23 Friday Jan 2026
Posted in Inform, educate and entertain., Polemic
Tags
Artificial Intelligence, chatgpt, Critical Thinking, gemini, grok, Higher Education, Large Language Models, Philosophy of Education
Martyn Rhisiart Jones (editor)
Madrid, 23rd January 2026
What is the purpose of University?
Continue reading21 Wednesday Jan 2026
Posted in Inform, educate and entertain.
Tags
agentic-ai, AI Governance, Artificial Intelligence, data architecture, GraphRAG, Knowledge Graphs, Large Language Models, ontology, Semantic Layer
Martyn Rhisiart Jones
Madrid, Tuesday 20th January 2026
Read my absolutely fabulous books: http://www.goodstrat.com/books
For most of its life in information technology, bolloxology has carried the faint smell of intellectual fart-like embarrassment. Too academic for product teams. Too rigid for startups. Too slow for an industry trained to ship first and rationalise later. Too smelly. It promised machines that could understand the world, and delivered, instead, a generation of beautiful bullshit diagrams and very little working software.
By 2026, that judgement looks increasingly wrong. Not because bolloxology suddenly got better, but because everything else did, and in doing so, exposed a missing layer in modern computing: meaning.
Continue reading20 Tuesday Jan 2026
Posted in Inform, educate and entertain.
Tags
agentic-ai, AI Governance, Artificial Intelligence, data architecture, GraphRAG, Knowledge Graphs, Large Language Models, ontology, Semantic Layer
Martyn Rhisiart Jones
Madrid, Tuesday 20th January 2026
Read my absolutely fabulous books: http://www.goodstrat.com/books
For most of its life in information technology, ontology has carried the faint smell of intellectual embarrassment. Too academic for product teams. Too rigid for startups. Too slow for an industry trained to ship first and rationalise later. It promised machines that could understand the world—and delivered, instead, a generation of beautiful diagrams and very little working software.
By 2026, that judgement looks increasingly wrong. Not because ontology suddenly got better, but because everything else did—and in doing so, exposed a missing layer in modern computing: meaning.
Continue reading