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<!DOCTYPE html><html lang="en" class="bg-bg-main"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="image" href="/img/hero/hero-bg-00.png"/><link rel="preload" as="image" href="/img/hero/hero-bg-01.png"/><link rel="preload" as="image" href="/img/hero/hero-bg-02.png"/><link rel="preload" as="image" href="/img/hero/hero-bg-03.png"/><link rel="stylesheet" href="/_next/static/css/2c7d7e3a975d4142.css" data-precedence="next"/><link rel="preload" as="script" fetchPriority="low" href="/_next/static/chunks/webpack-9edee2920554d0a5.js"/><script src="/_next/static/chunks/4bd1b696-843266b6bb2dc524.js" async=""></script><script src="/_next/static/chunks/587-522c783b56d381e1.js" async=""></script><script src="/_next/static/chunks/main-app-5d0993cd9015c0f0.js" async=""></script><script src="/_next/static/chunks/c15bf2b0-2e5094ff64f4d456.js" async=""></script><script src="/_next/static/chunks/854-584b35f6d6bcfa9a.js" 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style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" src="/_next/static/media/icon-arrow-yellow.42ad75e9.svg"/></div></a></div></div></div></div></div></div><div class="flex w-screen flex-col items-center justify-center overflow-x-hidden"><div id="hero" class="cont relative flex h-screen w-screen items-center justify-center"><div class="absolute flex h-full w-screen items-start justify-center pt-[20px] md:justify-end md:pt-[0px]"><div class="4xl:h-[1414px] 4xl:w-[2048px] 3xl:h-[1194px] 3xl:w-[1729px] absolute h-[530px] w-[768px] lg:h-[707px] lg:w-[1024px] xl:h-[884px] xl:w-[1280px] 2xl:h-[995px] 2xl:w-[1440px]"><img src="/img/hero/hero-bg-00.png" alt="Hellas AI" class="absolute z-[2] h-full w-full" style="opacity:0;transform:none"/><img data-speed="0.1" src="/img/hero/hero-bg-01.png" alt="Hellas AI" class="absolute z-[0] h-full w-full" style="opacity:0;transform:none"/><img src="/img/hero/hero-bg-02.png" alt="Hellas AI" class="absolute z-[1] h-full w-full" style="opacity:0;transform:none"/><img src="/img/hero/hero-bg-03.png" alt="Hellas AI" class="absolute z-[3] h-full w-full" style="opacity:0;transform:none"/></div></div><div class="flex h-full w-full max-w-[1440px] flex-col items-start justify-end pb-[100px] md:flex-row-reverse md:pb-[0]"><div class="relative z-[5] flex w-full flex-col items-start justify-start gap-[18px] self-end px-[20px] md:gap-[40px] md:px-[40px] md:font-bold"><h1 class="font-paplane text-[36px] leading-[120%] font-light md:text-[60px] md:leading-[110%] lg:text-[100px]" style="opacity:0;transform:none">Powering<br/>limitless<br/>intelligence</h1><div class="flex w-full items-end justify-start gap-[60px] pb-[40px] md:pb-[80px]"><p class="w-full max-w-[170px] text-[14px] font-light md:max-w-[250px] md:text-[16px] lg:text-[20px]" style="opacity:0;transform:none">Hellas is the ecosystem for distributed compute, the foundation for an AI-powered civilization.</p><a href="#about" class="group relative cursor-pointer" style="opacity:0;transform:none"><div class="group-hover:bg-gray-secondary/[0.5] bg-gray-secondary relative px-[20px] py-[12px] text-[14px] transition-all duration-300 md:px-[32px] md:py-[18px] md:text-[16px] lg:px-[40px] lg:py-[20px] lg:text-[20px]">Explore</div><div class="t-box bg-yellow-primary absolute right-[-12px] bottom-[-12px] flex size-[28px] items-center justify-center transition-all duration-300 group-hover:bottom-[-24px] md:right-[-20px] md:bottom-[-20px] md:size-[40px]"><img alt="arrow icon" loading="lazy" width="29" height="28" decoding="async" data-nimg="1" class="size-[12px] md:size-[18px]" style="color:transparent" src="/_next/static/media/icon-arrow.6c941dda.svg"/></div></a></div></div></div></div><div