@wordliftit has been selected by ICSC 4 Startup, with our work on #SEOcrate supported by Italy’s National Research Centre for HPC and Quantum Computing. Ontology-led RL for training trustworthy Small Language Models for Agentic AI is getting funded 🦾🥳 wor.ai/GCZrGV

mapped europe through the 9-layer AI stack: L1-L2 energy/foundries: dependent L3-L4 silicon/networking: no position L5 compute: 5% global L6 models: Mistral only L7-L8 harness/distribution: tenant L9 governance: strong (EU AI Act) one strong layer. governance. but governance without the layers beneath it is a fence around an empty field. (source: europe2031.ai/)

💪 The Latest SEO & AI Search News of the Week [From #SEOFOMO - June 14, 2026] 👇 - ​Google adds guidance on third-party SEO tools, services, advice and updates hiring an SEO doc. - ​Google can be directly liable for false AI Overview claims: German court. - ​Apple introduced Siri AI at WWDC this week: What Apple’s Gemini-Powered Siri Means For Search Visibility. - Google is adding Google Business Profile connection and Business Notebooks to Gemini. - ​Anthropic Forced To Shut Down Fable 5 By U.S. Government Order. - ​In 2026, Less than one-third of Google Searches Still Send a Click. - Google is building an Audience Loyalty ecosystem - ​The SERP is sinking: What pixel depth data reveals about visibility [Presentation]. - ​Why Your Product Feed Is An SEO Asset (And Who Should Own It). - ​How to Build a Representative AI Search Prompt Library for Better AI Visibility Measurement. - ​Exploring the Future of AI-Driven Agentic Search Architecture and RAG [Presentation] - ​Ontologies for the Agentic Web. - Much more! Including SEO & AI Search jobs, tools, events. From SEOs like @cyberandy , @shahzadabbas , @dawnieando, @gfiorelli1 , @DarrenShaw_, @DemiriE , @THCapper, @randfish, @rustybrick, @MrDannyGoodwin and more! Check it out: seofomo.co/posts/the-latest-…

Beautiful research.

🚨 @Karpathy predicted the power of the "LLM Wiki." Google just formalized it. Meet Open Knowledge Format (OKF): a vendor-neutral standard for giving foundation models the curated context they need. I can genuinely see this replacing Notion, Obsidian, or traditional wikis for developer teams, and the reason comes down to bookkeeping. Traditional wikis fail because humans inevitably abandon the tedious work of updating them. As Andrej Karpathy pointed out recently, LLMs don't get bored. They don't forget to update a cross-reference, and they can touch 15 files in a single pass. OKF standardizes the interoperability layer so agents can actually do that heavy lifting autonomously. Because the format is minimally opinionated, it doesn't dictate what you write, it just dictates how it's structured. You get: → Human-readable documents that live right alongside your code in version control → Cross-links that map out complex entity relationships without needing a graph database → A system that survives moving between different tools and organizations There is no complex compression scheme. No central registry. If you can cat a file, you can read it. If you can git clone a repo, you can deploy it. This is how we stop rebuilding context pipelines from scratch every time a new model drops. Announcement spec file in 🧵↓

I tend to agree with the thesis, but there is a hard constraint behind it. Europe may want AI sovereignty, but frontier AI is no longer just a software problem. It is an energy, chips, infrastructure, and capital problem. Knowledge infrastructure yes, Energy-aware compute yes.

Google’s Open Knowledge Format validates the idea that agents need portable, inspectable knowledge bundles. Markdown alone is not enough. The next layer is to connect OKF-style agent memory with formal ontologies, validation, and persistent entity IDs. A good start.

Chinese teams that already distilled Fable 5.

Turns out Fable 5 is shadowbanning AI researchers 🫤

I knew how this was going to end. My most important Fable 5 task was not writing posts, summaries, or code. It was crafting training datasets.

A perfect complement to RLM-on-KG! You’re using KGs to surface the hardest multi-hop chains for private evals. I’m using them at inference time so the model recursively navigates those exact long paths as a structured environment. Great work as always 👇👇

Direct customer actions like calls, directions, and website clicks into your Analytics reporting. Not bad.

