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Spot

spot

We’re a custom software house with a team of 25 developers. During 2020 we’ve been experimenting with different B2B marketing techniques: one of these was an email newsletter, which we trialled at the beginning of September. Here’s how it went. Why did we want to do a newsletter? We went live with an overhaul of our website in July, and changed domain at the same time (our previous domain was .it and we wanted to go international). We needed ways to bring traffic to the website while we build up the authority of the new domain. Secondly, and more importantly, we already had a database of people who had registered interest in our company and we were looking for a way to stay in touch and give them something useful at the same time. We’re a lean organization and all our initiatives are strictly evaluated to maximize impact against time investment. The newsletter fit all these objectives. We can reach a few hundred people with a few hours’ work per week. We build our reputation for keeping up with the latest technology developments, which is what our clients pay us for. Since the beginning of September the newsletter has contributed to a 40% increase in traffic to our website. The first Issue was more successful than we'd hoped... The first issue was a collection of links with a bit of blatant promotion in the form of a client success story. Our audience is developers, IT or R&D managers and startup leaders, so we scoured the web for the articles we thought would be most useful and relevant to those people and put them together into an email. It was well received. Some people got in touch to say thanks. The open rate was just under 29%, above average for a software developer. ( ). Open rates and click rates are easy stats to monitor but they’re also an important indicator of engagement - whether your subscribers appreciate what you’re sending. We’re more interested in engagement than total subscribers, because of the reasons I mentioned above. Benchmarks differ by industry However, there were a bunch of hard bounces so the next task was to clean up the CRM. We use Hubspot and they have a tool that automates that. We removed about thirty email addresses from the mailing list because they were incorrect or no longer in use. ...but our subscribers soon got bored Over the next 4-5 weeks, the open rate declined a little bit each week, to around 22%. We kind of expected this - new stuff is always more interesting, right? So at the 6 week mark, we reviewed the stats and decided to make some tweaks. This is what the numbers told us: We’d had a few new signups, but also a bunch of unsubscribes. Most of them said they were getting too many emails. Decrease the frequency from weekly to bi-weekly 1. The tweak: We’re based in Italy, and we started marketing internationally less than a year ago. So about 90% of our contacts are in Italy. We initially had a mix of Italian and English language content in the newsletter. We noticed that Italian contacts were not clicking on links to English-language content. And when international contacts opened the newsletter they usually didn’t click at all. Split the database into two lists: Italy-based and international. We used dynamic lists so that they will automatically update when we add new contacts. 2. The tweak: . In week 4 we had included an excerpt of long-form writing from our blog. That week’s click rate was double the previous one. In week 5 (links only), open rate was up but click rate was down, and in week 6 both open rate and click rate went down again. Include more long-form content. Producing quality content takes time, so reducing the frequency helped us here. The latest editions include a mix of our content and curated reading recommendations. 3 The tweak: Emails with a custom subject line performed better than those with a generic subject line (like SPOT.letter). Vary the subject line to reflect that edition’s content. 4. The tweak: The tweaks are working… for now Open rates for the last few issues are between 30 and 40% and click rates have doubled to almost 6%. So for now we’re sticking with the changes we’ve made, but we’ll probably review again soon. If there’s one thing we’ve learnt this year, it’s that you have to keep moving.

Here's Our "So, We Decided To Start Sending Out A Newsletter" Story

The HackerNoon Newsletter: Zombies Among Us: Deadcoins  How to Spot Them (11/1/2024)