id="about" class="flex w-screen items-center justify-center px-[20px] md:px-[40px]"><div class="flex w-full max-w-[1440px] flex-col items-center justify-center md:flex-row"><div class="relative flex w-full items-center justify-center md:w-[50%]"><div class="relative flex h-[485px] w-[300px] items-center justify-center py-[0px] lg:h-[808px] lg:w-[500px]"><img alt="" loading="lazy" width="767" height="1238" decoding="async" data-nimg="1" class="absolute z-[2] h-full w-full" style="color:transparent" src="/_next/static/media/about-img-00.18f90fff.png"/><img alt="" loading="lazy" width="767" height="1238" decoding="async" data-nimg="1" class="absolute z-[3] h-full w-full" style="color:transparent" src="/_next/static/media/about-img-01.1959f222.png"/><img alt="" loading="lazy" width="767" height="1238" decoding="async" data-nimg="1" class="absolute z-[1] h-full w-full" style="color:transparent" src="/_next/static/media/about-img-02.7960518d.png"/><img alt="" loading="lazy" width="767" height="1238" decoding="async" data-nimg="1" class="absolute z-[0] h-full w-full" style="color:transparent" src="/_next/static/media/about-img-03.930344ce.png"/></div></div><div class="w-full md:w-[50%] md:pl-[40px]"><p class="w-full md:max-w-[540px] lg:text-[18px]">Artificial intelligence is already flooding every aspect of our society. Over the next few years it will transform our civilization in ways that we can scarcely imagine—and at a dizzying, accelerating pace. <br/><br/> The only certainty is that it will not be controlled or contained by a few central players. Intelligence wants to be free, and will eventually circumvent any barriers.<br/><br/><b>We are embracing this reality with a foundation as fluid and limitless as intelligence itself. Hellas is the network for decentralized serverless AI compute, secured by an L1 blockchain, powered by our own deep learning framework.</b></p></div></div></div><div class="flex w-screen flex-col items-center justify-center py-[200px] pb-[120px]"><div class="relative flex w-full max-w-[1440px] flex-col items-center justify-center px-[20px] md:px-[40px]"><img alt="" loading="lazy" width="912" height="814" decoding="async" data-nimg="1" class="absolute top-[-150px] right-[-60px] z-[1] w-[240px] lg:top-[-130px] lg:left-[50%] lg:w-[540px]" style="color:transparent" src="/_next/static/media/keypoints-img-00.cc5e9477.png"/><img alt="" loading="lazy" width="429" height="594" decoding="async" data-nimg="1" class="absolute top-[90%] right-[80%] z-[0] w-[150px] md:top-[85%] md:right-[80%] md:w-[240px] lg:top-[55%] lg:left-[20%] lg:w-[280px]" style="color:transparent" src="/_next/static/media/keypoints-img-01.089393e6.png"/><div class="z-[0] flex w-full flex-col items-center justify-center gap-[40px] lg:flex-row lg:justify-stretch"><div class="w-full lg:nth-1:mb-[200px] lg:nth-3:mt-[200px]"><div class="flex w-full flex-col items-center justify-center gap-[40px] self-stretch rounded-[20px] border-[0.5px] border-[#767c8a]/[0.85] bg-[#e1e8ef]/[0.85] p-[40px] text-center leading-[100%] md:max-w-[300px] md:max-w-none md:p-[70px] md:py-[60px] lg:py-[80px]"><p class="mb-[10px] text-[70px]">+</p><p class="text-[28px] leading-[125%] font-bold">Trustless</p><p class="text-[16px] leading-[200%]">Compute providers can join the network trustlessly and earn the Hellas token, ensuring a fully open, permissionless compute economy</p></div></div><div class="w-full lg:nth-1:mb-[200px] lg:nth-3:mt-[200px]"><div class="flex w-full flex-col items-center