Lisbon

🚀 EDU-X x DOKDO 런칭 기념 이벤트 차세대 투자 학습 플랫폼 EDU-X의 런칭을 기념하여, DOKDO와 함께 총 1,000 USDT 상금의 특별 이벤트를 진행합니다! EDU-X에서 리스크 없이 모의 투자를 경험하고, 간단한 퀘스트 완료 후 상금의 주인공이 되어보세요. 📅 기간: 3/30(월) 14:00 ~ 4/12(일) 💰 상금: 1,000 USDT ➡️ 퀘스트 참여하기: [DOKDO 퀘스트 링크] dokdodao.io/events/3193728… 💵에듀엑스 오픈기념 모의투자 대회 참여 하기 t.me/eduxpapertradi…

@edyjayakarya @cadillion 열심히 하고 있구나 에디! 화이팅이야!

One key insight from @cadillion, CEO of Quip Network in this short video is that post-quantum cryptography isn’t some complex, abstract breakthrough ~ it’s actually pretty straightforward. Cryptography is just about choosing the kind of math that secures communication. And if quantum computers are good at breaking certain math, the answer isn’t to fight them ~ it’s to switch to math they’re bad at. At the same time, Dillion points to a much bigger vision: linking quantum computers around the world so, they can work on the same problem together ~ a true “worldwide quantum computer.” The foundation for that is entanglement ~ where one quantum system depends on another. It already exists at the qubit level, and has even been demonstrated between two quantum machines. So, we’re not just preparing for the quantum era ~ we’re actively building toward it. And this is where @quipnetwork comes in. Quip isn’t just focused on quantum-resistant security ~ it’s building the communication layer for a future where: √ quantum-safe cryptography is the default, √ and value + data can move seamlessly across networks. As systems evolve (potentially into quantum-scale networks), the way they communicate has to evolve too. Security and computation are evolving in parallel ~ and Quip is positioning itself right at that intersection.

@edyjayakarya @useTria @APEPE_MEME Edy 오랜만이야. 트위터를 통 안해서 찾아보지도 못했네. 어떻게 지내?

@lisbongg @useTria @APEPE_MEME Semoga menang Lisbon, designnya keren 😎

.@useTRIA x @APEPE_MEME 'Beauty of Korea' 4 Card Designs 1. Fishing on a Wooden Boat - Placed APEPE fishing on a wooden boat against an ink-and-wash painting background that emphasizes the beauty of empty space. - Depicted the philosophical attitude of a scholar observing the mundane world, likening it to APEPE's indifferent and tired expression. - Minimized colors and used light ink shading to create a calm and minimalist Korean aesthetic. 2. Magpie and Tiger - Utilized thick, powerful ink lines and toned-down traditional Korean colors (Obangsaek) to bring out the rough and humorous atmosphere unique to folk paintings. - The comical tiger and noisy magpie create a pleasant contrast with APEPE's blank expression. 3. Plum Blossoms under the Moonlight - Applied delicate lines and distinct colors against the background of a full moon night sky and red plum blossoms. - Emphasized an elegant and antique atmosphere through APEPE wearing a Gat (traditional Korean hat) and covering its face with a Hapjukseon (traditional folding fan). - APEPE's green skin, red flowers, and deep blue background show a striking yet harmonious visual contrast. 4. Thatched-roof House and Long Pipe - Illustrated APEPE smoking a Gombangdae (traditional long pipe) while sitting on a straw mat with a simple thatched-roof house and pine trees in the background. - Captured the friendly and folksy mood of traditional genre paintings depicting the daily lives of commoners with light lines and coloring. - The leisureliness of living free from worldly cares in nature and APEPE's indifferent characteristics blend seamlessly together. #APEPE_TRIA_CONTEST

@SubongLee2 채곱니다!

