Mixture of experts
AI Tools · first detected 8 Aug 2026 · scored 6 Oct 2026
Trend score
0/100
Opportunity
0/100
Confidence
66%
Trend, 30 days
Why this score
- −No source shows a clear spike yet
- −Flat week over week
How this score was calculated
| Component | Value | Weight | Points |
|---|---|---|---|
| Attention growth | 4% | 0.40 | +1.4 |
| Coverage growth | 0% | 0.00 | +0.0 |
| Cross-source breadth | 0% | 0.27 | +0.0 |
| Acceleration | 0% | 0.20 | +0.0 |
| Freshness | 0% | 0.13 | +0.0 |
| Saturation (subtracted) | 23% | 0.25 | −5.7 |
| Trend score (0–100) | 0.0 |
Opportunity = trend 0.0 × (1 − saturation 23%) × stage weight 0.4 × niche relevance 0.7 = 0.0
Saturation parts: volume 41%, time elevated 7%, mainstream 0%. Spike ratio = mean of the last 3 days ÷ median of days 4–31. A source counts as spiking at ≥ 1.5× and robust z ≥ 2.
| Source | Spike | Robust z | Week over week | Spiking |
|---|---|---|---|---|
| wikipedia | 1.08× | 0.4 | -2% | no |
Full method: methodology. Rising means rising now; it is not a prediction that a topic will go viral.
Signals by source
Wikipedia views
335/day
2026-09-07 → 2026-10-06 · fetched 7 Oct, 12:50 UTC
Attention data: Wikipedia pageviews via the Wikimedia Analytics API · Data as of 7 Oct, 12:50 UTC
Licences and terms
- Attention data: Wikipedia pageviews via the Wikimedia Analytics API: CC0 (pageview data)
Key headlines
- Reading, Not Manipulating: Leveraging Router Logits for Multimodal Safety in MoE Vision-Language ModelsarXiv · arxiv.org · 6 Oct 2026
- TRACE: Rollout-Guided Quantization-Aware Training for FP4 Reinforcement Learning of MoE Language ModelsarXiv · arxiv.org · 6 Oct 2026
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What to make about it
Content angles are written once a topic passes the publish threshold.
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