We have zombies from past crypto eras lurking on some exchanges and personal wallets: they’re called ‘deadcoins’. Sometimes, you can't tell a "live" coin from a dead one at first glance. If you hit buy or trade, the rotten thing might stay with you forever. Not a pleasant experience. Deadcoins are cryptocurrencies that have lost all or most of their value, have no active development, or have been abandoned by their creators and community. This can happen for various reasons, like scams, lack of interest, or poor execution of the project. Essentially, they’re digital assets that no longer have a viable future and are considered defunct. But here’s the catch: they may keep existing in some networks, and could still be available for trading on some DEXes. So, they’re like zombies, running around as they were programmed, but with no one to maintain their codes, make new plans, or even use them. They may keep some price and/or a low trade volume, depending on the coin, but it’s just zombie activity. Once in your portfolio, they’ll likely rot in there forever. What kills a coin? According to CoinGecko, over 50% of all cryptocurrencies (at least from the thousands listed in their platform), have died between 2014 and 2024. If you think about it, it was just meant to happen when a lot of people are only copying and pasting the same Bitcoin code with another name. Cryptocurrencies die for several reasons, and one common cause is the lack of interest or demand. Without enough users or investors, the project can’t sustain itself, leaving it with no real value. Another key reason is poor development; if the team behind the coin doesn’t deliver on their promises or the technology isn’t strong, people lose trust and abandon it. However, sometimes they’re created with the specific purpose of being deadcoins soon. In scams and frauds, they’re offered just to take money from investors, amid big and fake promises. Once the scammers are paid, they promptly disappear, leaving the coin worthless. On the other hand, in prediction markets like Prophet on Obyte, two or three tokens are created to represent potential results on a bet. Once the results are delivered, one or two of those tokens will become a deadcoin with zero value —but that’s expected from the beginning. Besides, competition in the crypto world is fierce, and if a coin doesn’t stand out or offer something unique, it can easily get overshadowed by more successful projects. Lastly, regulatory issues can kill a coin, especially if it’s new or has a small community. Governments might crack down on certain projects or declare them illegal, causing their value to plummet. When a coin faces legal trouble, people may be less likely to invest, and it often fades away. Prominent deadcoins You may think that deadcoins exclusively come from those shady Initial Coin Offerings (ICOs) from 2017, scams and frauds, old jokes, or projects that never had enough relevance, right? Well, then you’d be wrong. Some deadcoins and failed projects have been in the top ten by market capitalization and/or have been a total hit for different reasons. There’s no such a thing as “too big to fail” and it would do us good to remember that at all times. Auroracoin (AUR): This coin even had its own blockchain and aimed to be Iceland's national cryptocurrency. It briefly hit the top 10 by market capitalization in early 2014, shortly after its launch. However, the hype was short-lived, and the coin quickly lost value due to regulatory challenges, skepticism, and lack of widespread adoption. Its market cap has decreased by 99% since then, and its team is running another project already.
Bitconnect (BCC): Launched in 2016, Bitconnect offered a lending platform promising high returns through its native token. It reached the top 10 by market cap in 2017. However, it was exposed as a Ponzi scheme in 2018, leading to its collapse and regulatory shutdowns. Bitconnect tokens are no longer actively traded. https://www.youtube.com/watch?v=W6g8ShHEXns&embedable=true Terra (LUNA): Terra, launched in 2019, offered a stablecoin ecosystem with its native token, LUNA, reaching the top 10 by market cap in 2021. Terra's collapse occurred in 2022 when its algorithmic stablecoin, UST, de-pegged from the U.S. dollar, causing LUNA's value to plummet. Terra 2.0 exists as a new project, but the original blockchain was discontinued. The old asset (renamed LUNA Classic - LUNC) is still traded on some exchanges, with no small amount of risk involved. Zombie or not zombie Spotting deadcoins