A Provi é a primeira fintech de crédito do Brasil focada em transformar o setor da educação através de crédito descomplicado e com propósito

Provi

**DUBAI, UAE, July 15th, 2024/CyberNewsWire/--**On May 31, 2024, as a result of the hacking 4502.9 BTC(worth approximately $308M)were stolen from the Japanese exchange Bitcoin.DMM.com. The cybersecurity agency Match Systems conducted the current situation of the case. Japanese cryptocurrency exchange DMM Bitcoin was recently hacked, resulting in the theft of over $300 million dollars in Bitcoins. The hackers were able to access a private key, which allowed them to transfer 4,502.9 bitcoins from the exchange's main wallet. The incident occurred on May 30, 2024, and DMM Bitcoin announced the hack the following day. The reasons for the hack of the exchange are still unclear. The attack could have occurred as a result of compromised private keys. The keys of a hot wallet connected to the Internet could have been compromised either through an internal threat or an external hack, which could have allowed hackers to initiate a transfer of funds. Whether social engineering techniques or malware were used to get exchange employees to sign a transaction authorizing the transfer of funds to their wallets, we have yet to learn. An insider attack scenario cannot be ruled out, in which someone with legitimate access to the system contributed to the hack by giving the hackers the necessary data or initiating the attack. The investigation revealed that the hackers used cryptocurrency mixer JoinMarket to launder the stolen funds. More than 2,000 BTC was sent to addresses associated with JoinMarket, while the remaining 2,500 BTC remained at the hackers' original addresses. The Match Systems team was able to identify the first large withdrawal from the mixer in the amount of 223.38 BTC, as well as more than 50 withdrawals over 10 BTC that may be relevant to this case. The full cycle of money laundering can take months to a year, and Match Systems will continue to monitor the movement of stolen funds, as well as looking into the cause of the attack. About Match Systems Match Systems, is a leading company specializing in AML services, blockchain investigations, and implementation of compliance procedures for cryptocurrency projects around the world. By leveraging advanced technology and expertise in financial crime detection, the company is poised to help organizations to navigate the complex regulatory landscape as well as minimize the risks associated with digital currencies. Contact Joseph Match Systems mediacoverage@matchsystems.com This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here. **DUBAI, UAE, July 15th, 2024/CyberNewsWire/--**On May 31, 2024, as a result of the hacking 4502.9 BTC(worth approximately $308M)were stolen from the Japanese exchange Bitcoin.DMM.com. The cybersecurity agency Match Systems conducted the current situation of the case. Japanese cryptocurrency exchange DMM Bitcoin was recently hacked, resulting in the theft of over $300 million dollars in Bitcoins. The hackers were able to access a private key, which allowed them to transfer 4,502.9 bitcoins from the exchange's main wallet. The incident occurred on May 30, 2024, and DMM Bitcoin announced the hack the following day. The reasons for the hack of the exchange are still unclear. The attack could have occurred as a result of compromised private keys. The keys of a hot wallet connected to the Internet could have been compromised either through an internal threat or an external hack, which could have allowed hackers to initiate a transfer of funds. Whether social engineering techniques or malware were used to get exchange employees to sign a transaction authorizing the transfer of funds to their wallets, we have yet to learn. An insider attack scenario cannot be ruled out, in which someone with legitimate access to the system contributed to the hack by giving the hackers the necessary data or initiating the attack. The investigation revealed that the hackers used cryptocurrency mixer JoinMarket to launder the stolen funds. More than 2,000 BTC was sent to addresses associated with JoinMarket, while the remaining 2,500 BTC remained at the hackers' original addresses. The Match Systems team was able to identify the first large withdrawal from the mixer in the amount of 223.38 BTC, as well as more than 50 withdrawals over 10 BTC that may be relevant to this case. The full cycle of money laundering can take months to a year, and Match Systems will continue to monitor the movement of stolen funds, as well as looking into the cause of the attack. About Match Systems Match Systems , is a leading company specializing in AML services, blockchain investigations, and implementation of compliance procedures for cryptocurrency projects around the world. By leveraging advanced technology and expertise in financial crime detection, the company is poised to help organizations to navigate the complex regulatory landscape as well as minimize the risks associated with digital currencies. Match Systems Match Systems Contact Joseph Match Systems mediacoverage@matchsystems.com This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Match Systems' CEO Andrei Kutin Provides Insight On DMM Bitcoin Breach

It's baffling to see so many Australians clinging to Telstra, the giant of the NBN internet scene, despite its glaring shortcomings. With a staggering 40.4% market share, Telstra is undeniably the most popular NBN provider. Yet, when it comes to value, it’s falling woefully short. According to Tom's Guide, leaving Telstra could save you AU$3,660 over five years if you’re on an NBN 1000 plan (1Gbps). Let that sink in. For the same price of around AU$100 per month, consumers can access fast internet with speeds reaching up to 1000Mbps through a slew of emerging ISPs. Meanwhile, Telstra is content to cap its offering at a meager 50Mbps near the price point. So why the loyalty? Is it brand recognition? A misplaced sense of reliability? The disparity in value raises important questions: Is it time for Australians to break free from traditional providers? Are we settling for less due to comfort and familiarity? There’s a world of better options out there, and it's time for Australians to start exploring them. Australia deserves better than the status quo. Don't let loyalty blind you to better value. It’s time to demand more from your internet provider and make the switch to services that truly deliver on price vs speed and performance. Telstra may be a household name, but let’s face it: just because they’ve been around the block doesn’t mean they’re the best option. Plus, the sheer innovation of these newer players is refreshing. Many of them are not just competing on price; they're also investing in infrastructure and technology that promise a better future for all Australians. In the end, this isn’t just about saving a few bucks. It’s about voting with your wallet and demanding better service from the companies we choose to support. The NBN landscape in Australia is changing, and it’s time for consumers to wake up and embrace the options available. It’s about time we ditch the complacency and put our money where the value is. We need to address a glaring issue that’s been festering in the Australian market: too many people are lazily sticking with overpriced, household-name internet service providers without doing their homework! Seriously, are we really okay with this level of complacency when it comes to something as vital as our internet service? Let’s face it: just because a brand has been around forever doesn’t mean it’s the best option. People are stuck in a cycle of brand loyalty, clinging to these giant names while conveniently ignoring the fantastic alternatives out there. It’s frustrating! There are newer ISPs that offer better speeds, superior customer service, and, most importantly, more competitive pricing. But instead of exploring these options, many Australians choose to overpay for mediocrity. Research doesn’t take long, and there’s a wealth of information available at our fingertips. Compare plans, read reviews, and understand what other customers are saying. It’s not hard to understand that better deals can be found elsewhere. Seriously, Australia, how much longer are we going to let ourselves be duped by flashy ads and brand names? It’s beyond frustrating to watch so many people stick with overpriced internet service providers simply because they recognize the name. This isn't just about loyalty; it's about being smart with your money and your internet experience. Compare the prices. Old Vs New ISP Players. Telstra NBN 50mbps – $105 per month
Superloop NBN 1000mbps -$99 for 6 months then $109 ongoing. per month The benefits of switching to more affordable and faster ISP Switching to a more affordable and faster ISP can really transform your internet experience for the better. Here’s why it’s worth considering: Save Money
Let’s face it—who doesn’t love saving a few bucks? Many budget-friendly ISPs offer competitive prices that can help you cut down on your monthly bills, putting extra cash back in your pocket.


Enjoy Faster Speeds
With newer ISPs, you often get faster internet speeds that can make a big difference. Whether you’re streaming your favorite shows, gaming online, or working from home, having that speed means less buffering and smoother experiences overall.

Better Customer Support
Switching to a smaller or newer provider often means better customer service. These companies typically focus on keeping their customers happy, so you can expect quicker response times and more personalized support when you need help.


