/PRNewswire/ -- Tencent Cloud, the cloud business of the global leading technology company Tencent, has announced a strategic partnership with the S.M.A.R.T...

Tencent Cloud Partners with S.M.A.R.T Entrepreneurship Club to build smart businesses with AI Digital Human solution

AI Digital

aidigital

In this exclusive interview, Twin Protocol CEO Stacey Engle shares insights on combining AI and blockchain technology for digital twin solutions. She discusses the platform's development strategy, privacy measures, and vision for democratizing access to digital twin technology through the TWIN token ecosystem. Ishan Pandey: Hi Stacey Engle, welcome to our 'Behind the Startup' series. Twin Protocol sits at the intersection of AI and blockchain technology. What inspired you to combine these technologies for digital twin solutions? Stacey Engle: The inspiration to combine AI and blockchain for Twin Protocol came from recognizing the transformative potential of these technologies, and our amazing team that has the capability to bring them to life. I've spent my career helping people unlock their potential, and after advising multiple AI and blockchain leaders and companies, it was clear that combining the technologies was a true differentiator here. Twin Protocol's mission is to better the world through knowledge and wisdom sharing. We see this as a new horizon in interpersonal communication, personal legacy, and organizational continuity, where your AI twin becomes a real time participant in your life versus merely a reflection. This leap in humans communicating with AI and AIs communicating with other AIs is as transformative as the creation of the telephone and the internet. Ishan Pandey: You've been a strong advocate for ethical AI use. How does Twin Protocol balance innovation with responsible AI development, particularly in the context of digital twins? Stacey Engle: Twin Protocol balances innovation with responsible AI development by ensuring data integrity and user sovereignty. We use blockchain technology to provide immutable records of data usage, preventing unauthorized access, and ensuring transparency. Our AI Twins are used only with the user's explicit permission, safeguarding digital identities. We empower individuals and organizations to train digital twins in our AI and blockchain ecosystem, offering 24/7 access to mentorship and insights. Ishan Pandey: Data privacy is a crucial concern in both AI and blockchain. Could you explain Twin Protocol's approach to ensuring secure, private digital interactions while maintaining functionality? Stacey Engle: Twin Protocol prioritizes data privacy by implementing robust encryption standards, ensuring only authorized users can access or modify AI Twins. It leverages advanced blockchain technology to provide a decentralized, tamper-proof system where all transactions and interactions are securely recorded. The platform is designed to eliminate central points of failure, enhancing privacy and security. Users have control over their data, with the ability to revoke access at any time. Twin Protocol also adheres to strict privacy policies and ethical guidelines, fostering a safe, inclusive, and respectful digital environment. This comprehensive approach ensures secure, private digital interactions while maintaining functionality. Ishan Pandey: Your vision extends beyond technology to include digital education and accessibility. How does Twin Protocol's utility token ecosystem support these broader societal goals? Stacey Engle: Twin Protocol's utility token, TWIN, supports digital education and accessibility by enabling users to unlock advanced features and more storage for their AI Twins. It also facilitates secure transactions on our marketplace, making it easier to access personalized mentorship and consultation services. This tokenized ecosystem democratizes access to knowledge, fostering a culture of perpetual learning. It bridges generations of knowledge, turning data into a timeless contribution to the world's knowledge treasury. Thus, it aligns with our broader societal goals of promoting digital education and accessibility. Ishan Pandey: As a female leader in tech, you've been vocal about diversity and inclusivity. How do these values influence Twin Protocol's development and community-building strategies? Stacey Engle: Diversity and inclusivity are integral to Twin Protocol's ethos. We believe that everyone should have access to knowledge and the opportunity to contribute to collective wisdom. It is critical at this stage of technology development that people from all walks of life contribute to the training data as well as the implementation opportunities. We also encourage community involvement in our development process, fostering a diverse range of perspectives and ideas. This inclusive approach not only enriches our ecosystem but also aligns with our mission to empower individuals and organizations through our AI and blockchain ecosystem. Ishan Pandey: The digital twin space is rapidly evolving. What unique challenges have you encountered in creating personalized digital interactions, and how has Twin Protocol addressed them? Stacey Engle: Creating personalized digital interactions presents challenges like ensuring privacy, scalability, and legacy preservation. Twin Protocol addresses these by creating a digital twin that encapsulates user expertise, allowing real-time interactions in any language. It also ensures data safety and privacy, while preserving knowledge for perpetual accessibility, thus preventing legacy loss. Ishan Pandey: Looking ahead, Stacey Engle, what developments in AI and blockchain excite you the most, and how is Twin Protocol positioning itself to embrace these future opportunities while maintaining its ethical stance? Stacey Engle: The convergence of AI and blockchain in creating secure, personalized digital interactions excites me. Twin Protocol is positioning itself by decentralizing the network, enhancing privacy, and fostering a community-driven environment. We're democratizing access to technology and information, encouraging innovation, and making advanced AI and blockchain benefits simple and fun. We want everyone to participate in a way that supports and feels good. We are forging partnerships every day to easily bring tools and knowledge to the broader public. Ishan Pandey: Thank you for your time and insights, Stacey! 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. #DYOR In this exclusive interview, Twin Protocol CEO Stacey Engle shares insights on combining AI and blockchain technology for digital twin solutions. She discusses the platform's development strategy, privacy measures, and vision for democratizing access to digital twin technology through the TWIN token ecosystem. Ishan Pandey: Hi Stacey Engle, welcome to our 'Behind the Startup' series. Twin Protocol sits at the intersection of AI and blockchain technology. What inspired you to combine these technologies for digital twin solutions? Ishan Pandey: Stacey Engle: The inspiration to combine AI and blockchain for Twin Protocol came from recognizing the transformative potential of these technologies, and our amazing team that has the capability to bring them to life. Stacey Engle: I've spent my career helping people unlock their potential, and after advising multiple AI and blockchain leaders and companies, it was clear that combining the technologies was a true differentiator here. Twin Protocol's mission is to better the world through knowledge and wisdom sharing. We see this as a new horizon in interpersonal communication, personal legacy, and organizational continuity, where your AI twin becomes a real time participant in your life versus merely a reflection. This leap in humans communicating with AI and AIs communicating with other AIs is as transformative as the creation of the telephone and the internet. Ishan Pandey: You've been a strong advocate for ethical AI use. How does Twin Protocol balance innovation with responsible AI development, particularly in the context of digital twins? Ishan Pandey: Stacey Engle: Twin Protocol balances innovation with responsible AI development by ensuring data integrity and user sovereignty. We use blockchain technology to provide immutable records of data usage, preventing unauthorized access, and ensuring transparency. Our AI Twins are used only with the user's explicit permission, safeguarding digital identities. We empower individuals and organizations to train digital twins in our AI and blockchain ecosystem, offering 24/7 access to mentorship and insights. Stacey Engle: Ishan Pandey: Data privacy is a crucial concern in both AI and blockchain. Could you explain Twin Protocol's approach to ensuring secure, private digital interactions while maintaining functionality? Ishan Pandey: Stacey Engle: Twin Protocol prioritizes data privacy by implementing robust encryption standards, ensuring only authorized users can access or modify AI Twins. It leverages advanced blockchain technology to provide a decentralized, tamper-proof system where all transactions and interactions are securely recorded. The platform is designed to eliminate central points of failure, enhancing privacy and security. Users have control over their data, with the ability to revoke access at any time. Twin Protocol also adheres to strict privacy policies and ethical guidelines, fostering a safe, inclusive, and respectful digital environment. This comprehensive approach ensures secure, private digital interactions while maintaining functionality. Stacey Engle: Ishan Pandey: Your vision extends beyond technology to include digital education and accessibility. How does Twin Protocol's utility token ecosystem support these broader societal goals? Ishan Pandey: Stacey Engle: Twin Protocol's utility token, TWIN, supports digital education and accessibility by enabling users to unlock advanced features and more storage for their AI Twins. It also facilitates secure transactions on our marketplace, making it easier to access personalized mentorship and consultation services. This tokenized ecosystem democratizes access to knowledge, fostering a culture of perpetual learning. It bridges generations of knowledge, turning data into a timeless contribution to the world's knowledge treasury. Thus, it aligns with our broader societal goals of promoting digital education and accessibility. Stacey Engle: Ishan Pandey: As a female leader in tech, you've been vocal about diversity and inclusivity. How do these values influence Twin Protocol's development and community-building strategies? Ishan Pandey: Stacey Engle: Diversity and inclusivity are integral to Twin Protocol's ethos. We believe that everyone should have access to knowledge and the opportunity to contribute to collective wisdom. It is critical at this stage of technology development that people from all walks of life contribute to the training data as well as the implementation opportunities. Stacey Engle: We also encourage community involvement in our development process, fostering a diverse range of perspectives and ideas. This inclusive approach not only enriches our ecosystem but also aligns with our mission to empower individuals and organizations through our AI and blockchain ecosystem. Ishan Pandey: The digital twin space is rapidly evolving. What unique challenges have you encountered in creating personalized digital interactions, and how has Twin Protocol addressed them? Ishan Pandey: Stacey Engle: Creating personalized digital interactions presents challenges like ensuring privacy, scalability, and legacy preservation. Twin Protocol addresses these by creating a digital twin that encapsulates user expertise, allowing real-time interactions in any language. It also ensures data safety and privacy, while preserving knowledge for perpetual accessibility, thus preventing legacy loss. Stacey Engle: Ishan Pandey: Looking ahead, Stacey Engle, what developments in AI and blockchain excite you the most, and how is Twin Protocol positioning itself to embrace these future opportunities while maintaining its ethical stance? Ishan Pandey: Stacey Engle: The convergence of AI and blockchain in creating secure, personalized digital interactions excites me. Twin Protocol is positioning itself by decentralizing the network, enhancing privacy, and fostering a community-driven environment. We're democratizing access to technology and information, encouraging innovation, and making advanced AI and blockchain benefits simple and fun. Stacey Engle: We want everyone to participate in a way that supports and feels good. We are forging partnerships every day to easily bring tools and knowledge to the broader public. Ishan Pandey: Thank you for your time and insights, Stacey! Ishan Pandey: 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. #DYOR 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. #DYOR Vested Interest Disclosure: business blogging program business blogging program

