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Welcome! Happy to see you in the seventh part of my Vuejs Amsterdam Conference 2022 summary series, in which I share a summary of all the talks with you. You can read my JSWorld Conference 2022 Summary series (in four parts) , where I summarized all the first day’s talks. You can also find the previous Talks of the Vue Amsterdam conference 2022 in my blog. here (Recurring) Introduction After two and a half years, JSWorld and Vue Amsterdam Conference were back in Theater Amsterdam between 1 and 3 June, and I had the chance to attend this conference for the first time. I learned many things, met many wonderful people, spoke with great developers, and had a great time. On the first day the JSWorld Conference was held, and on the second and third days, the Vue Amsterdam. The conference was full of information with great speakers, each of whom taught me something valuable. They all wanted to share their knowledge and information with other developers. So I thought it would be great if I could continue to share it and help others use it. At first, I tried to share a few notes or slides, but I felt it was not good enough, at least not as good as what the speaker shared with me. So I decided to re-watch each speech, dive deeper into them, search, take notes and combine them with their slides and even their exact words in their speech and then share it with you so that what I share with you is at least at the same level as what I learned from them. A Very Important Point and I have only tried to learn them so that I can turn them into these articles. Even This means if you learn something new, it is because of their efforts. Everything you read during these few articles is the result of the effort and time of the speaker itself, many of the sentences written in these articles are exactly what they said or what they wrote in Slides. Last but not least, I may not dig into every technical detail or live codings in some of the speeches. But if you are interested and need more information, let me know and I’ll try to write a more detailed article separately. Also, don’t forget to check out their Twitter/Linkedin. you can find the program of the conference. Here Animating with Vue - Frontend Developer at SAP Ramona Biscoveanu Sometimes our applications need a little bit of "wow" and we can do this with some "movement" just the perfect amount to make them more alive. We will be looking at how to use the Vue magic to create awesome animations, from simple ones to more complex ones, combining Vue with animation libraries. 90s Websites On 90s websites, there were sometimes a lot of motions and colors. But the only way we could have animations back then was with gifs. Just imagine the bandwidth those gifs consumed in the era of Dial-Up internet! So we end up with some tiny low-frame gifs to limit the bandwidth consumption, and this was the result: Why Animate? One of the reasons we use animations these days, even back then, is to capture users' attention and focus. Think of how many distractions we have, notifications on our phones, pop-ups on the websites, or the jumping icons on the dock on macOS. We can also trick users into thinking that our website is a lot faster. We give them this perception that our APIs are faster by putting loaders and progress bars. Studies are saying if you have a custom loader you have a chance of keeping the people on our website longer. Sometimes we try to inform our users efficiently. Maybe we have lots of things going on on our website and we want to tell the user what is the next step in the flow of the application with an animated button. Other times we need interactive content for marketing materials to keep users there. Animations are also powerful when you try to tell a story. Vue <Transition /> In Vanilla JavaScript or jQuery, you need to manually calculate the timings and delays, and decide when to add or remove classes. But in Vue, we wrap the target element into the component and it does many of those hard things automatically. Here is a simple fade animation: <Transition /> <transition name="fade">
  <p v-if="show">hello</p>
</transition> .fade-enter-active, .fade-leave-active {
  transition: opacity .5s;
}
.fade-enter-from, .fade-leave-to 
  opacity: 0;
} This is how Vue handles that: Vue <TransitionGroup /> is a built-in component designed for animating the insertion, removal, and order change of elements or components that are rendered in a list. <TransitionGroup> This is a simple example of some tiles sliding on the screen: <transition-group tag="div" class="tile-section" name="list" appear>
  <TileComp
    v-for="(tile, i) in tiles"
    :key="i + 'tile'"
    :header="tile.title"
    :content="tile.content"
    :footer="tile.footer"
  ></TileComp>
</transition-group> .list-enter-active,
.list-leave-active {
  transition: all 1s ease;
}
.list-enter-from,
.list-leave-to {
  opacity: 0;
  transform: translateY(70px);
} JavaScript Hooks CSS is awesome and we can do a lot with it, but sometimes it’s not enough. Vue provides some hooks on the component. <Transition /> <Transition
  @before-enter="onBeforeEnter"
  @enter="onEnter"
  @after-enter="onAfterEnter"
  @enter-cancelled="onEnterCancelled"
  @before-leave="onBeforeLeave"
  @leave="onLeave"
  @after-leave="onAfterLeave"
  @leave-cancelled="onLeaveCancelled"
>
  
</Transition> GreenSock GSAP The GreenSock Animation Platform ( for short) is a powerful JavaScript library that enables front-end developers and designers to create robust timeline-based animations. GSAP One of the most important things you will hear a lot in GSAP is Tween. A Tween is what does all the animation work — think of it like a high-performance property setter. You feed in targets (the objects you want to animate), a duration, and any properties you want to animate and when its playhead moves to a new position, it figures out what the property values should be at that point and applies them accordingly. Common methods for creating a Tween (all of these methods return a Tween instance): gsap.to() gsap.from() gsap.fromTo() For simple animations (no fancy sequencing), the methods above are all you need! gsap.to(".selector", {toVars});
gsap.from(".selector", {fromVars});
gsap.fromTo(".selector", {fromVars}, {toVars});
// special properties (duration, ease, etc.) go in toVar Now let’s add GSAP to our tiles example: <div class="tile-section">
  <TileComp
    v-for="(tile, i) in tiles"
    :key="i + 'tile'"
    :header="tile.title"
    :content="tile.content"
    :footer="tile.footer"
  ></TileComp>
</div> import gsap from "gsap";
...
mounted() {
  gsap.from(".tile", {
    duration: 0.5,
    opacity: 0,
    scale: 0,
    y: 200,
    ease: "power2",
    stagger: 0.1,
  });
}, Vue Animation Counter Another simple example of using GSAP to make nice animations can be a celebrate counter animation. Here you can see what it will look like: All we have in the template is just an h1 element where we pass the formatted value and a reset button. <div>
  <h1 ref="celebrate" class="counter" :class="{ celebrate: isCelebrate }">
    {{ this.numberWithCommas(value) }}
  </h1>
  <button class="restart" @click="restart">Restart</button>
</div> We need to use function of GSAP. Think of it as a tool to sequence your animations. timeline import gsap from "gsap";
import confetti from "canvas-confetti";
const tl = gsap.timeline();
const start = 100000;
const end = 3240074;

