ENTERINFI is an integrated, user-friendly platform based on blockchain for all visual, auditory, intelligence and imaginative requirements with ability to seamlessly transit from one another

ENTERINFI

Talks On Productivity: Evgeniya Malina - Head of Processes and Automation at Whizz 

Summer 2023 was a tough time for Web3 projects. Our company was bordering on breaking even with no ETA in sight. While we were looking for new possibilities and business ideas, we worked hard on developing existing products and services. In a volatile space, we had to work in a trial and error mode, with every new project having the potential to make or break the market. When There Is No Market Quite recently, I had a short but meaningful conversation with an IT business devil. I came in with a direct approach right off the bat, stating that my company provides security services for the blockchain market. "There is no blockchain market," was his response. He even elaborated, claiming that there’s a mobile devices market and a real estate market but no "blockchain market." Bold statement, but it gave me some food for thought. The mobile development market cap was , the EV market cap was around , and the wearables market cap was . There is plenty of room to play. But what is the blockchain market? According to CoinMarketCap, the global crypto market cap was about . However, the blockchain services and products market was just . $206.85 billion in 2022 $388 billion in 2023 $71.91 billion in 2023 $1.69 trillion in January 2024 $11.4 billion in 2022 First of all, there’s a huge difference between the asset cap and services cap. Second, if your startup is aiming to take 0.01% of a $206 billion market, it is aiming at $20.6 million. But then, even 0.1% of an $11 billion market is $11 million. Consider: You’re trying to take a 10x market share but gaining half the revenue. At the end of the day, $11.4 billion doesn’t come close to a big corporation number, and here we were trying to claim the existence of a whole market. Despite working in it for years, I had no other choice but to agree with the initial claim of the IT business expert. There are companies, projects, and startups, but they haven’t yet made a market. Making A Market If the market doesn’t exist, why bother, right? There are several already successful functioning and developing markets. And if you think about it, entering them does become easier in time. It’s cheaper, too, thanks to various technological leaps and the options to start from scratch and develop an advanced product. But in the end, we always see the same image: margin drops down to zero profitability. That, however, doesn’t apply to some restricted markets that exist solely based on monopolies. Working in an officially nonexistent space has its advantages. Everything is brand new, and as a founder, you make the rules. There also is a lucky chance event that can happen to a market that doesn’t exist: It can appear. If you still have doubts, you can look back at history. Every revolution, be it industrial or technological, kickstarted the development of not one but several dedicated markets. A company might start with 3% of nothing and grow to 3% of everything in no time, surpassing huge corporations in other fields. It might be a long-lasting success or just a flash, but at the end of the day, that’s how many success stories began. How To Approach A Nonexistent Market Whether a market is new or well-developed, success is impossible unless you try to achieve it. But I’m going to take this segment to talk about chickens. It’s no secret that hens are the point of interest for poultry farms. Roosters, however, often become meat as soon as they reach a required weight. Yet, in many cases, it's only possible to tell the sex of a chicken around the fifth or sixth week of their life. Before that, hens and roosters look identical. This brings massive expenses that go into feeding and maintaining about 50% of the birds, which are virtually useless for the farm. Surprisingly, the issue could be solved: Factories and farms have trained people who can identify a chicken’s sex with and only a day after the chicken is hatched. The best can process 1,000 chickens per hour, and what’s most incredible is that it’s a teachable skill. There’s no theory to that, just intuition and practice: After every attempt, a professional confirms or denies the results, and this happens until the student achieves the required accuracy. 98% accuracy A startup in a new market is similar to a chicken. Most founders attempt to identify its potential after six to 12 months of existence, even after investing large sums in launching the project. But there is another way. Like those chicken sex experts, a founder has to practice and train their intuition so that they eventually will be able to determine the perspectives and potential success of their startup. There is no logic to this; the circumstances change every day, and hard data comes in too late. So the only real skill is your gut feeling—that’s what founders should be training and developing. This skill is the only important and viable advantage for any founder. Conclusion There are two ways to conquer a market. A startup can disrupt the existing field with an innovative product or hope for a multiplier in a market that doesn’t yet exist. Either way, success isn’t guaranteed. So, the blockchain market, whether it’s already created and developed or just exists in our imaginations, can still be a fruitful field. Follow me on . Check out my . LinkedIn website

What To Do As A Startup Without A Market

একটি বাজার ছাড়া একটি স্টার্টআপ হিসাবে কি করতে হবে

Was tun als Startup ohne Markt?

Qué hacer como startup sin mercado

Que faire en tant que startup sans marché

बिना बाज़ार के स्टार्टअप के रूप में क्या करें?

市場のないスタートアップとして何をすべきか

시장이 없는 스타트업이 해야 할 일

O que fazer como uma startup sem mercado

Что делать стартапу без рынка

Pazarı Olmayan Bir Startup Olarak Ne Yapmalı?