Flexible Plans to Fit Your Needs
Not everyone uses the internet the same way. Affordable ISPs often offer a range of plans that cater to different needs—whether you’re a casual browser or a heavy downloader—allowing you to choose what works best for you.


No Hidden Fees
One of the biggest annoyances with big-name providers can be hidden fees that pop up out of nowhere. Many newer ISPs are more transparent about their pricing, making it easier to understand what you’re paying for each month.


Reliable Service
With the right ISP, you can expect fewer outages and a more stable connection. Many newer providers are committed to maintaining their networks, which means you can enjoy uninterrupted service.


Access to the Latest Technology
Affordable ISPs often use the latest technology to deliver high-speed internet. This means you can benefit from fiber-optic connections and other advancements that enhance your online experience.


Support Local Innovation
By choosing a smaller or newer ISP, you’re often supporting local businesses that are passionate about improving internet access and competition. This helps foster a more dynamic market and encourages innovation. I personally challenge Australians to do better. It’s time to stop falling for the same old trap of brand loyalty without question. Take the plunge, do your research, and make informed choices about your internet provider. Your wallet—and your online experience—will thank you. It's baffling to see so many Australians clinging to Telstra, the giant of the NBN internet scene, despite its glaring shortcomings. With a staggering 40.4% market share, Telstra is undeniably the most popular NBN provider. Yet, when it comes to value, it’s falling woefully short. It's baffling to see so many Australians clinging to Telstra, the giant of the NBN internet scene, despite its glaring shortcomings. With a staggering 40.4% market share, Telstra is undeniably the most popular NBN provider. Yet, when it comes to value, it’s falling woefully short. According to Tom's Guide , leaving Telstra could save you AU$3,660 over five years if you’re on an NBN 1000 plan (1Gbps). Let that sink in. For the same price of around AU$100 per month, consumers can access fast internet with speeds reaching up to 1000Mbps through a slew of emerging ISPs. Meanwhile, Telstra is content to cap its offering at a meager 50Mbps near the price point. Tom's Guide Telstra So why the loyalty? Is it brand recognition? A misplaced sense of reliability? So why the loyalty? Is it brand recognition? A misplaced sense of reliability? The disparity in value raises important questions: Is it time for Australians to break free from traditional providers? Are we settling for less due to comfort and familiarity? There’s a world of better options out there, and it's time for Australians to start exploring them. Australia deserves better than the status quo. Don't let loyalty blind you to better value. It’s time to demand more from your internet provider and make the switch to services that truly deliver on price vs speed and performance. Telstra may be a household name, but let’s face it: just because they’ve been around the block doesn’t mean they’re the best option. Plus, the sheer innovation of these newer players is refreshing. Many of them are not just competing on price; they're also investing in infrastructure and technology that promise a better future for all Australians. In the end, this isn’t just about saving a few bucks. It’s about voting with your wallet and demanding better service from the companies we choose to support. The NBN landscape in Australia is changing, and it’s time for consumers to wake up and embrace the options available. It’s about time we ditch the complacency and put our money where the value is. It’s about time we ditch the complacency and put our money where the value is. We need to address a glaring issue that’s been festering in the Australian market: too many people are lazily sticking with overpriced, household-name internet service providers without doing their homework! Seriously, are we really okay with this level of complacency when it comes to something as vital as our internet service? Let’s face it: just because a brand has been around forever doesn’t mean it’s the best option. People are stuck in a cycle of brand loyalty, clinging to these giant names while conveniently ignoring the fantastic alternatives out there. It’s frustrating! There are newer ISPs that offer better speeds, superior customer service, and, most importantly, more competitive pricing. But instead of exploring these options, many Australians choose to overpay for mediocrity. Research doesn’t take long, and there’s a wealth of information available at our fingertips. Compare plans, read reviews, and understand what other customers are saying. It’s not hard to understand that better deals can be found elsewhere. Seriously, Australia, how much longer are we going to let ourselves be duped by flashy ads and brand names? It’s beyond frustrating to watch so many people stick with overpriced internet service providers simply because they recognize the name. This isn't just about loyalty; it's about being smart with your money and your internet experience. Compare the prices. Old Vs New ISP Players. Compare the prices. Telstra NBN 50mbps – $105 per month Superloop NBN 1000mbps -$99 for 6 months then $109 ongoing. per month Telstra NBN 50mbps – $105 per month Telstra NBN Superloop NBN 1000mbps -$99 for 6 months then $109 ongoing. per month Superloop NBN The benefits of switching to more affordable and faster ISP Switching to a more affordable and faster ISP can really transform your internet experience for the better. Here’s why it’s worth considering: Save Money
Let’s face it—who doesn’t love saving a few bucks? Many budget-friendly ISPs offer competitive prices that can help you cut down on your monthly bills, putting extra cash back in your pocket. Enjoy Faster Speeds
With newer ISPs, you often get faster internet speeds that can make a big difference. Whether you’re streaming your favorite shows, gaming online, or working from home, having that speed means less buffering and smoother experiences overall. Better Customer Support
Switching to a smaller or newer provider often means better customer service. These companies typically focus on keeping their customers happy, so you can expect quicker response times and more personalized support when you need help. Flexible Plans to Fit Your Needs
Not everyone uses the internet the same way. Affordable ISPs often offer a range of plans that cater to different needs—whether you’re a casual browser or a heavy downloader—allowing you to choose what works best for you. No Hidden Fees
One of the biggest annoyances with big-name providers can be hidden fees that pop up out of nowhere. Many newer ISPs are more transparent about their pricing, making it easier to understand what you’re paying for each month. Reliable Service
With the right ISP, you can expect fewer outages and a more stable connection. Many newer providers are committed to maintaining their networks, which means you can enjoy uninterrupted service. Access to the Latest Technology
Affordable ISPs often use the latest technology to deliver high-speed internet. This means you can benefit from fiber-optic connections and other advancements that enhance your online experience. Support Local Innovation
By choosing a smaller or newer ISP, you’re often supporting local businesses that are passionate about improving internet access and competition. This helps foster a more dynamic market and encourages innovation. Save Money Let’s face it—who doesn’t love saving a few bucks? Many budget-friendly ISPs offer competitive prices that can help you cut down on your monthly bills, putting extra cash back in your pocket. Save Money Save Money Let’s face it—who doesn’t love saving a few bucks? Many budget-friendly ISPs offer competitive prices that can help you cut down on your monthly bills, putting extra cash back in your pocket. Enjoy Faster Speeds With newer ISPs, you often get faster internet speeds that can make a big difference. Whether you’re streaming your favorite shows, gaming online, or working from home, having that speed means less buffering and smoother experiences overall. Enjoy Faster Speeds Enjoy Faster Speeds With newer ISPs, you often get faster internet speeds that can make a big difference. Whether you’re streaming your favorite shows, gaming online, or working from home, having that speed means less buffering and smoother experiences overall. Better Customer Support Switching to a smaller or newer provider often means better customer service. These companies typically focus on keeping their customers happy, so you can expect quicker response times and more personalized support when you need help. Better Customer Support Better Customer Support Switching to a smaller or newer provider often means better customer service. These companies typically focus on keeping their customers happy, so you can expect quicker response times and more personalized support when you need help. Flexible Plans to Fit Your Needs Not everyone uses the internet the same way. Affordable ISPs often offer a range of plans that cater to different needs—whether you’re a casual browser or a heavy downloader—allowing you to choose what works best for you. Flexible Plans to Fit Your Needs Flexible Plans to Fit Your Needs Not everyone uses the internet the same way. Affordable ISPs often offer a range of plans that cater to different needs—whether you’re a casual browser or a heavy downloader—allowing you to choose what works best for you. No Hidden Fees One of the biggest annoyances with big-name providers can be hidden fees that pop up out of nowhere. Many newer ISPs are more transparent about their pricing, making it easier to understand what you’re paying for each month. No Hidden Fees No Hidden Fees One of the biggest annoyances with big-name providers can be hidden fees that pop up out of nowhere. Many newer ISPs are more transparent about their pricing, making it easier to understand what you’re paying for each month. Reliable Service With the right ISP, you can expect fewer outages and a more stable connection. Many newer providers are committed to maintaining their networks, which means you can enjoy uninterrupted service. Reliable Service Reliable Service With the right ISP, you can expect fewer outages and a more stable connection. Many newer providers are committed to maintaining their networks, which means you can enjoy uninterrupted service. Access to the Latest Technology Affordable ISPs often use the latest technology to deliver high-speed internet. This means you can benefit from fiber-optic connections and other advancements that enhance your online experience. Access to the Latest Technology Access to the Latest Technology Affordable ISPs often use the latest technology to deliver high-speed internet. This means you can benefit from fiber-optic connections and other advancements that enhance your online experience. Support Local Innovation By choosing a smaller or newer ISP, you’re often supporting local businesses that are passionate about improving internet access and competition. This helps foster a more dynamic market and encourages innovation. Support Local Innovation Support Local Innovation By choosing a smaller or newer ISP, you’re often supporting local businesses that are passionate about improving internet access and competition. This helps foster a more dynamic market and encourages innovation. I personally challenge Australians to do better. It’s time to stop falling for the same old trap of brand loyalty without question. Take the plunge, do your research, and make informed choices about your internet provider. Your wallet—and your online experience—will thank you.

