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.
A Jev-powered AI news aggregator
The author describes building a Jev-powered aggregator that automatically filters papers and information every hour, while noting that it still requires people to read the results.
You're lazy, and keeping up with AI news feels like a full-time job. That's why I built a Jev-powered aggregator that automatically filters the best papers and information every hour. But then I remembered... that still requires people to read it. In today's fast-paced
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Semantic Querying Use Case with Jev and TypeSafe AI
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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.
