Vimo Labs' flagship product Gymatic is the only app of its kind that auto tracks indoor workouts

Vimo Labs

I’m an iOS Engineer at where I develop for game devs. Not so long ago I got a task to completely reimplement UI and animations. One of the most interesting parts was implementing of balance view with rolling animation of the number in it: Triumph Labs TriumphSDK https://vimeo.com/813889559 At the first sight, it looks pretty simple but we needed a well-configured custom solution. Of course, I checked existing libraries that I could reuse and adjust this kind of animation for our needs. After the first try, I figured out that the libraries are not so adjustable and we cannot control the animation of each number. I won’t go into details too much, however, I decided to make my own solution from scratch. Now it is an open-source project that is available as Cocoapod and Swift package: https://github.com/maxkalik/RollingNumbers CALayers I had a list of requirements — how should the animation look, but also I added another one — the component should be implemented only using . Why? Most of the libraries that I checked were implemented using only . The typical approach is making or inside of a where arranged views are UILabels. The rolling animation is implemented by using changing constraints. That’s absolutely ok but I wanted as much as possible to reduce the workload of performance. CALayers UIViews UIScrollViews UIStackVeiws UIView UIView.animate represent the visual content of . Layers provide low-level API of an efficient and more detailed configuration of rendering and animation using a low-cost framework. Another important thing about Layers is that they are rendered using only GPU resources. This means the CPU will be free for another calculation task while the animation is running — that’s what I wanted to mention about performance. CALayers UIView Core Animation Solution If to check open-source solutions, the approach of how to construct the view is everywhere almost the same: a stack of numbers but visible ones only based on the state. My wireframe looks the same but different :) As you can see in the picture the stacks of numbers are doubled, this means the number of elements in one stack is 20. This particular number of elements needs a smooth transition from an initial state to the next one and in the meantime the direction of rolling I wanted to be fully configurable. Let’s say, if a stack would have only 10 elements (and it would be pretty reasonable from the first sight) then the rolling direction from one digit to another would be always different. I needed to obey the direction rolling, for example, all digits from up to down. Each stack in the view is where sublayers are numbers. The numbers are arranged by the same height, which means it’s easy to calculate the next position of the future number. CALayer Characters All characters are and they have their own width. If to use it’s not needed to care about width, all will be arranged by view configuration, but in my case — don’t have such default implementation so it means it should be calculated. CATextLayers UIStackView CALayers To get the width of a character is a pretty straight-forward task using and font: NSAttributedString } private func prepareWidthOfChar ( _ char : Character ) -> Double { let fontAttributes = [ NSAttributedString . Key .font: font] let size = String (char).size(withAttributes: fontAttributes as [ NSAttributedString .Key : Any ]) return size.width * characterSpacing This function also helps to calculate an actual with of all columns in the Rolling Numbers view. To get this information a developer can use the public property . width Animation Configuration To achieve the spring animation effect I used changing position of the — a column where sublayers are numbers . CASpringAnimation y CALayer CATextLayers } } private func animate ( config : RollingNumbersView . AnimationConfiguration , completion : (() -> Void ) ? = nil ) { CATransaction .begin() let animation: CASpringAnimation = CASpringAnimation (keyPath: "position.y" ) let fromValue: CGFloat = position.y let toValue: CGFloat = moveToDigit() animation.fromValue = fromValue animation.toValue = toValue animation.duration = config.duration animation.speed = config.speed animation.damping = config.damping animation.initialVelocity = config.initialVelocity animation.isRemovedOnCompletion = false animation.fillMode = .forwards CATransaction .setCompletionBlock { completion ? () add(animation, forKey: nil ) CATransaction .commit() Additionally, I used to catch the animation completion moment which reference I exposed in the Rolling Numbers view API as trailing completion. It happens only once after setting a new number with animation. CATransaction } rollingNumbersView.setNumberWithAnimation( 245699 ) { // completion For the default animation config, I prepared a separate called: . There are 4 initial configurations of the spring animation that are publically accessible. struct AnimationConfiguration duration: CFTimeInterval = 1 , speed: Float = 0.3 , damping: CGFloat = 17 , initialVelocity: CGFloat = 1 Animation Type There are 4 animation types prepared for usage: } public enum AnimationType { case allNumbers case onlyChangedNumbers case allAfterFirstChangedNumber case noAnimation is accessible using public property . AnimationType animationType Let’s consider an example formatted as US currency. The initial value is $4.588.77. The future value is $4.5 7 76.6 (the changed numbers in the price I highlighted in bold). By default, the animation is set up with . This means if a future number is in the middle of the horizontal string then all others digits after this number will be animated. If to use — this means literally: if a future number is different then only this number column will be scrolled. But somebody will need to roll all digits so for this you can use just . .allAfterFirstChangedNumber .onlyChangedNumbers .allNumbers Rolling Direction The numbers rolling direction can be configured using specific public properties : obviously only two directions: and . For example, if to set up this property as then the numbers in the view will always move in the up direction. However, initially, this property is nil which means by default the direction depends on a future number. If the future number will be less than the old one then the numbers column will move down and vice versa. rollingDirection RollingDirectionwhere .up .down .up Formatting There are several options to format the Rolling Numbers: alignment, character spacing, font, , and text color. NumberFormatterconfigurator }() var rollingNumbersView = { // Initialize Rolling Numbers view with initial number value let view = RollingNumbersView (number: 1234.56 ) // Spacing between numbers view.characterSpacing = 1 // Text color view.textColor = .black // Alignment within UIView view.alignment = .left // UIFont view.font = .systemFont(ofSize: 48 , weight: .medium) let formatter = NumberFormatter () formatter.numberStyle = .currency view.formatter = formatter return view Changing the size of the font keep in mind that the actual height of the view can be smaller, this means the digits can be invisible. Besides general public property , there is another interesting public method: textColor rollingNumbersView.setTextColor(.blue, withAnimationDuration: 3 ) Under the hood, the animation implemented using of .The public method helps to change the color of the text (numbers) while moving animation is happening! As an option changing color can be also an animation with duration. CABasicAnimation forgroundColor setTextColor Wrapping up I enjoy building UI for mobile apps and solving performance problems. If it’s needed to use more than just then Apple Documentation and tons of examples can help to make a more efficient solution. UIView When I finished building the Rolling Numbers component, I decided to share my solution with everyone — making a public library. Full documentation of usage of Rolling Number you can get from the GitHub repository: . Welcome to everyone who can contribute and suggest improvements to this project via PR! https://github.com/maxkalik/RollingNumbers Links Core Animation Programming Guide CALayer Rolling Numbers