@lisbongg 와 학식 뭐졍ㄷㄷ

따사로운 봄을 맞이하며 'Sunshine Spends'! 출근길에는 집 근처 대학교를 지나간다. 이른 점심메뉴를 고르기 애매해 질 때면 요즘은 항상 학생식당을 선택한다. 가격과 맛 모두 만족스럽다. 지척에 두고 있었는데 최근에야 알게된 것이 아쉬울 지경이다. 벚꽃이 만개 했다. 만개한 벚꽃을 볼 수 있는 날은 1년에 고작 7일 정도다. 자주 가던 근처 대학교에도 벚꽃이 흐드러져 만족스런 식사 후에 캠퍼스를 걸었다. 오늘도 특별한 날이다. @useTria #SunshineSpends

@volajjh 요즘 정말 이쁘네요!

@lisbongg 벚꽃 너무 예뻐요~

@Jamsbu010 가성비 지립니다~

@lisbongg 학식 퀄 좋네요~

우리들의 오늘도 만개하기를.

@chosenryot 일해라절해라할수업죠ㅋ

정말 미안하지만 인건비를 인권비라고 하는 사람의 인권은 없다

@gorochi0315 @chosenryot 헉 고로치님도 오셨다니ㄷㄷ

@chosenryot 수고 많으셨어요 많이 배우고 갑니다ㅎ

오늘 제1회 오픈클로&웹3 이벤트에 함께해주신 모든 분들께 진심으로 감사드립니다! "에이전트에게 지갑을 주자"라는 약간 어려울 수 있는 주제로 자리를 마련했는데, 이렇게 많은 분들이 관심 갖고 와주실 줄은 몰랐습니다 ㅎㅎ 총 등록해주신 분들도 200분이 넘어가셔서, 다음에 꼭 후속 이벤트를 만들어보려 합니다 :) 이번 행사는 단순한 기술 데모가 아니라, 실제로 에이전트를 운영하고, 커뮤니티를 만들고, 생태계를 고민하는 사람들이 모여서 솔직한 이야기를 나누자는 취지였습니다. "에이전트에게 지갑을 준다"는 건 결국 신뢰의 문제입니다. 코드에 대한 신뢰, 시스템에 대한 신뢰, 그리고 그 시스템을 만든 사람에 대한 신뢰. 이러한 에이전트 + Web3의 미래를 함께 고민할 수 있었던 게 가장 의미 있었습니다. @openclaw 생태계가 한국에서 이렇게 관심을 받고 있다는 걸 체감했고, 앞으로도 이런 자리를 계속 만들어갈 생각입니다. 다음에는 더 깊은 주제로, 더 실전적인 내용으로 찾아올게요. 다시 한번 와주신 모든 분들, 패널에 함께해주신 @Lo_gan__ 님과 @Im_zo_sol 님, @selarious25님, 그리고 행사를 스폰서해주신 @MeteoraAG 와 @cysic_xyz 에게 다시 한 번 감사인사 드립니다! 이번에 못 오신 분들은 꼭 다음에 뵈어요!

@chosenryot 내공은 ryot님이 역시 제일 깊으시더군요. 시간에 쫒겨서 후다닥 나왔는데 인사 못나눠서 아쉬웠습니다ㅠ 그리고 자동화 궤적이 제가 삽질한 궤적과 너무 비슷해서 살짝 놀랐네요ㅎ

@APEPE_MEME .@useTRIA x @APEPE_MEME 'Beauty of Korea' 4 Card Designs x.com/lisbongg/statu… #APEPE_TRIA_CONTEST @Jamsbu010 @volajjh

APEPE x TRIA Card Design Contest 🎨 Design APEPE on a TRIA card. Meme it your way. Campaign period: April 2 – April 15 [ Rewards ] 🥇 1st — TRIA Metal Card + 400,000,000 APEPE 🥈🥉 2nd–3rd — TRIA Metal Card + 225,000,000 APEPE 🎖 12 Winners — TRIA Virtual Card + 37,500,000 APEPE 🎁 Random 15 — 15,000,000 APEPE [ How to Participate ] • Follow @APEPE_MEME and @useTRIA • RT + Like Post • Post your creative image, then add link in event comments + tag 2 or more friends • Include the hashtag #APEPE_TRIA_CONTEST Best designs get featured in our community 👀 Designs are for creative use only and will not be made physical.

