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π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯𝐟
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π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“

@TheCrypticWolf1

Author of an Amazon #1 Best Seller | Crypto Investor | Finding Undiscovered & Undervalued Projects | Market Insights | Onchain Investigator | AMB: @nonossystems

987 Following22.6K Followers82.2K Posts
  2. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    This $AUKI demo looks like a simple no code interface for connecting cameras, AI, spatial data, and other components. You’re seeing different peers and components connected through spatial data pipelines, a camera feeding a semantic detector, with spatial data then being used for occupancy mapping. A robot doesn’t necessarily need to handle every part of a task by itself. One device can capture the data, another node can process it, and nother system can use the result within its spatial environment. That’s the idea behind composable spatial pipelines. The posemesh makes this especially interesting for physical AI because machines need more than intelligence. They need a way to exchange information about the physical world. The future of robotics needs infrastructure that allows machines to coordinate and share spatial information in the real world. $AUKI is building exactly that.
    Auki @Auki
    Preview: no-code building of spatial data pipelines β€” drag and drop or ask your agent to do it. Example: Send video from robot A to node B which blurs people, then to node C running CV, then drop it in robot D's map.
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  3. Aukiβœ“@Auki
    Preview: no-code building of spatial data pipelines β€” drag and drop or ask your agent to do it. Example: Send video from robot A to node B which blurs people, then to node C running CV, then drop it in robot D's map.
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    111431.6K
  4. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    $IXS had a good thing going. It was in my top 10 for RWAs. The supply is what attracted me originally. Now they're diluting the supply. Anytime I've witnessed a migration the project usually fails. For these reasons. I'm out.
    IXS @IxsFinance
    We're moving to Robinhood Chain. To enable the next phase of IXS. For two years we've weighed where IXS should live to best suit future plans. This year, together with our partners, we chose Robinhood Chain: the chain Robinhood built for tokenized assets. Many of our biggest plans are with partners building on Robinhood Chain too and this move aligns IXS with them. Why Robinhood Chain? Robinhood has named tokenized stocks, pre IPO assets and institutional yield products as the defining opportunity in RWA And it is directing capital, infrastructure and users to that thesis on its chain. We are moving to where that is happening. It is where Robinhood is putting stocks onchain, and where it is giving its 28 million customers AI agents that trade and manage money. More than 150,000 customers had opened agentic accounts by late September, and agents were using Robinhood’s tools about 30 million times a day. Every agent needs somewhere to hold idle balances and earn on them. That is what IXS vaults are built for. Where this goes: a regulated onchain market for real world assets. Funds, credit and tokenized stocks in one place, where you can hold them, earn on them, and borrow & lend against them. That is what we are building towards with our partners on Robinhood Chain, and it needs one IXS in one place. Today it doesn't. IXS is split across Ethereum, Base and Polygon, three separate markets. The migration brings it into one native token on Robinhood Chain. Setting up the token for what's coming. Live today: > A $10M Pre-IPO vault for institutional investors. $10M in added TVL on day one. > 25% of vault fees now buy and burn IXS, up from 20%. What comes next: > AI-agent vaults on Robinhood Chain > New RWA vaults, built with partners on the chain > Partner launches, announced as each one goes live The token: 1 IXS on Ethereum = 10 IXS on Robinhood Chain. The symbol stays IXS. Holders get 72% of a fixed 2.5B supply. The rest is a recapitalisation for deeper liquidity and ecosystem growth, needed for what's planned: to attract TVL and investors and give token holders a better venue to trade. Migration runs 27 Oct 12:00 UTC to 21 Dec 23:59 UTC. After that, IXS on Ethereum, Base and Polygon is retired. New IXS contract: 0xDcD7FaCE6A1d0bDD0665Ea1B0842fc9CE797862b Migrate here, and only here: IXS is not affiliated with Robinhood. Our Pre-IPO vault is open to eligible institutional investors only.