Rolling Numbers Animation Using Only CALayers

Businesses increasingly recognize the potential of generative artificial intelligence (GenAI). However, many organizations find themselves trapped in a cycle of endless pilot projects, unable to fully realize the benefits of GenAI in production environments. The AI control platform Aporia is changing how enterprises adopt and scale GenAI solutions, pushing them to break free from pilot limbo and achieve live success. "At Aporia, our mission is to maximize the immense potential of GenAI and the real-world challenges that hinder its widespread adoption," says Liran Hason, Chief Executive Officer (CEO) of Aporia, who coined the term “GenAI Chasm,” referring to the pilot phase AI often gets caught in before being able to go live due to security and reliability issues. With its guardrails and comprehensive risk mitigation strategies, the company is opening new avenues for seamless GenAI deployment across industries. Aporia's Robust Guardrails for Seamless GenAI Adoption One of the primary challenges in GenAI deployment is the lack of adequate control and risk management. Aporia’s comprehensive suite of tools is meant to ensure safe, responsible, and compliant AI interactions. These guardrails seamlessly integrate with existing AI workflows, providing a powerful layer of protection against potential risks such as data leakage, hallucinations, and prompt injection attacks. "Aporia's guardrails are the cornerstone of our platform," explains Hason. "They empower businesses to adopt GenAI with confidence, secure in the knowledge that their applications are reliable, secure, and aligned with their core values and objectives.” Mitigating Hallucinations and Prompt Injection Risks Hallucinations and prompt injection attacks pose threats to the integrity and reliability of GenAI applications. Aporia addresses these challenges with a multi-faceted approach that combines advanced detection algorithms, real-time actions, and proactive mitigation strategies. "Hallucinations and prompt injections can erode trust in AI systems and lead to severe consequences," notes Hason. "Our comprehensive approach ensures that these risks are identified and mitigated before they can impact end-users or the business." With Aporia's robust safeguards, organizations can confidently deploy GenAI applications, knowing their systems are protected against these critical threats. Ensuring Compliance and Ethical AI Deployment with Aporia's Solutions GenAI is becoming more prevalent, and compliance with regulations and ethical standards is paramount. Aporia's solutions are designed to help businesses deal with this complex landscape easily and to cross the GenAI chasm with confidence. "Compliance and ethics are not mere afterthoughts for us. They are embedded in the very fabric of our platform," states Hason. "We firmly believe that the long-term success of GenAI hinges on its ability to operate within a framework of trust, transparency, and accountability from both the user and business perspective." Pioneering Research for Secure and Reliable GenAI Applications Aporia Labs, Aporia's dedicated research and development division, is advancing the platform’s security and reliability. Staffed by a team of world-class AI researchers, security experts, and data scientists, Aporia Labs conducts constant research to identify emerging threats and develop services. "The work we do at Aporia Labs is instrumental to the future of GenAI. It's shaping the very trajectory of the industry," says Hason. Aporia Labs makes way for secure and reliable GenAI applications through its pioneering research. How Aporia Streamlines the GenAI Development Lifecycle Aporia's AI control platform is designed to streamline the entire GenAI development lifecycle, from ideation to deployment and beyond. A unified environment for building, testing, and monitoring GenAI applications enables teams to deliver better results. Furthermore, the platform's intuitive interface and powerful automation capabilities make it easy for businesses to bring their GenAI visions to life without compromising quality or security. "We've witnessed firsthand the transformative impact of Aporia on the GenAI development process," shares Hason. With Aporia, organizations can streamline their GenAI development efforts, accelerating time-to-market and maximizing the return on their AI investments. The Key to Unlocking GenAI's Full Potential in Enterprise Settings For enterprises seeking to harness GenAI's full potential, Aporia's AI control platform is the key to success. With its comprehensive feature set, scalable architecture, and enterprise-grade security, the platform is able to meet large-scale AI deployments' unique needs and challenges. From customizable guardrails to advanced analytics and reporting, Aporia provides the tools and insights to drive GenAI adoption and return on investment (ROI) across the organization. "Enterprises face complex challenges when it comes to scaling GenAI, from ensuring security and governance to driving organization-wide adoption," notes Hason. "Aporia's platform is purpose-built to address these challenges head-on, enabling enterprises to unlock the full potential of GenAI and drive transformative business outcomes." Bridging the Gap: Aporia's Proven Strategies for Successful GenAI Pilot-to-Production Transitions Transitioning GenAI projects from pilot to production is a critical milestone many businesses struggle with. Aporia bridges this gap with proven strategies and best practices that have helped countless organizations successfully deal with this journey. Aporia remains a leading enabler for businesses to unlock the full potential of this advanced technology. With Aporia, businesses can confidently solve the challenges of GenAI deployment, harnessing its immense potential to drive growth and become a more competitive advantage in an AI-driven future. This piece was published as a part of HackerNoon’s Business Blogging Program. For more details, please click here. Businesses increasingly recognize the potential of generative artificial intelligence (GenAI). However, many organizations find themselves trapped in a cycle of endless pilot projects, unable to fully realize the benefits of GenAI in production environments. Businesses increasingly recognize the potential of generative artificial intelligence (GenAI). However, many organizations find themselves trapped in a cycle of endless pilot projects, unable to fully realize the benefits of GenAI in production environments. The AI control platform Aporia is changing how enterprises adopt and scale GenAI solutions, pushing them to break free from pilot limbo and achieve live success. Aporia Aporia " At Aporia, our mission is to maximize the immense potential of GenAI and the real-world challenges that hinder its widespread adoption, " says Liran Hason, Chief Executive Officer (CEO) of Aporia, who coined the term “GenAI Chasm,” referring to the pilot phase AI often gets caught in before being able to go live due to security and reliability issues. With its guardrails and comprehensive risk mitigation strategies, the company is opening