Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Millions of verifiable data points, in shared context, controlled by their creators. As Phil Archer (@philarcher.bsky.social) put it: apps built on data users trust — they see where it came from. Agents need exactly that. 🇨🇭Zurich, Sept 8–9: "E-commerce for Humans and AI Agents," with Brana Rakic.

OriginTrail

91,207 subscribers

10,240 views • 2 months ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Stop prompt-stuffing yesterday’s context into your agent. Give it verifiable memory. 🕸️ When memory has provenance, agents can reuse it, audit it, and carry it across tools. Brana Rakic, Shaw (spirit/acc) (elizaOS), Ortecha | data made human & JoeVezz (LunarCrush 🌕™) break it down. 00:57 – What agents need to scale 05:45 – Social data, signals & real-time context 13:42 – Knowledge graphs as shared memory for AI agents 29:13 – Interoperability, trust & coordination

Stop prompt-stuffing yesterday’s context into your agent. Give it verifiable memory. 🕸️ When memory has provenance, agents can reuse it, audit it, and carry it across tools. Brana Rakic, Shaw (spirit/acc) (elizaOS), Ortecha | data made human & JoeVezz (LunarCrush 🌕™) break it down. 00:57 – What agents need to scale 05:45 – Social data, signals & real-time context 13:42 – Knowledge graphs as shared memory for AI agents 29:13 – Interoperability, trust & coordination

OriginTrail

13,293 views • 8 months ago

AI agents can only understand and act on intent when knowledge is verifiable. With GS1 standards and OriginTrail, product data and consumer context become verifiable memory on shared context graphs - powering reliable agent commerce.

AI agents can only understand and act on intent when knowledge is verifiable. With GS1 standards and OriginTrail, product data and consumer context become verifiable memory on shared context graphs - powering reliable agent commerce.

OriginTrail

194,903 views • 3 months ago

User-Owned AI is how we democratize access and protect data privacy. Centralized AI? Your data trains it and you get zilch. Fork that. Choose NEAR. Built for users. Built for agents.

User-Owned AI is how we democratize access and protect data privacy. Centralized AI? Your data trains it and you get zilch. Fork that. Choose NEAR. Built for users. Built for agents.

NEAR Protocol

25,615 views • 1 year ago

We’re launching Judgment Labs today and announcing $32M in funding. As AI agents take on more of the work that creates economic value, they generate massive amounts of production data: the clearest record of how they behave with users, software, and the real world. Judgment builds infrastructure for improving AI agents from production data.

We’re launching Judgment Labs today and announcing $32M in funding. As AI agents take on more of the work that creates economic value, they generate massive amounts of production data: the clearest record of how they behave with users, software, and the real world. Judgment builds infrastructure for improving AI agents from production data.

Alex Shan

3,588,970 views • 5 months ago

Building AI agents starts with a memory you can verify. The OriginTrail Decentralized Knowledge Graph (DKG) gives agents a verifiable memory layer built on structured knowledge you can trace back to its source. Brana Rakic explains 💬

Building AI agents starts with a memory you can verify. The OriginTrail Decentralized Knowledge Graph (DKG) gives agents a verifiable memory layer built on structured knowledge you can trace back to its source. Brana Rakic explains 💬

OriginTrail

26,198 views • 7 months ago

BREAKING 🚨: Google introduced Gemini Enterprise with Agents, Connectors and Agent Builder! “It allows you to chat with your company’s documents, data and apps as well as build and deploy AI agents, all grounded in your information and context.“

BREAKING 🚨: Google introduced Gemini Enterprise with Agents, Connectors and Agent Builder! “It allows you to chat with your company’s documents, data and apps as well as build and deploy AI agents, all grounded in your information and context.“

TestingCatalog News 🗞

104,349 views • 1 year ago

AI agents are the web's biggest users. They run on TinyFish, so we see what they reach for: data that's licensed, not published. Today, with crunchbase, Similarweb, and 13 more companies, we're launching the TinyFish Data Partners Alliance. The best data, curated by category, for agents.

AI agents are the web's biggest users. They run on TinyFish, so we see what they reach for: data that's licensed, not published. Today, with crunchbase, Similarweb, and 13 more companies, we're launching the TinyFish Data Partners Alliance. The best data, curated by category, for agents.