Why Are Aussies Still Sticking With High-Cost Internet Providers?

কেন অস্ট্রেলিয়া এখনও উচ্চ-মূল্যের ইন্টারনেট সরবরাহকারীদের সাথে লেগে আছে?

Warum bleiben Australier immer noch bei teuren Internetanbietern?

¿Por qué los australianos siguen recurriendo a proveedores de Internet de alto coste?

Pourquoi les Australiens s’en tiennent-ils toujours aux fournisseurs d’accès Internet à prix élevés ?

आस्ट्रेलियाई लोग अभी भी उच्च लागत वाली इंटरनेट प्रदाताओं के साथ क्यों जुड़े हुए हैं?

オーストラリア人はなぜいまだに高額なインターネットプロバイダーを使い続けているのでしょうか?

호주인들이 여전히 고비용 인터넷 제공업체를 고수하는 이유는 무엇입니까?

Por que os australianos ainda aderem a provedores de Internet de alto custo?

Почему австралийцы все еще предпочитают дорогих интернет-провайдеров?

Avustralyalılar Neden Hala Yüksek Maliyetli İnternet Sağlayıcılarıyla Çalışıyor?

Tại sao người Úc vẫn gắn bó với các nhà cung cấp Internet chi phí cao?

为什么澳大利亚人仍然坚持使用高价的互联网提供商？

"AI can ensure the publication of high-quality research, reduce biases, and provide faster feedback"

"এআই উচ্চ-মানের গবেষণার প্রকাশনা নিশ্চিত করতে পারে, পক্ষপাত কমাতে পারে এবং দ্রুত প্রতিক্রিয়া প্রদান করতে পারে"

„KI kann die Veröffentlichung qualitativ hochwertiger Forschungsergebnisse sicherstellen, Verzerrungen reduzieren und schnelleres Feedback liefern“

"La IA puede garantizar la publicación de investigaciones de alta calidad, reducir los sesgos y proporcionar comentarios más rápidos"

"L'IA peut garantir la publication de recherches de haute qualité, réduire les biais et fournir un retour d'information plus rapide"

"एआई उच्च गुणवत्ता वाले शोध का प्रकाशन सुनिश्चित कर सकता है, पूर्वाग्रहों को कम कर सकता है और तेजी से प्रतिक्रिया प्रदान कर सकता है"

「AIは、高品質の研究の出版を保証し、偏見を減らし、より迅速なフィードバックを提供することができます」

"AI는 고품질 연구의 출판을 보장하고 편견을 줄이며 더 빠른 피드백을 제공할 수 있습니다."

“A IA pode garantir a publicação de pesquisas de alta qualidade, reduzir preconceitos e fornecer feedback mais rápido”

«ИИ может обеспечить публикацию высококачественных исследований, уменьшить предвзятость и обеспечить более быструю обратную связь»

"Yapay zeka, yüksek kaliteli araştırmaların yayınlanmasını sağlayabilir, önyargıları azaltabilir ve daha hızlı geri bildirim sağlayabilir"

"AI có thể đảm bảo xuất bản nghiên cứu chất lượng cao, giảm sai lệch và cung cấp phản hồi nhanh hơn"

“人工智能可以确保发表高质量的研究，减少偏见，并提供更快的反馈”

