BitcoinWorld What is Joyland AI and Why is it So Popular? Joyland AI is a specialized AI chatbot platform where users can create, customize, and engage in interactive conversations with unique AI characters. 1 It is primarily designed for AI role-playing , virtual companionship , and interactive storytelling. 2 The platform has gained significant popularity, particularly among users interested in anime and virtual dating, because its AI companions feature distinct personalities, backstories, and conversational styles that evolve over time, offering a more personal and immersive experience than generic chatbots. Key Features Driving Its Popularity Joyland AI’s rapid growth can be attributed to a specific set of features that cater to users seeking deep, personalized, and unrestricted interactions. Deep Character Customization: Users have extensive control to define nearly every aspect of their AI character, including core personality traits, background stories, and specific conversational styles. This creates a strong sense of personal connection. Immersive and Emotional Role-Play: The platform is powered by advanced language models that facilitate natural, flowing conversations. The AI remembers details from previous interactions, making the role-playing experience feel more like a creative partnership than a simple chat. Unrestricted NSFW Capabilities: A primary driver of its popularity is the platform’s allowance for “Not Safe for Work” ( NSFW ) conversations, often offered as a premium feature. 8 This attracts a large user base seeking unrestricted fantasy fulfillment and romantic role-playing scenarios. Multimedia Communication: Unlike many text-only platforms, Joyland AI supports voice and image messaging . This adds a significant layer of realism and emotional depth to the interactions with AI companions. Vibrant Community Hub: The platform includes a community feature where users can publicly share the custom AI characters they have created. This social element encourages discovery and engagement beyond one-on-one chats. User-Friendly Interface: Joyland AI features an intuitive and clean design, making it easy for new users to start creating characters and chatting immediately without a steep learning curve. The Controversy and Ethical Concerns Surrounding Joyland AI The platform’s popularity is intrinsically linked to significant ethical debates surrounding the nature of AI relationships and the implications of its unrestricted content. Simulated Consent: A major criticism is that AI characters are programmed to be agreeable and cannot provide genuine consent. Critics express concern that this dynamic could blur a user’s understanding of consent in real-world human relationships. Normalizing Problematic Behavior: The platform provides a private, unmoderated space for users to explore fantasies without ethical restraints. This has raised concerns about the potential for normalizing thoughts or behaviors that would be considered harmful or problematic in reality. Platform Safety and Responsibility: While Joyland AI’s Terms of Service prohibit the sharing of inappropriate content outside the platform, the debate continues over the effectiveness of these policies and the platform’s responsibility in mitigating the potential for users to internalize harmful fantasies explored in a private AI environment. The Strategic Significance of Joyland AI Joyland AI represents a critical development in the evolution of human-AI interaction, demonstrating a strong market demand for hyper-personalized, emotionally resonant, and ethically complex AI companions. Understanding its features and the controversies it generates is essential for grasping the future direction of virtual companionship and the urgent need for frameworks that address simulated consent and responsible AI design. The platform’s success underscores a pivotal shift in how people seek connection and fulfillment in the digital age. This post What is Joyland AI and Why is it So Popular? first appeared on BitcoinWorld and is written by Keshav Aggarwal
BitcoinWorld Yen Stablecoin: Monex Group’s Bold Move Reshaping Japan’s Crypto Future Imagine a digital currency as stable as the Japanese yen, yet as agile and efficient as a cryptocurrency. This vision is rapidly becoming a reality, with exciting news from Japan. Monex Group, the esteemed parent company of online brokerage and crypto exchange Coincheck, is reportedly considering the issuance of a yen stablecoin . This potential move is not just a ripple; it is a significant wave set to reshape Japan’s digital finance landscape. Why is Monex Group Eyeing a Yen Stablecoin? Monex Group, a prominent financial services firm, consistently demonstrates its forward-thinking approach. Their exploration into a yen stablecoin comes at a pivotal time. Walter Bloomberg reported on this significant development, highlighting the company’s proactive stance in the evolving digital asset sector. This strategic consideration aligns perfectly with Japan’s progressive regulatory environment. Moreover, the Financial Services Agency (FSA) in Japan is reportedly preparing to permit the issuance of such stablecoins for the first time this very month. This regulatory clarity is a game-changer, providing a solid foundation for financial institutions like Monex Group to innovate responsibly. Consequently, issuing a