TypeGPU + ruNNtime + Jev @typesafeai is a very fun combo :D
Combined TypeGPU, ruNNtime, and Jev so camera and mic input feed three local models, and Jev sets lights, shadows, and bloom in realtime.
The original post
TypeGPU + ruNNtime + Jev @typesafeai is a very fun combo :D
ruNNtime gives me efficient local inference, TypeGPU lets inference and rendering share GPU resources directly with zero copy. That’s 3 separate NN inferences plus rendering, all happening in realtime
Since we control the pipeline, Jev can just sit in the middle and add the semantic bit.
camera + mic → Moonshine + YOLO26 + DepthART → Jev → lights, shadows and bloom
Engagement when collected
Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.
Where this case fits
Filed under agents & workflows, video, animation & media. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the agents & workflows page.
Related Jev cases
found the perfect use case for @typesafeai Jev: instant
Agents
Breaking: Browser Use + Jev = Ultrafast Findings flights
AgentsBrowser agents
Here's a 45-second TL;DR on Jev.
Video & media
Jev case: in 40 seconds it broke down 724 live ads from 37
WebsitesAgents
Keep browsing: all 1173 Jev cases · more from @reczko_konrad · builders · what Jev is
Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post