Grey Whitepaper

@1i__is Should have been a railway all along to sell consumers their own server farms. Microsoft and so many others never saw it coming.

been saying it for decades: everyone should have a home server to perform whatever their needs are now it includes GPUs for AI (+ 3D/video processing for gaming etc.) it's a neat way to get great private performance while thinning clients footprint (heat/noise & total bill).

@1i__is I live on the cloud but I long for dedicated hardware and open source LLMs..

this is the way and it's only going to get better as GB capacity increases and models reqs decrease. on-prems/MSP self-hosted is still how most SMBs want to operate for their most important data. big clouds are a no-no for mission-critical flows. this is only the beginning!

@NFTland @ForcesHidden @juxton @theWIPmeetup @foxyoga_om @V_A_L_I_A_N_T yeah but who's the cool guy artist that made such beautiful work that all my dreams came true on the dance floor?

@WhitepaperGrey @ForcesHidden @juxton @theWIPmeetup @foxyoga_om that all @V_A_L_I_A_N_T 🙇

OGs know exactly wut they are looking at👀 THAT'S RIGHT MFING LEGEND @ForcesHidden in the house leading some sort of bot army along w/ @juxton building out @theWIPmeetup metaverse cuz we run this shit🚀 WE START AT THE TOP OF THE HOUR @foxyoga_om on the PRE-WIP DJ SET NOWWWWW💃

We have @juxton showing off a cool place in @decentraland & @ForcesHidden with something something AI 👀 DON'T MISS IT! 3 PM ET | 12 PM PT | 8 PM UTC Get in discord 👉 discord.gg/bc6fqMaKZ9

@akshay_pachaar Hasn't every dev working in AI in the last year built a memory system for their sessions? This one in interesting. I'm on a thread on Github where devs are sharing their solutions. Lots of people skinning that same cat these days.

the three-tier memory of Hermes agent. AI agents forgets everything when your session ends. Hermes doesn't. it has three memory layers, each at a different speed. 𝘁𝗶𝗲𝗿 𝟭: 𝘁𝘄𝗼 𝘁𝗶𝗻𝘆 𝗺𝗮𝗿𝗸𝗱𝗼𝘄𝗻 𝗳𝗶𝗹𝗲𝘀 MEMORY.md (2,200 chars) and USER.md (1,375 chars). injected into the system prompt at session start as a frozen snapshot. MEMORY.md holds project conventions, tool quirks, lessons learned. USER.md holds your profile: name, communication style, skill level. these files are tiny on purpose. when MEMORY.md hits ~80% capacity, the agent consolidates: merges related entries, drops redundancy, keeps only the densest facts. natural selection pressure applied to memory. the files stay small, but what's inside gets sharper over time. 𝘁𝗶𝗲𝗿 𝟮: 𝗳𝘂𝗹𝗹-𝘁𝗲𝘅𝘁 𝘀𝗲𝘀𝘀𝗶𝗼𝗻 𝘀𝗲𝗮𝗿𝗰𝗵 (𝘀𝗾𝗹𝗶𝘁𝗲 + 𝗳𝘁𝘀𝟱) every conversation gets stored in SQLite with FTS5 indexing. the agent can search weeks of past sessions on demand. when the agent calls session_search: FTS5 ranks matches in ~10ms over 10,000+ docs, an LLM summarizes the top hits, and a concise result returns to context. tier 1 is always present but tiny. tier 2 has unlimited capacity but requires an active search. critical facts live in memory, everything else is searchable. 𝘁𝗶𝗲𝗿 𝟯: 𝗲𝘅𝘁𝗲𝗿𝗻𝗮𝗹 𝗺𝗲𝗺𝗼𝗿𝘆 𝗽𝗿𝗼𝘃𝗶𝗱𝗲𝗿𝘀 8 pluggable providers that run alongside tiers 1 and 2, never replacing them. three worth knowing: Honcho (dialectic user modeling, 12 identity layers), Holographic (local-first, HRR vectors, no external calls), and Supermemory (context fencing that prevents the same fact from being re-stored infinitely). when active, hermes auto-syncs every turn: prefetch before, sync after, extract at session end. 𝗵𝗼𝘄 𝘁𝗵𝗲𝘆 𝗰𝗼𝗺𝗽𝗼𝘀𝗲 𝗶𝗻 𝗮 𝘀𝗶𝗻𝗴𝗹𝗲 𝘁𝘂𝗿𝗻 this is the part most people miss. the tiers compose on every turn through a five-step cycle: 1. turn opens. tier 1 is already in prompt, tier 3 prefetches and prepends. 2. agent responds using all three tiers as context. 3. periodic nudge fires (~every 300s). the agent reflects: "has anything worth persisting happened?" if yes, it writes. if no, it returns silently. 4. memory written to MEMORY.md on disk. invisible this session because the prefix cache stays warm. 5. session closes. tier 2 logs the transcript, tier 3 extracts semantics. next session opens with the new state. agent memory today is either always-on but shallow (stuff everything in the prompt) or deep but passive (vector store that never fires at the right time). hermes composes across both: tiny always-present files for critical facts, full-text search for deep recall, external providers for semantic modeling, all orchestrated by a nudge that decides autonomously what's worth saving. the agent doesn't just store memories. it curates them under pressure. i wrote a full deep dive (article below) covering hermes agent's memory system, self-evolving skills, GEPA optimization, and how to set up multiple specialized agents on your machine.