justify-center gap-[40px] self-stretch rounded-[20px] border-[0.5px] border-[#767c8a]/[0.85] bg-[#e1e8ef]/[0.85] p-[40px] text-center leading-[100%] md:max-w-[300px] md:max-w-none md:p-[70px] md:py-[60px] lg:py-[80px]"><p class="mb-[10px] text-[70px]">+</p><p class="text-[28px] leading-[125%] font-bold">Permissionless</p><p class="text-[16px] leading-[200%]">Run any model off-the-shelf or custom code on Hellas’ open network without barriers, centralized control, or reliance on traditional frameworks</p></div></div><div class="w-full lg:nth-1:mb-[200px] lg:nth-3:mt-[200px]"><div class="flex w-full flex-col items-center justify-center gap-[40px] self-stretch rounded-[20px] border-[0.5px] border-[#767c8a]/[0.85] bg-[#e1e8ef]/[0.85] p-[40px] text-center leading-[100%] md:max-w-[300px] md:max-w-none md:p-[70px] md:py-[60px] lg:py-[80px]"><p class="mb-[10px] text-[70px]">+</p><p class="text-[28px] leading-[125%] font-bold">Token-secured</p><p class="text-[16px] leading-[200%]">Optimized, low-overhead AI compute is secured and incentivized with the Hellas token, ensuring efficiency, transparency and decentralized governance</p></div></div></div></div></div><div id="catgrad" class="flex w-screen flex-col items-center justify-center"><div class="flex w-full flex-col items-center justify-center gap-[80px]"><div class="flex w-full flex-col items-center justify-center gap-[80px] md:flex-row md:gap-[0px]"><div class="flex w-full flex-col items-start justify-start md:order-2 md:w-[50%]"><div class="flex w-full max-w-[560px] flex-col items-start justify-start gap-[24px] px-[20px] md:px-[40px] md:pl-[80px]"><h2 class="false text-left font-paplane w-full text-center text-[40px] leading-[110%] md:text-[60px]">catgrad</h2><p class="mb-[24px] leading-[175%]">Catgrad is our custom deep learning compiler that uses category theory to transform AI models into efficient code. By representing models as structured hypergraphs, it enables scalable, flexible, and optimized AI training in any environment without the need for traditional deep learning frameworks.</p><a href="https://catgrad.com/" target="_blank" class="group relative flex items-center justify-center gap-[12px] bg-black px-[16px] py-[12px] text-white"><div class="from-yellow-primary to-yellow-secondary absolute bottom-0 z-[0] h-[2px] w-full bg-linear-to-r transition-all duration-250 group-hover:h-[100%]"></div><p class="z-[1] transition-all duration-250 group-hover:text-black">Catgrad</p><svg id="Layer_2" data-name="Layer 2" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 27.03 27.03" width="14" height="14" class="z-[1] fill-white transition-all duration-250 group-hover:fill-black"><g><path d="M24.81,27.03h0c-1.22,0-2.22-.99-2.22-2.22V6.65c0-1.22-.99-2.22-2.22-2.22H2.22c-1.22,0-2.22-.99-2.22-2.22h0C0,.99.99,0,2.22,0h22.59c1.22,0,2.22.99,2.22,2.22v22.59c0,1.22-.99,2.22-2.22,2.22Z"></path><rect x="-3.51" y="11.73" width="33.18" height="4.43" rx="2.22" ry="2.22" transform="translate(-6.03 13.33) rotate(-45)"></rect></g></svg></a></div></div><div class="h relative mb-[-120px] flex items-center justify-center md:order-1 md:mb-[-145px] md:h-auto md:w-[50%] md:items-start md:justify-start"><img alt="catgrad Hellas AI" loading="lazy" width="1082" height="1054" decoding="async" data-nimg="1" class="absolute z-[1] w-full" style="color:transparent" src="/_next/static/media/catgrad-img-00.5a938088.png"/><img alt="catgrad Hellas AI" loading="lazy" width="1082" height="1054" decoding="async" data-nimg="1" class="z-[0] w-full" style="color:transparent" src="/_next/static/media/catgrad-img-01.8bf88292.png"/><img alt="catgrad