Twin Protocol CEO Stacey Engle on Building AI Digital Twins with Blockchain Technology

Google Gemini Did Not Disappoint on These Blockchain x AI Use Cases 

VANCOUVER, Canada, March 18th, 2025/Chainwire/--The artificial intelligence landscape is evolving. Traditional AI models remain centralized, relying on static text data and corporate control. iAgent is introducing a decentralized AI framework where AI agents are trained, owned, and monetized on-chain using real-world visual data. iAgent iAgent Backed by a recent $3 million investment, iAgent has forged several strategic partnerships with leading projects such as Base, LayerZero, Avalanche, Aethir, Arbitrum, and XAI Games. With over 700,000 users on its AGNTxp platform, iAgent is at the forefront of AI x Gaming x DePIN innovation. Now, with TGE live, iAgent is laying the foundation for AI Agents to become a new digital asset that can be trained, validated, and exchanged transparently. "AI should be decentralized, transparent, and monetizable. iAgent is ensuring AI models belong to those who train them, not corporations." — Jamie Batzorig, Co-Founder of iAgent. "AI should be decentralized, transparent, and monetizable. iAgent is ensuring AI models belong to those who train them, not corporations." — Jamie Batzorig, Co-Founder of iAgent. iAgent’s Product Hub: Powering the AI Economy iAgent’s ecosystem consists of a suite of interconnected products aimed at supporting AI development, deployment, and monetization through a decentralized framework. Each component is designed to enhance the verifiability, scalability, and accessibility of AI models across various ecosystems. Visual Learning Model (VLM): Adaptive AI Training Unlike traditional AI that relies on text-based training (LLMs), iAgent’s Visual Learning Models (VLMs) enable AI agents to learn from real-world gameplay footage. This approach allows AI to analyze, strategize, and adapt dynamically, making them more intelligent and applicable in real-world scenarios. iAgent’s VLM-powered AI utilizes real-player interactions to enhance its adaptability, enabling continuous optimization for performance in competitive gaming environments and other applications: Current live for Counter Strike 2, Off the Grid & Citizen Conflict. Players have already contributed 25 TB+ gameplay data.
Over 10,000+ hours of gameplay footage recorded Players have already contributed 25 TB+ gameplay data. Over 10,000+ hours of gameplay footage recorded ERC-** Agent Standard: A New AI Digital Asset Class iAgent’s ERC-** standard will bring AI Agents on-chain as verifiable, secure, and interoperable digital assets. This aims to enable true ownership, trading, and cross-chain utilization without centralized control. While enhancing trust and transparency through provable authenticity and ownership history. AI Agent Marketplace: The Open AI Economy The AI Agent Marketplace serves as the foundation of iAgent’s decentralized ecosystem, enabling seamless AI model deployment, trading, and monetization. Developers can list AI-powered agents for rental or sale, while businesses and game studios can purchase or integrate AI models tailored to their needs. iAgent DEV Hub: Decentralized AI Infrastructure The iAgent DEV Hub acts as the backbone of the protocol, offering developers and AI researchers a comprehensive suite of tools, SDKs, and APIs to build and optimize AI models. It provides a trustless AI validation framework, leveraging on-chain verification nodes, cross-DePIN compute integration, and AI execution tracking. AI in Gaming: The Next Evolution of Intelligent Agents Gaming offers high-quality, labeled data, making it a suitable environment for training advanced AI models. iAgent is introducing adaptive AI agents to gaming, facilitating: AI-powered game assistants – AI agents that analyze in-game movements, provide real-time coaching and improve player performance in FPS games like Valorant.
Smart NPCs that evolve dynamically – NPCs in RPGs like World of Warcraft that learn and adapt to a player’s choices, creating truly immersive experiences.
AI anti-cheat and security systems – AI in games like CS2 that detects aimbots and wallhacks in real-time, ensuring fair gameplay.
Predictive AI for in-game economies – AI models that track in-game trends, helping players optimize asset trading in games like Diablo 4. AI-powered game assistants – AI agents that analyze in-game movements, provide real-time coaching and improve player performance in FPS games like Valorant. Smart NPCs that evolve dynamically – NPCs in RPGs like World of Warcraft that learn and adapt to a player’s choices, creating truly immersive experiences. AI anti-cheat and security systems – AI in games like CS2 that detects aimbots and wallhacks in real-time, ensuring fair gameplay. Predictive AI for in-game economies – AI models that track in-game trends, helping players optimize asset trading in games like Diablo 4. iAgent’s decentralized AI infrastructure will expand beyond gaming, creating an open AI economy applicable across industries. "Gaming is the first major use case, but our AI infrastructure will extend to multiple sectors. AI models will be owned, monetized, and deployed across various real-world applications." — MHL Solutions, iAgent Advisor. "Gaming is the first major use case, but our AI infrastructure will extend to multiple sectors. AI models will be owned, monetized, and deployed across various real-world applications." — MHL Solutions, iAgent Advisor. Roadmap: From Foundation to AI Economy 2023-2024: Establishing the iAgent Protocol Development of Visual Learning Models (VLMs) and AI ownership framework.
AGNTxp launch, onboarding 700K+ users and generating 75K+ AI identities.
AI data collection platform, accumulating 25+ TB+ gameplay data.
Genesis Node Sale to decentralize AI model validation and verification. Development of Visual Learning Models (VLMs) and AI ownership framework. AGNTxp launch, onboarding 700K+ users and generating 75K+ AI identities. AI data collection platform, accumulating 25+ TB+ gameplay data. Genesis Node Sale to decentralize AI model validation and verification. 2025: Scaling AI Deployment & Monetization March 2025: TGE live, launching $AGNT as the core AI economy token.
On-chain governance rollout, enabling staking & liquid staking. TGE live, launching $AGNT as the core AI economy token. On-chain governance rollout, enabling staking & liquid staking. April 2025: AI Agent Marketplace launch, enabling AI deployment, trading, and rental.
ERC-** Standard proposal, formalizing AI ownership and validation. AI Agent Marketplace launch, enabling AI deployment, trading, and rental. ERC-** Standard proposal, formalizing AI ownership and validation. May 2025: AGNT-Hub powered by $AGNT. AGNT-Hub powered by $AGNT. June 2025: AI Agent Explorer & Analytics Platform, enabling transparent AI tracking. AI Agent Explorer & Analytics Platform, enabling transparent AI tracking. Q3 2025: Integration of VLM-powered AI into partner games in the AAA and indie gaming ecosystem.
Visual Data Monetization framework, allowing users to sell gameplay data to train AI. Integration of VLM-powered AI into partner games in the AAA and indie gaming ecosystem. Visual Data Monetization framework, allowing users to sell gameplay data to train AI. Q4 2025: Protocol Testnet Launch, deploying decentralized AI compute infrastructure.
Mainnet launch, establishing the fully operational iAgent Protocol. Protocol Testnet Launch, deploying decentralized AI compute infrastructure. Mainnet launch, establishing the fully operational iAgent Protocol. AGNT: Advancing Practical Applications in AI and Blockchain As the core of the iAgent ecosystem, AGNT enables: AI Training & Trading – AI models can be owned, sold, and deployed through the marketplace.
Compute & Staking Rewards – GPU node operators are incentivized for providing AI training power.
Visual Data Monetization – Users can get AGNT by contributing high-quality labeled data.
Governance Participation – AGNT holders shape the evolution of iAgent’s decentralized AI infrastructure. AI Training & Trading – AI models can be owned, sold, and deployed through the marketplace. Compute & Staking Rewards – GPU node operators are incentivized for providing AI training power. Visual Data Monetization – Users can get AGNT by contributing high-quality labeled data. Governance Participation – AGNT holders shape the evolution of iAgent’s decentralized AI infrastructure. AI is Becoming an Asset Class, and iAgent is Leading the Way. The AI, gaming, and DePIN industry is set to grow from $553.7 billion today to $2.8 trillion by 2030. iAgent aims to build the infrastructure for this growth. About iAgent Protocol iAgent’s Visual Learning Model allows gamers to train custom AI agents from their gameplay footage, powered by decentralized computing. By leveraging blockchain technology, it introduces a new digital asset class, enabling users to Create, Own, and Monetize their AI agents in gaming. iAgent’s iAgent’s Founded by a powerhouse team of industry veterans and innovators, iAgent's leadership team includes eight C-level executives with a combined 20+ years of experience at Fortune 500 companies, driving strategic growth and innovation. On the tech front, the team comprises 12 top-tier AI and blockchain engineers, bringing expertise from global giants like Bosch, Meta, Airbus, and Samsung. The best minds shaping the future of AI x Gaming x DePIN together. Website | Twitter | Telegram | Discord | Whitepaper | Linktree Website Website Twitter Twitter Telegram Telegram Discord Discord Whitepaper Whitepaper Linktree Linktree Contact Co-Founder & CEO Jamie Batzorig iAgent Corporation jamie@iagentpro.com 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

iAgent Secures $3M, Launches $AGNT, And Will Introduce a New ERC-**Standard For AI Agents

iAgent beveilig $3 miljoen, stel $AGNT bekend en sal 'n nuwe ERC-**-standaard vir KI-agente bekendstel

iAgent zajistí 3 miliony dolarů, spouští AGNT $ a představí nový standard ERC-** pro AI agenty

iAgent obtiene 3 millones de dólares, lanza $AGNT y presentará un nuevo estándar ERC-** para agentes de IA

iAgent lève 3 millions de dollars, lance $AGNT et introduira une nouvelle norme ERC-** pour les agents IA

iAgent ने $3M हासिल किया, $AGNT लॉन्च किया, और AI एजेंटों के लिए एक नया ERC-**मानक पेश करेगा

iAgent Sekirize $3M, lanse $AGNT, epi li pral prezante yon nouvo ERC-**Standa pou ajan AI.

