Aligned

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This is Part 6 of a 7-part series of the research paper “Towards Usability Guidelines for the Design of Effective Arabic Websites”. Use the table of links below to navigate to the other parts. Table of Links Abstract and I. Introduction II. Previous Works III. Research Methodology IV. Font and Image Inspection Studies V. Results VI. Discussion VII. Conclusions, Future Research Directions, and References VI. DISCUSSION Our comprehensive inspection of current practices concerning text formatting and image usage within the top visited Arabic websites in Saudi Arabia revealed various interesting findings. The usability inspection was performed to gather insights about the font types and sizes used to style Arabic text, especially that they could directly influence the legibility of text on websites. Let us review and attempt to answer the research questions posited in the introduction. What font types and font sizes are used by major Arabic websites? On the positive side, the selection of the Arabic websites included a large pool of websites, which were selected objectively by relying on Alexa Internet latest ranking. In effect, the inspection covered a total of 73 top viewed websites (52 local and 21 international) in Saudi Arabia. The websites' ranking is based on a set of metrics, primarily the average viewing time for the last three months. Typically, a font has several characteristics including type, size, width, weight, and serifs [37], [46]. However, for the purpose of this research, we directed our focus towards two key font characteristics namely type and size. On the web, font type usually refers to the font family that represents a certain typeface, including all sizes and styles, for example, Arial and Verdana. To style a particular family type, the size of text may be increased or decreased using the font size attribute. There are different ways to resize the font including Ems (em), pixels (px), points (pt), and percent (%). In our font size analysis, we used pixels (px) as the sole measurement for the font since it is the main measurement unit for media shown on computer screens. Moreover, web designers usually use pixels as their key measurement unit for font size. Points, however, are used to measure font size for print media. It is noted that more than half of the Arabic websites breached the principle of consistency when applying font types to the text. This means that multiple font types were used on the same web pages. Previous research, however, has already emphasized the role of consistency of user interface elements, such as font, in the overall usability of websites [35], [36]. On that basis, it is recommended that designers should adhere to the same font family to create attractive and consistent Arabic web designs. Moreover, there was no evident consensus amongst the websites in favoring a particular font type in order to display the Arabic text. More than 35 font types were used by the selected 73 websites. There are various potential theories that could explain this staggering variability; firstly, the lack of research and thereby guidelines with respect to styling Arabic text to guide the effective design of Arabic websites; secondly, the weak conformance to international design practices and recommendations; thirdly, the lack of awareness that text formatting might ultimately impact text legibility and thereby readers' mental load and overall satisfaction. Nonetheless, a pattern of font usage emerged within the Arabic websites; six font types recurred several times in the formatting of titles/headline, menus, and paragraphs. These font types were used differently according to the type of text element. For titles and menus, Droid Arabic Kufi, Tahoma, Helvetica, and Arial, emerged as favorites. It is no surprise that Droid Arabic Kufi came out as a winner for it is a unique font that reflects the Arabic calligraphy. This font gives a true feeling of the traditional Arabic scripts (Kufic scripts) that date back to the 7th century. For paragraphs, Tahoma, Helvetica, Arial and Times New Roman were used more frequently. International recommendations suggest using font type Verdana since it is one of the most legible fonts as rated by online readers of English websites [38]. Nonetheless, this font did not appear frequently in the Arabic websites that we tested. Moreover, other famous fonts that were found earlier to be legible or attractive by English readers, such as Georgia [18] and Courier [10], did not rank well in the Arabic websites. However, Arial emerged as one of the top six font types used by the Arabic websites. Previous research confirmed that font type Arial was read significantly faster and was perceived as legible [10]. Design guidelines have indicated that font size 12 points (~ 16 pixels) is the most suited size for displaying text on English websites [39]. This is somewhat disputable as subsequent research suggested the use of font size 14 points (~19 pixels) instead. For displaying the Arabic text, recommendations are inconclusive yet. For example, [17] proposed to use font 14 points (~19 pixels) whereas [4] argued that font size 16 (22 pixels) to 18 points (~24 pixels) must be used for better readability. These suggestions are in strike contrast with the current practices of the Arabic web design. More than 60% of the inspected websites used font size ranging between 12 pixels to 16 pixels (i.e. 9 points to 12 points) to style the paragraphs. Similarly, menu items are sized from 13 pixels to 14 pixels, which is still considerably illegible [17]. In respect to using images in web design, we aimed at answering the following question. What types of images are incorporated within the Saudi websites given the Saudi culture? All Arabic websites included images as part of their content. Authors in [40] and [41] suggested that graphics improve the overall attractiveness of websites. Moreover, 90% of the Arabic websites we tested included human images. This is known to improve user engagement, trust, and satisfaction [21]. However, 80% of the Arabic websites used conservative images that respect the Islamic identity and cultural values of the Saudi people. Research studies agree that web designs should adhere to the cultural values of its users to achieve success and acceptance [42], [43], [44]. Two-thirds of the websites used images of both genders. The remaining third, however, used images of men only. This could be explained by the masculine dimension of the Saudi society as indicated by Hofstede scores [45]. More than 80% of the websites included images containing groups of people. Again, this can be justified by the collectivism dimension of the Saudi society [45]. Finally, there was high usage of animations, possibly, in an attempt to engage web visitors and improve the aesthetics of the websites. Evidently, the high presence of images in these websites contributed to lower performance scores and increased site loading time. Optimization of images‟ size, using the appropriate image compression techniques, is therefore recommended as a result of our analysis. Authors:
(1) Abdallah Namoun, Department of Information Systems, Faculty of Computer and Information Systems, Madinah, Saudi Arabia;