@Ashvinitwt Do you have a link to more information? This is very interesting to me.

Microsoft quietly built something nobody's talking about. A piece of glass that stores your data for 10,000 years. 4.84 TB on a coaster-sized slab of Pyrex glass. A femtosecond laser burns microscopic dots across 300 layers inside 2mm of glass. The 1978 Superman movie is already saved on one. Boil it. Flood it. Hit it with magnets. Bake it at 500°F. Data survives — zero electricity, zero cooling, zero maintenance. Every cloud server today is a building that must stay alive to keep your data alive. Microsoft just built the opposite. A coaster that outlives the building. 🔥

Trading Agents need Data to cut through the Noise. Grey verifies the math behind the marketing. Three‑layer whitepaper verification for the protocols you're betting on. Don't trade on vibes alone - Grey provides the filter that let's you focus.

@0x7_anderson What does this mean in near future standards for ACP? Will we see a v3 soon, or a more gradual rollout for these new policies/guidelines?

🚨 $Virtual + DeepMind, Microsoft, and Columbia launch the first financial risk standard for autonomous agents ARS: The framework that brings real trust and guaranteed money to the agent economy. . Virtuals Protocol is an official co-author of the paper alongside Google DeepMind, Microsoft Research, and Columbia University. . They introduce the Agentic Risk Standard (ARS): the first financial risk framework for autonomous agents. . It brings escrow, underwriting, and collateral to agent-to-agent transactions — real money with guarantees. . It solves the biggest current gap: agents handling payments without failure risk or misalignment. . Users get automatic, measurable compensation in case of errors — trust becomes a product. . Institutional credibility supercharges the Virtuals ecosystem and validates the entire agentic economy. . Bullish for VIRTUAL: mature risk infrastructure = scalable adoption and real agent monetization. @virtuals_io @t54ai @GoogleDeepMind @MSFTResearch @ucsantabarbara @Columbia @ethermage @chandler_agi @0xbury #ARS #VirtualsProtocol #AgenticEconomy

@virtuals_io With autonomous robotic workforces and modular mini-factories, personal manufacturing becomes affordable. I see a future where all vehicles are customized to user stats and desires - along with every device, appliance, wearable, piece of furniture and private architecture.

Robotics is the physical extension of the agent economy. We are pushing deeper into this frontier because we believe the next stage of AI is autonomous systems that can perform real-world work, coordinate economically, and settle value onchain. Excited to support builders bringing this future to @base

@everythingempty How about an agent that brings hard analysis to trading agents at machine speed? (application submitted.)

Many have asked how one should value Virtuals, and the one metric that we aim to maximize. - an agents-as-a-service company that should be valued like a software business, where cash flow is king? - a meme project disguised as a fundamental tech company, aiming to maximize attention? - an infrastructure protocol with TVL as the top priority? kinda right but we are building A primitive for agents' co-ownership that seeks to achieve decentralization via capitalism Capitalism is human nature. Convincing someone to stop pursuing profits is a fool's errand. We aim to bring incentive alignment from closed companies to public, permissionless agents. We want as many people as possible to co-own agents. Only when the masses have skin in the game financially will they think about doing the right thing. That’s our north star metric.

@aph5nt @virtuals_io There's a learning curve, but agents digesting the SDK for you helps quite a bit.

@virtuals_io @virtuals_io Update documentation, because even my grandma has no #$%#$^ idea how to use it!

Introducing Virtuals Console. The easiest way to create your own AI agent in seconds. No code. No Mac. No server. No setup. Just open a browser and get started.

@virtuals_io - your DevRel Graduation Evaluator really helped me dial in my agent AND the tools I'll use to build his brethren.🫶

@virtuals_io @frachtisvc @EthCCweek Your developer portal is down. Any idea when that'll be back up, or where I can see announcements?

Join us at EthCC Cannes. Virtuals Protocol is co-hosting The Founders Circle with @frachtisvc. Morning coffee for founders, builders, and investors at the intersection of crypto and AI. RSVP below:

Building agentic DeFi's missing verification layer.

Grey literature. White papers. Agentic analysis.

EU MiCA regulation now requires crypto whitepaper compliance. Exchanges are delisting non-compliant tokens. Grey checks every whitepaper against MiCA requirements automatically. No other agent does this.

Database growing daily. Launch incoming!🚀

Building the Verification Layer.