export default {
  props: {
    msg: String,
  },
  data() {
    return {
      isCelebrate: false,
      value: start,
    };
  },
  mounted() {
    tl.fromTo(
      ".counter",
      {
        innerText: start,
        scale: 0.8,
      },
      {
        innerText: end,
        snap: { innerText: 1 },
        duration: 4,
        ease: "linear",
        onUpdate: () => {
          this.$refs.celebrate.innerText = this.numberWithCommas(
            this.$refs.celebrate.innerText
          );
        },
        onComplete: () => {
          this.celebrate();
        },
      }
    );
  },
  methods: {
    celebrate() {
      this.isCelebrate = true;
      confetti({
        particleCount: 150,
        spread: 100,
        origin: { y: 0.6 },
        colors: ["#647eff", "#42d392"],
        disableForReducedMotion: true,
      });
    },
    numberWithCommas(x) {
      return x.toString().replace(/\B(?=(\d{3})+(?!\d))/g, ",");
    },
    restart() {
      tl.restart();
      this.isCelebrate = false;
    },
  },
}; Page Transition In Vue Router 4 the syntax for transitioning pages has changed a bit. We don’t wrap the router into the transition component anymore. instead, we use the : v-slot <router-view v-slot="{ Component }">
  <transition name="fade">
    <component :is="Component" />
  </transition>
</router-view> Here is an example of a page transition: For building this page transition, we need the enter hook: <router-view v-slot="{ Component }">
  <transition
    :key="$route.path"
    @enter="onEnter"
    :css="false"
  >
    <component :is="Component" />
  </transition>
</router-view> Then we need to register the plugin from GSAP: SplitText import gsap from "gsap";
import SplitText from "gsap/SplitText";

gsap.registerPlugin(SplitText);

gsap.defaults({
  duration: 1,
  ease: "power3.inOut",
}); And then using the plugin we split the text to be able to animate it: mySplitText(el) {
  return new SplitText(el, { type: "words,chars,lines" });
}, Let’s take a look at hook: onEnter onEnter(el, done) {
  const masterTL = gsap.timeline({
    onComplete: () => {
      done;
    },
  });

  masterTL.add(
    this.enterContentTextAnimation(
      mySplitText(".content-text-header").chars
    )
  );
  masterTL.add(
    this.enterContentTextAnimation(".content-text-body"),
    "-=0.9" //overlap with previous by 0.9s
  );
  masterTL.add(this.imgScaleOut(".content img"), "<");
	//The start of previous animation
}, And here you can see how you can nest GSAP timelines and what and functions do: enterContentTextAnimation imgScaleOut enterContentTextAnimation(id) {
  const tl = gsap.timeline();

  tl.fromTo(
    id,
    {
      yPercent: "100",
      opacity: 0,
    },
    {
      yPercent: "0",
      opacity: 1,
      stagger: 0.03,
    }
  );
},

imgScaleOut(id) {
  const tl = gsap.timeline();

  tl.from(id, {
    scale: 1.5,
  });

  return tl;
}, SVG Animated charts can be a good example of SVG animation: Here is the part of the code that makes this chart animation possible: watch: {
  data(newValue, oldValue) {
    newValue.map((data, index) => {
      var id = "#arc" + index;
      var d = this.calculateArc(data, index);
      var oldValueD = this.calculateArc(oldValue[index]);
      const tl = gsap.timeline();

      tl.fromTo(
        id,
        {
          attr: { d: oldValueD },
        },
        {
          duration: 0.5,
          attr: { d: d },
          yoyo: true,
        }
      );
    });
  },
}, It’s important to not abuse animations on your website. Sometimes they are useful, but sometimes they can kill your audience. End of The Seventh Talk I hope you enjoyed this part and it can be as valuable to you as it was to me. Over the next few days, I’ll share the rest of the talks with you. Stay tuned…

Vue Amsterdam 2022: Part VII - Animating with Vue

Vue Amsterdam 2022: Parte VII - Animación con Vue

Vue Amsterdam 2022 : Partie VII - Animer avec Vue

Vue एम्स्टर्डम 2022: भाग VII - Vue . के साथ एनिमेट करना

Vue アムステルダム 2022: パート VII - Vue によるアニメーション化

Vue Amsterdam 2022: Parte VII - Animando com Vue

Vue Amsterdam 2022: Phần VII - Hoạt hình với Vue

Vue Amsterdam 2022：第七部分 - 使用 Vue 制作动画

Combination of Abstractive & Extractive methods for Text Summarization (Tutorial 7)