(2) Ahmad B. Alkhodre, Department of Information Technology, Faculty of Computer and Information Systems, Madinah, Saudi Arabia. This paper is available on arxiv under CC BY 4.0 DEED license. This is Part 6 of a 7-part series of the research paper “Towards Usability Guidelines for the Design of Effective Arabic Websites”. Use the table of links below to navigate to the other parts. This is Part 6 of a 7-part series of the research paper “ Towards Usability Guidelines for the Design of Effective Arabic Websites ”. Use the table of links below to navigate to the other parts. Part 6 Towards Usability Guidelines for the Design of Effective Arabic Websites Table of Links Abstract and I. Introduction Abstract and I. Introduction II. Previous Works II. Previous Works III. Research Methodology III. Research Methodology IV. Font and Image Inspection Studies IV. Font and Image Inspection Studies V. Results V. Results VI. Discussion VI. Discussion VII. Conclusions, Future Research Directions, and References VII. Conclusions, Future Research Directions, and References VI. DISCUSSION Our comprehensive inspection of current practices concerning text formatting and image usage within the top visited Arabic websites in Saudi Arabia revealed various interesting findings. The usability inspection was performed to gather insights about the font types and sizes used to style Arabic text, especially that they could directly influence the legibility of text on websites. Let us review and attempt to answer the research questions posited in the introduction. What font types and font sizes are used by major Arabic websites? On the positive side, the selection of the Arabic websites included a large pool of websites, which were selected objectively by relying on Alexa Internet latest ranking. In effect, the inspection covered a total of 73 top viewed websites (52 local and 21 international) in Saudi Arabia. The websites' ranking is based on a set of metrics, primarily the average viewing time for the last three months. Typically, a font has several characteristics including type, size, width, weight, and serifs [37], [46]. However, for the purpose of this research, we directed our focus towards two key font characteristics namely type and size. On the web, font type usually refers to the font family that represents a certain typeface, including all sizes and styles, for example, Arial and Verdana. To style a particular family type, the size of text may be increased or decreased using the font size attribute. There are different ways to resize the font including Ems (em), pixels (px), points (pt), and percent (%). In our font size analysis, we used pixels (px) as the sole measurement for the font since it is the main measurement unit for media shown on computer screens. Moreover, web designers usually use pixels as their key measurement unit for font size. Points, however, are used to measure font size for print media. It is noted that more than half of the Arabic websites breached the principle of consistency when applying font types to the text. This means that multiple font types were used on the same web pages. Previous research, however, has already emphasized the role of consistency of user interface elements, such as font, in the overall usability of websites [35], [36]. On that basis, it is recommended that designers should adhere to the same font family to create attractive and consistent Arabic web designs. Moreover, there was no evident consensus amongst the websites in favoring a particular font type in order to display the Arabic text. More than 35 font types were used by the selected 73 websites. There are various potential theories that could explain this staggering variability; firstly, the lack of research and thereby guidelines with respect to styling Arabic text to guide the effective design of Arabic websites; secondly, the weak conformance to international design practices and recommendations; thirdly, the lack of awareness that text formatting might ultimately impact text legibility and thereby readers' mental load and overall satisfaction. Nonetheless, a pattern of font usage emerged within the Arabic websites; six font types recurred several times in the formatting of titles/headline, menus, and paragraphs. These font types were used differently according to the type of text element. For titles and menus, Droid Arabic Kufi, Tahoma, Helvetica, and Arial, emerged as favorites. It is no surprise that Droid Arabic Kufi came out as a winner for it is a unique font that reflects the Arabic calligraphy. This font gives a true feeling of the traditional Arabic scripts (Kufic scripts) that date back to the 7th century. For paragraphs, Tahoma, Helvetica, Arial and Times New Roman were used more frequently. International recommendations suggest using font type Verdana since it is one of the most legible fonts as rated by online readers of English websites [38]. Nonetheless, this font did not appear frequently in the Arabic websites that we tested. Moreover, other famous fonts that were found earlier to be legible or attractive by English readers, such as Georgia [18] and Courier [10], did not rank well in the Arabic websites. However, Arial emerged as one of the top six font types used by the Arabic websites. Previous research confirmed that font type Arial was read significantly faster and was perceived as legible [10]. Design guidelines have indicated that font size 12 points (~ 16 pixels) is the most suited size for displaying text on English websites [39]. This is somewhat disputable as subsequent research suggested the use of font size 14 points (~19 pixels) instead. For displaying the Arabic text, recommendations are inconclusive yet. For example, [17] proposed to use font 14 points (~19 pixels) whereas [4] argued that font size 16 (22 pixels) to 18 points (~24 pixels) must be used for better readability. These suggestions are in strike contrast with the current practices of the Arabic web design. More than 60% of the inspected websites used font size ranging between 12 pixels to 16 pixels (i.e. 9 points to 12 points) to style the paragraphs. Similarly, menu items are sized from 13 pixels to 14 pixels, which is still considerably illegible [17]. In respect to using images in web design, we aimed at answering the following question. What types of images are incorporated within the Saudi websites given the Saudi culture? All Arabic websites included images as part of their content. Authors in [40] and [41] suggested that graphics improve the overall attractiveness of websites. Moreover, 90% of the Arabic websites we tested included human images. This is known to improve user engagement, trust, and satisfaction [21]. However, 80% of the Arabic websites used conservative images that respect the Islamic identity and cultural values of the Saudi people. Research studies agree that web designs should adhere to the cultural values of its users to achieve success and acceptance [42], [43], [44]. Two-thirds of the websites used images of both genders. The remaining third, however, used images of men only. This could be explained by the masculine dimension of the Saudi society as indicated by Hofstede scores [45]. More than 80% of the websites included images containing groups of people. Again, this can be justified by the collectivism dimension of the Saudi society [45]. Finally, there was high usage of animations, possibly, in an attempt to engage web visitors and improve the aesthetics of the websites. Evidently, the high presence of images in these websites contributed to lower performance scores and increased site loading time. Optimization of images‟ size, using the appropriate image compression techniques, is therefore recommended as a result of our analysis. Authors: (1) Abdallah Namoun, Department of Information Systems, Faculty of Computer and Information Systems, Madinah, Saudi Arabia; (2) Ahmad B. Alkhodre, Department of Information Technology, Faculty of Computer and Information Systems, Madinah, Saudi Arabia. Authors : Authors (1) Abdallah Namoun, Department of Information Systems, Faculty of Computer and Information Systems, Madinah, Saudi Arabia; (2) Ahmad B. Alkhodre, Department of Information Technology, Faculty of Computer and Information Systems, Madinah, Saudi Arabia. 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 available on arxiv