versus live projects, or those simply going through tough market conditions, requires attention to several key factors. A deadcoin often shows little to no development activity. If the team behind the coin has stopped updating its technology, releasing new features, or engaging with its community, that’s a red flag. In contrast, a live project going through a rough patch will usually still have active development and a committed team working to improve the situation, even if the market value has dropped. Another sign of a deadcoin is low or non-existent trading volume. If the coin can barely be traded on any major exchanges or only shows minimal movement, it indicates that there’s no interest or liquidity. On the other hand, coins in a market slump may see reduced trading volume, but they will still be available on multiple platforms, with some level of ongoing buying and selling, showing people haven’t completely lost faith. Community engagement also tells a lot. Deadcoins tend to have stagnant social media, forums, or developer channels, with little interaction or discussion. Live projects, even if struggling, will have active communities discussing solutions and the future. An engaged community often means that the project is still alive, despite setbacks. You can also sum it up with three questions: is the team long inactive on social media and code repositories, especially on X (Twitter), Discord, and GitHub? Is trading the coin nearly impossible? Are the founders in jail or running away from authorities? —yes, that happens. If the answer to those questions is “yes” for most of them, you’re totally seeing a zombie there. Could your coin die soon? Determining if a cryptocurrency is on the verge of dying can be tricky, but there are clear signs to watch for. One major factor is the absence of recent development activity. If a project doesn’t share a clear vision for future updates or improvements, it may indicate uncertainty or stagnation. Additionally, reduced community engagement is a strong indicator. If online forums and social media channels become quiet, it suggests that users are losing interest, which can be detrimental to the coin's overall health. Another concern is negative publicity or ongoing controversies surrounding a coin. Regular scandals, public exploits, or legal troubles can damage a cryptocurrency’s reputation, leading to a loss of trust among investors. Additionally, a lack of partnerships or real-world applications can hinder a project’s growth. Coins that struggle to find use cases or secure collaborations with other projects or networks often find it hard to gain traction and may face challenges in maintaining relevance. In contrast to the above, Obyte, along with its native currency, GBYTE, stands out as a thriving project with a vibrant community and constant updates. Its Directed Acyclic Graph (DAG) structure ensures more decentralized transactions, and the ongoing development by its team reflects a strong commitment to improvement. Obyte’s focus on libertarian ideals has attracted a dedicated user base, while applications and improvements continue to grow, ensuring its place in the market. Overall, Obyte's proactive approach and engaged community signal a promising and decentralized future for all its users. Featured Vector Image by Freepik We have zombies from past crypto eras lurking on some exchanges and personal wallets: they’re called ‘deadcoins’. Sometimes, you can't tell a "live" coin from a dead one at first glance. If you hit buy or trade, the rotten thing might stay with you forever. Not a pleasant experience. Deadcoins are cryptocurrencies that have lost all or most of their value, have no active development, or have been abandoned by their creators and community. This can happen for various reasons, like scams, lack of interest, or poor execution of the project. Essentially, they’re digital assets that no longer have a viable future and are considered defunct. Deadcoins are cryptocurrencies that have lost all or most of their value, have no active development, or have been abandoned by their creators and community. But here’s the catch: they may keep existing in some networks, and could still be available for trading on some DEXes. So, they’re like zombies, running around as they were programmed, but with no one to maintain their codes, make new plans, or even use them. They may keep some price and/or a low trade volume, depending on the coin, but it’s just zombie activity. Once in your portfolio, they’ll likely rot in there