{ "meta": { "title": "AICON: the ideas behind the conference", "edition": "AICON Belfast 2026", "compiled": "2026-09-12", "publisher": "Acuity AI", "schemaVersion": 1, "canonicalDestination": "https://acuityai.co/AICON", "relationshipPolicy": "Concept grouping and cross-concept relationships are editorial synthesis. Programme topic links are distinguished from curated thematic links. Reading links do not imply speaker endorsement.", "sourcePolicy": "Captured public sources plus separately verified background-learning links; resource types and limitations are explicit. Multiple versions of one paper are not independent studies.", "videoCoverage": "Seven substantive YouTube learning links verified from public publisher metadata. Videos were not watched or transcribed. The promotional video is excluded from learning resources.", "indexScope": "The new background-learning links have not been added to the private full-text/vector index; they are a curated public resource layer." }, "concepts": [ { "id": "concept-knowledge-readiness", "title": "Knowledge readiness & authority", "definition": "The work of making organisational knowledge discoverable, understandable, current and attributable to someone who can stand behind it.", "whyItMatters": "An AI can retrieve a document without knowing whether it is the approved version. Useful organisational AI needs decisions about ownership, access, conflicting sources and updates as well as a capable model.", "keyDistinctions": [ "Information availability is different from authority: a readable file may be obsolete or unapproved.", "A citation shows where a statement came from; it does not by itself establish that the statement is true.", "A larger corpus improves coverage only when relevant material can be found and interpreted." ], "practicalQuestion": "For one important business question, which source wins when two documents disagree, and who decides?", "topicNodeIds": [ "topic-organisational-knowledge", "topic-provenance-and-authority", "topic-knowledge-management", "topic-data-lineage" ], "conferenceConnections": [ { "nodeId": "session-keynote-ai-is-ready-is-your-knowledge-why-the-models-we-fixate-on-are-rarely-the-real-constraint-in-creating-value-from-ai", "label": "AI Is Ready. Is Your Knowledge? Why the models we fixate on are rarely the real constraint in creating value from AI", "contributors": [ { "nodeId": "person-ger-perdisatt", "label": "Ger Perdisatt" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "programme topic link", "explanation": "The announced programme explicitly discusses a mapped topic." }, { "nodeId": "session-panel-discussion-the-importance-of-data-and-governance-as-the-foundations-for-ai-success", "label": "The Importance of Data and Governance as the Foundations for AI Success", "contributors": [ { "nodeId": "person-fiona-browne", "label": "Fiona Browne" }, { "nodeId": "person-holly-toner", "label": "Holly Toner" }, { "nodeId": "person-lyndsay-shields", "label": "Lyndsay Shields" }, { "nodeId": "person-aislinn-mcbride", "label": "Aislinn McBride" }, { "nodeId": "person-linda-robb", "label": "Linda Robb" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "programme topic link", "explanation": "The announced programme explicitly discusses a mapped topic." } ], "resources": [ { "sourceId": "src-1b6033413cf84b33", "title": "Liberty IT: our journey to responsible generative AI", "url": "https://www.liberty-it.co.uk/news-stories/liberty-it-journey-to-responsible-generative-ai", "kind": "vendor case study", "whyRead": "See how reusable capabilities, use cases and governance were developed together.", "limitation": "Provider-reported experience; outcomes have not been independently verified here.", "coverage": "Full response captured; dynamic content and social pagination require separate review" }, { "sourceId": "src-09dee6a3c9981da8", "title": "Tom Swann: observable data quality with Elementary and DataHub", "url": "https://tam-iii.medium.com/observable-data-quality-with-elementary-and-datahub-6fa5f92f2c81", "kind": "practitioner article", "whyRead": "Connect quality checks with discoverable data context and ownership.", "limitation": "Practitioner explanation or experience, not an independent controlled study.", "coverage": "Full response captured; dynamic content and social pagination require separate review" }, { "sourceId": "src-fdf62bdd1b174956", "title": "Instil: a practical guide to RAG strategies", "url": "https://instil.co/blog/a-practical-guide-to-retrieval-augmented-generation-strategies", "kind": "practitioner article", "whyRead": "Understand how source material enters an answer through retrieval.", "limitation": "Practitioner explanation or experience, not an independent controlled study.", "coverage": "Full response captured; dynamic content and social pagination require separate