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aientity · one source so far

sglang

for ml engineers, devs

Steadygithub
Signal score
0
as of 1d ago
Live items
1
Trajectory
Cooling
7-day est. ~0

Why this scored 0

every term, weighted
Velocity+0.0 / 40

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

Acceleration+12.3 / 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+0.0 / 10

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

Saturation penalty16.8 / 30

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

Composite-4.5 → clamped to 0

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 012

14-day

~0

range 014

30-day

~0

range 019

Signal history

7-day window (free)
029

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
    25

    The Complete Guide to Local LLM Inference Tools in July 2026: llama.cpp, Ollama, vLLM, SGLang, and Beyond

    Local LLM tools compared · for ai devs, researchers

    devtoEmergingai53d ago
  2. 2
    10

    time-to-first-token — A 10-week, 30-minutes-a-day roadmap for LLM inference serving and optimization. vLLM, SGLang, quantization, speculativ

    LLM optimization roadmap · for llm devs

    githubSteady 2 · vllmai16 saturated36d ago
  3. 3
    8

    zero-to-sglang — Official SGLang × Datawhale course on LLM inference (中英双语): understand inference, build a mini-sglang from scratch, then re

    Course shows how to build a mini SGLang inference engine with CUDA support. · for ml engineers, devs

    githubSteady 2 · cudaai17 saturated3d ago
  4. 4
    0

    axrl — AxisRL is an agentic RL post-training framework built on SGLang rollout, Megatron training, and real-world agent workflows.

    New RL framework · for ai devs

    githubSteadyai18 saturated45d ago