Design Arabic Websites with Consistent Fonts, Optimal Sizes, and Culturally Aligned Images

RateX Goes Live on Solana Mainnet on 17th Oct 2024. RateX, the world’s first leveraged yield exchange, has officially launched on the Solana mainnet, marking a significant milestone in the decentralized finance (DeFi) space. Built with innovation at its core, RateX enables users to trade synthetic yield tokens (YT) of various yield-bearing assets (YBA) with leverage of up to 10x. This powerful platform introduces groundbreaking solutions to maximize capital efficiency while addressing common DeFi challenges, such as impermanent loss and limited yield-trading opportunities. RateX, a proud recipient of a grant from the Solana Foundation and the first-place winner of the Solana Renaissance Hackathon (MCM), aims to push the boundaries of decentralized finance. The platform’s unique value proposition comes from its use of synthetic yield tokens, which track the yield of different assets and allow traders to take positions with leveraged exposure. This gives users more flexibility and opportunities to capitalize on fluctuations in yields, empowering them to generate higher returns on their investments. The introduction of RateX also brings a cutting-edge Time-Decaying Automated Market Maker (AMM) to the forefront. This AMM is designed to improve capital efficiency while reducing the risks traditionally associated with liquidity provisioning, particularly in expiring contracts. The mechanism minimizes the potential for impermanent loss—a common issue for liquidity providers (LPs) in volatile markets—and aims to eventually eliminate it altogether. As a result, RateX offers a more robust and rewarding environment for both traders and liquidity providers. In addition to its leveraged yield trading capabilities, RateX caters to users looking for stability by providing fixed-yield options. These options allow users to lock in specific yields over a predetermined period, offering more predictable returns compared to the highly variable DeFi market. Whether traders are seeking high-risk, high-reward opportunities or more stable, consistent gains, RateX provides an ecosystem that accommodates diverse trading strategies. Key Partnerships with Jupiter and Jito Further bolstering its platform, RateX has announced strategic partnerships with two prominent players in the Solana ecosystem—Jupiter and Jito. These partnerships not only strengthen RateX’s technological infrastructure but also extend its reach within the DeFi and staking communities. Jupiter, one of the largest decentralized trading platforms on Solana, is known for its high liquidity and strong governance framework. With an extensive community and a focus on enabling smooth cross-asset trading, Jupiter plays a pivotal role in bringing liquidity to the RateX platform. This partnership ensures that RateX users will benefit from deep liquidity pools, efficient price discovery, and seamless execution of trades. Jupiter’s active governance community also opens the door for collaborative development efforts, allowing RateX to evolve in line with community-driven innovations. On the staking side, RateX has joined forces with Jito, the leading liquid staking platform on Solana. Jito’s expertise in liquid staking will enhance RateX’s offerings by providing users with access to staking-derived yield-bearing assets. By leveraging Jito’s technology, RateX can integrate liquid staking into its synthetic yield ecosystem, offering even more diverse options for traders to earn yield. With this partnership, users can expect enhanced staking efficiency, better capital utilization, and a broader range of yield-bearing assets available for leveraged trading. A New Era for DeFi: RateX as a Pillar of Infrastructure The launch of RateX comes at a time when the DeFi sector is evolving rapidly, and the demand for more sophisticated financial products is higher than ever. By pioneering leveraged yield trading and forming key partnerships with Jupiter and Jito, RateX is positioning itself as a crucial pillar of the Solana ecosystem and DeFi infrastructure at large. RateX’s mission is to redefine how yield movements are traded, making the entire process more efficient, transparent, and accessible to both seasoned traders and new entrants to the space. As the world’s first leveraged yield exchange, RateX is primed to play a central role in shaping the next phase of decentralized finance, often referred to as the “next DeFi summer.” With its innovative platform, strong partnerships, and focus on capital efficiency, RateX is setting the stage for a new era of financial freedom and opportunities for DeFi enthusiasts worldwide. Learn more about RateX and join the future of decentralized finance: Website: rate-x.io Twitter: RateX_Dex Discord: RateX Community RateX Goes Live on Solana Mainnet on 17th Oct 2024. RateX, the world’s first leveraged yield exchange, has officially launched on the Solana mainnet, marking a significant milestone in the decentralized finance (DeFi) space. Built with innovation at its core, RateX enables users to trade synthetic yield tokens (YT) of various yield-bearing assets (YBA) with leverage of up to 10x. This powerful platform introduces groundbreaking solutions to maximize capital efficiency while addressing common DeFi challenges, such as impermanent loss and limited yield-trading opportunities. RateX Goes Live on Solana Mainnet on 17th Oct 2024. RateX, a proud recipient of a grant from the Solana Foundation and the first-place winner of the Solana Renaissance Hackathon (MCM), aims to push the boundaries of decentralized finance. The platform’s unique value proposition comes from its use of synthetic yield tokens, which track the yield of different assets and allow traders to take positions with leveraged exposure. This gives users more flexibility and opportunities to capitalize on fluctuations in yields, empowering them to generate higher returns on their investments. The introduction of RateX also brings a cutting-edge Time-Decaying Automated Market Maker (AMM) to the forefront. This AMM is designed to improve capital efficiency while reducing the risks traditionally associated with liquidity provisioning, particularly in expiring contracts. The mechanism minimizes the potential for impermanent loss—a common issue for liquidity providers (LPs) in volatile markets—and aims to eventually eliminate it altogether. As a result, RateX offers a more robust and rewarding environment for both traders and liquidity providers. Time-Decaying Automated Market Maker (AMM) In addition to its leveraged yield trading capabilities, RateX caters to users looking for stability by providing fixed-yield options. These options allow users to lock in specific yields over a predetermined period, offering more predictable returns compared to the highly variable DeFi market. Whether traders are seeking high-risk, high-reward opportunities or more stable, consistent gains, RateX provides an ecosystem that accommodates diverse trading strategies. Key Partnerships with Jupiter and Jito Key Partnerships with Jupiter and Jito Further bolstering its platform, RateX has announced strategic partnerships with two prominent players in the Solana ecosystem—Jupiter and Jito. These partnerships not only strengthen RateX’s technological infrastructure but also extend its reach within the DeFi and staking communities. Jupiter, one of the largest decentralized trading platforms on Solana, is known for its high liquidity and strong governance framework. With an extensive community and a focus on enabling smooth cross-asset trading, Jupiter plays a pivotal role in bringing liquidity to the RateX platform. This partnership ensures that RateX users will benefit from deep liquidity pools, efficient price discovery, and seamless execution of trades. Jupiter’s active governance community also opens the door for collaborative development efforts, allowing RateX to evolve in line with community-driven innovations. On the staking side, RateX has joined forces with Jito, the leading liquid staking platform on Solana. Jito’s expertise in liquid staking will enhance RateX’s offerings by providing users with access to staking-derived yield-bearing assets. By leveraging Jito’s technology, RateX can integrate liquid staking into its synthetic yield ecosystem, offering even more diverse options for traders to earn yield. With this partnership, users can expect enhanced staking efficiency, better capital utilization, and a broader range of yield-bearing assets available for leveraged trading. A New Era for DeFi: RateX as a Pillar of Infrastructure A New Era for DeFi: RateX as a Pillar of Infrastructure The launch of RateX comes at a time when the DeFi sector is evolving rapidly, and the demand for more sophisticated financial products is higher than ever. By pioneering leveraged yield trading and forming key partnerships with Jupiter and Jito, RateX is positioning itself as a crucial pillar of the Solana ecosystem and DeFi infrastructure at large. RateX’s mission is to redefine how yield movements are traded, making the entire process more efficient, transparent, and accessible to both seasoned traders and new entrants to the space. As the world’s first leveraged yield exchange, RateX is primed to play a central role in shaping the next phase of decentralized finance, often referred to as the “next DeFi summer.” With its innovative platform, strong partnerships, and focus on capital efficiency, RateX is setting the stage for a new era of financial freedom and opportunities for DeFi enthusiasts worldwide. Learn more about RateX and join the future of decentralized finance: Learn more about RateX and join the future of decentralized finance: Website: rate-x.io Website: rate-x.io Twitter: RateX_Dex Twitter: RateX_Dex Discord: RateX Community Discord: RateX Community

RateX Goes Live on Solana: The First Leveraged Yield Exchange is Now Jupiter & Jito Aligned 

RateX geht auf Solana live: Die erste Leveraged Yield Exchange ist jetzt auf Jupiter und Jito ausgerichtet

RateX se lanza en línea en Solana: el primer exchange con rendimiento apalancado ahora está alineado con Jupiter y Jito

RateX در Solana فعال می شود: اولین تبادل بازدهی اهرمی اکنون مشتری و جیتو هم تراز شده است 

RateX-ը գործարկվում է Solana-ում. Առաջին լծակային եկամտաբերության փոխանակումն այժմ հավասարեցված է Յուպիտերին և Ջիտոնին 

RateX Hadir di Solana: Bursa Hasil Leverage Pertama Kini Selaras dengan Jupiter & Jito

RateX va in diretta su Solana: il primo exchange di rendimento con leva finanziaria è ora allineato con Jupiter e Jito

RateXがSolanaで稼働開始: 初のレバレッジ利回り取引所がJupiterとJitoと提携

RateX Solana дээр ажиллаж байна: Анхны хөшүүрэгтэй өгөөжийн бирж нь одоо Бархасбадь ба Житотой нийцэж байна 

RateX Bersiaran Langsung di Solana: Pertukaran Hasil Leveraj Pertama Kini Diselaraskan dengan Musytari & Jito 

RateX gaat live op Solana: de eerste leveraged yield exchange is nu Jupiter & Jito Aligned

RateX Solanapi kawsan: Ñawpaq kaq Intercambio de Rendimiento Apalancado Kunanqa Jupiter & Jito Alineado kachkan 

RateX Goes Live on Solana: Ang Unang Leveraged Yield Exchange ay Jupiter at Jito Aligned na Ngayon 