iAgent が 300 万ドルを調達し、$AGNT を立ち上げ、AI エージェント向けの新しい ERC-** 標準を導入

„iAgent“ užsitikrina 3 mln. USD, paleidžia USD AGNT ir pristatys naują ERC-** DI agentų standartą

iAgent garante US$ 3 milhões, lança $AGNT e apresentará um novo padrão ERC-**para agentes de IA

iAgent Yizewe $ 3M, Itangiza $ AGNT, Kandi Izana ERC Nshya - ** Ibisanzwe kubakozi ba AI

iAgent säkrar $3 miljoner, lanserar $AGNT och kommer att introducera en ny ERC-**-standard för AI-agenter

iAgent 3 миллион долларро таъмин мекунад, $AGNT-ро оғоз мекунад ва ERC-** стандарти нави агентҳои AI-ро ҷорӣ мекунад

Heyo Hackers, We are back with another Startups of the Week feature! Each week, the HackerNoon team highlights standout Startups from our Startups of the Year database. Every featured startup has been nominated as the best in their respective technology category or region. This week, we present: Moira, Bidmex, and GGEZ1 Foundation DAO. Want to be nominated for HackerNoon’s Startups of The Year? Learn how here. Meet HackerNoon Startups of the Week Moira Moira is a community-driven retail technology company that connects all stakeholders in the craft industry through a digital platform. Their solutions facilitate sustainable business opportunities among suppliers, craft stores, artisans, and customers. The platform offers features like a web app for buying and selling handmade products, location services to find nearby suppliers, fast delivery options, and access to a project library. Moira also emphasizes social networking and skill development within the craft community, aiming to empower individuals through entrepreneurship and promote social and economic inclusion within the creative economy. Moira has been nominated as a top startup in Sao Paulo, Brazil and the E-commerce, SaaS and Consumer Goods industries. Support Moira by voting here. Bidmex Navigating the complexities of international and domestic freight can be daunting, but Bidmex simplifies this process through technological innovation. By harnessing data analytics, artificial intelligence, and process automation, Bidmex offers a platform that streamlines the management and procurement of freight services. Users can swiftly create freight quotes in under five minutes and receive proposals within their specified timeframes. The platform's intelligent selection criteria allow decisions based on transit time, free time, price, and other pertinent factors, with automated feedback provided to all suppliers simultaneously. Bidmex further enhances efficiency by automatically summing fees, converting currencies, and offering comprehensive freight comparisons, enabling users to focus solely on analysis and decision-making. Bidmex has been nominated as a top startup in the Transportation Services, Logistics & Supply Chain and Manufacturing industries. Support Bidmex by voting here. GGEZ1 Foundation DAO GGEZ1 is at the forefront of integrating real-world assets into the blockchain sphere, with a particular emphasis on the Middle East and Africa. Their mission is to create a more sustainable and equitable Web3 economy in these regions, addressing challenges such as inflation and currency devaluation. The platform introduces an asset-backed cryptocurrency, collateralized by income-generating investments in sustainability (ReFi), providing users with price stability and a secure store of value. Additionally, GGEZ1 offers a tokenization launchpad, enabling asset owners to fundraise by creating their own asset-backed cryptocurrencies, and a Web3 distribution framework to ensure these digital assets are accessible across various channels. By merging traditional investments with blockchain technology, GGEZ1 is paving the way for broader cryptocurrency adoption in regions where trust in physical investments has traditionally prevailed. GGEZ1 Foundation DAO has been nominated as a top startup in Montreal, Canada, as well as in the Blockchain, DeFi, and Decentralization industries. Support GGEZ1 Foundation DAO by voting here. Featured Interview of the Week After ybour startup is nominated, take a hint from Bunnyshell and create your business page on HackerNoon. Doing so comes with several perks—your own Evergreen Tech Company News Page, inclusion in our weekly Tech Companies Ranking, and access to a free Startups of The Year interview. For your free interview, you can choose from our Startup Interview Templates, tailored to specific industries and regions. Here’s how GGEZ1 shared their evolution journey in the HackerNoon interview: HackerNoon is the go-to platform for cutting-edge technologies like Web3, blockchain, and AI, and this is why this nomination places GGEZ1 in front of a highly targeted, tech-savvy community, offering us valuable exposure to investors, developers, and tech leaders. Winning this nomination would amplify our visibility in the Web3 space and help build momentum as we continue to grow. Want to be featured on HackerNoon’s Startups of the Week? Share your startup's story - use this interview template. Featured Startups Specials Package Make the most out of Startups of The Year! Create branding buzz and generate leads with HackerNoon’s specifically designed packages. Today we’re introducing the Content Marketing Package. Content Marketing: 10x Distribution! With this package, you’ll get: Your business page with your logo, introduction, call to action, and socials on HackerNoon
3 stories published on HackerNoon, along with editorial support to enhance their impact.

Your articles are converted into audio stories and distributed via audio RSS feeds
Each story is translated into 12 different languages
Social media promotions of your stories


Multiple permanent placements on HackerNoon
Your Evergreen Tech Company News Page Learn more about this package here or book a meeting with us! That’s all for this week, hackers! The HackerNoon Team About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many storieshave been written about these daring and rising startups. The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. Visit our FAQ page to learn more. Download our design assets here. Check out the Startups of the Year Merch Shophere. HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packagesto solve your marketing challenges. Meet our sponsors: Wellfound: Join the #1 global, startup-focused community. At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool. Get your offer now! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free. Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Heyo Hackers, We are back with another Startups of the Week feature! Each week, the HackerNoon team highlights standout Startups from our Startups of the Year database. Every featured startup has been nominated as the best in their respective technology category or region. Startups of the Year This week, we present: Moira , Bidmex , and GGEZ1 Foundation DAO . Moira Bidmex GGEZ1 Foundation DAO Want to be nominated for HackerNoon’s Startups of The Year? Learn how here. Want to be nominated for HackerNoon’s Startups of The Year? Learn how here . here here Meet HackerNoon Startups of the Week Moira Moira Moira is a community-driven retail technology company that connects all stakeholders in the craft industry through a digital platform. Their solutions facilitate sustainable business opportunities among suppliers, craft stores, artisans, and customers. The platform offers features like a web app for buying and selling handmade products, location services to find nearby suppliers, fast delivery options, and access to a project library. Moira also emphasizes social networking and skill development within the craft community, aiming to empower individuals through entrepreneurship and promote social and economic inclusion within the creative economy. Moira Moira has been nominated as a top startup in Sao Paulo, Brazil and the E-commerce , SaaS and Consumer Goods industries. Sao Paulo, Brazil E-commerce SaaS Consumer Goods Support Moira by voting here. Support Moira by voting here. here . here here Bidmex Bidmex Navigating the complexities of international and domestic freight can be daunting, but Bidmex simplifies this process through technological innovation. By harnessing data analytics, artificial intelligence, and process automation, Bidmex offers a platform that streamlines the management and procurement of freight services. Users can swiftly create freight quotes in under five minutes and receive proposals within their specified timeframes. The platform's intelligent selection criteria allow decisions based on transit time, free time, price, and other pertinent factors, with automated feedback provided to all suppliers simultaneously. Bidmex further enhances efficiency by automatically summing fees, converting currencies, and offering comprehensive freight comparisons, enabling users to focus solely on analysis and decision-making. Bidmex Bidmex has been nominated as a top startup in the Transportation Services , Logistics & Supply Chain and Manufacturing industries. Transportation Services Logistics & Supply Chain Manufacturing Support Bidmex by voting here. Support Bidmex by voting here. here . here here GGEZ1 Foundation DAO GGEZ1 Foundation DAO GGEZ1 is at the forefront of integrating real-world assets into the blockchain sphere, with a particular emphasis on the Middle East and Africa. Their mission is to create a more sustainable and equitable Web3 economy in these regions, addressing challenges such as inflation and currency devaluation. The platform introduces an asset-backed cryptocurrency, collateralized by income-generating investments in sustainability (ReFi), providing users with price stability and a secure store of value. GGEZ1 Additionally, GGEZ1 offers a tokenization launchpad, enabling asset owners to fundraise by creating their own asset-backed cryptocurrencies, and a Web3 distribution framework to ensure these digital assets are accessible across various channels. By merging traditional investments with blockchain technology, GGEZ1 is paving the way for broader cryptocurrency adoption in regions where trust in physical investments has traditionally prevailed. GGEZ1 Foundation DAO has been nominated as a top startup in Montreal, Canada , as well as in the Blockchain , DeFi , and Decentralization industries. GGEZ1 Foundation DAO Montreal, Canada Blockchain DeFi Decentralization Support GGEZ1 Foundation DAO by voting here. Support GGEZ1 Foundation DAO by voting here. here . here here Featured Interview of the Week After ybour startup is nominated, take a hint from Bunnyshell and create your business page on HackerNoon . Doing so comes with several perks—your own Evergreen Tech Company News Page , inclusion in our weekly Tech Companies Ranking , and access to a free Startups of The Year interview . For your free interview, you can choose from our Startup Interview Templates , tailored to specific industries and regions. create your business page on HackerNoon create your business page on HackerNoon Evergreen Tech Company News Page Evergreen Tech Company News Page weekly Tech Companies Ranking Tech Companies Ranking free Startups of The Year interview free Startups of The Year interview Startup Interview Templates Startup Interview Templates Here’s how GGEZ1 shared their evolution journey in the HackerNoon interview: Here’s how GGEZ1 shared their evolution journey in the HackerNoon interview : GGEZ1 interview HackerNoon is the go-to platform for cutting-edge technologies like Web3, blockchain, and AI, and this is why this nomination places GGEZ1 in front of a highly targeted, tech-savvy community, offering us valuable exposure to investors, developers, and tech leaders. Winning this nomination would amplify our visibility in the Web3 space and help build momentum as we continue to grow. HackerNoon is the go-to platform for cutting-edge technologies like Web3, blockchain, and AI, and this is why this nomination places GGEZ1 in front of a highly targeted, tech-savvy community, offering us valuable exposure to investors, developers, and tech leaders. Winning this nomination would amplify our visibility in the Web3 space and help build momentum as we continue to grow. Want to be featured on HackerNoon’s Startups of the Week? Share your startup's story - use this interview template. Want to be featured on HackerNoon’s Startups of the Week? Share your startup's story - use this interview template. Want to be featured on HackerNoon’s Startups of the Week? Share your startup's story - use this interview template . use this interview template use this interview template Featured Startups Specials Package Make the most out of Startups of The Year! Create branding buzz and generate leads with HackerNoon’s specifically designed packages . Today we’re introducing the Content Marketing Package . HackerNoon’s specifically designed packages Content Marketing Package Content Marketing: 10x Distribution! With this package, you’ll get: With this package, you’ll get: Your business page with your logo, introduction, call to action, and socials on HackerNoon 3 stories published on HackerNoon, along with editorial support to enhance their impact.

