What truly motivates the corporate crackdown on remote and hybrid work, and why your work-from-home days may be numbered.

The Real Reasons Companies Are Forcing You Back To The Office

Is BlackBerry’s rally over? If you are looking for another good rally, consider adding this Canadian AI stock to your watchlist. The post Move Over, BlackBerry: This AI Stock Is the Real Deal for Canadian appeared first on The Motley Fool Canada.

Move Over, BlackBerry: This AI Stock Is the Real Deal for Canadian

NVIDIA engineers have developed an AI-powered neural network capable of generating ultra realistic virtual characters in real-time. Technically speaking, a neural network-based simulation super-resolution framework that can efficiently and realistically enhance a facial performance produced ...

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RWPQC 2025 Unites Industry Leaders to Drive Cybersecurity and Quantum Innovation - IT Security Guru

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If Elon Musk Had Any Real Guts, He Would Go After the Gigantic Budget of the US Military

A Gaming Leaderboard is a ranked list of players, typically sorted by a specific metric such as score, points or level.

System Design of a Real-Time Gaming Leaderboard

Real

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While billion-dollar crypto heists like the Bybit hack dominate headlines, there are threats that are far more subtle and more disruptive than any data breach. I have recently interviewed Alex Ferrer, Director of Forensics at Crypto Legal, who once again reminded me of how often we cybersecurity reporters fail to keep our readers’ eyeballs where they should be. Take the recent Bybit Hack as an example: “Everyone’s shocked by big numbers in a single hack… But phishing is death by a thousand cuts-quiet, constant, and devastating.” “Everyone’s shocked by big numbers in a single hack… But phishing is death by a thousand cuts-quiet, constant, and devastating.” So let’s unpack his warning about the true scale of phishing in crypto, what loopholes in internet infrastructure are making the problem worse, and why regulators urgently need to rethink their approach to this. With scammers outpacing security teams using AI and automation, this isn’t just a crypto issue - it’s a growing threat to consumer trust, financial systems, and digital safety as a whole. Numbers speak Phishing scams are quietly stealing just as much (if not more) than the most publicized hacks every few months. Just CoinMarketCap data shows phishing accounted for an estimated $1.05 billion in crypto losses in 2024-roughly 40% of all stolen crypto that year. every few months But the real damage goes far beyond money: But the real damage goes far beyond money: Phishing fuels ransomware and terrorism – In one case, £2.3 million from a fake NFT platform was traced to a sanctioned entity.
Victims aren’t always crypto users – A retired couple wired £45,000 to scammers impersonating police to “unfreeze” crypto their son never even owned.
Some web hosting companies and domain registrars are enabling it – Ferrer’s team reported 132 fraudulent sites to a major registrar this year. Only 17 were removed. Some providers even charge for takedowns-creating a perverse incentive to delay. Phishing fuels ransomware and terrorism – In one case, £2.3 million from a fake NFT platform was traced to a sanctioned entity. Victims aren’t always crypto users – A retired couple wired £45,000 to scammers impersonating police to “unfreeze” crypto their son never even owned. Some web hosting companies and domain registrars are enabling it – Ferrer’s team reported 132 fraudulent sites to a major registrar this year. Only 17 were removed. Some providers even charge for takedowns-creating a perverse incentive to delay. “Crypto exchanges are heavily regulated. Hosting providers? Almost zero oversight. Until that changes, phishing will keep thriving-and evolving with AI.” “Crypto exchanges are heavily regulated. Hosting providers? Almost zero oversight. Until that changes, phishing will keep thriving-and evolving with AI.” “Crypto exchanges are heavily regulated. Hosting providers? Almost zero oversight. Until that changes, phishing will keep thriving-and evolving with AI.” Crypto Legal tracks over 100 new phishing domains weekly and runs the free public Crypto Legal Scam Hub, with 50,000+ entries to help victims verify threats. Even so, he admitted, "For every domain we report, three more emerge.” The good news is that many phishing attacks can be avoided with stronger habits, smarter tech, and clearer accountability from the companies that power the web. What you can do I asked Ferrer what people should  start doing today to prevent crypto phishing scams. Here are his tips: Never trust links from search ads - Always use in-app support
Bookmark sites you trust - Typosquatting like Binancce[.]com is rampant
Use hardware multi-factor authentication (MFA) - SMS-based two-factor authentication (2FA) is vulnerable to SIM Swapping (when an attacker socially engineers a mobile provider or bribes an insider into transferring your phone number to a SIM card they control), and does not prevent phishing
Search "Crypto Legal Scam Hub" to check for known scam sites
Report anything suspicious - To registrars, the NCSC, and Action Fraud Never trust links from search ads - Always use in-app support Never trust links from search ads Bookmark sites you trust - Typosquatting like Binancce[.]com is rampant Bookmark sites you trust Binancce[.]com Use hardware multi-factor authentication (MFA) - SMS-based two-factor authentication (2FA) is vulnerable to SIM Swapping (when an attacker socially engineers a mobile provider or bribes an insider into transferring your phone number to a SIM card they control), and does not prevent phishing Use hardware multi-factor authentication (MFA) not Search "Crypto Legal Scam Hub" to check for known scam sites Search "Crypto Legal Scam Hub" Report anything suspicious - To registrars, the NCSC, and Action Fraud Report anything suspicious What the big guys should do Ferrer’s tips will help people stay safer only to a certain extent, since the problem isn’t just the scammers. It’s the system that lets them flourish: hosting providers that ignore abuse, regulators that overlook infrastructure, and consumers left fighting sophisticated scams with outdated tools. Otherwise, we’re fighting with toothpicks against AI-powered hydras. Scammers are counting on that.

Forget The Bybit Hack - This is the REAL Crypto Epidemic Fueling Global Crime

When one hears the phrase "dark web", it usually evokes visions of illicit transactions, hoodie-wearing hackers, and clandestine operations. Yes, some of that does occur, but the dark web is really more complicated and less Hollywood than what films or the news portray. Here in this blog, let's get deep into the dark web—what it is, what it isn't, and debunk myths vs. reality—all in simple, bite-sized language. What is the Dark Web? The dark web is a portion of the internet that isn't searched by engines like Google, Bing, or Yahoo. You need special programs like Tor (The Onion Router) or I2P (Invisible Internet Project) to access it. Unlike the “surface web” (what most of us use daily), the dark web isn’t directly accessible through normal browsers. It’s part of a broader category known as the deep web, which includes any content that requires a login, like your Gmail inbox or bank account. But the dark web is a smaller, intentionally hidden portion of this deep web. Myth #1: The Dark Web is 100% Illegal Reality: Not all on the dark web is criminal. Yes, the dark web does have illegal marketplaces, stolen information, and other illicit services. But not all of it is criminal. Some websites and communities use the dark web for privacy. For instance: Whistleblowers provide information without putting their safety at risk.


Journalists communicate securely with sources.


Citizens in repressive nations get uncensored news and services. Whistleblowers provide information without putting their safety at risk. Whistleblowers provide information without putting their safety at risk. Journalists communicate securely with sources. Journalists communicate securely with sources. Citizens in repressive nations get uncensored news and services. Citizens in repressive nations get uncensored news and services. Actually, organizations such as The New York Times, BBC, and ProPublica have mirror sites of their websites on Tor precisely for this reason. Myth #2: The Dark Web is One Giant Black Market Reality: Markets do exist, but it's more than that. Yes, you can discover illicit marketplaces on the dark web selling weapons, drugs, false IDs, and stolen data. One of the most notorious examples was Silk Road, a dark web marketplace seized by the FBI in 2013. However, the dark web is also inhabited by: Political discussion forums


Privacy-conscious communities


Libraries of prohibited books or censored material


Tech enthusiasts and security researchers Political discussion forums Political discussion forums Privacy-conscious communities Privacy-conscious communities Libraries of prohibited books or censored material Libraries of prohibited books or censored material Tech enthusiasts and security researchers Tech enthusiasts and security researchers It's not only a black market—it's an entire ecosystem of multiple purposes, good and evil. Myth #3: You'll Get Hacked Instantly Reality: It's not inherently dangerous—but caution is a must. The dark web itself will not hack you for visiting it. But yes, it can be dangerous if you're irresponsible. Risks include: Clicking malicious links


Downloading infected software


Posting personal data


Trusting strangers or phishing sites Clicking malicious links Clicking malicious links Downloading infected software Downloading infected software Posting personal data Posting personal data Trusting strangers or phishing sites Trusting strangers or phishing sites If you're on the dark web, it's important to: Use a VPN + Tor for extra anonymity
Never download files or share personal information
Not click random links
Only use sites with established reputations Use a VPN + Tor for extra anonymity Never download files or share personal information Not click random links Only use sites with established reputations Myth #4: You Can Be Totally Anonymous Reality: Complete anonymity is difficult—but Tor makes it easier. Tor conceals your IP address by routing your connection through multiple nodes around the globe. This provides you with a degree of anonymity, but it's not guaranteed. Governments and skilled attackers have de-anonymized users before through: Malware


