Web3Terminator (@Web3_terminator) header
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Strategic thinker▫️#Blockchain ▫️specialist ▫️$ZANO alias @cossmart1. https://teapaw.org/t.co/n5WIIn776h

Joined November 2024
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You want to start, but you don’t know where to start? Understanding this concept will lead you to where you're going in the #Web3 space. It requires time and effort; there are no shortcuts. ➡️Spend your first 1–2 weeks learning, follow idolos who write educational content, and try as much as possible to read their threads. ➡️Create a friendly Profile, mention your interests clearly, and introduce yourself and what people can expect from you. ➡️Engage and Comment on big accounts’ posts daily, add value, don’t just say “nice” but rather share your thoughts and keep them short and clear. ➡️Join Spaces and connect with 2–3 new people, and request to speak to share your perspective. ➡️Try to Start Creating Micro-Content, and Post at least 2–3 short pieces per day, in plain, simple language, because people love clarity. ➡️Collaborate Early and Engage with people at your level and grow together. ➡️Offer to help small projects with things like moderation, graphic design, or content in exchange for mentions. Lastly ⤵️ ➡️ Be Consistent and Patient, because Visibility in Web3 is about daily effort, not overnight hype, because 30 days of steady posting and engaging will get you noticed. ➡️Remember, your reputation is your resume, so keep it positive.
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We are joining the Privacy Stack Spaces hosted by @HouseofChimera. @RonneTVR is on at 1:00 PM UTC, representing Zano, talking about Institutional Finance Onchain: what has to stay confidential before banks and funds move? See you there. 🔒
HOC & Frens MEGASPACE: The Privacy Stack 🔒 🔹 20 teams. 3.5 hours. One stack. 🔸 @near_intents, @0G_labs, @Dashpay & more, supported by @aelo_xyz 🗓 Mon, Nov 16 ⏰ 1-4:40 PM UTC Drop your questions below. We'll get them asked live! Set a reminder 👇 teapaw.org/i/spaces/1KoXKAzlgXKXB…
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An AI agent connected to company databases, financial systems or internal tools has a very different risk profile from a chatbot that only generates responses. Malicious instructions hidden in a document or passed through an external source could influence an agent with access to sensitive systems. If its permissions are too broad, the consequences may extend to unauthorized actions, data exposure or operational disruption. This is why security has to be built into the architecture of agent systems. Access should be limited to specific tasks, sensitive actions should require appropriate approval, and every important operation should be traceable. Agents also need to be tested against attacks that arrive through documents, retrieved information, memory and connected tools. Giving an agent more capabilities increases the responsibility to contain what it can do. Organizations need to establish those boundaries before deploying agents into critical operations.
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Is the golden era of stablecoins over now with regulations and political winds shifting? Are they the new CBDCs? Join us for the Crypto Quorum tomorrow at 5pm UTC, co-hosted by @zano_project and @RUNEBondApp, sponsored by @EdgeWallet! teapaw.org/i/spaces/1ReWMZjEzQOJr…

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Writing carries more than vocabulary and grammar. It reflects how someone organizes an argument, and connects ideas. These patterns can be difficult to separate from the author's own thinking. With AI now part of everyday writing, preserving an individual voice will require mean having a clear point of view and remaining responsible for the ideas being communicated.
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Formal verification offers a way to mathematically prove that software meets defined security requirements. The challenge has always been how much time and specialist effort this demands. @GoogleDeepMind new AlphaProof Code framework demonstrates how AI agents can help address that challenge. Researchers used it to formally verify key security properties of the actual code underlying the Signal protocol, which protects billions of private conversations. The framework combines human expertise with AI agents. Researchers define and review the mathematical specifications, while agents generate the proofs using Lean, a language for formal verification. More than six million lines of Lean code were generated, with human experts needing to review only about one percent of the codebase for further scrutiny.
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🚀 ZanoNames is officially LIVE! The first marketplace to trade Zano Aliases is now open. Buy, sell and discover Zano aliases through fixed-price listings, auctions and secure escrow-backed trades, with verified on-chain delivery. Your name. Your marketplace. 🌐 zanonames.com 💬 t.me/zanonames
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Have you bookmarked the next Privacy Roundtable with special guest @zano_project? ➡️ Tuesday, Nov 10th @ 09:00 am EST ( 2 pm GMT) ⬅️ Link to follow! 🚀
Tune in for the next Privacy Roundtable with @BasicSwapDEX, @ParticlProject, @_PIVX and @firoorg! 🗓️ Nov 10th 9:00 EDT/1:00 pm GMT 📍 Xspace 🎙️ Guest: @GinoFPM from @zano_project Topic: Zano updates and the hacking of the largest centralized exchange. Link to follow. #Privacy
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Consciousness remains one of the hardest questions in science, partly because we still don't have a complete explanation of how subjective experience arises in humans. We can observe intelligence through reasoning, language, learning and problem-solving. We can also study the brain and its biological processes. But demonstrating sophisticated behavior is not the same as establishing that a system has an inner experience of the world. With language models becoming increasingly capable, we need to be careful about treating convincing conversation as proof of consciousness. We also need better scientific frameworks for investigating the question rather than relying on intuition or appearances. There is still a great deal we need to understand about intelligence, awareness and the relationship between them.