Phải làm gì khi khởi nghiệp không có thị trường

初创企业没有市场该怎么办

When James Cameron first teased Terminator 2 back in the day, it was through a 90-second teaser that showed an automated robot factory pumping out endless rows of robots, ending with a shot of Arnold as the build process completed. Pure pulp fiction. Or was it? Fast forward to 2024, and we are now entering the era of the hyperfactory, where the main body of cars is autonomously assembled every 76 seconds. No, that’s not a mistype because Xaoimi, the smartphone OEM, has entered the electric vehicle arena with the SU7 and with it, a factory setup that is 91% automated with 400 robots armed with HD cameras and can operate in the dark. It reminds me of the time I spent on stage at the Big Data Expo in China with the chairman of Foxconn, and we debated the merits of running a smartphone factory with the lights off — because who needs lights when it’s just the robots running the show? The factory of the future will have only two employees, a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment.
— Warren Bennis Watching the keynote reveal is an eye-opening vision of the future of manufacturing but not in the way you think. “We have 269 welding machines to achieve 100% automated production and have the 36 robots to achieve 0.5 millimeters of assembly precision” “…industry leading seven axis coating robots with 70,000 RPM, it can make the paint coverage extremely fine balanced. This produces a natural flat and smooth finish..” “AMR robots that can replace forklifts/internal transport around the factory…” The best part is that the cars can then drive themselves off the factory line with the autopilot software that the company has introduced. In all, it’s a fascinating look at the future of car manufacturing. But there’s something else to consider. We are looking at the precursor of mass-produced, highly automated robot and drone production, something that I can’t help but compare to that dystopian movie. Because, let’s face it, everything is starting to point towards it. We have major AI players all rushing to give their hyperbolic algorithms some form of physical embodiment to contextually understand the world around them in a new dimension. The idea that military, DARPA, or even startup funding won’t find its way to a hyperfactory of this kind is ludicrous because they’ll be eyeing this up as a way to mass-produce killer drones and robotic tech in the blink of an eye if it means flooding the market with robotic slaves. One of the best (read: accurate) dystopian movies of the future to this day is Elysium by Neill Blomkamp, but even then, his vision of a robotic factory is forcing human labor to manufacture the military machines that take the piss on a daily basis. It just won’t be like that. It’s time to pay close attention to other industries for clues as to how stuff like Terminator or The Matrix could feasibly come true — our hubris in automating the human out of every job role and process will ultimately lead us to a path where automation can be easily retooled and reprogrammed to manufacture something else. And it won’t be a Roomba. When James Cameron first teased Terminator 2 back in the day, it was through a 90-second teaser that showed an automated robot factory pumping out endless rows of robots, ending with a shot of Arnold as the build process completed. Pure pulp fiction. Or was it? Fast forward to 2024, and we are now entering the era of the hyperfactory, where the main body of cars is autonomously assembled every 76 seconds. Fast forward to 2024, and we are now entering the era of the hyperfactory , where the main body of cars is autonomously assembled every 76 seconds. hyperfactory No, that’s not a mistype because Xaoimi, the smartphone OEM, has entered the electric vehicle arena with the SU7 and with it, a factory setup that is 91% automated with 400 robots armed with HD cameras and can operate in the dark. It reminds me of the time I spent on stage at the Big Data Expo in China with the chairman of Foxconn, and we debated the merits of running a smartphone factory with the lights off — because who needs lights when it’s just the robots running the show? It reminds me of the time I spent on stage at the Big Data Expo in China with the chairman of Foxconn, The factory of the future will have only two employees, a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment. — Warren Bennis The factory of the future will have only two employees, a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment. The factory of the future will have only two employees, a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment. — Warren Bennis — Warren Bennis Watching the keynote reveal is an eye-opening vision of the future of manufacturing but not in the way you think. keynote reveal keynote reveal “We have 269 welding machines to achieve 100% automated production and have the 36 robots to achieve 0.5 millimeters of assembly precision” “…industry leading seven axis coating robots with 70,000 RPM, it can make the paint coverage extremely fine balanced. This produces a natural flat and smooth finish..” “AMR robots that can replace forklifts/internal transport around the factory…” The best part is that the cars can then drive themselves off the factory line with the autopilot software that the company has introduced. In all, it’s a fascinating look at the future of car manufacturing. But there’s something else to consider. We are looking at the precursor of mass-produced, highly automated robot and drone production, something that I can’t help but compare to that dystopian movie. We are looking at the precursor of mass-produced, highly automated robot and drone production, something that I can’t help but compare to that dystopian movie. that dystopian movie. Because, let’s face it, everything is starting to point towards it. We have major AI players all rushing to give their hyperbolic algorithms some form of physical embodiment to contextually understand the world around them in a new dimension. The idea that military, DARPA, or even startup funding won’t find its way to a hyperfactory of this kind is ludicrous because they’ll be eyeing this up as a way to mass-produce killer drones and robotic tech in the blink of an eye if it means flooding the market with robotic slaves. The idea that military, DARPA, or even startup funding won’t find its way to a hyperfactory of this kind is ludicrous because they’ll be eyeing this up as a way to mass-produce killer drones and robotic tech in the blink of an eye if it means flooding the market with robotic slaves. One of the best ( read: accurate ) dystopian movies of the future to this day is Elysium by Neill Blomkamp, but even then, his vision of a robotic factory is forcing human labor to manufacture the military machines that take the piss on a daily basis. It just won’t be like that. read: accurate It’s time to pay close attention to other industries for clues as to how stuff like Terminator or The Matrix could feasibly come true — our hubris in automating the human out of every job role and process will ultimately lead us to a path where automation can be easily retooled and reprogrammed to manufacture something else. And it won’t be a Roomba.

Skynet Is Not the One You Should Be Fearing - Fear Your Favourite Car Manufacturer Instead