JavaScript exploits


Misconfigured browsers


Revealing personal info accidentally Malware Malware JavaScript exploits JavaScript exploits Misconfigured browsers Misconfigured browsers Revealing personal info accidentally Revealing personal info accidentally If anonymity is your goal, remember: Disable JavaScript in your Tor browser
Don’t log in to any real-world accounts (like Gmail, Facebook)
Don’t use your real name or identity anywhere Disable JavaScript in your Tor browser Don’t log in to any real-world accounts (like Gmail, Facebook) Don’t use your real name or identity anywhere Myth #5: Law Enforcement Can’t Access the Dark Web Reality: They can—and they do. While the dark web is anonymous by design, it’s not invisible to law enforcement. Agencies have: Infilitrated marketplaces


De-anonymized server locations


Located cybercriminals through errors that they committed


Utilized advanced traffic analysis tools Infilitrated marketplaces Infilitrated marketplaces De-anonymized server locations De-anonymized server locations Located cybercriminals through errors that they committed Located cybercriminals through errors that they committed Utilized advanced traffic analysis tools Utilized advanced traffic analysis tools The shut down of markets such as AlphaBay, Hansa, and Silk Road illustrates that criminals aren't safe because they are in the dark web. So no—the dark web isn't some lawless wasteland. Police are monitoring it, and people using it to commit crimes can and do get arrested. Myth #6: The Dark Web is Only for Criminals and Hackers Reality: It's a tool, just like any aspect of the internet. Imagine the dark web as a technology platform—similar to email or social media. It's up to the user how it's used. Though it's become a haven for cybercriminals, it's also used: Activists


Whistleblowers


Reporters


Daily users who want to be private Activists Activists Whistleblowers Whistleblowers Reporters Reporters Daily users who want to be private Daily users who want to be private Most times, individuals use the dark web not to be a criminal, but to escape surveillance, censorship, or data collection from big companies. Do You Go to the Dark Web? It depends on why you're interested. If you're merely browsing for knowledge or to know how it functions, that's okay—as long as you're safe and ethical. Safe Browsing Tips: Download the official Tor Browser
Use a VPN before booting up Tor
Don't disclose your true identity
Avoid downloading anything
Never trust a site blindly—scams happen everywhere Download the official Tor Browser Use a VPN before booting up Tor Don't disclose your true identity Avoid downloading anything Never trust a site blindly—scams happen everywhere Final Thoughts The dark web isn't evil in and of itself, but it's not totally safe, either. Like any technology, it's a double-edged sword—capable of both safeguarding freedom and facilitating harm. If you ever decide to go there, do it with eyes wide open, on your toes, and with a purpose in mind. Don't believe everything you hear, nor should you act hysterically based upon some myth or urban legend. The point to take away? The Dark Web is just a tool-in how it gets used is the actor.

So How Scary is The Dark Web Really?

Science fiction has always pushed the boundaries of our imagination. From movies like Star Wars to books by Arthur C. Clarke, these stories introduced big ideas like space travel, robots, and satellite networks long before they became real. Today, many of those once-impossible dreams are part of everyday life. Star Wars This article explores how science fiction has influenced real-world space technology. I will also look at how a modern project called Spacecoin continues that journey by using satellites to make money and communication more accessible worldwide. Spacecoin Spacecoin How Sci-Fi Sparked Innovation How Sci-Fi Sparked Innovation Science fiction, or “sci-fi,” is more than just entertainment. It allows writers and creators to imagine the future freely without worrying about cost or current technology. That freedom often leads to ideas that scientists and engineers may later turn into reality. Arthur C. Clarke’s Satellite Vision In 1945, sci-fi writer Arthur C. Clarke wrote an article describing a network of satellites that could send signals around the world. This idea didn’t exist in real life, but it inspired scientists to make it happen. Today, satellites power GPS, the global internet, and phone networks. article Star Trek’s High-Tech Tools The Star Trek TV series showed people using handheld communicators (like today’s cell phones), tablets, and voice-controlled computers. These tools seemed like science fiction in the 1960s. Now, we use similar devices every day. Many engineers say Star Trek helped shape their careers. Star Trek Star Trek Real Tech That Started in Sci-Fi Real Tech That Started in Sci-Fi Let’s look at real space technologies today that first appeared in sci-fi stories or shows. Starlink: Internet from the Sky SpaceX’s Starlink uses thousands of satellites to bring internet access to places without it. This idea of satellite-based communication has been featured in many sci-fi books and movies. Starlink In those stories, people living on other planets or in remote areas use space technology to stay connected, just like Starlink does now. Mars Rovers: Robots on Another World NASA’s Mars rovers, like Perseverance, drive around the surface of Mars, studying rocks and soil. These smart robots are similar to the droids in Star Wars or the robots from older movies like Forbidden Planet (1956). Sci-fi excited people about space robots, which helped push real science forward. Perseverance Star Wars Forbidden Planet Reusable Rockets Many rockets used to burn up after a single trip to space. Sci-fi stories often imagined rockets landing safely and being used again, like in the Thunderbirds show or Robert A. Heinlein's books. Today, companies like SpaceX reuse rockets to save money and reduce waste. Thunderbirds Spacecoin: Sci-Fi Ideas Meet Modern Tech Spacecoin: Sci-Fi Ideas Meet Modern Tech Spacecoin is a new project that uses satellites to build a different financial system. It allows people to send and receive digital money (cryptocurrency) without needing internet or cell service. Spacecoin Why Use Satellites? Most digital money systems depend on the Internet. But what if you’re in a place without connection, like a remote village or during a natural disaster? With satellite networks, Spacecoin lets people make secure payments from almost anywhere on Earth. This idea sounds like it’s from a sci-fi movie. In many stories, people in space or off-grid locations still manage to trade and communicate using satellite tools. Spacecoin makes that vision real. Sci-Fi Parallels In the show Firefly, people trade across planets using space-based systems. Spacecoin does something similar here on Earth.
In books like Snow Crash, people use digital money controlled by smart contracts. Spacecoin uses blockchain to do just that.
In many sci-fi stories, privacy and freedom are protected through high-tech systems. Spacecoin offers those same protections through encryption and decentralized tools. In the show Firefly, people trade across planets using space-based systems. Spacecoin does something similar here on Earth. Firefly In books like Snow Crash, people use digital money controlled by smart contracts. Spacecoin uses blockchain to do just that. Snow Crash In many sci-fi stories, privacy and freedom are protected through high-tech systems. Spacecoin offers those same protections through encryption and decentralized tools. How Sci-Fi and Real Tech Inspire Each Other How Sci-Fi and Real Tech Inspire Each Other The connection between science fiction and real technology works both ways: Sci-fi shows bold new ideas.
Engineers and scientists get inspired and build them.
These new inventions give writers new material for future stories. Sci-fi shows bold new ideas. Engineers and scientists get inspired and build them. These new inventions give writers new material for future stories. For example, after Starlink became popular, sci-fi books started featuring more believable space-based internet systems. For example, after Starlink became popular, sci-fi books started featuring more believable space-based internet systems. Now that satellite-based money like Spacecoin is real, writers are beginning to include it in their stories, too. Movies and TV Help Us Understand Space Movies and TV Help Us Understand Space Movies don’t just entertain, they also teach. When The Martian came out in 2015, it showed what life might be like for someone stuck on Mars. NASA helped with the film to ensure it was mostly accurate. The movie helped people understand the science and sparked interest in space careers. The Martian Even Elon Musk, founder of SpaceX and Tesla, has said movies like Iron Man and Blade Runner influenced him. Those futuristic styles can be seen in Tesla dashboards and SpaceX space suits. Big Challenges Ahead Turning sci-fi into real life isn’t always easy. There are still many challenges: Money: Some ideas are too expensive to build today.
Ethics: Real-world tech must consider safety, privacy, and fairness, something sci-fi sometimes ignores.
Science Limits: Some concepts, like faster-than-light travel, are impossible. Money: Some ideas are too expensive to build today. Money Ethics: Real-world tech must consider safety, privacy, and fairness, something sci-fi sometimes ignores. Ethics Science Limits: Some concepts, like faster-than-light travel, are impossible. Science Limits Still, sci-fi gives us a direction to explore. Even when an idea isn’t possible now, it can spark research that leads to discoveries. A Future Powered by Satellites Spacecoin is just one example of using satellite tech for more than communication. Similar systems could support: Remote learning, where students in faraway places get access to the same lessons as city schools.
Emergency support, where rescue teams use satellite networks after disasters.
Health care is where doctors are advised by satellite in areas without hospitals. Remote learning, where students in faraway places get access to the same lessons as city schools. Remote learning Emergency support, where rescue teams use satellite networks after disasters. Emergency support Health care is where doctors are advised by satellite in areas without hospitals. Health care Sci-fi dreamed of a future where space tech helps everyone. With Spacecoin and projects like it, that future is starting now. Final Thoughts Science fiction shows us what is possible, gets us excited about the future, and sometimes helps make that future real. From Arthur C. Clarke’s satellite vision to SpaceX’s Starlink and now Spacecoin’s global mission, sci-fi has guided innovation for decades. Ideas once only found in books and movies are now part of our daily lives. And as we continue to build the future, sci-fi will keep lighting the way.

