{"data":{"slug":"transformer","etype":"concept","name":"Transformer","cat":"Core Technical","subtitle":"The 2017 architecture everything on this site exists to run.","summary":"The transformer processes every token in a sequence in parallel, using attention to let each token consult every other. That parallelism is why GPUs and transformers co-evolved: the architecture is essentially a giant matrix-multiplication workload, which is exactly what accelerator silicon does best. GPT, Claude, Gemini, Llama, image diffusion backbones and even robot policies are transformers; challengers (state-space models, hybrids) so far nibble at its edges. One paper — 'Attention Is All You Need' — sits under roughly a trillion dollars of infrastructure.","attrs":null,"kf":null,"aliases":["transformers","attention"],"ticker":null,"exchange":null,"hq":null,"founded":null,"website":null,"status":null,"region":null,"asof":"2026-01-15","sources":[{"url":"https://arxiv.org/abs/1706.03762","label":"Attention Is All You Need"}]},"meta":{"found":true,"count":1,"served_from":"site cache (no live upstream calls)","as_of":"2026-10-14T09:49:57+00:00","disclaimer":"Research and information only — not investment advice. Structured records carry basis labels (vendor spec / reported / estimate); market quotes are delayed/indicative.","attribution":"Records compiled from vendor documentation, official filings and reputable public reporting; market quotes via financial data providers. See /data-sources."}}