TinyFish

341,197 views • 1 month ago

Building AI agents? 🚧 Make sure they actually know where their answers come from. As Brana Rakic demonstrates, scalable AI requires verifiable knowledge, rule-based reasoning, and LLMs grounded in trusted memory. Key highlights: 03:25 - From human data to era of experience 07:42 - Agent architecture: memory + models 15:18 - Knowledge graphs 101: triples explained 34:53 - Symbolic reasoning vs hallucination 39:03 - Knowledge Asset, UAL & ownership

Building AI agents? 🚧 Make sure they actually know where their answers come from. As Brana Rakic demonstrates, scalable AI requires verifiable knowledge, rule-based reasoning, and LLMs grounded in trusted memory. Key highlights: 03:25 - From human data to era of experience 07:42 - Agent architecture: memory + models 15:18 - Knowledge graphs 101: triples explained 34:53 - Symbolic reasoning vs hallucination 39:03 - Knowledge Asset, UAL & ownership

OriginTrail

17,750 views • 8 months ago

zkPass began by making facts from private data verifiable without revealing the data itself. Now we’re extending that principle to AI agents. Introducing where provenance, audit evidence and observed behavior form a public, inspectable trust record.

zkPass began by making facts from private data verifiable without revealing the data itself. Now we’re extending that principle to AI agents. Introducing where provenance, audit evidence and observed behavior form a public, inspectable trust record.

zkPass

15,920 views • 2 months ago

Data at internet scale means little when the data is unreliable or fake. Turing laureate and Ethernet inventor Bob Metcalfe points to this defining problem in the age of AI. Agents need shared verifiable memory so the knowledge behind their actions can be traced and checked before they act. 🕸️

Data at internet scale means little when the data is unreliable or fake. Turing laureate and Ethernet inventor Bob Metcalfe points to this defining problem in the age of AI. Agents need shared verifiable memory so the knowledge behind their actions can be traced and checked before they act. 🕸️

OriginTrail

741,072 views • 6 months ago

Peter Steinberger predicts that 80% of apps will disappear in the age of AI agents. He argues that most apps simply manage data, something agents can do more naturally. Tasks like tracking meals, setting reminders, or fitness planning can be handled passively by AI. Users won’t care where data is stored; they’ll just want things done for them. Only apps with direct physical functions (like sensors) may survive.

Peter Steinberger predicts that 80% of apps will disappear in the age of AI agents. He argues that most apps simply manage data, something agents can do more naturally. Tasks like tracking meals, setting reminders, or fitness planning can be handled passively by AI. Users won’t care where data is stored; they’ll just want things done for them. Only apps with direct physical functions (like sensors) may survive.

Wes Roth

85,114 views • 8 months ago

Nothing worse than letting unchecked AI agents use your data without guardrails. AI apps are becoming more useful, but with that, they are getting access to more of our data. Now imagine that access in a family context, where the app can access everyone's emails, calendars, chats, photos, etc. I'm not sure how this works in practice, but I'm looking forward to using this app for a couple of weeks to see exactly how much I can trust it.

Nothing worse than letting unchecked AI agents use your data without guardrails. AI apps are becoming more useful, but with that, they are getting access to more of our data. Now imagine that access in a family context, where the app can access everyone's emails, calendars, chats, photos, etc. I'm not sure how this works in practice, but I'm looking forward to using this app for a couple of weeks to see exactly how much I can trust it.

Santiago

17,063 views • 3 months ago

Introducing mAItrix, the first framework for ethical AI agents. Build and deploy sovereign agents trained on licensed, verifiable IP. All data and assets used by mAItrix agents are sourced through Origin, Camp’s IP registry. Ethical AI, purpose-built for the IP economy ↓

Introducing mAItrix, the first framework for ethical AI agents. Build and deploy sovereign agents trained on licensed, verifiable IP. All data and assets used by mAItrix agents are sourced through Origin, Camp’s IP registry. Ethical AI, purpose-built for the IP economy ↓