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  5. IXSβœ“@IxsFinance
    We're moving to Robinhood Chain. To enable the next phase of IXS. For two years we've weighed where IXS should live to best suit future plans. This year, together with our partners, we chose Robinhood Chain: the chain Robinhood built for tokenized assets. Many of our biggest plans are with partners building on Robinhood Chain too and this move aligns IXS with them. Why Robinhood Chain? Robinhood has named tokenized stocks, pre IPO assets and institutional yield products as the defining opportunity in RWA And it is directing capital, infrastructure and users to that thesis on its chain. We are moving to where that is happening. It is where Robinhood is putting stocks onchain, and where it is giving its 28 million customers AI agents that trade and manage money. More than 150,000 customers had opened agentic accounts by late September, and agents were using Robinhood’s tools about 30 million times a day. Every agent needs somewhere to hold idle balances and earn on them. That is what IXS vaults are built for. Where this goes: a regulated onchain market for real world assets. Funds, credit and tokenized stocks in one place, where you can hold them, earn on them, and borrow & lend against them. That is what we are building towards with our partners on Robinhood Chain, and it needs one IXS in one place. Today it doesn't. IXS is split across Ethereum, Base and Polygon, three separate markets. The migration brings it into one native token on Robinhood Chain. Setting up the token for what's coming. Live today: > A $10M Pre-IPO vault for institutional investors. $10M in added TVL on day one. > 25% of vault fees now buy and burn IXS, up from 20%. What comes next: > AI-agent vaults on Robinhood Chain > New RWA vaults, built with partners on the chain > Partner launches, announced as each one goes live The token: 1 IXS on Ethereum = 10 IXS on Robinhood Chain. The symbol stays IXS. Holders get 72% of a fixed 2.5B supply. The rest is a recapitalisation for deeper liquidity and ecosystem growth, needed for what's planned: to attract TVL and investors and give token holders a better venue to trade. Migration runs 27 Oct 12:00 UTC to 21 Dec 23:59 UTC. After that, IXS on Ethereum, Base and Polygon is retired. New IXS contract: 0xDcD7FaCE6A1d0bDD0665Ea1B0842fc9CE797862b Migrate here, and only here: IXS is not affiliated with Robinhood. Our Pre-IPO vault is open to eligible institutional investors only.
    Download
    663620030.5K
  6. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    $SLC is building the infrastructure for the next generation of AI. Through its DePIN network, Silencio is turning real world contributors into a global source of environmental and location data, while its Voice AI side is building a massive, consent based speech data layer for the AI and robotics economy. Silencio is building something worth watching and I'm looking forward to the upcoming quarterly update.
    Silencio | Voice Data for AI @silencioNetwork
    Exciting days ahead. Stay tuned πŸ‘€
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  8. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    This is actually a pretty big deal for $PLI and the $XDC Network. Plugin RPCaaS becoming the default RPC for the XDC Post-Quantum Onchain Communicator shows how Plugin is becoming more deeply integrated into the infrastructure being built around XDC. @GoPlugin already provides decentralized oracle and data feed infrastructure, bringing real world data onchain. Now its RPC infrastructure is helping applications communicate with XDC. What really caught my attention is the post-quantum side. @XDCNetwork is actively researching and planning its transition toward post-quantum security, and infrastructure like this will be important as the ecosystem evolves. Seeing Plugin’s oracle technology, data feeds and RPC infrastructure developing alongside XDC’s post-quantum work is exciting. These are the infrastructure pieces that may not always get the attention they deserve, but they can become incredibly important as adoption grows. Bullish on $PLI.
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    114541.8K
  10. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯𝐟
    RT @TheCrypticWolf1: Crypto is a generational wealth opportunity. I focus on utility, uniqueness, and projects solving real world problems. Here are 10 projects I believe will be extremely successful: $SLC @silencioNetwork $PEAQ @peaq $AUKI @Auki $DMTR @dimitratech $PLI @GoPlugin $NATIX @NATIXNetwork $ZBCN @Zebec_HQ $VELO @veloprotocol $SHX @strongholdpay $DEXTF @Memento_Bc AI, Robotics, DePIN, Privacy, and PayFi will be among the top performing categories.
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  11. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    $NATIX is building something I think will become incredibly important for autonomous machines, access to data and real world footage. Alireza’s point about Munich vs. Jakarta goes much deeper than autonomous driving. A near miss in Munich can teach a model something completely different from a near miss in Jakarta. Roads are different, traffic is different, weather is different and most importantly people behave differently. Some of the most valuable footage isn't when everything goes right, it's when something almost goes wrong. Those moments are rare, difficult to collect and incredibly useful for teaching machines how the real world actually behaves. @NATIXNetwork is a decentralized camera network can capture real world conditions at scale and turn that footage into data that can help train autonomous systems, simulations and physical AI. This goes far beyond vehicles too. Robots, drones, delivery systems and other autonomous machines will all need both massive amounts of data and footage to operate safely around us. $NATIX is building the network to help give them both.
    Alireza Ghods @AlirezaGhods2
    The industry spent a decade arguing about lidar vs cameras. The next argument is quieter: who owns footage of the moments that almost went wrong. A near miss in Munich teaches a model very little about a near miss in Jakarta. Driving is local. Most training data isn’t.
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  12. Alireza Ghods@AlirezaGhods2
    The industry spent a decade arguing about lidar vs cameras. The next argument is quieter: who owns footage of the moments that almost went wrong. A near miss in Munich teaches a model very little about a near miss in Jakarta. Driving is local. Most training data isn’t.