Hellas AI" loading="lazy" width="1081" height="1054" decoding="async" data-nimg="1" class="absolute z-[2] w-full" style="color:transparent" src="/_next/static/media/catgrad-img-02.d1033c34.png"/></div></div><div class="flex w-full max-w-[1440px] flex-col items-center justify-center gap-[40px] px-[20px] md:flex-row md:items-stretch md:px-[40px]"><div class="flex w-full items-center justify-center"><div class="flex h-auto w-full flex-col items-center justify-center gap-[40px] rounded-[20px] bg-black px-[20px] py-[40px] text-center text-white md:self-stretch md:px-[40px] md:py-[60px] lg:px-[60px] lg:py-[80px]"><img alt="" loading="lazy" width="24" height="24" decoding="async" data-nimg="1" style="color:transparent" src="/_next/static/media/icon-cross.ad2651e2.svg"/><div class="flex w-full flex-col items-center justify-center gap-[20px]"><h3 class="text-[26px] leading-[150%] font-bold">ZK verification</h3><p class="text-[14px] leading-[175%] lg:text-[16px]">Enhanced with zero-knowledge proofs, Catgrad ensures secure, verifiable AI computations while preserving data privacy and decentralized trust</p></div></div></div><div class="flex w-full items-center justify-center"><div class="flex h-auto w-full flex-col items-center justify-center gap-[40px] rounded-[20px] bg-black px-[20px] py-[40px] text-center text-white md:self-stretch md:px-[40px] md:py-[60px] lg:px-[60px] lg:py-[80px]"><img alt="" loading="lazy" width="24" height="24" decoding="async" data-nimg="1" style="color:transparent" src="/_next/static/media/icon-cross.ad2651e2.svg"/><div class="flex w-full flex-col items-center justify-center gap-[20px]"><h3 class="text-[26px] leading-[150%] font-bold">Framework-free</h3><p class="text-[14px] leading-[175%] lg:text-[16px]">Compiles models into efficient code without relying on traditional frameworks like PyTorch or TensorFlow, giving developers more freedom and adaptability</p></div></div></div><div class="flex w-full items-center justify-center"><div class="flex h-auto w-full flex-col items-center justify-center gap-[40px] rounded-[20px] bg-black px-[20px] py-[40px] text-center text-white md:self-stretch md:px-[40px] md:py-[60px] lg:px-[60px] lg:py-[80px]"><img alt="" loading="lazy" width="24" height="24" decoding="async" data-nimg="1" style="color:transparent" src="/_next/static/media/icon-cross.ad2651e2.svg"/><div class="flex w-full flex-col items-center justify-center gap-[20px]"><h3 class="text-[26px] leading-[150%] font-bold">Epic scalability</h3><p class="text-[14px] leading-[175%] lg:text-[16px]">Engineered for distributed compute, enables seamless scaling across decentralized networks, ensuring efficient AI training and deployment at any scale</p></div></div></div></div></div></div><div id="research" class="flex w-screen flex-col items-center justify-center bg-[url(/img/research/research-globe.png)] bg-cover text-white md:bg-bottom"><div class="bg-bg-main mt-[-2px] h-[80px] w-full rounded-b-[30px]"></div><div class="flex w-full max-w-[1440px] flex-col items-start justify-start"><div class="flex w-full flex-col items-start justify-start gap-[40px] px-[20px] pt-[60px] pb-[80px] md:gap-[60px] md:px-[40px] md:py-[150px]"><h2 class="text-white text-left font-paplane w-full text-center text-[40px] leading-[110%] md:text-[60px]">research</h2><div class="flex w-full flex-col items-start justify-start gap-[40px] md:gap-[50px]"><div class="w-full"><a href="https://" target="_blank" class="group flex w-full items-end justify-start gap-[20px] md:gap-[40px]"><div class="relative size-[36px] md:size-[60px]"><img alt="" loading="lazy" decoding="async" data-nimg="fill" class="absolute