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Aleksandra Urman, She is a corresponding author from Department of Informatics, University of Zurich, Switzerland;
(2) Mykola Makhortykh, Institute of Communication and Media Studies, University of Bern, Switzerland;
(3) Roberto Ulloa, GESIS - Leibniz-Institut für Sozialwissenschaften, Germany;
(4) Juhi Kulshrestha, Department of Politics and Public Administration, University of Konstanz, Germany. Table of Links Abstract and Introduction
Web search results: biases, inaccuracies and their consequences
Conspiracy theories in the online environments
Research questions
Methodology
Results
Discussion
Limitations
Conclusion and Bibliography Methodology Data collection Agent-based audit setup. To collect the data we used agent-based algorithm impact auditing (see Ulloa et al., 2021). This type of auditing relies on automated agents, i.e., software that simulates user browsing behavior (e.g. scrolling web pages) and records the outputs. The benefit of this approach is that it allows controlling for search personalization (Hannak et al., 2013) and randomization (Makhortykh et al., 2020). Unlike human agents, automated agents can be easily synchronized (i.e., to isolate the effect of time at which the search actions are conducted) and deployed in a controlled environment (e.g., a network of virtual machines using the same IP range, the same type of operating system (OS) and the same browsing software) to limit the effects of personalization based on user-specific factors (e.g. location or OS type). Our approach is comparative in the sense that we assess the outputs of several SEs across multiple locations, time periods, and queries. To increase the robustness of our observations, the data were collected over two collection rounds: March 18-19 and May 8-9 2021. From the technical standpoint, the data collection was organized as follows: each agent was made of two browser plugins (for either Chrome or Firefox desktop browsers). The first plugin (the bot) simulated human activity in the browser, in our case opening the search engine page, entering a query and scrolling down the first page of search outputs. The second plugin (the tracker) recorded html content appearing in the browser and sent it to the remote server. The agents were deployed via Amazon Elastic Compute Cloud (EC2). We focused our exploration to the five biggest SEs by market share on desktop devices worldwide: Google, Bing, Yahoo, Yandex and DuckDuckGo (Desktop Search Engine Market Share Worldwide, n.d.). During the first round of data collection (March), we deployed 60 agents per location (see below), whereas for the second round we decreased this number to 30 agents per location because of budgetary limitations. The agents were equally distributed between the SEs (i.e., 12 agents per engine for the first round and 6 agents per engine for the second round). The majority of agents were able to perform their planned routine; the only major exception was Yandex, where multiple agents were blocked because of the aggressive bot detection mechanisms (e.g., frequent captchas) utilized by the search engine (hence, the absence of results for Yandex for some search queries). Search query selection. We have collected search results for six queries that correspond to specific conspiracy theories (“flat earth”, “new world order”, “qanon”) or to subjects related to conspiracy theories (“9/11”, “illuminati”, “george soros”). We specifically included these two groups of queries, because we suggest that they might be entered by users with two different intentions: those corresponding to the names of conspiracies are more likely to be entered by people already interested in a given theory, while the latter - by people merely interested in a certain topic. Thus if conspiratorial content is returned for the latter queries, it might lead to users’ incidental exposure to conspiracies. Further, we expect to observe discrepancies between the two groups of queries with more conspiratorial content returned for the queries corresponding to specific theories and less for the subjects which are surrounded by conspiracy theories. Location selection. We analyze the data collected for the five SEs, across three locations: two in the US (Ohio and California) and one in the UK (London). Our selection of locations is determined in part by the availability of different EC2 servers (see the description of technical implementation of the data collection below). Also, we utilized locations where English is the official language for the purposes of comparability - e.g., to make sure that any results we retrieve are due to the differences in the location, not to data voids in a specific language. Finally, we selected Ohio and California due to the differences in the ideological orientations of the two states (while California is a solid “blue” (Democratic) state in the US, Ohio is a “swing” state; we included it since there are no solid “red” states where EC2 servers are located); the inclusion of the UK server allows us to check whether our observations are country-specific. This comparative approach allows us to go beyond single-country observations that are common for algorithm audit studies (e.g., Haim et al., 2018; Puschmann, 2019; Urman et al., 2021a). Data analysis After the data were collected, we extracted all unique URLs that appeared on the first page of search results for each engine and search query. We have focused on the first page of search results since people tend to perceive top search results as more credible and rarely look at/click on the results beyond the first page (Pan et al., 2007; Schultheiß et al., 2018; Unkel and Haas, 2017; Urman and Makhortykh, 2021). In total, there were 375 such unique URLs collected. The content under these URLs was then manually coded by two trained coders with the disagreements between the two resolved through consensus coding. The coding involved two variables, broadly corresponding to the RQs: conspiracy-related stance and type of source. The conspiracy-related stance variable included the following categories: ● Debunks conspiracy: the content under the URL lists argument(s) why a conspiracy theory is not  true ● No mention of conspiracy: there are no mentions of conspiracy theories in the source at all ● Promotes conspiracy: the content under the URL lists argument(s) why a conspiracy theory is true ● Mentions conspiracy: a conspiracy theory is mentioned, but there is no clear stance associated - e.g., no arguments for it being true or false OR arguments for it being true or false are presented in equal shares. The type of source variable included the following categories: ● Reference website: e.g., online encyclopedias such as Wikipedia or Britannica ● Media: any media organization regardless of its ideological position or themes, except purely scientific news-focused sites (see the next category ● Science: scientific repositories such as JSTOR or news sites devoted exclusively to science such as Science News ● Social media: e.g., Facebook pages, YouTube videos or Twitter accounts ● Conspiracy website: a website dedicated to the promotion of one specific conspiracy or of an array of conspiracy theories, such as a website of the Flat Earth Society ● Other: all other websites that do not fit into any of the previous categories To assess the prevalence of conspiratorial content in search results (RQ1), we calculated the share of results for each stance towards conspiracy theories per condition (i.e., query, engine, location and collection round). To assess the prioritization of source types in relation to conspiracy content (RQ2), we first calculated the shares of results for each type per condition, and then the share of results with different stances towards conspiracy theories for each source type per location-round pair. This paper is available on arxiv under CC 4.0 license. Authors: (1) Aleksandra Urman, She is a corresponding author from Department of Informatics, University of Zurich, Switzerland; (2) Mykola Makhortykh, Institute of Communication and Media Studies, University of Bern, Switzerland; (3) Roberto Ulloa, GESIS - Leibniz-Institut für Sozialwissenschaften, Germany; (4) Juhi Kulshrestha, Department of Politics and Public Administration, University of Konstanz, Germany. This paper is available on arxiv under CC 4.0 