While 2.0 was in the works, we took a pause on creating new Collate Clues, but with 2.0 now released, we have a new Clues that is going to give you a great overview of what is happening in this revolutionary new release. Watch🎥 here👉 buff.ly/g7PyjtM #OpenMetadata #OpenLineage #DataEngineering #AIContext #Ontology #KnowledgeBase #ContextCenter

Nick Doyle, Head of Growth at Collate, joins @progrockrec for an insightful discussion about what has been happening in the data ecosystem, what they think is coming next, and tips for effectively using AI. Hook up your big-screen and surround-sound system for this one. Watch🎥 here👉buff.ly/u0zZSDW #DataLineage #DataGovernance #OpenMetadata #OpenLineage #Context #DataContext #MetadataManagement #DataStewardship

Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead. You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement. I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible. But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier. Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want. Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well. So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it. If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop.

Data without context is just noise. But what happens when "context" itself changes depending on where you stand? Mustapha Fonsau, CIO of Talentys, joins @progrockrec for this latest installment of Ask the Experts, where they explore that and other interesting ideas. Don't miss out on all the goodness. Watch🎥here👉buff.ly/X7N1rq1 #DataLineage #DataGovernance #OpenMetadata #OpenLineage #Context #Culture #GDPR #CNDP #DataIntelligence #DataMesh #DataContext #MetadataManagement #DataStewardship

We're seeing six mistakes stalling enterprise AI. And if your pilot demoed well and died in production, you probably made one of these: 1. Reaching for a bigger model when the model was never the constraint 2. Engineering the prompt instead of the environment it reads from 3. Evaluating generated SQL instead of table selection 4. Treating the catalog as the context layer 5. Buying context without ontology and memory 6. Letting meaning fragment with no named owner The demo works because someone put the definition in the prompt. Then that definition lives in a prompt rather than in your data, and the next agent starts from zero. All six broken down in the new video, along with the questions to ask before you sign a vendor contract. 🎥Watch👉here: buff.ly/PJZ8eUD

AI agents confidently deliver wrong answers when they're missing context. In our benchmarks, Collate 2.0 delivers 86% fewer errors and 66% lower token spend. Watch the 2-minute video highlights of what shipped with this release: → Context Center + Memory to organize your context, ontology, and memory → Persona-Based Context Curation to shape context per user and agent → Context API + MCP Tooling to serve trusted context to any AI application → AI-Native Experience with AI Analytics, Studio, Automations, Shared Chats → AI Governance Studio (Release Preview) to govern every LLM, MCP server, and agent Watch: buff.ly/l3dqmgh #Collate #OpenContextLayer #AIAgents #AIforData #OpenMetadata