GRAND CAYMAN, Cayman Islands, May 3rd, 2024/Chainwire/--Protocol launches, growth trajectory, and industry-leading technology point toward more success to come. On the first anniversary of Sui’s Mainnet launch, the Sui community is celebrating a landmark year that saw it rise from a nascent ecosystem to the top tier of Layer 1 blockchains, amassing household name partners and shipping multiple technology breakthroughs in the process. In the build-up to its launch in 2023, the chatter around Sui reached a level of excitement that has not been matched by any chain that has launched since. The first anniversary of Sui represents a culmination of the remarkable milestones achieved by the network in its first year. While centralized institutions face growing public distrust due to decades of anti-competitive and anti-consumer behavior and legacy blockchains lack the speed and technology to solve the problem, in a single year, Sui has emerged as the decentralized solution most capable of disrupting the status quo at scale. The innovations of Sui begin with Sui’s novel programming language, Move, which was created by Mysten Labs Co-founder and CTO Sam Blackshear. Move introduced a new architecture centered around objects, enabling performance and functionality that was simply not available on existing blockchains. The result is a blockchain that is singular in the industry — the universal coordination layer for intelligent assets. “Like many transformative innovations before us, we knew the problem we had to solve and built the technology to solve it without applying labels, but a year after launch, it is clear that Sui is a vibrant developer ecosystem,” said Evan Cheng, Co-founder and CEO of Mysten Labs. “Developers are taking advantage of Sui’s performance, and its scalable, composable, on-chain storage, and native accessibility features to build sustainable business models with a consumer ownership-first approach. While the Network’s achievements to date are remarkable, the road to onboarding the next billion users to web3 has just started.” Technology Innovations The results Sui has achieved have validated the team’s approach. In addition to not experiencing a single minute of downtime or instance of degraded performance since Mainnet launch, in the last 12 months, Sui has achieved: Lightning-fast transaction speeds — time to finality clocked at just 400 milliseconds
Massive scale — 297,000 peak TPS in a controlled environment
Record-setting Mainnet performance — 65.8M transactions executed in a single day, the most of any blockchain ever
Extremely low fees — predictable, stable transaction fees even during high usage Yet technology improvements are a constant at Sui. In recent weeks, including at its first global in-person conference, Sui Basecamp, Sui unveiled Mysticeti, which significantly shortens Sui’s end-to-end time to finality, and Pilotfish, which enables nearly unlimited horizontal scaling by enabling individual validators to use multiple machines to extend their capacity. Sui has also introduced unique implementations of technologies that make adoption easier and make the blockchain accessible to mainstream users, both at the enterprise and retail levels. zkLogin is on-chain authorization with traditional OAuth providers like Google and Twitter, allowing all users to directly operate on-chain with the single sign-on process they have become accustomed to, removing the hurdle of managing wallet addresses and seed phrases. zkSend is an application exclusive to Sui that utilizes zkLogin to enable users to send and claim tokens simply by sharing or clicking a link. Sponsored transactions, enabled by Sui’s extremely low fees, empower builders to remove a final hurdle for engagement. Finally, Enoki, which was announced at Sui Basecamp, removes requirements for enterprises looking to incorporate blockchain technology with a turnkey solution that gives them access to build seamlessly on Sui. “The rate at which the ecosystem’s deep and talented developer community has shipped powerful protocols and industry-first technology breakthroughs has been breathtaking, and it’s only a year in,” said Adeniyi Abiodun, Co-founder and CPO at Mysten Labs. “Sui’s purpose is to redefine how individuals and businesses collaborate to create, grow, and share value in a digital-first economy and since its mainnet launch, Sui has demonstrated important and unique capabilities in that regard.” Network Momentum – Sui is a destination for DeFi, Gaming and Commerce Also owing to the strength of the network and especially notable for an ecosystem so early in its development, Sui has quickly become one of the preeminent destinations for DeFi activity. Within 9 months of its Mainnet launch, Sui ranked in the Top 10 of all blockchains in TVL. A month later, Sui’s DEX volume also achieved top 10 status. Throughout, Wormhole stats show Sui as a top destination for bridging from Ethereum, including over a 30-day period where Sui saw more inflows than all other blockchains combined, and more than twice as much as the next closest blockchain. In each of these cases, Sui eclipsed numerous well-known networks that have existed for far longer. Builders and enterprises integrating with Sui are also adding to the growing momentum. Bluefin, a derivatives exchange that had already executed billions in transaction volume in its first iteration on another chain, shut that integration down to build on Sui. Solend, a leading lending protocol on Solana, chose Sui for its first integration beyond its initial network, launching the Suilend protocol which has already amassed over $30M TVL. Additionally, First Digital Labs, creator of FDUSD, the fastest-growing stablecoin in crypto with over $4B in market cap, chose Sui for its first expansion since its launch on Ethereum and BNB. “As we mark the first anniversary of Sui's launch, the growth and innovation within the Sui ecosystem have been sensational and Sui has quickly ascended to the forefront of Layer 1 blockchains,” said Greg Siourounis, Managing Director of the Sui Foundation. “Sui’s global footprint has continued to expand at a remarkable rate as more and more builders see Sui as the best platform for enabling real world solutions aimed at addressing the world’s most pressing challenges.” Gaming is another focus for Sui that will continue in the coming months and years. With low, predictable fees that allow game developers to build with confidence and dynamic objects that make games built on Sui more expressive, Sui is the optimal blockchain for gaming studios. Dozens of development teams are currently building games on Sui, including established studios such as NHN (Pebble City), ONBUFF x SNK (Samurai Shodown), NDUS Interactive (Xociety), Orange Comet (The Walking Dead: Lands), and Ambrus Studio (E4C: Final Salvation). Leading professional esports team, Team Liquid, will leverage Sui for the relaunch of its fan loyalty program, and at Sui Basecamp in April, Sui joined gaming infrastructure developer Playtron in announcing SuiPlay0X1, the first handheld gaming device with native blockchain capabilities to wide acclaim. Other notable ecosystem partnerships achieved in Sui’s first year include those with Alibaba Cloud and Google Cloud, which focused on enhancing security, scalability, developer tools and user experiences across a range of Web 3.0 and AI-powered applications. BytePlus, the web3 arm of ByteDance, partnered with Sui ecosystem partner Mysten Labs to explore collaboration on data warehousing, AI recommendation algorithms, and AI visual algorithms in web3 game platforms and socialFi projects on Sui. The crowds that gathered for Sui Basecamp 2024 represented the culmination of Sui’s arrival, as over 1,000 projects, partners, investors and enthusiasts from 65 countries around the world came to Paris in April to celebrate Sui at the vaunted Layer 1’s inaugural global conference. Contact Sui Foundation media@sui.