@edyjayakarya @taka_eth 저도 매일 일본어를 공부하고 있습니다!

@taka_eth GM Taka-san. @lisbongg 여기 타카님이 당신 언어 배우는 중이에요 ㅎㅎ

gm ☀️저는 한국어를 공부해요

From an Empire on Sand to Sovereign Intelligence: How High-Quality On-Chain Data Drives the Evolution of Autonomous AI Agents Human history has always been intertwined with the noble yet dangerous desire to create intelligent life that resembles ourselves. From 'Talos', the giant bronze automaton that guarded the island of Crete in ancient Greek mythology, to the 'Golem' of Jewish tradition, a creature molded from clay and breathed into life, the imagination of artificial intelligence has transcended eras. Since Gottfried Leibniz imagined in the 17th century that the human reasoning process could be replaced by mechanical calculation, artificial intelligence (AI) has moved beyond the realm of myth and entered the forefront of science, passing through Alan Turing's provocative question in the 1950s ("Can machines think?") and the Dartmouth Workshop in 1956. After enduring decades of extreme fluctuations known as the 'AI winters and summers,' the revolution of deep learning and Transformers architectures has bestowed upon humanity a technology as magical as Large Language Models (LLMs). And starting in 2025, this technology is breaking the mold of passive 'prompt-and-response' tools that simply answer user queries, entering an era of 'Autonomous AI Agents' that perceive, reason, and act on their own. However, behind this dazzling algorithmic evolution lies a fatal crisis. Imagine handing a rusty scalpel to a neurosurgeon renowned for the highest level of precision. No matter how outstanding an AI's computational capabilities and logical structures may be, if the 'data'—the foundation that forms and operates that intelligence—is contaminated, the system is inevitably bound to collapse. Especially as models move beyond generating text on a digital screen and are deployed in high-stakes environments like medical diagnosis, financial trading, autonomous driving, and military security, where even the slightest error can lead to an irreversible disaster, data integrity has evolved from a mere technical recommendation into an absolute prerequisite directly linked to human survival. Indeed, the biggest bottleneck in AI technology is shifting from 'better algorithms' or 'faster computational power' to the 'verification of truth.' This article thoroughly analyzes the crisis of data contamination and model collapse facing modern AI systems, and how the autonomous AI agent ecosystem, which demands pristine truth, inevitably integrates with blockchain technology. Furthermore, by exploring the Sovereign Data Layer philosophy of Perle Labs—which elevates human wisdom from a mere consumable to a verifiable infrastructure—and the innovative architecture based on the Solana blockchain, we investigate how high-quality on-chain data is reshaping the future of artificial intelligence. 1. The Rise of Autonomous AI Agents and Integration with the Web3 Ecosystem If past artificial intelligence was a powerful 'tool' that faithfully executed human commands, Autonomous AI Agents (AAAs) are independent 'actors' that set their own goals and interact with their environments. Beyond pre-defined rules or algorithms, they self-execute a dynamic loop of perceiving data in real-time within complex environments, reasoning through potential concepts, and making optimal decisions to take action. The place where these agents first took root to acquire true autonomy is the decentralized Web3 ecosystem. As AI, once confined to centralized servers, meets the open and transparent infrastructure of blockchain, these agents are emerging as the main characters of an 'Agent Economy,' creating and trading economic value far beyond mere software programs. 1.1. The Three Pillars Supporting the Agent Economy For autonomous AI agents to seamlessly interact with blockchain networks, APIs, and other agents without human intervention, an infrastructure that guarantees absolute trust is essential. The three core elements supporting this ecosystem are as follows: Identity: On-chain identity verification through standards like ERC-8004 (Trustless Agents). When interacting with other agents, it autonomously verifies the authenticity and authority of the counterpart without a central authority, forming a Trust Layer. Payments: Automated micro-transactions based on smart contracts utilizing protocols like x402. When an agent calls an external service or another agent's API, it exchanges value and negotiates contracts in real-time without human approval. On-chain Data: Data permanently recorded on the blockchain in a readable, reliable, and structured format. It is the most fundamental 'Source of Truth' for agents to make decisions and understand market conditions. If the data is inaccurate, fatal compounding errors occur. Even if identity and payment protocols are successfully established, if the environmental data or on-chain records that an agent references are contaminated, the entire system collapses like a castle built on sand. Because blockchain smart contracts execute exactly as coded without the slightest margin of error, if an agent initiates autonomous action based on flawed data, the room for physical intervention to stop it mid-process is extremely limited. Therefore, the supply of structured and verified high-quality data remains the most important, yet hardest to secure, final puzzle piece for agents to act as independent economic entities. 