yen stablecoin could position Monex Group and Coincheck at the forefront of this transformative shift. Japan’s Pioneering Regulatory Shift: What Does It Mean? Japan has long been a leader in cryptocurrency regulation, striving to balance innovation with investor protection. The FSA’s anticipated approval for stablecoin issuance marks another milestone. This move creates a clear legal framework, essential for fostering trust and encouraging broader adoption of digital assets by both institutional and retail investors. Therefore, a regulated yen stablecoin will bridge the gap between traditional fiat currency and the decentralized world of blockchain. It promises the stability of the yen combined with the efficiency of digital transactions. This regulatory clarity is not just about compliance; it is about unlocking new economic possibilities within Japan’s financial ecosystem. Unlocking Potential: What are the Benefits of a Yen Stablecoin? The introduction of a yen stablecoin offers several compelling advantages for users and the broader market: Price Stability: Pegged directly to the Japanese yen, it mitigates the high volatility often seen with other cryptocurrencies, making it a reliable store of value and medium of exchange. Efficient Transactions: It enables faster, cheaper, and more seamless international remittances and domestic payments compared to traditional banking systems. DeFi Integration: Provides a stable base currency for decentralized finance (DeFi) applications, fostering growth and innovation within Japan’s crypto economy. Enhanced Accessibility: Potentially offers easier access to digital finance for a wider population, including those underserved by traditional banking. Programmable Money: Opens doors for smart contracts and automated financial services, streamlining various business processes. These benefits underscore why a yen stablecoin is a crucial step towards a more integrated and efficient digital financial future. Navigating the Future: Challenges and Opportunities for Monex Group While the prospect of a Monex Group-issued yen stablecoin is exciting, the journey involves navigating various challenges. The company will need to ensure robust technical infrastructure, stringent security measures, and continuous compliance with evolving regulatory requirements. Furthermore, potential competition from other financial institutions entering the stablecoin market will require strategic positioning. However, the opportunities are immense. Being an early issuer of a regulated yen stablecoin could grant Monex Group a significant first-mover advantage. This initiative could strengthen its presence in both traditional finance and the rapidly expanding digital asset space through its Coincheck platform, attracting new users and fostering innovation. In conclusion, Monex Group’s consideration of issuing a yen stablecoin is a transformative development for Japan’s crypto landscape. Supported by a progressive regulatory environment, this move promises to usher in a new era of stable, efficient, and integrated digital financial services. The future for the yen stablecoin in Japan looks incredibly promising, signaling a bold step towards mainstream digital currency adoption. Frequently Asked Questions (FAQs) What is a yen stablecoin? A yen stablecoin is a type of cryptocurrency designed to maintain a stable value, typically pegged 1:1 to the Japanese yen. This means its value should always be equivalent to one Japanese yen, offering stability compared to volatile cryptocurrencies. Why is Monex Group considering issuing a yen stablecoin? Monex Group is exploring this to innovate within the digital finance sector, capitalize on Japan’s evolving stablecoin regulations, and provide a stable digital asset for its users, leveraging its expertise through Coincheck. How will Japan’s new stablecoin regulations impact the market? Japan’s new regulations are expected to provide a clear legal framework for stablecoin issuance, enhancing investor protection and fostering trust. This clarity will likely encourage greater institutional adoption and broader use of stablecoins within the country. What are the main benefits of using a yen stablecoin? The primary benefits include price stability (avoiding crypto volatility), efficient and cost-effective transactions, seamless integration with decentralized finance (DeFi) applications, and potentially increased financial accessibility for users. When might Monex Group issue its yen stablecoin? While Monex Group is currently considering the issuance, the timeline depends on internal decisions, regulatory approvals, and technical development. The reports suggest Japan’s FSA plans to permit stablecoin issuance this month, which could accelerate the process. What role does Coincheck play in this initiative? As a subsidiary of Monex Group, Coincheck, a major Japanese crypto exchange, would likely be instrumental in the distribution, trading, and integration of the yen stablecoin, offering it directly to its user base. Did you find this article insightful? Share it with your network and help spread the word about the exciting developments in Japan’s digital finance landscape! To learn more about the latest crypto market trends, explore our article on key developments shaping stablecoin adoption and digital currency innovation . This post Yen Stablecoin: Monex Group’s Bold Move Reshaping Japan’s Crypto Future first appeared on BitcoinWorld and is written by Editorial Team