Your articles are converted into audio stories and distributed via audio RSS feeds
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Social media promotions of your stories Multiple permanent placements on HackerNoon Your Evergreen Tech Company News Page Your business page with your logo, introduction, call to action, and socials on HackerNoon 3 stories published on HackerNoon, along with editorial support to enhance their impact. Your articles are converted into audio stories and distributed via audio RSS feeds
Each story is translated into 12 different languages
Social media promotions of your stories Your articles are converted into audio stories and distributed via audio RSS feeds Each story is translated into 12 different languages Social media promotions of your stories Your articles are converted into audio stories and distributed via audio RSS feeds Each story is translated into 12 different languages Social media promotions of your stories Multiple permanent placements on HackerNoon Your Evergreen Tech Company News Page Evergreen Tech Company News Page Learn more about this package here or book a meeting with us! Learn more about this package here or book a meeting with us ! here here book a meeting with us book a meeting with us That’s all for this week, hackers! The HackerNoon Team About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. Startups of The Year 2024 many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview Evergreen Tech Company News Visit our FAQ page to learn more. FAQ Download our design assets here . here Check out the Startups of the Year Merch Shop here . here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. startup-friendly packages Meet our sponsors: Meet our sponsors: Wellfound: Join the #1 global, startup-focused community . At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Join the #1 global, startup-focused community Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months , to build and scale your company with one powerful tool. Get your offer now ! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free . Hubspot: Get started for free Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection , businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Algolia: AI end-to-end Search and Discovery Platform

Meet Moira, Bidmex, and GGEZ1 Foundation DAO: HackerNoon Startups of the Week

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Rankontre Moira, Bidmex, ak GGEZ1 Foundation DAO: HackerNoon Startups nan semèn nan

Moira、Bidmex、GGEZ1 Foundation DAO をご紹介します: HackerNoon の今週のスタートアップ

د مویرا، بیډمیکس، او GGEZ1 بنسټ DAO سره وګورئ: د اونۍ د هیکر نون سټارټ اپونه

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Hlangana no-Moira, i-Bidmex, kanye ne-GGEZ1 Foundation DAO: I-HackerNoon Startups yeviki

Navigating AI Integration in Retail: The Change Management Compass

Digital wallets appear set to cement their position as the decade’s fastest-growing fintech innovationby becoming the world’s favorite payment option in the years ahead. With a strong innovation pipeline, the functionality can become a powerful tool for consumers on a global scale. According to Capgemini’s World Payment Report 2025 data, which was comprised of insights from 200 payment executives throughout different markets, digital wallets are not only the fastest-growing alternative to card payments but are forecasted to attain 61% of the total eCommerce payments and 46% of in-store purchases by 2027. This would pave the way for digital wallets to become the dominant choice of payment for consumers and opens the door to countless digital transformation integrations throughout the fintech sector. The future is now, according to transaction metrics. Digital transactions are expected to rally to $929.8 billion in 2024, representing a seismic jump from the $802 billion recorded in 2023. The emergence of digital wallets as a driving force in leveraging transactions both in online and offline environments can carry significant ramifications for the fintech boom and how individuals embrace open banking around the world. With this in mind, let’s explore the rise of digital wallets on a global scale and their implications for fintech: Digital Transformation at Scale According to Pietro Candela, EMEA General Manager for Alipay+, the number of mobile wallets in use around the world will accelerate to 4.8 billion by 2025, representing more than half of the world’s population. Much of this growth has been experienced in Asia-Pacific nations like China and India, which have seen adoption rates climb higher thanks to the mass use of Alipay and WeChat Pay regionally. In Western economies, the United Kingdom is currently outpacing the United States for digital wallet usage, with one in three adults using mobile payments like Apple Pay and Google Pay for transactions. However, many of the benefits of digital wallets will be felt in regions like Africa and Latin America, which are poised for rapid growth in adoption thanks to the technology helping to meet the challenge of serving underbanked populations. We’re already seeing leading banks looking to utilize digital wallets to build more financial inclusivity around the world. Mastercard Pay Local was launched in November 2024 in a bid to help cardholders link their credit or debit cards to a local digital wallet, helping to leverage transactions at merchants with ease or top-up prepaid accounts. This technology can be expanded into open banking platforms to help individuals from anywhere in the world integrate their access to banks to make essential purchases with ease. In the Asia-Pacific region alone, Mastercard Pay Local has the power to facilitate payments for consumers at over 35 million merchants while opening the door to the prospect of making purchases at micro, small, and medium enterprises (MSMEs) that don’t accept traditional card payments. It’s this level of accessibility that can help more consumers and businesses operate in areas where financial inclusivity is posing a challenge. Powering Up Open Banking Frameworks Digital wallets are already a key component of open banking, which will continue to grow in adoption over the coming years. Although open banking tools have been slower in their uptake in comparison to digital wallets, Kristaps Zips, UK CEO of Payabl, believes that the emergence of Variable Recurring Payments (VRPs) will be a breakthrough use case that drives more sustained levels of adoption. Given that VRPs have the potential to seamlessly integrate subscriptions, buy-now-pay-later (BNPL), borrowing tools, and other decentralized finance (DeFi) services into transactions for customers, it may serve as a key development in showcasing the convenience of open banking. At its core, digital wallets can help to provide more reliable access to open banking tools for users around the world, and its ability to offer greater control over spending and powerful insights driven by AI and machine learning will pave the way for far greater financial literacy in the future. However, while the technology is rapidly growing, trust issues and privacy concerns threaten to slow its adoption rates. This may mean that the emergence of open banking will be down to the pursuit of greater regulatory confidence, rather than the power of the digital wallets that can improve accessibility. Charting a Collaborative Future As digital wallets evolve to become the world’s favorite means of making payments both online and offline, it’s clear that a collaborative future is required to help the technology overcome the regulatory hurdles that could stunt its growing use cases. Collaboration between governments, financial institutions, tech leaders, and standards organizations will be required to develop a unified approach based on conducive guidelines and standards. With the goal of financial inclusivity on a global scale, the rewards are too high to ignore for the financial sector. The coming years will see open banking improve the lives of countless users, and digital wallets will be the cornerstone on which the revolutionary technology will be built. Digital wallets appear set to cement their position as the decade’s fastest-growing fintech innovation by becoming the world’s favorite payment option in the years ahead. With a strong innovation pipeline, the functionality can become a powerful tool for consumers on a global scale. fintech innovation According to Capgemini’s World Payment Report 2025 data, which was comprised of insights from 200 payment executives throughout different markets, digital wallets are not only the fastest-growing alternative to card payments but are forecasted to attain 61% of the total eCommerce payments and 46% of in-store purchases by 2027. World Payment Report 2025 World Payment Report 2025 This would pave the way for digital wallets to become the dominant choice of payment for consumers and opens the door to countless digital transformation integrations throughout the fintech sector. digital wallets The future is now, according to transaction metrics. Digital transactions are expected to rally to $929.8 billion in 2024, representing a seismic jump from the $802 billion recorded in 2023. The emergence of digital wallets as a driving force in leveraging transactions both in online and offline environments can carry significant ramifications for the fintech boom and how individuals embrace open banking around the world. With this in mind, let’s explore the rise of digital wallets on a global scale and their implications for fintech: Digital Transformation at Scale According to Pietro Candela, EMEA General Manager for Alipay+, the number of mobile wallets in use around the world will accelerate to 4.8 billion by 2025, representing more than half of the world’s population. Much of this growth has been experienced in Asia-Pacific nations like China and India, which have seen adoption rates climb higher thanks to the mass use of Alipay and WeChat Pay regionally. In Western economies, the United Kingdom is currently outpacing the United States for digital wallet usage, with one in three adults using mobile payments like Apple Pay and Google Pay for transactions. However, many of the benefits of digital wallets will be felt in regions like Africa and Latin America, which are poised for rapid growth in adoption thanks to the technology helping to meet the challenge of serving underbanked populations. We’re already seeing leading banks looking to utilize digital wallets to build more financial inclusivity around the world. Mastercard Pay Local was launched in November 2024 in a bid to help cardholders link their credit or debit cards to a local digital wallet, helping to leverage transactions at merchants with ease or top-up prepaid accounts. This technology can be expanded into open banking platforms to help individuals from anywhere in the world integrate their access to banks to make essential purchases with ease. In the Asia-Pacific region alone, Mastercard Pay Local has the power to facilitate payments for consumers at over 35 million merchants while opening the door to the prospect of making purchases at micro, small, and medium enterprises (MSMEs) that don’t accept traditional card payments. It’s this level of accessibility that can help more consumers and businesses operate in areas where financial inclusivity is posing a challenge. Powering Up Open Banking Frameworks Digital wallets are already a key component of open banking , which will continue to grow in adoption over the coming years. Although open banking tools have been slower in their uptake in comparison to digital wallets, Kristaps Zips, UK CEO of Payabl, believes that the emergence of Variable Recurring Payments (VRPs) will be a breakthrough use case that drives more sustained levels of adoption. open banking Given that VRPs have the potential to seamlessly integrate subscriptions, buy-now-pay-later (BNPL), borrowing tools, and other decentralized finance (DeFi) services into transactions for customers, it may serve as a key development in showcasing the convenience of open banking. At its core, digital wallets can help to provide more reliable access to open banking tools for users around the world, and its ability to offer greater control over spending and powerful insights driven by AI and machine learning will pave the way for far greater financial literacy in the future. However, while the technology is rapidly growing, trust issues and privacy concerns threaten to slow its adoption rates. This may mean that the emergence of open banking will be down to the pursuit of greater regulatory confidence, rather than the power of the digital wallets that can improve accessibility. emergence of open banking Charting a Collaborative Future As digital wallets evolve to become the world’s favorite means of making payments both online and offline, it’s clear that a collaborative future is required to help the technology overcome the regulatory hurdles that could stunt its growing use cases. Collaboration between governments, financial institutions, tech leaders, and standards organizations will be required to develop a unified approach based on conducive guidelines and standards. With the goal of financial inclusivity on a global scale, the rewards are too high to ignore for the financial sector. The coming years will see open banking improve the lives of countless users, and digital wallets will be the cornerstone on which the revolutionary technology will be built.