Authors:
(1) Hamid Reza Saeidnia, Department of Information Science and Knowledge Studies, Tarbiat Modares University, Tehran, Islamic Republic of Iran;
(2) Elaheh Hosseini, Department of Information Science and Knowledge Studies, Faculty of Psychology and Educational Sciences, Alzahra University, Tehran, Islamic Republic of Iran;
(3) Shadi Abdoli, Department of Information Science, Université de Montreal, Montreal, Canada
(4) Marcel Ausloos, School of Business, University of Leicester, Leicester, UK and Bucharest University of Economic Studies, Bucharest, Romania. Table of Links Abstract and Introduction Materials and Methods Results RQ 1: AI and scientometrics RQ 2: AI and webometrics RQ 3: AI and bibliometrics Discussion RQ 4: Future of Scientometrics, Webometrics, and Bibliometrics with AI RQ 5: Ethical Considerations of Scientometrics, Webometrics, and Bibliometrics with AI Conclusion, Limitations, and References RQ 3: AI and bibliometrics In bibliometrics, AI can provide several specific benefits including Automated Data Collection, Citation Analysis, Author Disambiguation, Co-authorship Analysis, Research Impact Analysis, Text Mining, and Recommender Systems (see Figure 4) as analyzed in [28-30, 47-53]. These 6 studies demonstrate the potential benefits and strategies for utilizing AI capabilities in bibliometrics. They highlight how AI can improve the quality, accessibility, and data collection processes in bibliometrics analyses (Table 3), among the main outcome points. It has been shown that AI algorithms can automatically collect bibliographic data from various sources, such as online databases, academic libraries, and digital repositories [21, 49]. This saves time and effort for researchers involved in data collection, allowing them to focus on other aspects of bibliometric analysis. Thought-provokingly, AI can analyze citation networks to identify influential papers, authors, and journals [28, 31], - as already mentioned in the section “AI and Scientometrics”. By examining citation patterns and relationships, AI algorithms can help researchers understand the impact and visibility of research outputs, as well as identify key research trends and collaborations. Interestingly, AI techniques can be employed to disambiguate authors with similar names, a common issue in bibliometrics [47, 53]. By analyzing author affiliations, publication history, and co-authorship networks, in order to ensure the accuracy of bibliometric analyses, AI algorithms can effectively identify authors with similar names and distinguish them from one another. As also already mentioned in the section “AI and Scientometrics”, through AI one can analyze co-authorship networks to identify collaborations and research networks [28, 30]. By examining co-authorship patterns and relationships, AI algorithms can help researchers understand the dynamics and structure of collaborations, as well as identify influential researchers and research teams. This can also be an advantage at funding time. Easily, AI can analyze bibliometric indicators, such as citation counts and h-index, to assess the impact and visibility of individual researchers, research groups, and institutions [21, 48, 52]. In so doing, AI algorithms can provide insights into research productivity, citation patterns, and research impact over time, assisting researchers and institutions in assessing research fame or performance. Last but not least, AI techniques, including natural language processing, can be utilized to analyze the textual content of research publications [50, 51]. In this manner, keywords, topics, and sentiments can be extracted from the literature, - also mentioning plagiarism control [54, 55], thereby facilitating comprehensive analysis and understanding of research findings [56]. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Hamid Reza Saeidnia, Department of Information Science and Knowledge Studies, Tarbiat Modares University, Tehran, Islamic Republic of Iran; (2) Elaheh Hosseini, Department of Information Science and Knowledge Studies, Faculty of Psychology and Educational Sciences, Alzahra University, Tehran, Islamic Republic of Iran; (3) Shadi Abdoli, Department of Information Science, Université de Montreal, Montreal, Canada (4) Marcel Ausloos, School of Business, University of Leicester, Leicester, UK and Bucharest University of Economic Studies, Bucharest, Romania. Authors: Authors: (1) Hamid Reza Saeidnia, Department of Information Science and Knowledge Studies, Tarbiat Modares University, Tehran, Islamic Republic of Iran; (2) Elaheh Hosseini, Department of Information Science and Knowledge Studies, Faculty of Psychology and Educational Sciences, Alzahra University, Tehran, Islamic Republic of Iran; (3) Shadi Abdoli, Department of Information Science, Université de Montreal, Montreal, Canada (4) Marcel Ausloos, School of Business, University of Leicester, Leicester, UK and Bucharest University of Economic Studies, Bucharest, Romania. Table of Links Abstract and Introduction Abstract and Introduction Materials and Methods Materials and Methods Results Results RQ 1: AI and scientometrics RQ 1: AI and scientometrics RQ 2: AI and webometrics RQ 2: AI and webometrics RQ 3: AI and bibliometrics RQ 3: AI and bibliometrics Discussion Discussion RQ 4: Future of Scientometrics, Webometrics, and Bibliometrics with AI RQ 4: Future of Scientometrics, Webometrics, and Bibliometrics with AI RQ 5: Ethical Considerations of Scientometrics, Webometrics, and Bibliometrics with AI RQ 5: Ethical Considerations of Scientometrics, Webometrics, and Bibliometrics with AI Conclusion, Limitations, and References Conclusion, Limitations, and References RQ 3: AI and bibliometrics In bibliometrics, AI can provide several specific benefits including Automated Data Collection, Citation Analysis, Author Disambiguation, Co-authorship Analysis, Research Impact Analysis, Text Mining, and Recommender Systems (see Figure 4) as analyzed in [28-30, 47-53]. These 6 studies demonstrate the potential benefits and strategies for utilizing AI capabilities in bibliometrics. They highlight how AI can improve the quality, accessibility, and data collection processes in bibliometrics analyses (Table 3), among the main outcome points. It has been shown that AI algorithms can automatically collect bibliographic data from various sources, such as online databases, academic libraries, and digital repositories [21, 49]. This saves time and effort for researchers involved in data collection, allowing them to focus on other aspects of bibliometric analysis. Thought-provokingly, AI can analyze citation networks to identify influential papers, authors, and journals [28, 31], - as already mentioned in the section “AI and Scientometrics”. By examining citation patterns and relationships, AI algorithms can help researchers understand the impact and visibility of research outputs, as well as identify key research trends and collaborations. Interestingly, AI techniques can be employed to disambiguate authors with similar names, a common issue in bibliometrics [47, 53]. By analyzing author affiliations, publication history, and co-authorship networks, in order to ensure the accuracy of bibliometric analyses, AI algorithms can effectively identify authors with similar names and distinguish them from one another. As also already mentioned in the section “AI and Scientometrics”, through AI one can analyze co-authorship networks to identify collaborations and research networks [28, 30]. By examining co-authorship patterns and relationships, AI algorithms can help researchers understand the dynamics and structure of collaborations, as well as identify influential researchers and research teams. This can also be an advantage at funding time. Easily, AI can analyze bibliometric indicators, such as citation counts and h-index, to assess the impact and visibility of individual researchers, research groups, and institutions [21, 48, 52]. In so doing, AI algorithms can provide insights into research productivity, citation patterns, and research impact over time, assisting researchers and institutions in assessing research fame or performance. Last but not least, AI techniques, including natural language processing, can be utilized to analyze the textual content of research publications [50, 51]. In this manner, keywords, topics, and sentiments can be extracted from the literature, - also mentioning plagiarism control [54, 55], thereby facilitating comprehensive analysis and understanding of research findings [56]. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

"In bibliometrics, AI can provide several specific benefits including Automated Data Collection..."

"বাইবলিওমেট্রিক্সে, এআই স্বয়ংক্রিয় ডেটা সংগ্রহ সহ বেশ কয়েকটি নির্দিষ্ট সুবিধা প্রদান করতে পারে..."

„In der Bibliometrie kann KI mehrere spezifische Vorteile bieten, darunter die automatisierte Datenerfassung …“

"En bibliometría, la IA puede proporcionar varios beneficios específicos, incluida la recopilación automatizada de datos..."

"En bibliométrie, l'IA peut offrir plusieurs avantages spécifiques, notamment la collecte automatisée de données..."

"ग्रंथमिति में, एआई स्वचालित डेटा संग्रह सहित कई विशिष्ट लाभ प्रदान कर सकता है..."

「計量書誌学において、AI は自動データ収集など、いくつかの具体的なメリットをもたらすことができます...」

"계량학에서 AI는 자동화된 데이터 수집을 포함하여 여러 가지 구체적인 이점을 제공할 수 있습니다..."

"Na bibliometria, a IA pode fornecer vários benefícios específicos, incluindo a coleta automatizada de dados..."

«В библиометрии ИИ может предоставить несколько конкретных преимуществ, включая автоматический сбор данных…»

"Bibliyometride yapay zeka, Otomatik Veri Toplama da dahil olmak üzere çeşitli spesifik faydalar sağlayabilir..."

"Trong đo lường thư mục, AI có thể mang lại một số lợi ích cụ thể bao gồm Thu thập dữ liệu tự động..."

“在文献计量学中，人工智能可以提供一些具体的好处，包括自动数据收集......”