license. Authors: (1) Aleksandra Urman, She is a corresponding author from Department of Informatics, University of Zurich, Switzerland; (2) Mykola Makhortykh, Institute of Communication and Media Studies, University of Bern, Switzerland; (3) Roberto Ulloa, GESIS - Leibniz-Institut für Sozialwissenschaften, Germany; (4) Juhi Kulshrestha, Department of Politics and Public Administration, University of Konstanz, Germany. Table of Links Abstract and Introduction Web search results: biases, inaccuracies and their consequences Conspiracy theories in the online environments Research questions Methodology Results Discussion Limitations Conclusion and Bibliography Abstract and Introduction Abstract and Introduction Web search results: biases, inaccuracies and their consequences Web search results: biases, inaccuracies and their consequences Conspiracy theories in the online environments Conspiracy theories in the online environments Research questions Research questions Methodology Methodology Results Results Discussion Discussion Limitations Limitations Conclusion and Bibliography Conclusion and Bibliography Methodology Data collection Data collection Agent-based audit setup. To collect the data we used agent-based algorithm impact auditing (see Ulloa et al., 2021). This type of auditing relies on automated agents, i.e., software that simulates user browsing behavior (e.g. scrolling web pages) and records the outputs. The benefit of this approach is that it allows controlling for search personalization (Hannak et al., 2013) and randomization (Makhortykh et al., 2020). Unlike human agents, automated agents can be easily synchronized (i.e., to isolate the effect of time at which the search actions are conducted) and deployed in a controlled environment (e.g., a network of virtual machines using the same IP range, the same type of operating system (OS) and the same browsing software) to limit the effects of personalization based on user-specific factors (e.g. location or OS type). Our approach is comparative in the sense that we assess the outputs of several SEs across multiple locations, time periods, and queries. Agent-based audit setup. To increase the robustness of our observations, the data were collected over two collection rounds: March 18-19 and May 8-9 2021. From the technical standpoint, the data collection was organized as follows: each agent was made of two browser plugins (for either Chrome or Firefox desktop browsers). The first plugin (the bot) simulated human activity in the browser, in our case opening the search engine page, entering a query and scrolling down the first page of search outputs. The second plugin (the tracker) recorded html content appearing in the browser and sent it to the remote server. The agents were deployed via Amazon Elastic Compute Cloud (EC2). We focused our exploration to the five biggest SEs by market share on desktop devices worldwide: Google, Bing, Yahoo, Yandex and DuckDuckGo (Desktop Search Engine Market Share Worldwide, n.d.). During the first round of data collection (March), we deployed 60 agents per location (see below), whereas for the second round we decreased this number to 30 agents per location because of budgetary limitations. The agents were equally distributed between the SEs (i.e., 12 agents per engine for the first round and 6 agents per engine for the second round). The majority of agents were able to perform their planned routine; the only major exception was Yandex, where multiple agents were blocked because of the aggressive bot detection mechanisms (e.g., frequent captchas) utilized by the search engine (hence, the absence of results for Yandex for some search queries). Search query selection. We have collected search results for six queries that correspond to specific conspiracy theories (“flat earth”, “new world order”, “qanon”) or to subjects related to conspiracy theories (“9/11”, “illuminati”, “george soros”). We specifically included these two groups of queries, because we suggest that they might be entered by users with two different intentions: those corresponding to the names of conspiracies are more likely to be entered by people already interested in a given theory, while the latter - by people merely interested in a certain topic. Thus if conspiratorial content is returned for the latter queries, it might lead to users’ incidental exposure to conspiracies. Further, we expect to observe discrepancies between the two groups of queries with more conspiratorial content returned for the queries corresponding to specific theories and less for the subjects which are surrounded by conspiracy theories. Search query selection. Location selection. We analyze the data collected for the five SEs, across three locations: two in the US (Ohio and California) and one in the UK (London). Our selection of locations is determined in part by the availability of different EC2 servers (see the description of technical implementation of the data collection below). Also, we utilized locations where English is the official language for the purposes of comparability - e.g., to make sure that any results we retrieve are due to the differences in the location, not to data voids in a specific language. Finally, we selected Ohio and California due to the differences in the ideological orientations of the two states (while California is a solid “blue” (Democratic) state in the US, Ohio is a “swing” state; we included it since there are no solid “red” states where EC2 servers are located); the inclusion of the UK server allows us to check whether our observations are country-specific. This comparative approach allows us to go beyond single-country observations that are common for algorithm audit studies (e.g., Haim et al., 2018; Puschmann, 2019; Urman et al., 2021a). Location selection. Data analysis Data analysis After the data were collected, we extracted all unique URLs that appeared on the first page of search results for each engine and search query. We have focused on the first page of search results since people tend to perceive top search results as more credible and rarely look at/click on the results beyond the first page (Pan et al., 2007; Schultheiß et al., 2018; Unkel and Haas, 2017; Urman and Makhortykh, 2021). In total, there were 375 such unique URLs collected. The content under these URLs was then manually coded by two trained coders with the disagreements between the two resolved through consensus coding. The coding involved two variables, broadly corresponding to the RQs: conspiracy-related stance and type of source. The conspiracy-related stance variable included the following categories: ● Debunks conspiracy: the content under the URL lists argument(s) why a conspiracy theory is not  true ● No mention of conspiracy: there are no mentions of conspiracy theories in the source at all ● Promotes conspiracy: the content under the URL lists argument(s) why a conspiracy theory is true ● Mentions conspiracy: a conspiracy theory is mentioned, but there is no clear stance associated - e.g., no arguments for it being true or false OR arguments for it being true or false are presented in equal shares. The type of source variable included the following categories: ● Reference website: e.g., online encyclopedias such as Wikipedia or Britannica ● Media: any media organization regardless of its ideological position or themes, except purely scientific news-focused sites (see the next category ● Science: scientific repositories such as JSTOR or news sites devoted exclusively to science such as Science News ● Social media: e.g., Facebook pages, YouTube videos or Twitter accounts ● Conspiracy website: a website dedicated to the promotion of one specific conspiracy or of an array of conspiracy theories, such as a website of the Flat Earth Society ● Other: all other websites that do not fit into any of the previous categories To assess the prevalence of conspiratorial content in search results (RQ1), we calculated the share of results for each stance towards conspiracy theories per condition (i.e., query, engine, location and collection round). To assess the prioritization of source types in relation to conspiracy content (RQ2), we first calculated the shares of results for each type per condition, and then the share of results with different stances towards conspiracy theories for each source type per location-round pair.