opacity-100 transition-all duration-300 group-hover:opacity-0" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" src="/_next/static/media/icon-hyperlink.8df5c05c.svg"/><img alt="" loading="lazy" decoding="async" data-nimg="fill" class="absolute opacity-0 transition-all duration-300 group-hover:opacity-100" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" src="/_next/static/media/icon-hyperlink-yellow.f3cb9788.svg"/></div><div class="group-hover:text-yellow-primary w-full border-b-[0.5px] border-white/[0.5] pb-[8px] text-[14px] leading-[175%] font-[700] transition-all duration-300 md:text-[24px]">Data-Parallel Algorithms for String Diagrams</div></a></div><div class="w-full"><a href="https://" target="_blank" class="group flex w-full items-end justify-start gap-[20px] md:gap-[40px]"><div class="relative size-[36px] md:size-[60px]"><img alt="" loading="lazy" decoding="async" data-nimg="fill" class="absolute opacity-100 transition-all duration-300 group-hover:opacity-0" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" src="/_next/static/media/icon-hyperlink.8df5c05c.svg"/><img alt="" loading="lazy" decoding="async" data-nimg="fill" class="absolute opacity-0 transition-all duration-300 group-hover:opacity-100" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" src="/_next/static/media/icon-hyperlink-yellow.f3cb9788.svg"/></div><div class="group-hover:text-yellow-primary w-full border-b-[0.5px] border-white/[0.5] pb-[8px] text-[14px] leading-[175%] font-[700] transition-all duration-300 md:text-[24px]">Reverse Derivative Ascent: A Categorical Approach to Learning Boolean Circuits</div></a></div><div class="w-full"><a href="https://" target="_blank" class="group flex w-full items-end justify-start gap-[20px] md:gap-[40px]"><div class="relative size-[36px] md:size-[60px]"><img alt="" loading="lazy" decoding="async" data-nimg="fill" class="absolute opacity-100 transition-all duration-300 group-hover:opacity-0" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" src="/_next/static/media/icon-hyperlink.8df5c05c.svg"/><img alt="" loading="lazy" decoding="async" data-nimg="fill" class="absolute opacity-0 transition-all duration-300 group-hover:opacity-100" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" src="/_next/static/media/icon-hyperlink-yellow.f3cb9788.svg"/></div><div class="group-hover:text-yellow-primary w-full border-b-[0.5px] border-white/[0.5] pb-[8px] text-[14px] leading-[175%] font-[700] transition-all duration-300 md:text-[24px]">Categories of Differentiable Polynomial Circuits for Machine Learning</div></a></div></div></div></div><div class="bg-bg-main mt-[-2px] h-[80px] w-full rounded-t-[30px]"></div></div><div id="team" class="flex w-screen flex-col items-center justify-center gap-[60px]"><h2 class="false text-center font-paplane w-full text-center text-[40px] leading-[110%] md:text-[60px]">meet the team</h2><div class="grid grid-cols-1 gap-[80px] px-[20px] md:grid-cols-2 md:px-[40px] xl:grid-cols-4"><div class="false relative"><div class="absolute right-[50%] z-[0] top-[10%]"><img alt="" loading="lazy" width="284" height="39" decoding="async" data-nimg="1" style="color:transparent" src="/_next/static/media/team-bar.ddb79f31.png"/></div><div class="relative flex w-full max-w-[300px] flex-col items-center justify-center text-center md:max-w-[450px]"><img alt="George Whewell" loading="lazy" width="721" height="898" decoding="async" data-nimg="1" class="w-full" style="color:transparent" src="/_next/static/media/team-george.12938768.png"/><div class="mt-[-20px] flex w-full flex-col items-center justify-center gap-[20px]"><p class="text-[22px] font-bold">George Whewell</p><p class="w-full max-w-[320px] text-[16px]">George Whewell is an experienced software engineer with an interest in OSS, P2P, and permissionless software. He has previously worked on Foundry, ethers-rs, Moonbeam and ZKSync tooling.