  The combinatorics of track seeding has long been a computational bottleneck
for triggering and offline computing in High Energy Physics (HEP), and remains
so for the HL-LHC. Next-generation pixel sensors will be sufficiently
fine-grained to determine angular information of the charged particle passing
through from pixel-cluster properties. This detector technology immediately
improves the situation for offline tracking, but any major improvements in
physics reach are unrealized since they are dominated by lowest-level hardware
trigger acceptance. We will demonstrate track angle and hit position
prediction, including errors, using a mixture density network within a single
layer of silicon as well as the progress towards and status of implementing the
neural network in hardware on both FPGAs and ASICs.