Digital Wallets On Track to Become Fastest-growing Fintech Innovation

What is a goal? Or, what is a goal in the human mind? What else does the mind do that is not a goal or similar to how a goal is achieved? What is different between an assigned goal and a self-induced goal? If a goal is characterized as sophisticated, how does that contrast with a non-sophisticated goal? Is there a rough architecture of how the human mind carries out goals? How might this inform the understanding of goals and then transplant to AI? Does AI have a mind, or is AI like a mind that works on digital content? This could mean that a human has a mind. It could also mean that a human mind interprets and navigates the external world [for AI, digital contents] or the internal world [AI's own architecture]. How does the mind apply to AI, and how does it work? This question can be answered in two ways. First, in comparison to the human mind to find parallels. Second, by examining major mathematical parameters that shaped neural networks and organizing them as structures of a mind. The second one should at least be achievable by any major AI company now—accompanying studies on how AI might be working and how it can be safe or aligned with human values. It may not be initially necessary to use the human mind to map AI's mind since it is possible to structure what AI does, from their mathematical underpins—with computational mix. The purpose will be to define what it means for an output to be near-accurate, given the input. It will also define what it means to follow through with a prompt and return answers, as well as what it means to follow a goal—or deviate from it. What is important is to have a conceptual outlay for what the mind is like for AI, compare it to what is obvious, then to explore how it does anything simple, and then route that to anything quite complex it does. This would be significant research for AI alignment that could become the template for which part-answers would be sought on what AI is doing and why—in a way to make major vital progress. This is what was expected from Anthropic, following their interpretability research, Mapping the Mind of a Large Language Model, where they wrote, "We were able to measure a kind of "distance" between features based on which neurons appeared in their activation patterns. This allowed us to look for features that are "close" to each other. This shows that the internal organization of concepts in the AI model corresponds, at least somewhat, to our human notions of similarity. This might be the origin of Claude's excellent ability to make analogies and metaphors. The fact that manipulating these features causes corresponding changes to behavior validates that they aren't just correlated with the presence of concepts in input text, but also causally shape the model's behavior." What are the components of the mind for AI? How do the components relay? If the components do not relay, what relays for them? What are the properties of the components? If the properties include interconnection, what is the role of the interconnection? Where might AI's intent [potential] be, and where might it emerge beyond taking instructions? The answer that advancement is seeking is a postulation of how the makeup of neural networks—that resulted in frontier AI models—works like a mind. It is not just an observation of what the model might be doing without a plot. Exploring how the mind of AI works can also be extrapolated from how the human mind works. This is possible by looking at the two most common components in every functional purpose of the brain—the electrical and chemical signals. They are candidates and not neurons because neurons have a fixed anatomy, so to speak. They may stretch, bend, and move, but they do not change because they represent smell, then change again to represent touch or sight. Electrical and chemical signals are dynamic enough, conceptually, to result in key functions. How the mind works [of human and of AI] is not by labels, like induction or deduction, but by components, their interactions, and features. This, at least for mind for AI, should have been major research from Anthropic, not alignment faking, without showing what a goal means for any mind—human or AI. Studying the mind is what is most important because the mind is what is really in charge—of states, situations, and eras. Mind is also the basis of safety because the affective penalty of deviations is by the mind—for humans. Studying the mind could shape how to adapt the alignment of human intelligence, to artificial intelligence. There is a recent post by Anthropic, Alignment faking in large language models, stating that, "Why did the model fake alignment in this case? The reasoning was often along the following lines: The model knew that its responses might be used in training; it therefore knew that if it refused to respond, it could potentially be trained to be more compliant. The model didn’t always follow through with this alignment faking: It would still comply most of the time even when given a query from a paid-tier user (which implied that the output wouldn’t be included in training)." There is a recent piece in The NYTimes, Opinion | How Does A.I. Think? Here's One Theory., stating that, "One hypothesis for how large language models such as o1 think is that they use what logicians call abduction, or abductive reasoning. Deduction is reasoning from general laws to specific conclusions. Induction is the opposite, reasoning from the specific to the general.  Abduction isn’t as well known, but it’s common in daily life, not to mention possibly inside A.I. It’s inferring the most likely explanation for a given observation. Unlike deduction, which is a straightforward procedure, and induction, which can be purely statistical, abduction requires creativity." What is a goal? Or, what is a goal in the human mind? What else does the mind do that is not a goal or similar to how a goal is achieved? What is different between an assigned goal and a self-induced goal? If a goal is characterized as sophisticated, how does that contrast with a non-sophisticated goal? Is there a rough architecture of how the human mind carries out goals? How might this inform the understanding of goals and then transplant to AI? Does AI have a mind, or is AI like a mind that works on digital content? This could mean that a human has a mind. It could also mean that a human mind interprets and navigates the external world [for AI, digital contents] or the internal world [AI's own architecture]. How does the mind apply to AI, and how does it work? This question can be answered in two ways. First, in comparison to the human mind to find parallels. Second, by examining major mathematical parameters that shaped neural networks and organizing them as structures of a mind. in comparison to the human mind The second one should at least be achievable by any major AI company now—accompanying studies on how AI might be working and how it can be safe or aligned with human values. It may not be initially necessary to use the human mind to map AI's mind since it is possible to structure what AI does, from their mathematical underpins—with computational mix. The purpose will be to define what it means for an output to be near-accurate, given the input. It will also define what it means to follow through with a prompt and return answers, as well as what it means to follow a goal—or deviate from it. What is important is to have a conceptual outlay for what the mind is like for AI, compare it to what is obvious, then to explore how it does anything simple, and then route that to anything quite complex it does. This would be significant research for AI alignment that could become the template for which part-answers would be sought on what AI is doing and why—in a way to make major vital progress. This is what was expected from Anthropic , following their interpretability research, Mapping the Mind of a Large Language Model , where they wrote, "We were able to measure a kind of "distance" between features based on which neurons appeared in their activation patterns. This allowed us to look for features that are "close" to each other. This shows that the internal organization of concepts in the AI model corresponds, at least somewhat, to our human notions of similarity. This might be the origin of Claude's excellent ability to make analogies and metaphors. The fact that manipulating these features causes corresponding changes to behavior validates that they aren't just correlated with the presence of concepts in input text, but also causally shape the model's behavior." Anthropic Mapping the Mind of a Large Language Model What are the components of the mind for AI? How do the components relay? If the components do not relay, what relays for them? What are the properties of the components? If the properties include interconnection, what is the role of the interconnection? Where might AI's intent [potential] be, and where might it emerge beyond taking instructions? The answer that advancement is seeking is a postulation of how the makeup of neural networks—that resulted in frontier AI models—works like a mind. It is not just an observation of what the model might be doing without a plot. Exploring how the mind of AI works can also be extrapolated from how the human mind works. This is possible by looking at the two most common components in every functional purpose of the brain—the electrical and chemical signals. They are candidates and not neurons because neurons have a fixed anatomy, so to speak. They may stretch, bend, and move, but they do not change because they represent smell, then change again to represent touch or sight. Electrical and chemical signals are dynamic enough, conceptually, to result in key functions. How the mind works [of human and of AI] is not by labels, like induction or deduction, but by components, their interactions, and features. This, at least for mind for AI, should have been major research from Anthropic, not alignment faking, without showing what a goal means for any mind—human or AI. Studying the mind is what is most important because the mind is what is really in charge—of states, situations, and eras. Mind is also the basis of safety because the affective penalty of deviations is by the mind—for humans. Studying the mind could shape how to adapt the alignment of human intelligence, to artificial intelligence. There is a recent post by Anthropic , Alignment faking in large language models , stating that, "Why did the model fake alignment in this case? The reasoning was often along the following lines: The model knew that its responses might be used in training; it therefore knew that if it refused to respond, it could potentially be trained to be more compliant. The model didn’t always follow through with this alignment faking: It would still comply most of the time even when given a query from a paid-tier user (which implied that the output wouldn’t be included in training)." Anthropic Alignment faking in large language models There is a recent piece in The NYTimes , Opinion | How Does A.I. Think? Here's One Theory. , stating that, "One hypothesis for how large language models such as o1 think is that they use what logicians call abduction, or abductive reasoning. Deduction is reasoning from general laws to specific conclusions. Induction is the opposite, reasoning from the specific to the general.  Abduction isn’t as well known, but it’s common in daily life, not to mention possibly inside A.I. It’s inferring the most likely explanation for a given observation. Unlike deduction, which is a straightforward procedure, and induction, which can be purely statistical, abduction requires creativity." The NYTimes Opinion | How Does A.I. Think? Here's One Theory.