forever. What kills a coin? According to CoinGecko , over 50% of all cryptocurrencies (at least from the thousands listed in their platform), have died between 2014 and 2024. If you think about it, it was just meant to happen when a lot of people are only copying and pasting the same Bitcoin code with another name. According to CoinGecko According to CoinGecko over 50% of all cryptocurrencies (at least from the thousands listed in their platform), have died between 2014 and 2024. Cryptocurrencies die for several reasons, and one common cause is the lack of interest or demand. Without enough users or investors, the project can’t sustain itself, leaving it with no real value. Another key reason is poor development; if the team behind the coin doesn’t deliver on their promises or the technology isn’t strong, people lose trust and abandon it. However, sometimes they’re created with the specific purpose of being deadcoins soon. In scams and frauds, they’re offered just to take money from investors, amid big and fake promises . Once the scammers are paid, they promptly disappear, leaving the coin worthless. On the other hand, in prediction markets like Prophet on Obyte, two or three tokens are created to represent potential results on a bet. Once the results are delivered, one or two of those tokens will become a deadcoin with zero value —but that’s expected from the beginning. In scams and frauds , they’re offered just to take money from investors, amid big and fake promises In scams and frauds In scams and frauds Prophet Prophet Besides, competition in the crypto world is fierce, and if a coin doesn’t stand out or offer something unique, it can easily get overshadowed by more successful projects. Lastly, regulatory issues can kill a coin, especially if it’s new or has a small community. Governments might crack down on certain projects or declare them illegal, causing their value to plummet. When a coin faces legal trouble, people may be less likely to invest, and it often fades away. Prominent deadcoins You may think that deadcoins exclusively come from those shady Initial Coin Offerings (ICOs) from 2017, scams and frauds, old jokes, or projects that never had enough relevance, right? Well, then you’d be wrong. Some deadcoins and failed projects have been in the top ten by market capitalization and/or have been a total hit for different reasons. There’s no such a thing as “too big to fail” and it would do us good to remember that at all times. Some deadcoins and failed projects have been in the top ten by market capitalization and/or have been a total hit for different reasons. Some deadcoins and failed projects Some deadcoins and failed projects Auroracoin (AUR): This coin even had its own blockchain and aimed to be Iceland's national cryptocurrency. It briefly hit the top 10 by market capitalization in early 2014, shortly after its launch. However, the hype was short-lived, and the coin quickly lost value due to regulatory challenges, skepticism, and lack of widespread adoption. Its market cap has decreased by 99% since then, and its team is running another project already. Bitconnect (BCC): Launched in 2016, Bitconnect offered a lending platform promising high returns through its native token. It reached the top 10 by market cap in 2017. However, it was exposed as a Ponzi scheme in 2018, leading to its collapse and regulatory shutdowns. Bitconnect tokens are no longer actively traded. Auroracoin (AUR): This coin even had its own blockchain and aimed to be Iceland's national cryptocurrency. It briefly hit the top 10 by market capitalization in early 2014 , shortly after its launch. However, the hype was short-lived, and the coin quickly lost value due to regulatory challenges, skepticism, and lack of widespread adoption. Its market cap has decreased by 99% since then, and its team is running another project already. Auroracoin (AUR): early 2014 early 2014 Bitconnect (BCC): Launched in 2016, Bitconnect offered a lending platform promising high returns through its native token. It reached the top 10 by market cap in 2017. However, it was exposed as a Ponzi scheme in 2018, leading to its collapse and regulatory shutdowns. Bitconnect tokens are no longer actively traded. Bitconnect (BCC): https://www.youtube.com/watch?v=W6g8ShHEXns&embedable=true https://www.youtube.com/watch?v=W6g8ShHEXns&embedable=true Terra (LUNA): Terra, launched in 2019, offered a stablecoin ecosystem with its native token, LUNA, reaching the top 10 by market cap in 2021. Terra's collapse occurred in 