Skip to content
Signalcrest
Get alerts
Back to entity feed
aientity · one source so far

tpu

for ml engineers

Steadydevto
Signal score
3
as of 22d ago
Live items
1
Trajectory
⏳ Too early
needs a few more snapshots

Why this scored 3

every term, weighted
Velocity+0.0 / 40

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

Acceleration+6.1 / 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 penalty−2.9 / 30

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

Composite3.2

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)
Not enough history yet — the trend line fills in as snapshots accrue (every 30 min).

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

    Self-hosting a lite agent backend on one TPU: Gemma 4 E2B + vLLM on a v5e-1

    Run lite agent backend on one TPU · for devtools founders

    devtoSteady 2 · vllmhardware32d ago
  2. 2
    28

    Deploying a QAT Checkpoint Your Serving Stack Can't Load: Gemma 4 E2B in Pure JAX on One TPU

    Runs quantized Gemma-4 E2B on JAX using a single TPU, enabling efficient LLM serving. · for ml engineers

    devtoSteady 2 · jaxai22d ago
  3. 3
    22

    Serving Gemma 4 E2B on a TPU v6e-1: what Trillium buys, and what it doesn't

    Trillium buys TPU · for ai founders

    devtoSteadyai31d ago
  4. 4
    18

    TPU Deployments with Gemma 31B, v6e-8, and Antigravity CLI

    TPU deployments with Gemma · for ai engineers

    devtoCooling 2 · gemmaai57d ago
  5. 5
    15

    Serving Gemma 4 2B on a Single TPU v5e Chip with MCP and Antigravity CLI

    Gemma 4 optimized on TPU · for ai engineers

    devtoSteadyai36d ago
  6. 6
    13

    Gemma 4 E2B on a Single TPU v6e Chip: A Serving Deep Dive

    Gemma 4 E2B on TPU v6e · for ai researchers

    devtoSteady 3 · gemmaai52d ago
  7. 7
    13

    Self-Hosted Gemma 4 on TPU v6e: Deployment & SRE with Antigravity

    Gemma deployment on TPU · for ai devs

    devtoSteady 2 · gemmaai47d ago
  8. 8
    12

    One TPU Chip, Eight Agents: Serving Small Agent Workloads with Raw JAX

    Efficient agent workloads · for ai engineers

    devtoSteady 2 · jaxai43d ago