A lot of remote teams start using Slack as a watering hole for getting everyone together to discuss what's going on and what'll happen next. Having all of these discussions happening in the #general channel is way too noisy. So teams start creating a bunch of random channels devoted to a specific purpose. Here are some of the channels we have at Hacker Noon. - We talk about stats, KPIs and really anything we can easily quantify that correlates to the success of HN. #analytics - Easy way for us to gather discussions about HN from any random corner of the internet. #aroundtheweb - Talk about how we build and maintain our infrastructure. #backend - Where we talk about supporting and developing our . #community community forum - Discussion about how we can incorporate more blindingly green pixels into our work without actually blinding users. #design - How do we promote our author's stories to give them a broader reader base? #distribution - Discussion about how our editorial team can help take story submissions and release them into the wild. #editorial - Discussion about newsletters and emails we're sending to users based on their activity. #emails - Talk about how we can iterate on our product to make it more usable and enjoyable. #frontend - Raw feed of new releases. #git - Hiring related discussion goes here. #jobs - Where we keep the team updated on what's new. #progress - Space where we share tips and tricks. #protips - Where we talk about the product direction and challenges we're facing. #product - Where we fix bugs. #techsupport - Where we monitor the status of our tests. #testing The above list is really only a sample of our channels. As you might notice, it's natural to organize channels based on a function within the organization. If a few people start working together on something, they'll either DM or start a new channel to keep organized. Overall, I think this type of setup is pretty natural and I don't really have a problem with it. But I do feel that something is missing from this setup and I'd like to talk about the problem and a potential solution. When we organize our communication by function, people  become fixated on their immediate responsibilities, but detached from how their work fits into the bigger picture. This detachment tends to get people thinking about how they can solve problems limited to the domain they have authority over. The result is often a prioritization of developer/designer problems over user problems. When user problems aren't a priority, teams tend to invest way too much energy scaling up things that aren't needed. It's like building a massive dog house with every amenity your dog could ever need...then finding out your dog prefers to sleep on the porch. What a colossal waste of time and money. You could have just bought a comfortable mat and Rover would have been much happier. It's absolutely critical to spend time daily talking about what your users actually need. Otherwise, your team is going to be stressed out building dog houses for no good reason. In the above list of Slack channels, we're not 100% silo'ing ourselves by how we organize our communication by function. A few of the channels, such as , are setup to talk about the big picture. But these channels are often detached from the actual work being done and are often neglected. #product So we're going to try reorganizing a few of our Slack channels to hopefully inspire more user-centric discussion and hopefully break down a few of our self imposed silos. 1. We're removing a few channels such as , , and . No more watering holes for people to organize purely based on their function. #design #frontend #backend 2. We'll introduce and phase out channels based on bigger cross-functional milestones. For example, we're working on annotations functionality and have a temporary channel. This brings together designers, developers, marketers, and whoever else is interested in contributing. This gets people talking about the problem we're trying to solve. #annotations 3. We're changing up how we think about the channel to make it more of a central focus for everyone on the team. To achieve this, we're introducing a few new product channels that more closely map to our development process. 👇👇👇 #product Our development process is a funnel, not a roadmap Instead of building a timeline of things we plan to build, we've got a funnel. At the top, we've got a list of things we're thinking about building. The middle is for various stages of projects in progress. And the bottom is for deploying projects into the wild. Here are the current stages and the associated Slack channels: At this stage, we're just talking about the product. Discussion should inspire ideas about things we can do to better solve problems for our users. Discussion Stage: #product When we've developed a theory about something that has the potential to improve Hacker Noon, We post and pin an idea in this channel for further discussion. At this stage, 3 things can happen. Idea Stage: #product-ideas We immediately decide to build it. This usually happens because the value is clear and we know what needs to happen to make it a reality. In this case we fast track it past the next stage and jumps to the . Delivery Stage We decide the idea isn't worth investing in right now. We think the idea is valuable but needs to be validated before we invest energy building it. In this case, it moves to the . Discovery Stage This is for ideas we're actively exploring. Here we'll usually prototype concepts to share with the team or users. Once we're confident that a design or prototype is worth building, we'll created a pinned post in the channel. This thread should include all the deliverables needed to move onto the next stage. Discovery Stage: #product-opportunities #product-opportunities This is where active development work is happening to either introduce new features or make changes to existing features. Once a change is complete and in production, we'll add a post to the channel so everyone is aware of what is changing. Delivery Stage: #product-progress #product-progress Once we deliver a feature/change that we want to track, we should create a pinned thread in that details what we'd like to learn from the change. Maybe we're interested in seeing how the change impacts engagement, we might want to monitor cost/performance, or maybe we'd like to get qualitative feedback from users. Results Stage: #product-results #product-results Conclusion A lot of people view Slack as a distraction that just gets in the way of real work from getting done. It certainly can have that effect if you aren't careful. Slack can also be a tool that reinforces silos and discourages collaboration. Slack can also be an invaluable tool that helps people work together to bring ideas to life. It's just not possible to get the same level of communication through emails, meetings, and other traditional means. A little organization along with a little discipline can go a long way.

Keeping Our Ducks Aligned With Slack

Intro Nearly all markets at some point go through a bubble. But not all bubbles are the same, and some of them tend to get more attention due to various events, hype or the level of a potential impact on the global economy. Just for a perspective, at some point of their development, the following stocks had a significant drop in value: GOPRO (GoPro): -95%, FIT (FitBit): -92%; LC (LendingClub): -91%; SNAP (most known as a creator of Snapchat): -83%; ZNGA (Zynga): -77%; TWTR (Twitter): -63%; SPOT (Spotify): -48%; DOCU (Docusign): -45%; FB (Facebook): -42%. Perhaps the most conspicuous analogy of an infamous crypto crash is the dot-com bubble. Crypto market cap fell by 80% to its high, while Nasdaq Composite Index’s fell by 78% during the dot-com crash. Other similarities include explosive growth and grandiose expectations of the capabilities of underlying technologies. Does this mean that crypto market is following the pattern of the dot-com bubble? Indeed, the dot-com bubble and the hypothetical crypto bubble share many striking similarities. Introduction Dot-com In the early 1990s, the internet was fast emerging and by mid-1990s a rapid increase in the households computer ownership rose from 15% to 35%. The sense of the “next big thing” incentivized the launch of internet-based companies met with significant injections of investments thanks to the low interest rates. Crypto In the early 2010s, bitcoin and its underlying technology blockchain were fast emerging. A few years later, increasing publicity, a rush to make a quick fortune, and the idea of a decentralized and free-of-the-government-involvement financial system incentivized the launch of many blockchain-based companies, met with significant injections of investments thanks to the economic stability in some countries and the lack of thereof in others. Investment FOMO Dot-com Adding .com to a company’s name significantly increased the companies’ valuations. Most of these companies didn’t have profits, but pure speculation and a lack of a robust fundamental basis led to their significant overvaluation and the interest of the investors sensing the ‘next big thing’. Crypto Adding ‘crypto’ or ‘blockchain’ words to a company’s name significantly the companies’ valuations. Most of these companies didn’t have a product, robust business model or profits. However, pure speculation and a lack of a robust fundamental basis led to their significant overvaluation and the interest of the investors sensing the ‘next big thing’. increased IPO and ICO IPO: Dot-com As the bubble grew, Investment banks got involved, profiting greatly from initial public offerings (IPO) and subsequently, touting further investment. ICO: Crypto As the bubble grew, the coin issuance companies got involved, profiting greatly from initial coin offerings (ICO) that resulted in 8.7bn in total funding. Peak Dot-com Many people had started trading full time and investors were turning into millionaires overnight. Between 1995 and 2000, the Nasdaq composite stock market index rose 400 to an all-time reaching the value of over in March of 2000. % $6 trillion Crypto Between 2016 and 2017, the price of bitcoin and many other coins kept rising, and by the end of 2017 the Bitcoin price rose to $19k. Many investors started trading full time and turning into millionaires overnight. Bubble Burst Dot-com Expectations were set high, the market was too excited, while many of the dot-coms were unable to come up with sustainable business models to help them prove at least some correlation between companies’ valuations and the invested funds. The dot-com bubble burst happened in March 2000, shortly after the Nasdaq index posted its high of 5048 points. This was followed by sell-offs of the stocks by large tech firms such as Intel, Dell, and Cisco causing a public panic. Crypto Expectations were set high, the market was too excited, while many of the blockchain companies were unable to develop sustainable business models which would help prove at least some correlation between companies’ valuations and the invested funds. The crypto bubble burst in December 2017, shortly after the Bitcoin price surpassed $19k. This was the breaking point for selling off the bitcoin and other crypto holdings by many investors, causing even more panic. Sequel Dot-com Within the 2-year period after the burst, the Nasdaq composite dropped from 5048.62 points to 1114.11 points, equal to 77% and a disappeared $5 trillion worth of investments. Hundreds of companies liquidated what little capital they had left, and closed by 2004. 48% of companies managed to continue their operations. Some of those that managed to stay afloat eventually surpassed their original market caps. Among those are Amazon and Google. Crypto Hundreds of companies liquidated what little capital they had left, and closed by 2019. Only some of the companies managed to continue their operations. Some of them were met with regulatory accusations. Companies that managed to stay afloat could potentially surpass their original market caps. New players are entering the industry. What’s common: dot-com & Crypto According to Morgan Stanley report, cryptocurrency price chart and Nasdaq index chart indeed correlate. During both of these historical events, the eagerness to make quick monetary rewards and the excitement for new disruptive technology fuelled a FOMO (fear of missing out)-based investments and the eventual high drops by 80%. Post-Bubble Dot-com In December 1999, Amazon‘s stock price hit its first and the only one for the upcoming decade, peak of $107, followed by a massive drop of ~90% to ~$6 in about a year. It took almost a decade to reach its previous highs. Today, AMZN’s price is at $1,950, which is 32000% growth from its lows $6. Crypto Following the crash and till now, the hype has fallen down and speculation got to the normal levels. Meanwhile, the companies are developing the technology and launching new products while regulators are working out the regulatory mechanisms of the industry. All these advancements lead to a slow but sure adoption. A crypto market leader Bitcoin (BTC) is currently trading at just over $5,000, down -75% from its all-time high of around $19,665 in December 2017. If we go ahead and draw a straight parallel line between the performance of these market leaders, we can predict an astonishing future for Bitcoin. Assuming we take the Bitcoin’s lowest point after all highs at $3,288.45, the AMZN’s ~32000% growth would take us to around $1,052,304 per Bitcoin. Regardless of how realistic this price point is, this dot-com comparison offers a point of view that we should consider. However, it is important to note that blindly comparing the price of one of the dot-com market leaders to Bitcoin would be immature. Is This Important? While this comparison offers an interesting and a potentially possible point of view on the future of Bitcoin and the blockchain industry, an output of any endeavor, be it new technology, a new type of currency or a completely new industry, and its value have to eventually align. Among success factors are efficiency/ technological robustness, market adoption, network effects, the scale of its impact on economies and industries, team, and a community. The scope of a provided value will determine Amazons and Googles of the blockchain industry. In the meantime, while Bitcoin is going through continuous improvements, we may very well see new market players entering the gameboard with the only desire to get the crown.