2022 when its algorithmic stablecoin, UST, de-pegged from the U.S. dollar, causing LUNA's value to plummet. Terra 2.0 exists as a new project, but the original blockchain was discontinued. The old asset (renamed LUNA Classic - LUNC) is still traded on some exchanges, with no small amount of risk involved. Terra (LUNA): Terra, launched in 2019, offered a stablecoin ecosystem with its native token, LUNA, reaching the top 10 by market cap in 2021. Terra's collapse occurred in 2022 when its algorithmic stablecoin, UST, de-pegged from the U.S. dollar, causing LUNA's value to plummet. Terra 2.0 exists as a new project, but the original blockchain was discontinued . The old asset (renamed LUNA Classic - LUNC) is still traded on some exchanges, with no small amount of risk involved. Terra (LUNA): was discontinued was discontinued Zombie or not zombie Spotting deadcoins versus live projects, or those simply going through tough market conditions, requires attention to several key factors. A deadcoin often shows little to no development activity. If the team behind the coin has stopped updating its technology, releasing new features, or engaging with its community, that’s a red flag. In contrast, a live project going through a rough patch will usually still have active development and a committed team working to improve the situation, even if the market value has dropped. Another sign of a deadcoin is low or non-existent trading volume. If the coin can barely be traded on any major exchanges or only shows minimal movement, it indicates that there’s no interest or liquidity. On the other hand, coins in a market slump may see reduced trading volume, but they will still be available on multiple platforms, with some level of ongoing buying and selling, showing people haven’t completely lost faith. Another sign of a deadcoin is low or non-existent trading volume. Community engagement also tells a lot. Deadcoins tend to have stagnant social media, forums, or developer channels, with little interaction or discussion. Live projects, even if struggling, will have active communities discussing solutions and the future. An engaged community often means that the project is still alive, despite setbacks. You can also sum it up with three questions: is the team long inactive on social media and code repositories, especially on X (Twitter), Discord, and GitHub? Is trading the coin nearly impossible? Are the founders in jail or running away from authorities? —yes, that happens . If the answer to those questions is “yes” for most of them, you’re totally seeing a zombie there. You can also sum it up with three questions: that happens that happens Could your coin die soon? Determining if a cryptocurrency is on the verge of dying can be tricky, but there are clear signs to watch for. One major factor is the absence of recent development activity. If a project doesn’t share a clear vision for future updates or improvements, it may indicate uncertainty or stagnation. Additionally, reduced community engagement is a strong indicator. If online forums and social media channels become quiet, it suggests that users are losing interest, which can be detrimental to the coin's overall health. Another concern is negative publicity or ongoing controversies surrounding a coin. Regular scandals, public exploits, or legal troubles can damage a cryptocurrency’s reputation, leading to a loss of trust among investors. Additionally, a lack of partnerships or real-world applications can hinder a project’s growth. Coins that struggle to find use cases or secure collaborations with other projects or networks often find it hard to gain traction and may face challenges in maintaining relevance. Another concern is negative publicity or ongoing controversies surrounding a coin. In contrast to the above, Obyte , along with its native currency, GBYTE, stands out as a thriving project with a vibrant community and constant updates. Its Directed Acyclic Graph (DAG) structure ensures more decentralized transactions, and the ongoing development by its team reflects a strong commitment to improvement. Obyte’s focus on libertarian ideals has attracted a dedicated user base, while applications and improvements continue to grow, ensuring its place in the market. Overall, Obyte's proactive approach and engaged community signal a promising and decentralized future for all its users. Obyte Obyte applications and improvements applications and improvements Featured Vector Image by Freepik Featured Vector Image by Freepik Freepik Freepik