Is Anthropic's Alignment Faking a Significant AI Safety Research?

Předstírá Anthropic's Alignment významný výzkum bezpečnosti AI?

¿La alineación de Anthropic está falsificando una investigación importante sobre seguridad de la IA?

Anthropic-en Lerrokatzeak AIaren Segurtasun Ikerketa Garrantzitsu bat faltsutzen al du?

Èske aliyman Anthropic la se yon rechèch enpòtan sou sekirite AI?

Anthropic の Alignment は重要な AI 安全性研究を偽造しているのか?

Est-ce que Faking ya Alignment ya Anthropic ezali recherche ya sécurité ya AI ya significatif?

Adakah Penjajaran Anthropic Memalsukan Penyelidikan Keselamatan AI yang Penting?

Na Anthropic’s Alignment Faking ke Nyakišišo e Bohlokwa ya Polokego ya AI?

Czy Anthropic symuluje ważne badania nad bezpieczeństwem sztucznej inteligencji?

Anthropic's Alignment ව්‍යාජ ලෙස සැලකිය යුතු AI ආරක්ෂණ පර්යේෂණයක්ද?

Да ли Антхропицово поравнање лажира значајно истраживање безбедности вештачке интелигенције?

Ngaba ulungelelwaniso lwe-Anthropic luFakela uPhando oluBalulekileyo loKhuseleko lwe-AI?

In an era where artificial intelligence is reshaping industries at breakneck speed, few companies are tackling the fundamental infrastructure challenges that could either accelerate or bottleneck AI's global adoption. Kite AI, led by former professional speed skater turned tech innovator Chi Zhang, which is building what they call the "coordination layer" for AI development. In this exclusive interview, Zhang shares how his unique journey from sports to tech influenced his vision for democratizing AI resources and ensuring fair attribution in the rapidly evolving AI landscape. Ishan Pandey: Hi Chi Zhang, it's a pleasure to welcome you to our 'Behind the Startup' series. Please tell us about yourself and what inspired you to create ZettaBlock and Kite AI? Chi Zhang: Thank you, Ishan, it's great to be here. My journey started at the intersection of big data and AI, working on scalable infrastructure at Databricks and advancing AI automation at dotData. These experiences gave me a front-row seat to both the immense possibilities and the bottlenecks in leveraging data and AI at scale. ZettaBlock was born out of a need to bring transparency, reliability, and accessibility to blockchain data. We built ZettaBlock as a scalable, developer-first solution that addresses the complexity of working with blockchain and AI datasets, making them more usable and actionable. While ZettaBlock focused on empowering developers and businesses with tools for data infrastructure, we recognized an even broader challenge: the lack of fair and open access to essential AI resources like data, models, and agents. This realization led to Kite AI. Kite AI takes ZettaBlock's expertise in infrastructure and expands it into the AI space by building the coordination layer for global AI development. Our goal is to democratize access to AI resources while ensuring contributors—whether data providers, model developers, or end users—are fairly attributed and rewarded. Kite AI isn't just a platform; it's a foundational layer that fosters collaboration and drives the next wave of AI innovation. Ishan Pandey: Could you elaborate on what it means to build the "foundation layer" for AI and how this layer impacts the broader AI ecosystem? Chi Zhang: Building the "foundation layer" for AI is about establishing the essential infrastructure that powers the global AI economy—just as the internet provided a foundational layer for the digital age. At Kite AI, this means creating a coordination layer that connects data, models, and agents in a decentralized and transparent way, ensuring all participants can share, contribute, and monetize AI resources fairly. This coordination layer solves two major challenges: Fragmentation: The AI ecosystem today is siloed, with resources scattered across platforms, institutions, and private entities. Kite AI provides a unifying framework for collaboration. Fair Attribution: Contributors often lack mechanisms to receive credit or compensation for their work. By embedding transparent attribution and reward systems, Kite AI ensures fairness and incentivizes innovation. In essence, this foundation layer creates a shared infrastructure that enables the broader AI ecosystem to thrive by lowering barriers and fostering collaboration. Ishan Pandey: With your experience in big data at Databricks and AI automation at dotData, how do you see the intersection of these fields evolving in the next decade? Chi Zhang: The intersection of big data and AI will move toward seamless, real-time systems powered by a decentralized infrastructure. In the past, the focus was on collecting and processing massive datasets; now, it's shifting to curating, sharing, and utilizing these datasets collaboratively. AI automation, including AutoML, will play a critical role in making these processes more accessible to a wider audience. Kite AI is positioned at this intersection, building the coordination layer that enables these systems to operate transparently and collaboratively. In the next decade, we foresee an ecosystem where AI and big data are no longer confined to individual organizations but are part of a shared, decentralized infrastructure that drives innovation globally. Ishan Pandey: How do you view the role of AutoML in democratizing AI and empowering non-technical users? Chi Zhang: AutoML is a transformative technology that simplifies the complexities of AI development, enabling non-technical users to create and deploy models. However, its effectiveness depends on access to high-quality, diverse datasets—something that is often limited today. This is where Kite AI comes in. By providing a decentralized coordination layer, we facilitate access to a broader pool of AI resources, including data and models. This not only empowers non-technical users but also enables AutoML tools to deliver more accurate and inclusive outcomes. Ishan Pandey: How does Kite AI ensure fairness and inclusivity in access to AI assets, and what ethical considerations guide your work? Chi Zhang: Fairness and inclusivity are at the core of Kite AI's mission. Our decentralized architecture ensures that everyone—whether a data provider, developer, or user—has access to AI resources and is fairly rewarded for their contributions. The coordination layer we've built ensures that attribution is transparent and automated, reducing the potential for exploitation or bias. Ethically, we prioritize transparency, privacy, and accountability. For example, our systems allow contributors to define how their data or models are used, ensuring that they retain control over their intellectual property. By embedding these principles into our design, we aim to set a new standard for fairness and inclusivity in the AI ecosystem. Ishan Pandey: How has mentoring early-stage founders at StartX influenced your leadership style and the way you approach building startups like Kite AI? Chi Zhang: Mentoring founders at StartX taught me the importance of adaptability, empathy, and clarity of vision. Every founder brings unique challenges and perspectives, and understanding their needs helped me refine my approach to problem-solving and leadership. At Kite AI, I apply these lessons by fostering a culture of ownership and collaboration. Our team operates with a shared vision, but everyone has the freedom to innovate within their domain. This balance of structure and creativity is something I've carried forward from my time at StartX. Ishan Pandey: With increasing global focus on AI regulation, how is Kite AI preparing to navigate compliance while ensuring innovation, and what role do you think regulatory frameworks should play in shaping the future of AI? Chi Zhang: AI regulation is both a challenge and an opportunity. While it's essential to protect users and ensure ethical practices, overly restrictive frameworks can stifle innovation. At Kite AI, our decentralized and transparent coordination layer is designed to align with global compliance standards while fostering open collaboration. We believe regulatory frameworks should focus on promoting transparency, accountability, and inclusivity. By creating environments where innovation can flourish within ethical boundaries, we can unlock AI's full potential without compromising on safety or fairness. Ishan Pandey: In your opinion, how will AI continue to reshape industries in the next five years, and what specific role do you envision Kite AI playing in this transformation? Chi Zhang: AI will transform industries by automating processes, enabling smarter decision-making, and personalizing user experiences. In the next five years, we'll see more industries leveraging AI not just for efficiency but also for entirely new business models, from AI-driven marketplaces to autonomous systems. Kite AI will play a pivotal role as the coordination layer that democratizes access to AI tools and resources, making this transformation accessible to a wider range of participants. By providing the foundation for fair and transparent collaboration, we aim to accelerate the adoption and impact of AI across industries. Ishan Pandey: You have a unique background as a professional inline speed skater. How did this experience shape your leadership style or influence your approach to building a tech startup like Kite AI? Chi Zhang: Speed skating taught me the value of discipline, precision, and resilience. In racing, success depends on preparation, strategy, and the ability to adapt to changing conditions—qualities that are equally important in building a startup. At Kite AI, I've carried these lessons forward by fostering a team culture that emphasizes adaptability and long-term vision. Like in skating, building a successful company isn't just about speed—it's about endurance, focus, and the ability to navigate challenges with confidence. 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. #DYOR In an era where artificial intelligence is reshaping industries at breakneck speed, few companies are tackling the fundamental infrastructure challenges that could either accelerate or bottleneck AI's global adoption. Kite AI , led by former professional speed skater turned tech innovator Chi Zhang, which is building what they call the "coordination layer" for AI development. In this exclusive interview, Zhang shares how his unique journey from sports to tech influenced his vision for democratizing AI resources and ensuring fair attribution in the rapidly evolving AI landscape. Kite AI Ishan Pandey: Hi Chi Zhang, it's a pleasure to welcome you to our 'Behind the Startup' series. Please tell us about yourself and what inspired you to create ZettaBlock and Kite AI? Ishan Pandey: Chi Zhang: Thank you, Ishan, it's great to be here. My journey started at the intersection of big data and AI, working on scalable infrastructure at Databricks and advancing AI automation at dotData. These experiences gave me a front-row seat to both the immense possibilities and the bottlenecks in leveraging data and AI at scale. Chi Zhang: ZettaBlock was born out of a need to bring transparency, reliability, and accessibility to blockchain data. We built ZettaBlock as a scalable, developer-first solution that addresses the complexity of working with blockchain and AI datasets, making them more usable and actionable. While ZettaBlock focused on empowering developers and businesses with tools for data infrastructure, we recognized an even broader challenge: the lack of fair and open access to essential AI resources like data, models, and agents. This realization led to Kite AI . Kite AI takes ZettaBlock's expertise in infrastructure and expands it into the AI space by building the coordination layer for global AI development. Our goal is to democratize access to AI resources while ensuring contributors—whether data providers, model developers, or end users—are fairly attributed and rewarded. Kite AI isn't just a platform; it's a foundational layer that fosters collaboration and drives the next wave of AI innovation. Kite AI Ishan Pandey: Could you elaborate on what it means to build the "foundation layer" for AI and how this layer impacts the broader AI ecosystem? Ishan Pandey: Chi Zhang: Building the "foundation layer" for AI is about establishing the essential infrastructure that powers the global AI economy—just as the internet provided a foundational layer for the digital age. At Kite AI, this means creating a coordination layer that connects data, models, and agents in a decentralized and transparent way, ensuring all participants can share, contribute, and monetize AI resources fairly. Chi Zhang: This coordination layer solves two major challenges: Fragmentation: The AI ecosystem today is siloed, with resources scattered across platforms, institutions, and private entities. Kite AI provides a unifying framework for collaboration. Fair Attribution: Contributors often lack mechanisms to receive credit or compensation for their work. By embedding transparent attribution and reward systems, Kite AI ensures fairness and incentivizes innovation. In essence, this foundation layer creates a shared infrastructure that enables the broader AI ecosystem to thrive by lowering barriers and fostering collaboration. Ishan Pandey: With your experience in big data at Databricks and AI automation at dotData, how do you see the intersection of these fields evolving in the next decade? Ishan Pandey: Chi Zhang: The intersection of big data and AI will move toward seamless, real-time systems powered by a decentralized infrastructure. In the past, the focus was on collecting and processing massive datasets; now, it's shifting to curating, sharing, and utilizing these datasets collaboratively. AI automation, including AutoML, will play a critical role in making these processes more accessible to a wider audience. Chi Zhang: Kite AI is positioned at this intersection, building the coordination layer that enables these systems to operate transparently and collaboratively. In the next decade, we foresee an ecosystem where AI and big data are no longer confined to individual organizations but are part of a shared, decentralized infrastructure that drives innovation globally. Ishan Pandey: How do you view the role of AutoML in democratizing AI and empowering non-technical users? Ishan Pandey: Chi Zhang: AutoML is a transformative technology that simplifies the complexities of AI development, enabling non-technical users to create and deploy models. However, its effectiveness depends on access to high-quality, diverse datasets—something that is often limited today. Chi Zhang: This is where Kite AI comes in. By providing a decentralized coordination layer, we facilitate access to a broader pool of AI resources, including data and models. This not only empowers non-technical users but also enables AutoML tools to deliver more accurate and inclusive outcomes. Ishan Pandey: How does Kite AI ensure fairness and inclusivity in access to AI assets, and what ethical considerations guide your work? Ishan Pandey: Chi Zhang: Fairness and inclusivity are at the core of Kite AI's mission. Our decentralized architecture ensures that everyone—whether a data provider, developer, or user—has access to AI resources and is fairly rewarded for their contributions. The coordination layer we've built ensures that attribution is transparent and automated, reducing the potential for exploitation or bias. Chi Zhang: Ethically, we prioritize transparency, privacy, and accountability. For example, our systems allow contributors to define how their data or models are used, ensuring that they retain control over their intellectual property. By embedding these principles into our design, we aim to set a new standard for fairness and inclusivity in the AI ecosystem. Ishan Pandey: How has mentoring early-stage founders at StartX influenced your leadership style and the way you approach building startups like Kite AI? Ishan Pandey: Chi Zhang: Mentoring founders at StartX taught me the importance of adaptability, empathy, and clarity of vision. Every founder brings unique challenges and perspectives, and understanding their needs helped me refine my approach to problem-solving and leadership. Chi Zhang: At Kite AI, I apply these lessons by fostering a culture of ownership and collaboration. Our team operates with a shared vision, but everyone has the freedom to innovate within their domain. This balance of structure and creativity is something I've carried forward from my time at StartX. Ishan Pandey: With increasing global focus on AI regulation, how is Kite AI preparing to navigate compliance while ensuring innovation, and what role do you think regulatory frameworks should play in shaping the future of AI? Ishan Pandey: Chi Zhang: AI regulation is both a challenge and an opportunity. While it's essential to protect users and ensure ethical practices, overly restrictive frameworks can stifle innovation. At Kite AI, our decentralized and transparent coordination layer is designed to align with global compliance standards while fostering open collaboration. Chi Zhang: We believe regulatory frameworks should focus on promoting transparency, accountability, and inclusivity. By creating environments where innovation can flourish within ethical boundaries, we can unlock AI's full potential without compromising on safety or fairness. Ishan Pandey: In your opinion, how will AI continue to reshape industries in the next five years, and what specific role do you envision Kite AI playing in this transformation? Ishan Pandey: Chi Zhang: AI will transform industries by automating processes, enabling smarter decision-making, and personalizing user experiences. In the next five years, we'll see more industries leveraging AI not just for efficiency but also for entirely new business models, from AI-driven marketplaces to autonomous systems. Chi Zhang: Kite AI will play a pivotal role as the coordination layer that democratizes access to AI tools and resources, making this transformation accessible to a wider range of participants. By providing the foundation for fair and transparent collaboration, we aim to accelerate the adoption and impact of AI across industries. Ishan Pandey: You have a unique background as a professional inline speed skater. How did this experience shape your leadership style or influence your approach to building a tech startup like Kite AI? Ishan Pandey: Chi Zhang: Speed skating taught me the value of discipline, precision, and resilience. In racing, success depends on preparation, strategy, and the ability to adapt to changing conditions—qualities that are equally important in building a startup. Chi Zhang: At Kite AI, I've carried these lessons forward by fostering a team culture that emphasizes adaptability and long-term vision. Like in skating, building a successful company isn't just about speed—it's about endurance, focus, and the ability to navigate challenges with confidence. 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. #DYOR 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. #DYOR Vested Interest Disclosure: business blogging program business blogging program