How Irrational Exuberance aligned Dot-Com and Crypto bubbles.

Authors:
(1) Rafael Kuffner dos Anjos;
(2) Joao Madeiras Pereira. Authors: Authors: (1) Rafael Kuffner dos Anjos; (2) Joao Madeiras Pereira. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Work and 2.1 Virtual avatars 2 Related Work and 2.1 Virtual avatars 2.2 Point cloud visualization 2.2 Point cloud visualization 3 Test Design and 3.1 Setup 3 Test Design and 3.1 Setup 3.2 User Representations 3.2 User Representations 3.3 Methodology 3.3 Methodology 3.4 Virtual Environment and 3.5 Tasks Description 3.4 Virtual Environment and 3.5 Tasks Description 3.6 Questionnaires and 3.7 Participants 3.6 Questionnaires and 3.7 Participants 4 Results and Discussion, and 4.1 User preferences 4 Results and Discussion, and 4.1 User preferences 4.2 Task performance 4.2 Task performance 4.3 Discussion 4.3 Discussion 5 Conclusions and References 5 Conclusions and References 2 RELATED WORK In this section we present and discuss the related work regarding user representation. First, we introduce and define virtual avatars and concepts associated. Following, a brief review of point cloud visualization techniques is discussed, and their use and viability in Virtual Reality setups 2.1 Virtual avatars An important part of the experience is how users are represented on the virtual scene. As opposed to CAVE-like systems, the use of Head-Mounted Display technology occludes users’ real self, compromising the overall virtual-reality session. A way of overcoming this problem is by using a fully-embodied representation of the user within the virtual environment [31]. A virtual body can supply them with a reference of recognizable size and a connectedness to the virtual environment [13, 26], even though studies indicate that the use of a virtual body setups may still cause distance underestimation [24]. The feeling of presence is related to the concept of proprioception, which is the ability to sense stimuli arising within the body regarding position, motion, and equilibrium. The sense of embodiment into an avatar is constitutive of the sense of presence in virtual reality (VR) and affects the way one interacts with virtual elements [16]. This concept is subdivided in three components: the sense of agency, i.e. feeling of motor control over the virtual body; (ii) the sense of body ownership, i.e. feeling that the virtual body is one’s own body; and (iii) self-location, i.e. the experienced location of the self. The level of realism of the avatar also plays an important part on the VR experience and how it relates to the sense of embodiment of an user. A common problem on this matter is the uncanny valley [21], which states that the acceptability of an artificial character will not increase linearly in relation to its likeness to human form. Instead, after an initial rise in acceptability there will be a pronounced decrease when the character is similar, but not identical to human form. Additionally, Piwek et al.[22] state that the effect of realism in the deepest part of the valley become more acceptable when it is animated. Works by Lugrin et al. [19, 20] also state that the uncanny valley also affect the feeling of presence and embodiment of avatars in first person perspective (1PP) when viewed through a head-mounted display. Another possibility when using a self-embodied avatar of the user is changing the perspective which the avatar is viewed. This approach is normally used on video-games to increase user’s spatial awareness when navigating and interacting on the scene. The sense of body ownership is also possible when using artificial bodies (in real scenarios) and avatars (in virtual environment scenarios) in immersive setups. A classical extra-corporeal experience is known by Rubber Hand Illusion (RHI) [5]. In this illusion, a subject is made to believe a rubber hand is in fact his own hand, which is hidden from view, to the point of pulling his own hand away if the rubber hand is attacked. This illusion has similar effects in Virtual Reality setups, which is called Virtual Hand illusion, and can be induced by visuotactile [30] and visuomotor synchrony [29, 34]. The Rubber-hand Illusion has also proven to work with full-body embodiment. Ehrrson et al. [9] proves this by streaming a the image of the body of the participant with an image of his body in a third-person perspective using an stereoscopic camera. Leggenhager et al. [18] confirms this by using a similar setup to prove that when using a Third-person perspective behind users bodies, users felt to be located there they saw the virtual body to be. In VR, the usage of orthogonal third person viewpoints has been explored and was for instance recommended to help setting the posture of a motion controlled virtual body [6]. Further work by Salamin et al. use an augmented-reality setup with a displaced camera and an HMD to show that the best perspective depends on the performed action: first-person perspective (1PP) for more precise object manipulations and third-person perspective (3PP) for moving actions. Work by the same work also shown that the users preferred the use of the 3PP in comparison with 1PP and needed less training in a ball catching scenario [28]. Further work by Kosch et al. [17], find that the preferred viewpoint in a 3PP is behind user’s head, providing a real life third person experience. Distance underestimation is also present when the avatar is seen on a third person perspective [28]. 2.2 Point cloud visualization The main challenge when dealing with point-cloud visualization is the unstructured nature of the data and its sparsity. Rendering point clouds with point primitives has several drawbacks when compared to other techniques (e.g., background/foreground confusion, loss of definition on close-ups), when confronting a low resolution scenario [1]. Katz et. al [14] solved the problem of background foreground confusion by estimating the direct visibility of sets of points. However, in a mixed visualization scenario such as the one applied on this work, confusion still exists between the rendered points and for the body and the mesh-based environment. Surface reconstruction is the standard approach to visualize point cloud data [10] with several successful techniques estimating the original surfaces from point sets [12, 15]. A single depth stream can be easily remeshed using delaunay triangulation [11], or multistream fusion can be performed such as shown in the work of Dou et al. [8]. While single stream triangulation can be performed in real time, multi stream fusion can be a very consuming task that requires specialized hardware for processing data. Screen-aligned splats [33] have been proposed as a more efficient alternative to polygonal mesh rendering [27], and are easily implemented in an interactive system, being the to go approach for visualization of real time data. Authors claim to have a comparable visual appearance to closed surfaces for visualization uses [4]. Although surface aligned splats [23, 3, 35] which create a better approximation of the surface, normal estimation in real-time can be also a costly operation. Splatting has been used in the past for point cloud visualization of environments [2], but not in a real time reconstruction of the users body. 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

How Your Avatar Shapes Your Virtual Reality Experience

Meet SNATIKA, Winner of HackerNoon's Startups of The Year 2024 in Training And Consulting