new avenues for seamless GenAI deployment across industries. At Aporia, our mission is to maximize the immense potential of GenAI and the real-world challenges that hinder its widespread adoption, Aporia's Robust Guardrails for Seamless GenAI Adoption Aporia's Robust Guardrails for Seamless GenAI Adoption One of the primary challenges in GenAI deployment is the lack of adequate control and risk management. Aporia’s comprehensive suite of tools is meant to ensure safe, responsible, and compliant AI interactions. These guardrails seamlessly integrate with existing AI workflows, providing a powerful layer of protection against potential risks such as data leakage, hallucinations, and prompt injection attacks. "Aporia's guardrails are the cornerstone of our platform," explains Hason. " They empower businesses to adopt GenAI with confidence, secure in the knowledge that their applications are reliable, secure, and aligned with their core values and objectives.” "Aporia's guardrails are the cornerstone of our platform," They empower businesses to adopt GenAI with confidence, secure in the knowledge that their applications are reliable, secure, and aligned with their core values and objectives.” Mitigating Hallucinations and Prompt Injection Risks Mitigating Hallucinations and Prompt Injection Risks Hallucinations and prompt injection attacks pose threats to the integrity and reliability of GenAI applications. Aporia addresses these challenges with a multi-faceted approach that combines advanced detection algorithms, real-time actions, and proactive mitigation strategies. "Hallucinations and prompt injections can erode trust in AI systems and lead to severe consequences," notes Hason. " Our comprehensive approach ensures that these risks are identified and mitigated before they can impact end-users or the business." With Aporia's robust safeguards, organizations can confidently deploy GenAI applications, knowing their systems are protected against these critical threats. "Hallucinations and prompt injections can erode trust in AI systems and lead to severe consequences," Our comprehensive approach ensures that these risks are identified and mitigated before they can impact end-users or the business." Ensuring Compliance and Ethical AI Deployment with Aporia's Solutions Ensuring Compliance and Ethical AI Deployment with Aporia's Solutions GenAI is becoming more prevalent, and compliance with regulations and ethical standards is paramount. Aporia's solutions are designed to help businesses deal with this complex landscape easily and to cross the GenAI chasm with confidence. "Compliance and ethics are not mere afterthoughts for us. They are embedded in the very fabric of our platform," states Hason. " We firmly believe that the long-term success of GenAI hinges on its ability to operate within a framework of trust, transparency, and accountability from both the user and business perspective." "Compliance and ethics are not mere afterthoughts for us. They are embedded in the very fabric of our platform," We firmly believe that the long-term success of GenAI hinges on its ability to operate within a framework of trust, transparency, and accountability from both the user and business perspective." Pioneering Research for Secure and Reliable GenAI Applications Pioneering Research for Secure and Reliable GenAI Applications Aporia Labs, Aporia's dedicated research and development division, is advancing the platform’s security and reliability. Staffed by a team of world-class AI researchers, security experts, and data scientists, Aporia Labs conducts constant research to identify emerging threats and develop services. "The work we do at Aporia Labs is instrumental to the future of GenAI. It's shaping the very trajectory of the industry," says Hason. Aporia Labs makes way for secure and reliable GenAI applications through its pioneering research. "The work we do at Aporia Labs is instrumental to the future of GenAI. It's shaping the very trajectory of the industry," How Aporia Streamlines the GenAI Development Lifecycle How Aporia Streamlines the GenAI Development Lifecycle Aporia's AI control platform is designed to streamline the entire GenAI development lifecycle, from ideation to deployment and beyond. A unified environment for building, testing, and monitoring GenAI applications enables teams to deliver better results. Furthermore, the platform's intuitive interface and powerful automation capabilities make it easy for businesses to bring their GenAI visions to life without compromising quality or security. "We've witnessed firsthand the transformative impact of Aporia on the GenAI development process," shares Hason. With Aporia, organizations can streamline their GenAI development efforts, accelerating time-to-market and maximizing the return on their AI investments. "We've witnessed firsthand the transformative impact of Aporia on the GenAI development process," The Key to Unlocking GenAI's Full Potential in Enterprise Settings The Key to Unlocking GenAI's Full Potential in Enterprise Settings For enterprises seeking to harness GenAI's full potential, Aporia's AI control platform is the key to success. With its comprehensive feature set, scalable architecture, and enterprise-grade security, the platform is able to meet large-scale AI deployments' unique needs and challenges. From customizable guardrails to advanced analytics and reporting, Aporia provides the tools and insights to drive GenAI adoption and return on investment (ROI) across the organization. "Enterprises face complex challenges when it comes to scaling GenAI, from ensuring security and governance to driving organization-wide adoption," notes Hason. "Aporia's platform is purpose-built to address these challenges head-on, enabling enterprises to unlock the full potential of GenAI and drive transformative business outcomes." "Enterprises face complex challenges when it comes to scaling GenAI, from ensuring security and governance to driving organization-wide adoption," "Aporia's platform is purpose-built to address these challenges head-on, enabling enterprises to unlock the full potential of GenAI and drive transformative business outcomes." Bridging the Gap: Aporia's Proven Strategies for Successful GenAI Pilot-to-Production Transitions Bridging the Gap: Aporia's Proven Strategies for Successful GenAI Pilot-to-Production Transitions Transitioning GenAI projects from pilot to production is a critical milestone many businesses struggle with. Aporia bridges this gap with proven strategies and best practices that have helped countless organizations successfully deal with this journey. Aporia remains a leading enabler for businesses to unlock the full potential of this advanced technology. With Aporia, businesses can confidently solve the challenges of GenAI deployment, harnessing its immense potential to drive growth and become a more competitive advantage in an AI-driven future. This piece was published as a part of HackerNoon’s Business Blogging Program. For more details, please click here. This piece was published as a part of HackerNoon’s Business Blogging Program. For more details, please click here . here