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. GRAND CAYMAN, Cayman Islands, May 3rd, 2024/Chainwire/--Protocol launches, growth trajectory, and industry-leading technology point toward more success to come. On the first anniversary of Sui’s Mainnet launch, the Sui community is celebrating a landmark year that saw it rise from a nascent ecosystem to the top tier of Layer 1 blockchains, amassing household name partners and shipping multiple technology breakthroughs in the process. In the build-up to its launch in 2023, the chatter around Sui reached a level of excitement that has not been matched by any chain that has launched since. The first anniversary of Sui represents a culmination of the remarkable milestones achieved by the network in its first year. While centralized institutions face growing public distrust due to decades of anti-competitive and anti-consumer behavior and legacy blockchains lack the speed and technology to solve the problem, in a single year, Sui has emerged as the decentralized solution most capable of disrupting the status quo at scale. The innovations of Sui begin with Sui’s novel programming language, Move, which was created by Mysten Labs Co-founder and CTO Sam Blackshear. Move introduced a new architecture centered around objects, enabling performance and functionality that was simply not available on existing blockchains. The result is a blockchain that is singular in the industry — the universal coordination layer for intelligent assets. “Like many transformative innovations before us, we knew the problem we had to solve and built the technology to solve it without applying labels, but a year after launch, it is clear that Sui is a vibrant developer ecosystem,” said Evan Cheng, Co-founder and CEO of Mysten Labs. “Like many transformative innovations before us, we knew the problem we had to solve and built the technology to solve it without applying labels, but a year after launch, it is clear that Sui is a vibrant developer ecosystem,” said Evan Cheng, Co-founder and CEO of Mysten Labs. “Developers are taking advantage of Sui’s performance, and its scalable, composable, on-chain storage, and native accessibility features to build sustainable business models with a consumer ownership-first approach. While the Network’s achievements to date are remarkable, the road to onboarding the next billion users to web3 has just started.” “Developers are taking advantage of Sui’s performance, and its scalable, composable, on-chain storage, and native accessibility features to build sustainable business models with a consumer ownership-first approach. While the Network’s achievements to date are remarkable, the road to onboarding the next billion users to web3 has just started.” Technology Innovations The results Sui has achieved have validated the team’s approach. In addition to not experiencing a single minute of downtime or instance of degraded performance since Mainnet launch, in the last 12 months, Sui has achieved: Lightning-fast transaction speeds — time to finality clocked at just 400 milliseconds Massive scale — 297,000 peak TPS in a controlled environment Record-setting Mainnet performance — 65.8M transactions executed in a single day, the most of any blockchain ever Extremely low fees — predictable, stable transaction fees even during high usage Lightning-fast transaction speeds — time to finality clocked at just 400 milliseconds Massive scale — 297,000 peak TPS in a controlled environment Record-setting Mainnet performance — 65.8M transactions executed in a single day, the most of any blockchain ever Extremely low fees — predictable, stable transaction fees even during high usage Yet technology improvements are a constant at Sui. In recent weeks, including at its first global in-person conference, Sui Basecamp, Sui unveiled Mysticeti, which significantly shortens Sui’s end-to-end time to finality, and Pilotfish, which enables nearly unlimited horizontal scaling by enabling individual validators to use multiple machines to extend their capacity. Sui has also introduced unique implementations of technologies that make adoption easier and make the blockchain accessible to mainstream users, both at the enterprise and retail levels. zkLogin is on-chain authorization with traditional OAuth providers like Google and Twitter, allowing all users to directly operate on-chain with the single sign-on process they have become accustomed to, removing the hurdle of managing wallet addresses and seed phrases. zkSend is an application exclusive to Sui that utilizes zkLogin to enable users to send and claim tokens simply by sharing or clicking a link. Sponsored transactions, enabled by Sui’s extremely low fees, empower builders to remove a final hurdle for engagement. Finally, Enoki, which was announced at Sui Basecamp, removes requirements for enterprises looking to incorporate blockchain technology with a turnkey solution that gives them access to build seamlessly on Sui. “The rate at which the ecosystem’s deep and talented developer community has shipped powerful protocols and industry-first technology breakthroughs has been breathtaking, and it’s only a year in,” said Adeniyi Abiodun, Co-founder and CPO at Mysten Labs. “Sui’s purpose is to redefine how individuals and businesses collaborate to create, grow, and share value in a digital-first economy and since its mainnet launch, Sui has demonstrated important and unique capabilities in that regard.” Network Momentum – Sui is a destination for DeFi, Gaming and Commerce Also owing to the strength of the network and especially notable for an ecosystem so early in its development, Sui has quickly become one of the preeminent destinations for DeFi activity. Within 9 months of its Mainnet launch, Sui ranked in the Top 10 of all blockchains in TVL. A month later, Sui’s DEX volume also achieved top 10 status. Throughout, Wormhole stats show Sui as a top destination for bridging from Ethereum, including over a 30-day period where Sui saw more inflows than all other blockchains combined, and more than twice as much as the next closest blockchain. In each of these cases, Sui eclipsed numerous well-known networks that have existed for far longer. Builders and enterprises integrating with Sui are also adding to the growing momentum. Bluefin, a derivatives exchange that had already executed billions in transaction volume in its first iteration on another chain, shut that integration down to build on Sui. Solend, a leading lending protocol on Solana, chose Sui for its first integration beyond its initial network, launching the Suilend protocol which has already amassed over $30M TVL. Additionally, First Digital Labs, creator of FDUSD, the fastest-growing stablecoin in crypto with over $4B in market cap, chose Sui for its first expansion since its launch on Ethereum and BNB. “As we mark the first anniversary of Sui's launch, the growth and innovation within the Sui ecosystem have been sensational and Sui has quickly ascended to the forefront of Layer 1 blockchains,” said Greg Siourounis, Managing Director of the Sui Foundation. “Sui’s global footprint has continued to expand at a remarkable rate as more and more builders see Sui as the best platform for enabling real world solutions aimed at addressing the world’s most pressing challenges.” “As we mark the first anniversary of Sui's launch, the growth and innovation within the Sui ecosystem have been sensational and Sui has quickly ascended to the forefront of Layer 1 blockchains,” said Greg Siourounis, Managing Director of the Sui Foundation. “Sui’s global footprint has continued to expand at a remarkable rate as more and more builders see Sui as the best platform for enabling real world solutions aimed at addressing the world’s most pressing challenges.” Gaming is another focus for Sui that will continue in the coming months and years. With low, predictable fees that allow game developers to build with confidence and dynamic objects that make games built on Sui more expressive, Sui is the optimal blockchain for gaming studios. Dozens of development teams are currently building games on Sui, including established studios such as NHN (Pebble City), ONBUFF x SNK (Samurai Shodown), NDUS Interactive (Xociety), Orange Comet (The Walking Dead: Lands), and Ambrus Studio (E4C: Final Salvation). Leading professional esports team, Team Liquid, will leverage Sui for the relaunch of its fan loyalty program, and at Sui Basecamp in April, Sui joined gaming infrastructure developer Playtron in announcing SuiPlay0X1, the first handheld gaming device with native blockchain capabilities to wide acclaim. Other notable ecosystem partnerships achieved in Sui’s first year include those with Alibaba Cloud and Google Cloud, which focused on enhancing security, scalability, developer tools and user experiences across a range of Web 3.0 and AI-powered applications. BytePlus, the web3 arm of ByteDance, partnered with Sui ecosystem partner Mysten Labs to explore collaboration on data warehousing, AI recommendation algorithms, and AI visual algorithms in web3 game platforms and socialFi projects on Sui. The crowds that gathered for Sui Basecamp 2024 represented the culmination of Sui’s arrival, as over 1,000 projects, partners, investors and enthusiasts from 65 countries around the world came to Paris in April to celebrate Sui at the vaunted Layer 1’s inaugural global conference. Contact Sui Foundation media@sui.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Sui Turns One: Debut Year Of Growth and Tech Breakthroughs Puts Sui At Forefront Of Web3