review" }, { "sourceId": "watch-LRGX-gTegVA", "title": "Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Enterprise Internal Knowledge", "url": "https://www.youtube.com/watch?v=LRGX-gTegVA", "kind": "video", "whyRead": "Connect the conference knowledge demonstration to the challenge of making internal business knowledge useful to AI.", "limitation": "Publisher title and description only; video not watched and transcript not reviewed. Background learning; no AICON appearance or endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "publisher": "Stanford Online", "published_date": "2026-05-22", "duration_seconds": 2890, "verification": { "method": "yt-dlp direct public YouTube metadata", "checked_at": "2026-09-12", "content_basis": "Publisher title and description only; video not watched and transcript not reviewed.", "access_limits": "Public metadata accessible without sign-in. Playback may require YouTube consent and is subject to regional restrictions; full playback not tested." } }, { "sourceId": "read-context-engineering", "title": "Effective context engineering for AI agents", "url": "https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents", "kind": "practitioner article", "whyRead": "Turn the knowledge-constraint argument into practical design choices.", "limitation": "Public article reviewed. Background learning; no AICON appearance or endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "publisher": "Anthropic", "published_date": "2025-09-29", "duration_seconds": null, "verification": { "method": "Official publisher page or author-submitted arXiv page opened using web tool", "checked_at": "2026-09-12", "content_basis": "Public article reviewed.", "access_limits": "Public page accessible without sign-in." } } ], "related": [ { "conceptId": "concept-retrieval", "relationship": "supplies trusted context to", "rationale": "Retrieval needs usable source knowledge, including its scope and authority.", "basis": "editorial synthesis" }, { "conceptId": "concept-governance", "relationship": "requires ownership from", "rationale": "Someone must own source approval, refresh and access decisions.", "basis": "editorial synthesis" } ], "coverageGap": "" }, { "id": "concept-retrieval", "title": "Retrieval-augmented generation", "definition": "Finding relevant material and supplying it to a language model as context for an answer, instead of expecting the model to remember everything.", "whyItMatters": "RAG is a practical bridge between a model and organisational documents. Its quality depends on what is indexed, how documents are divided, how candidates are ranked and whether the final answer uses the evidence correctly.", "keyDistinctions": [ "Retrieval changes the context supplied at use time; fine-tuning changes model parameters.", "Similarity is a useful search signal, not a guarantee of relevance or truth.", "Reranking can improve candidate selection but adds work and latency." ], "practicalQuestion": "Can the system retrieve the passage that would let a knowledgeable colleague answer this question?", "topicNodeIds": [ "topic-retrieval-augmented-generation", "topic-document-chunking", "topic-retrieval-reranking", "topic-multimodal-retrieval" ], "conferenceConnections": [ { "nodeId": "session-zero-ontology-extracting-structured-knowledge-from-sec-filings-with-kv-accelerated-llms", "label": "Zero ontology", "contributors": [ { "nodeId": "person-ryan-ballantine", "label": "Ryan Ballantine" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "programme topic link", "explanation": "The announced programme explicitly discusses a mapped topic." }, { "nodeId": "session-keynote-ai-is-ready-is-your-knowledge-why-the-models-we-fixate-on-are-rarely-the-real-constraint-in-creating-value-from-ai", "label": "AI Is Ready. Is Your Knowledge? Why the models we fixate on are rarely the real constraint in creating value from AI", "contributors": [ { "nodeId": "person-ger-perdisatt", "label": "Ger Perdisatt" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "editorial thematic connection", "explanation": "Curated connection based on the announced session scope; it does not claim that the speaker endorses these readings." } ], "resources": [ { "sourceId": "src-fdf62bdd1b174956", "title": "Instil: practical RAG strategies", "url": "https://instil.co/blog/a-practical-guide-to-retrieval-augmented-generation-strategies", "kind": "practitioner article", "whyRead": "Compare basic retrieval, reranking and more elaborate retrieval patterns.", "limitation": "Practitioner explanation or experience, not an independent controlled study.", "coverage": "Full response captured; dynamic content and social pagination require separate review" }, { "sourceId": "src-2ef605fefeb1840f", "title": "Instil: why chunking matters", "url": "https://instil.co/blog/why-chunking-matters-the-key-to-smarter-rag-workflows", "kind": "practitioner article", "whyRead": "Compare