Most people talk about the tokenization of real-world assets as a theory. Christopher Kelly is turning it into a global financial operating system. As Co-Founder and President of droppGroup, Kelly is helping build what could become the most significant shift in capital markets since securitization - a new asset class powered by tokenized real-world assets (RWAs) - backed by infrastructure, deployed across sovereigns and connected to citizen level impact. He’s not selling hype; he’s engineering precision While most of the industry is still chasing proof of concepts, Kelly is building something different - a financial framework that merges the liquidity of DeFi with the institutional rigor of TradFi and ties it all to tangible, real-world value. Call it financial mobility, built on top of droppOne - droppGroup’s quantum-resilient, AI-integrated blockchain platform. But Kelly’s version of mobility isn’t about speculation. It’s about balance sheets, syndication and capital that behaves with transparency and accountability. Tokenizing More Than Assets Kelly’s work is not just about digitizing real estate or infrastructure, it’s about reengineering how governments and corporations unlock dead balance sheet capital and turn it into a living, programmable asset class. With droppGroup, Kelly is creating a system where nations can tokenize everything from energy reserves to housing developments and syndicate that value across regulated compliant, automated networks. These aren’t just smart contracts. These are financial instruments with yield, risk profiles, compliance rails and embedded impact logic. It’s the hyper-syndication of private credit, structured for liquidity, engineered for transparency. “We’re a technology company that creates balance sheet liquidity,” Kelly says. “And we do it by turning locked value into programmable capital with built-in purpose.” The Saudi Aramco Example One of the clearest demonstrations of Kelly’s financial vision in action is droppGroup’s work with Saudi Aramco - the world’s largest energy company. Under a single-source agreement, droppGroup deployed droppOne to tokenize Aramco’s human capital, mapping skills, talent and institutional knowledge into digital assets that enable instant, automated rewards for employees based on performance and contribution. This wasn’t about headlines. It was about turning Aramco’s intangible assets into financial-grade instruments and setting a precedent for how enterprise assets could evolve into programmable, tradable instruments. From Structured Derivatives to Structured Sovereigns Kelly’s credibility is earned. He comes from the inside. A former investment banker with Goldman Sachs and Credit Suisse, Kelly specialized in structured derivatives - complex, multi-layered financial instruments that require precision, risk management and creativity. That foundation gave him a unique vantage point, he understood the flaws of traditional capital formation, but also the architecture that makes it work. After leaving banking, he advised on large-scale commodity and infrastructure projects across West Africa and the Caribbean, navigating government level negotiations, capital markets and real-world execution. Today, he’s using that playbook to build next-generation finance, with the goal of transforming tokenization from a niche curiosity into a universal liquidity protocol for governments and global enterprises. A Company Built for Profit, Not Permission The AI and Web3 industries are still flooded with speculative burn rates and inflated valuations, droppGroup stands apart - profitable, deployed and scaling across continents. That’s not just due to engineering. It’s Kelly’s financial architecture. While companies like OpenAI have raised tens of billions, droppGroup has raised 100x less, yet delivers a deeper, more embedded enterprise AI and tokenization business than any of its peers. Through strategic capital discipline and sovereign-grade partnerships, droppGroup now operates in the USA, Saudi Arabia, Qatar, Bermuda and Colombia, serving governments, Fortune 500 companies and financial institutions across key global markets. The result is an infrastructure company that doesn’t just promise transformation - it delivers it. A New Language of Capital In Kelly’s world, the future of finance is modular, measurable and mission-aligned. He sees a world where a city can tokenize affordable housing, where a green energy plant can syndicate yield directly to a tokenized capital market and where social value is no longer a report, but a real-time metric embedded in the flow of capital. “We’re not just moving money faster. We’re making it more accountable,” he says. “And we’re doing it without asking permission from the old gatekeepers.” Building the Financial Engine for the Machine Economy As AI agents begin to transact, negotiate and settle contracts in real time, Kelly believes financial infrastructure must evolve with them. That’s what droppOne enables. Through tokenized assets, programmable liquidity and multi-agent coordination, it becomes the foundation not just for sovereign finance, but for autonomous capital systems that are intelligent, responsive and equitable. If others are still asking what tokenization can be, Christopher Kelly is already deploying the answer. And it’s changing how the world values everything. Most people talk about the tokenization of real-world assets as a theory. Christopher Kelly is turning it into a global financial operating system. Christopher Kelly As Co-Founder and President of droppGroup , Kelly is helping build what could become the most significant shift in capital markets since securitization - a new asset class powered by tokenized real-world assets (RWAs) - backed by infrastructure, deployed across sovereigns and connected to citizen level impact. droppGroup tokenized real-world assets He’s not selling hype; he’s engineering precision While most of the industry is still chasing proof of concepts, Kelly is building something different - a financial framework that merges the liquidity of DeFi with the institutional rigor of TradFi and ties it all to tangible, real-world value. Call it financial mobility, built on top of droppOne - droppGroup’s quantum-resilient, AI-integrated blockchain platform. But Kelly’s version of mobility isn’t about speculation. It’s about balance sheets, syndication and capital that behaves with transparency and accountability. Tokenizing More Than Assets Tokenizing More Than Assets Kelly’s work is not just about digitizing real estate or infrastructure, it’s about reengineering how governments and corporations unlock dead balance sheet capital and turn it into a living, programmable asset class. With droppGroup, Kelly is creating a system where nations can tokenize everything from energy reserves to housing developments and syndicate that value across regulated compliant, automated networks. These aren’t just smart contracts. These are financial instruments with yield, risk profiles, compliance rails and embedded impact logic. It’s the hyper-syndication of private credit, structured for liquidity, engineered for transparency. “We’re a technology company that creates balance sheet liquidity,” Kelly says. “And we do it by turning locked value into programmable capital with built-in purpose.” The Saudi Aramco Example The Saudi Aramco Example One of the clearest demonstrations of Kelly’s financial vision in action is droppGroup’s work with Saudi Aramco - the world’s largest energy company. Saudi Aramco Under a single-source agreement, droppGroup deployed droppOne to tokenize Aramco’s human capital, mapping skills, talent and institutional knowledge into digital assets that enable instant, automated rewards for employees based on performance and contribution. This wasn’t about headlines. It was about turning Aramco’s intangible assets into financial-grade instruments and setting a precedent for how enterprise assets could evolve into programmable, tradable instruments. From Structured Derivatives to Structured Sovereigns From Structured Derivatives to Structured Sovereigns Kelly’s credibility is earned. He comes from the inside. A former investment banker with Goldman Sachs and Credit Suisse , Kelly specialized in structured derivatives - complex, multi-layered financial instruments that require precision, risk management and creativity. Goldman Sachs Credit Suisse That foundation gave him a unique vantage point, he understood the flaws of traditional capital formation, but also the architecture that makes it work. After leaving banking, he advised on large-scale commodity and infrastructure projects across West Africa and the Caribbean, navigating government level negotiations, capital markets and real-world execution. Today, he’s using that playbook to build next-generation finance , with the goal of transforming tokenization from a niche curiosity into a universal liquidity protocol for governments and global enterprises. next-generation finance universal liquidity protocol A Company Built for Profit, Not Permission A Company Built for Profit, Not Permission The AI and Web3 industries are still flooded with speculative burn rates and inflated valuations, droppGroup stands apart - profitable, deployed and scaling across continents. That’s not just due to engineering. It’s Kelly’s financial architecture. While companies like OpenAI have raised tens of billions, droppGroup has raised 100x less, yet delivers a deeper, more embedded enterprise AI and tokenization business than any of its peers. Through strategic capital discipline and sovereign-grade partnerships, droppGroup now operates in the USA , Saudi Arabia, Qatar, Bermuda and Colombia , serving governments, Fortune 500 companies and financial institutions across key global markets. The result is an infrastructure company that doesn’t just promise transformation - it delivers it. USA Saudi Arabia, Qatar, Bermuda and Colombia A New Language of Capital A New Language of Capital In Kelly’s world, the future of finance is modular, measurable and mission-aligned. He sees a world where a city can tokenize affordable housing, where a green energy plant can syndicate yield directly to a tokenized capital market and where social value is no longer a report, but a real-time metric embedded in the flow of capital. “We’re not just moving money faster. We’re making it more accountable,” he says. “And we’re doing it without asking permission from the old gatekeepers.” Building the Financial Engine for the Machine Economy As AI agents begin to transact, negotiate and settle contracts in real time, Kelly believes financial infrastructure must evolve with them. That’s what droppOne enables. Through tokenized assets, programmable liquidity and multi-agent coordination, it becomes the foundation not just for sovereign finance, but for autonomous capital systems that are intelligent, responsive and equitable. autonomous capital systems If others are still asking what tokenization can be, Christopher Kelly is already deploying the answer. And it’s changing how the world values everything.