</p></div><a href="https://x.com/0xBaltar/" class="group relative mt-[24px] flex size-[50px] items-center justify-center"><img alt="Twitter" loading="lazy" width="54" height="54" decoding="async" data-nimg="1" class="absolute size-[50px] opacity-100 transition-all duration-300 group-hover:opacity-0" style="color:transparent" src="/_next/static/media/icon-x-enabled.478b4d34.svg"/><img alt="Twitter" loading="lazy" width="54" height="54" decoding="async" data-nimg="1" class="absolute size-[50px] opacity-0 transition-all duration-300 group-hover:opacity-100" style="color:transparent" src="/_next/static/media/icon-x-hovered.9d92bb10.svg"/></a></div></div><div class="lg:mt-[60%] relative"><div class="absolute left-1/2 z-[1] -translate-x-1/2 transform top-[10%]"><img alt="" loading="lazy" width="284" height="39" decoding="async" data-nimg="1" style="color:transparent" src="/_next/static/media/team-bar.ddb79f31.png"/></div><div class="relative flex w-full max-w-[300px] flex-col items-center justify-center text-center md:max-w-[450px]"><img alt="Jani Monoses" loading="lazy" width="721" height="898" decoding="async" data-nimg="1" class="w-full" style="color:transparent" src="/_next/static/media/team-jani.8c47bf46.png"/><div class="mt-[-20px] flex w-full flex-col items-center justify-center gap-[20px]"><p class="text-[22px] font-bold">Jani Monoses</p><p class="w-full max-w-[320px] text-[16px]">Jani Monoses is a veteran software engineer, former Ubuntu core developer, Xubuntu project founder and Linux Kernel developer with a passion for open source software. He has a keen interest in machine learning, with contributions to software like catgrad, candle-rs, vLLM, and SGLang.</p></div></div></div><div class="false relative"><div class="absolute top-[12%] left-[12%] z-[0] top-[10%]"><img alt="" loading="lazy" width="284" height="39" decoding="async" data-nimg="1" style="color:transparent" src="/_next/static/media/team-bar.ddb79f31.png"/></div><div class="relative flex w-full max-w-[300px] flex-col items-center justify-center text-center md:max-w-[450px]"><img alt="Paul Wilson" loading="lazy" width="720" height="898" decoding="async" data-nimg="1" class="w-full" style="color:transparent" src="/_next/static/media/team-paul.080546b4.png"/><div class="mt-[-20px] flex w-full flex-col items-center justify-center gap-[20px]"><p class="text-[22px] font-bold">Paul Wilson</p><p class="w-full max-w-[320px] text-[16px]">Dr. Paul Wilson is a computer scientist whose research combines category theory and machine learning, with work focusing on data parallel AoT automatic differentiation algorithms.</p></div><a href="https://x.com/statusfailed" class="group relative mt-[24px] flex size-[50px] items-center justify-center"><img alt="Twitter" loading="lazy" width="54" height="54" decoding="async" data-nimg="1" class="absolute size-[50px] opacity-100 transition-all duration-300 group-hover:opacity-0" style="color:transparent" src="/_next/static/media/icon-x-enabled.478b4d34.svg"/><img alt="Twitter" loading="lazy" width="54" height="54" decoding="async" data-nimg="1" class="absolute size-[50px] opacity-0 transition-all duration-300 group-hover:opacity-100" style="color:transparent" src="/_next/static/media/icon-x-hovered.9d92bb10.svg"/></a></div></div><div class="lg:mt-[60%] relative"><div