Sci-Fi to Sky-Fi: How Pop Culture Inspired Real-World Space Tech

At this time, it would be unusual for an industry not to have a place in the world of decentralized ledgers and cryptocurrencies. Everyone can offer something here. Memecoins, for instance, offer basically nothing besides fun, but we also have the other side of the coin with Real-World Assets (RWA) tokens and platforms. Just as the name suggests, they offer assets that already exist in the real world (the world outside of crypto) through tokenization features. To go into detail, Real-World Assets (RWAs) refer to physical or traditional financial assets that can be represented as digital tokens on a crypto network. These assets, which may include real estate, commodities, bonds, and art, hold intrinsic value and are widely recognized in global financial markets. To go into detail, Real-World Assets (RWAs) refer to physical or traditional financial assets that can be represented as digital tokens on a crypto network. The process of tokenizing RWAs involves converting ownership rights into ledger-based tokens, allowing these assets to be traded and accessed in a decentralized manner. Now, for practical reasons, every time you see the term “RWA” inside crypto, they’ll likely be talking about the tokens and platforms related to this concept, and not exactly to the assets involved. The process of tokenizing The process of tokenizing One of the most significant advantages of RWA tokenization is its ability to improve liquidity. Unlike traditional asset markets, which often involve complex transactions and lengthy processing times, crypto-based RWAs enable instant and global trading. Additionally, tokenization allows for fractional ownership, lowering entry barriers for investors who might otherwise be excluded due to high capital requirements —not everyone can buy a whole house, for instance, but a lot of people could hold a fraction of it and enjoy the benefits. RWA Use Cases Real-World assets (RWAs) have the potential to revolutionize various industries by making traditionally illiquid assets more accessible and flexible. One major use case is in government and corporate bonds, where tokenization allows investors to purchase small portions of these financial instruments instead of needing large sums of money upfront. This fractional ownership makes bond investments more inclusive while maintaining the benefits of Distributed Ledger Technology (DLT), such as enhanced transparency and instant transactions. In real estate, RWAs enable fractional property ownership, lowering the barriers to entry. Instead of purchasing an entire building, investors can buy tokens representing a share of a property and earn rental income. This simplifies real estate investment, making it more transparent and accessible. Additionally, tokenized industrial properties like warehouses and factories provide businesses with easier capital-raising options while offering investors a diversified portfolio. In real estate, RWAs enable fractional property ownership, lowering the barriers to entry. Instead of purchasing an entire building, investors can buy tokens representing a share of a property and earn rental income. RWAs also apply to physical commodities and collectibles, allowing fractional ownership of precious metals, artwork, and machinery. Instead of buying a whole gold bar or a rare painting, individuals can invest in small shares, benefiting from potential appreciation. As the adoption of RWAs grows, industries will continue to explore how tokenization can optimize asset ownership, increase market efficiency, and create new economic opportunities. RWAs in Obyte Obyte provides a cost-effective and accessible way to create tokenized RWAs, making it an appealing platform for both beginners and experts. As a decentralized, DAG-based system, Obyte eliminates intermediaries while ensuring seamless transactions. Users can generate custom tokens either with coding for advanced configurations or without coding through a simple online tool. This flexibility allows businesses and individuals to tokenize a wide range of assets, from financial instruments to loyalty rewards, without incurring high costs. Obyte Obyte Users can generate custom tokens either with coding for advanced configurations or without coding through a simple online tool. Unlike other networks, where tokens require separate smart contracts for transactions, Obyte treats all tokens equally, just like its native currency, GBYTE. This means transfers happen smoothly within the core protocol, reducing complexity and potential errors. Transaction fees are minimal, often less than $0.01, making it ideal for frequent and small-value transfers. Additional token features include adjustable supply, privacy settings, and regulatory compliance options, like requiring verified users for transfers. all tokens all tokens A notable real-world application of Obyte’s tokenization is Aufort, a European investment firm that represents gold holdings using Obyte's DAG network. This enables instant and global transactions while maintaining a custodial model for simplicity. Beyond this, Obyte’s tokenization tools can be used for any kind of fractional ownership, internal business credits, or custom digital assets tailored to specific needs. Obyte gives you the power to decide—no middlemen, no high costs, just your vision made real on-chain. Obyte’s tokenization tools Obyte’s tokenization tools Featured Vector Image by Freepik Featured Vector Image by Freepik Freepik Freepik

Educational Byte: What are Real-World Assets (RWA) Tokens in Crypto?

Opvoedkundige Byte: Wat is Real-World Assets (RWA) Tokens in Crypto?

Адукацыйны байт: Што такое рэальныя сусветныя актывы (RWA) токены ў крыпта?

Uddannelsesbyte: Hvad er real-world assets (RWA) tokens i Crypto?

Byte educativo: ¿Qué son los tokens de activos del mundo real (RWA) en Crypto?

Byte educativo: cosa sono i token del mondo reale (RWA) in Crypto?

教育バイト:仮想通貨における現実世界の資産(RWA)トークンとは何ですか?

ការបណ្តុះបណ្តាលបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តុះបណ្តាល

Образовни бајтови: Што се реалниот свет средства (RWA) токени во крипто?

د زده کړې بیټ: په Crypto کې د حقیقي نړۍ د اټکلونو (RWA) ټوکنونه څه دي؟

Byte educacional: O que são tokens de ativos do mundo real (RWA) em criptografia?

Dubai, UAE, April 10th, 2025/Chainwire/--Zodor has announced the launch of its live, enterprise-grade tokenization infrastructure, developed to facilitate the secure and compliant issuance of real-world assets (RWAs). The platform will hold a fair token launch on April 15, with no pre-sale, providing access to tokenized assets for both institutional and retail participants. The blockchain platform, focused on advancing the tokenization of RWAs, introduces a full-stack infrastructure designed to support tokenized equity, debt, and renewable energy assets. Zodor’s end-to-end ecosystem emphasizes compliance, security, and accessibility for a broad range of users. The tokenization of RWAs is projected to become a $16 trillion market by 2030. However, the current ecosystem remains fragmented and largely conceptual. Zodor aims to address this gap with a production-ready infrastructure that prioritizes compliance, scalability, and privacy. “Zodor was built to bridge traditional finance with decentralized systems in a practical, regulation-friendly way,” said Allen C James, Co-Founder & CSO at Zodor. “We’ve spent years building a platform that is not only technically sound but also aligned with real-world legal and operational standards.” “Zodor was built to bridge traditional finance with decentralized systems in a practical, regulation-friendly way,” said Allen C James, Co-Founder & CSO at Zodor. “We’ve spent years building a platform that is not only technically sound but also aligned with real-world legal and operational standards.” Zodor’s Four Core Verticals Include: Zodor Infra: Secure, scalable infrastructure for compliant RWA issuance and trading.
Zodor Capital: A decentralized capital platform enabling startups and SMEs to raise funding directly from global investors.
Zodor Energy: A vertical focused on tokenizing renewable energy and climate-impact projects.
Zodor Infinity: A no-code platform that allows businesses to tokenize revenue, equity, or debt—similar to a decentralized version of Shopify for tokenized economies. Zodor Infra: Secure, scalable infrastructure for compliant RWA issuance and trading. Zodor Capital: A decentralized capital platform enabling startups and SMEs to raise funding directly from global investors. Zodor Energy: A vertical focused on tokenizing renewable energy and climate-impact projects. Zodor Infinity: A no-code platform that allows businesses to tokenize revenue, equity, or debt—similar to a decentralized version of Shopify for tokenized economies. A Unique Approach to Compliance and Privacy Zodor’s infrastructure incorporates advanced cryptographic tools, including Paillier homomorphic encryption, which enables privacy-preserving transactions while maintaining regulatory alignment. This focus on privacy and compliance makes Zodor a viable gateway for institutions seeking exposure to the crypto space. Key Launch Details: No pre-sale or insider allocations
Fair token launch on April 15
Products are live and accessible
Built for both institutional and retail users No pre-sale or insider allocations Fair token launch on April 15 Products are live and accessible Built for both institutional and retail users Targeted Use Cases and Global Focus Rather than attempting to tokenize all asset classes, Zodor concentrates on high-impact sectors, including: Revenue-generating startups seeking capital
Renewable energy projects in emerging markets
Institutional-grade assets with retail access pathways
Jurisdictions with clear regulatory frameworks Revenue-generating startups seeking capital Renewable energy projects in emerging markets Institutional-grade assets with retail access pathways Jurisdictions with clear regulatory frameworks Website | Whitepaper |  Twitter/X | Telegram Website Website Whitepaper Whitepaper Twitter/X Twitter/X Telegram Telegram About Zodor Zodor is a blockchain-based infrastructure provider focused on compliant and scalable tokenization of real-world assets. The platform integrates decentralized finance principles with traditional finance standards to unlock liquidity, transparency, 0and opportunity for both issuers and investors. Zodor Zodor Contact Principal founder Dinesh Kumar Zodor dinesh@zodor.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Zodor Launches Scalable Infrastructure For Real-World Asset Tokenization Ahead Of April 15 Launch