Inside Christopher Kelly’s Mission to Redesign Global Finance from the Ground Up

በ Christopher Kelly ውስጥ የዓለም ኢንቨስትመንት ከ Ground Up ይመዝገቡ

Innerhalb von Christopher Kellys Mission, globale Finanzen aus dem Ground Up neu zu gestalten

La misión de Christopher Kelly para rediseñar las finanzas globales desde el fondo

クリストファー・ケリー「グローバル・ファイナンスをグローバル・アップから再設計するミッション」

Christopher Kelly- ის მიზნით გლობალური ფინანსების დიზაინი Ground Up-დან

In de missie van Christopher Kelly om wereldwijde financiën te herontwerpen van de Ground Up

په کور کې د کریستوفر کیلی د نړیوالو مالیاتو د Ground Up څخه رامینځته کولو ماموریت

Миссия Кристофера Келли по переосмыслению глобальных финансов

ක් රිස්ටරෝපර් ක්ලිගේ මෙහෙයුමේ ඇතුළත ගෝලීය මූල් ය ව්යාපාරය Ground Up වලින් නැවත නිර්මාණය කිරීම

Sida loo yaqaan "Christopher Kelly's Mission to Redesign Global Finance from the Ground Up"

Ndani ya Ujumbe wa Christopher Kelly kurekebisha Fedha za Kimataifa kutoka kwa Ground Up

عالمی مالیاتی ڈیزائن کو Ground Up سے دوبارہ ڈیزائن کرنے کے کرسٹر کلی کی مشن کے اندر

Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Community Challenges Overview and 2.1 CCKS 2. Community Challenges Overview and 2.1 CCKS 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 3. Evaluation Tasks Overview and 3.1 Information Extraction 3. Evaluation Tasks Overview and 3.1 Information Extraction 3.2 Text Classification and Text Similarity 3.2 Text Classification and Text Similarity 3.3 Knowledge Graph and Question Answering 3.3 Knowledge Graph and Question Answering 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 4. Translational Informatics in Biomedical Text Mining 4. Translational Informatics in Biomedical Text Mining 5. Discussion and Perspective 5.1. Contributions of Community Challenges 5.1. Contributions of Community Challenges 5.2. Limitations of Current Community Challenges 5.2. Limitations of Current Community Challenges 5.3. Future Perspectives in the Era of Large Language Models, and References 5.3. Future Perspectives in the Era of Large Language Models, and References Figure Legends and Tables Figure Legends and Tables 5.2. Limitations of Current Community Challenges There are some limitations in current community challenge evaluation tasks on biomedical text mining. Firstly, there is a lack of representativeness of data in evaluation tasks. Biomedical and healthcare data possess sensitivity and privacy concerns, making it difficult to obtain largescale datasets. This results in many tasks using small or synthetic datasets, which may limit the representativeness and applicability. Data quality and annotation are also challenging, as the annotation of medical data are complex and requires high levels of expertise from annotators. For data types, many tasks only collect a single type of data. In the future, task organizer should consider incorporating data from multiple sources and modalities. Additionally, some datasets are restricted for use only during the evaluations and not made available afterward, limiting the impact of community challenge evaluation tasks. Secondly, the developed solutions may lack sufficient innovation and exhibit poor reproducibility. Some participants tend to apply established methods to achieve quick results, rather than exploring novel and innovative approaches. This can lead to a lack of innovation and diversity in methods, limiting further technical advancements. On the other hand, some algorithms may perform well on specific datasets but fail to generalize to others, reducing their broad applicability and reliability. To encourage innovation, future community challenges should emphasize the exploration of novel techniques and reward participants for their creativity. When integrating with existing systems, algorithm performance must be evaluated across multiple datasets and scenarios to ensure robustness and generalizability. Lastly, there exists a gap between evaluation tasks and applications in clinical practice. These tasks are generally abstracted from complex real-world problems and simplified to facilitate evaluation and comparison. However, such simplification may not reflect the complexity, diversity, and ambiguity of problems in real-world clinical settings. For example, several tasks focus on fundamental NLP tasks, such as medical information extraction and text classification, while more intricate challenges closely aligned with clinical practice are lacking. In real-world clinical practice, models always need to handle more noise and uncertainty, which may not have been fully considered in current evaluation tasks. Therefore, even systems that perform well in evaluation tasks may not be able to achieve similar results in practical applications. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv Authors:
(1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China;
(4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China;
(5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China;
(6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China;
(7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China;
(8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China;
(9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author. Authors: Authors: (1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China; (4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China; (5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China; (6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China; (7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China; (8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China; (9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author.

Limitations of Current Biomedical Text Mining Community Challenges

Partner Marketing is still a relatively new field. For a long time, it sat under Demand Gen or Growth — sometimes owned by whoever had capacity, sometimes a shared effort across departments. But in the last couple of years, that’s changed quickly. “Partnerships and Alliances” is now a formal revenue category in many companies, including startups. Most fast-growing tech businesses now have dedicated Partnerships teams, and increasingly, Partner Marketing is becoming one of the most strategic levers in Go-to-Market. Partner Marketing I’ve led Partner Marketing at a fast-scaling B2B company, growing the channel from zero to millions of euros pipeline and revenue over a year. This article shares how I built that (and learnings obtained along the way) — I will talk about the campaigns structure, mindset shifts, and cross-functional enablement that helped make it work. Start with ecosystem fit — not logo hype Start with ecosystem fit — not logo hype Start with ecosystem fit — not logo hype This is where most Partner Marketers go wrong from the start. They prioritise brand name over real alignment. Instead, begin by looking at your ICP and mapping your ecosystem around it. Ask: Who already sells to the same audience?


Who solves a different problem in the same buying journey?


Who has similar sales cycles and GTM motion? It’s tempting to chase big names, but if your buyers don’t overlap, you won’t see results — no matter how many co-branded assets you ship. Who already sells to the same audience? Who already sells to the same audience? Who solves a different problem in the same buying journey? Who solves a different problem in the same buying journey? Who has similar sales cycles and GTM motion? It’s tempting to chase big names, but if your buyers don’t overlap, you won’t see results — no matter how many co-branded assets you ship. Who has similar sales cycles and GTM motion? It’s tempting to chase big names, but if your buyers don’t overlap, you won’t see results — no matter how many co-branded assets you ship. Use data to prioritise projects, you won’t move far with guesswork Use data to prioritise projects, you won’t move far with guesswork Use data to prioritise projects, you won’t move far with guesswork Once you have a list of potential partners, it’s time to bring in the data. There are tools that integrate yours and partner’s CRMs and help  surfacing actual customer overlap, open opportunities, and exciting new prospects in the partner’s database. When I started prioritising partners based on real account data, it changed everything — campaign outcomes, partner relationships, internal buy-in. I stopped guessing who we should work with and started proving it. Build together or don’t bother (much) Build together or don’t bother (much) Build together or don’t bother (much) Here’s something I learned the hard way: if one side is doing all the work, it’s not a partnership — it’s outsourced content. If you want a campaign to perform, co-create it. That means: Building messaging together