Zombies Among Us: Deadcoins & How to Spot Them

Zombies entre nosotros: monedas muertas y cómo detectarlas

زامبی ها در میان ما: ددکوین ها و نحوه تشخیص آنها

Zombeja keskuudessamme: Deadcoinit ja kuinka löytää ne

Les zombies sont parmi nous : les Deadcoins et comment les repérer

Zombies Among Us: Deadcoins e como detectalos

हमारे बीच ज़ॉम्बी: डेडकॉइन्स और उन्हें कैसे पहचानें

Զոմբիները մեր մեջ. Deadcoins և ինչպես նկատել դրանք

私たちの中にゾンビがいる: デッドコインとその見分け方

Zombies Among Nos: Deadcoins & Imaynatataq chaykunata riqsina

ዞምቢ ኣብ መንጎና: Deadcoins & ከመይ ጌርና ንርእዮም

Zombies Among Us: Deadcoin'ler ve Bunları Nasıl Tespit Edebilirsiniz

我们身边的僵尸：死亡币及其识别方法

If you’ve spent any time on Facebook lately—and who hasn’t?—you’ve probably seen it. A group with a title that practically waves a red flag: “SCAMMERS LIST UPDATE.” It sounds like the place where you'd finally find the justice you’ve been looking for after falling victim to an online scam. Editor’s note: This story represents the views of the author of the story. The author is not affiliated with HackerNoon staff and wrote this story on their own. The HackerNoon editorial team has only verified the story for grammatical accuracy and does not condone/condemn any of the claims contained herein. #DYOR Maybe they’ll track down your lost money, or better yet, the scammer who conned you. Well, spoiler alert: they won’t. In fact, the ones behind this group are likely the same folks who ripped you off in the first place. Facebook, now going by Meta (because a rebrand magically fixes everything), is supposedly equipped with state-of-the-art systems to protect users from fraud. You’d think that includes shutting down a group that’s effectively a wolf in sheep’s clothing. But no, “SCAMMERS LIST UPDATE” is still up and running, despite countless reports by concerned users. And let’s be honest—Meta’s reaction has been about as useful as shouting into the wind. At first glance, this group seems almost noble. They’ve got the look of a do-gooder vigilante squad, dedicated to helping scam victims recover their hard-earned cash. But here’s where it gets twisted: the group is nothing more than a scam itself, a sinister plot to squeeze even more money out of already vulnerable victims. It’s like getting pickpocketed and then paying the thief to "help" you find your wallet. In what can only be described as a truly bitter irony, these fraudsters charge fees for “recovering” stolen funds. Spoiler number two: once you’ve sent money to a scammer, it’s gone. Vanished. The chances of some random Facebook group recovering it? About as likely as Facebook’s customer service actually responding to your complaints in a timely manner. But the real kicker? The group is riddled with scammers pretending to be everyday users. These aren’t your average internet trolls; these are organized scammers, often from overseas, posing as Westerners with stolen photos and fake profiles. And while the average user might not notice anything amiss, a closer look shows this group for what it is: a full-on scam factory. Profiles are fake, motives are even faker, and the whole thing is operating under the not-so-watchful eye of Meta. Despite numerous reports—complaints about everything from fake profiles to the scams happening right in plain sight—Meta has responded with a resounding, “We did not take any action.” Yeah, you read that right. One of the biggest tech companies in the world, with access to the kind of AI most of us can only dream of, is apparently powerless against a bunch of digital con artists. It’s almost laughable, except it’s not. Meta’s failure to act sends a chilling message: scammers are safe here. As long as they don’t get too loud about it, they can operate under the radar with little to no fear of getting booted off the platform. So what happens when someone, already humiliated and out a chunk of cash, turns to Meta for help? They’re met with silence—or worse, with a dismissive shrug. Why It's Time for Governments to Step In Meta's apparent refusal to address the rising tide of scams on its platform sends a troubling message: scammers have a safe haven under their watch. Rather than cracking down on fraud, Meta’s inaction seems to shield the very criminals preying on innocent users. Victims, already humiliated and financially drained, find no justice when they report fake profiles and fraudulent activity—just silence. The negligence isn't just a technological glitch; it’s a moral failure. It's time for governments to intervene, hold Meta accountable, and put an end to this unchecked lawlessness. Australia’s Albanese Government is stepping up to the plate with draft legislation aimed at slapping hefty penalties—up to $50 million—on banks, telecoms, and social media platforms like Facebook if they fail to fight back against fraud. Assistant Treasurer Stephen Jones is leading the charge, declaring that Australia will become one of the toughest places in the world for scammers to operate. He emphasized, "The best protections anywhere in the world should be available to people here in Australia." The truth is, Australians are losing too much money to scams. Although we've avoided the international trend where scam losses double yearly, we’re still seeing far too many victims. Jones' words signal a shift in accountability—finally