Recommendations by Concise User Profiles from Review Text: Ethics Statement and References

Authors:
(1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Abstract This research delves into the comparative advantages of Generative AI chatbots (GenAIbots) - ChatGPT, Bing Chat, Bard, and Claude - in the context of Chemistry education, framed within a constructivist perspective. Our primary objective was to identify which of these four AI tools is more effective for enhancing Chemistry learning. Employing a single-case study approach, we scrutinised interaction logs between the AI systems and a simulated student persona during Chemistry learning simulations, incorporating Content Analysis methodology to delve deeper into the discourse. Our findings underscore these tools' potential as "agents-to-think-with", enhancing critical thinking, problem-solving, comprehension, creativity, and tailored learning. Especially noteworthy is their ability to stimulate learners through Socratic-like questioning, aligning with constructionist principles. The research emphasises the pivotal role of prompt crafting to coax desired responses from GenAIbots, engendering iterative reflections. It also highlights the need for robust educator training to infuse these technologies into educational settings. Conclusively, while ChatGPT, Bing Chat, Bard, and Claude are poised to enrich Chemistry education by fostering dynamic, inclusive learning experiences, ChatGPT stood out, decisively surpassing Bing Chat's performance. Bard and Claude trailed closely, with all three showcasing a more in-depth, precise, and nuanced understanding, underscoring ChatGPT's adeptness at contextual comprehension. Keywords: Chemistry education, ChatGPT, Bing Chat, Bard, Claude, Artificial Intelligence in Education, agents-to-think-with Introduction Chemistry, a core Science Education subject, clarifies matter's properties and transformations, thus critically shaping our daily lives (Dunlop et al., 2020). However, Chemistry is also a complex and dynamic field that necessitates a profound grasp of fundamental concepts and principles, and it is sometimes difficult for students to associate real-life circumstances with abstract chemistry concepts (Dewi et al., 2021). Research in Chemistry Education seeks effective strategies to alleviate these learning difficulties (Permatasari et al., 2022; Timilsena et al., 2022; Tümay, 2016). Timilsena et al. (2022) identified difficulties in understanding the abstract nature of chemical reactions and factors such as inadequate teaching materials and curriculum complexity, emphasising the need for effective teaching strategies and tools. Tümay (2016) discussed students' struggles in understanding fundamental chemistry concepts and emphasised the importance of addressing misconceptions and learning difficulties. Dewi et al. (2021) underscored the need for critical thinking skills and the integration of digital technology to enhance the quality of Chemistry education for Generation Z students. Dunlop et al. (2020) proposed introducing philosophical dialogue in higher education to address undergraduate Chemistry students' challenges, suggesting that it can stimulate new ways of thinking. In 2023, Castro Nascimento and Pimentel undertook a study to evaluate the proficiency of the ChatGPT model by having it respond to five distinct tasks across various subfields of chemistry (Castro Nascimento & Pimentel, 2023). These tasks included converting compound names to their SMILES chemical representation and vice versa, procuring information on the octanol-water partition coefficient of chemical compounds, extracting structural information on coordination compounds, determining the water solubility of polymers, and identifying the molecular point groups of simple molecular compounds. The unsatisfactory outcomes highlighted potential limitations in the model's ability to adequately address these specific chemistry-related queries. Notably, the suboptimal performance observed might be attributed to utilising an antiquated version of ChatGPT, specifically the GPT-3 model introduced by OpenAI in 2020 (Brown et al., 2020). In a separate study conducted in the same year, Leon and Vidhani (2023) explored the reliability of ChatGPT responses within the framework of an introductory college-level Chemistry course. Their findings indicated a significant reliability concern, with ChatGPT failing to secure a score above 37%. Such a performance implies that learners relying on this tool for study support would predominantly receive incorrect responses, with the variability of the tool leading to different responses for individual learners. Although the authors didn't specify which version of ChatGPT they utilised in their study, their reference to "ChatGPT's free original version" and the citation of Floridi and Chiriatti's (2020) research on ChatGPT-3 hint at the likelihood that they employed this version. Additionally, Pimentel et al. (2023) delved into the efficacy of ChatGPT versions 3 and 4 in responding to intricate questions spanning six topics in Chemistry. While they concluded that both versions were currently inadequate in addressing the nuances of complex topics, they also observed noteworthy advancements from ChatGPT-3 to ChatGPT-4. Such progress signals promising potential for the tool to aid scientists in future literature reviews, surveys, and educational endeavours. Generative AI-powered chatbots (GenAIbots), including ChatGPT, Bing Chat, Bard, and Claude, have been introduced as innovative solutions to persistent challenges in Chemistry education (Baidoo-Anu & Owusu Ansah, 2023; Taylor et al., 2022). Their emergence offers a dynamic, inclusive educational environment, transforming how complex concepts are conveyed and understood. These GenAIbots simplify intricate topics, promote self-reflection, engage users in stimulating dialogues, facilitate personalised learning, and enhance critical thinking, collaboration, and cognitive development (Okonkwo & Ade-Ibijola, 2021). As a result, they have played a pivotal role in revolutionising Chemistry education. In the discourse on agency, traditional theories, such as the ones of Anscombe and Davidson, attribute actions to entities based on representational mental states encompassing desires, beliefs, and intentions. However, alternative perspectives, drawing from the works of Heider and Simmel, Dennett, Davidson, and Barandiaran et al., challenge this representation dependent view, suggesting potential agency without such mental representations (Schlosser, 2019). When considering GenAIbots within these frameworks, the entity's ability to respond based on training contrasts with its lack of self-awareness, intentions, and proactive behaviour— characteristics central to the agency. Consequently, while dominant philosophical and cognitive models would not grant ChatGPT agency, more expansive interpretations, as offered by these cited thinkers, could accept it. Building on this foundation and inspired by Melanie Swan's suggestion, we have expanded upon Papert's (1980) concept of "objects-to-think-with" to introduce “agents-to-thinkwith.” This positions GenAIbots as integral participants in the educational path, echoing Turkle's (1984) concept of "metacognitive machines," in the sense that they assist in enhancing one's awareness of their own cognitive processes, i.e., "thinking about thinking" as described by Flavell (1976). In Latour's (1991) perspective, we can perceive GenAIbots as "hybrids," which blur the boundaries between humans and non-human entities. Such a perspective further aligns with Swan's (2015) vision of a future where augmented humans and AI collaborate and thrive symbiotically. While GenAIbots posit themselves as powerful metacognitive educational tools, promoting critical thinking, problem-solving, and deep comprehension of concepts, it's imperative to acknowledge their limitations. For instance, there's the possibility of generating nonsensical or inaccurate content, as OpenAI (2023) highlighted. Nevertheless, the unique ability of GenAIbots to provide instant feedback, introduce diverse perspectives, and foster an interactive engagement with complex ideas solidifies their position as influential agents-to-think-with in the realm of Chemistry education. This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Authors: Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Abstract and Introduction Materials And Methods Materials And Methods Results and Analyses Results and Analyses Prompts and generated texts Prompts and generated texts Conceptualizing chemical reactions Conceptualizing chemical reactions Deepening on understanding of chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about combustion Question about a graph of gases turning into water over time Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Deepening on the concept