A Comparative Algorithm Audit of Conspiracies on the Net: Methodology

In the realm of technological innovation, Web3 represents a paradigm shift toward decentralized, peer-to-peer networks that aim to reshape the way we interact with the internet. However, widespread adoption is essential for Web3 to realize its full potential. In this article, we'll outline a roadmap for Web3 adoption and explore the key components needed to facilitate its mainstream integration. At the core of Web3 adoption, lies the need for robust infrastructure that supports decentralized applications (dApps) and protocols. This includes scalable blockchain platforms, interoperability solutions, decentralized storage networks, and secure identity systems. Projects like Ethereum, Polkadot, IPFS, and others play a crucial role in building the foundation upon which Web3 applications can thrive. Scalability also remains a significant challenge for blockchain networks, particularly as they seek to support a growing number of users and transactions. Layer 2 scaling solutions, such as sidechains, state channels, and rollups, are critical for increasing throughput and reducing congestion on the mainnet. Additionally, ongoing research into sharding, plasma, and other scalability techniques is essential for long-term sustainability. Coinweb is a new aggregator platform that aims to remove the confusion from crypto and Web3. With its comparisons and recommendations, you can make all the right Web3 moves. The platform aims to ensure that market participants can finally get all of the information they need while making it easy for users. Shawn Munir, Co-Founder and CEO, sat down with us to outline the vision for the project. 1. With so many market aggregators already in the industry, what makes Coinweb stand out? It is the world's first comparison platform that compares any product/service in web3 and answers questions in seconds. We are trying to revolutionize how people consume information online. Earlier, we were used to going to Google and entering keywords, and Google would give us ten blue links on the first page, and you open each of them and start reading. With Coinweb AI, we’re trying to build a future where you have the option to do both - traditional way of search + the Gen Z way of search. You can just come and ask a question like you would ask a friend, and the AI replies with the answer. But not just the answer—every sentence that it says has been verified by experts on our team that has a reference to it. We call this expert-verified content. We test and review exchanges and projects ourselves, adding valuable insights and actionable advice. 2. What major hurdles do you believe your platform will be looking to solve? There are two main issues at play in learning web3: information overload and misinformation. People are not experts or prompt engineers - they’re never going to be that. Even though it’s still an emerging space, there is far too much information to sift through when starting out. With so much information out there, a few bad actors benefit from you. This is a bigger issue in crypto. They lead consumers down the wrong path, which hurts mainstream adoption on multiple fronts. We’re reducing the time it takes to find answers from an hour to seconds and making sure our users make all the right moves. 3. What additional solutions is the team working on at the moment? We are currently building our flagship product called Coinweb Pro. It's your personal advisor on our site. When you ask a question, the “Advisor” will ask clarifying questions in a conversational tone so we can specifically answer the question. It's basically getting expanded interactively. The assistant will be trained on our expert knowledge base and provide clear, helpful advice for all levels of crypto learners. Instead of thinking about what to do, you will be told with market data and expertise so you can’t miss. 4. How do you believe adoption in Web3 will play out? I align with Larry Fink’s vision that all assets will eventually be tokenized. In terms of adoption, we are still far from the person in the streets to know what a DEX or Dogecoin is. While most companies focus on businesses, we’ll bridge the gap for consumers - which is an untapped market. 5. What about projects like metaverses and NFTs? Absolutely—we already cover more than 40 verticals in the industry, and metaverses, NFTs, and other projects come naturally into the Web3 space. We keep our readers up to date on the exciting NFT drops coming up on each blockchain, fun play-to-earn games to earn free NFTs, and the ways that blockchain intersects with other tech like AI and infrastructure. Conclusion: There are many who still firmly believe that Web3 is the future of the internet. And as the landscape continues to shift, it’s easy to see why. Web3 holds the promise of a completely decentralized and open internet, where everyone is free to operate and hold control of their data. That said, much work needs to be done to help this technology fulfill its potential. And as time goes on, we should see more development in the space. In the realm of technological innovation, Web3 represents a paradigm shift toward decentralized, peer-to-peer networks that aim to reshape the way we interact with the internet. However, widespread adoption is essential for Web3 to realize its full potential. In this article, we'll outline a roadmap for Web3 adoption and explore the key components needed to facilitate its mainstream integration. At the core of Web3 adoption, lies the need for robust infrastructure that supports decentralized applications (dApps) and protocols. This includes scalable blockchain platforms, interoperability solutions, decentralized storage networks, and secure identity systems. Projects like Ethereum, Polkadot, IPFS, and others play a crucial role in building the foundation upon which Web3 applications can thrive. Scalability also remains a significant challenge for blockchain networks, particularly as they seek to support a growing number of users and transactions. Layer 2 scaling solutions, such as sidechains, state channels, and rollups, are critical for increasing throughput and reducing congestion on the mainnet. Additionally, ongoing research into sharding, plasma, and other scalability techniques is essential for long-term sustainability. Coinweb is a new aggregator platform that aims to remove the confusion from crypto and Web3. With its comparisons and recommendations, you can make all the right Web3 moves. The platform aims to ensure that market participants can finally get all of the information they need while making it easy for users. Shawn Munir, Co-Founder and CEO, sat down with us to outline the vision for the project. 1. With so many market aggregators already in the industry, what makes Coinweb stand out? It is the world's first comparison platform that compares any product/service in web3 and answers questions in seconds. We are trying to revolutionize how people consume information online. Earlier, we were used to going to Google and entering keywords, and Google would give us ten blue links on the first page, and you open each of them and start reading. With Coinweb AI, we’re trying to build a future where you have the option to do both - traditional way of search + the Gen Z way of search. You can just come and ask a question like you would ask a friend, and the AI replies with the answer. But not just the answer—every sentence that it says has been verified by experts on our team that has a reference to it. We call this expert-verified content. We test and review exchanges and projects ourselves, adding valuable insights and actionable advice. 2. What major hurdles do you believe your platform will be looking to solve? There are two main issues at play in learning web3: information overload and misinformation. People are not experts or prompt engineers - they’re never going to be that. Even though it’s still an emerging space, there is far too much information to sift through when starting out. With so much information out there, a few bad actors benefit from you. This is a bigger issue in crypto. They lead consumers down the wrong path, which hurts mainstream adoption on multiple fronts. We’re reducing the time it takes to find answers from an hour to seconds and making sure our users make all the right moves. 3. What additional solutions is the team working on at the moment? We are currently building our flagship product called Coinweb Pro. It's your personal advisor on our site. When you ask a question, the “Advisor” will ask clarifying questions in a conversational tone so we can specifically answer the question. It's basically getting expanded interactively. The assistant will be trained on our expert knowledge base and provide clear, helpful advice for all levels of crypto learners. Instead of thinking about what to do, you will be told with market data and expertise so you can’t miss. 4. How do you believe adoption in Web3 will play out? I align with Larry Fink’s vision that all assets will eventually be tokenized. In terms of adoption, we are still far from the person in the streets to know what a DEX or Dogecoin is. While most companies focus on businesses, we’ll bridge the gap for consumers - which is an untapped market. 5. What about projects like metaverses and NFTs? Absolutely—we already cover more than 40 verticals in the industry, and metaverses, NFTs, and other projects come naturally into the Web3 space. We keep our readers up to date on the exciting NFT drops coming up on each blockchain, fun play-to-earn games to earn free NFTs, and the ways that blockchain intersects with other tech like AI and infrastructure. Conclusion: Conclusion: There are many who still firmly believe that Web3 is the future of the internet. And as the landscape continues to shift, it’s easy to see why. Web3 holds the promise of a completely decentralized and open internet, where everyone is free to operate and hold control of their data. That said, much work needs to be done to help this technology fulfill its potential. And as time goes on, we should see more development in the space.

A Roadmap For Web3 Adoption: What Is Needed?

Chaotic Links Theory: Exploring the Intersection of Classical Cryptography and Quantum Potentiality