class="absolute left-[50%] z-[0] top-[10%]"><img alt="" loading="lazy" width="284" height="39" decoding="async" data-nimg="1" style="color:transparent" src="/_next/static/media/team-bar.ddb79f31.png"/></div><div class="relative flex w-full max-w-[300px] flex-col items-center justify-center text-center md:max-w-[450px]"><img alt="Ember Arlynx" loading="lazy" width="720" height="898" decoding="async" data-nimg="1" class="w-full" style="color:transparent" src="/_next/static/media/team-ember.c370c7ad.png"/><div class="mt-[-20px] flex w-full flex-col items-center justify-center gap-[20px]"><p class="text-[22px] font-bold">Ember Arlynx</p><p class="w-full max-w-[320px] text-[16px]">Ember Richardson Arlynx, formerly of o1Labs (Mina Protocol) and the Rust project, believes in using maths and formal methods to make open source computer systems that deserve the trust we place in them.</p></div><a href="https://x.com/ember_arlynx" class="group relative mt-[24px] flex size-[50px] items-center justify-center"><img alt="Twitter" loading="lazy" width="54" height="54" decoding="async" data-nimg="1" class="absolute size-[50px] opacity-100 transition-all duration-300 group-hover:opacity-0" style="color:transparent" src="/_next/static/media/icon-x-enabled.478b4d34.svg"/><img alt="Twitter" loading="lazy" width="54" height="54" decoding="async" data-nimg="1" class="absolute size-[50px] opacity-0 transition-all duration-300 group-hover:opacity-100" style="color:transparent" src="/_next/static/media/icon-x-hovered.9d92bb10.svg"/></a></div></div></div></div><div class="relative flex w-screen flex-col items-center justify-center gap-[60px] py-[120px]"><h2 class="false text-center font-paplane w-full text-center text-[40px] leading-[110%] md:text-[60px]">join the community</h2><div class="relative flex w-full items-center justify-center"><div class="absolute left-0 flex w-[50%] items-center justify-center pr-[120px] md:pr-[70px]"><img alt="" loading="lazy" width="911" height="489" decoding="async" data-nimg="1" class="right-0 h-[118px] md:h-auto md:w-full" style="color:transparent" src="/_next/static/media/socials-bg-l.8dab12a4.svg"/></div><img alt="" loading="lazy" width="482" height="373" decoding="async" data-nimg="1" class="z-[1] w-[60%] md:w-[25%]" style="color:transparent" src="/_next/static/media/socials-discord-big.d6d2452a.svg"/><div class="absolute right-0 flex w-[50%] items-center justify-center pl-[120px] md:pl-[70px]"><img alt="" loading="lazy" width="911" height="489" decoding="async" data-nimg="1" class="left-0 h-[118px] md:h-auto md:w-full" style="color:transparent" src="/_next/static/media/socials-bg-r.88e5c3ef.svg"/></div></div><div class="flex w-full flex-col items-center justify-center gap-[24px] px-[20px] md:px-[40px]"><p class="w-full max-w-[540px] text-center text-[16px] md:text-[20px]">Connect with us!</p><a href="https://discord.gg/YWZCWPrNTb" target="_blank" class="group relative flex items-center justify-center gap-[12px] bg-black px-[16px] py-[12px] text-white"><div class="from-yellow-primary to-yellow-secondary absolute bottom-0 z-[0] h-[2px] w-full bg-linear-to-r transition-all duration-250 group-hover:h-[100%]"></div><p class="z-[1] transition-all duration-250 group-hover:text-black">Discord</p><svg id="Layer_2" data-name="Layer 2" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 27.03 27.03" width="14" height="14" class="z-[1] fill-white transition-all duration-250 group-hover:fill-black"><g><path d="M24.81,27.03h0c-1.22,0-2.22-.99-2.22-2.22V6.65c0-1.22-.99-2.22-2.22-2.22H2.22c-1.22,0-2.22-.99-2.22-2.22h0C0,.99.99,0,2.22,0h22.59c1.22,0,2.22.99,2.22,2.22v22.59c0,1.22-.99,2.22-2.22,2.22Z"></path><rect