Zodor lanseer skaalbare infrastruktuur vir real-world asset tokenisasie voor 15 April lanseer

Zodor startet skalierbare Infrastruktur für Real-World-Asset-Tokenisierung vor dem Start am 15. April

Zodor lanza infraestructura escalable para tokenización de activos en el mundo real antes del lanzamiento del 15 de abril

Zodor מציגה תשתית מתוחכמת עבור טוקניזציה של נכסים בעולם האמיתי לפני ההשקה ב-15 באפריל

Zodor Luncurkan Infrastruktur Scalable untuk Tokenisasi Aset Dunia Real Sebelum Luncurkan 15 April

Zodor、4月15日の発売前にリアルな資産トークニケーションのためのスケーラブルインフラストラクチャを導入

„Zodor“ pristato skalbiamą realaus pasaulio turto tokenizacijos infrastruktūrą iki balandžio 15 d.

Zodor uzsāk skalējamu infrastruktūru reālās pasaules aktīvu tokenizācijai pirms 15. aprīļa uzsākšanas

Ny Zodor dia manomboka ny fanatsarana ny fanorenana ho an'ny tokenization ara-toekarena amin'ny alàlan'ny famoahana ny 15 Aprily

Zodor лансира скалабилна инфраструктура за реалниот свет токенизација на средства пред лансирањето на 15 април

Zodor, 15 Nisan'ın başlatılması öncesinde gerçek dünya varlık tokenizasyonu için ölçeklenebilir altyapı başlattı

San Francisco, United States/California, April 10th, 2025/Chainwire/--Huma Finance, the first PayFi Network, announced the launch of Huma 2.0, a permissionless, compliant, and composable real-yield platform built on Solana today. This launch opens global access to Huma's stable real yield from global payment financing related to everyday commerce and trade activities. This development broadens individual access to stable, real-world yield—historically more common in institutional finance—by leveraging payment-financing mechanisms. Simultaneously, the existing permissioned service has been rebranded as Huma Institutional to continue serving institutions and accredited investors. Users can begin depositing on the new Huma 2.0 platform immediately. Huma 2.0 offers users alternative ways to participate as liquidity providers. It introduces two primary modes to cater to different user preferences: Classic Mode, designed for those seeking stable, double-digit USDC yield (updated monthly) combined with rewards called Huma Feathers; and Maxi Mode, tailored for users aiming to maximize their accumulation of Huma Feathers, earning rewards at 5x the base rate, without receiving USDC yield. Users can switch the mode of their existing positions at any time. DeFi composability is also a core feature of Huma 2.0, enabled by the $PST, short for PayFi Strategy Token. This liquid, yield-bearing LP token allows holders to integrate their Huma positions with leading protocols on Solana. At launch, users can swap $PST for USDC via Jupiter, the first of several planned integrations with top Solana DeFi platforms. Support for using $PST as collateral on Kamino and trading future rewards via RateX are expected shortly after launch. While participation does not require capital lock-up, users can opt for 3-month or 6-month terms to significantly boost their Huma Feather rewards via multipliers. Notably, during the initial launch period, these multipliers are significantly elevated as part of a limited-time promotion, offering particularly high boosts in Maxi Mode. These features offer users enhanced flexibility and choice in managing their positions. In just two years, Huma Finance's PayFi Network has rapidly achieved significant scale, processing over $3.8 billion in transactions and generating $8 million in annualized revenue. Huma supports its partners to generate yield from their PayFi operations. Unlike DeFi yields often reliant on token incentives, market speculation, or typically low rates in traditional finance, PayFi yield originates directly from fees paid by businesses using the network for payment financing and settlement liquidity. Capital is recycled rapidly—often within days—compounding fees generated from tangible economic activity. This mechanism has enabled Huma to consistently deliver stable, double-digit USDC yields, showcasing a sustainable model further validated by backing from leading investors and recognition from industry analysts like Messari regarding PayFi's potential to address a $30 trillion market. Messari Messari “Huma 2.0 isn’t just another yield product — it’s a structural shift.” Said Erbil Karaman, Co-founder of Huma Finance. “By giving payments institutions a new source of liquidity that operates 24/7 with incredible capital efficiency, we are creating a new type of yield that is composable, transparent, and grounded in real economic activity. It finally gives DeFi access to a source of returns that institutions have kept to themselves for decades — and it does so without compromising on what makes DeFi powerful.” “Huma 2.0 isn’t just another yield product — it’s a structural shift.” Said Erbil Karaman, Co-founder of Huma Finance. “By giving payments institutions a new source of liquidity that operates 24/7 with incredible capital efficiency, we are creating a new type of yield that is composable, transparent, and grounded in real economic activity. It finally gives DeFi access to a source of returns that institutions have kept to themselves for decades — and it does so without compromising on what makes DeFi powerful.” The launch of Huma 2.0 comes during significant shifts in global finance and within the DeFi landscape itself. While legacy payment infrastructures like SWIFT face challenges with speed and transparency and trillions in capital remain inefficiently allocated, the demand for modern, blockchain-based solutions is clear, evidenced by stablecoin transaction volumes recently reaching a reported $35 trillion. Huma 2.0 leverages this shift, providing efficient settlement liquidity and broadening access for individuals worldwide to earn from foundational financial activities – an opportunity previously confined mainly to institutions. Crucially, the yield generated through PayFi is designed to be less dependent on crypto market cycles. Whether markets are booming or in a downturn, economic activities like payments and trade may continue, potentially offering a more stable foundation for Huma’s yield generation. This structure may make double-digit returns more relevant during bear markets, where speculative yields often decline. As DeFi matures, there is a readiness for this type of yield – one grounded in tangible commerce rather than token speculation. PayFi serves as a foundational layer, enabling new DeFi strategies like the recent Solmate product from Splyce, which combines Huma's $PST yield with SOL liquid staking, bridging decentralized finance with productive economic use. Huma 2.0 marks a key step in building a new financial future, fundamentally expanding participation by inviting everyone into a financial revolution where access is open and fair. Early participants can benefit from various reward multipliers, including boosts for prior Huma depositors and partner communities. As the platform expands with more DeFi integrations and plans to be the first major project on Jupiter's LFG 2.0 launchpad – Huma continues to build finance that is truly accessible. To learn more about Huma 2.0 or participate, users can visit https://huma.finance or follow @humafinance on X. https://huma.finance https://huma.finance @humafinance @humafinance For media inquiries, users can contact: Ejiro Oviri, ejiro@huma.finance. About Huma Finance Huma is the first PayFi (Payment Finance) network. It features an open-stack liquidity protocol with applications for key areas like cross-border payments, stablecoin-backed cards and trade finance. Huma Huma The network addresses a total market estimated at over $30 trillion. Its mission is to accelerate the movement of money for a world that’s always on. Huma is the source of this content. This Press Release is for informational purposes only. The information does not constitute investment advice or an offer to invest. Contact Director of Brand Marketing Ejiro Huma Finance ejiro@huma.finance This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Huma Finance 2.0 Launches On Solana, Bringing Composable Real Yield To DeFi Users

የ Huma Finance 2.0 በ Solana ላይ ይጀምራል, የ DeFi ተጠቃሚዎች የ komposable Real Return ያቀርባል

Huma Finance 2.0 spouští na Solana, přináší kompozitní reálný výnos pro uživatele DeFi

Huma Finance 2.0 lanza en Solana, trayendo rendimiento real compuesto a los usuarios de DeFi

Huma Finance 2.0 Launches On Solana, Bringing Composable Real Yield To DeFi Users ソラナで実現

Huma Finance 2.0 იწყება Solana- ში, რათა DeFi- ის მომხმარებელს კომპიუტერული რეალური მოგება

Huma Finance 2.0은 Solana를 출시하여 DeFi 사용자에게 복합 가능한 실제 수익을 가져옵니다.

