Role in the system
Transformers provide the principal architectural reference for understanding attention, context and token prediction in modern large language models.
TECHNOLOGY
Transformer Architecture
The transformer is a neural-network architecture built around attention mechanisms and parallel sequence processing.
active
production
EDITORIAL FRAME
What this entry establishes.
A concise view of its scope, position, limitations and supporting sources.
Category, versions and official source
Tags and disciplines
TransformerAttentionNeural NetworksArtificial IntelligenceMachine Learning
References behind this page
- Attention Is All You Need Ashish Vaswani et al. / arXiv / 2017-06-12
Role
The transformer processes token relationships through attention and feed-forward layers, enabling parallel training and flexible sequence modeling.
Use
Electronic Artefacts uses the transformer as a technical reference for explaining LLMs and multimodal systems rather than as a synonym for intelligence.
References
See Attention Is All You Need and Large Language Model.
DOCUMENTED RELATIONSHIPS
Connected work and ideas.
Each link names the relationship between two entries and why it matters.
How Large Language Models Actually Work
How Large Language Models Actually Work uses the transformer architecture as its principal technical reference.
Knowledge Hub Third Wave
Transformer Architecture is an explicit member of the Knowledge Hub Third Wave collection.
How Large Language Models Actually Work
How Large Language Models Actually Work documents Transformer Architecture as one of its declared subjects.
Record details Metadata, sharing and citation
Transformer Architecture
Cite this page
Transformer Architecture. 1.0.0. Electronic Artefacts, 2026-06-24. https://electronicartefacts.com/knowledge/technologies/transformer-architecture/
Nearby relationships
3 public links connect this page to nearby projects, concepts and references.