Authors:
(1) Hamid Reza Saeidnia, Department of Information Science and Knowledge Studies, Tarbiat Modares University, Tehran, Islamic Republic of Iran;
(2) Elaheh Hosseini, Department of Information Science and Knowledge Studies, Faculty of Psychology and Educational Sciences, Alzahra University, Tehran, Islamic Republic of Iran;
(3) Shadi Abdoli, Department of Information Science, Université de Montreal, Montreal, Canada
(4) Marcel Ausloos, School of Business, University of Leicester, Leicester, UK and Bucharest University of Economic Studies, Bucharest, Romania. Table of Links Abstract and Introduction Materials and Methods Results RQ 1: AI and scientometrics RQ 2: AI and webometrics RQ 3: AI and bibliometrics Discussion RQ 4: Future of Scientometrics, Webometrics, and Bibliometrics with AI RQ 5: Ethical Considerations of Scientometrics, Webometrics, and Bibliometrics with AI Conclusion, Limitations, and References RQ 2: AI and webometrics In webometrics, AI can provide several specific benefits including Web Crawling and Data Collection, Web Link Analysis, Web Content Analysis, Social Media Analysis, Web Impact Analysis, and Recommender Systems as sketched in Figure 3, and e.g. it has been demonstrated through papers like [9, 10, 21, 36-45]. These 6 considerations point to the potential benefits and suggest focused strategies for utilizing AI capabilities in webometrics. The resulting findings highlight how AI can improve the quality, accessibility, and data collection processes in webometrics analyses, as outlined in Table 2. Indeed, algorithms based on artificial intelligence can automatically crawl and collect data from websites, including institutional websites, scientific research portals, and online repositories [39, 42]. This enables researchers to gather large amounts of web-based information for analysis, including publication data, author profiles, and citation patterns. In order to understand the relationship between publications, websites, and authors, artificial intelligence approaches can analyze hyperlink structures and web link patterns [9, 43]. By analyzing the link structure, AI algorithms can identify influential websites and authors, as well as detect communities, collaborations, and research networks within the web-based scientific ecosystem [17]. AI techniques, such as natural language processing and machine learning, can be employed to analyze the content of webpages and scientific publications available online [40, 41]. This enables researchers to extract key information, such as keywords, topics, and sentiments, from web-based documents, facilitating comprehensive analysis and understanding of research outputs. AI can analyze social media platforms, such as Twitter, to understand the online discussions, trends, and interactions related to scientific research [36, 38, 44]. By analyzing hashtags, mentions, and user behavior, AI algorithms can identify influential research topics, key opinion leaders, and potential collaborations within the online scientific community, as demonstrated in such previous works. AI can assess the impact and visibility of scientific research on the web [37, 46]. Indeed, by analyzing web traffic, page views, and social media metrics, AI algorithms can provide insights into the online visibility, dissemination, and engagement of scientific publications, authors, and research institutions. “Finally”, AI-powered recommender systems can assist researchers in discovering relevant scientific websites, online resources, and research collaborations [35, 45]. These papers, based on user preferences, reading behavior, and web usage data, show that personalized recommendations can be generated using AI algorithms, making it easier for researchers to explore the web-based scientific landscape and discover new opportunities for further research. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Hamid Reza Saeidnia, Department of Information Science and Knowledge Studies, Tarbiat Modares University, Tehran, Islamic Republic of Iran; (2) Elaheh Hosseini, Department of Information Science and Knowledge Studies, Faculty of Psychology and Educational Sciences, Alzahra University, Tehran, Islamic Republic of Iran; (3) Shadi Abdoli, Department of Information Science, Université de Montreal, Montreal, Canada (4) Marcel Ausloos, School of Business, University of Leicester, Leicester, UK and Bucharest University of Economic Studies, Bucharest, Romania. Authors: Authors: (1) Hamid Reza Saeidnia, Department of Information Science and Knowledge Studies, Tarbiat Modares University, Tehran, Islamic Republic of Iran; (2) Elaheh Hosseini, Department of Information Science and Knowledge Studies, Faculty of Psychology and Educational Sciences, Alzahra University, Tehran, Islamic Republic of Iran; (3) Shadi Abdoli, Department of Information Science, Université de Montreal, Montreal, Canada (4) Marcel Ausloos, School of Business, University of Leicester, Leicester, UK and Bucharest University of Economic Studies, Bucharest, Romania. Table of Links Abstract and Introduction Abstract and Introduction Materials and Methods Materials and Methods Results Results RQ 1: AI and scientometrics RQ 1: AI and scientometrics RQ 2: AI and webometrics RQ 2: AI and webometrics RQ 3: AI and bibliometrics RQ 3: AI and bibliometrics Discussion Discussion RQ 4: Future of Scientometrics, Webometrics, and Bibliometrics with AI RQ 4: Future of Scientometrics, Webometrics, and Bibliometrics with AI RQ 5: Ethical Considerations of Scientometrics, Webometrics, and Bibliometrics with AI RQ 5: Ethical Considerations of Scientometrics, Webometrics, and Bibliometrics with AI Conclusion, Limitations, and References Conclusion, Limitations, and References RQ 2: AI and webometrics In webometrics, AI can provide several specific benefits including Web Crawling and Data Collection, Web Link Analysis, Web Content Analysis, Social Media Analysis, Web Impact Analysis, and Recommender Systems as sketched in Figure 3, and e.g. it has been demonstrated through papers like [9, 10, 21, 36-45]. These 6 considerations point to the potential benefits and suggest focused strategies for utilizing AI capabilities in webometrics. The resulting findings highlight how AI can improve the quality, accessibility, and data collection processes in webometrics analyses, as outlined in Table 2. Indeed, algorithms based on artificial intelligence can automatically crawl and collect data from websites, including institutional websites, scientific research portals, and online repositories [39, 42]. This enables researchers to gather large amounts of web-based information for analysis, including publication data, author profiles, and citation patterns. In order to understand the relationship between publications, websites, and authors, artificial intelligence approaches can analyze hyperlink structures and web link patterns [9, 43]. By analyzing the link structure, AI algorithms can identify influential websites and authors, as well as detect communities, collaborations, and research networks within the web-based scientific ecosystem [17]. AI techniques, such as natural language processing and machine learning, can be employed to analyze the content of webpages and scientific publications available online [40, 41]. This enables researchers to extract key information, such as keywords, topics, and sentiments, from web-based documents, facilitating comprehensive analysis and understanding of research outputs. AI can analyze social media platforms, such as Twitter, to understand the online discussions, trends, and interactions related to scientific research [36, 38, 44]. By analyzing hashtags, mentions, and user behavior, AI algorithms can identify influential research topics, key opinion leaders, and potential collaborations within the online scientific community, as demonstrated in such previous works. AI can assess the impact and visibility of scientific research on the web [37, 46]. Indeed, by analyzing web traffic, page views, and social media metrics, AI algorithms can provide insights into the online visibility, dissemination, and engagement of scientific publications, authors, and research institutions. “Finally”, AI-powered recommender systems can assist researchers in discovering relevant scientific websites, online resources, and research collaborations [35, 45]. These papers, based on user preferences, reading behavior, and web usage data, show that personalized recommendations can be generated using AI algorithms, making it easier for researchers to explore the web-based scientific landscape and discover new opportunities for further research. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

"In webometrics, AI can provide several specific benefits including Web Crawling, Data Collection...

"ওয়েবমেট্রিক্সে, AI ওয়েব ক্রলিং, ডেটা সংগ্রহ সহ বেশ কিছু নির্দিষ্ট সুবিধা প্রদান করতে পারে...

„In der Webometrie kann KI mehrere spezifische Vorteile bieten, darunter Web-Crawling und Datenerfassung …

"En webmetría, la IA puede proporcionar varios beneficios específicos, incluido el rastreo web, la recopilación de datos...

"En webométrie, l'IA peut apporter plusieurs avantages spécifiques, notamment l'exploration du Web, la collecte de données...

"वेबमेट्रिक्स में, एआई वेब क्रॉलिंग, डेटा संग्रह सहित कई विशिष्ट लाभ प्रदान कर सकता है...

「ウェブメトリクスでは、AI は Web クロール、データ収集など、いくつかの具体的なメリットを提供できます...」

"웹 측정학에서 AI는 웹 크롤링, 데이터 수집 등 여러 가지 구체적인 이점을 제공할 수 있습니다.

"Na webometria, a IA pode fornecer vários benefícios específicos, incluindo rastreamento da Web, coleta de dados...

«В вебометрике искусственный интеллект может предоставить несколько конкретных преимуществ, включая веб-сканирование, сбор данных…

"Webometride yapay zeka, Web Taraması, Veri Toplama gibi çeşitli belirli faydalar sağlayabilir...

"Trong webometrics, AI có thể mang lại một số lợi ích cụ thể bao gồm Thu thập thông tin trên web, Thu thập dữ liệu...