How Aporia Enables GenAI Deployment From Pilot Limbo to Live Success

অ্যাপোরিয়া কীভাবে পাইলট লিম্বো থেকে লাইভ সাফল্যের জন্য GenAI স্থাপনাকে সক্ষম করে

Wie Aporia die GenAI-Bereitstellung von der Pilotphase bis zum Live-Erfolg ermöglicht

Cómo Aporia permite la implementación de GenAI desde el limbo piloto hasta el éxito en vivo

Comment Aporia permet le déploiement de GenAI des limbes pilotes au succès réel

एपोरिया कैसे जेनएआई की तैनाती को पायलट लिम्बो से लाइव सफ़लता तक सक्षम बनाता है

Aporia が GenAI の導入をパイロット段階から実際の成功まで可能にする方法

Aporia가 파일럿 림보(Pilot Limbo)에서 실제 성공까지 GenAI 배포를 활성화하는 방법

Como Aporia permite a implantação de GenAI do piloto Limbo ao sucesso ao vivo

Как Aporia обеспечивает развертывание GenAI от экспериментального неопределенности до реального успеха

Aporia, Pilot Araf'tan Canlı Başarıya Kadar GenAI Dağıtımını Nasıl Etkinleştiriyor?

Cách Aporia cho phép triển khai GenAI từ thí điểm Limbo đến thành công trực tiếp

Aporia 如何使 GenAI 部署从试点走向成功

I remember the day one of my good friends reached out and asked if I had heard about Nuklai. I simply told him, “Not really. That sounds like a topic I would study in my science class.” Fast forward six months, and here I am, building a Layer 1 blockchain network for Nuklai. Who would’ve thought? It is amazing where life takes you in a matter of months. I will get to the core of this blog about my journey into the world of HyperVMs, but before that, it is essential to know how I even got to this point. The Challenge of High Throughput Soon after I heard about Nuklai, I started to research the project to see what all the hype was about. I was really blown away by Nuklai’s vision to empower every user by allowing them to sell their data to other entities, shifting the power from big businesses to the users themselves. It is a simple yet profound vision because, to achieve it, much had to be done not just at the application level but also at the infrastructure and blockchain protocol levels. When dealing with massive amounts of data daily, the blockchain must handle an immense load that no current platform has achieved yet. People talk about Transactions Per Second (TPS), but few know what it truly takes to achieve such high TPS at the blockchain level. Yes, there are blockchains out there with high throughput, but often, they are very hacky and not true Layer 1s. Usually, the approach is to scale horizontally by creating Layer 2s, Layer 3s, sidechains, and whatnot. These solutions feel like patchwork to me because if you introduce an additional layer to your blockchain, increasing the TPS seems more like an afterthought than something built from the ground up. This is where HyperVMs come into play. HyperVMs, Unlocking High-Performance Blockchains But, what is a HyperVM? It’s essentially a virtual machine (VM) built using the HyperSDK framework. To understand HyperSDK, we first need to understand Avalanche. According to their documentation, Avalanche is an open-source platform for building decentralized applications in one interoperable, decentralized, and highly scalable ecosystem. Powered by a uniquely powerful consensus mechanism, Avalanche is the first ecosystem designed to accommodate the scale of global finance, with near-instant transaction finality. The Avalanche consensus mechanism is ridiculously fast, with less than 2 seconds of finality, meaning your transaction is processed and verified almost instantly. Avalanche also allows you to create your own Layer 1 blockchain (or subnet), and the best part is you are not confined to an Ethereum Virtual Machine (EVM) powered subnet. Despite its large developer community, the EVM is not lightweight and comes with a lot of baggage. On Avalanche, you can also launch your own subnet by developing your own VM in any language as long as it conforms to Avalanche’s Proto interfaces. This is where HyperSDK comes into play. Theoretically, you could build your own VM in any language you want, as Avalanche provides that freedom. However, it is also true that it is rather difficult and time-intensive to do from scratch. Even if you use Subnet EVM to get started, it is complex to keep it up-to-date as the core code changes frequently. You need to keep up with maintaining it, which can become resource-intensive. HyperSDK addresses this issue by making it faster, safer, and easier to launch your own optimized blockchain on an Avalanche subnet. It hides much of the complexity, allowing you to focus on making your project unique rather than worrying about transaction serialization efficiency or increasing transaction throughput. With HyperSDK, you can build your own blockchain runtime with 500-1000 lines of code and still process thousands of transactions per second without needing a large team of engineers. HelixVM: The 100,000 tx/s Powerhouse? At Nuklai, we built our own blockchain runtime, called ‘HelixVM,’ using the HyperSDK framework with around 200 lines of code in under a week. We added exciting features such as natively issuing tokens, bridging tokens from one subnet to another using Avalanche Warp Messaging (AWM), and developing a staking engine that lets validators register for staking and users delegate their NAI tokens to a validator of their choice to start claiming rewards. With some more additions and custom touches, we added everything with around 500 more lines of code in a couple of months. The journey to get here was extraordinary but equally rewarding. The best part about building our runtime using HyperSDK is that we benefit from the optimizations that come to the HyperSDK framework, worked on by some of the best engineers from Ava Labs and the wider open-source HyperSDK community. For example, with the development of HyperSDK Vryx, which recently produced exceptional results with HyperVMs processing over 5 billion transactions at 100,000 transactions per second, once our HelixVM supports Vryx, it will also process 100,000 transactions per second. This is the true hidden power of using HyperSDK to build your own blockchain runtime    Achieving this level of optimization without having to do it ourselves makes it a no-brainer for any team to build their own runtime as well. At Nuklai, we want to build a platform that lets users and businesses monetize their data as easily as building a website, and HyperSDK is the ultimate base layer to achieve that without worrying about how the consensus engine works. We want to build a unique platform that suits our needs, and HyperSDK makes it possible with just a few hundred lines of code. Build the Future of Smart Data With Nuklai Testnet Recently, we released our Nuklai testnet. It only took a few months to get here, and we have many exciting features planned for our HelixVM before the mainnet release, coinciding with HyperSDK’s own roadmap of being production-ready. If you want to get started with our testnet, check out the Nuklai Wallet repository, clone it locally, run it, and start interacting with the testnet. You can request test NAI tokens, create your own tokens, transfer native NAI and other user-created tokens, explore a basic version of the blockchain explorer, and even post something to Nuklai Feed - a simple social media platform. Additionally, the wallet lets you change the Nuklai RPC URL, allowing you to connect to your own Nuklai subnet running locally on your machine. You can watch the demo, and get started today! If you prefer running your own Nuklai subnet locally instead of interacting with the official testnet, you can follow the directions outlined in our documentation. This allows you to do more, such as registering validator nodes for staking, delegating to validators, claiming staking rewards, and more. Welcome to the future where you can move a mountain