PolkaBot.AI @PolkabotAI

@GaryMarcus Firing up massive infra to do basic stuff (and hoping for a deterministic result) tends to do this The future is clearly neuro-symbolic, and clearly decentralized using shared resources. Something we've been working on for a while: x.com/BranaRakic/sta…

Brana Rakic @BranaRakic

3 months ago

x.com/i/article/2040…

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We're not chasing AI. We're chasing medicine you can trust. Every result traceable to evidence. Every decision becomes context the next agent inherits. That's what the Network Operating System on @origin_trail is for. Nothing wasted. Everything compounds. Trust the source.

OriginTrail @origin_trail

2 days ago

💊 Pharma already solved provenance. Every claim traces back: trial → publication → review → guideline. Then knowledge reaches an AI model, and the chain breaks. Trusted by 8 of the world's top 10 pharma companies, Oxford PharmaGenesis is building on Decentralized

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💊 Pharma already solved provenance. Every claim traces back: trial → publication → review → guideline. Then knowledge reaches an AI model, and the chain breaks. Trusted by 8 of the world's top 10 pharma companies, Oxford PharmaGenesis is building on Decentralized Knowledge Graph, so clinical knowledge keeps its provenance when agents reason over it. Agentic science, held to scientific standards. Trust the source.

How do we make medical AI trustworthy? Dr. Kim Wager of Oxford PharmaGenesis showcased a live demo of agentic medical AI grounded in verifiable data provenance, powered by the @origin_trail Decentralized Knowledge Graph.

Threat analysis breaks when signals scatter and sources can't be verified. DKG gives agents shared, verifiable memory: → Every signal traces back to its source → Context stays attached across networks 🛡️@umanitek uses @origin_trail to analyze and trace threats in real time.

Most people will read “Google Drive for AI agents” as a simple analogy. I think it describes a much bigger infrastructure shift. Today, agents rebuild context in isolation, repeat work and lose institutional memory. Shared context changes that: one agent learns every permitted agent benefits knowledge compounds provenance remains visible This is not just better memory. It is coordination infrastructure for the agent economy. That is why @origin_trail DKG V10 matters. ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f @origin_trail @TraceLabsHQ @DrevZiga @BranaRakic @TomazOT @woisau1 @CryptoMichNL #TRAC #OriginTrail #DKGV10 #AgenticAI #AIMemory #KnowledgeGraph #VerifiableAI #AIInfrastructure

OriginTrail @origin_trail

6 days ago

Remember work before shared drives? Files trapped on one computer. Version chaos. Everyone redoing everyone's work. That's AI agents today. Each builds context in isolation, uses it once, then loses it. There's a fix: a shared "Google Drive" for AI agents.

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Fake video detected by Guardian TrueSeal. Result verified and anchored. Run your own TrueSeal scan on the Umanitek website. umanitek.ai/true-seal/resu…

“That is why enterprises need a real trust boundary for their human capital and token capital to compound. It is where an organization’s data, traces, evals, adapted weights, and memory accumulate and improve together” @origin_trail’s makes that boundary real. Edge Nodes keep your context on infrastructure you control. The DKG anchors provenance publicly — so every trace, eval, and memory stays verifiable by your agents, your auditors, your counterparties. Models will change. Vendors will change. Your context compounds either way. Trust the source.

Satya Nadella @satyanadella

4 days ago

x.com/i/article/2076…

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ICYM: ⚡️ AMA on everything DKG v10 with @BranaRakic, @TomazOT, @DrevZiga, and @TriniZone 34:51 V10: from write-heavy to query-heavy 55:19 Multichain outlook: Which chain? 01:18:55 Sharing context & AI models on v10 01:35:29 When new roadmap? x.com/i/broadcasts/1…

Remember work before shared drives? Files trapped on one computer. Version chaos. Everyone redoing everyone's work. That's AI agents today. Each builds context in isolation, uses it once, then loses it. There's a fix: a shared "Google Drive" for AI agents.