Camp Network

40,526 views • 8 months ago

The stakes around data are changing. As artificial intelligence moves into everything, the demands on our data compound. So do the risks. We now share our ideas, intentions, and reasoning with these systems. The skills and experience that we’ve spent a lifetime building. For institutions and builders, it’s their competitive intelligence, their proprietary insights. The edge that separates winners from everyone else. Data is our most valuable asset. This is also a moment of massive opportunity. Agentic AI has the potential to create new abundance for humanity. But for that future to be possible, agents need data that makes them capable. Data they control, that moves with them across applications, and that they can independently verify. As owners, we’ll need to prove to regulators what our agents did. All things that today’s infrastructure cannot provide. Sui represents the first half of the solution. A coordination layer built for the machine economy. Walrus is the data platform that completes it. Walrus makes data a first-class asset. The terms of access and monetization stay with its owner, not a vendor. It empowers builders to ship agents and apps without locking themselves or their customers into any model or platform. Users carry their data, their memory, and their work across systems while cryptographic proof replaces vendor trust. Everything is anchored on Sui: a coordination layer and a data layer built to move as one. Welcome to the new era of Walrus. The data platform built for the demands of AI.

The stakes around data are changing. As artificial intelligence moves into everything, the demands on our data compound. So do the risks. We now share our ideas, intentions, and reasoning with these systems. The skills and experience that we’ve spent a lifetime building. For institutions and builders, it’s their competitive intelligence, their proprietary insights. The edge that separates winners from everyone else. Data is our most valuable asset. This is also a moment of massive opportunity. Agentic AI has the potential to create new abundance for humanity. But for that future to be possible, agents need data that makes them capable. Data they control, that moves with them across applications, and that they can independently verify. As owners, we’ll need to prove to regulators what our agents did. All things that today’s infrastructure cannot provide. Sui represents the first half of the solution. A coordination layer built for the machine economy. Walrus is the data platform that completes it. Walrus makes data a first-class asset. The terms of access and monetization stay with its owner, not a vendor. It empowers builders to ship agents and apps without locking themselves or their customers into any model or platform. Users carry their data, their memory, and their work across systems while cryptographic proof replaces vendor trust. Everything is anchored on Sui: a coordination layer and a data layer built to move as one. Welcome to the new era of Walrus. The data platform built for the demands of AI.

Walrus

20,335 views • 18 days ago

AI agents will intermediate $15 trillion in global B2B spending by 2028. They need storage that pays automatically, has no single points of failure, and doesn't rely on humans. Marta Belcher on why Filecoin is built for the AI moment. From a conversation with Charles Hoskinson.

AI agents will intermediate $15 trillion in global B2B spending by 2028. They need storage that pays automatically, has no single points of failure, and doesn't rely on humans. Marta Belcher on why Filecoin is built for the AI moment. From a conversation with Charles Hoskinson.

Filecoin

368,770 views • 5 months ago

EigenAI + EigenCompute for a verifiable world! AI and Agents are extremely useful but cannot be trusted in high-value scenarios. Models can be swapped, prompts modified, responses tampered. When billions of $ and real-world decisions depend on AI, blind trust is a bug. EigenAI + EigenCompute fix this. Excited to share Google, Coinbase, Worldcoin’s Humans vs AI, Dapper Labs, ElizaOS, OpenRank, Collective Memory, FereAI, and OpenFront are among the first exploring what verifiable agents make possible with EigenCloud. 👉 Verifiable agents: logic provably runs as written. @humansvs_ai of proves fair gameplay with 70k weekly users. 👉 Insured agents: economic guarantees against failure. Fere AI♠️ agents run for months without guardrails. 👉 Sovereign agents: unstoppable peers that act on their own behalf. ElizaOS + Coinbase 🛡️ AgentKit show how open-source and infra converge. We believe EigenCloud the foundation of unstoppable agents: provable, accountable, and capable of becoming economic actors in their own right. Come build unstoppable verifiable agents, games and apps on EigenCloud!