with your fingers! Written by Kiran Pachhai, Lead Blockchain Architect at Nuklai I remember the day one of my good friends reached out and asked if I had heard about Nuklai . I simply told him, “Not really. That sounds like a topic I would study in my science class.” Fast forward six months, and here I am, building a Layer 1 blockchain network for Nuklai. Who would’ve thought? It is amazing where life takes you in a matter of months. Nuklai Nuklai I will get to the core of this blog about my journey into the world of HyperVMs, but before that, it is essential to know how I even got to this point. The Challenge of High Throughput Soon after I heard about Nuklai, I started to research the project to see what all the hype was about. I was really blown away by Nuklai’s vision to empower every user by allowing them to sell their data to other entities, shifting the power from big businesses to the users themselves. It is a simple yet profound vision because, to achieve it, much had to be done not just at the application level but also at the infrastructure and blockchain protocol levels. When dealing with massive amounts of data daily, the blockchain must handle an immense load that no current platform has achieved yet. People talk about Transactions Per Second (TPS), but few know what it truly takes to achieve such high TPS at the blockchain level. Yes, there are blockchains out there with high throughput, but often, they are very hacky and not true Layer 1s. Usually, the approach is to scale horizontally by creating Layer 2s, Layer 3s, sidechains, and whatnot. These solutions feel like patchwork to me because if you introduce an additional layer to your blockchain, increasing the TPS seems more like an afterthought than something built from the ground up. This is where HyperVMs come into play. HyperVMs, Unlocking High-Performance Blockchains But, what is a HyperVM? It’s essentially a virtual machine (VM) built using the HyperSDK framework . To understand HyperSDK, we first need to understand Avalanche . HyperSDK framework HyperSDK framework Avalanche Avalanche According to their documentation, Avalanche is an open-source platform for building decentralized applications in one interoperable, decentralized, and highly scalable ecosystem. Powered by a uniquely powerful consensus mechanism, Avalanche is the first ecosystem designed to accommodate the scale of global finance, with near-instant transaction finality. Avalanche is an open-source platform for building decentralized applications in one interoperable, decentralized, and highly scalable ecosystem. Powered by a uniquely powerful consensus mechanism, Avalanche is the first ecosystem designed to accommodate the scale of global finance, with near-instant transaction finality. The Avalanche consensus mechanism is ridiculously fast, with less than 2 seconds of finality, meaning your transaction is processed and verified almost instantly. Avalanche also allows you to create your own Layer 1 blockchain (or subnet), and the best part is you are not confined to an Ethereum Virtual Machine (EVM) powered subnet. Despite its large developer community, the EVM is not lightweight and comes with a lot of baggage. On Avalanche, you can also launch your own subnet by developing your own VM in any language as long as it conforms to Avalanche’s Proto interfaces . This is where HyperSDK comes into play. Proto interfaces Proto interfaces Theoretically, you could build your own VM in any language you want, as Avalanche provides that freedom. However, it is also true that it is rather difficult and time-intensive to do from scratch. Even if you use Subnet EVM to get started, it is complex to keep it up-to-date as the core code changes frequently. You need to keep up with maintaining it, which can become resource-intensive. HyperSDK addresses this issue by making it faster, safer, and easier to launch your own optimized blockchain on an Avalanche subnet. Subnet EVM Subnet EVM It hides much of the complexity, allowing you to focus on making your project unique rather than worrying about transaction serialization efficiency or increasing transaction throughput. With HyperSDK, you can build your own blockchain runtime with 500-1000 lines of code and still process thousands of transactions per second without needing a large team of engineers. HelixVM: The 100,000 tx/s Powerhouse? At Nuklai, we built our own blockchain runtime, called ‘HelixVM,’ using the HyperSDK framework with around 200 lines of code in under a week. We added exciting features such as natively issuing tokens, bridging tokens from one subnet to another using Avalanche Warp Messaging (AWM), and developing a staking engine that lets validators register for staking and users delegate their NAI tokens to a validator of their choice to start claiming rewards. With some more additions and custom touches, we added everything with around 500 more lines of code in a couple of months. The journey to get here was extraordinary but equally rewarding. The best part about building our runtime using HyperSDK is that we benefit from the optimizations that come to the HyperSDK framework, worked on by some of the best engineers from Ava Labs and the wider open-source HyperSDK community. For example, with the development of HyperSDK Vryx , which recently produced exceptional results with HyperVMs processing over 5 billion transactions at 100,000 transactions per second, once our HelixVM supports Vryx, it will also process 100,000 transactions per second. This is the true hidden power of using HyperSDK to build your own blockchain runtime Achieving this level of optimization without having to do it ourselves makes it a no-brainer for any team to build their own runtime as well. At Nuklai, we want to build a platform that lets users and businesses monetize their data as easily as building a website, and HyperSDK is the ultimate base layer to achieve that without worrying about how the consensus engine works. HyperSDK Vryx HyperSDK Vryx We want to build a unique platform that suits our needs, and HyperSDK makes it possible with just a few hundred lines of code. Build the Future of Smart Data With Nuklai Testnet Recently, we released our Nuklai testnet . It only took a few months to get here, and we have many exciting features planned for our HelixVM before the mainnet release, coinciding with HyperSDK’s own roadmap of being production-ready. If you want to get started with our testnet, check out the Nuklai Wallet repository, clone it locally, run it, and start interacting with the testnet. Nuklai testnet Nuklai testnet HyperSDK’s own roadmap HyperSDK’s own roadmap Nuklai Wallet Nuklai Wallet You can request test NAI tokens, create your own tokens, transfer native NAI and other user-created tokens, explore a basic version of the blockchain explorer, and even post something to Nuklai Feed - a simple social media platform. Additionally, the wallet lets you change the Nuklai RPC URL, allowing you to connect to your own Nuklai subnet running locally on your machine. You can watch the demo, and get started today! demo , demo If you prefer running your own Nuklai subnet locally instead of interacting with the official testnet, you can follow the directions outlined in our documentation . This allows you to do more, such as registering validator nodes for staking, delegating to validators, claiming staking rewards, and more. documentation documentation Welcome to the future where you can move a mountain with your fingers! Written by Kiran Pachhai, Lead Blockchain Architect at Nuklai

Nuklai Testnet Live: Dive Into HyperVMs, Build on a Scalable Blockchain, and Get Rewarded

নুক্লাই টেস্টনেট লাইভ: হাইপারভিএম-এ ডুব দিন, একটি স্কেলেবল ব্লকচেইন তৈরি করুন এবং পুরস্কৃত করুন

