for autonomous vehicle applications in the absence of LIDAR. CMOS dynamic range and response isn't as good as the human eye. LIDAR+CMOS is considerably better in many ways.
AMD and NVIDIA are fabless. They are not comparable. It takes far more people to R&D a cutting-edge process node and run a dozen fabs 24/7 365.25 than it takes to design cutting edge chips.
The problem is that an exponential slowdown at each level requires discounting the probability of being in a simulation by an exponential amount per level. So instead of being able to say that the weighted odds of being in a simulation are higher than the odds of not being in a simulation, you have to say that, at best, there's a small chance of being in a simulation.
Oh, the irony.