of mole Question about changing of state Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about plasma, a state of matter Question about chemical bondings Question about chemical bondings Question about illustration of chemical bonds Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Question about the essence of the type of chemical bonding Further analysis Further analysis Conclusions Conclusions Limitations of the study and possible future studies Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Author Contributions, Conflicts of interest, Acknowledgements, and References Abstract This research delves into the comparative advantages of Generative AI chatbots (GenAIbots) - ChatGPT, Bing Chat, Bard, and Claude - in the context of Chemistry education, framed within a constructivist perspective. Our primary objective was to identify which of these four AI tools is more effective for enhancing Chemistry learning. Employing a single-case study approach, we scrutinised interaction logs between the AI systems and a simulated student persona during Chemistry learning simulations, incorporating Content Analysis methodology to delve deeper into the discourse. Our findings underscore these tools' potential as "agents-to-think-with", enhancing critical thinking, problem-solving, comprehension, creativity, and tailored learning. Especially noteworthy is their ability to stimulate learners through Socratic-like questioning, aligning with constructionist principles. The research emphasises the pivotal role of prompt crafting to coax desired responses from GenAIbots, engendering iterative reflections. It also highlights the need for robust educator training to infuse these technologies into educational settings. Conclusively, while ChatGPT, Bing Chat, Bard, and Claude are poised to enrich Chemistry education by fostering dynamic, inclusive learning experiences, ChatGPT stood out, decisively surpassing Bing Chat's performance. Bard and Claude trailed closely, with all three showcasing a more in-depth, precise, and nuanced understanding, underscoring ChatGPT's adeptness at contextual comprehension. Keywords: Chemistry education, ChatGPT, Bing Chat, Bard, Claude, Artificial Intelligence in Education, agents-to-think-with Keywords: Introduction Chemistry, a core Science Education subject, clarifies matter's properties and transformations, thus critically shaping our daily lives (Dunlop et al., 2020). However, Chemistry is also a complex and dynamic field that necessitates a profound grasp of fundamental concepts and principles, and it is sometimes difficult for students to associate real-life circumstances with abstract chemistry concepts (Dewi et al., 2021). Research in Chemistry Education seeks effective strategies to alleviate these learning difficulties (Permatasari et al., 2022; Timilsena et al., 2022; Tümay, 2016). Timilsena et al. (2022) identified difficulties in understanding the abstract nature of chemical reactions and factors such as inadequate teaching materials and curriculum complexity, emphasising the need for effective teaching strategies and tools. Tümay (2016) discussed students' struggles in understanding fundamental chemistry concepts and emphasised the importance of addressing misconceptions and learning difficulties. Dewi et al. (2021) underscored the need for critical thinking skills and the integration of digital technology to enhance the quality of Chemistry education for Generation Z students. Dunlop et al. (2020) proposed introducing philosophical dialogue in higher education to address undergraduate Chemistry students' challenges, suggesting that it can stimulate new ways of thinking. In 2023, Castro Nascimento and Pimentel undertook a study to evaluate the proficiency of the ChatGPT model by having it respond to five distinct tasks across various subfields of chemistry (Castro Nascimento & Pimentel, 2023). These tasks included converting compound names to their SMILES chemical representation and vice versa, procuring information on the octanol-water partition coefficient of chemical compounds, extracting structural information on coordination compounds, determining the water solubility of polymers, and identifying the molecular point groups of simple molecular compounds. The unsatisfactory outcomes highlighted potential limitations in the model's ability to adequately address these specific chemistry-related queries. Notably, the suboptimal performance observed might be attributed to utilising an antiquated version of ChatGPT, specifically the GPT-3 model introduced by OpenAI in 2020 (Brown et al., 2020). In a separate study conducted in the same year, Leon and Vidhani (2023) explored the reliability of ChatGPT responses within the framework of an introductory college-level Chemistry course. Their findings indicated a significant reliability concern, with ChatGPT failing to secure a score above 37%. Such a performance implies that learners relying on this tool for study support would predominantly receive incorrect responses, with the variability of the tool leading to different responses for individual learners. Although the authors didn't specify which version of ChatGPT they utilised in their study, their reference to "ChatGPT's free original version" and the citation of Floridi and Chiriatti's (2020) research on ChatGPT-3 hint at the likelihood that they employed this version. Additionally, Pimentel et al. (2023) delved into the efficacy of ChatGPT versions 3 and 4 in responding to intricate questions spanning six topics in Chemistry. While they concluded that both versions were currently inadequate in addressing the nuances of complex topics, they also observed noteworthy advancements from ChatGPT-3 to ChatGPT-4. Such progress signals promising potential for the tool to aid scientists in future literature reviews, surveys, and educational endeavours. Generative AI-powered chatbots (GenAIbots), including ChatGPT, Bing Chat, Bard, and Claude, have been introduced as innovative solutions to persistent challenges in Chemistry education (Baidoo-Anu & Owusu Ansah, 2023; Taylor et al., 2022). Their emergence offers a dynamic, inclusive educational environment, transforming how complex concepts are conveyed and understood. These GenAIbots simplify intricate topics, promote self-reflection, engage users in stimulating dialogues, facilitate personalised learning, and enhance critical thinking, collaboration, and cognitive development (Okonkwo & Ade-Ibijola, 2021). As a result, they have played a pivotal role in revolutionising Chemistry education. In the discourse on agency, traditional theories, such as the ones of Anscombe and Davidson, attribute actions to entities based on representational mental states encompassing desires, beliefs, and intentions. However, alternative perspectives, drawing from the works of Heider and Simmel, Dennett, Davidson, and Barandiaran et al., challenge this representation dependent view, suggesting potential agency without such mental representations (Schlosser, 2019). When considering GenAIbots within these frameworks, the entity's ability to respond based on training contrasts with its lack of self-awareness, intentions, and proactive behaviour— characteristics central to the agency. Consequently, while dominant philosophical and cognitive models would not grant ChatGPT agency, more expansive interpretations, as offered by these cited thinkers, could accept it. Building on this foundation and inspired by Melanie Swan's suggestion, we have expanded upon Papert's (1980) concept of "objects-to-think-with" to introduce “agents-to-thinkwith.” This positions GenAIbots as integral participants in the educational path, echoing Turkle's (1984) concept of "metacognitive machines," in the sense that they assist in enhancing one's awareness of their own cognitive processes, i.e., "thinking about thinking" as described by Flavell (1976). In Latour's (1991) perspective, we can perceive GenAIbots as "hybrids," which blur the boundaries between humans and non-human entities. Such a perspective further aligns with Swan's (2015) vision of a future where augmented humans and AI collaborate and thrive symbiotically. While GenAIbots posit themselves as powerful metacognitive educational tools, promoting critical thinking, problem-solving, and deep comprehension of concepts, it's imperative to acknowledge their limitations. For instance, there's the possibility of generating nonsensical or inaccurate content, as OpenAI (2023) highlighted. Nevertheless, the unique ability of GenAIbots to provide instant feedback, introduce diverse perspectives, and foster an interactive engagement with complex ideas solidifies their position as influential agents-to-think-with in the realm of Chemistry education. This paper is available on arxiv under CC BY-SA 4.0 DEED license. This paper is available on arxiv under CC BY-SA 4.0 DEED license. available on arxiv