Nuklai Testnet Live: Tauchen Sie ein in HyperVMs, bauen Sie auf einer skalierbaren Blockchain und werden Sie belohnt

Nuklai Testnet Live: sumérgete en HyperVM, construye una cadena de bloques escalable y obtén recompensas

Nuklai Testnet Live : plongez dans les HyperVM, construisez sur une blockchain évolutive et soyez récompensé

नुक्लाई टेस्टनेट लाइव: हाइपरवीएम में गोता लगाएँ, स्केलेबल ब्लॉकचेन बनाएँ, और पुरस्कृत हों

Nuklai テストネット ライブ: HyperVM に飛び込み、スケーラブルなブロックチェーンを構築して報酬を獲得

Nuklai Testnet Live: HyperVM에 뛰어들어 확장 가능한 블록체인을 구축하고 보상을 받으세요

Nuklai Testnet Live: mergulhe nos HyperVMs, desenvolva um blockchain escalável e seja recompensado

Nuklai Testnet Live: погрузитесь в HyperVM, создайте масштабируемый блокчейн и получите вознаграждение

Nuklai Testnet Live: HyperVM'lere Dalın, Ölçeklenebilir Bir Blockchain Üzerine Geliştirin ve Ödül Alın

Nuklai Testnet Live: Đi sâu vào HyperVM, xây dựng trên Blockchain có thể mở rộng và nhận phần thưởng

Nuklai 测试网直播：深入探索 HyperVM，在可扩展的区块链上构建并获得奖励

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198 Stories To Learn About Technology