Huma Finance 2.0 dia manomboka amin'ny Solana, mitondra tombontsoa ara-toekarena ho an'ny mpampiasa DeFi

Huma Finance 2.0 wprowadza na Solana, przynosząc kompozytowy realny zysk użytkownikom DeFi

Huma Finance 2.0 Solana හි ප්රදර්ශනය, DeFi පරිශීලකයින්ට සංකීර්ණ සැබෑ ආදායමක් ලබා දීම

Huma Finance 2.0 இன் Solana இல் தொடங்கியது, DeFi பயனர்களுக்கு Composable Real Return கொண்டு வருகிறது

Blockchain introduces the promise of a decentralized video games landscape where players can earn rewards, own in-game assets and have a real say in the direction of their future development. \It’s a compelling promise, and yet it’s one that many gamers strongly resist. Gamers have become some of the most vocal naysayers against crypto, labeling digital assets as worthless, with many arguing that the entire industry is a scam. Given the number of hacks and ill-intentioned social media influencers around, it’s understandable that many might think like this. Web3 Gaming Is Far From Dead In a recent editorial in Cointelegraph, NPC Labs co-founder and CEO Daryl Xu argues that Web3 games have failed to achieve mainstream adoption because they’ve ended up recreating many of the problems they set out to fix, creating walled gardens that aim to keep players trapped in their gaming ecosystems. Moreover, he claims developers tend to place too much emphasis on blockchain and tokenomics, at the expense of fun gameplay. editorial editorial But there are many reasons to believe that decentralization can be better for gaming. One of the most compelling is the idea that gamers can exercise control over their development. Indeed, Vitalik Buterin says that a decision by the creators of World of Warcraft to nerf his favorite character was one of the main inspirations that drove him to create the Ethereum blockchain. Then there was the infamous incident with Madden NFL 23, where a data storage issue on one of EA’s servers caused the progress of thousands of gamers to be permanently erased.  With blockchain’s decentralized governance and distributed network, neither of these things can happen. nerf his favorite character nerf his favorite character permanently erased permanently erased Web3 gaming has its share of success stories too. The rise of so-called “tap-to-earn” games on Telegram such as Hamster Combat and Notcoin, which boast millions of players, speaks to the appeal of crypto rewards in gaming. Then there’s the case of Off The Grid, the hit battle royale shooting game that gathered 9.12 million users and processed more than 100 million transactions within the first month of its launch. Hamster Combat Hamster Combat gathered 9.12 million users gathered 9.12 million users A Showcase Of Token Stability A recent spate of token delistings on platforms like Binance stoked apprehension for blockchain gamers. A number of native gaming tokens were included among them, but this is not so much a criticism of the value of these assets, but rather a reaction to the rise of numerous worthless memecoins, which has resulted in many exchanges tightening their listing requirements to protect customers. token delistings token delistings While there may be a few bad apples among blockchain games, most Web3 gaming assets boast sound tokenomics and provide genuine utility. Web3 games developers have put a lot of thought and effort into strengthening their tokenomics models in the wake of what happened to Axie Infinity’s, whose token price crashed once the game’s popularity peaked. But that’s unlikely to happen with newer games like My Neighbor Alice and Alien Worlds. The price of MNA’s ALICE token has been stable since the summer of 2022, propped up by the growing popularity of its metaverse-based farming and social adventure, ample liquidity with more than 50 exchanges listing the asset, and its adherence to industry compliance standards. My Neighbor Alice My Neighbor Alice Alien Worlds Alien Worlds ALICE ALICE It’s a similar story for Alien Worlds, widely regarded as one of the most successful blockchain games. Its native token TLM has a market cap of around $25 million, with its price hovering around the $0.004 mark for more than three years, in stark contrast to the usual volatility of crypto assets. TLM TLM A closer look at ALICE highlights some strong fundamentals. More than 90% of its total supply is already in circulation, reducing any chances of inflation. It provides vast utility, serving as the main rewards token and currency (for buying NFT-based virtual assets and acquiring skills). Players can also unlock exclusive content by paying with ALICE, and they can even start an in-game business and earn ALICE tokens. ALICE also powers MNA’s decentralized governance. By holding ALICE tokens, players are eligible to make proposals to the community and vote on those ideas, with their votes proportional to the amount of tokens they hold. They can thus play an active role in the game’s development and help shape its future. ALICE’s time-tested tokenomics model is based on the idea that transaction fees are returned to the game’s treasury, then fed back to players as rewards for fulfilling various in-game tasks. The game’s economy is rounded out by DeFi features such as staking, lending and borrowing, providing further utility. Continuous Development and Community Engagement Games must evolve if they don’t want to die, and MNA has been transforming itself rapidly with new features such as the launch of its race-inspired NFT Collection, which fuels an ongoing event called “From Land to Track”. In the event, players are encouraged to design their very own race track, on land they own, with big ALICE prizes for those that attract the most community votes. MNA is also celebrating its birthday with its second ALICE airdrop, rewarding its loyal gamers for sticking around, and has many new gaming features planned, such as an innovative new guest mode for new players and WebGPU to ensure smoother gameplay. race-inspired NFT Collection race-inspired NFT Collection celebrating its birthday celebrating its birthday new gaming features new gaming features The pace of innovation in Alien Worlds is just as frenetic, with recent examples being the launch of its Battlefleet Armageddon and Starblind mini-games. It has also introduced community grants to help fund developers who want to create new experiences within the Alien Worlds universe, and launched a new, 10-week community engagement program to help kick start its expansion into China. community engagement program community engagement program Stability: The Key To Success Mainstream adoption remains a distant dream for blockchain gaming, for the industry continues to be dogged by misplaced narratives and broader market challenges. Nonetheless, it’s encouraging to see the resilience, the ongoing innovation and the never-ending community engagement with newer Web3 games like MNA and Alien Worlds. With their strong token fundamentals and loyal player bases, these games have established a strong foundation for the future that won’t easily crumble. With their unwavering commitment to continuous development, they showcase just the kind of sustainability needed by the Web3 gaming industry to further its progress. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYO Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYO Vested Interest Disclosure: Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYO business blogging program business blogging program

Ignore The Noise: Web3 Gaming Is Making Real Progress

Jan yäqañaw Ruido: Web3 Juegos ukax Chiqpach nayrar sartaski

Ignore el soroll: Web3 Gaming està fent progrés real

Ignore el ruido: los juegos Web3 están logrando un progreso real

ERROR: invalid target_lang (fa-AF)

शोर को अनदेखा करें: Web3 गेमिंग वास्तविक प्रगति कर रहा है

Abaikan Kebisingan: Web3 Gaming Membuat Kemajuan Nyata

התעלם מהרעש: משחקי Web3 מתקדמים ממש

雑音は無視：Web3ゲームは真の進歩を遂げている

소음을 무시하십시오 : Web3 Gaming은 진정한 진전을 이루고 있습니다.