x="-3.51" y="11.73" width="33.18" height="4.43" rx="2.22" ry="2.22" transform="translate(-6.03 13.33) rotate(-45)"></rect></g></svg></a></div></div><div id="faq" class="flex w-screen items-center justify-center bg-radial-[at_75%_25%] from-[#d5e1f7] to-[#767c8a] px-[20px] py-[120px] md:px-[40px]"><div class="flex w-full max-w-[1080px] flex-col items-start justify-start gap-[40px] md:flex-row md:gap-[120px]"><h2 class="font-paplane w-full text-left text-[60px] leading-[110%] md:w-auto md:text-[60px] xl:text-[90px]">FAQ</h2><div class="flex w-full flex-col items-start justify-start"><div class="w-full"><div class="flex w-full cursor-pointer flex-col items-start justify-start border-b-1 border-black pt-[18px] pb-[9px]"><p class="w-full pb-[9px] text-[18px] font-bold">Q. What advantages does Catgrad provide?</p><p class="max-h-[0px] w-full overflow-hidden text-[16px] leading-[175%] transition-all duration-700 ease-in-out">Models in catgrad are completely symbolic and use a tiny number of core ops (like tinygrad!). This means that models have a small representation which can be optimized, serialized and transferred between hosts. This lets us run your model on any appropriate hardware, from an H200 or an iPhone, without overhead.</p></div></div><div class="w-full"><div class="flex w-full cursor-pointer flex-col items-start justify-start border-b-1 border-black pt-[18px] pb-[9px]"><p class="w-full pb-[9px] text-[18px] font-bold">Q. What models are supported on the Hellas Network?</p><p class="max-h-[0px] w-full overflow-hidden text-[16px] leading-[175%] transition-all duration-700 ease-in-out">The Hellas Network supports any model: you just needs to express it in Catgrad. We're adding more models every day, but you can also add your own: it's fully permissionless.</p></div></div><div class="w-full"><div class="flex w-full cursor-pointer flex-col items-start justify-start border-b-1 border-black pt-[18px] pb-[9px]"><p class="w-full pb-[9px] text-[18px] font-bold">Q: How difficult is it to write models in Catgrad?</p><p class="max-h-[0px] w-full overflow-hidden text-[16px] leading-[175%] transition-all duration-700 ease-in-out">Right now, it's as easy as implementing a model in any other framework -- but we're working on tools for importing models from other frameworks like Torch.</p></div></div><div class="w-full"><div class="flex w-full cursor-pointer flex-col items-start justify-start border-b-1 border-black pt-[18px] pb-[9px]"><p class="w-full pb-[9px] text-[18px] font-bold">Q. How do I know my computation has been run correctly?</p><p class="max-h-[0px] w-full overflow-hidden text-[16px] leading-[175%] transition-all duration-700 ease-in-out">The Hellas Network uses a combination of economic incentives, optimistic security, and Zero-Knowledge proofs to ensure your computation is run correctly.</p></div></div><div class="w-full"><div class="flex w-full cursor-pointer flex-col items-start justify-start border-b-1 border-black pt-[18px] pb-[9px]"><p class="w-full pb-[9px] text-[18px] font-bold">Q. What security guarantees does the Hellas Network provide?</p><p class="max-h-[0px] w-full overflow-hidden text-[16px] leading-[175%] transition-all duration-700 ease-in-out">The Hellas Network ensures that when your model is run, the output can be trusted.</p></div></div><div class="w-full"><div class="flex w-full cursor-pointer flex-col items-start justify-start border-b-1 border-black pt-[18px] pb-[9px]"><p class="w-full pb-[9px] text-[18px] font-bold">Q. 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