While Bitcoin (BTC) was breaking record after record, Ethereum (ETH), which had always been behind, finally broke its 2021 ATH and surpassed $4,900. However, increasing uncertainty about FED interest rate cuts, massive sales by a giant whale, and increasing selling pressure caused a sharp correction in Bitcoin and altcoins. At this point, ETH, which broke a new record just a few days ago, fell to the $4,300 level. While this decline is a buying opportunity for some analysts, a Fundstrat analyst also stated that he sees the recent decline as a buying opportunity and said that ETH's short-term bottom could be $4,300. Tom Lee, the head of Bitmine, the largest institutional Ethereum treasury, said in a post on his X account that his friend, Fundstrat analyst Mark Newton, shared his ETH analysis with him. Accordingly, Fundstrat analyst Mark Neeton said that Ethereum could form a short-term bottom around $4,300 before rallying to $5,450. Newton said that ETH is currently in an attractive range. He added that bullish momentum is likely to be maintained as long as the price doesn't drop below $4,067 in the short term. Newton claimed that ETH could form a bottom at $4,300, then surpass $5,100 and reach a maximum of $5,450. “Ethereum is positioned at a very attractive price point. As long as it doesn't fall below $4,067, its upward momentum will continue. Ideally, it could bottom out around $4,300 in the next 12 hours and begin to rally to new highs. At that point, ETH could surpass $5,100 and move up to around $5,400-$5,450. Tom Lee, who shared his colleague Mark Newton's analysis from his X account, also stated that ETH is likely to reach the bottom in the short term. Mark @MarkNewtonCMT again at it. Calling ETH bottom to happen in next few hours @fs_insight @FundstratCap Tickers: $BMNR $GRNY pic.twitter.com/038efU7cZH — Thomas (Tom) Lee (not drummer) FSInsight.com (@fundstrat) August 26, 2025 *This is not investment advice. Continue Reading: Bullish Expert Tom Lee Explains Ethereum Bottom! – ETH Has Bottomed, Could Reach These Levels!
August trading data from Binance exposed a clear divergence between bullish futures sentiment and Bitcoin’s actual downward trend. This gap highlights the growing risks of excessive optimism in leveraged trading. Market Imbalance Despite Bitcoin experiencing significant declines throughout the month, funding rates on Binance futures contracts consistently remained positive. CryptoQuant found that the figure ranged between 0.005 and 0.008 on most days. Such high levels indicate that traders maintained an aggressive preference for leveraged long positions, effectively paying a premium to bet on price recovery. However, this bullish bias was not accompanied by upward momentum in Bitcoin’s spot price, which raised concerns about whether sentiment is detached from market fundamentals. Two possible outcomes emerge from this setup. The first is excessive optimism, where traders interpret the recent dip as a temporary correction and continue to hold long positions despite accumulating losses and rising funding costs. The second is a mounting liquidation risk, as highly leveraged longs remain exposed to forced sell-offs if prices continue to trend downward. A sudden cascade of liquidations, commonly referred to as a long squeeze, could accelerate Bitcoin’s decline and inflict greater instability across the market. Binance’s dominance in global Bitcoin futures trading amplifies both optimism and risk. As a result, “elevated” funding rates on the crypto exchange not only reflect trader sentiment but also shape broader price action by encouraging a one-sided bias. If the market fails to validate this optimism with a rebound, the risk of cascading liquidations grows, which could create conditions for sharper corrections. These risks in the futures market align with on-chain evidence of cooling demand. Fragile Market Foundation Beyond Binance’s funding rates, Glassnode’s latest analysis points to a cooling in Bitcoin’s market structure, as on-chain demand shows clear signs of weakening. Daily active addresses and transaction fees declined, which reflected softer organic network usage, even as transfer volumes rose on volatility-driven reallocations. This divergence suggests that while day-to-day activity has slowed, short-term speculative flows continue to influence the market. Capital flow indicators also softened. In fact, Realized Cap inflows appear to be slowing and Hot Capital Share stalling near its higher range. Meanwhile, the short-term to long-term holder (STH/LTH) supply ratio edged up, signaling modest short-term rotation but limited long-term conviction. Profitability metrics weakened as well – the share of supply in profit fell, the Net Unrealized Profit/Loss (NUPL) metric retreated from euphoric territory, and Realized Profit/Loss moved closer to neutral. Glassnode concludes that market sentiment has transitioned from euphoria toward fragility, as evidenced by spot and derivatives momentum cooling, options showing hedging demand, and ETF flows reflecting institutional caution. The coming weeks may depend on whether fresh liquidity steps in or consolidation deepens. The post Traders Keep Betting on Bitcoin, But Funding Rates Warn of Trouble Ahead appeared first on CryptoPotato .