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  14. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    $DMTR is more than a ticker to me, it represents an agricultural infrastructure story I think deserves attention. I watched Dimitra’s conversation with Forum Kakao Aceh, and the message was clear, after floods destroyed homes, trees and future harvests, Aceh’s cocoa community is still looking forward. Their goal? Make Aceh cocoa the best in Sumatra. That takes more than planting. It takes knowledge, traceability, farmer mapping, environmental data and stronger connections between farmers, cooperatives, governments and buyers. This is where @dimitratech can make a real difference. Dimitra's Connected Farmer can help digitize farm boundaries, activities, harvests, photos and field records, turning knowledge traditionally passed from generation to generation into documented, usable data. That data can support traceability, EUDR readiness, deforestation risk checks and better supplychain visibility. The potential goes further, reliable data can become a foundation for ESG, carbon/MRV and other future programs, depending on verification and project requirements. The goal is preserving knowledge, strengthening farmers, opening market opportunities and making sure communities aren’t left behind. Better data, better connections, and a stronger future for Aceh cocoa. That’s the Dimitra story I want to help amplify. Fact: Agriculture affects us all. $DMTR has built solutions for the agriculture industry and is helping solve problems many of us didn't even know existed.
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    26401.3K
  15. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯𝐟
    RT @TheCrypticWolf1: $SLC can bridge the gap. Take Filipino accented English. Leading speech recognition systems had word error rates ranging from 10.8% all the way to 44.7%. Same accent, same test, huge difference in performance. That’s the problem Silencio is helping solve. Voice AI doesn’t live in clean benchmark datasets. It lives in real conversations with different accents, languages, devices, environments and ways of speaking. If a model can’t understand the people using it, a great benchmark score doesn’t mean much. Silencio is building something incredibly important: a real world speech data layer that helps AI learn how people actually speak. Millions of contributors, hundreds of languages, real voices, real environments, verified metadata and consent. Silencio has the potential to become one of the leading voice AI data providers.
    Silencio | Voice Data for AI @silencioNetwork
    Filipino-accented English. One public benchmark. Leading ASR systems: 10.8% to 44.7% word error rate. Same accent, same test. Choose your model on the accents your users have. What we heard at Interspeech 2026:
    0501.3K
  16. Silencio | Voice Data for AIβœ“@silencioNetwork
    Filipino-accented English. One public benchmark. Leading ASR systems: 10.8% to 44.7% word error rate. Same accent, same test. Choose your model on the accents your users have. What we heard at Interspeech 2026:
    12221437.4K
  17. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    $NOX is building something that goes way beyond another privacy focused app. We are looking at a new marketplace that gives us a look at what the OS is actually trying to accomplish. Apps get their own isolated environments instead of having broad access to your files. They run in memory, and those environments are cleared when you restart. That means less persistent data and a much smaller attack surface. The networking side is just as interesting. Chat and wallet apps can use privacy networks, while local AI runs directly on your machine instead of sending your prompts to a centralized server. Then NØNOS checks the software before it even installs it, verifying package and publisher signatures and stopping anything that fails the integrity checks. That stands out to me and it should stand out to you as well. Privacy and security are extremely important. Privacy, isolation, software verification, and local computing aren’t separate features here. They’re part of the OS design. As NØNOS continues to execute on their vision, future users won’t have to choose between convenience and privacy. They'll have an OS where privacy is the foundation. We are very early on the $NOX vision.
    NØNOS @nonossystems
    On most computers, any app you install can read your files. On NØNOS, every app gets a sealed room of its own and your files are never in it. An early look at the new Marketplace, coming in this week release.
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  18. NØNOSβœ“@nonossystems
    On most computers, any app you install can read your files. On NØNOS, every app gets a sealed room of its own and your files are never in it. An early look at the new Marketplace, coming in this week release.
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    519632.4K
  19. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    $AUKI is showing what happens when you give AI spatial context from the physical world. Bring your own model (Qwen running on Jetson Thor here) and give it the Auki spatial harness, and suddenly it can do more than generate text. In this demo, Qwen acts as a scene assistant, querying the environment to identify exactly where the ketchup is, down to the fixture, shelf, and 3D coordinates, and then visualizing the result. Any model can leverage @CactusXR data, spatio semantic data, or other domain specific data. That gives AI a way to process not just information, but where things are and how they relate to the physical environment. Auki is building the infrastructure that connects AI to a shared, machine readable understanding of physical space. That can extend far beyond retail to robots, warehouses, logistics, manufacturing, smart glasses, and other devices. The model provides the intelligence. Auki provides the spatial context that lets it understand where things are and how they relate to the physical world. These @Auki demos continue to be very insightful into what they're building and honestly I can see this technology being used by massive retailers around the globe, like @Walmart @Target. I'm extremely bullish on what $AUKI is building.