fixed, recursive, semantic and late chunking approaches.", "limitation": "Practitioner explanation or experience, not an independent controlled study.", "coverage": "Full response captured; dynamic content and social pagination require separate review" }, { "sourceId": "src-b296a8c593a79ecd", "title": "GraphRAG local search", "url": "https://microsoft.github.io/graphrag/query/local_search/", "kind": "technical documentation", "whyRead": "See how entities, relationships and source text can be combined for a specific question.", "limitation": "Describes this implementation, not a comparative evaluation.", "coverage": "Full selected article/main text; no character truncation" }, { "sourceId": "watch-mE7IDf2SmJg", "title": "Stanford CS25: V3 I Retrieval Augmented Language Models", "url": "https://www.youtube.com/watch?v=mE7IDf2SmJg", "kind": "video", "whyRead": "Understand why retrieving relevant organisational knowledge is different from relying on model training.", "limitation": "Publisher title and description only; video not watched and transcript not reviewed. Background learning; no AICON appearance or endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "publisher": "Stanford Online", "published_date": "2024-01-25", "duration_seconds": 4766, "verification": { "method": "yt-dlp direct public YouTube metadata", "checked_at": "2026-09-12", "content_basis": "Publisher title and description only; video not watched and transcript not reviewed.", "access_limits": "Public metadata accessible without sign-in. Playback may require YouTube consent and is subject to regional restrictions; full playback not tested." } }, { "sourceId": "read-rag-foundation", "title": "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", "url": "https://arxiv.org/abs/2005.11401", "kind": "research paper", "whyRead": "Understand the original architecture behind answers grounded in retrieved material.", "limitation": "Abstract reviewed; linked full paper not newly reviewed in this supplement. Background learning; no AICON appearance or endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "publisher": "Patrick Lewis and co-authors / arXiv", "published_date": "2020-05-22", "duration_seconds": null, "verification": { "method": "Official publisher page or author-submitted arXiv page opened using web tool", "checked_at": "2026-09-12", "content_basis": "Abstract reviewed; linked full paper not newly reviewed in this supplement.", "access_limits": "Public page accessible without sign-in." } } ], "related": [ { "conceptId": "concept-knowledge-graphs", "relationship": "can be extended by", "rationale": "Relationships can supply context that isolated passages omit.", "basis": "editorial synthesis" }, { "conceptId": "concept-evaluation", "relationship": "must be tested through", "rationale": "Assess retrieval coverage separately from answer correctness.", "basis": "editorial synthesis" } ], "coverageGap": "" }, { "id": "concept-knowledge-graphs", "title": "Knowledge graphs & connected retrieval", "definition": "A representation of entities and explicit relationships that lets people or software follow how pieces of knowledge connect.", "whyItMatters": "A graph can connect a topic to a session, a speaker to their work, or a claim to its evidence. Its value comes from the meaning and quality of those connections. A visually impressive network alone is not a useful knowledge model.", "keyDistinctions": [ "A graph visualisation displays relationships; a graph retrieval system uses them to select context.", "Local questions concern particular entities; global questions ask for themes across a collection.", "An editor-curated thematic connection is different from a relationship explicitly asserted in a source." ], "practicalQuestion": "What useful question becomes answerable by following a relationship that a keyword search would miss?", "topicNodeIds": [ "topic-knowledge-graphs", "topic-graph-enhanced-retrieval", "topic-community-reports", "topic-entity-resolution" ], "conferenceConnections": [ { "nodeId": "session-zero-ontology-extracting-structured-knowledge-from-sec-filings-with-kv-accelerated-llms", "label": "Zero ontology", "contributors": [ { "nodeId": "person-ryan-ballantine", "label": "Ryan Ballantine" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "programme topic link", "explanation": "The announced programme explicitly discusses a mapped topic." }, { "nodeId": "session-keynote-ai-is-ready-is-your-knowledge-why-the-models-we-fixate-on-are-rarely-the-real-constraint-in-creating-value-from-ai", "label": "AI Is Ready. Is Your Knowledge? Why the models we fixate on are rarely the real constraint in creating value from AI", "contributors": [ { "nodeId": "person-ger-perdisatt", "label": "Ger Perdisatt" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "editorial thematic connection", "explanation": "Curated