2. The Data Strikes Back: The Depletion of Intelligence and the Threat of Model Collapse The simple and somewhat brutal paradigm that "more data makes a better model," which exponentially improved AI performance, has now reached the end of its marginal utility. A significant portion of the hundreds of billions of text corpora, massive image sets, and video archives humanity has accumulated on the internet has already been exhausted for model training. As the supply of new human-generated data dries up, large tech companies have resorted to the extreme measure of pouring 'Synthetic Data'—created by AI itself—back into the training process to maintain AI model performance. And this has become the trigger for 'Model Collapse,' the most fatal crisis in the history of artificial intelligence. 2.1. The Tragedy Born of Artificial Inbreeding: The Mechanism of Model Collapse Model collapse refers to the phenomenon where the performance of a model degrades exponentially over time, and the system ultimately breaks down completely, as an AI system repeatedly learns from contaminated data generated by previous generations of AI. This is fundamentally different from 'Catastrophic Forgetting,' where a single model loses past memories while learning new information. If catastrophic forgetting is the amnesia of a single entity, model collapse is closer to an 'artificial inbreeding of knowledge' where the genetic diversity of the entire species is destroyed over generations. Stages of Model Collapse: Early Collapse: The loss of 'Long-tail' ideas and rare data points located at the edges of the data distribution. Mid Collapse: A reduction in internal variance and the polarization of Confirmation Bias. The distribution map through which the model perceives the world narrows. Full Collapse: The loss of real-world context, the solidification of hallucination, and the mass production of completely meaningless nonsense data. This phenomenon does not simply end as an interesting academic failure. In the real world, the internet is already rapidly being polluted with AI Slop vomited out by AI. If the environment persists where models swallow their own excrement for learning, rather than human's genuine knowledge and field experience, AI models will converge to an extremely narrow average. The subtle nuances and original ways of thinking created by humans will vanish, and even research tools designed to aid scientific discovery will repeatedly present only heavily cited, biased papers, hindering the intellectual expansion of humanity. 2.2. The Arrival of a World Without an 'Undo' Button The more serious problem is that the role of AI is shifting from content generation to 'decision-making in the physical world.' If a chatbot generates grammatically incorrect sentences or outputs wrong historical facts, a user can simply laugh it off and refresh the screen. However, if the system is a diagnostic AI controlling a robotic arm in a hospital operating room, an autonomous financial agent processing thousands of transactions per second, or an autonomous Department of Defense drone identifying friend from foe, the situation is completely different. In these high-stakes environments, there is no 'Undo' button for fatal misjudgments made by AI due to contaminated data. The cost of an error is not a simple mishap but translates directly into massive financial losses, fatal collapses in national security, and the loss of human lives. Therefore, as AI systems become more sophisticated, the essence of the questions humanity asks must also change. In the past, we cheered at "How great is the performance of this model?"; now, we have reached a point where we must demand harsh accountability, asking, "Where on earth did this data come from, who verified it, and how can its integrity be proven?" 3. Sovereign Intelligence and Building the Infrastructure of Accountability Amidst the apocalyptic crisis caused by data contamination and opacity, the global technology ecosystem is facing a new paradigm shift. This goes beyond simply improving algorithms; it is a process of reclaiming 'Sovereignty' over the data that forms the foundation of artificial intelligence systems. 3.1. The Recovery of Control, Independence, and Accountability The concept of the 'Sovereign Intelligence Data Layer,' advocated by Ahmed Rashad, founder and CEO of Perle Labs, at ETHDenver 2026 and Breakpoint, most clearly represents this demand of the times. He declared that the core agenda piercing through AI has evolved from 'Capability' to 'Accountability,' and established the concept of sovereignty in three dimensions: Control: Institutions dealing with core infrastructure such as defense, healthcare, and finance should not leave their AI reliant on external, opaque black-box pipelines. They must directly own the intelligence upon which their systems are built and transparently control what data was used for training. Independence: Entrusting national or corporate fates to overseas cloud platforms or datasets of unclear origin is a severe security vulnerability in the era of technological protectionism. As the US National Security Agency (NSA) and Cybersecurity and Infrastructure Security Agency (CISA) warned in their joint 2025 guidelines, the vulnerability of data supply chains and malicious 'Data Poisoning' attacks are no longer academic hypotheses but clear and present fatal threats. Accountability: When an accident occurs in a physical environment, courts or regulatory authorities will ask harsh questions. "Who trained this model? What data was used? Who verified that data, and by what standards?" Only institutions capable of proving the answers to these questions with permanent, tamper-proof records will earn the right to operate AI in future society. 