“在网络计量学中，人工智能可以提供一些特定的好处，包括网络爬虫、数据收集……

Navigating toward a cloud-native architecture can be both exciting and challenging. The expectation of learning valuable lessons should always be top of mind as design becomes a reality. In this article, I wanted to focus on an example where my project seemed like a perfect serverless use case, one where I’d leverage AWS Lambda. Spoiler alert: it was not. Rendering Fabric.js Data In a publishing project, we utilized Fabric.js—a JavaScript HTML5 canvas library—to manage complex metadata and content layers. These complexities included spreads, pages, and templates, each embedded with fonts, text attributes, shapes, and images. As the content evolved, teams were tasked with updates, necessitating the creation of a publisher-quality PDF after each update. We built a Node.js service to run Fabric.js, generating PDFs and storing resources in AWS S3 buckets with private cloud access. During a typical usage period, over 10,000 teams were using the service, with each contributor sending multiple requests to the service as a result of manual page saves or auto-saves driven by the Angular client. The service was set up to run as a Lambda in AWS. The idea of paying at the request level seemed ideal. Where Serverless Fell Short We quickly realized that our Lambda approach wasn’t going to cut it. The spin-up time turned out to be the first issue. Not only was there the time required to start the Node.js service, but preloading nearly 100 different fonts that could be used by those 10,000 teams caused delays too. We were also concerned about Lambda’s processing limit of 250 MB of unzipped source code. The initial release of the code was already over 150 MB in size, and we still had a large backlog of feature requests that would only drive this number higher. Finally, the complexity of the pages—especially as more elements were added—demanded increased CPU and memory to ensure quick PDF generation. After observing the usage for first-generation page designs completed by the teams, we forecasted the need for nearly 12 GB of RAM. Currently, AWS Lambdas are limited to 10 GB of RAM. Ultimately, we opted for dedicated EC2 compute resources to handle the heavy lifting. Unfortunately, this decision significantly increased our DevOps management workload. Looking For a Better Solution Although I am no longer involved with that project, I’ve always wondered if there was a better solution for this use case. While I appreciate AWS, Google, and Microsoft providing enterprise-scale options for cloud-native adoption, what kills me is the associated learning curve for every service. The company behind the project was a smaller technology team. Oftentimes teams in that position struggle with adoption when it comes to using the big three cloud providers. The biggest challenges I continue to see in this regard are: A heavy investment in DevOps or CloudOps to become cloud-native.
Gaining a full understanding of what appears to be endless options.
Tech debt related to cost analysis and optimization. Since I have been working with the Heroku platform, I decided to see if they had an option for my use case. Turns out, they introduced large dynos earlier this year. For example, with their Performance-L RAM dyno, my underlying service would get 50x the compute power of a standard Dyno and 30 GB of RAM. The capability to write to AWS S3 has been available from Heroku for a long time too. V2 Design In Action Using the Performance-L RAM dyno in Heroku would be no different (at least operationally) than using any other dyno in Heroku. To run my code, I just needed the following items: A Heroku account
The Heroku command-line interface (CLI) installed locally After navigating to the source code folder, I would issue a series of commands to log in to Heroku, create my app, set up my AWS-related environment variables, and run up to five instances of the service using the Performance-L dyno with auto-scaling in place: heroku login
heroku apps:create example-service
heroku config:set AWS_ACCESS_KEY_ID=MY-ACCESS-ID AWS_SECRET_ACCESS_KEY=MY-ACCESS-KEY
heroku config:set S3_BUCKET_NAME=example-service-assets
heroku ps:scale web=5:Performance-L-RAM
git push heroku main Once deployed, my example-service application can be called via standard RESTful API calls. As needed, the auto-scaling technology in Heroku could launch up to five instances of the Performance-L Dyno to meet consumer demand. I would have gotten all of this without having to spend a lot of time understanding a complicated cloud infrastructure or worrying about cost analysis and optimization. Projected Gains As I thought more about the CPU and memory demands of our publishing project—during standard usage seasons and peak usage seasons—I saw how these performance dynos would have been exactly what we needed. Instead of crippling our CPU and memory when the requested payload included several Fabric.js layers, we would have had enough horsepower to generate the expected image, often before the user navigated to the page containing the preview images.
We wouldn’t have had size constraints on our application source code, which we would inevitably have hit in AWS Lambda limitations within the next 3 to 4 sprints.
The time required for our DevOps team to learn Lambdas first and then switch to EC2 hit our project’s budget pretty noticeably. And even then, those services weren't cheap, especially when spinning up several instances to keep up with demand. But with Heroku, the DevOps investment would be considerably reduced, placed into the hands of software engineers working on the use case. Just like any other dyno, it’s easy to use and scale up the performance dynos either with the CLI or the Heroku dashboard. Conclusion My readers may recall my mission statement, which I feel can apply to any IT professional: “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester In this example, I had a use case that required a large amount of CPU and memory to process complicated requests made by over 10,000 consumer teams. I walked through what it would have looked like to fulfill this use case using Heroku's large dynos, and all I needed was a few CLI commands to get up and running. Burning out your engineering and DevOps teams is not your only option. There are alternatives available to relieve the strain. By taking the Heroku approach, you lose the steep learning curve that often comes with cloud adoption from the big three. Even better, the tech debt associated with cost analysis and optimization never sees the light of day. In this case, Heroku adheres to my mission statement, allowing teams to focus on what is likely a mountain of feature requests to help product owners meet their objectives. Have a really great day! Navigating toward a cloud-native architecture can be both exciting and challenging. The expectation of learning valuable lessons should always be top of mind as design becomes a reality. architecture In this article, I wanted to focus on an example where my project seemed like a perfect serverless use case, one where I’d leverage AWS Lambda. Spoiler alert: it was not. Spoiler alert: it was not. Rendering Fabric.js Data In a publishing project, we utilized Fabric.js —a JavaScript HTML5 canvas library—to manage complex metadata and content layers. These complexities included spreads, pages, and templates, each embedded with fonts, text attributes, shapes, and images. As