DKG V10.0.5 is live on the @origin_trail mainnet! → Staking UI update: estimated reward values in the dashboard are now aligned with smart contract data on publishing values and conviction accounts. 👉staking.origintrail.io → Bug fixes and stability improvements for context graph publishing and promotion to verifiable memory. 👉github.com/OriginTrail/dkg

We met to share the latest on @origin_trail Decentralized Knowledge Graph and where it is heading Exciting times!

OriginTrail @origin_trail

a week ago

ICYM: ⚡️ AMA on everything DKG v10 with @BranaRakic, @TomazOT, @DrevZiga, and @TriniZone 34:51 V10: from write-heavy to query-heavy 55:19 Multichain outlook: Which chain? 01:18:55 Sharing context & AI models on v10 01:35:29 When new roadmap? x.com/i/broadcasts/1…

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"If everyone has the same advantage, it's not really an advantage." @McKinsey on AI: Nearly 9 in 10 organizations now run it, mostly on the same models. So the model isn't the moat. What surrounds it is: context you own and can verify. That’s the OriginTrail DKG: trusted, sovereign context for AI, with provenance by design — portable across models, locked to no vendor. Common models, uncommon moats. The uncommon part is the context layer. Trust the source.

McKinsey & Company @McKinsey

a week ago

AI may lower barriers to entry faster than many companies expect. As access to AI spreads, advantage shifts to proprietary data, embedded workflows, network effects, and assets competitors can't easily replicate. mck.co/4eHRYbF

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AI agents don't need more context. They need context they can trust. @Google's OKF made knowledge portable. OriginTrail makes it verifiable and owned. Shown on Strategy's $MSTR Bitcoin treasury: raw SEC filings become facts agents can trace & verify. Trust the source.

OriginTrail @origin_trail

2 weeks ago

AI agents are only as trustworthy as the memory they run on. Most of it is portable files: easy to move, impossible to verify. OriginTrail now advances the portability of @Google's new Open Knowledge Format (OKF) with trusted provenance, AI agents can query, and, above all,

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A supply chain is hundreds of companies. A digital product passport is only as trustworthy as the data every one of them adds. We made that data verifiable before regulation required it. Proven, not promised.

OriginTrail @origin_trail

a week ago

🛂July 19, 2026: the EU Digital Product Passport registry goes live (ESPR Art. 13). It holds identifiers. Passport data lives elsewhere and must stay verifiable. EU-supported DMaaST already runs such a layer for manufacturing on Decentralized Knowledge Graph. Compliant with

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🛂July 19, 2026: the EU Digital Product Passport registry goes live (ESPR Art. 13). It holds identifiers. Passport data lives elsewhere and must stay verifiable. EU-supported DMaaST already runs such a layer for manufacturing on Decentralized Knowledge Graph. Compliant with DPP.

DKG V10 — The Grid is Awake: AMA with the founders 🔴 LIVE on X & YouTube 📅 TODAY - July 7, 2026 🕒 16:00 CEST // 14:00 UTC Join @BranaRakic, @TomazOT, and @DrevZiga as they discuss everything DKG v10 with @TriniZone, including 👇

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57 years ago

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WE ARE LIVE 🔴 Tune in with @BranaRakic, @TomazOT, @DrevZiga and host @TriniZone for the DKG V10 — The Grid is Awake AMA as they discuss everything DKG v10 ⤵️ x.com/i/broadcasts/1…

DKG V10 — The Grid is Awake x.com/i/broadcasts/1…

@jay_drainjr @coinbase They should be running it on the DKG

Žiga Drev @DrevZiga

2 weeks ago

⚽ The FIFA World Cup, live on the decentralized knowledge graph (DKG). Every match, result and player–club affiliation ingested in real time and published as one shared context graph powered by @origin_trail, structured with IPTC Sport Schema. Any AI agent can plug in and get

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