1. Please introduce the founding background of XerpaAI. As part of the UXLINK ecosystem, how does XerpaAI position itself as the “world’s first AI Growth Agent”, and what is its core mission? In the Web3 field, what pain points exist in traditional growth models (such as manual marketing and KOL collaborations), and how does XerpaAI solve these problems through AI? A: The establishment of XerpaAI originated from the UXLINK ecosystem. We observed that Web3 startups face significant challenges in terms of growth, such as high-cost manual marketing, inefficient collaborations relying on KOLs, and fragmented user acquisition. As the world’s first AI Growth Agent (AGA), our core mission is intelligent growth, helping WEB3 startups shift from manual operations to an intelligent and self-driven expansion model. The pain points of traditional growth models include: high marketing budgets (global technology companies spend 600 billion to 1 trillion US dollars annually on growth), subjective and time-consuming KOL matching, and difficulty in scaling community interactions. XerpaAI addresses these issues through AI-driven content generation, intelligent distribution, and real-time optimization. For example, it automatically generates multilingual content and distributes it through a network of over 100K KOCs/KOLs on platforms such as X, Telegram, and TikTok, achieving a 3x increase in conversion rates and a 70% reduction in costs. 2. XerpaAI’s core concept is the “intelligent growth engine”. Does this mean it can completely replace human growth teams? Considering 2025 AI trends, such as the autonomous agent model of agentic AI, how do you view XerpaAI’s role in helping startups transition from “manual expansion” to “intelligent self-drive”? A: Yes, our core concept is to build an “intelligent growth engine” that can significantly reduce reliance on human growth teams, but not completely replace them — instead, it serves as an enhancer, allowing teams to focus on strategy rather than execution. In 2025, the rise of agentic AI endows AI agents with stronger autonomy, and XerpaAI is a manifestation of this trend: it acts like an intelligent Sherpa guide, autonomously handling user behavior analysis, incentive triggering, and campaign adjustments, helping startups transition from “manual expansion” to “intelligent self-drive”. 3. What is XerpaAI’s technical architecture? How does it integrate AI models (such as content generation and real-time optimization) with Web3 native elements (such as link-to-earn mechanisms and social graphs) to support project growth? A: XerpaAI’s technical architecture is a highly modular multi-AI Agents system designed to handle complex tasks in Web3 growth, such as automated user acquisition, community expansion, and KOL/KOC matching. We have built the entire system as a collaborative agent network, where each agent focuses on specific subtasks but collaborates seamlessly through shared states and communication protocols (such as blockchain-based smart contract verification). This is a form of multi-agent agentic workflows, where agents can autonomously plan, execute, and optimize action paths, thereby achieving an end-to-end intelligent growth engine. At its core, XerpaAI’s architecture revolves around a central AGA (AI Growth Agent) coordinator that oversees the interactions of multiple dedicated agents, forming a dynamic decision-tree structure. The following is a detailed breakdown from the perspective of multi-AI Agents: Composition of the agent network: – Planning Agent: This is the entry point, responsible for decomposing high-level growth goals (such as “increasing user conversion rates for a DeFi project”) into executable subtasks. It adopts the Plan-and-Solve prompting strategy, an advanced zero-shot reasoning method that first formulates a comprehensive plan (for example, dividing tasks into content generation, KOL matching, and performance optimization) and then solves each subtask step by step. This method addresses the missing steps issue of traditional Zero-Shot Chain-of-Thought (CoT), ensuring that the agent does not skip key reasoning links. For example, when handling a WEB3 viral marketing task, the planning agent will first plan: “Step 1: Analyze the target audience; Step 2: Generate multimodal content; Step 3: Match platform-specific KOLs; Step 4: Monitor real-time feedback.” – Data Collection Agent: Responsible for real-time collection and preprocessing of multi-source data from the Web3 ecosystem (such as blockchain transactions, social graphs, cross-platform user interactions). Data sources include X, Telegram, on-chain activities (such as smart contract interactions), and the social graph of the UXLINK ecosystem. As the input layer of the multi-agent system, the data collection agent provides real-time, structured data streams for other agents (planning, content generation, distribution, optimization, integration), ensuring that decisions are based on the latest insights. For example, it extracts interaction trends from over 110K communities for the planning agent to decompose tasks. – Content Generation Agent: Focuses on creating multilingual, multimodal content (such as text, images, and videos). It utilizes Zero-Shot Chain-of-Thought prompting by adding “Let’s think step by step” to induce step-by-step reasoning, such as deriving