u/Neat_Education8515

So... I'm thinking about pitching an ASIC accelerator that can support vision-language models for edge devices. I'm curious if there are any compelling use cases for running a VLM on the edge (as opposed to offloading the VLM workloads to the cloud).

So... immediate benefits I see to doing edge-VLM is

1. Privacy (no data sent offline)

2. Latency (no need to send images/input data to a remote machine, where it can then run inference)

Reason 1 is valid but does not have the "wow factor" reasons for supporting VLMs on edge devices (since this is a reason that is workload agnostic). Reason 2 is fair, but where would a latency-sensitive application of VLMs be needed?

Curious to hear folks' opinions on supporting VLMs for edge devices!

Curious on how I can better learn the delay characteristics of a signal propagating across a wire. I know there are two factors that contribute to the delay: speed of light flight time and the RC delay. I'm not sure if these delays are purely additive (since the RC delay is basically derived from the elmore's delay of the wire, which is a approximate transmission line model without inductance).

I know certain factors like frequency of the signal, unit RLC, and wire length will all impact the delay, but uncertain how I should go about approximating the delay (at what point is the RC dominated vs at what point is it speed of light dominated)