The end of an era.

Never before has a single book defined an entire industry. Which book am I referring to?

Build Meaning Before Machines: Why Semantics, Ontologies, And Knowledge Graphs Matter For Agentic AI Forrester's analysis notes that Agentic AI is exposing a foundational gap in most enterprise data strategies: Data without meaning is unusable for autonomous systems. Agents don’t just retrieve data — they interpret, decide, and act. Without explicit context, they guess. And when agents guess, they get joins wrong, misinterpret metrics, and act on flawed assumptions. This is why ontologies, semantic layers, and knowledge graphs are rapidly becoming core architectural components. They provide what agentic systems lack in traditional data environments: a shared language, explicit relationships, and machine-readable context. Two recently published reports give leaders clear definitions for semantics, ontologies, and knowledge graphs and provide a path for enterprises to get started on their AI transformation journey. Semantic Layers Are The Starting Point Make Data AI Ready Via Semantic Layer Platforms (with Noel Yuhanna) focuses on the first step in this journey: making data interpretable before making it intelligent.  Semantic layers have long ensured business-intelligence consistency. In the agentic era, they also give agents the governed context needed to turn natural language into accurate queries and actions. Modern semantic layer platforms also extend beyond metric definitions with runtime services, APIs, lineage, and policy enforcement across hybrid and multicloud environments — keeping business meaning stable as platforms change.  The report also introduces the data graph as a bridge to knowledge graphs, capturing relationships and usage patterns so organizations can give agents more context without jumping directly to a full knowledge graph architecture. Knowledge Graphs Define The Destination Combine Semantics, Ontology, And Knowledge Graphs For AI-Ready Data (with Indranil Bandyopadhyay and Charlie Dai) demystifies semantics, ontology, and knowledge graphs as terms.  The report suggests a desired end state: a semantically rich enterprise where all enterprise entities are not just connected but understood. It proposes a layered approach in which ontologies define knowledge, semantics enforce clarity and consistency, and knowledge graphs connect these elements into a model that supports reasoning and discovery.  Knowledge graphs are more than a data integration technique; they form the foundation of an enterprise digital twin. By making all enterprise entities and relationships explicit, they help AI interpret context, infer connections, and act more accurately across domains. Start With Semantics, Then Evolve To A Digital Twin The two reports together define a clear evolution path. Most organizations are not yet ready to build a knowledge graph. The semantic layer is the right starting point. It creates a consistent foundation of meaning: standardized definitions, governed metrics, and shared logic across tools and teams. The knowledge graph is the long-term destination — a form of digital twin that enables agentic AI to reason and act across the enterprise. forrester.com/blogs/build-me… #AgenticAI #KnowledgeGraph #SemanticLayer #DataStrategy #EnterpriseAI #DigitalTwin #AIReadyData -- Connected Data London 2026 | 11–12 November | Leonardo Royal Hotel London Tower Bridge 🎤 Share your work with the world's most passionate data community. The Call for Submissions is open.  connected-data.london/2026-c… 🎟 Tickets on sale now. Early bird discounts up to 30%. 2026.connected-data.london?u… 📺 Sponsorship opportunities available. Contact info@connected-data.london for details. #KnowledgeGraph #GraphRAG #Ontology #Graph #AI #DataScience #GraphDB #SemTech

A silent form of dictatorship.

👀You can now connect your Google Business Profile to Gemini and make a Business Notebook. It has access to customer reviews, questions and also performance data. It can tell you trends, new market opportunities and you can ask Gemini to update your profile with new business hours, etc. blog.google/innovation-and-a…

Ontologies aren't disappearing in the age of AI agents. They're becoming the layer that helps agents retrieve, remember, validate, and act. A great read from @cyberandy: eu1.hubs.ly/H0v-Ymp0 #AI #KnowledgeGraphs

Join the movement.

Rome and SEO fall in love again. Join me 🍕.

GPU cycles are teaching me one thing: enterprise agents need specialized intelligence for the long-tail reasoning tasks that AI labs cannot model deeply. Training is not a race toward a single score. It is a search for useful specialization.