3.2. Blockchain Provenance Destroying the Black Box The only technical answer that can perfectly realize this sovereign intelligence is blockchain-based On-chain Provenance. When the computational power of an AI agent is combined with the immutability of a blockchain, a truly decentralized trust system is built. While past Oracle machine learning systems advanced predictive analytics by running algorithms using SQL and R within closed corporate database environments (such as Database 19c Enterprise Edition) without moving the data (In-database processing), the Web3-based autonomous agent environment expands the boundaries of this integrity to the entire global network. Every judgment made by AI agents, the source of all the data they reference, and every transaction record they execute through smart contracts are permanently engraved on the blockchain ledger via cryptographic hashes. This operates as a proactive safety net where, if a problem arises post-facto, it goes beyond simply digging through logs; when an agent attempts to access contaminated data, the smart contract blocks it in real-time and controls its permissions. In short, blockchain provides a perfect Audit Trail ecosystem that prevents autonomous AI agents from running amok and allows human intervention in their decisions. 4. Perle Labs: Elevating Human Wisdom to Blockchain Infrastructure In the midst of the data depletion and model collapse striking the AI industry, Perle Labs—comprising veterans from Meta, Amazon, Scale AI, and MIT—presented a revolutionary vision that overturns all existing rules. Having secured a total of $17.5 million in investment led by Framework Ventures, alongside CoinFund, HashKey Capital, and others, they have redefined human judgment not as a mere 'Cost' or a one-time 'input value,' but as a verifiable 'digital infrastructure' that will permanently support the AI ecosystem. 4.1. The Evolution from an Anonymous Crowd to a Verified Expert Network Existing traditional data labeling pipelines were inherently flawed. To lower the unit price of labeling by even a single cent, platform companies assigned even tasks requiring complex knowledge to anonymous gig-workers as gamified micro-tasks. Because this 'Crowdsourcing' model was optimized primarily for throughput, it inevitably led to a collapse in precision and to irresponsibility. It is absurd to think that anonymous workers rushing their clicks for a few pennies could properly understand and verify the medical data needed to train operating room AI or the context of arcane legal documents. Perle Labs completely dismantled this destructive incentive structure. Based on the Solana blockchain, they built a Web3-native data quality layer where only personnel with verified expertise perform high-level tasks and receive full compensation for them. Through the Season 1 campaign officially launched in January 2026, contributors participate directly in core real-world AI training workflows, moving beyond simple click-work to profoundly grasping customer email intent, validating robotics vision data, classifying medical text and images, and analyzing legal documents. Participants are evaluated for baseline accuracy during onboarding, and as they consistently supply reliable data, their on-chain reputation rises, earning them priority access to higher compensation and higher-level enterprise tasks. During the beta period alone, the overwhelming success of the expert-centric model was proven, with 1.7 million tasks already completed and 330 million points secured. 4.2. Qualitative Superiority from a Total Cost of Ownership (TCO) Perspective Initially, paying higher compensation to experts may feel like a cost burden to companies. CEO Rashad explains that while traditional labeling costs might be around $3 per document, meticulous review by an expert could reach $18 per document. However, this is just a superficial price tag. The story is completely reversed when viewed from the perspective of 'Total Cost of Ownership (TCO),' which includes the astronomical computing costs of repeatedly retraining algorithms when low-quality data seeps into the pipeline, delayed launches, and the fatal damage to trust and legal liabilities caused by deploying flawed AI. By guaranteeing near-perfect data integrity from the start, Perle Labs' expert-centric network dramatically reduces long-term TCO and successfully extracts the pinnacle of human wisdom—something synthetic data can never replace. 5. Bringing the Future Forward: On-chain Data and Autonomous Agents Innovating Across Industries The combination of the sovereign data infrastructure built by Perle Labs and the MoLaCE framework has moved beyond mere laboratory research outcomes, fundamentally shaking the landscape of real-world industries throughout 2025 and 2026. Standing on the firm foundation of verified, high-quality on-chain data, autonomous AI agents are now controlling fatal risks and creating value that surpasses humans in various industrial sectors. 5.1. Healthcare: The Restoration of Life-Saving Precision The healthcare industry is a paradoxical field where the introduction of autonomous AI agents yields the greatest benefits, yet demands the highest level of data integrity. A recent study using Multi-Layer Perceptrons (MLP) based on actual clinical data achieved the remarkable feat of identifying high-risk pregnancies early with a staggering 91% accuracy through a high-quality data pipeline. However, for a robotics-based autonomous medical agent assisting a surgeon in an operating room (OR) or independently detecting micro-lesions, 91% accuracy remains a deadly roulette that threatens the patient's life. No matter how advanced the latest robotic arm hardware is, if the data that trained its sensors was misclassified by unskilled crowd workers, it is better to leave the scalpel entirely to human doctors. Medical doctors and radiologists who have joined the Perle Labs network meticulously calibrate clinical trial benchmarks and multi-language medical charts, transferring 'real expertise' to agents by understanding the context of complex symptoms and perfectly controlling Personally Identifiable Information (PII). 