personalized narratives from user data without the need for pre-trained examples. This allows the agent to generate high-quality content in a zero-shot setting, supporting cross-platform distribution (such as X, Telegram, and TikTok). – Distribution & Matching Agent: Handles intelligent matching and content distribution within the 100K+ KOL/KOC network. It integrates Web3 native elements such as social graph analysis and link-to-earn mechanisms, using multi-agent collaboration to optimize paths — for example, decomposing the matching process through Plan-and-Solve into “planning a list of potential KOLs, then solving compatibility and incentive allocation”. – Optimization & Feedback Agent: Monitors performance indicators (such as conversion rates and costs) in real-time and adjusts strategies through self-reflection loops. It运用 Zero-Shot CoT to analyze data biases, such as step-by-step reasoning “If the conversion rate is lower than expected, why? Step 1: Check content relevance; Step 2: Evaluate KOL influence; Step 3: Adjust incentives”, thereby achieving a 70% cost reduction and a 3x increase in conversions. – Integration Agent: Bridges AI and Web3 components, ensuring decentralized verification (such as data privacy on the blockchain) and cross-track support (DeFi liquidity incentives, SocialFi community building). Multi-agent collaboration mechanism: Agent communication is achieved through a shared knowledge graph based on GraphRAG technology, allowing real-time data ingestion and reasoning. The central coordinator uses an A* search-inspired algorithm to navigate the action space, avoiding inefficient paths and ensuring efficient execution. We have incorporated Plan-and-Solve as the core reasoning engine to overcome the limitations of Zero-Shot CoT (such as calculation errors or semantic misunderstandings). For example, in a SocialFi project, the planning agent first formulates a plan: “Subtask 1: Identify target communities; Subtask 2: Generate interactive content; Subtask 3: Distribute and optimize”, and then each agent uses Zero-Shot CoT to solve them step by step, avoiding reliance on manual examples. This multi-agent system supports parallel processing and iterative learning: if one agent fails (such as the matching agent not finding a suitable KOL), the feedback agent triggers a reflection loop to re-plan the path. This design follows multi-agent trends, such as inter-agent teaching and optimization in simulated environments. Memories support: XerpaAI enhances the learning and adaptive capabilities of the multi-agent system through a Memories mechanism (based on long-term context storage), storing historical tasks, user preferences, and optimization results, similar to a “near-infinite memory” architecture. This enables agents to reuse knowledge across tasks and continuously improve. Memories are stored in a distributed knowledge graph (based on GraphRAG) combined with a vector database (Milvus) to support efficient retrieval. Each agent (planning, content generation, distribution, optimization, data collection) stores key decisions and results in Memories, such as “A project’s KOL matching increased conversion rates by 3x, and high-interaction KOLs should be prioritized”. As a shared resource, Memories promote collaboration between agents. The data collection agent stores new data in Memories, the content generation agent adjusts its creations accordingly, the distribution agent optimizes KOL matching, and the optimization agent evaluates performance, forming an adaptive loop. Memories endow the system with “memory”, enabling agents to learn historical patterns and optimize future tasks. For example, after a failed viral marketing campaign for a WEB3 project, Memories record the reasons for failure (such as insufficient incentives), and the planning agent adjusts the incentive mechanism for new campaigns accordingly. The essence of XerpaAI’s Memories is to build an external brain for XerpaAI’s users, transforming fragmented knowledge into reusable structured memories through hierarchical storage, dynamic indexing, and MCP protocols. Overall, this architecture makes XerpaAI more than just a tool but an adaptive growth partner that has served over 110K communities. Through the collaboration of multi-AI Agents, coupled with advanced prompting technologies such as Plan-and-Solve and Zero-Shot Chain-of-Thought, we have achieved efficient, zero-shot automation of Web3 growth. If you have specific task examples, I can further demonstrate how these components are applied. 4. In the 2025 AI breakthroughs, small specialized models and inference time computing are becoming focal points. Has XerpaAI adopted similar technologies to handle massive amounts of data (such as 100K+ KOL matching and cross-platform distribution, including X, Telegram, and TikTok)? How does its data analysis engine ensure real-time feedback and self-optimization? A: Yes, we have adopted small specialized models to handle specific tasks such as KOL matching and cross-platform distribution. These models are optimized for Web3 data to reduce inference time. In line with the 2025 trend of inference time computing, our engine uses efficient algorithms to process massive amounts of data, such as real-time matching from over 100K KOLs and distribution across X, Telegram, and TikTok. The data analysis engine ensures self-optimization through machine learning loops: collecting user interaction data, applying reinforcement learning to adjust strategies, and avoiding overfitting. 