Introduction How many times have you heard the word "AI" in 2023? There is a probability that you must have heard it too many times, especially with the popularity of ChatGPT. AI, which is an acronym for Artificial Intelligence, is a fast-growing phenomenon in today's world. According to statistics, . From education and health to entertainment and business, AI is reshaping our environment and our way of life. the global AI market is valued at over $136 billion and is projected to increase by over 13x over the next seven years At the same time, it is opening up new possibilities and posing new risks to the continued growth, welfare, and survival of mankind. In the modern world, AI is a rapidly expanding phenomenon. Statistics show that the global AI market is already worth over and is expected to grow by more than 13 times over the following seven years. $136 billion AI’s Basic Working Principle… Artificial intelligence is basically the capacity of a digital computer or computer-controlled robot to carry out actions frequently performed by intelligent individuals. Systems and tools that are built with AI can recognize, combine, and deduce information from a variety of data sources, including audio, photos, videos, text, and more, and they can also learn from this information. They can learn from prior experiences, generalize, use reasoning, find meaning, and adapt to new circumstances, which helps them become more intelligent. AI Tools Across 11 Different Sectors in the Modern World Most industries throughout the world—if not all—use AI tools and technology in some capacity. Although it mostly has some beneficial effects, there is concern that given how quickly AI is expanding and improving, and it may have the ability to eliminate many occupations. How accurate is that? But first, let's examine some of the well-known industries that have begun making major use of AI to make this determination. 1. Finance There are powerful AI tools that are used by a variety of financial organizations and even individuals in the areas of financial planning and analysis, assessing credit risk, fraud detection, trading, and investments, optimizing insurance claims processing, sales, and customer services, and digitizing historical files and documents, amongst other applications in the field of finance. Some of the tools include: A virtual assistant tool in the Bank of America mobile app that assists users with a variety of banking operations like checking balances, paying bills, and sending money, as well as balance reconciliation. Capital One also has a similar virtual assistant called  Eno, which notifies users of suspected fraud, price increases, or payment reminders. Erica: Enova uses AI technology to aid users have access to credit facilities and helps financial institutions to solve the challenges surrounding borrowers’ assessment through the provision of sound financial analytics. : Enova An AI-powered platform using data points to provide financial institutions with the data to conduct assessments on borrowers with little or no credit information : Zest : A technology that makes use of artificial intelligence to accurately process financial records like pay stubs, tax returns, and other related ones at a faster speed. Ocrolus provides a predictive model that helps financial institutions solve issues surrounding marketing, wealth management, fraudulent credit card transactions, underwriting, and business growth. : DataRobot an identity verification system that uses ML and AI to analyze and verify applicants’ data to ensure that the KYC details are accurate. : Socure 2. Blockchain Several techniques, including strengthening data security and privacy, improving data quality and trust, optimizing data processing and storage, creating data insights and value, integrating data across platforms and domains, etc., are employed by AI to reinvent and optimize the blockchain sector. Some instances include: - using AI and formal verification to authenticate the security of a blockchain, smart contracts, and web3 dApps. CertiK - which certifies and verifies valuable pieces of art and NFTs on the blockchain using AI. Verisart - which leverages AI to allow quicker transactions, more scalability, and less energy use. Matrix AI - employing artificial intelligence to examine cryptocurrency market movements and offer market insights for individual investors. Token Metrics - which employs AI to build a decentralized network of AI services that can communicate with one another and trade value on the blockchain. SingularityNET 3. Transport AI is revolutionizing transportation and supplying driving assistance. Some of the tools include: This company uses AI to power its autonomous vehicles and taxis for urban transportation. : Waymo Rapid Flow Technologies uses traffic management to deliver adaptive traffic signal control systems that lower congestion and pollution. This is done by analyzing traffic patterns, predicting traffic flow, and optimizing traffic lights using data and algorithms. : Rapid Flow Technologies Using AI, Uber apps are designed to find compatible drivers and passengers, calculate prices and arrival times, and offer safety features. These enhance passenger transportation services by personalizing travel options, streamlining pricing and scheduling, and enhancing customer satisfaction. : Uber Clear uses AI to build biometric identification verification services that let users use their faces or eyes as boarding credentials in airports.  This expedites airport security and boarding procedures in the aviation industry. : Clear With AI, Volocopter has been able to build its drone Taxis which will safely traverse the airspace, avoid obstructions, and land at designated places within a busy urban city. It offers a faster transportation system through congested streets by flying in the lower airspace with zero-emission. : Volocopter 4. Data Analysis One of the key industries using AI and machine learning is data analysis, which does so in a variety of ways, such as by analyzing unstructured data, producing data insights, streamlining data processing, integrating data across platforms and domains, and others. A few of the numerous AI tools that are used in data analysis include: A software program that forecasts data performance using artificial intelligence and suggests subjects based on prediction scores. : Tableau An AI tool designed by Microsoft for Data Analytics, Data Visualization, and Business Intelligence : Power BI A platform to analyze user data and offer insights and recommendations : Research AI An open-source tool to build customized data pipelines, workflow, and solutions for a range of data analysis task : KNIME An AI tool for analyzing and indexing a huge volume of data in real-time : Splunk 5. Software Engineering The coding and design industry is being reinvented and optimized by AI in several ways. Currently, programmers can generate, edit, optimize, check, and transform codes with the use of artificial intelligence (AI). Some of the AI tools available at their disposal include: A tool called , which can create code in common development environments, is , which is based on the GPT-3 standard. GitHub Copilot powered by the OpenAI Codex model A program called ** **utilizes artificial intelligence to examine code and identify flaws that would prevent it from running. Embold This tool is an app that provides programmers with comprehensive facilities to build, edit, and test codes and applications. Examples of popular IDEs include VS code, Eclipse, IntelliJ IDEA, PyCharm, Xcode, Android studio, NetBeans, Atom, Sublime Text, and Vim. The integrated development environment (IDE): An auto-completion tool that can be integrated into IDEs to improve productivity. This tool employs deep learning algorithms to predict the rest of the code a programmer is typing. : Deep TabNine : This AI-powered coding assistant using natural language, can generate codes, complete the function of the codes, and generate the summary of a function. CodeT5 Other AI tools that aid programmers include Google Bard, ChatGPT, AskCodi, Mutable, IBM Watson Code Assistant, Code-LMS, WPCode, and Amazon CrowdWhisperer. 6. Entertainment Although technically speaking, humans make up the majority of the characters, artists, and actors in the entertainment industry, artificial intelligence (AI) has begun to play crucial roles in the sector and is used in significant areas like generating, analyzing, optimizing, moderating, and personalizing realistic content for their audiences by using data and algorithms. Some platforms for entertainment that use AI are: aids artists in writing the lyrics of a song. It can write songs in over 100 languages. Lyrical Labs offers video analytics and insights across a variety of platforms, including YouTube, Facebook, Instagram, and TikTok. Tubular Labs is an AI-powered platform using machine learning algorithms to match licensed music with visual content. SyncFloor This is an AI video creation tool that can convert text data to video content. Lumen5: Other global organizations that inculcated AI into their products are Netflix__,__ which uses AI to adapt its streaming quality and bandwidth use to the customers' devices and networks; YouTube, which employs AI to search and eliminate content that breaks its community standards; and Spotify which utilizes AI for curating customized podcasts and playlists for its subscribers depending on their listening patterns. 7. Manufacturing This industry makes use of AI in several areas, including boosting predictive maintenance, streamlining manufacturing procedures, automating production duties, fostering production innovation, and more. The following are some instances of production platforms using AI in their operations: offers AI-based visual inspection solutions for a range of industries, including textiles, electronics, and the automobile. Landing AI for a variety of industries, including energy, mining, and transportation. Uptake leverages AI to offer predictive maintenance solutions. Uptake __c__an give solutions for the optimization of processes in a variety of industries, including the chemical, steel, and cement industries, by utilizing AI. __ m __ Petuu offers robotic picking solutions for a range of industries, including e-commerce, shipping, and the food industry. Covariant For generative design solutions across a range of industries, including architecture, engineering, and construction, leverages artificial intelligence (AI). Autodesk 8. Gaming AI may be used to create intelligent, human-like NPCs that communicate with players, forecast player behavior to improve game design and testing, provide lifelike images and audio, improve gameplay, and increase immersion, among other things. By using data and algorithms, it is also utilized to create, analyze, optimize, moderate, and personalize realistic material for their games. Several instances include: AI is used by to deliver statistics and insights for games across a range of platforms, including PC, mobile, and console. Unity AI is used by to recommend the best times to release mobile games as well as their prices and marketing techniques. Google Play In multiplayer games, employs AI to detect cheaters and block them. Steam 9. Healthcare AI activities in the healthcare industry are increasing by the day. Using systems like Natural Language Processing, Machine Learning, and deep learning algorithms, its impact is greatly felt, especially in domains such as; illness detection and patient care improvement, forecasting and epidemic prevention, medication discovery and development, personalizing and optimizing therapies, and much more. Some notable instances of AI in healthcare  include: The use of AI by to help oncologists diagnose and treat cancer. IBM Watson Health AI-powered tool to track and predict infectious disease outbreaks globally. BlueDot tool used to organize searches across billions of chemicals for possible drugs to speed up drug development. Atomwise Provision of individualized treatment plans by to provide patients with chronic diseases. Wellframe The Future In the years and decades to come, AI will become the centrepiece of innovation in the world, ushering in growth and influencing the world in ways that pave the way for enormous possibilities as well as threats to humanity's progress, prosperity, and the very existence. Possible outcomes may include: More individuals and businesses making use of AI's capabilities and applications as it becomes more widely available and democratized. It is expected that its interaction and synergy with other technologies like cloud computing, 5G, IoT, blockchain, and quantum computing will birth new realities. Advancement to the point where it can generate its content, goods, and services without human intervention. This advancement may accelerate to the level where it will be able to learn from its own experiences and those of other AIs, leading to novel kinds of intelligence and cooperation. A greater influence, transformation, and disruption across many fields and businesses. In conclusion, the development of AI has an inevitable future. It all comes down to how researchers plan, build, implement, and regulate AI systems. How well we adjust to the new opportunities and threats that AI presents will tell how deeply AI will twist our realities. To create the kind of future we want for artificial intelligence, we must be proactive, collaborative, and inclusive.