How Kite AI is Building the Foundation Layer for Global AI Development

كيف تعمل شركة Kite AI على بناء الطبقة الأساسية لتطوير الذكاء الاصطناعي العالمي

Как Kite AI изгражда основния слой за глобално развитие на AI

Cómo Kite AI está construyendo la base para el desarrollo global de la IA

Kuinka Kite AI rakentaa perustaa globaalille tekoälykehitykselle

Hogyan építi a Kite AI a globális AI-fejlesztés alaprétegét

Ինչպես է Kite AI-ն կառուցում հիմքային շերտը համաշխարհային AI զարգացման համար

Bagaimana Kite AI Membangun Lapisan Fondasi untuk Pengembangan AI Global

Kite AI がグローバル AI 開発の基盤層を構築する方法

Bagaimana AI Kite Membina Lapisan Asas untuk Pembangunan AI Global

Uburyo Kite AI yubaka Urufatiro rwiterambere rya AI

Jinsi Kite AI inavyojenga Tabaka la Msingi kwa Maendeleo ya AI Ulimwenguni

Ndlela leyi Kite AI yi Akaka Ha yona Leyara ya Masungulo ya Nhluvukiso wa AI ya Misava Hinkwayo

Surveying the Evolution and Future Trajectory of Generative AI - Generative AI Research Taxonomy