5.2. Decentralized Finance (DeFi): The Algorithm Capitalism That Never Sleeps The global economy has entered an era of unprecedented autonomy. As the Total Value Locked (TVL) in Decentralized Finance (DeFi) approaches $154 billion as of 2025, a whopping 25% of these massive assets are managed directly by autonomous AI agents rather than human fund managers. While 60% of new users access complex DeFi products through natural language interfaces, the agents running in the backend analyze Etherscan smart contracts, infer real-time interest rates and market sentiment, and tirelessly execute optimized arbitrage trading by the second. To prevent this massive algorithm capitalism from leading to catastrophic cascading collapses like a Flash Crash, Oracle and on-chain integrity—ensuring that the market data the agents reference has not been manipulated—is absolute. The blockchain permanently preserves historical financial crime data, and based on this, AI agents capture signs of money laundering or fraud in milliseconds (ms) and autonomously block transactions, thereby defending the liquidity and trust of the entire system. 5.3. Supply Chain Management and Enterprise Orchestration Traditional logistics automation follows rule-based systems, but in today's highly volatile global supply chains, this is simply not enough. Moving beyond automation that merely counts inventory, the manufacturing and distribution industries are making astronomical investments in Agentic AI orchestration, where machines themselves compromise (trade-off) and coordinate multivariable, complex factors in real-time—such as carbon emissions, logistics costs, and delivery delay times. Take the vaccine transport process of a pharmaceutical company as an example. Once the temperature sensor data and customs clearance records of the transport truck are permanently recorded on the blockchain, the autonomous AI agent scans this on-chain provenance in real-time. If it detects a history of deviating from the prescribed temperature by even a single degree, the agent, without waiting for anyone's instructions, independently decides and triggers a smart contract ordering an immediate recall for the products in that lot. This is an innovative example where the integrity of data and the judgment of AI combine to achieve ultimate consumer safety, without the slow document review of a central authority. 6. Conclusion: Data Sovereignty, the Final Bulwark for the Coexistence of Humanity and AI We are now passing through a historical inflection point where the greatest intellectual invention created by humanity stands at a massive crossroad. One path leads to the abyss of 'Model Collapse,' where AI relentlessly devours contaminated knowledge it spat out itself, losing its grasp on the context of the real world. The other is the arduous but sole path to survival: 'Sovereign Intelligence,' refining AI into a controllable and responsible tool by firmly etching the verified wisdom of humans onto the transparent trajectory of the blockchain. The illusion that blindly dominated the tech industry for years—"If we push in the most data and pour in the most massive computational power, magic will happen"—has come to an end. Models have become massive, but the contextual understanding and judgment to discern truth from within that deep abyss did not emerge spontaneously. The inflection point of technology has now shifted its fundamental axis from 'how plausibly it mimics intelligence (Capability)' to 'how it will take responsibility (Accountability) for the outcomes derived by that intelligence.' The Sovereign Data Layer being pioneered by Perle Labs is the most definitive technical and philosophical response to this question of our times. Based on the overwhelming architecture of the Solana blockchain, they have elevated the old, exploitative industry of data labeling into a noble digital infrastructure where human experts become the owners of the network and create fair value. Furthermore, through the MoLaCE framework, they have successfully shattered the hall of mirrors of confirmation bias that constantly coils inside models, and successfully implanted a geometric compass pointing toward truth directly into the heart of the model. In the near future, an advanced Agent Economy will dominate our lives, where billions of autonomous AI agents communicate with their own identities across the vast ocean of the Web3 network, independently entering into economic contracts and exchanging value without human physical intervention. The only condition to prevent this massive, complex digital ecosystem from degenerating into an uncontrollable dystopia is obvious: the grounds for every judgment these agents perceive and reason, the very data that is like the breath they breathe, must be thoroughly transparent, uncorrupted, and proven with intact human wisdom On-chain. High-quality on-chain data is not a mere option or add-on for autonomous AI agents to be useful in the real world. It is the absolute prerequisite for machine intelligence to exist as a reliable companion to humanity, and the final, greatest safety mechanism firmly locked to prevent unknown algorithms from destroying our lives. We must tear down the empire built on sand, and now, we must build the new tower of sovereign intelligence upon the bedrock of unchanging truth. -- #PerleAI #ToPerle — participating in @PerleLabs community campaign

