dreamrsi
for AI researchers, ML engineers
Why this scored 10
every term, weightedIts fastest-moving item, measured against the pace of its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities its own items come from
Decays to zero over 14 days, counted from when we first saw it
Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Signal history
7-day window (free)The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
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Recursive self-improvement: what Google's Dream-RSI paper really does
Paper details recursive self-improvement techniques impacting LLM safety research. · for AI researchers, ML engineers
devtoSteady 2 · googleai33d ago - 229
Dream-RSI: Recursive Self-Improvement through Evolving Worlds
Explores recursive self-improvement via evolving simulated worlds, relevant for AI safety research. · for AI safety researchers, ML engineers
hackernewsSteady 2 · dreamrsiai48d ago - 30
Dream-RSI — The offical repo for "Dream-RSI: Recursive Self-Improvement through Evolving Worlds"
Dream-RSI repo explores recursive self-improvement via evolving simulated worlds. · for AI researchers, ML engineers
githubSteadyai−17 saturated48d ago