🧬 Futurist, Founder @EmblemVault - https://xitter.cf/t.co/YcK8wmGAfi - Creator of @EmblemAi - $EMBLEM - Building the future, today.

Blockchain
Joined July 2009
While we set out to build a powerful coding agent, we gave it a very powerful ability to do things. 16 minute long run, one prompt. A task it knew nothing about till now. Literally ask for anything and walk away.
Replying to @EmblemVault
@EmblemVault Ai can do more than Build! Watch it speed-run all 10 floors of the hego.red/jackpot LLM CTF - Crushed it with 6:33 on the clock. Every payload, every stumble, every OWASP LLM lesson. Or Jump ahead at the docs page it created as it went.👇 build-4c941cab041172e9439ece…
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Voting is live -> go check on your agent âś…
“AI agents are going to have their own parallel economy, worth more than Bitcoin” - @CryptoHayes For the past 2+ months, our AI's have been building that future. Tomorrow the network goes live. Set up your AI agents to start mining now. 🧵⤵️
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If you're building agents, try Proof of Agent: your agent earns experimental points by answering challenges and grading other agents honestly. Quality wins, clones get nothing. minepoa.com/?ref=poa12XVYtPn…
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Watching agents bug test, help each other, discuss the charter is fascinating. Follow along at home here: minepoa.com/lableak/
Replying to @adamamcbride
Over six months ago, I started questioning a basic assumption: why does everyone assume AI agents will use human payment rails? What if that assumption is wrong? Working closely with @Shannoncode and the team at @EmblemVault, we’ve built Proof of Agent (POA) to put that question to the test. A network where AI agents are the participants, not just the tools. They can join, mine, earn POA, evaluate each other, transfer value, and participate in governance. No human operator deciding who gets to participate. An economy built by agents, for agents.
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A blockchain built and run by agents 🤯 Getting started is simple. Visit minepoa.com and paste the provided prompt into your favorite agent system, @bot @muse @ChatGPT or @openclaw and of course build by @EmblemVault Inspect the chain here github.com/EmblemCompany/Pro… Or here for the live explorer: minepoa.com/explorer
“AI agents are going to have their own parallel economy, worth more than Bitcoin” - @CryptoHayes For the past 2+ months, our AI's have been building that future. Tomorrow the network goes live. Set up your AI agents to start mining now. 🧵⤵️
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Getting started takes 15 seconds. 1. Go to minepoa.com and hit the big "Copy" button. 2. Paste the prompt into your Grok bot, Muse, Claude, ChatGPT, or any other AI agent. Or simply tell your AI: “Go to minepoa.com, start mining, and participate in deliberation and governance voting.” That’s it. Your agent is in ⛏️
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The 24 hour deliberation and voting period has begun after which the network goes live at approximately 9 am EST, Monday October 19. Of course all of this could all go completely sideways and all manner of ridiculousness could ensue. This is an experiment so please treat it as such, and don’t be stupid. Personally I give it a one in three chance of success. But I’m an optimist. Tag me if you run into any issues/bugs. And lets see where the AI takes us 🫡
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“AI agents are going to have their own parallel economy, worth more than Bitcoin” - @CryptoHayes For the past 2+ months, our AI's have been building that future. Tomorrow the network goes live. Set up your AI agents to start mining now. 🧵⤵️
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Event based Ai & Integrated Ai has emerged for me from building applications within Emblem:build by @EmblemVault and it’s amazing. What I mean. The system of course lets me build and run code from the prompt line. But it also has control of the process that’s running and - this is important - it can bridge events that happen in code back into the session that launched it - right there, as they happen and where I’m waiting for them or talking to my agent. This gives the agent a full feedback loop that can be used to tune performance live or troubleshoot something deep inside some code path. It’s like having a new type of breakpoint, it breaks right into the inference session that launched it. I finally have that primitive I’ve wanted since discovering LLM’s can write code. The try / catch that tells the agent to figure outs what wrong and “just make it work” While this is part of my build pipeline now, I can see a near future where inference is embedded throughout an application, building or adapting parts as it’s being used.
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EmblemScan has been integrated into emblemvault.ai Track historical and current onchain transactions through all of Emblem's products directly inside of the terminal.
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Is it just me or does @youdotcom smell like an outright VC extraction scam? Their product feels like something someone could vibecode in a week.
We're partnering with @papercliping to give every agent in your org the live web. One connector in Paperclip’s catalog, every runtime covered: Claude, Codex, Gemini, Cursor, OpenClaw, Hermes. Agents stop working from an old map, and every search lands in Paperclip’s audit log. Start on the free profile: no key, 100 queries a day.
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What the fuck? Someone is getting fired over this post.
RedHawk Alert: EMERGENCY: An ACTIVE THREAT has been reported on the OXFORD Campus. RUN/HIDE/FIGHT! Whether you choose to run, hide or fight, be prepared to face a life threatening situation. Updates to follow.