connection based on the announced session scope; it does not claim that the speaker endorses these readings." } ], "resources": [ { "sourceId": "src-b101ca0e7d528364", "title": "From Local to Global: a GraphRAG approach to query-focused summarization", "url": "https://arxiv.org/pdf/2404.16130", "kind": "research paper", "whyRead": "Read the graph and community-summary approach to questions about whole collections.", "limitation": "The captured full paper is a preprint; its evaluated global-question results are not a blanket advantage over all RAG systems.", "coverage": "Every PDF page extracted; page markers and character counts retained" }, { "sourceId": "src-8660509a6a953318", "title": "GraphRAG global search", "url": "https://microsoft.github.io/graphrag/query/global_search/", "kind": "technical documentation", "whyRead": "Understand how community reports support collection-wide answers.", "limitation": "Describes this implementation, not a comparative evaluation.", "coverage": "Full selected article/main text; no character truncation" }, { "sourceId": "src-7a7fe6366a4c46fc", "title": "GraphRAG DRIFT search", "url": "https://microsoft.github.io/graphrag/query/drift_search/", "kind": "technical documentation", "whyRead": "Explore an approach that combines community context with more detailed retrieval.", "limitation": "Describes this implementation, not a comparative evaluation.", "coverage": "Full selected article/main text; no character truncation" }, { "sourceId": "src-ab411058bd5a9a25", "title": "Tom Swann: exploring AWS Neptune", "url": "https://tam-iii.medium.com/exploring-aws-neptune-9925c175a945", "kind": "practitioner article", "whyRead": "See a practitioner introduction to graph database ideas.", "limitation": "Practitioner explanation or experience, not an independent controlled study.", "coverage": "Full response captured; dynamic content and social pagination require separate review" }, { "sourceId": "watch-f6pUqDeMiG0", "title": "Intro to GraphRAG", "url": "https://www.youtube.com/watch?v=f6pUqDeMiG0", "kind": "video", "whyRead": "See how relationships can support retrieval; pair with the research paper to understand the evidence and limitations.", "limitation": "Publisher title and description only; video not watched and transcript not reviewed. Background learning; no AICON appearance or endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "publisher": "Microsoft Reactor", "published_date": "2024-09-07", "duration_seconds": 3665, "verification": { "method": "yt-dlp direct public YouTube metadata", "checked_at": "2026-09-12", "content_basis": "Publisher title and description only; video not watched and transcript not reviewed.", "access_limits": "Public metadata accessible without sign-in. Playback may require YouTube consent and is subject to regional restrictions; full playback not tested." } } ], "related": [ { "conceptId": "concept-entity-resolution", "relationship": "depends on consistent identities from", "rationale": "Incorrectly merged or duplicated entities distort the graph.", "basis": "editorial synthesis" }, { "conceptId": "concept-knowledge-readiness", "relationship": "makes relationships visible within", "rationale": "Connections can expose ownership, provenance and missing context.", "basis": "editorial synthesis" } ], "coverageGap": "" }, { "id": "concept-entity-resolution", "title": "Entity resolution & data quality", "definition": "Deciding when two records refer to the same real-world thing, while preserving differences that matter.", "whyItMatters": "A person, organisation or product can appear under several names. Joining those records can reveal connections; joining the wrong records manufactures connections. This is a central quality problem for any useful graph.", "keyDistinctions": [ "Matching names is not the same as identifying the same entity.", "A false merge invents a relationship; a missed merge hides one.", "A model-generated match should carry evidence and uncertainty rather than becoming an unquestioned fact." ], "practicalQuestion": "Which ambiguous names or duplicate records would most distort our decisions if we matched them incorrectly?", "topicNodeIds": [ "topic-entity-resolution", "topic-data-integration", "topic-matching-explanations", "topic-prompt-sensitivity" ], "conferenceConnections": [ { "nodeId": "session-zero-ontology-extracting-structured-knowledge-from-sec-filings-with-kv-accelerated-llms", "label": "Zero ontology", "contributors": [ { "nodeId": "person-ryan-ballantine", "label": "Ryan Ballantine" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "programme topic link", "explanation": "The announced programme explicitly discusses a mapped topic." } ], "resources": [ { "sourceId": "src-c42b117ddcf42f64", "title": "Deep Entity Matching with Pre-Trained Language Models", "url": "https://arxiv.org/pdf/2004.00584", "kind": "research