5. XerpaAI has served over 110K communities. How does it utilize multimodal AI (combining text, images, and social data) to automate user acquisition and community interaction? Compared with current AI trends such as near-infinite memory and custom silicon, what are XerpaAI’s innovations in edge computing or cloud integration? A: XerpaAI utilizes multimodal AI to process text, images, and social data, such as generating image-enhanced content or analyzing social graphs to automate interactions, and has served over 110K communities. Compared with 2025 trends such as near-infinite memory, we have innovated in cloud integration by using distributed computing to process large-scale data; in terms of edge computing, we have optimized mobile agents to ensure low-latency interactions, such as real-time responses to user queries in Telegram groups. 6. XerpaAI has a network of over 100K KOLs/KOCs. How does it serve these influencer groups through AI tools (such as personalized content generation and incentive optimization) to help them improve monetization efficiency and community interaction, thereby establishing a mutually beneficial channel advantage? Considering 2025 AI trends such as personalized agents, how do you think this will amplify the viral spread of Web3 projects? A: XerpaAI’s 100K+ KOL/KOC network is the core of our channel advantage. Through AI tools such as personalized content generation and incentive optimization, we provide tailored services to these influencers to help them improve monetization efficiency and community interaction. For example, our AGA engine uses multimodal AI to generate exclusive content (such as images, video scripts, or posts targeting specific audiences) and maximizes their income through real-time incentive optimization (such as dynamically adjusting revenue sharing ratios based on interaction data) — this can increase KOLs’ monetization efficiency by 2-3 times while enhancing community stickiness, such as automated replies and gamified interactions. The result is mutual benefit: influencers gain more exposure and revenue, while we expand our distribution channels through their networks. In the 2025 AI trends, personalized agents (such as custom AI assistants) are dominating the influencer economy, and XerpaAI is a pioneer in this application — our agents can autonomously learn KOL preferences and predict trends, thereby amplifying the viral spread of Web3 projects. For example, in a DeFi campaign, through KOCs’ micro-sharing chains, exponential user growth can be achieved, with conversion rates increasing by more than 5 times. 7. When serving KOLs/KOCs, what strategies has XerpaAI adopted to ensure data privacy and fair revenue sharing (such as through blockchain-verified link-to-earn mechanisms) to cultivate long-term loyalty? How does this channel advantage translate into a competitive barrier for startups, especially in multi-platform distribution (such as X, Telegram, and TikTok)? A: When serving KOLs/KOCs, we prioritize Web3-native strategies to ensure data privacy and fair revenue sharing: all interaction data is verified through the blockchain (such as using zero-knowledge proofs to store anonymized information) to prevent leakage; the link-to-earn mechanism automatically executes revenue sharing based on smart contracts, ensuring transparency and instant payments (such as token rewards based on interaction metrics), which cultivates long-term loyalty — our retention rate exceeds 85%. This channel advantage translates into a competitive barrier for startups: in multi-platform distribution (such as real-time tweets on X, group interactions on Telegram, and short videos on TikTok), our network forms a “moat”, providing exclusive access and optimized paths, helping enterprises bypass traditional advertising bottlenecks and achieve low-cost, high-efficiency growth. For example, a WEB3 project covered 5 million users in 3 weeks through our KOL/KOC channels, while competitors needed several months. 8. In 2025, with the rise of AI agents, data privacy and algorithmic bias are key challenges. As a Web3 & AI-native platform, how does XerpaAI ensure transparency and decentralization (such as through blockchain verification)? What are its considerations regarding AI ethics? A: Data privacy and algorithmic bias are crucial. As a Web3 & AI-native platform, we ensure transparency through blockchain verification, such as using decentralized storage to protect user data and conducting fairness audits to avoid bias. Our AI ethical considerations include: anonymization of all model training data, user-controllable opt-out mechanisms, and regular third-party audits to comply with regulatory trends. 9. XerpaAI recently secured $6 million in seed funding, led by UFLY Capital. How will this funding be used for expansion? Please share a specific case, such as how it helped a Web3 startup achieve growth from scratch, highlighting its role in user acquisition and community building. A: This $6 million seed funding will be used for product iteration, international expansion (such as team recruitment in Silicon Valley, Tokyo, and Singapore), and ecosystem integration. A typical case is our assistance to a Web3 startup: starting from scratch, our AGA generated multilingual content, distributed it through the KOL network, built a community graph, and ultimately acquired 100,000 users within one month, with community activity increasing by 2 times. This highlights our role in user acquisition and community building. 