D1 · BRAND CLARITY
WEIGHT ×1.0 · 10%
Consistent, unambiguous naming and positioning across owned surfaces. AI engines cite entities that resolve to a single canonical identity.
Yoshua Bengio OC OQ OBE FRS FRSC is the most AI-visible living scientist in the world, and the highest-scoring entity in the IdeaLab database across all categories. A Canadian computer scientist born in Paris in 1964, he is the recipient of the 2018 ACM A.M. Turing Award — the "Nobel Prize of Computing" — shared with Geoffrey Hinton and Yann LeCun for their foundational work on deep learning. He is the most-cited computer scientist globally and, since October 27, 2025, the most-cited living scientist across all fields — the first ever to surpass 1 million Google Scholar citations. He founded Mila (1993, now 1,300+ researchers), chairs the International AI Safety Report, sits on the UN Scientific Advisory Board, and in June 2025 launched LawZero — a $30M AI safety nonprofit whose board includes Yuval Noah Harari, Jacinda Ardern (former NZ Prime Minister), Stefan Löfven (former Swedish PM), and whose funders include the Gates Foundation and Schmidt Sciences. His Wikipedia article is confirmed, comprehensive, and maintained by the global academic community.
award property (Turing Award, with specific ACM URL), sameAs (Wikipedia, Wikidata, DBLP, Google Scholar profile, Mila profile, LawZero profile), and honorificSuffix: "OC OQ OBE FRS FRSC". This is a polish action, not a gap.honorificSuffix: "OC OQ OBE FRS FRSC", award array (Turing Award with ACM URL, Order of Canada with Globe and Mail citation URL, OBE, FRS, FRSC, Légion d'Honneur, Killam, Prix du Québec), affiliation (Université de Montréal, Mila, LawZero, CIFAR, IVADO), knowsAbout (deep learning, neural networks, AI safety, generative models, attention mechanisms, AI governance). The impact is marginal given the extraordinary existing schema coverage across academic platforms — but it makes yoshuabengio.org a first-party structured confirmation of the entity that all other platforms already confirm.* IdeaLab AI Visibility OS v1.1. The gap between Yoshua Bengio (97) and the next-highest personality (Hormozi, 87) is 10 points. This is the largest score gap between any #1 and #2 in the database. The gap exists because Bengio holds two 100/100 dimension scores (D3 Entity Recognition and D6 Social Proof) that no other entity in the database achieves. His D3 of 100/100 — Wikipedia + Wikidata + Knowledge Panel + ACM Awards database + Google Scholar + DBLP + Semantic Scholar — is the reference target that every other audited entity's action plan is designed to approach. The database instruction "create a Wikidata entry" is an instruction to move one step toward what Yoshua Bengio already has fully built over 30+ years of documented academic and institutional work.
Every recommendation in this database — Wikidata, Wikipedia, Person JSON-LD, LLMs.txt — is an instruction to build infrastructure that Yoshua Bengio has had, through three decades of academic and institutional work, since before most of these platforms existed. The audit shows you how to close the gap.
Every IdeaLab audit uses the AI Visibility OS v1.1 — a seven-dimension framework that measures how discoverable, citable, and trustworthy an entity is to answer engines like ChatGPT, Perplexity, Google AI Overviews, Claude, and Gemini. Each dimension is scored 0–100, multiplied by its weight, and summed into a composite 0–100 score. The composite maps to a letter grade that describes AI-answer behavior for the entity's core queries.
Consistent, unambiguous naming and positioning across owned surfaces. AI engines cite entities that resolve to a single canonical identity.
Long-form, first-hand, evidence-rich content on owned domains. Depth is the largest single driver of LLM citation frequency.
Presence in knowledge graphs — Wikipedia article, Wikidata QID, Google Knowledge Panel, sameAs coverage. Anchors the entity for AI retrieval.
Schema.org JSON-LD coverage: Organization, Person, Article, Product, aggregateRating, FAQPage, BreadcrumbList. Machine-readable = AI-citable.
Verified accounts and consistent identity across YouTube, LinkedIn, X, Instagram, TikTok, GitHub, Substack, podcasts. Cross-surface coherence lifts AI confidence.
Independent third-party citations: press, podcasts, academic references, high-authority backlinks, reviews. The corroboration layer AI engines weigh above self-claims.
AI-crawler posture: robots.txt policy for GPTBot / ClaudeBot / PerplexityBot / Google-Extended, llms.txt policy file, canonical URLs, sitemap freshness, dateModified hygiene.
Score = (D1×0.10) + (D2×0.20) + (D3×0.15) + (D4×0.20)
+ (D5×0.15) + (D6×0.20) + (D7×0.10)
The two heaviest weights — D2 Content Depth and D4/D6 Structured Knowledge and Citations — reflect the empirical drivers of AI answer inclusion. D3 Entity Recognition acts as a ceiling: without Wikipedia and Wikidata anchoring, most audits cap at Grade B regardless of the other six dimensions.
The per-dimension scores and weighted contributions for this specific audit are shown in the scoring table above. The Top Gap and Top Action highlighted on this page correspond to the lowest-scoring high-weight dimensions — the fixes with the largest projected uplift to the composite score.
Closest matches by category, keyword overlap, and AI Visibility Score — all scored on the same 7-dimension framework.