tencent
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
low 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.
- 122
tencent/WeMM-Embedding-9B (feature-extraction)
Tencent releases a 9B embedding model for image-text to text tasks. · for ml engineers
huggingfaceSteady 2 · tencentdata−7 saturated10d ago - 214
tencent/Hy4-preview (text-generation)
Tencent unveiled Hy4-preview, a new text-generation model for developers building LLM applications. · for ml engineers, ai product teams
huggingfaceSteady 2 · tencentai−13 saturated14d ago - 30
WeMM-Embedding — WeMM-Embedding is a family of universal multimodal embedding models by the WeChat Vision Team at Tencent, supporting multim
Tencent's WeMM-Embedding offers universal multimodal vectors for cross-modal AI tasks. · for ml engineers, ai researchers
githubSteadyai−19 saturated14d ago