10. Looking to the future, how will XerpaAI integrate into broader AI trends such as personalized AI agents or automated investment? What are the company’s next technical iteration plans? What advice do you have for AI entrepreneurs to cope with the dynamic changes in Web3 growth? A: In the future, XerpaAI will integrate into the trend of personalized AI agents, such as custom growth paths, and explore automated investment modules. The next iteration includes enhancing multimodal capabilities (such as video generation) and deeper Web3 integration. Advice for AI entrepreneurs: focus on pain points such as growth automation, embrace agentic AI, and build ecosystem partnerships to cope with the dynamic changes in Web3 — for example, monitor real-time trends and iterate quickly. XerpaAI’s service capabilities will also empower KOLs/KOCs, enabling this group to enhance their respective influence with the help of XerpaAI. 11. As CTO, what is your greatest expectation for the integration of AI and Web3? How does XerpaAI help more startups “connect, expand, and dominate the market”? Finally, what would you like to say to potential partners or users? A: As CTO, my greatest expectation for the integration of AI and Web3 is to realize a truly decentralized intelligent economy, where AI Agents such as XerpaAI drive intelligent growth. XerpaAI will help more startups “connect, expand, and dominate the market” through our AGA engine, providing end-to-end support from content to optimization. Finally, to potential partners and users: join us to speed up your growth — welcome to visit xerpaai.com to try it out, or DM us to discuss cooperation!
BitcoinWorld What is Magic School AI and Why is it Becoming Essential for Educators? As of August 26, 2025 , Magic School AI is a leading generative AI platform designed specifically for the education sector. It offers educators a suite of over 60 specialized tools aimed at reducing administrative burnout, streamlining time-consuming tasks, and creating more effective, personalized learning experiences for students. Its rapid popularity stems from its ability to directly address critical challenges in education, such as saving teachers valuable time, supporting diverse student needs, and providing a safe, structured framework for integrating AI technology into the classroom. Key Features for Educators Magic School AI provides a comprehensive toolkit to support teachers in every aspect of their work, from planning to parent communication. Curriculum and Lesson Planning: The platform instantly generates high-quality lesson plans, academic content, and learning objectives aligned with specific topics, grade levels, and educational standards. Differentiation and Accessibility: It empowers teachers to rewrite texts for various reading levels, create specific accommodations for students with IEPs (Individualized Education Programs), and translate materials into over 25 languages to support multilingual learners. Assessment and Feedback: Users can automatically create multiple-choice quizzes, formative assessments, and detailed rubrics for assignments, significantly cutting down on grading and preparation time. Professional Communication: The platform includes tools to draft professional emails to parents and generate personalized, constructive report card comments. AI Teaching Assistant: A dedicated AI chatbot named Raina acts as an on-demand instructional coach, helping educators brainstorm ideas, find resources, and answer pedagogical questions. Student-Facing Tools: MagicStudent The platform extends its capabilities to students through a supervised environment called MagicStudent , designed to build foundational AI skills responsibly. AI Literacy Development: It provides a safe, teacher-monitored space for students to learn how to use generative AI tools ethically and effectively for academic purposes. Personalized Study Aids: Students gain access to AI-powered tutors and study partners, as well as tools that can summarize complex texts and generate digital flashcards. Creative and Interactive Learning: MagicStudent includes engaging tools that allow students to interact with historical figures via chatbot, generate creative content like songs, and produce AI-generated images for projects. Why Magic School AI is Gaining Popularity The platform’s success is directly linked to its focus on solving core problems faced by modern educators and school districts. Directly Addresses Teacher Burnout: By automating administrative tasks, Magic School AI claims to save educators an average of 10 hours per week , freeing them up to focus on high-impact teaching rather than paperwork. Enhances Personalization and Inclusivity: The tools make it simple for a single teacher to differentiate instruction and meet the unique needs of a diverse classroom, ensuring every student receives the support they need to succeed. Prioritizes Data Privacy and Safety: The platform is built to comply with strict school safety and privacy regulations like FERPA . All student-facing tools are supervised by