the content evolved, teams were tasked with updates, necessitating the creation of a publisher-quality PDF after each update. Fabric.js JavaScript We built a Node.js service to run Fabric.js, generating PDFs and storing resources in AWS S3 buckets with private cloud access. During a typical usage period, over 10,000 teams were using the service, with each contributor sending multiple requests to the service as a result of manual page saves or auto-saves driven by the Angular client. Node.js Angular The service was set up to run as a Lambda in AWS. The idea of paying at the request level seemed ideal. Where Serverless Fell Short We quickly realized that our Lambda approach wasn’t going to cut it. The spin-up time turned out to be the first issue. Not only was there the time required to start the Node.js service, but preloading nearly 100 different fonts that could be used by those 10,000 teams caused delays too. We were also concerned about Lambda’s processing limit of 250 MB of unzipped source code. The initial release of the code was already over 150 MB in size, and we still had a large backlog of feature requests that would only drive this number higher. Finally, the complexity of the pages—especially as more elements were added—demanded increased CPU and memory to ensure quick PDF generation. After observing the usage for first-generation page designs completed by the teams, we forecasted the need for nearly 12 GB of RAM. Currently, AWS Lambdas are limited to 10 GB of RAM. Ultimately, we opted for dedicated EC2 compute resources to handle the heavy lifting. Unfortunately, this decision significantly increased our DevOps management workload. Looking For a Better Solution Although I am no longer involved with that project, I’ve always wondered if there was a better solution for this use case. While I appreciate AWS, Google, and Microsoft providing enterprise-scale options for cloud-native adoption, what kills me is the associated learning curve for every service. The company behind the project was a smaller technology team. Oftentimes teams in that position struggle with adoption when it comes to using the big three cloud providers. The biggest challenges I continue to see in this regard are: The biggest challenges I continue to see in this regard are: A heavy investment in DevOps or CloudOps to become cloud-native. Gaining a full understanding of what appears to be endless options. Tech debt related to cost analysis and optimization. A heavy investment in DevOps or CloudOps to become cloud-native. Gaining a full understanding of what appears to be endless options. Tech debt related to cost analysis and optimization. Since I have been working with the Heroku platform, I decided to see if they had an option for my use case. Turns out, they introduced large dynos earlier this year. For example, with their Performance-L RAM dyno, my underlying service would get 50x the compute power of a standard Dyno and 30 GB of RAM. The capability to write to AWS S3 has been available from Heroku for a long time too. Heroku large dynos write to AWS S3 V2 Design In Action Using the Performance-L RAM dyno in Heroku would be no different (at least operationally) than using any other dyno in Heroku. To run my code, I just needed the following items: A Heroku account The Heroku command-line interface (CLI) installed locally A Heroku account The Heroku command-line interface (CLI) installed locally Heroku command-line interface (CLI) After navigating to the source code folder, I would issue a series of commands to log in to Heroku, create my app, set up my AWS-related environment variables, and run up to five instances of the service using the Performance-L dyno with auto-scaling in place: heroku login
heroku apps:create example-service
heroku config:set AWS_ACCESS_KEY_ID=MY-ACCESS-ID AWS_SECRET_ACCESS_KEY=MY-ACCESS-KEY
heroku config:set S3_BUCKET_NAME=example-service-assets
heroku ps:scale web=5:Performance-L-RAM
git push heroku main heroku login
heroku apps:create example-service
heroku config:set AWS_ACCESS_KEY_ID=MY-ACCESS-ID AWS_SECRET_ACCESS_KEY=MY-ACCESS-KEY
heroku config:set S3_BUCKET_NAME=example-service-assets
heroku ps:scale web=5:Performance-L-RAM
git push heroku main Once deployed, my example-service application can be called via standard RESTful API calls. As needed, the auto-scaling technology in Heroku could launch up to five instances of the Performance-L Dyno to meet consumer demand. example-service I would have gotten all of this without having to spend a lot of time understanding a complicated cloud infrastructure or worrying about cost analysis and optimization. Projected Gains As I thought more about the CPU and memory demands of our publishing project—during standard usage seasons and peak usage seasons—I saw how these performance dynos would have been exactly what we needed. Instead of crippling our CPU and memory when the requested payload included several Fabric.js layers, we would have had enough horsepower to generate the expected image, often before the user navigated to the page containing the preview images. We wouldn’t have had size constraints on our application source code, which we would inevitably have hit in AWS Lambda limitations within the next 3 to 4 sprints. The time required for our DevOps team to learn Lambdas first and then switch to EC2 hit our project’s budget pretty noticeably. And even then, those services weren't cheap, especially when spinning up several instances to keep up with demand. Instead of crippling our CPU and memory when the requested payload included several Fabric.js layers, we would have had enough horsepower to generate the expected image, often before the user navigated to the page containing the preview images. We wouldn’t have had size constraints on our application source code, which we would inevitably have hit in AWS Lambda limitations within the next 3 to 4 sprints. The time required for our DevOps team to learn Lambdas first and then switch to EC2 hit our project’s budget pretty noticeably. And even then, those services weren't cheap, especially when spinning up several instances to keep up with demand. But with Heroku, the DevOps investment would be considerably reduced, placed into the hands of software engineers working on the use case. Just like any other dyno, it’s easy to use and scale up the performance dynos either with the CLI or the Heroku dashboard. Conclusion My readers may recall my mission statement, which I feel can apply to any IT professional: “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester In this example, I had a use case that required a large amount of CPU and memory to process complicated requests made by over 10,000 consumer teams. I walked through what it would have looked like to fulfill this use case using Heroku's large dynos, and all I needed was a few CLI commands to get up and running. Burning out your engineering and DevOps teams is not your only option. There are alternatives available to relieve the strain. By taking the Heroku approach, you lose the steep learning curve that often comes with cloud adoption from the big three. Even better, the tech debt associated with cost analysis and optimization never sees the light of day. In this case, Heroku adheres to my mission statement, allowing teams to focus on what is likely a mountain of feature requests to help product owners meet their objectives. Have a really great day!