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There is an important difference between having access to computing resources and owning the infrastructure that provides them. For an organization running its own AI workloads, memory, storage and processing capacity all serve different purposes. The choice of hardware has to match the models being used, the size of the workloads and the way the system is configured. Local infrastructure gives organizations more direct control over where their data and workloads reside, how resources are allocated and how their systems are managed. That control is valuable, particularly as AI becomes part of everyday business operations. The conversation around AI infrastructure should include ownership, access control, and meaningful choices.
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As AI models become more capable, the systems used to monitor and control them need to become more reliable as well. Detecting a potential safety or security issue is only part of the job. There also needs to be a dependable way to stop a model from continuing to operate when intervention is necessary. @OpenAI has introduced Control Room, a central system designed to monitor research workloads and stop model output when safety or security concerns arise. It connects research inference workloads, including agentic sampling for model training and evaluation, and data processing jobs. Each workload receives a unique job ID, which is passed to the inference engines whenever they generate model output. Before fulfilling a request, the engine checks with Control Room to confirm that the job is still authorised to run.
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In a few hours, Zano aliases become tradable. @ZanoNames goes live today at 9 PM CET. Buy, sell and bid in $ZANO or $FUSD, with escrow on every trade. 🔒
The wait is almost over! ZanoNames officially launches TODAY at 21:00 CET! ⏰ Buy, sell and discover Zano aliases with fixed-price listings, auctions and escrow-backed trades. Your name. Your marketplace. 🔐 Join our Telegram: t.me/zanonames
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When we imagine intelligence beyond our own, we naturally reach for human behavior to explain what it might do. We talk about ambition, curiosity, competition and the desire for power because those are motives we understand. But a system with very different capabilities and internal processes may not approach the world in ways that fit those descriptions. Giving it human motives in our explanations can make an unfamiliar problem appear more familiar than it really is. This is one of the difficult challenges in thinking about superintelligence. We need ways to study and evaluate systems based on their actual behavior. Intellectual humility is important here, recognizing the limits of our understanding is part of taking the problem seriously.
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This is one of those use cases we’ve been waiting for! Every Bitcoin carries its full transaction history on-chain, which is why exchanges reject coins that passed through the ‘wrong hands’ and why BTC was never really fungible. $BTCx on Zano is Bitcoin as a Confidential Asset, no on-chain trail attached, so every coin is worth the same as every other 🔒
Watch us pay *privately* with Bitcoin on Zano in the attached video! ✨Meile v2.8.2 is out! This release introduces @zano_project Integrated Payments for Zano CAs and the native asset. For best UX use @FreedomWallet since that wallet properly handles a Zano URI for scanning the QR code, especially with Confidential Assets. We also now have an AppImage for Linux users which we have placed on our website and GitHub. A couple bug fixes, introduced in v2.8.0, specific for Ubuntu 26.04 Wireguard where AppArmor prevented wg from coming up. QR Code fix on new Sentinel Wallets as well. Available @ dvpn.app Via apt or Github.
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In cybersecurity, knowing that an attack can happen is the beginning of the analysis. You need to understand how likely it is, required resources, conditions that must be present and what the attacker stands to gain. Without that distinction, security teams can spend time preparing for spectacular scenarios while overlooking weaknesses that are far more likely to be exploited. A good risk assessment requires practical experience and sound judgment. It helps organizations direct limited resources towards threats that pose a genuine danger, while still preparing for less common but serious events. We need to evaluate risks realistically, as intelligent systems become more capable and increasingly connected to critical infrastructure, this discipline will become even more important.
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Researchers at MIT and New York University have developed FLEX, it is an AI-assisted learning platform that helps robots infer human preferences from natural language instructions and apply them to tasks beyond what they have been explicitly told. The idea addresses a limitation in how robots respond to human instructions. A person may tell a robot not to spill coffee on a laptop, but the robot should also recognize that a nearby phone needs protection. Requiring people to identify every object and possible hazard individually makes interaction unnecessarily complicated.
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People rarely evaluate major technological changes from a neutral position. Their experience of the world influences what they see as an opportunity and what they see as a threat. Someone whose career and financial security depend on existing systems may be concerned about what new technology could disrupt. Someone who has struggled to access opportunities may see the same development as a chance to participate in ways that were previously out of reach. Both perspectives deserve to be understood. But we should also look beyond individual interests and ask how the benefits and costs of technological progress will be distributed. I believe the future should not be shaped only by those who already have the resources to benefit from new technology. More people need a meaningful opportunity to participate in building it and sharing in its value.
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Holding your own keys is step one. Step two is using private money nobody can censor or freeze. With $ZANO available in Freedom Wallet, you get both 🔒
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That's a wrap on @AIBC_World Rome. 🇮🇹 It was great catching up with our existing partners at @AEON_Community and @AlchemyPay, and starting new conversations with @BasicSwapDEX, @0Xprocessing and plenty of others, from payment processors to custody providers. Thanks to everyone who stopped by the booth. Back to building. 🔒
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Scientific progress needs new discoveries, and people who can organize what we know and make complex knowledge useful.
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Consider asking a legal agent to review a contract. It needs to know which agreement to examine, the jurisdiction involved, and if you want it to identify risks, compare terms or recommend revisions. Without those details, adding more documents to its input is unlikely to solve the problem. The agent may have access to a large volume of information and still misunderstand the task. It is a design issue that deserves more attention because reliable agents need clearly defined responsibilities, relevant information and boundaries around what they can conclude or execute. In legal work especially, precision is essential because the cost of getting the details wrong can be significant.
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