Ignore Udhaifu: Web3 Gaming inafanya maendeleo ya kweli

Gürültüyi görmezden gelin: Web3 Gaming Gerçek Gelişme Yaptı

Honisa Mpfumawulo: Web3 Gaming Yi Endla Nhluvuko Wa Xiviri

Authors:
(1) Sanchit Sinha, University of Virginia (sanchit@virginia.edu);
(2) Guangzhi Xiong, University of Virginia (hhu4zu@virginia.edu);
(3) Aidong Zhang, University of Virginia (aidong@virginia.edu). Table of Links Abstract and 1 Introduction 2 Related Work 3 Methodology and 3.1 Representative Concept Extraction 3.2 Self-supervised Contrastive Concept Learning 3.3 Prototype-based Concept Grounding 3.4 End-to-end Composite Training 4 Experiments and 4.1 Datasets and Networks 4.2 Hyperparameter Settings 4.3 Evaluation Metrics and 4.4 Generalization Results 4.5 Concept Fidelity and 4.6 Qualitative Visualization 5 Conclusion and References Appendix 4.3 Evaluation Metrics We consider the following evaluation metrics to evaluate each component of the concept discovery framework. • Generalization: We start by quantitatively evaluating the quality of concepts learned by measuring how well the learned concepts can generalize to new domains. To achieve this, we compare our proposed method against the aforementioned baselines on domain adaptation settings. • Concept Fidelity: To evaluate consistency in the learned concepts, we compute the intersection over union of the concept sets associated with for two data points xi and xj from same class as defined in Equation 10: 4.4 Genenralization Results Tables 2, 3, and 4 report the domain adaptation results on the OfficeHome, DomainNet, VisDA and the Digit datasets, respectively. The notation X→Y represents models trained on X as the source domain (with abundant data) and Y as the target domain (with limited data) and evaluated on the test set of domain Y . The best statistically significant accuracy is reported in bold. The last three rows in all the tables list the performance of the RCE framework, RCE trained with regularization (RCE+PCG), and RCE trained with both regularization and contrastive learning paradigm (RCE+PCG+CCL). Comparision with baselines. The first row in each table lists the performance of a standard Neural Network trained using the setting described in [Yu and Lin, 2023] (S+T). As a standard NN is not inherently explainable, we consider this setting as a baseline to understand the upper bound of the performance-explainability tradeoff. The second and third rows in each table lists the performance of SENN and DiSENN respectively. SENN performs worse than S+T setting in almost all settings, except in a handful of settings where the performance matches S+T. This is expected, as SENN is formulated as an overparameterized version of a standard NN with regularization. Recall that DiSENN replaces the autoencoder in SENN with a VAE, and as such is not generalizable to bigger datasets without domain engineering. DiSENN performs the worst among all approaches for all datasets due to poor VAE generalization. Recall that UnsupervisedCBM is an improved version of SENN architecture with a discriminator in addition to the aggregation function. In most cases, it performs slightly better than SENN and is at par with S+T. However, in particular cases in OfficeHome data (R→A) and DomainNet (S→P), UnsupCBM performs the best. We attribute this result to two factors: first, the Art (A) and Sketch (S) domains are significantly different from Real (R) and Picture (P) domains due to both of the former being hand-drawn while the latter being photographed as mentioned in [Yu and Lin, 2023]. Second, the use of a discriminator as proposed in UnsupervisedCBM helps enforce domain invariance in those particular cases. BotCL explicitly attempts to improve concept fidelity and applies contrastive learning to discover concepts. However, the contrastive loss formulation is rather basic and they never focuses on domain invariance. BotCL’s performance is similar to S+T for the most part except in OfficeHome data (C→A), where it just outperforms all other approaches. One possible reason is that Clipart domain is significantly less noisy, and hence basic transformations in BotCL work well. As the last row demonstrates, our proposed framework RCE+PCG+CCL outperforms all baselines on a vast majority of the settings across all four datasets and is comparable to SOTA baselines in the other settings. Ablation studies. We also report the performance corresponding to various components of our proposed approach. We observe that the performance of RCE is almost identical to SENN, which is expected as there is very weak regularization in both cases. In almost all cases, adding prototype-based grounding regularization (RCE+PCG) improves performance over RCE while models trained with both PCG regularization and contrastive learning (RCE+PCG+CCL) outperform all approaches on a vast majority of settings across all datasets. Note that the setting RCE+CCL is not reported, as it defeats the fundamental motivation of maintaining concept fidelity. Effect of the number of concepts and dimensions. We observe that there are no significant differences in performance over a varying number of concepts or dimensions. For all results reported, the number of concepts is set to a number of classes in the dataset, and their dimension is set to 1. For results on varying numbers of concepts and dimensions - refer to Appendix. 4.5 Concept Fidelity As the RCE framework is explicitly regularized with a concept fidelity regularizer and grounded using prototypes, we would expect high fidelity scores. Table 5 lists the fidelity scores for the aforementioned baselines and our proposed method. Fidelity scores are averaged for each domain when taken as a target (e.g. for the domain (A) in DomainNet, the score is an average of C→A, P→A and R→A). As expected, our method and BotCL, both with specific fidelity regularization outperform all other baseline approaches. Our method outperforms BotCL in most settings, except when the target domains are Art in DomainNet and Clipart in OfficHome due to significant domain dissonance. 4.6 Qualitative Visualization Domain Alignment. We consider the extent to which the models trained using both concept grounding and contrastive learning maintain concept consistency not only within the source domain but also across the target domain as well. To understand what discriminative information is captured by a particular concept, Figure 5 shows the most important prototypes selected from the training set of both the source and target domains corresponding to five randomly selected concepts. We observe that prototypes explaining each concept are visually similar. For more results, refer Appendix. Explanation using prototypes. For a given input sample, we also plot the prototypes associated with the highest activated concept, i.e., the important concept. Figure 6 shows the prototypes associated with the concepts most responsible for prediction (highest relevance scores). As can be seen, the prototypes possess distinct features, for eg., they capture the round face of an alarm clock. More results are reported in Appendix. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Sanchit Sinha, University of Virginia (sanchit@virginia.edu); (2) Guangzhi Xiong, University of Virginia (hhu4zu@virginia.edu); (3) Aidong Zhang, University of Virginia (aidong@virginia.edu). Authors: Authors: (1) Sanchit Sinha, University of Virginia (sanchit@virginia.edu); (2) Guangzhi Xiong, University of Virginia (hhu4zu@virginia.edu); (3) Aidong Zhang, University of Virginia (aidong@virginia.edu). Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Work 2 Related Work 3 Methodology and 3.1 Representative Concept Extraction 3 Methodology and 3.1 Representative Concept Extraction 3.2 Self-supervised Contrastive Concept Learning 3.2 Self-supervised Contrastive Concept Learning 3.3 Prototype-based Concept Grounding 3.3 Prototype-based Concept Grounding 3.4 End-to-end Composite Training 3.4 End-to-end Composite Training 4 Experiments and 4.1 Datasets and Networks 4 Experiments and 4.1 Datasets and Networks 4.2 Hyperparameter Settings 4.2 Hyperparameter Settings 4.3 Evaluation Metrics and 4.4 Generalization Results 4.3 Evaluation Metrics and 4.4 Generalization Results 4.5 Concept Fidelity and 4.6 Qualitative Visualization 4.5 Concept Fidelity and 4.6 Qualitative Visualization 5 Conclusion and References 5 Conclusion and References Appendix Appendix 4.3 Evaluation Metrics We consider the following evaluation metrics to evaluate each component of the concept discovery framework. • Generalization : We start by quantitatively evaluating the quality of concepts learned by measuring how well the learned concepts can generalize to new domains. To achieve this, we compare our proposed method against the aforementioned baselines on domain adaptation settings. Generalization • Concept Fidelity: To evaluate consistency in the learned concepts, we compute the intersection over union of the concept sets associated with for two data points xi and xj from same class as defined in Equation 10: • Concept Fidelity: 4.4 Genenralization Results Tables 2, 3, and 4 report the domain adaptation results on the OfficeHome, DomainNet, VisDA and the Digit datasets, respectively. The notation X→Y represents models trained on X as the source domain (with abundant data) and Y as the target domain (with limited data) and evaluated on the test set of domain Y . The best statistically significant accuracy is reported in bold. The last three rows in all the tables list the performance of the RCE framework, RCE trained with regularization (RCE+PCG), and RCE trained with both regularization and contrastive learning paradigm (RCE+PCG+CCL) . RCE RCE (RCE+PCG), RCE (RCE+PCG+CCL) Comparision with baselines. The first row in each table lists the performance of a standard Neural Network trained using the setting described in [Yu and Lin, 2023] (S+T). As a standard NN is not inherently explainable, we consider this setting as a baseline to understand the upper bound of the performance-explainability tradeoff. Comparision with baselines. The second and third rows in each table lists the performance of SENN and DiSENN respectively. SENN performs worse than S+T setting in almost all settings, except in a handful of settings where the performance matches S+T. This is expected, as SENN is formulated as an overparameterized version of a standard NN with regularization. Recall that DiSENN replaces the autoencoder in SENN with a VAE, and as such is not generalizable to bigger datasets without domain engineering. DiSENN performs the worst among all approaches for all datasets due to poor VAE generalization. Recall that UnsupervisedCBM is an improved version of SENN architecture with a discriminator in addition to the aggregation function. In most cases, it performs slightly better than SENN and is at par with S+T. However, in particular cases in OfficeHome data (R→A) and DomainNet (S→P), UnsupCBM performs the best. We attribute this result to two factors: first, the Art (A) and Sketch (S) domains are significantly different from Real (R) and Picture (P) domains due to both of the former being hand-drawn while the latter being photographed as mentioned in [Yu and Lin, 2023]. Second, the use of a discriminator as proposed in UnsupervisedCBM helps enforce domain invariance in those particular cases. BotCL explicitly attempts to improve concept fidelity and applies contrastive learning to discover concepts. However, the contrastive loss formulation is rather basic and they never focuses on domain invariance. BotCL’s performance is similar to S+T for the most part except in OfficeHome data (C→A), where it just outperforms all other approaches. One possible reason is that Clipart domain is significantly less noisy, and hence basic transformations in BotCL work well. As the last row demonstrates, our proposed framework RCE+PCG+CCL outperforms all baselines on a vast majority of the settings across all four datasets and is comparable to SOTA baselines in the other settings. Ablation studies. We also report the performance corresponding to various components of our proposed approach. We observe that the performance of RCE is almost identical to SENN, which is expected as there is very weak regularization in both cases. In almost all cases, adding prototype-based grounding regularization (RCE+PCG) improves performance over RCE while models trained with both PCG regularization and contrastive learning (RCE+PCG+CCL) outperform all approaches on a vast majority of settings across all datasets. Note that the setting RCE+CCL is not reported, as it defeats the fundamental motivation of maintaining concept fidelity. Ablation studies. Effect of the number of concepts and dimensions. We observe that there are no significant differences in performance over a varying number of concepts or dimensions. For all results reported, the number of concepts is set to a number of classes in the dataset, and their dimension is set to 1. For results on varying numbers of concepts and dimensions - refer to Appendix. Effect of the number of concepts and dimensions. 4.5 Concept Fidelity As the RCE framework is explicitly regularized with a concept fidelity regularizer and grounded using prototypes, we would expect high fidelity scores. Table 5 lists the fidelity scores for the aforementioned baselines and our proposed method. Fidelity scores are averaged for each domain when taken as a target (e.g. for the domain (A) in DomainNet, the score is an average of C→A, P→A and R→A). As expected, our method and BotCL, both with specific fidelity regularization outperform all other baseline approaches. Our method outperforms BotCL in most settings, except when the target domains are Art in DomainNet and Clipart in OfficHome due to significant domain dissonance. 4.6 Qualitative Visualization Domain Alignment. We consider the extent to which the models trained using both concept grounding and contrastive learning maintain concept consistency not only within the source domain but also across the target domain as well. To understand what discriminative information is captured by a particular concept, Figure 5 shows the most important prototypes selected from the training set of both the source and target domains corresponding to five randomly selected concepts. We observe that prototypes explaining each concept are visually similar. For more results, refer Appendix. Domain Alignment. Explanation using prototypes. For a given input sample, we also plot the prototypes associated with the highest activated concept, i.e., the important concept. Figure 6 shows the prototypes associated with the concepts most responsible for prediction (highest relevance scores). As can be seen, the prototypes possess distinct features, for eg., they capture the round face of an alarm clock. More results are reported in Appendix. Explanation using prototypes. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