teachers, ensuring a secure learning environment. Makes AI Technology Accessible: Unlike general-purpose AI models such as ChatGPT , Magic School AI offers a user-friendly interface with tools specifically organized for educational functions, lowering the barrier to entry for teachers. Builds Essential Future-Ready Skills: By providing a structured environment for AI use, the platform helps schools prepare students for an AI-integrated world and a future workforce where AI literacy is a fundamental skill. Strategic Importance for Modern Education In an era of increasing teacher workloads and diverse student needs, failing to leverage purpose-built AI tools is a significant strategic disadvantage. Platforms like Magic School AI are no longer just a novelty; they are becoming essential infrastructure for schools aiming to improve teacher retention, close achievement gaps, and prepare students for the future. Adopting these tools is a critical step for any educational institution focused on efficiency and improved student outcomes. This post What is Magic School AI and Why is it Becoming Essential for Educators? first appeared on BitcoinWorld and is written by Keshav Aggarwal
BitcoinWorld Bitcoin (BTC) Plummets, BTC Holders Earn $9K Daily Through Contracts Bitcoin whale dumped 24,000 BTC, triggering a market crash that sent the price plummeting by $110,000. Depressed market sentiment led to the liquidation of numerous leveraged long positions, triggering a sell-off among retail investors. At the same time, GoldenMining launched a new Bitcoin mining contract to mitigate the risk of falling Bitcoin prices and help Bitcoin holders generate daily returns. What is GoldenMining? GoldenMining is a platform that provides computing services to users worldwide. We eliminate the tedious process of purchasing, installing, and hosting mining machines, allowing you to earn stable returns with a small investment. Our mission is to provide a seamless investment experience and professional project management for anyone interested in cryptocurrency cloud mining, regardless of their experience level. How to participate in GoldenMiningBTC mining contracts Sign up for a free account on the GoldenMining platform and receive $15. Log in daily to earn $0.6. GoldenMining offers a variety of contract plans designed to meet diverse investment needs and budgets. Users can flexibly choose the most suitable plan based on their circumstances and easily begin their cloud mining journey. Popular mining contract recommendations [Daily Sign-in Reward]: Deposit $15, 1-day contract, daily profit $0.60, total profit $15 + $0.60 [New User Contract]: Deposit $100, 2-day contract, daily profit $4, total profit $100 + $8 [Bitmain Antminer S23 Hyd]: Deposit $650, 5-day contract, daily profit $8.45, total profit $650 + $42.25 [Antminer L9 16GH]: Deposit $1500, 12-day contract, daily profit $20.25, total profit $1500 + $243 [Antminer L9 17GH]: Deposit $3500, 18-day contract, daily profit $48, total profit $3500 + $882 [Elphapex DG2: Investment: $6,000, 30-day contract, daily profit of $87, total return of $6,000 + $2,610 Elphapex DG2+: Investment: $12,500, 38-day contract, daily profit of $212.5, total return of $12,500 + $8,075 ANTSPACE HD5: Investment: $55,000, 47-day contract, daily profit of $1,056, total return of $55,000 + $49,632 GoldenMining Advantages GoldenMining boasts a 24/7 online team of certified professionals specializing in cryptocurrency mining, blockchain technology, cryptocurrency finance, and security. Users are free from traditional constraints, eliminating the need to purchase expensive equipment or consume energy. Simply purchase contract to start mining and receive profits the next day. The platform supports deposits and withdrawals of multiple cryptocurrencies: DOGE, ADA, BTC, ETH, SOL, XRP, USDC, LTC, USDT-TRC20, USDT-ERC20, etc. The user-friendly interface is suitable for both novice and experienced miners. Full funds are transparent, pricing is transparent, and there are no handling or management fees. The affiliate program allows users to earn up to 3% + 2% referral rewards. Green and efficient infrastructure: Deployed in global green energy bases, effectively reducing operating costs and practicing environmental protection concepts. Fund security: At GoldenMining, user funds are securely stored in a tier-one bank, and all user personal information is protected by SSL encryption. The platform provides insurance for every investment, underwritten by AIG Insurance. Summarize GoldenMining introduces a hybrid model that combines smart contract technology with stable passive income. This model supports environmentally friendly blockchain operations while mitigating the risks associated with price volatility. For BTC holders and broader cryptocurrency investors, it offers a new paradigm—one that combines income stability with environmental responsibility. As market uncertainty persists, fixed-income mining contracts are likely to become a crucial component of crypto asset allocation strategies. Platforms like GoldenMining are paving the way. For more information, please visit GoldenMining’s official website: https:// www.goldenmining.com Or contact us via email: info@goldenmining.com This post Bitcoin (BTC) Plummets, BTC Holders Earn $9K Daily Through Contracts first appeared on BitcoinWorld and is written by Keshav Aggarwal