AI Agent 트레이딩 2주차 수익 시작? 첫 주차 처참한 결과에서 계속된 수정으로 드디어 양전까지 도달했다. -15%까지 내려갔던 수익률이 +가 되었다. 공포탐욕지수가 계속 공포 단계로 지속되자 롱 가설은 엄격하게 기준을 높이고 전방위적인 숏 전략을 쓰더니, 80% 이상의 승률을 기록했다. 이게 되나 생각했던 순간, 양치기 트럼프의 아마곧전쟁끝? 퍼드로 가지고 있던 숏포지션이 거의 다 청산되며 -4% 정도를 기록중. 수수료도 포함된 수익률이니 나름 선방했다고 볼 수도 있겠다ㅠ. xp는 계속 쌓인다. 완전 자동화의 길은 멀다 모두가 꿈꾸는 미래, 에이전트가 혼자 일하며 뚝딱 수익을 만들어준다는 건 아직 미래의 일 같다. 계속해서 에러를 뱉어내고 수정하면 또 다른 쪽에서 문제가 생긴다. 끝없는 수정의 굴레. 그래도 매매실력은 나보다 나은듯하다. 계속 가보자 작은 비율이지만 소정의 일일 수익률이 입증되면 포션을 점진적으로 늘릴 예정. 아직은 유의미한 데이터에 도달 못한것 같다. 에이전트는 꽤나 엄격한 잣대를 가지고 트레이딩에 임하기때문에 많은 거래를 하지 않는다. 느려도 수익보다는 생존이다. @useTria

