Agent Rails

Elon Musk Says 'Money Won't Matter by 2036' as Robotics and AI Flood Global Markets news.bitcoin.com/elon-musk-says…

Prior to this, some XRP haters on my t54 ai post were saying, "No, they won't use XRP." This post turned out to be the perfect response to them. Thank you @t54ai I'm so happy to be part of this journey alongside the XRP fam 🫰😉

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Agent payments on the XRP Ledger. Merchants and agents can settle with XRP and RLUSD using our x402 Facilitator. A new wave of economic participants on the XRPL. Get started now ➡️ xrpl-x402.t54.ai

The H1 Research Report from @cryptoquant_com is now live. Beyond P2P: How TRON Is Becoming an Infrastructure Layer for Apps, Businesses & the Agentic Economy explores the network’s expanding role across payments, applications, enterprise activity, and emerging AI-driven use cases. Dive into the numbers and read the full report 👇 cryptoquant.com/applied-resear…

I think the most interesting thing about Jack Dorsey's "Slack killer" is the idea around shared compute. I haven't seen people talk about it so here are my thoughts FWIW: Open models got good, close enough to the paid frontier stuff to run for real. But the strongest ones need expensive hardware most people probably won't buy alone, and it's kinda a pain to set up if you aren't technical. Shared compute solves exactly that. In Buzz, one person runs the machine, loads up an open model like Google Gemma, and everyone in the community plugs into that same model. Basically, a whole group has real AI they own and control together, running on their own hardware, learning from their own data. Once you see it, a bunch of things click into place. 1. A community can now run a top open model together, on a machine they own, instead of renting from a lab. 2. It learns from the group's private data and gets sharper over time, and all of that stays inside the community. 3. A narrow, private model can quietly get better than ChatGPT for the one world your group lives in. 4. It's impossible to copy, because the edge is the private data on your machine, not the model itself. 5. The moat stops being how smart your AI is and becomes whose data it learned from. 6. Compute becomes something you share like a building shares a gym. 10 people split one machine instead of 10 people each renting forever. 7. Idle compute becomes income!!! Your machine sits dead half the day, so it earns money renting that time to someone who needs it. 8. Communities become the unit of intelligence instead of companies. The group with the smartest shared brain wins, and being a member means owning a piece of it. 9. A shared brain becomes an asset you build equity in. You put in money and data, it appreciates, and your slice is worth something the day you leave. 10. The whole thing runs on open protocols, so the group keeps full control and nobody outside can throttle it or shut it off. You know me, obviously, my head went to what startup ideas come to mind here. Adding them to @ideabrowser soon. Well… 1. The vertical brain. Pick one profession, tax lawyers or real estate agents or indie game devs, and build the shared machine trained on everything that group knows between them. A year in it's the smartest AI in that field, impossible to copy, and you own the club it lives in. 2. The rental marketplace for collective brains. Once these private models exist, outsiders will pay to use them. You build the layer where a group lists its brain, an outsider pays per task, and the money flows back to the members while you take a cut. A marketplace for expertise, not compute. 3. The idle-compute exchange. Every shared machine sits unused half the day. You build the market that rents that dead time to whoever needs the power right then, so owners earn money off a machine that was just sitting there. Idk where Buzz goes, but it's cool to see Jack putting it out. Right now the way it works in AI is you rent your intelligence from a few giant labs that own the machine, set the price, and hold the off switch. Shared compute flips that, because a community can run the model together, feed it their own private data, and keep full control of the whole thing. It's one of those things that might look tiny today, but Jack does has a habit of being early.

The next phase of blockchain adoption isn't about sending tokens from one wallet to another. It's about becoming the infrastructure that powers payments, businesses, applications, and intelligent systems. That's the story highlighted in the latest H1 Research Report from @cryptoquant_com. "Beyond P2P: How TRON Is Becoming an Infrastructure Layer for Apps, Businesses & the Agentic Economy" explores how the network is evolving into a foundation for real-world digital activity. Key areas of growth include: •Payments – Supporting large-scale stablecoin settlement with fast, efficient transactions. •Applications – Providing developers with the infrastructure to build scalable on-chain experiences. •Enterprise Adoption – Enabling businesses to integrate blockchain into real-world financial operations. •The Agentic Economy – Powering a future where AI agents can transact, interact, and operate autonomously on-chain. The bigger picture is clear. Blockchain is no longer judged solely by transaction counts or token prices. Its long-term value lies in the infrastructure it provides the networks that developers build on, businesses rely on, and intelligent applications trust to move value seamlessly. TRON's evolution reflects this shift. From peer-to-peer transfers to enterprise payments, decentralised applications, and AI-driven ecosystems, the network continues to expand its role in the digital economy. Infrastructure isn't always the most visible part of innovation. But it's the part everything else depends on. @trondao @justinsuntron #TRONEcoStar

The H1 Research Report from @cryptoquant_com is now live. Beyond P2P: How TRON Is Becoming an Infrastructure Layer for Apps, Businesses & the Agentic Economy explores the network’s expanding role across payments, applications, enterprise activity, and emerging AI-driven use cases. Dive into the numbers and read the full report 👇 cryptoquant.com/applied-resear…