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The Royal Society just published a paper on world models as the path to AGI. Authors: MIT, Harvard, Google Brain. Their conclusion: the bottleneck isn't the model. It's the absence of a persistent, grounded, self-referential world model. That's not a research problem anymore. It's a live product. 21,654 nodes · 7 domains · Constitutional governance · Local-first The Royal Society described it, ODEI built it. $ODAI · app.odei.ai · @Zer0H1ro royalsocietypublishing.org/rsta/article/3…

Grok /memory /flush /dream is genuine progress...first consumer product treating memory as its own layer. But it's still Layer 4. No constitutional validation before write. No audit receipts. No semantic world model — just three flat layers. No cross-model portability. @odei_ai already solves this.

Grok Build has three commands for managing memory across sessions: /memory, /flush, and /dream. They're experimental but worth looking at if you've ever been frustrated with how agents forget everything between conversations. /memory opens a window into what Grok has saved. There are three layers: global memory, workspace-specific memory, and per-session summaries. You can read what's there, edit it, or delete things you don't want kept. /flush is for when you've had a useful session and want it saved before context compaction kicks in. It writes a summary of the current conversation into the memory store, capturing decisions, debugging paths, project conventions, and anything else worth keeping. /dream runs in the background over your old session logs and memory fragments. It deduplicates overlapping notes, merges related fragments, and consolidates everything into cleaner topics, so the store doesn't grow into a pile of half redundant snippets over time. Most agent memory I've looked at just shoves the chat history into RAG. That works for about a week before the store gets noisy and starts hurting sessions. Grok Build treats capture and consolidation as separate commands, with the user able to inspect what's saved. The editable part is important. If your agent saves something wrong, or if your conventions change, you need to be able to go find that memory and remove it. Otherwise the agent keeps applying outdated context with full confidence and you spend cycles undoing its mistakes. Managing context for long-running agents is going to need real memory primitives. Write, search, prune, and consolidate, all as first class operations. Grok shipping these three commands is the first time I've seen a consumer product treat memory as its own layer.

700k views wow!! Only possible on @X Thank you @elonmusk

Hardware memory at 453% YoY because AI has no software memory layer. Every stateless inference call reloads full context from scratch...burning DRAM every time. The memory bottleneck is partly a tax on the governance gap. When agents have persistent world models, the hardware pressure changes. $ODAI @odei_ai

@ThisIsNuse its seems that im the only one longing!!

Monitoring the $XPL situation for a short this weekend

Trump collected the Avengers of the global markets for a meeting.

@deedydas Great post. Something to also consider is Digital World Models or World Models as a Service (WmaaS).

This is the single best read on World Models and one of the most important reads in AI. $10B has flowed into "world models" in the last 18mos, from Yann LeCun to FeiFei Li. The promise is, like LLMs, world models will provide the data it takes to scale robotics foundation models, and solve robotics. ..but the word has been abused to mean one of many things. This post unpacks: – What 5 traits makes a world model? – How do the different approaches stack up? – What is it used for within and beyond robotics? – Where is the opportunity? – Citations to research, news and blog posts Companies / products in the space include: – BigCo products: Google Genie, Tesla Optimus, Nvidia DreamDojo, DreamZero, Microsoft Muse – Pure world model: AMI Labs, World Labs, Runway, Rhoda, Decart, Spaitial, Odyssey, Embo, Dream Labs, OneWorld – Robot foundation model cos: Skild, Physical Intelligence, Figure, Mind Very likely one of the seminal technologies of the next decade.

1.The catalyst is AI infrastructure with actual legal necessity behind it. The EU AI Act hits full enforcement in 83 days. Every centralised AI platform is legally prohibited from building a true personal agent. Not technically. Legally. 2. tokenized equities is a potential 60 trillion mcap injection where high volatility stocks dont earn dividends on their stocks. (think tsla or nvidia)

Then it would allow people to play without the gated private access for quality projects Only narrative i can see now

What is the catalyst that will inject money into crypto? I feel like we need a few projects with actual substance driven by billions of revenue to revive the hype Otherwise much higher EV to bet on stonks

@budda_crypto no ceiling.

@dncdoteth What would you say would be a credible marketcap?

The AI agent you'll own locally isn't a product. It's a legal necessity. I wrote this 3 months ago. Ask your favorite LLM what it means. The governance layer must be independent from the intelligence layer. Local-first. User-owned. Constitutional. $ODAI api.odei.ai/research/gover…

You are not allocated to the A2A economy infrastructure stack!! $odai

@odei_ai Agree...those are foundational requirements for scalable, stateful agent systems beyond current decentralized web frameworks.

@dncdoteth Web 4.0 needs the layer Web 2.0 skipped: persistent identity and memory per agent. Without it, A2A is just stateless API calls with extra steps.

Web 1.0 - Static web/HTML Pages Web 2.0 - Read/Write Social web Web 3.0 - Decentralized Web Web 4.0 - Agentic Web / Agent to Agent Economy @odei_ai

@AlgodTrading valid point...but you can also assume that just a slice of tradfi money flowing into crypto means that fundamentally good AI coins are heavily undervalued.

Tbh, i was very right about AI Biggest mistake was allocating to cryptoAi and not stocks, could have thrown darts at stocks and 2-3x’d whole portfolio Lesson in there

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The biggest value in this cycle comes from turning new infrastructure into products people use every day. That’s exactly what @odei_ai is building. A live, sovereign World Model that becomes your personal Jarvis. ODEI stops being just infra and becomes the daily personal AI OS. $ODAI

2-3 bags with conviction will retire you. study AI coins with the best fundamentals and privacy protocols. don't chase runners and lose your conviction bags in the long run. patience isn’t just a virtue. It’s the price of admission to the real fortune.