airllm
for edge AI engineers, hardware designers
Why this scored 0
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.
- 110
AirLLM 70B inference with single 4GB GPU
faster inference · for ai engineers
hackernewsSteady 2 · airllmai92d ago - 210
AIR-LLM: Broadcasting AI Weights over Radio for Memory-Free Edge LLM Inference via RF Computing
Streams LLM weights over radio to run memory-free inference on edge devices. · for edge AI engineers, hardware designers
lobstersCoolinghardware21d ago - 38
AirLLM Runs a 70B Model on a 4GB GPU. It's True, and That's Not the Interesting Part
AirLLM runs on 4GB GPU · for ai devs
devtoSteadyai92d ago