How Reliable Are AI Concepts in Real-World Domain Adaptation Tasks?

Today, we are excited to announce the support of continuous updates for long-running pipelines in CocoIndex. This powerful feature automatically applies incremental source changes to keep your index up-to-date with minimal latency. With continuous updates, your indexes remain synchronized with your source data in real time, ensuring that your applications always have access to the most current information without the performance overhead of full reindexing. If you like our work, it would mean a lot to us if you could support Cocoindex on Github with a star. Thank you so much with a warm coconut hug 🥥🤗. Cocoindex on Github When to use it? It fits into situations that you need to access the fresh target data continuously in most of the time. How does it work? It continuously captures changes from the source data and updates the target data accordingly. It's long-running and only stops when being aborted explicitly. A data source may enable one or multiple change capture mechanisms: CocoIndex supports two main categories of change detection mechanisms: General Mechanism:

Refresh Interval: A universal approach applicable to all data sources, allowing periodic checks for changes by scanning and comparing the current state with the previous state.


Source-Specific Mechanisms:

Push Change Notification: Many data sources offer built-in mechanisms for real-time change notification which CocoIndex can subscribe to (coming soon!)
Recent Changes Poll: Some data sources provide APIs for tracking recently modified entries, allowing efficient detection of changes; for example, Google Drive. General Mechanism:

Refresh Interval: A universal approach applicable to all data sources, allowing periodic checks for changes by scanning and comparing the current state with the previous state. General Mechanism Refresh Interval: A universal approach applicable to all data sources, allowing periodic checks for changes by scanning and comparing the current state with the previous state. Refresh Interval: A universal approach applicable to all data sources, allowing periodic checks for changes by scanning and comparing the current state with the previous state. Refresh Interval Source-Specific Mechanisms:

Push Change Notification: Many data sources offer built-in mechanisms for real-time change notification which CocoIndex can subscribe to (coming soon!)
Recent Changes Poll: Some data sources provide APIs for tracking recently modified entries, allowing efficient detection of changes; for example, Google Drive. Source-Specific Mechanisms Push Change Notification: Many data sources offer built-in mechanisms for real-time change notification which CocoIndex can subscribe to (coming soon!)
Recent Changes Poll: Some data sources provide APIs for tracking recently modified entries, allowing efficient detection of changes; for example, Google Drive. Push Change Notification: Many data sources offer built-in mechanisms for real-time change notification which CocoIndex can subscribe to (coming soon!) Push Change Notification Recent Changes Poll: Some data sources provide APIs for tracking recently modified entries, allowing efficient detection of changes; for example, Google Drive. Recent Changes Poll These mechanisms work together to ensure CocoIndex can detect and process changes as they happen, maintaining your index in perfect sync with source data with minimal latency and resource usage. Under the hood, after the change is detected, CocoIndex will use its incremental processing mechanism to update the target data. incremental processing mechanism How to enable continuous updates? Here is an example of how to enable continuous updates for Google Drive. It is pretty simple: example 1. Configure the change capture mechanisms for the source @cocoindex.flow_def(name="GoogleDriveIndex")
def my_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoindex.DataScope):
    data_scope["documents"] = flow_builder.add_source(
        cocoindex.sources.GoogleDrive(
            service_account_credential_path=credential_path,
            root_folder_ids=root_folder_ids,
            recent_changes_poll_interval=datetime.timedelta(seconds=10)),
        refresh_interval=datetime.timedelta(minutes=1)) @cocoindex.flow_def(name="GoogleDriveIndex")
def my_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoindex.DataScope):
    data_scope["documents"] = flow_builder.add_source(
        cocoindex.sources.GoogleDrive(
            service_account_credential_path=credential_path,
            root_folder_ids=root_folder_ids,
            recent_changes_poll_interval=datetime.timedelta(seconds=10)),
        refresh_interval=datetime.timedelta(minutes=1)) In this example, we've configured two change detection mechanisms: recent_changes_poll_interval=datetime.timedelta(seconds=10): This is a Google Drive-specific mechanism that uses the Drive API's changes endpoint to efficiently detect modifications every 10 seconds. This is effecient fast scan to capture all latest modified files, and we could set it to a short interval to get fresher data. It doesn't capture file deletions, so we need the fallback mechanism to ensure all changes are eventually captured.


refresh_interval=datetime.timedelta(minutes=1): This is the universal fallback mechanism that performs a complete scan of the data source every minute. This is to scan all the files, to ensure all the changes - including the deleted files, are captured.
The refresh_interval parameter is particularly important as it serves as a safety net to ensure all changes are eventually captured, even if source-specific mechanisms miss something. It works by:

Periodically scanning the list of entries (e.g. file list with metadata like last modified time) at the specified interval
Comparing the current list with the previously known list
Identifying any differences (additions, modifications, deletions)
Triggering updates only for the changed items recent_changes_poll_interval=datetime.timedelta(seconds=10): This is a Google Drive-specific mechanism that uses the Drive API's changes endpoint to efficiently detect modifications every 10 seconds. This is effecient fast scan to capture all latest modified files, and we could set it to a short interval to get fresher data. It doesn't capture file deletions, so we need the fallback mechanism to ensure all changes are eventually captured. recent_changes_poll_interval=datetime.timedelta(seconds=10): This is a Google Drive-specific mechanism that uses the Drive API's changes endpoint to efficiently detect modifications every 10 seconds. This is effecient fast scan to capture all latest modified files, and we could set it to a short interval to get fresher data. It doesn't capture file deletions, so we need the fallback mechanism to ensure all changes are eventually captured. recent_changes_poll_interval=datetime.timedelta(seconds=10) refresh_interval=datetime.timedelta(minutes=1): This is the universal fallback mechanism that performs a complete scan of the data source every minute. This is to scan all the files, to ensure all the changes - including the deleted files, are captured.
The refresh_interval parameter is particularly important as it serves as a safety net to ensure all changes are eventually captured, even if source-specific mechanisms miss something. It works by:

Periodically scanning the list of entries (e.g. file list with metadata like last modified time) at the specified interval
Comparing the current list with the previously known list
Identifying any differences (additions, modifications, deletions)
Triggering updates only for the changed items refresh_interval=datetime.timedelta(minutes=1): This is the universal fallback mechanism that performs a complete scan of the data source every minute. This is to scan all the files, to ensure all the changes - including the deleted files, are captured. refresh_interval=datetime.timedelta(minutes=1) The refresh_interval parameter is particularly important as it serves as a safety net to ensure all changes are eventually captured, even if source-specific mechanisms miss something. It works by: refresh_interval Periodically scanning the list of entries (e.g. file list with metadata like last modified time) at the specified interval
Comparing the current list with the previously known list
Identifying any differences (additions, modifications, deletions)
Triggering updates only for the changed items Periodically scanning the list of entries (e.g. file list with metadata like last modified time) at the specified interval Comparing the current list with the previously known list Identifying any differences (additions, modifications, deletions) Triggering updates only for the changed items While source-specific mechanisms like recent_changes_poll_interval are more efficient for near real-time updates, the refresh_interval provides comprehensive coverage. We recommend setting it to a reasonable value based on your freshness requirements and resource constraints - shorter intervals provide fresher data but consume more resources. recent_changes_poll_interval refresh_interval You can read the full documentation: for source specific change detection mechanisms here. Different sources have different mechanisms supported.
for the universal fallback mechanism here. for source specific change detection mechanisms here. Different sources have different mechanisms supported. here for the universal fallback mechanism here. here 2. Run the flow in live update mode Option 1: CLI Add a @cocoindex.main_fn() decorator to your main function, so CocoIndex CLI will take over the control (when cocoindex is the first command line argument). @cocoindex.main_fn() @cocoindex.main_fn()
def main():
    pass

if __name__ == "__main__":
  main() @cocoindex.main_fn()
def main():
    pass

if __name__ == "__main__":
  main() To run the CLI with live update mode, you can use the following command: python main.py cocoindex update -L python main.py cocoindex update -L This will start the flow in live update mode, which will continuously capture changes from the source and update the target data accordingly. Option 2: Python API You can create cocoindex.FlowLiveUpdater. For example, cocoindex.FlowLiveUpdater @cocoindex.main_fn()
async def main():
    my_updater = cocoindex.FlowLiveUpdater(demo_flow)
    await my_updater.wait()
    ...