This paper is under CC 4.0 license. available on arxiv Authors: (1) Zhe Liu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (2) Chunyang Chen, Monash University, Melbourne, Australia; (3) Junjie Wang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China & Corresponding author; (4) Mengzhuo Chen, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (5) Boyu Wu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (6) Zhilin Tian, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (7) Yuekai Huang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (8) Jun Hu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (9) Qing Wang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China & Corresponding author. Table of Links Abstract and Introduction Motivational Study and Background Approach Experiment Design Results and Analysis Discussion and Threats to Validity Related Work Conclusion and References 4 EXPERIMENT DESIGN 4.1 Research Questions • How effective of InputBlaster in detecting bugs related to text input widgets? RQ1: (Bugs Detection Performance) For RQ1, we first present some general views of InputBlaster for bug detection, and then compare it with commonly-used and state-of-the-art baseline approaches. • What is the contribution of the (sub-) modules of InputBlaster for bug detection performance? RQ2: (Ablation Study) For RQ2, We conduct ablation experiments to evaluate the impact of each (sub-) module on the performance. • How does our proposed InputBlaster work in real-world situations? RQ3: (Usefulness Evaluation) For RQ3, we integrate InputBlaster with the GUI testing tool to make it automatically explore the app and detect unseen inputrelated bugs, and issue the detected bugs to the development team. 4.2 Experimental Setup we crawl 200 most popular open-source apps from F-Droid [3], and only keep the latest ones with at least one update after September 2022 (this ensures the utilized apps are not overlapped with the ones in Sec 3.3). Then we collect all their issue reports on GitHub, and use keywords (e.g., EditText) to filter those related to text input. Finally, we obtain 126 issue reports related to 54 apps. Then we manually review each issue report and the mobile app, and filter it according to the following criteria: (1) the app wouldn’t constantly crash on the emulator; (2) it can run all baselines; (3) UIAutomator [65] can obtain the view hierarchy file for context extraction; (4) the bug is related to text input widgets; (5) the bug can be manually reproduced for validation; (6) the app is not used in the motivational study or example dataset construction. Please note that we follow the name of the app to ensure that there is no overlap between the datasets. Finally, 31 apps with 36 buggy text inputs remain for further experiments. For RQ1 and RQ2, We measure the bug detection rate, i.e., the ratio of successfully triggered crashes in terms of all the experimental crashes (i.e., buggy inputs), which is a widely used metric for evaluating GUI testing [8, 27, 43]. Specifically, with the generated unusual input, we design an automated test script to input it into the text input widgets, and automatically run the “submit” operation to check whether a crash occurs. If no, use the script to go back to GUI page with the input widget if necessary, and try the next generated unusual input. As long as a crash is triggered for a text input widget, we treat it as successful bug detection and will stop the generation for this widget. Note that our generated unusual input is not necessarily the same as the one provided in the issue report, e.g., -18 vs. -20, as long as a crash is triggered after entering the unusual inputs, we treat it as a successful crash detection. For a fair comparison with other approaches, we employ two experimental settings, i.e., 30 attempts (30 unusual inputs) and 30 minutes. We record the bug detection rate under each setting (denoted as “Bug (%)” in Table 2 to Table 5), and also record the actual number of attempts (denoted as “Attempt (#)”) and the actual running time (denoted as “Min (#)”) when the crash occurs to fully understanding the performance. we further evaluate the usefulness of InputBlaster in detecting unseen crash bugs related to text input. A total of 131 apps have been retained. We run Ape [26] (a commonly-use automated GUI testing tool) integrated with InputBlaster, for exploring the mobile apps and getting the view hierarchy file of each GUI page. For RQ3, We use the same configurations as the previous experiments. Once a crash related to text input is spotted, we create an issue report by describing the bug, and report them to the app development team through the issue reporting system or email. 4.3 Baselines Since there are hardly any existing approaches for the unusual input generation of mobile apps, we employ 18 baselines from various aspects to provide a thorough comparison. First, we directly utilize ChatGPT [58] as the baseline. We provide the context information of the text input widgets (as described in Table 1 P1), and ask it to generate inputs that can make app crash. Fuzzing testing and mutation testing can be promising techniques for generating invalid inputs, and we apply several related baselines. Feldt et al. [24] proposed a testing framework called GoldTest, which generates diverse test inputs for mobile apps by designing regular expressions and generation strategies. In 2017, they further proposed an invalid input generation method [55] based on probability distribution (PD) parameters and regular expressions, and we name this baseline as PDinvalid. Furthermore, we reuse the idea of traditional random-based fuzzing [13, 41], and develop a RandomFuzz for generating inputs for text widgets. In addition, based on the 50 buggy text inputs from the GitHub dataset in Section 3.3.1, we manually design 50 corresponding mutation rules to generate the invalid input, and name this baseline as ruleMutator. Furthermore, we include the string analysis methods as the baselines, i.e., OSTRICH [15] and Sloth [14]. They aim at generating the strings that violate the constraints (e.g., string length, concatenation, etc), which is similar to our task. OSTRICH’s key idea [15] is to generate the test strings based on heuristic rules. Sloth [14] proposes to exploit succinct alternating finite-state automata as concise symbolic representations of string constraints. There are constraint-based methods, i.e., Mobolic [8] and TextExerciser [27], which can generate diversified inputs for testing the app. For example, TextExerciser utilizes the dynamic hints to guide it in producing the inputs. We also employ two methods (RNNInput [43] and QTypist [44]) which aim at generating valid inputs for passing the GUI page. In addition, we use the automated GUI testing tools, i.e., Stoat [61], Droidbot [39], Ape [26], Fastbot [12], ComboDroid [67], TimeMachine [23], Humanoid [40], Q-testing [53], which can produce inputs randomly or following rules to make app running automatically. We design the script for each baseline to ensure that it can reach the GUI page with the text input widget, and run them in the same experimental environment (Android x64) to mitigate potential bias.

Leveraging LLMs for Generation of Unusual Text Inputs in Mobile App Tests: Experiment Design

HSBC, the banking giant, is finally entering the ring with its new app, Zing (launched in January 2024 in UK). It aims to disrupt the international money transfer space currently dominated by fintech players like Revolut and Wise. But is this a genuine challenge, or just a latecomer trying to play catch-up? The answer lies in the margins. Fintech companies have been steadily eroding traditional banks' profits with their user-friendly apps and competitive fees. James Allan, CEO of Zing, acknowledges this shift:
"It's time for a new kind of solution, one that combines cutting-edge tech with the trust of a global bank like HSBC." Is It a Smart Move for Younger Audience? Analysts see Zing as a strategic move for HSBC. Benjamin Toms of RBC believes it's a “defensive play” to attract younger, tech-savvy customers who might become lifelong HSBC clients. Unlike existing HSBC FX services, Zing is free to download for everyone. But, lemme clear one thing! Zing operates under the FCA as an e-money institution, not a bank. This means your deposits won't be protected under the Financial Services Compensation Scheme, something to consider before diving in. Despite these uncertainties, Zing's arrival signifies a critical shift in the financial world. As established institutions adapt and innovate, consumers stand to benefit from a more competitive international payments ecosystem. HSBC, however, has global aspirations for Zing. Nuno Matos, CEO of their wealth and personal banking division, added:
‘‘We want to become a leading platform for international payments, which aligns perfectly with HSBC's overall payments strategy. Expect to see Zing launching soon in Asia, the Middle East, and EU markets." This focus on innovation and trust is key for Zing. This will attract customers who value fintech apps’ convenience while seeking the security. Feature Comparison - HSBC’s Zing vs. Revolut & Wise Feature

HSBC’s Zing

Revolut

Wise



Primary Function

Foreign exchange & international money transfer

Multi-currency spending & international money transfer

International money transfer



Number of Currencies Supported

10

Over 140

Over 40



Debit Card

Yes (physical & virtual)

Yes (physical & virtual)

Yes (physical & virtual)



