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aientity · one source so far

lean4

for AI researchers

Steadyhackernews
Signal score
8
Live items
1
Trajectory
↓ Cooling
7-day est. ~0

Why this scored 8

every term, weighted
Velocity+1.2 / 40

Its fastest-moving item, measured against the pace of its own source

Acceleration+6.9 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities its own items come from

Recency+5.7 / 10

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty−6.2 / 30

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite7.5

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

Outlook

low confidence · estimate, not a guarantee

7-day

~0

range 0–12

14-day

~0

range 0–14

30-day

~0

range 0–19

Signal history

7-day window (free)
049

projected trajectory (estimate, not a guarantee)

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.

  1. 1
    30

    OpenAI’s Navier-Stokes release included a Lean 4 formal proof

    OpenAI released a Navier-Stokes formal proof in Lean 4, showcasing verification for ML research. · for AI researchers

    hackernewsSteady 2 · openaiai11h ago
  2. 2
    16

    Fermat's Last Theorem in Lean 4

    Lean 4 now hosts a formal proof of Fermat's Last Theorem, showcasing its math-library power. · for formal methods engineers

    hackernewsSteadydevtools6d ago