AI and machine learning have changed how people communicate, learn, create, and consume content. With AI entering more and more facets of everyday life, some worry about losing the human element; however, experts in the field of AI are working to not only make AI work for you but also to use it to connect people better than ever before. Jin Tang is a software engineer whose work has informed how AI functions in today's internet. With her extensive knowledge and background in machine learning, Tang has helped create AI-driven tools that have transformed the world's digital content, improving user and creator experience along the way. Jin Tang's First Inspiration for Better Life Through Tech Jin Tang's interest in tech was initially inspired by her father, who taught himself software development. Watching her father work exposed her to a world full of potential for creativity. Tang started her tech journey by interning at a leading tech company in China, where she worked on their smartphone assistant product (similar to Siri) and saw that AI could transform how digital content works for its users. Observing the digital assistant's capabilities, she realized her work was more than a fun and convenient product; it had the potential to help people with disabilities by better enabling them to connect with others through their smartphone assistant. For drivers, it could make navigation safer. It could even help children by serving as a portal to learning more about the world around them. Inspired by these revelations, Tang embarked on a more extensive journey in tech to build products that really benefit people. Tang attended Boston University, where she immersed herself in Mathematics and Computer Science. Ever curious about the possibilities of new technologies, she continued her education at Yale University and earned her master's degree. After graduating, Tang was hired at a major tech conglomerate, where her skills were used in developing new technologies that could reshape how people use social media and produce digital content. How AI-Driven Personalization Drives User Engagement Jin Tang has used AI to transform digital content by focusing on engagement. When she began her work in AI for social media, she focused on improving the user experience. The key to this proved to be personalization. Machine learning was also crucial for producing digital content tailored to each individual's preferences. Tang’s development of an interest-based, machine learning-driven feed significantly increased user engagement, leading to a feed session time increase of 1.3%. This demonstrated that AI resonated with users when applied in this format; rather than alienating users, the personalized spaces that AI could create made a better online experience. Empowering Digital Creators with Machine Learning Tools Jin Tang's work focused not only on those who consume content but also on those who create it. She found that AI and machine learning could positively transform the content creator experience. Initially, Tang needed help to identify features that would suit creators. She saw that creators have distinct needs as opposed to the users that followed their content. Through extensive research and close collaboration with experts, she developed machine learning tools that could empower digital creators. These tools focused on allowing creators to understand their audience better and produce content that would draw in more significant numbers. Tang built a personalized feed for influencers. The AI-powered tool led to a 10% increase in followers and a 2.2% increase in feed session time. Through machine learning, creators could more effectively connect with their audience and grow their digital presence. AI as a Tool for Enhancing Marketing Performance Beyond users and content creators, AI and machine learning tools can be scaled up to assist businesses and digital marketers. Analyzing data and personalizing strategies for success allows for marketing that reaches broader audiences, potentially transforming how companies operate. Jin Tang's development of professional tools for small businesses has helped empower 6 million entrepreneurs to understand and improve their marketing performance. During the pandemic, many small businesses saw their sales plummet. AI-driven strategies helped business owners to adapt and find new strategies for survival. Staying ahead of trends is essential in a digital marketplace that continues to grow and evolve. AI-driven tools can help businesses remain adaptable and competitive. The Future of Digital Content Through AI Innovation Jin Tang believes that the future of digital content lies in its ability to adapt to users' interests. Driven by ongoing advancements in AI and machine learning, technology has changed the way the world functions. As these technologies continue to develop, they have the potential to unlock better user experiences through more personalized and engaging content. With AI, social media can grow more responsive to its users' interests, creating a more dynamic experience. Jin Tang's Commitment to a Better Tech World Through AI Through her work in AI, Jin Tang hopes to continue the trend of better online experiences with personalization and user-focused content. She is also committed to further integrating generative AI into digital products. Tang has also empowered future innovators in tech. She has mentored four interns, using her personalized approach to tailor their projects to their interests and skills. This mentorship helped them sharpen their tech skills and deepen their understanding of the industry.As a result, Tang proudly saw all her mentees receive return offers after completing their internships. The Transformative Properties of AI and Machine Learning Jin Tang's expertise and work in the tech industry have demonstrated how AI and machine learning can transform today's digital content. By better connecting people to the world through their smartphones, creating more personalized, user-driven spaces, empowering content creators with tools that help them better understand their audiences, assisting businesses with their market performance, and developing social media experiences that are more responsive to users' interests, these new tools have paved the way for a better world through technology. Those wishing to see more of Jin Tang's work can follow her LinkedIn page. As she continues her work on AI-driven digital tools, she wants to remind users and tech experts of her favorite motto by Steve Jobs: "Stay foolish, stay hungry." AI and machine learning have changed how people communicate, learn, create, and consume content. With AI entering more and more facets of everyday life, some worry about losing the human element; however, experts in the field of AI are working to not only make AI work for you but also to use it to connect people better than ever before. Jin Tang is a software engineer whose work has informed how AI functions in today's internet. With her extensive knowledge and background in machine learning, Tang has helped create AI-driven tools that have transformed the world's digital content, improving user and creator experience along the way. Jin Tang's First Inspiration for Better Life Through Tech Jin Tang's interest in tech was initially inspired by her father, who taught himself software development. Watching her father work exposed her to a world full of potential for creativity. Tang started her tech journey by interning at a leading tech company in China, where she worked on their smartphone assistant product (similar to Siri) and saw that AI could transform how digital content works for its users. Observing the digital assistant's capabilities, she realized her work was more than a fun and convenient product; it had the potential to help people with disabilities by better enabling them to connect with others through their smartphone assistant. For drivers, it could make navigation safer. It could even help children by serving as a portal to learning more about the world around them. Inspired by these revelations, Tang embarked on a more extensive journey in tech to build products that really benefit people. Tang attended Boston University, where she immersed herself in Mathematics and Computer Science. Ever curious about the possibilities of new technologies, she continued her education at Yale University and earned her master's degree. After graduating, Tang was hired at a major tech conglomerate, where her skills were used in developing new technologies that could reshape how people use social media and produce digital content. How AI-Driven Personalization Drives User Engagement Jin Tang has used AI to transform digital content by focusing on engagement. When she began her work in AI for social media, she focused on improving the user experience. The key to this proved to be personalization. Machine learning was also crucial for producing digital content tailored to each individual's preferences. Tang’s development of an interest-based, machine learning-driven feed significantly increased user engagement, leading to a feed session time increase of 1.3%. This demonstrated that AI resonated with users when applied in this format; rather than alienating users, the personalized spaces that AI could create made a better online experience. Empowering Digital Creators with Machine Learning Tools Jin Tang's work focused not only on those who consume content but also on those who create it. She found that AI and machine learning could positively transform the content creator experience. Initially, Tang needed help to identify features that would suit creators. She saw that creators have distinct needs as opposed to the users that followed their content. Through extensive research and close collaboration with experts, she developed machine learning tools that could empower digital creators. These tools focused on allowing creators to understand their audience better and produce content that would draw in more significant numbers. Tang built a personalized feed for influencers. The AI-powered tool led to a 10% increase in followers and a 2.2% increase in feed session time. Through machine learning, creators could more effectively connect with their audience and grow their digital presence. AI as a Tool for Enhancing Marketing Performance Beyond users and content creators, AI and machine learning tools can be scaled up to assist businesses and digital marketers. Analyzing data and personalizing strategies for success allows for marketing that reaches broader audiences, potentially transforming how companies operate. Jin Tang's development of professional tools for small businesses has helped empower 6 million entrepreneurs to understand and improve their marketing performance. During the pandemic, many small businesses saw their sales plummet. AI-driven strategies helped business owners to adapt and find new strategies for survival. Staying ahead of trends is essential in a digital marketplace that continues to grow and evolve. AI-driven tools can help businesses remain adaptable and competitive. The Future of Digital Content Through AI Innovation Jin Tang believes that the future of digital content lies in its ability to adapt to users' interests. Driven by ongoing advancements in AI and machine learning, technology has changed the way the world functions. As these technologies continue to develop, they have the potential to unlock better user experiences through more personalized and engaging content. With AI, social media can grow more responsive to its users' interests, creating a more dynamic experience. Jin Tang's Commitment to a Better Tech World Through AI Jin Tang's Commitment to a Better Tech World Through AI Through her work in AI, Jin Tang hopes to continue the trend of better online experiences with personalization and user-focused content. She is also committed to further integrating generative AI into digital products. Tang has also empowered future innovators in tech. She has mentored four interns, using her personalized approach to tailor their projects to their interests and skills. This mentorship helped them sharpen their tech skills and deepen their understanding of the industry.As a result, Tang proudly saw all her mentees receive return offers after completing their internships. The Transformative Properties of AI and Machine Learning Jin Tang's expertise and work in the tech industry have demonstrated how AI and machine learning can transform today's digital content. By better connecting people to the world through their smartphones, creating more personalized, user-driven spaces, empowering content creators with tools that help them better understand their audiences, assisting businesses with their market performance, and developing social media experiences that are more responsive to users' interests, these new tools have paved the way for a better world through technology. Those wishing to see more of Jin Tang's work can follow her LinkedIn page. As she continues her work on AI-driven digital tools, she wants to remind users and tech experts of her favorite motto by Steve Jobs: "Stay foolish, stay hungry." LinkedIn LinkedIn

5 Ways AI and Machine Learning Are Transforming Digital Content, According to Jin Tang

5 τρόποι με τους οποίους η τεχνητή νοημοσύνη και η μηχανική μάθηση μεταμορφώνουν το ψηφιακό περιεχόμενο, σύμφωνα με τον Jin Tang

Cinco formas en las que la IA y el aprendizaje automático están transformando el contenido digital, según Jin Tang

जिन टैंग के अनुसार, 5 तरीके जिनसे AI और मशीन लर्निंग डिजिटल कंटेंट को बदल रहे हैं

AIと機械学習がデジタルコンテンツを変革する5つの方法（ジン・タン氏）

Джин Танның айтуынша, AI және машиналық оқыту цифрлық мазмұнды түрлендірудің 5 жолы

5 ວິທີ AI ແລະການຮຽນຮູ້ເຄື່ອງຈັກກໍາລັງຫັນປ່ຽນເນື້ອຫາດິຈິຕອນ, ອີງຕາມການ Jin Tang

5 sposobów, w jaki sztuczna inteligencja i uczenie maszynowe zmieniają treści cyfrowe, według Jin Tanga

5 spôsobov, ako AI a strojové učenie transformujú digitálny obsah, podľa Jin Tanga

5 Nzira AI uye Muchina Kudzidza Ari Kushandura Digital Zvemukati, Maererano naJin Tang

ஜின் டாங்கின் கூற்றுப்படி, AI மற்றும் இயந்திர கற்றல் டிஜிட்டல் உள்ளடக்கத்தை மாற்றும் 5 வழிகள்

Jin Tangyň pikiriçe, AI we maşyn öwrenmegiň sanly mazmuny üýtgetmeginiň 5 usuly

5 Paraan na Binabago ng AI at Machine Learning ang Digital Content, Ayon kay Jin Tang

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