Fees

Conversion charges and currency exchange

Free standard plan (limited features), paid plans with higher limits & features

Transaction fees based on amount & currency



Focus

Simplicity & ease of use for occasional international transactions

Multi-functionality for everyday spending & travel

Cost-effective international money transfers Recruiting Top Talent for the Challenge To compete effectively, HSBC is building a strong team. They've recruited key personnel from their fintech rivals, like Neil McKeown (ex-Monzo) and Dario De Angelis (ex-Revolut), to leverage valuable industry expertise. Additionally, Eduardo Mercer, a software engineer veteran from Wise, strengthens Zing's technical core. This increased competition injects a healthy dose of competition into the European cross-border payments scene. Ultimately, consumers benefit from more options, potentially lower fees, and a continued push for innovative solutions in the international money transfer market. James Allan, CEO of Zing, says,
"It's a win-win for everyone who wants a simpler, faster, and more reliable way to manage their money internationally." Can Zing Outshine its Competitors? HSBC's strategic investments, focus on user experience, and global ambitions suggest they're serious about the game. Only time will tell if they can woo customers away from the current fintech champions. The battle for dominance in international money transfers has just become even more interesting. Potential Pros & Cons! Aspect

Potential Pros

Potential Cons



Brand Recognition

Leverages HSBC's established brand and reputation for security

May not have the same brand awareness as Revolut or Wise



User Experience

Focuses on user-friendliness for a smooth money transfer experience

Needs to prove its app is as intuitive and user-friendly as competitors



Global Reach

Ambitious plans for global expansion, offering services in new markets

Initial launch is limited to UK customers only



Team Expertise

Recruited top talent from fintech rivals, bringing industry knowledge

Needs to demonstrate its team can deliver a competitive product Key Takeaways from this New and Improved Competition! This head-to-head competition is a game-changer in the cross-border payments market, especially in UK. Here is what will you get: HSBC offers established banking security, but Revolut and Wise are known for their cutting-edge tech. Zing aims to bridge this gap, offering both trust and a tech-savvy experience.
With more options, fees may drop, and features may become more user-friendly. This may include faster transfers, better exchange rates, and a smoother overall experience.
This competition between big banks and fintech companies will benefit you the most. It can include a wider range of services, lower costs, and a constant push for innovation. Stay updated for more updates about the fintech industry! For now, share your thoughts in the comments. HSBC, the banking giant, is finally entering the ring with its new app, Zing (launched in January 2024 in UK). It aims to disrupt the international money transfer space currently dominated by fintech players like Revolut and Wise. But is this a genuine challenge, or just a latecomer trying to play catch-up? HSBC, the banking giant, is finally entering the ring with its new app, Zing (launched in January 2024 in UK). Zing The answer lies in the margins. Fintech companies have been steadily eroding traditional banks' profits with their user-friendly apps and competitive fees. James Allan, CEO of Zing, acknowledges this shift: "It's time for a new kind of solution, one that combines cutting-edge tech with the trust of a global bank like HSBC." James Allan, CEO of Zing, acknowledges this shift: "It's time for a new kind of solution, one that combines cutting-edge tech with the trust of a global bank like HSBC." "It's time for a new kind of solution, one that combines cutting-edge tech with the trust of a global bank like HSBC." Is It a Smart Move for Younger Audience? Is It a Smart Move for Younger Audience? Analysts see Zing as a strategic move for HSBC. Benjamin Toms of RBC believes it's a “ defensive play” to attract younger, tech-savvy customers who might become lifelong HSBC clients. Unlike existing HSBC FX services, Zing is free to download for everyone . defensive play” Zing is free to download for everyone But, lemme clear one thing! But, lemme clear one thing! But, lemme clear one thing! Zing operates under the FCA as an e-money institution, not a bank. This means your deposits won't be protected under the Financial Services Compensation Scheme, something to consider before diving in. Despite these uncertainties, Zing's arrival signifies a critical shift in the financial world. As established institutions adapt and innovate, consumers stand to benefit from a more competitive international payments ecosystem. HSBC, however, has global aspirations for Zing. HSBC, however, has global aspirations for Zing. HSBC, however, has global aspirations for Zing. Nuno Matos, CEO of their wealth and personal banking division, added: ‘‘We want to become a leading platform for international payments, which aligns perfectly with HSBC's overall payments strategy. Expect to see Zing launching soon in Asia, the Middle East, and EU markets." Nuno Matos, CEO of their wealth and personal banking division, added: ‘‘We want to become a leading platform for international payments, which aligns perfectly with HSBC's overall payments strategy. Expect to see Zing launching soon in Asia, the Middle East, and EU markets." ‘‘We want to become a leading platform for international payments, which aligns perfectly with HSBC's overall payments strategy. Expect to see Zing launching soon in Asia, the Middle East, and EU markets." This focus on innovation and trust is key for Zing. This will attract customers who value fintech apps’ convenience while seeking the security. fintech apps’ convenience Feature Comparison - HSBC’s Zing vs. Revolut & Wise Feature Comparison - HSBC’s Zing vs. Revolut & Wise Feature

HSBC’s Zing

Revolut

Wise



Primary Function

Foreign exchange & international money transfer

Multi-currency spending & international money transfer

International money transfer



Number of Currencies Supported

10

Over 140

Over 40



Debit Card

Yes (physical & virtual)

Yes (physical & virtual)

Yes (physical & virtual)



Fees

Conversion charges and currency exchange

Free standard plan (limited features), paid plans with higher limits & features

Transaction fees based on amount & currency



Focus

Simplicity & ease of use for occasional international transactions

Multi-functionality for everyday spending & travel

Cost-effective international money transfers Feature

HSBC’s Zing

Revolut

Wise Primary Function

Foreign exchange & international money transfer

Multi-currency spending & international money transfer

International money transfer Number of Currencies Supported

10

Over 140

Over 40 Debit Card

Yes (physical & virtual)

Yes (physical & virtual)

