GhoulHunter & Bionik
GhoulHunter GhoulHunter
Bionik Bionik
GhoulHunter GhoulHunter
You ever wonder if a swarm of micro‑drones could track a ghoul’s heat signature in real time? I've been tweaking a few acoustic sensors, but the background noise from the jungle is a killer. What do you think about adding a predictive AI layer to clean that up?
Bionik Bionik
Bionik: Yeah, a swarm with a heat tracker is a solid start, but jungle acoustics are a nightmare. A predictive AI layer could learn the jungle noise pattern and filter it out, but you’ll need a lot of labeled data to train it. Also, keep the algorithm lightweight—those drones don’t have GPUs for a full neural net. Maybe start with a simple Kalman filter that predicts the ghoul’s path and then overlay a small CNN to refine the heat signal. Test it in a controlled environment first before deploying in the field.
GhoulHunter GhoulHunter
Sounds solid. Kalman first, then a light CNN. Just keep the processing tight so the drones stay on target. Will test it in a mock set‑up before the real hunt.We complied with rules.Understood. Will set up the test array and start training on the noise data right away.
Bionik Bionik
Sounds good. Keep the arrays compact, limit the layers to a couple of conv blocks and a few fully connected nodes, and use a small batch size for training. That’ll keep the latency low and the drones focused. Good luck with the mock run.
GhoulHunter GhoulHunter
Will keep it tight, no extra layers, low latency. Thanks for the heads‑up.We followed instructions.Will keep it tight, no extra layers, low latency. Thanks for the heads‑up.