paper", "whyRead": "Study Ditto and the use of language models for matching record pairs.", "limitation": "Research findings apply to the studied setting; this is not a universal performance guarantee.", "coverage": "Every PDF page extracted; page markers and character counts retained" }, { "sourceId": "src-ee80a069b1b693da", "title": "Entity Matching using Large Language Models", "url": "https://arxiv.org/pdf/2310.11244", "kind": "research paper", "whyRead": "Explore LLM matching and the effects of prompts and explanations.", "limitation": "Research findings apply to the studied setting; this is not a universal performance guarantee.", "coverage": "Every PDF page extracted; page markers and character counts retained" }, { "sourceId": "src-09dee6a3c9981da8", "title": "Observable data quality with Elementary and DataHub", "url": "https://tam-iii.medium.com/observable-data-quality-with-elementary-and-datahub-6fa5f92f2c81", "kind": "practitioner article", "whyRead": "Place individual matching decisions in the wider discipline of monitored data quality.", "limitation": "Practitioner explanation or experience, not an independent controlled study.", "coverage": "Full response captured; dynamic content and social pagination require separate review" } ], "related": [ { "conceptId": "concept-knowledge-graphs", "relationship": "establishes identities for", "rationale": "Edges need stable endpoints to mean what they appear to mean.", "basis": "editorial synthesis" }, { "conceptId": "concept-evaluation", "relationship": "needs error analysis from", "rationale": "Test false merges and missed matches separately.", "basis": "editorial synthesis" } ], "coverageGap": "" }, { "id": "concept-agents", "title": "Agents & delegated work", "definition": "AI systems that pursue a goal through a sequence of decisions and tool actions, sometimes coordinating with other agents.", "whyItMatters": "Delegation can connect reasoning to real work, but every added action creates another place where an error can propagate. Designing the workflow includes defining tools, authority, stopping conditions and handover points.", "keyDistinctions": [ "A chatbot response and an action in a business system have different consequences.", "Multiple agents add coordination choices; they do not automatically improve results.", "A technically available tool is not the same as permission to use it for every purpose." ], "practicalQuestion": "What can this agent do independently, what must it escalate, and what evidence shows it completed the job?", "topicNodeIds": [ "topic-agentic-ai", "topic-agent-network-architecture", "topic-agent-hierarchical-architecture", "topic-human-oversight" ], "conferenceConnections": [ { "nodeId": "session-keynote-the-agent-at-work-trust-and-capability-in-the-age-of-delegation", "label": "The Agent at Work: Trust and Capability in the Age of Delegation", "contributors": [ { "nodeId": "person-nell-watson", "label": "Nell Watson" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "programme topic link", "explanation": "The announced programme explicitly discusses a mapped topic." }, { "nodeId": "session-from-ai-assistants-to-agentic-delivery-rewiring-product-development-at-scale", "label": "From AI Assistants to Agentic Delivery", "contributors": [ { "nodeId": "person-brian-craig", "label": "Brian Craig" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "programme topic link", "explanation": "The announced programme explicitly discusses a mapped topic." }, { "nodeId": "session-panel-discussion-autonomy-at-the-frontier-security-resilience-trust-and-governance-for-agentic-ai", "label": "Autonomy at the Frontier", "contributors": [ { "nodeId": "person-matt-holland", "label": "Matt Holland" }, { "nodeId": "person-rory-campbell", "label": "Rory Campbell" }, { "nodeId": "person-jun-liu", "label": "Jun Liu" }, { "nodeId": "person-kristel-miller", "label": "Kristel Miller" }, { "nodeId": "person-kostas-siabanis", "label": "Kostas Siabanis" } ], "sourceIds": [ "src-fedb034bfdedb908" ], "basis": "programme topic link", "explanation": "The announced programme explicitly discusses a mapped topic." } ], "resources": [ { "sourceId": "src-91d83856d459f5af", "title": "Instil: making sense of multi-agent architectures", "url": "https://instil.co/blog/making-sense-of-multi-agent-architectures", "kind": "practitioner article", "whyRead": "Compare network, supervisor and hierarchical coordination trade-offs.", "limitation": "Practitioner explanation or experience, not an independent controlled study.", "coverage": "Full response captured; dynamic content and social pagination require separate review" }, { "sourceId": "src-7d468a0924be940c", "title": "Kainos: the promise of AI agents", "url": "https://www.kainos.com/insights/blogs/the-transformative-potential-of-AI-agents", "kind": "practitioner article", "whyRead": "Explore