📡 Technical Methodology (Under the Hood)
The AI-RADAR Signal Visualization is not an opinion piece. It is a deterministic projection of our database state, generated automatically by our ingestion and analysis pipeline.
1. Data ingestion & Categorization
Our system monitors 50+ high-signal RSS feeds (Arxiv, OpenAI Research, Hugging Face, Engineering Blogs). Every incoming article is:
- Vectorized: Converted into embeddings using `text-embedding-3-small`.
- Clustered: Grouped into "Trends" (Topics) using semantic similarity (Cosine Distance > 0.85).
- Tagged: Entities like "Llama-3", "H100", "QLoRA" are extracted via NER (Named Entity Recognition).
2. Signal Computation
For every identified active Trend, we compute two normalized scores every 24 hours:
Velocity (Y-Axis) = f(Volume, Time)
Calculated as the density of articles in the last 7-day trailing window.
High Velocity = Multiple independent sources reporting on this topic right now.
Low Velocity = Occasional mentions or "cold" news.
Maturity (X-Axis) = f(First_Seen, Persistence)
Calculated based on the days elapsed since the first detected signal, weighted by consistency derived from historical snapshots.
High Maturity = Topic has been active/relevant for > 6 months.
Low Maturity = Topic appeared < 14 days ago.
3. Quadrant Mapping
The intersection of these two scores places the Signal into one of four strategic quadrants:
-
🟣 Emerging / Breakout (High Velocity, Low Maturity)
"The New Hotness". Examples: New model releases (DeepSeek-V3), Viral papers (Mamba).
Action: Watch closely. High volatility. -
🟢 Mainstream / Adopt (High Velocity, High Maturity)
"The Industry Standard". Examples: OpenAI GPT-4, Llama 2/3 ecosystem.
Action: Safe to build on. Active ecosystem. -
🔵 Utility / Commodity (Low Velocity, High Maturity)
"The Backbone". Examples: NVIDIA H100, PyTorch, Transformers architecture.
Action: Foundational knowledge. Essential but news is slower. -
⚫ Niche / Experiment (Low Velocity, Low Maturity)
"The Fringe". Research proofs-of-concept or dying fads.
Action: Filter out unless highly relevant to niche needs.
This radar is an visualization of news attention, not technical quality. The algorithms are unsupervised and may occasionally misclassify "hype" as "velocity".