Wikipedia link race: choosing among thousands of options
The model chooses the next step from hundreds or thousands of links, demonstrating fast decisions with constrained outputs. The post includes a 4:04 video.
Jev AI Accesses Apple Photos for Second-Level Video Search
Developer shows how to give Jev AI access to all photos and videos, combining a Claude tagging system and Obsidian knowledge graph to retrieve any clip in seconds.
I gave Jev AI access to every photo and video I've ever taken. Now I can ask it to find any clip and it pulls it in seconds. Here's how: full developer access to Apple Photos, a tagging system in Claude, and an Obsidian Knowledge Graph. Link to the resource is in the reply 👇
· 0 likesOpen on X
More like this
Semantic Querying Use Case with Jev and TypeSafe AI
Nathan LeClaire shares a semantic querying use case for Jev and TypeSafe AI, noting people have only scratched the surface.
Building a live BS meter for the Trump vs Kamala debate with Jev
The author used Jev to run a live BS meter on every sentence of the Trump vs Kamala debate, with 5 yes/no questions per candidate, totaling 1,191 Jev calls, 1.18M tokens, 415 ms median latency, and $0.0497 total cost.