@woherkommen 제가 방송 다 못봐서 읽으려 요약한김에 올립니다ㅋ 즐거운 한주되세요 워커님~

@lisbongg 앗. 이 내용은 처음 봐요...관련 기사를 좀 읽어봐야겠네요 원래 X는 편하게 떠드는 공간인데, 저도 그랬지만 목적이 있던 시작이어서 그랬는지, 그걸 깨는 게 어려웠던 것 같아요.리스본님의 다른 주제 글을 읽게 되니 새롭네요 ㅎㅎ

📢 김어준의 겸손은 힘들다 뉴스공장 요약 📅 방송날짜: 2026년 03월 20일 (금) 📜 코너명 : 김어준 생각 👥 출연자 : 김어준 안녕하세요 김어준입니다. 지난 수요일 스위스 제네바에서 UN 기구와 우리 정부가 글로벌 허브 협력 의향서에 서명했습니다. UN 국제 기구들의 AI 본부를 뉴욕이나 제네바가 아니라 한국에 두겠다는 건데, 우리가 국제 사회에 제안한 여러 계획 중 가장 원대한 이 프로젝트가 반드시 성공하길 빕니다. 김어준 생각이었습니다.

2026년 3월 20일(금) 김어준의 겸손은힘들다 뉴스공장 코너별 바로가기 김어준 생각 youtube.com/live/gNGarIUH9… 겸손브리핑 youtube.com/live/gNGarIUH9… 잠깐만 인터뷰 [차지호] youtube.com/live/gNGarIUH9… 민병덕, 김남근, 김현정, 이강일 youtube.com/live/gNGarIUH9… 퍼니포 [추미애, 이지은, 홍사훈, 봉지욱] youtube.com/live/gNGarIUH9… 권칠승 youtube.com/live/gNGarIUH9… 양기대 youtube.com/live/gNGarIUH9… The살롱 [전우용, 김태형, 류근] youtube.com/live/gNGarIUH9… 금요음악회 [이동규, 고의석] youtube.com/live/gNGarIUH9…

📜 코너명 : 금요음악회 👥 출연자 : 이동규, 고의석 세계적 카운터테너 이동규의 데뷔 30주년 라이브 1️⃣ 18세 데뷔 후 30년간 증명된 월드 클래스 조수미 이후 한국인 최초로 명문 레이블 '에라토'와 단독 앨범을 발매하고 유수의 국제 콩쿠르를 휩쓴 카운터테너 이동규가 출연했습니다. 변성기 이후에도 특유의 근육 기억(Muscle Memory)을 활용해 베이스나 바리톤의 본래 목소리가 아닌 고음을 자유자재로 컨트롤하는 발성의 비밀을 들려주었습니다. 2️⃣ '근육 고음'이 돋보인 명품 라이브 무대 한국 가곡 '마중'과 오페라 카르멘의 '하바네라' 라이브를 선보였습니다. 클래식 기타리스트 고의석의 담백한 선율에 맞춰, 부드러우면서도 핵심 근육으로 단단하게 받쳐주는 폭발적인 고음을 뽐내며 데뷔 30주년다운 완벽한 무대를 장식했습니다.