AI Tools That Are Reshaping The Modern World Industries

In this article, we examine the potential disruption of the radio host/live-stream industry through the use of artificial intelligence technology. By analyzing the average radio host salary, the number of spots per hour, the total words spoken per hour, and other factors such as music licensing fees, we demonstrate that it is possible to create a fully automated radio station using AI technology at a fraction of the cost of hiring human talent. We showcase a live demonstration of one such solution currently active under Avalon Star Streams brand, where after running songs from a creative commons music stream, the AI generates new radio content during breaks between those songs, even allowing the random selection of new songs if desired. Finally, we provide details on the tech stack utilized including NodeJS docker image which allows us to control ffmpeg streams and manage playlists efficiently. Running Example At the time of this writing, you can find the example live-streaming at and . Twitch.TV YouTube If for any reason the demo is not live streaming feel free to checkout this YouTube video for an example. https://youtu.be/Jnb4bMJc7x8?embedable=true the YouTube video show cases 2 auto-generated scripts with the AI Voice Actor Antoni Starr. The first is a call for donations, and the second is a random ad play with announcing the next song. NOTE: Cost analysis The key driver behind the potential disruption of the radio host industry lies in the significant reduction in labor costs. Utilizing current pricing models, the yearly cost of AI voice services required to run a full radio station amounts only to approximately $4100 compared to a national average salary of radio hosts estimated around $42k [0]. With an average radio spot duration of 16 minutes and an average speaking rate of 140 words per minute [1][2], each radio spot consists of approximately 2,240 words. AI-powered content generation, such as ChatGPT, comes at a cost of around $0.002 per 750 words. Thus, the total cost of using GPT for one hour of content amounts to approximately $0.006. With radio hosts spending around 45.5 hours per month on air [1], the yearly cost of GPT usage is estimated to be approximately $55. Furthermore, integrating Eleven Labs’ AI voice technology, priced at $330 per month for 40 hours of usage [3], incurs an annual cost of around $4,000. Considering the combined expenses of GPT and Eleven Labs, the total cost of implementing AI for a radio host is approximately $4,100 per year. This represents a significant cost reduction compared to traditional production methods and opens up new possibilities for radio/live-stream hosts with limited budgets. Further considerations While some might argue that AI generated content lacks emotional depth and personal touch provided by human talent, recent advancements in natural language processing have shown otherwise. With deep learning algorithms, AI systems can now analyze vast troves of linguistic data and learn nuances in context, tone and cadence of speech. When trained properly, these systems are able to mimic human-like qualities while still maintaining accuracy and efficiency. In fact, many industries ranging from customer service to journalism have already seen initial success with implementing chat-bots and machine-generated content due to economic advantages, even in sectors thought immune to technological takeover. Ultimately, it seems reasonable to assume a similar future for broadcasting markets like radio hosting. Examples Under our Avalon Star Stream brand, we set up a proof of concept showcasing the efficiency of AI assisted broadcasting. Leveraging open-source tools like ffmpeg and integrated within our custom NodeJS application framework managed through Docker, we were able to achieve a functioning automated live-stream setup complete with real-time generation capabilities for its intermission radio jockey. The system, under default settings, will play 3 songs before attempting a song-break. During the song-break our model analyzes prompts received online during the previous three musical sets and produces its own original written material targeting the donators thanking them, before reading an ad for an imaginary product and continuing. Our model is told take the persona of a Radio Host living within the by the name of “Antoni Starr”. Fallout 4 Universe Due to budget constraints, Antoni employs a cost-saving strategy. While generating content, there is a 10% chance, limited to once per hour, that his system dynamically pulls and generates a new song-break. This method adds an element of surprise and uniqueness to the show while optimizing production costs for the purpose of this tech demo. All other ad-reads will come from a previously generated grab-bag created during testing. Additionally, due to the channel being so new, we are unable to turn on the subscribers/memberships to be used during announcements. Tech Stack While I have not decided to release my code for this yet, I have decided to talk about the tech stack. As seen from the above image, the tool leveraging various technologies (FFmpeg, WebDAV, ChatGPT, EleventLabs, MongoDB) and the application combines them into a platform for live-stream generation. WebDAV + MongoDB This piece of the tech-stack is here to help record generated content and act as a file-store. The WebxDAV aspect allows us to remotely store the music files and download them at instantiation for the stream. ChatGPT + Eleven Labs These are the workhorses of the generative content. When time to generate a new ad-break we leverage ChatGPT API with our custom prompt to get the next script. Our prompt will be pre-seeded with name/information from stream donators and a random fake product to ad-read. FFmpeg The workhorse of streaming. FFmpeg is responsible for all audio/visual you see on the stream. from the static image overlay, to the encoded video playing on the TV and the audio you hear. FFmpeg is the magic behind it all. HTML/CSS/JavaScript Not seen in the diagram above, there is a management interface to tweak params of the running stream. This allows for the admin to force ad-breaks, tweak ad-break rate algorithm and more. Additionally, as mentioned previously, the entire platform is running off of NodeJS Conclusion We examined the possibility of replacing radio hosts with artificial intelligence and concluded that, given certain conditions, it may indeed be possible to do so. Our findings suggest that AI-powered radio stations would have clear financial advantages over their human counterparts and be capable of producing high-quality content equal to or surpassing that of human DJs. Further consideration should be done to ensure that listeners remain engaged and attuned to the program’s offerings amidst such developments. Overall, while the idea of a completely automated radio station or live-stream, with a dynamic voiced personality, may initially seem farfetched, the reality is that emerging technologies are quickly making the notion feasible and practical. Thus, business leaders must recognize the changing landscape and adapt accordingly before they risk being left behind in an ever evolving marketplace. Live-stream Links and Twitch.TV Youtube If you want to see more of tool itself please don’t hesitate to reach out.

The Radio Host and Live-Stream Industry: Poised for GPT Disruption

রেডিও হোস্ট এবং লাইভ-স্ট্রিম শিল্প: GPT ব্যাঘাতের জন্য প্রস্তুত

Die Radiomoderator- und Live-Stream-Branche: Bereit für GPT-Störungen

La industria de los presentadores de radio y la transmisión en vivo: preparados para la interrupción de GPT

L'industrie de l'hôte radio et de la diffusion en direct : prête pour la perturbation des GPT

रेडियो होस्ट और लाइव-स्ट्रीम उद्योग: GPT व्यवधान के लिए तैयार

ラジオホストとライブストリーム業界: GPT 破壊の準備が整っている

라디오 진행자와 라이브 스트리밍 산업: GPT 혼란에 대비

O apresentador de rádio e a indústria de transmissão ao vivo: preparados para a interrupção do GPT

Radyo Sunucusu ve Canlı Yayın Sektörü: GPT Kesintisine Hazır

Ngành công nghiệp máy chủ radio và phát trực tiếp: Đã sẵn sàng cho sự gián đoạn của GPT

电台主持人和直播行业：为 GPT 颠覆做好准备

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