Enhancing Chemistry Learning with ChatGPT, Bing Chat, Bard, and Claude as Agents-to-Think-With

ChatGPT, Bing Chat, Bard, এবং Claude-এর সাথে এজেন্ট-টু-থিঙ্ক-এর মাধ্যমে রসায়ন শেখার উন্নতি করা

Verbesserung des Chemielernens mit ChatGPT, Bing Chat, Bard und Claude als Denkagenten

Mejora del aprendizaje de química con ChatGPT, Bing Chat, Bard y Claude como agentes con los que pensar

Améliorer l'apprentissage de la chimie avec ChatGPT, Bing Chat, Bard et Claude en tant qu'agents avec lesquels penser

चैटजीपीटी, बिंग चैट, बार्ड और क्लाउड के साथ रसायन विज्ञान सीखने को बेहतर बनाना, एजेंट-टू-थिंक-विथ

ChatGPT、Bing Chat、Bard、Claude をエージェントとして利用して化学学習を強化する

ChatGPT, Bing Chat, Bard 및 Claude를 생각하는 에이전트로 사용하여 화학 학습 강화

Aprimorando o aprendizado de química com ChatGPT, Bing Chat, Bard e Claude como agentes para pensar

Улучшение изучения химии с помощью ChatGPT, Bing Chat, Bard и Claude в качестве агентов для размышлений

Birlikte Düşünülecek Aracılar Olarak ChatGPT, Bing Chat, Bard ve Claude ile Kimya Öğrenimini Geliştirme

Nâng cao việc học hóa học với ChatGPT, Bing Chat, Bard và Claude với tư cách là Đại lý để suy nghĩ

