Transformer architecture

AI Adjacency 33/100 Confidence 50%

Updated 2026-09-11· researched 2026-09-11· next review 2026-10-11· listed 2026-09-11
⚠ research overdue — re-review queued

AI Impact Map

attention-is-all-you-need ENABLES 0 src · 98%

Claims & Evidence verified only

The Transformer architecture introduced in the paper processes all input simultaneously using attention mechanisms, rather than word by word like older RNN models.

✓ verified 95% confidence · 1 source(s)

Attention Is All You Need Explained - Parseur · Parseur · rel 55% · hash fd6d7463

Data Confidence

Overall 50% · 100% of 1 claims verified · 1 source(s) · mean reliability 55% · AI Adjacency 33/100 · Criticality 39/100 · evidence breakdown →

If Transformer architecture disappeared

Criticality 39/100 (calculated v1 — downstream reach, substitutes, concentration, geography, uniqueness). Impact analysis →

Sources (1)

Attention Is All You Need Explained - Parseur · Parseur · rel 55%

Timeline

View as of:

criticality_score changed 2026-09-13

null → 39

ai_adjacency_score changed 2026-09-13

31 → 33

ai_adjacency_score changed 2026-09-13

29 → 31

ai_adjacency_score changed 2026-09-13

27 → 29

ai_adjacency_score changed 2026-09-13

null → 27

Machine-readable

transformer-architecture.json · full · transformer-architecture/ld.json