beam
for ml engineers, ai researchers
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
Outlook
medium confidence · estimate, not a guarantee7-day
~0
range 0–12
14-day
~0
range 0–14
30-day
~0
range 0–19
Signal history
7-day window (free)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.
- 118
Imp is a full port of DSPy to the BEAM
Imp ports DSPy to BEAM, enabling Erlang/Elixir teams to use LLM prompting libraries. · for ML engineers
hackernewsSteadyai28d ago - 217
Gleam and BEAM- Looking beyond the JVM
Introduces Gleam on BEAM as a JVM alternative for backend development. · for backend engineers
lobstersSteadydevtools51d ago - 316
Beam: Reflection's 501B open-weight model
Beam releases an open-weight model that developers can fine-tune freely. · for ml engineers, ai researchers
hackernewsSteadyai21d ago - 40
reflection/Beam-1.0-501B-A23B (text-generation)
Beam 1.0 model introduces a mixture-of-experts text generation architecture. · for ml engineers, ai researchers
huggingfaceSteadyai−16 saturated7d ago