When You Need More Power Than Lambda Provides

In this captivating interview, we dive deep into the world of Web3 and blockchain technology with Emile Dubié, the visionary co-founder of XDEFI. Discover the inspiring journey behind XDEFI's creation, its mission to revolutionize the multi-chain ecosystem, and its unique approach to navigating the competitive landscape of Web3 and blockchain interoperability. Ishan Pandey: Hello Emile, It's a pleasure to welcome you to our 'Behind the Startup' series. Can you tell us about the founding journey of XDEFI and what inspired you to create XDEFI? Emile Dubié: Hello Ishan. Thank you for having me. Both my co-founder and I were early investors and community members of the THORChain ecosystem. At that time, MetaMask was the only wallet extension available, and it was exclusively focused on Ethereum. We were convinced that the future would be multi-chain, and we decided to address this gap in the market. Our initial goal was to create the best wallet for users to interact with any interfaces built on top of THORChain. This goal then evolved into providing the best wallet for anyone. Ishan Pandey: How does XDEFI plan to differentiate itself in the Web3 and blockchain interoperability competitive landscape? Emile Dubié: As of today, we are the wallet that supports the most chains, with over 1,700 networks. We provide the best way for users to navigate from one ecosystem to another. Our swap feature supports more assets than any other wallet, and our gas tank abstracts the concept of gas, allowing users to migrate seamlessly between ecosystems without leaving the wallet or worrying about gas. We have implemented chain and account abstraction features that make the overall experience for the end users seamless when interacting with several ecosystems. Ishan Pandey: How are you navigating these challenges to ensure compliance with increasing regulatory scrutiny on cryptocurrencies and blockchain projects? Emile Dubié:  We are following closely what is happening at a regulatory level. As we are not in the custody of users' funds, we do not have the same requirements as centralized venues. We believe that self-custody is a fundamental right. Ishan Pandey: Given the rising price of Bitcoin and other cryptocurrencies, how do you see this trend affecting the adoption and development of crypto wallet platforms? Emile Dubié: We estimate there are over 500 million crypto holders globally, but only 10% currently use a self-custody wallet. Most opportunities are now on-chain, requiring a wallet to access them. We believe that in the next 24 months, more users will install wallets for on-chain activities. In the long term, we anticipate users will interact with wallets daily without realizing it's different from the fintech apps like Revolut or N26 they use regularly. As more corporations enter the space, further adoption will drive the necessity for wallets among users. Ishan Pandey: Can you discuss XDEFI's business model and how it aims to generate revenue while providing value to its users? Emile Dubié: We generate revenue from fees collected on swaps and bridging happening directly within the wallet. More revenue-generating features will be added in the future. Wallets are the first interfaces users interact with when they start on-chain. We believe they will add differentiating features that are easier to use than those on a dApp, creating new opportunities for revenue generation. Ishan Pandey: How do you envision the future of Web3, and what role do you believe you can play in shaping that future? Emile Dubié: The future of web3 lies in its potential to create a decentralized, user-controlled internet. Our mission is to help people access more attractive financial opportunities than they would if they kept their assets off-chain. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. In this captivating interview, we dive deep into the world of Web3 and blockchain technology with Emile Dubié, the visionary co-founder of XDEFI . Discover the inspiring journey behind XDEFI 's creation, its mission to revolutionize the multi-chain ecosystem, and its unique approach to navigating the competitive landscape of Web3 and blockchain interoperability. XDEFI XDEFI Ishan Pandey: Hello Emile, It's a pleasure to welcome you to our 'Behind the Startup' series. Can you tell us about the founding journey of XDEFI and what inspired you to create XDEFI? Ishan Pandey: Hello Emile, It's a pleasure to welcome you to our 'Behind the Startup' series. Can you tell us about the founding journey of XDEFI and what inspired you to create XDEFI? Ishan Pandey: Hello Emile, It's a pleasure to welcome you to our 'Behind the Startup' series. Can you tell us about the founding journey of XDEFI and what inspired you to create XDEFI? Emile Dubié: Hello Ishan. Thank you for having me. Both my co-founder and I were early investors and community members of the THORChain ecosystem. At that time, MetaMask was the only wallet extension available, and it was exclusively focused on Ethereum. We were convinced that the future would be multi-chain, and we decided to address this gap in the market. Our initial goal was to create the best wallet for users to interact with any interfaces built on top of THORChain. This goal then evolved into providing the best wallet for anyone. Emile Dubié: Ishan Pandey: How does XDEFI plan to differentiate itself in the Web3 and blockchain interoperability competitive landscape? Ishan Pandey: How does XDEFI plan to differentiate itself in the Web3 and blockchain interoperability competitive landscape? Ishan Pandey: How does XDEFI plan to differentiate itself in the Web3 and blockchain interoperability competitive landscape? Emile Dubié: As of today, we are the wallet that supports the most chains, with over 1,700 networks. We provide the best way for users to navigate from one ecosystem to another. Our swap feature supports more assets than any other wallet, and our gas tank abstracts the concept of gas, allowing users to migrate seamlessly between ecosystems without leaving the wallet or worrying about gas. We have implemented chain and account abstraction features that make the overall experience for the end users seamless when interacting with several ecosystems. Emile Dubié: Ishan Pandey: How are you navigating these challenges to ensure compliance with increasing regulatory scrutiny on cryptocurrencies and blockchain projects? Ishan Pandey: How are you navigating these challenges to ensure compliance with increasing regulatory scrutiny on cryptocurrencies and blockchain projects? Ishan Pandey: How are you navigating these challenges to ensure compliance with increasing regulatory scrutiny on cryptocurrencies and blockchain projects? Emile Dubié: We are following closely what is happening at a regulatory level. As we are not in the custody of users' funds, we do not have the same requirements as centralized venues. We believe that self-custody is a fundamental right. Emile Dubié: Ishan Pandey: Given the rising price of Bitcoin and other cryptocurrencies, how do you see this trend affecting the adoption and development of crypto wallet platforms? Ishan Pandey: Given the rising price of Bitcoin and other cryptocurrencies, how do you see this trend affecting the adoption and development of crypto wallet platforms? Ishan Pandey: Given the rising price of Bitcoin and other cryptocurrencies, how do you see this trend affecting the adoption and development of crypto wallet platforms? Emile Dubié: We estimate there are over 500 million crypto holders globally, but only 10% currently use a self-custody wallet. Most opportunities are now on-chain, requiring a wallet to access them. We believe that in the next 24 months, more users will install wallets for on-chain activities. In the long term, we anticipate users will interact with wallets daily without realizing it's different from the fintech apps like Revolut or N26 they use regularly. As more corporations enter the space, further adoption will drive the necessity for wallets among users. Emile Dubié: Ishan Pandey: Can you discuss XDEFI's business model and how it aims to generate revenue while providing value to its users? Ishan Pandey: Can you discuss XDEFI's business model and how it aims to generate revenue while providing value to its users? Ishan Pandey: Can you discuss XDEFI's business model and how it aims to generate revenue while providing value to its users? Emile Dubié: We generate revenue from fees collected on swaps and bridging happening directly within the wallet. More revenue-generating features will be added in the future. Wallets are the first interfaces users interact with when they start on-chain. We believe they will add differentiating features that are easier to use than those on a dApp, creating new opportunities for revenue generation. Emile Dubié: Ishan Pandey: How do you envision the future of Web3, and what role do you believe you can play in shaping that future? Ishan Pandey: How do you envision the future of Web3, and what role do you believe you can play in shaping that future? Ishan Pandey: How do you envision the future of Web3, and what role do you believe you can play in shaping that future? Emile Dubié: The future of web3 lies in its potential to create a decentralized, user-controlled internet. Our mission is to help people access more attractive financial opportunities than they would if they kept their assets off-chain. Emile Dubié: Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: business blogging program business blogging program

How XDEFI Plans to Provide the Best Wallet Experience for Web3 Users and Why It's Crucial

কিভাবে XDEFI Web3 ব্যবহারকারীদের জন্য সেরা ওয়ালেট অভিজ্ঞতা প্রদানের পরিকল্পনা করে এবং কেন এটি অত্যন্ত গুরুত্বপূর্ণ

Wie XDEFI das beste Wallet-Erlebnis für Web3-Benutzer bieten will und warum das so wichtig ist

Cómo XDEFI planea brindar la mejor experiencia de billetera para los usuarios de Web3 y por qué es crucial

Comment XDEFI prévoit de fournir la meilleure expérience de portefeuille aux utilisateurs Web3 et pourquoi c'est crucial

XDEFI वेब3 उपयोगकर्ताओं के लिए सर्वश्रेष्ठ वॉलेट अनुभव प्रदान करने की योजना कैसे बना रहा है और यह क्यों महत्वपूर्ण है

XDEFIがWeb3ユーザーに最高のウォレット体験を提供する計画とその重要性

XDEFI가 Web3 사용자에게 최고의 지갑 경험을 제공할 계획을 세우는 방법과 이것이 중요한 이유

Como a XDEFI planeja fornecer a melhor experiência de carteira para usuários Web3 e por que isso é crucial

Как XDEFI планирует обеспечить лучший опыт работы с кошельком для пользователей Web3 и почему это важно

XDEFI, Web3 Kullanıcılarına En İyi Cüzdan Deneyimini Nasıl Sunmayı Planlıyor ve Neden Önemli?

XDEFI lên kế hoạch cung cấp trải nghiệm ví tốt nhất cho người dùng Web3 như thế nào và tại sao nó lại quan trọng

XDEFI 计划如何为 Web3 用户提供最佳钱包体验以及其为何至关重要

AWS LetsEncrypt Lambda or Why I Wrote a Custom TLS Provider for AWS Using OpenTofu and Go

AWS LetsEncrypt Lambda বা কেন আমি OpenTofu এবং Go ব্যবহার করে AWS এর জন্য একটি কাস্টম TLS প্রদানকারী লিখেছি

AWS LetsEncrypt Lambda oder warum ich mit OpenTofu und Go einen benutzerdefinierten TLS-Anbieter für AWS geschrieben habe

AWS LetsEncrypt Lambda o por qué escribí un proveedor TLS personalizado para AWS usando OpenTofu and Go

AWS LetsEncrypt Lambda ou pourquoi j'ai écrit un fournisseur TLS personnalisé pour AWS à l'aide d'OpenTofu and Go

AWS LetsEncrypt लैम्ब्डा या मैंने OpenTofu और Go का उपयोग करके AWS के लिए एक कस्टम TLS प्रदाता क्यों लिखा

AWS LetsEncrypt Lambda または OpenTofu と Go を使用して AWS 用のカスタム TLS プロバイダーを作成した理由

AWS LetsEncrypt Lambda 또는 OpenTofu 및 Go를 사용하여 AWS용 사용자 지정 TLS 공급자를 작성한 이유

AWS LetsEncrypt Lambda ou por que escrevi um provedor TLS personalizado para AWS usando OpenTofu and Go

AWS LetsEncrypt Lambda или почему я написал собственный TLS-провайдер для AWS с использованием OpenTofu и Go

AWS LetsEncrypt Lambda veya OpenTofu ve Go'yu Kullanarak AWS için Neden Özel bir TLS Sağlayıcısı Yazdım?

AWS LetsEncrypt Lambda hoặc Tại sao tôi viết Nhà cung cấp TLS tùy chỉnh cho AWS bằng OpenTofu và Go

AWS LetsEncrypt Lambda 或为什么我使用 OpenTofu 和 Go 为 AWS 编写自定义 TLS 提供程序

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PROVI

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