GPT-5.6 used a prompt to close a 30-year gap in convex optimization
GPT-5.6 advances convex optimization
SteadyWhy this scored 16
every term, weightedEngagement per hour, normalized against the fastest item on its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities are talking about the same entity
Decays to zero over 14 days
Subtracted once something is big and old — we rank what's next, not what's peaked
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On a topic's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement. Full methodology
Outlook
low confidence · estimate, not a guarantee7-day
~23
range 23–23
14-day
~25
range 25–26
30-day
~26
range 26–27
Signal history
7-day window (free)— — projected trajectory (estimate, not a guarantee)
Entities
Embed a live signal badge
[](https://www.signalcrest.app/topic/hn%3A48957779)
Drop this in a README or blog post — it updates automatically as the score moves.