使用 ChatGPT、Bing Chat、Bard 和 Claude 作为思考代理来增强化学学习

A distributed system is one in which the failure of a computer you didn't even know existed can render your own computer unusable. This famous quote from, Leslie Lamport, an A.M. Turing Award Laureate, summarizes the challenges in building and maintaining a distributed system. But why is there a need for such complicated systems? With the advent of the internet and smarter devices, the amount of data that needs to be processed has exploded. Simple day-to-day activities like ordering an Uber, watching a show on Netflix, a simple Google search, online shopping, or interacting with social media, all trivial actions that we take for granted are powered by hundreds of distribution services. All these services are built on the backbone of some  foundational papers in distributed systems. While this list is definitely not comprehensive, here are some of my favorite papers that have had a massive impact on the world of distributed systems. CAP Theorem While not a traditional paper, Eric Brewer first introduced it as a conjecture in a keynote address at the 2000 ACM Symposium on Principles of Distributed Computing (PODC). The paper was later formalized and proved by Nancy Lynch and Seth Gilbert in the paper Brewer’s Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services Eric Brewer's CAP theorem is a fundamental concept in distributed systems theory, stating that it is impossible for a distributed data store to simultaneously provide more than two out of three guarantees: consistency, availability, and partition tolerance. All other papers mentioned here apply the above principle and make the necessary tradeoffs in their system. CAP theorem always leads to a lot of discussions based on readers’ understanding of the paper. Martin Kleppmann's " " provides a better framework to discuss the tradeoffs. A Critique of the CAP Theorem Paxos Made Simple In this seminal from 2001, Leslie Lamport presents the Paxos algorithm for achieving consensus in a distributed system in an easy and accessible way.  Paxos-based consensus protocols form the backbone of many distributed databases, storage systems, messaging platforms, and coordination services used by many technology companies. It heavily influenced other technologies like Google's Chubby, Google's Spanner, Apache ZooKeeper, Apache BookKeeper, etc. paper The Google File System introduces a scalable distributed file system for large distributed data-intensive applications on commodity hardware, which is the foundation for many distributed file systems that followed. GFS served as a major inspiration for HDFS, the distributed file system used by the Apache Hadoop framework and eventually Amazon S3 (event though s3 is fundamentally different). The Google File System (GFS) paper MapReduce: Simplified Data Processing on Large Clusters This introduces the MapReduce programming model, which demonstrates a scalable approach to processing large-scale datasets using distributed computing infrastructure. MapReduce played a pivotal role in the "big data" revolution, enabling organizations to harness the power of distributed computing to analyze and derive insights from massive datasets. You can see how combining GFS and MapReduce allowed Google to process Petabytes of data to organize data of the "internet." paper The MapReduce paper (along with GFS) inspired the development of an entire ecosystem of tools and libraries built around Apache Hadoop such as Apache Hive (data warehouse infrastructure built on Hadoop), Apache Pig (high-level data flow language for Hadoop), Apache Spark (in-memory data processing engine), Apache HBase (distributed NoSQL database), and many others. Bigtable: A Distributed Storage System for Structured Data The represents a distributed storage system for managing structured data at Google. Once MapReduce and GFS allowed Google to process data at scale in a cost-effective manner, the next step was to enable access to the data in a reliable and highly available manner. BigTable was able to provide a flexible, high-performance solution for applications like web indexing, Google Earth, and Google Finance. Bigtable paper Just like MapReduce revolutionized the "big data" era, BigTable paper was the moving force for the "NoSQL" era. Many of the design principles and architectural concepts introduced in the Bigtable paper, were used in technologies like "Apache HBase", "Cassandra", "MongoD", etc. While some of these applications might use different data models (e.g., MongoDB),  they share common principles such as horizontal scalability, fault tolerance, and automatic sharding. Dynamo: Amazon's Highly Available Key-Value Store presents the design and implementation of a highly available key-value store developed by Amazon. Dynamo addressed the need for real-time access to highly dynamic data, such as items in your shopping cart. The paper introduced the concept of "eventual consistency" as a core principle of distributed systems design, allowing for relaxed consistency guarantees to achieve high availability and performance (hi CAP theorem!). Dynamo paper From the paper itself, “Compared to Bigtable, Dynamo targets applications that require only key/value access with primary focus on high availability where updates are not rejected even in the wake of network partitions or server failures.” Similar to BigTable, the Dynamo paper highly influenced subsequent technologies like Riak, Voldemort, Cassandra, and even event streaming technologies like Apache Kafka. Cassandra—A Decentralized Structured Storage System Facebook's rapid growth necessitated a database solution capable of handling massive amounts of data and supporting a large number of concurrent users. While BigTable and Dynamo were quite influential in their own right, Cassandra was the first technology that went a step ahead of others. By releasing it as an open-source contribution under the Apache License along with publishing the , Facebook was instrumental in enabling access to such technology to the entire industry. paper Cassandra differentiated itself from the previous two by providing a tunable consistency model, allowing users to choose between strong consistency (like BigTable) and eventual consistency (like Dynamo) based on their application requirements. ZooKeeper: Wait-free coordination for Internet-scale systems This introduces Apache ZooKeeper and presents its design principles and algorithms for providing highly reliable and scalable coordination services in distributed systems. Before the introduction of ZooKeeper, software developers often had to implement their own ad-hoc solutions for distributed coordination and consensus in distributed systems. paper ZooKeeper proposed a centralized service for distributed coordination, offering primitives such as distributed locks, leader election, and configuration management This allowed to simplify the development of distributed applications by offloading complex coordination logic to ZooKeeper. One of the most common use cases of using Zookeeper is for service discovery. Apache Kafka: a Distributed Messaging System for Log Processing This introduces Apache Kafka, a distributed messaging system designed for high-throughput, fault-tolerant processing of event streams. Kafka's publication as a research paper and its open-source release as an Apache project established it as a standard messaging system for highly scalable and fault-tolerant real-time data processing and event-driven architectures. paper Kafka introduced a highly scalable and fault-tolerant messaging system designed for handling large volumes of data streams in real time. Kafka was quite influential in enabling the development of Lambda architecture, which combines batch processing and stream processing to handle large volumes of data with low latency and high throughput. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing This introduces Resilient Distributed Datasets (RDDs), the core abstraction in Apache Spark, which enables fault-tolerant, in-memory data processing across distributed clusters. Spark's in-memory execution engine  provides significantly faster performance compared to MapReduce (which has a disk-based execution model), especially for iterative algorithms, machine learning, and interactive analytics. paper These papers cover a broad range of topics in distributed systems, including storage systems, consensus algorithms, fault tolerance, and scalability. Reading them will provide a solid foundation in the principles and practices of building and managing distributed systems. If you're starting your journey in distributed systems and want to learn more, or you're already an expert and simply want to refresh your fundamentals, there is no better way to learn than reading some of these foundational papers on distributed systems.

Unveiling the Architecture: Key Papers to Understand Distributed Systems!

স্থাপত্য উন্মোচন: ডিস্ট্রিবিউটেড সিস্টেম বোঝার মূল কাগজপত্র!

Enthüllung der Architektur: Wichtige Dokumente zum Verständnis verteilter Systeme!

Revelando la arquitectura: ¡Documentos clave para comprender los sistemas distribuidos!

Dévoilement de l'architecture : articles clés pour comprendre les systèmes distribués !

आर्किटेक्चर का अनावरण: वितरित सिस्टम को समझने के लिए महत्वपूर्ण दस्तावेज!

アーキテクチャの解明: 分散システムを理解するための重要な論文!

아키텍처 공개: 분산 시스템을 이해하기 위한 주요 문서!

Revelando a Arquitetura: Artigos Chave para Compreender Sistemas Distribuídos!

Раскрытие архитектуры: ключевые статьи для понимания распределенных систем!

Mimariyi Ortaya Çıkarmak: Dağıtılmış Sistemleri Anlamak İçin Temel Makaleler!

Tiết lộ Kiến trúc: Các bài viết chính để hiểu về Hệ thống Phân tán!

揭开架构的面纱：理解分布式系统的关键论文！

How to Build an End-to-End ML Platform

AI Is Changing How Developers Learn: Here’s What That Means

এআই পরিবর্তন করছে কীভাবে বিকাশকারীরা শিখতে পারে: এখানে এর অর্থ কী

KI verändert die Lernweise von Entwicklern: Das bedeutet das

La IA está cambiando la forma en que aprenden los desarrolladores: esto es lo que eso significa

L’IA change la façon dont les développeurs apprennent : voici ce que cela signifie

AI डेवलपर्स के सीखने के तरीके को बदल रहा है: जानिए इसका क्या मतलब है

AI が開発者の学習方法を変える: それが何を意味するのか

AI는 개발자의 학습 방식을 변화시키고 있습니다. 이것이 의미하는 바는 다음과 같습니다.

A IA está mudando a forma como os desenvolvedores aprendem: eis o que isso significa

ИИ меняет способ обучения разработчиков: вот что это значит

Yapay Zeka, Geliştiricilerin Öğrenme Şeklini Değiştiriyor: İşte Bu Ne Anlama Geliyor?

AI đang thay đổi cách các nhà phát triển học hỏi: Đây là ý nghĩa của điều đó

人工智能正在改变开发人员的学习方式：这意味着什么

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