Aligning on goals and follow-up


Sharing the lift across both teams
The best partners treat campaigns like internal launches. They loop in Sales, enable CS, share outcomes, and invest time. If they’re not up for that — it’s probably not worth your time either. Building messaging together Building messaging together Aligning on goals and follow-up Aligning on goals and follow-up Sharing the lift across both teams
The best partners treat campaigns like internal launches. They loop in Sales, enable CS, share outcomes, and invest time. If they’re not up for that — it’s probably not worth your time either. Sharing the lift across both teams The best partners treat campaigns like internal launches. They loop in Sales, enable CS, share outcomes, and invest time. If they’re not up for that — it’s probably not worth your time either. Move fast and learn as you go Move fast and learn as you go Move fast and learn as you go There’s no such thing as a perfect first campaign. My first partner GTM content was approved in a very short term as soon as the partnership was given a green light. We knew it wasn’t too polished, but we shipped it  — and used the feedback to tighten everything we did after. Momentum builds trust. Once Sales sees you’re doing things that bring them the engaged leads, the work you do will get more validation internally. Track revenue and pipeline, not just leads Track revenue and pipeline, not just leads Track revenue and pipeline, not just leads Forget about the leads. Shift your mind to: Pipeline sourced
Opportunities opened
But even if you are not measured on it, keep your eyes on: Revenue closed Pipeline sourced Opportunities opened But even if you are not measured on it, keep your eyes on: Revenue closed In my case, Partner Marketing was directly tied to Sales targets, not vanity metrics. This really helps for Leadership to care, for Marketing to lean in, for Sales to open up their time and resources. This led to this meme shared in our internal channel because interest in leveraging Partnerships internally was growing together with the numbers: Think of Partner Marketing as of an amplifier Think of Partner Marketing as of an amplifier Think of Partner Marketing as of an amplifier Partner Marketing doesn’t replace your Strategic Partnerships team — it supports and scales their work. It makes Partner Managers’ work not just about referral volume. A solid partner marketing motion helps you: Activate customers who aren’t showing intent signals yet;
Re-engage dormant accounts across both ecosystems;
Move from passive referrals to a structured GTM play. Activate customers who aren’t showing intent signals yet; Re-engage dormant accounts across both ecosystems; Move from passive referrals to a structured GTM play. But you need the right GTM playbook. If your partners sell to SMB, your campaigns will look very different from those targeting enterprise buyers with 18-months sales cycles. In those cases, you’ll need a shared ABM strategy and tight alignment between marketing and partnerships on content sequencing and touchpoints. But you need the right GTM playbook Cross-functional buy-in isn’t optional — it’s a must Cross-functional buy-in isn’t optional — it’s a must Cross-functional buy-in isn’t optional — it’s a must None of this works in a vacuum. To run Partner Marketing well, you need Sales, CS and Marketing on board. That means: Sales sees how you help source or accelerate deals;


CS understands how this impacts expansion and retention (and both CS and Sales give back, too, as Partnerships and Partner Marketing is about giving back to the Partner!);


Marketing is willing to resource campaigns — even when they didn’t own the original idea.
Sales buy-in is usually easier. They want warm leads and credible entry points into accounts. Marketing is the trickiest one from my own experience. Marketing is already running toward their own OKRs. Until your leadership team builds the target and attribution structure that doesn’t make teams to compete against each other, you’ll struggle to scale. It doesn’t mean you can’t take things in your own hands and challenge the status quo — using the data. Sales sees how you help source or accelerate deals; Sales sees how you help source or accelerate deals; CS understands how this impacts expansion and retention (and both CS and Sales give back, too, as Partnerships and Partner Marketing is about giving back to the Partner!); CS understands how this impacts expansion and retention (and both CS and Sales give back, too, as Partnerships and Partner Marketing is about giving back to the Partner!); Marketing is willing to resource campaigns — even when they didn’t own the original idea.
Sales buy-in is usually easier. They want warm leads and credible entry points into accounts. Marketing is the trickiest one from my own experience. Marketing is already running toward their own OKRs. Until your leadership team builds the target and attribution structure that doesn’t make teams to compete against each other, you’ll struggle to scale. It doesn’t mean you can’t take things in your own hands and challenge the status quo — using the data. Marketing is willing to resource campaigns — even when they didn’t own the original idea. Sales buy-in is usually easier. They want warm leads and credible entry points into accounts. Marketing is the trickiest one from my own experience. Marketing is already running toward their own OKRs. Until your leadership team builds the target and attribution structure that doesn’t make teams to compete against each other, you’ll struggle to scale. It doesn’t mean you can’t take things in your own hands and challenge the status quo — using the data. Final thoughts Final thoughts Partner Marketing works — but only when it’s treated as a function, not a favour. Done right, it creates leverage across your entire GTM engine. It helps you tap into warm networks, generate real pipeline, drive revenue, and build trust inside and outside the business. If you’re just starting, map your ICP, prioritise based on data, and get to your first campaign quickly. If you’re already running partner campaigns, ask yourself: are we aligned across functions, and are we tracking what really matters? Because when it clicks — it’s a channel like no other.

Partner Marketing Works Only If You Treat Is as a Function, and Not a Favor

We Thought It Was Fine I don’t remember exactly when the backlog started becoming a problem. Maybe it was the third time a stakeholder changed their mind about a request we’d already scoped. Or when we moved yet another story to the “parking lot” because no one could agree on whether we still needed it. Or maybe it was just the slow build-up of ideas, tickets, and half-baked items that never really went away. What I do know is that we ended up with a backlog full of... stuff. Some of it useful. Some of it once-relevant but now outdated. And some of it we were honestly too afraid to delete in case someone, somewhere, might come looking for it later. We didn’t think it was unmanageable at first. There weren’t hundreds of items—maybe around 90 or so. That seemed reasonable. But sprint planning became guesswork. Tickets would resurface that none of us remembered writing. Some stories lacked any context, others had no owner, and a few had ambiguous titles like “Optimize flow” or “Check alerts.” Developers started relying on Slack threads for real priorities instead of referencing the backlog. QA wasn’t sure what to expect next. The backlog was technically there, but nobody trusted it anymore. How It Spiraled The irony? We’d already cleaned it once. But the same clutter crept back in. We weren’t careless—we were trying to be helpful. A stakeholder would mention a feature, and we’d log it. Then they’d pivot, and we’d quietly move it down the list or tag it for “future consideration.” Designs changed. Priorities shifted. Some stories aged out without anyone noticing. And little by little, what was supposed to be a tool to guide delivery became a repository for indecision. What We Tried (That Actually Helped) We didn’t do a full reset. No dramatic purge or Jira bonfire. But we did start asking better questions. Why is this story still in the backlog? Do we know who it's for? If we built this tomorrow, would anyone care? What’s stopping us from deleting it? Sometimes we archived tickets. Other times, we rewrote them because there was still something valuable there—just not in the original form. And occasionally, reviewing a story revealed blockers or duplicated efforts we hadn’t noticed before. It wasn’t fast or flawless, but it helped. What We’re Still Learning Backlogs rarely fall apart overnight. It happens slowly. A couple of placeholder stories here. A few outdated ideas there.  Missed grooming sessions. Deferred decisions. Suddenly, you’re staring at a list no one fully understands. We’re still figuring it out, but a few changes made a difference: Archiving anything untouched for three months
Using a separate “idea board” for raw input
Requiring a clear owner and purpose before a ticket gets added
Accepting that backlog cleanup is a habit, not a one-time task Archiving anything untouched for three months Using a separate “idea board” for raw input Requiring a clear owner and purpose before a ticket gets added Accepting that backlog cleanup is a habit, not a one-time task Some weeks it looks clean and aligned. Other weeks, it starts slipping again. But now we catch it early—and course-correct as a team. Final Thought If your backlog feels bloated, unclear, or like a list of forgotten intentions, you’re not alone. You don’t have to fix it all today. But one small question might help get things moving again: “Are we actually using this the way we want to?” “Are we actually using this the way we want to?” That one question helped us reset. Still messy. Still learning. But the backlog is working again—and that’s what matters.

Here's Why Your Backlog Is Really Overloaded

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