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    34451.3K
  21. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    This is exactly why I’m paying attention to $SLC. Coin Bureau highlights Block’s new Dessa model speech to speech AI that can listen and respond naturally, with emotion, timing, sarcasm, laughter, etc. Many just realized how important Voice AI is. The next generation of AI will depend heavily on the quality and diversity of the voice data behind it. This is where @silencioNetwork comes into play and it's imo going to play an extremely important role. Big Tech can build incredible voice models, but collecting high quality, diverse, speech data across languages, accents and dialects is a massive scalability challenge. Silencio has been building the missing data layer and solved the scalability. 2.5M+ users contributing real world data creates something incredibly interesting, a decentralized network capable of collecting voice and environmental data on a global scale. Instead of a handful of companies controlling the entire data pipeline, Silencio is building an ecosystem where the people generating the data can participate in the network that monetizes it. Look at where AI is heading: From Text to multimodal to voice native AI. As AI becomes more conversational and more human, the demand for diverse voice datasets should only increase. Silencio is positioning itself where DePIN, voice data and AI all come together. Dessa is a glimpse of where voice AI is going. Silencio is building the data infrastructure AI needs to understand how the rest of the world actually speaks. BULLISH ON $SLC.
    Coin Bureau @coinbureau
    🚨This is genuinely WILD, you can now talk to an AI like it's a HUMAN. Twitter founder Jack Dorsey's Block just unveiled Dessa, a speech-to-speech model that learned to talk by listening, with no text at all. It listens and talks at the same time, with emotion, laughing mid-sentence, hearing sarcasm and sighs.
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  22. Coin Bureauβœ“@coinbureau
    🚨This is genuinely WILD, you can now talk to an AI like it's a HUMAN. Twitter founder Jack Dorsey's Block just unveiled Dessa, a speech-to-speech model that learned to talk by listening, with no text at all. It listens and talks at the same time, with emotion, laughing mid-sentence, hearing sarcasm and sighs.
    Download
    599878781.7K
  24. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    $AUKI is showing that this is WAY bigger than a Wi-Fi heatmap. Scentinel is demonstrating what happens when a robot can autonomously turn conditions in the physical environment into machine-readable, spatial data. β€’ 0% packet loss β€’ 48/48 survey points β€’ -78 to -41 dBm signal range β€’ Sub-ms to low-ms latency That spatial context matters for teleoperation, autonomous navigation, robot deployment, and fleet reliability. Now imagine that same spatial intelligence being available across more of the Physical AI ecosystem. Robots, cameras, phones, sensors, smart glasses, and AI agents. Physical AI doesn't just need intelligence, it needs context: Where am I? What's around me? Where can I operate reliably? What changed since the last time? What has another machine already observed? The goal isn't simply to make individual robots smarter, it's to build infrastructure that allows machines to build, share, and use a persistent understanding of the physical world. We're moving from machines that simply operate in physical spaces to machines that can understand those spaces. The physical world is becoming machine readable, and @Auki is building the infrastructure that makes that possible.
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  25. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    If you haven't been paying attention to $SLC, you should be. The market is down, but @silencioNetwork is in the green. Up nearly 8X since July low. Silencio is building the noise and voice AI data layer. This layer will help train AI models and robots. $SLC = Ears for the next generation of AI (Super Intelligence) and Robotics. Targeting $0.00055-$0.0025 on the short to mid term. With long term targets of $0.01-$0.10+
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    1314722.9K
  27. π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯πŸβœ“@TheCrypticWolf1
    π“π‘πžπ‚π«π²π©π­π’πœπ–π¨π₯𝐟
    RT @coinbureau: ⚠️DATA: Shipping addresses of nearly 120,000 crypto hardware wallet buyers have been exposed in 2026. Keystone just became the FOURTH wallet maker hit by a customer data breach this year. Your keys stay offline with a hardware wallet. Your name and address are held by whoever sold and shipped it. Ledger in January, with names, addresses and orders exposed through its e-commerce partner Global-e Trezor in August, with nearly 80,000 customers' addresses exposed through its shipping partner SafePal in August, with 39,798 customers' addresses exposed through an order-tracking plug-in Trezor again in September, when fake security alerts went to about 347,000 newsletter subscribers Keystone this week, with names, addresses and orders exposed Ledger and Keystone haven't said how many customers were affected. Back in 2020, Ledger's leak put about 1 MILLION emails and 272,000 home addresses online. None of the breaches exposed recovery phrases or private keys. Did you use your real home address when you ordered yours?
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