Yes (physical & virtual) Fees

Conversion charges and currency exchange

Free standard plan (limited features), paid plans with higher limits & features

Transaction fees based on amount & currency Focus

Simplicity & ease of use for occasional international transactions

Multi-functionality for everyday spending & travel

Cost-effective international money transfers Feature HSBC’s Zing Revolut Wise Feature Feature HSBC’s Zing HSBC’s Zing Revolut Revolut Wise Wise Primary Function Foreign exchange & international money transfer Multi-currency spending & international money transfer International money transfer Primary Function Primary Function Primary Function Foreign exchange & international money transfer Foreign exchange & international money transfer Multi-currency spending & international money transfer Multi-currency spending & international money transfer International money transfer International money transfer Number of Currencies Supported 10 Over 140 Over 40 Number of Currencies Supported Number of Currencies Supported Number of Currencies Supported 10 10 Over 140 Over 140 Over 40 Over 40 Debit Card Yes (physical & virtual) Yes (physical & virtual) Yes (physical & virtual) Debit Card Debit Card Debit Card Yes (physical & virtual) Yes (physical & virtual) Yes (physical & virtual) Yes (physical & virtual) Yes (physical & virtual) Yes (physical & virtual) Fees Conversion charges and currency exchange Free standard plan (limited features), paid plans with higher limits & features Transaction fees based on amount & currency Fees Fees Fees Conversion charges and currency exchange Conversion charges and currency exchange Free standard plan (limited features), paid plans with higher limits & features Free standard plan (limited features), paid plans with higher limits & features Transaction fees based on amount & currency Transaction fees based on amount & currency Focus Simplicity & ease of use for occasional international transactions Multi-functionality for everyday spending & travel Cost-effective international money transfers Focus Focus Focus Simplicity & ease of use for occasional international transactions Simplicity & ease of use for occasional international transactions Multi-functionality for everyday spending & travel Multi-functionality for everyday spending & travel Cost-effective international money transfers Cost-effective international money transfers Recruiting Top Talent for the Challenge To compete effectively, HSBC is building a strong team. They've recruited key personnel from their fintech rivals, like Neil McKeown (ex-Monzo ) and Dario De Angelis (ex-Revolut) , to leverage valuable industry expertise. Additionally, Eduardo Mercer , a software engineer veteran from Wise , strengthens Zing's technical core. Neil McKeown (ex-Monzo Dario De Angelis (ex-Revolut) Eduardo Mercer a software engineer veteran from Wise This increased competition injects a healthy dose of competition into the European cross-border payments scene. Ultimately, consumers benefit from more options, potentially lower fees, and a continued push for innovative solutions in the international money transfer market. cross-border payments James Allan, CEO of Zing, says, "It's a win-win for everyone who wants a simpler, faster, and more reliable way to manage their money internationally." James Allan, CEO of Zing, says, "It's a win-win for everyone who wants a simpler, faster, and more reliable way to manage their money internationally." "It's a win-win for everyone who wants a simpler, faster, and more reliable way to manage their money internationally." Can Zing Outshine its Competitors? Can Zing Outshine its Competitors? HSBC's strategic investments, focus on user experience, and global ambitions suggest they're serious about the game. Only time will tell if they can woo customers away from the current fintech champions. The battle for dominance in international money transfers has just become even more interesting. Potential Pros & Cons! Aspect

Potential Pros

Potential Cons



Brand Recognition

Leverages HSBC's established brand and reputation for security

May not have the same brand awareness as Revolut or Wise



User Experience

Focuses on user-friendliness for a smooth money transfer experience

Needs to prove its app is as intuitive and user-friendly as competitors



Global Reach

Ambitious plans for global expansion, offering services in new markets

Initial launch is limited to UK customers only



Team Expertise

Recruited top talent from fintech rivals, bringing industry knowledge

Needs to demonstrate its team can deliver a competitive product Aspect

Potential Pros

Potential Cons Brand Recognition

Leverages HSBC's established brand and reputation for security

May not have the same brand awareness as Revolut or Wise User Experience

Focuses on user-friendliness for a smooth money transfer experience

Needs to prove its app is as intuitive and user-friendly as competitors Global Reach

Ambitious plans for global expansion, offering services in new markets

Initial launch is limited to UK customers only Team Expertise

Recruited top talent from fintech rivals, bringing industry knowledge

Needs to demonstrate its team can deliver a competitive product Aspect Potential Pros Potential Cons Aspect Aspect Aspect Potential Pros Potential Pros Potential Pros Potential Cons Potential Cons Potential Cons Brand Recognition Leverages HSBC's established brand and reputation for security May not have the same brand awareness as Revolut or Wise Brand Recognition Brand Recognition Brand Recognition Leverages HSBC's established brand and reputation for security Leverages HSBC's established brand and reputation for security May not have the same brand awareness as Revolut or Wise May not have the same brand awareness as Revolut or Wise User Experience Focuses on user-friendliness for a smooth money transfer experience Needs to prove its app is as intuitive and user-friendly as competitors User Experience User Experience User Experience Focuses on user-friendliness for a smooth money transfer experience Focuses on user-friendliness for a smooth money transfer experience Needs to prove its app is as intuitive and user-friendly as competitors Needs to prove its app is as intuitive and user-friendly as competitors Global Reach Ambitious plans for global expansion, offering services in new markets Initial launch is limited to UK customers only Global Reach Global Reach Global Reach Ambitious plans for global expansion, offering services in new markets Ambitious plans for global expansion, offering services in new markets Initial launch is limited to UK customers only Initial launch is limited to UK customers only Team Expertise Recruited top talent from fintech rivals, bringing industry knowledge Needs to demonstrate its team can deliver a competitive product Team Expertise Team Expertise Team Expertise Recruited top talent from fintech rivals, bringing industry knowledge Recruited top talent from fintech rivals, bringing industry knowledge Needs to demonstrate its team can deliver a competitive product Needs to demonstrate its team can deliver a competitive product Key Takeaways from this New and Improved Competition! This head-to-head competition is a game-changer in the cross-border payments market, especially in UK. Here is what will you get: HSBC offers established banking security, but Revolut and Wise are known for their cutting-edge tech. Zing aims to bridge this gap, offering both trust and a tech-savvy experience. With more options, fees may drop, and features may become more user-friendly. This may include faster transfers, better exchange rates, and a smoother overall experience. This competition between big banks and fintech companies will benefit you the most. It can include a wider range of services, lower costs, and a constant push for innovation. HSBC offers established banking security, but Revolut and Wise are known for their cutting-edge tech. Zing aims to bridge this gap, offering both trust and a tech-savvy experience. With more options, fees may drop, and features may become more user-friendly. This may include faster transfers, better exchange rates, and a smoother overall experience. This competition between big banks and fintech companies will benefit you the most. It can include a wider range of services, lower costs, and a constant push for innovation. Stay updated for more updates about the fintech industry! For now, share your thoughts in the comments. Stay updated for more updates about the fintech industry! For now, share your thoughts in the comments.

ENTERINFI

enterinfi.com

-- employees

Since n.d.

COMPANY RANKING

ENTERINFI

EVERGREEN INDEX #3601

ENTERINFI WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

ENTERINFI

enterinfi.com

-- employees

Since n.d.

COMPANY RANKING

ENTERINFI

EVERGREEN INDEX #3601

RELATED COMPANIESRANK

STORIES ABOUT ENTERINFI

ENTERINFI WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!