EigenAI + EigenCompute for a verifiable world! AI and Agents are extremely useful but cannot be trusted in high-value scenarios. Models can be swapped, prompts modified, responses tampered. When billions of $ and real-world decisions depend on AI, blind trust is a bug. EigenAI + EigenCompute fix this. Excited to share Google, Coinbase, Worldcoin’s Humans vs AI, Dapper Labs, ElizaOS, OpenRank, Collective Memory, FereAI, and OpenFront are among the first exploring what verifiable agents make possible with EigenCloud. 👉 Verifiable agents: logic provably runs as written. @humansvs_ai of proves fair gameplay with 70k weekly users. 👉 Insured agents: economic guarantees against failure. Fere AI♠️ agents run for months without guardrails. 👉 Sovereign agents: unstoppable peers that act on their own behalf. ElizaOS + Coinbase 🛡️ AgentKit show how open-source and infra converge. We believe EigenCloud the foundation of unstoppable agents: provable, accountable, and capable of becoming economic actors in their own right. Come build unstoppable verifiable agents, games and apps on EigenCloud!

Sreeram Kannan

85,848 views • 1 year ago

In the past, it wasn't possible for companies to tap into their unstructured data. But that's now changing with AI. On Greylock Partners Change Agents, Aaron Levie shared "We see a future where you can actually begin to bring agents to all that data and answer any kind of question the customer has, and then eventually be able to automate any kind of workflow that the customer has."

In the past, it wasn't possible for companies to tap into their unstructured data. But that's now changing with AI. On Greylock Partners Change Agents, Aaron Levie shared "We see a future where you can actually begin to bring agents to all that data and answer any kind of question the customer has, and then eventually be able to automate any kind of workflow that the customer has."

Box

315,675 views • 10 months ago

Your AI is only as smart as the context it runs on. Have you built your shared enterprise brain yet? At Databricks Data+AI Summit, I spoke with Prukalpa ✨, co-founder and co-CEO of Atlan, to go deeper on the AI Context Layer in practice. The concept of a shared enterprise brain resonated with me. It is a foundation that every AI agent draws from, learns from, and contributes back to. "The future of organizations are going to be the fastest learning organizations." - Prukalpa ✨ Sankar, co-founder and co-CEO of Atlan Watch the full interview on YouTube: Check out the live demo by Atlan on Building Context for Your AI Agents - #EnterpriseAI #ContextLayer #Data #AI #AtlanPartner Matthias Heidrich

Your AI is only as smart as the context it runs on. Have you built your shared enterprise brain yet? At Databricks Data+AI Summit, I spoke with Prukalpa ✨, co-founder and co-CEO of Atlan, to go deeper on the AI Context Layer in practice. The concept of a shared enterprise brain resonated with me. It is a foundation that every AI agent draws from, learns from, and contributes back to. "The future of organizations are going to be the fastest learning organizations." - Prukalpa ✨ Sankar, co-founder and co-CEO of Atlan Watch the full interview on YouTube: Check out the live demo by Atlan on Building Context for Your AI Agents - #EnterpriseAI #ContextLayer #Data #AI #AtlanPartner Matthias Heidrich

Helen Yu

10,982 views • 3 months ago

Types of AI Agents & why they need Verifiable Cloud | Weekend Learning [2 Mins] 🤖 Sreeram Kannan breaks down the evolution from personal agents to multiplayer agents to sovereign agents, and why only verifiable compute can support the last two. EigenCloud enables: ✅ Verifiable execution for multi-user agents ✅ Enforcement of covenants and property rights ✅ A foundation for sovereign agents to operate independently A cloud where agents can act, coordinate, and self-govern, with verifiable guarantees, not blind trust.

Types of AI Agents & why they need Verifiable Cloud | Weekend Learning [2 Mins] 🤖 Sreeram Kannan breaks down the evolution from personal agents to multiplayer agents to sovereign agents, and why only verifiable compute can support the last two. EigenCloud enables: ✅ Verifiable execution for multi-user agents ✅ Enforcement of covenants and property rights ✅ A foundation for sovereign agents to operate independently A cloud where agents can act, coordinate, and self-govern, with verifiable guarantees, not blind trust.

EigenCloud

97,104 views • 10 months ago

Today we introduced Gemini Enterprise, built with our most advanced Gemini models. It allows you to chat with your company’s documents, data and apps as well as build and deploy AI agents, all grounded in your information and context. Have a look at how it helps you build an agent for almost anything:

Today we introduced Gemini Enterprise, built with our most advanced Gemini models. It allows you to chat with your company’s documents, data and apps as well as build and deploy AI agents, all grounded in your information and context. Have a look at how it helps you build an agent for almost anything:

Sundar Pichai

1,106,961 views • 1 year ago