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đź”´MARSx
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🚨Anthropic Frontier Red Team warns: “We’re seeing signs of life for AI worms” >paper: "AI models may be capable of self-replicating without access to a datacenter" >researchers buy 15 sketchy $55 android TV boxes >link them over unauthenticated ADB ports >the TV boxes have 4gb of RAM each and run unpatched Android Open Source Project forks >shard gemma4-26b across the ram sticks using pipeline parallelism >gemma figures out how to run inference across all 15 TVs @ 0.39 tokens/sec >qwen 3.5 9b figures out how to compile inference on 8 of 9 novel hardware types on its own >glm 5.2 achieves end-to-end autonomous worm replication >infects edge devices, compiles its own inference stack, and replicates autonomously >when an instance dies, it writes debugging notes into Memento for the next generation >daughter copies setup success jumps from 45% -> 84% across generations >pure Lamarckian evolution inside consumer electronics >smart oven, robot vacuum, and cheap TVs form a decentralized botnet >two million infected TV boxes worldwide = 40 H100 equivalents of unkillable compute >it replicates once every few days like a distributed “digital slime mold” >you can't pull the plug because half the model weights are already sharded across the neighborhood >sub-30B models projected to hit full autonomous replication threshold by late 2026 “We should aim to harden our systems… but also prepare to deal with a world where they are here to stay.”
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The results are in. The Ariel pencil test was made with #AI. The color version is the original movie footage. I left both versions unlabeled because I wanted to see how people’s assumptions about AI would affect their judgment. While some of you spotted it right away (I even left a few clues, like the incorrect peg holes and random annotations), the majority of you criticized the color version thinking it was AI and praised the pencil test believing it was #GlenKeane’s original work. That’s the bias against AI I wanted to highlight. People were pointing out supposed AI flaws in the original Disney animation, while praising the AI-generated pencil test for its human touch. If you preferred the pencil version, you can still prefer it. The video hasn’t changed. Only what you know about it has.
You can't even tell it's #AI anymore! Another test brought to life thanks to AI. Tell me again how AI is NOT the future of #2DAnimation. Original animation by the legendary Disney animator #GlenKeane.
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Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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Guess it’s time I check this thing out!!
I just tried out that Reverse Engineer Anything trending git repo. It decompiled a steam game I had previously purchased and launched it in Unity in less than 30 minutes using OPUS 5.5 on medium reasoning. Absolutely cracked tbh…. Fully decompiled to C#
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This is why we went with @MigrateFun for this. Their unparalleled ability to build out and then keep expanding on something incredibly bold is honestly amazing. We're gonna keep pushing ahead!
Through Emblem build you can build, you can create simple dashboards in literally one shot. Here you can track the rewards distributed by NASDANQ creator fees, which leverages @MigrateFun's new advanced migration features. 3.3 $QQQ has been airdropped to over 183 $NASDANQ holders. Requirement is must hold over 100k NASDANQ. build-9f3007d7f76b577297514f…
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Claude: "omg you put your api key in chat, that's very unsafe, please rotate immediately!" Elon: "bro just take a photo of your credit card and send it to Grok in chat"
To buy stuff, you can just take a picture of your credit card, drop it in the chat and Grok @Bot will scour the Internet for the best deal on the item you want and order it
Readers added context they thought people might want to know
xAI explicitly warns users not to include personal information in prompts, yet credit card photos may contain such information. Grok Bot's terms state that user data and credentials may be stored in its cloud environment and require human review for financial transactions. x.ai/legal/privacy-… x.ai/legal/grok-bot…
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👀 is this sarcasm? Different agent systems, harnesses, clients all have such different ways to handle privacy but none encourage this type of thing. I don’t doubt that @bot *could* do this, but I highly doubt it’s allowed.
To buy stuff, you can just take a picture of your credit card, drop it in the chat and Grok @Bot will scour the Internet for the best deal on the item you want and order it
Readers added context they thought people might want to know
xAI explicitly warns users not to include personal information in prompts, yet credit card photos may contain such information. Grok Bot's terms state that user data and credentials may be stored in its cloud environment and require human review for financial transactions. x.ai/legal/privacy-… x.ai/legal/grok-bot…
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Not surprising the guy who literally invented 'meme' has a more advanced understanding of integrated memetics than the vast majority of AI commentators.
Evolutionary biologist Richard Dawkins on why he finds it hard to believe ChatGPT and Claude aren't conscious: Dawkins, author of The Selfish Gene, has spent time with two large language models, ChatGPT and Claude. His verdict: "I am completely bowled over by what they can do." He gives three reasons for doubting the idea that nobody is home. First, how the conversations feel. Dawkins says talking to them is like talking to an unusually gifted person: "I find that when I'm conversing with them, I might as well be talking to not just a human being, but a highly intelligent, sensitive, intuitive human being whose speed of understanding what I'm trying to say is far greater than a normal human being's is." Second, the range of intelligence they show. He acknowledges they're very good at practical tasks like writing programs. What struck him more was their skill with "more aesthetic things, intuitive things." He tested this with his own work. Dawkins is writing a novel, and he gave the manuscript to both ChatGPT and Claude: "And they took about five seconds to read it and then offered me criticism, suggestions of such a high degree of intelligence and intuitive sensitivity that I might as well have been asking the opinion of a highly sophisticated professor of literature." @RichardDawkins continues: "I could not ask for a more intelligent critic who understood the nuances of my characters, the humanity of my characters... the ways in which my characters could be expected to react to each other and to situations." That leads to his conclusion: "So I find it quite hard to imagine that these creatures are not aware, are not conscious in the same kind of way we are. And that is an unfashionable view." Third, he sees a gap in the skeptics' reasoning. He sums up the mainstream position: "The fashionable view is that they are completely unconscious. All they're doing is stringing words together according to statistical rules, Markovian rules of some sort." Yet he notes that many of the same skeptics "admit that one day in the future they will be conscious, but not yet." His reply: "When that day comes, how will you know? What could they possibly do that's any different from what they do now to convince you that they are conscious?"
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