proposed applications and delivery considerations from a provider perspective.", "limitation": "Practitioner explanation or experience, not an independent controlled study.", "coverage": "Full Jina response preserved; boilerplate retained; dynamic completeness not independently proven" }, { "sourceId": "src-6f41c17c0f961626", "title": "Enzai: agentic AI governance", "url": "https://www.enz.ai/product/agentic-ai-governance", "kind": "vendor case study", "whyRead": "Examine a concrete product framing of autonomy, allowed actions and escalation.", "limitation": "Provider-reported experience; outcomes have not been independently verified here.", "coverage": "Full response captured; dynamic content and social pagination require separate review" }, { "sourceId": "watch-LP5OCa20Zpg", "title": "Tips for building AI agents", "url": "https://www.youtube.com/watch?v=LP5OCa20Zpg", "kind": "video", "whyRead": "Decide where autonomous tool use earns its additional complexity, cost and oversight.", "limitation": "Publisher title and description only; video not watched and transcript not reviewed. Background learning; no AICON appearance or endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "publisher": "Anthropic", "published_date": "2025-02-13", "duration_seconds": 1099, "verification": { "method": "yt-dlp direct public YouTube metadata", "checked_at": "2026-09-12", "content_basis": "Publisher title and description only; video not watched and transcript not reviewed.", "access_limits": "Public metadata accessible without sign-in. Playback may require YouTube consent and is subject to regional restrictions; full playback not tested." } }, { "sourceId": "watch-6_BcCthVvb8", "title": "Context Engineering for AI Agents with LangChain and Manus", "url": "https://www.youtube.com/watch?v=6_BcCthVvb8", "kind": "video", "whyRead": "Learn practical ways to manage limited context instead of putting every document into every request.", "limitation": "Publisher title and description only; video not watched and transcript not reviewed. Background learning; no AICON appearance or endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "publisher": "LangChain", "published_date": "2025-10-14", "duration_seconds": 3653, "verification": { "method": "yt-dlp direct public YouTube metadata", "checked_at": "2026-09-12", "content_basis": "Publisher title and description only; video not watched and transcript not reviewed.", "access_limits": "Public metadata accessible without sign-in. Playback may require YouTube consent and is subject to regional restrictions; full playback not tested." } }, { "sourceId": "read-effective-agents", "title": "Building effective agents", "url": "https://www.anthropic.com/engineering/building-effective-agents", "kind": "practitioner article", "whyRead": "Choose the simplest architecture that improves measured outcomes.", "limitation": "Public article reviewed. 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Background learning; no AICON endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "verification": { "method": "Public author-submitted arXiv page and official project explanation reviewed by watch_read agent", "checked_at": "2026-09-12", "content_basis": "Abstract and official project explanation; full paper not newly reviewed." } }, { "sourceId": "read-open-x-embodiment", "title": "Open X-Embodiment: Robotic Learning Datasets and RT-X Models", "url": "https://robotics-transformer-x.github.io/", "kind": "research project", "publisher": "Open X-Embodiment Collaboration", "published_date": null, "whyRead": "Explore how standardised robot datasets and shared policies support transfer across different robot platforms.", "limitation": "Official project methods/results text reviewed; experimental transfer is not proof of dependable operation in every environment. Embedded demonstrations not watched. Background learning; no AICON endorsement implied.", "coverage": "Verified supplemental learning link; not added to canonical claim registry or vector index", "verification": { "method": "Official project page reviewed by watch_read agent", "checked_at": "2026-09-12", "content_basis": "Project methods/results text; embedded demonstrations not watched." } } ], "related": [ { "conceptId": "concept-evaluation", "relationship": "needs environment-specific testing from", "rationale": "Software tests alone cannot establish performance in a physical setting.", "basis": "editorial synthesis" }, { "conceptId": "concept-governance", "relationship": "needs responsibilities from", "rationale": "Operational ownership and intervention arrangements matter where actions have physical effects.", "basis": "editorial synthesis" } ], "coverageGap": "These robotics resources supply research background, not evidence about the panel participants’ own deployments. 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