if __name__ == "__main__":
    asyncio.run(main()) @cocoindex.main_fn()
async def main():
    my_updater = cocoindex.FlowLiveUpdater(demo_flow)
    await my_updater.wait()
    ...

if __name__ == "__main__":
    asyncio.run(main()) And you run with the flow with python main.py python main.py You can also use the updater as a context manager. It will abort and wait for the updater to finish automatically when the context is exited. See full documentation here. here Now you are all set! It is super simple to get started and have continuous updates for your data. Get started now quickstart guide 🚀 quickstart guide It would mean a lot to us if you could support Cocoindex on Github with a star if you like our work. Thank you so much with a warm coconut hug 🥥🤗. Cocoindex on Github

Keep Your Indexes Fresh With This Real-time Pipeline

Singapore, Singapore, April 4th, 2025/Chainwire/--Yala, the Bitcoin-native liquidity layer enabling cross-ecosystem financial access, today announced the upcoming launch of Yala RealYield, a curated marketplace for real-world asset (RWA) yield opportunities powered by Bitcoin. The new platform will enable BTC holders to earn regulated, risk-adjusted yields by allocating capital into tokenized financial products, including U.S. Treasury bills, private credit, corporate bonds, and real estate-backed assets. Yala RealYield is designed as a unified access point to all of Yala’s RWA-related integrations. Rather than operating as a standalone product, it consolidates partnerships and investment opportunities into a structured platform where users can explore, compare, and combine diverse RWA yield sources, each offering distinct risk profiles, durations, and APYs. By enabling global, 24/7 access to high-quality, compliant RWA opportunities, Yala RealYield democratizes investment strategies previously limited to institutional investors and high-net-worth individuals. “Real-world assets are rapidly becoming the next frontier in blockchain finance. With RealYield, we’re offering Bitcoin holders a reliable, transparent way to earn real returns without leaving the decentralized economy,” said Kaitai Chang, COO at Yala. “This is a foundational step toward integrating BTC with the broader financial system.” “Real-world assets are rapidly becoming the next frontier in blockchain finance. With RealYield, we’re offering Bitcoin holders a reliable, transparent way to earn real returns without leaving the decentralized economy,” said Kaitai Chang, COO at Yala. “This is a foundational step toward integrating BTC with the broader financial system.” Key Features of Yala RealYield: Curated RWA Marketplace: Investors can access a wide selection of tokenized real-world yield opportunities, including sovereign debt, real estate, and private credit—all with transparent terms regarding risk, maturity, and return. Curated RWA Marketplace: Investors can access a wide selection of tokenized real-world yield opportunities, including sovereign debt, real estate, and private credit—all with transparent terms regarding risk, maturity, and return. Customizable Yield Strategies: Users can mix and match products to create bespoke portfolios tailored to individual preferences. Customizable Yield Strategies: Users can mix and match products to create bespoke portfolios tailored to individual preferences. Seamless Bitcoin Integration: All investments begin with BTC, ensuring on-chain transparency, verifiability, and security. Seamless Bitcoin Integration: All investments begin with BTC, ensuring on-chain transparency, verifiability, and security. Compliance-First Design: Robust legal and regulatory reviews to ensure real-world assets can be securely and legally onboarded. Compliance-First Design: Robust legal and regulatory reviews to ensure real-world assets can be securely and legally onboarded. Unified Experience: Yala offers a single dashboard for minting, trading, and managing RWA and DeFi positions—eliminating the need for fragmented platforms. Unified Experience: Yala offers a single dashboard for minting, trading, and managing RWA and DeFi positions—eliminating the need for fragmented platforms. Institutional-Grade Access: Multi-signature custody, on-chain governance, and permissioned access provide a secure foundation for institutional participation. Institutional-Grade Access: Multi-signature custody, on-chain governance, and permissioned access provide a secure foundation for institutional participation. Incentivized Participation: Yield farming and staking mechanisms will be introduced to drive engagement across both retail and institutional segments. Incentivized Participation: Yield farming and staking mechanisms will be introduced to drive engagement across both retail and institutional segments. Personalized Yield Through a Marketplace Model Yala RealYield operates as a marketplace, enabling users to browse and select from a range of yield products across categories such as: Risk Profile – From low-risk instruments like U.S. Treasuries to higher-yield private credit vehicles. Risk Profile – From low-risk instruments like U.S. Treasuries to higher-yield private credit vehicles. Time Horizon – Options range from short-duration liquidity to long-term fixed-income strategies. Time Horizon – Options range from short-duration liquidity to long-term fixed-income strategies. Target Returns – Each product includes APY benchmarks to help users align returns with personal investment objectives. Target Returns – Each product includes APY benchmarks to help users align returns with personal investment objectives. Yala will also introduce the RWA Vault Allocation Framework, a model that packages diversified real-world assets into unified yield vaults, each with defined allocation weights. This mirrors traditional asset allocation strategies but with the added composability and efficiency of Web3 infrastructure. Strategic Vision and Market Opportunity Yala RealYield addresses a long-standing gap in crypto: unlocking Bitcoin’s immense liquidity for productive, low-risk yield generation. The launch comes as institutional interest in tokenized real-world assets accelerates, with the total addressable market for RWAs projected to reach trillions of dollars in the coming years. By combining compliance-first infrastructure, seamless BTC access, and a growing roster of RWA partnerships, Yala is well-positioned to become the leading yield gateway for Bitcoin in traditional financial markets. “Bitcoin remains the most underutilized source of liquidity in the global financial system,” said Kaitai. “RealYield allows us to connect that capital to compliant, income-generating products, building a future where BTC earns real-world returns.” “Bitcoin remains the most underutilized source of liquidity in the global financial system,” said Kaitai. “RealYield allows us to connect that capital to compliant, income-generating products, building a future where BTC earns real-world returns.” Looking Ahead Yala plans to expand the RealYield marketplace over the coming months through additional integrations, refined yield packaging, and improved tooling for developers and institutional users. Long-term, Yala will support the use of RWA-backed positions as collateral for stablecoin minting, creating deeper synergies between DeFi and traditional finance. About Yala Yala is building a liquidity layer to unlock Bitcoin’s untapped yield across DeFi and RWAs. Users can deposit BTC and access seamless liquidity, enabling efficient capital movement and yield opportunities across ecosystems, chains, and protocols. Yala Yala To learn more, users can visit www.yala.org or follow Yala on X at @yalaorg. www.yala.org www.yala.org @yalaorg @yalaorg Contact Yala media@yala.org This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Yala Announces RealYield: A Marketplace For Bitcoin-Powered Real-World Asset Yields

Yala aangekondig RealYield: 'N Marketplace vir Bitcoin-aangedrewe werklike-wêreld asset opbrengs

Yalax RealYeld ukar uñt’ayi: Mä qhathuw Bitcoin-Powered Real-World Asset Yields ukataki

Yala обявява RealYield: Пазар за реални приходи от активи, задвижвани от Bitcoin

Yala anuncia RealYield: un mercado para rendimientos de activos reales basados en Bitcoin

Yala julkistaa RealYieldin: Bitcoin-pohjaisten reaaliaikaisten varojen tuottojen markkinapaikka

Yala annonce RealYield: un marché pour les rendements des actifs du monde réel alimentés par Bitcoin

Yala が RealYield を発表: ビットコインを利用した現実世界の資産利回りのマーケットプレイス

Yala Asakoli RealYield: Zando Ya Ba Rendements Ya Biloko Ya Mokili Ya Solo oyo Esalelaka Bitcoin

Ny Yala dia mampahafantatra ny RealYield: Marketplace ho an'ny Bitcoin-Powered Real-World Asset Yields

यालाले रियलइल्डको घोषणा गर्‍यो: बिटकॉइन-संचालित वास्तविक-विश्व सम्पत्ति उपजको लागि बजार

Yala ප්රකාශ කරයි RealYield: Bitcoins-Powered Real-World Asset Yields සඳහා වෙළෙඳපොළ

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