putting pressure on social media giants like Facebook, which have let scams flourish for far too long. Former Sunrise host David Koch knows the frustration all too well. For years, he’s called out scammers using his image and fake quotes to deceive people, with Facebook doing little to stop it. “I had a bloke on the weekend contact me through Facebook, abusing me because he lost $30,000 to a scam that used my picture and dodgy comments,” says Koch. The reality is this: Facebook has devolved into a breeding ground for scams. The platform, once intended to connect us, has become a cesspool for fraudsters, from fake ads to phishing schemes, all targeting users daily. Even worse, Facebook’s ad system seems to amplify these scams, giving fraudsters an even bigger stage. Rather than protecting users, Meta seems more focused on cashing in ad revenue, no matter how deceptive the ads may be. Scammers are thriving on the very platform that claims to keep us safe. If governments don't intervene, Meta’s complicity will only continue to endanger users worldwide. It’s time for someone to wake up and realize this isn’t just a technical oversight—it’s a moral issue. Meta’s refusal to take down groups like “SCAMMERS LIST UPDATE” doesn’t just allow scammers to thrive, it almost feels like an endorsement. And as much as we’d love to think we’re safe online, the truth is that until companies like Meta are held accountable, scam culture will continue to thrive in plain sight. At this point, maybe it’s time to ask the government to step in. We’ve let these platforms self-regulate long enough, and it’s clear that isn’t working. Letting scammers run rampant under the guise of “user-generated content” is more than irresponsible—it’s complicit. Meta may think a new name wipes the slate clean, but if this group is any indication, the mess is far from over. If you’ve spent any time on Facebook lately—and who hasn’t?—you’ve probably seen it. A group with a title that practically waves a red flag: “SCAMMERS LIST UPDATE.” It sounds like the place where you'd finally find the justice you’ve been looking for after falling victim to an online scam. Editor’s note: This story represents the views of the author of the story. The author is not affiliated with HackerNoon staff and wrote this story on their own. The HackerNoon editorial team has only verified the story for grammatical accuracy and does not condone/condemn any of the claims contained herein. #DYOR Editor’s note: This story represents the views of the author of the story. The author is not affiliated with HackerNoon staff and wrote this story on their own. The HackerNoon editorial team has only verified the story for grammatical accuracy and does not condone/condemn any of the claims contained herein. #DYOR Editor’s note: This story represents the views of the author of the story. The author is not affiliated with HackerNoon staff and wrote this story on their own. The HackerNoon editorial team has only verified the story for grammatical accuracy and does not condone/condemn any of the claims contained herein. #DYOR Editor’s note: This story represents the views of the author of the story. The author is not affiliated with HackerNoon staff and wrote this story on their own. The HackerNoon editorial team has only verified the story for grammatical accuracy and does not condone/condemn any of the claims contained herein. #DYOR Maybe they’ll track down your lost money, or better yet, the scammer who conned you. Well, spoiler alert: they won’t. In fact, the ones behind this group are likely the same folks who ripped you off in the first place. Facebook, now going by Meta (because a rebrand magically fixes everything), is supposedly equipped with state-of-the-art systems to protect users from fraud . You’d think that includes shutting down a group that’s effectively a wolf in sheep’s clothing. fraud But no, “ SCAMMERS LIST UPDATE ” is still up and running, despite countless reports by concerned users. And let’s be honest—Meta’s reaction has been about as useful as shouting into the wind. SCAMMERS LIST UPDATE At first glance, this group seems almost noble. They’ve got the look of a do-gooder vigilante squad, dedicated to helping scam victims recover their hard-earned cash. But here’s where it gets twisted: the group is nothing more than a scam itself, a sinister plot to squeeze even more money out of already vulnerable victims. scam victims It’s like getting pickpocketed and then paying the thief to "help" you find your wallet. It’s like getting pickpocketed and then paying the thief to "help" you find your wallet. It’s like getting pickpocketed and then paying the thief to "help" you find your wallet. In what can only be described as a truly bitter irony, these fraudsters charge fees for “recovering” stolen funds. Spoiler number two: once you’ve sent money to a scammer, it’s gone. Vanished. The chances of some random Facebook group recovering it? About as likely as Facebook’s customer service actually responding to your complaints in a timely manner. Facebook But the real kicker? The group is riddled with scammers pretending to be everyday users. These aren’t your average internet trolls; these are organized scammers, often from overseas, posing as Westerners with stolen photos and fake profiles. And while the average user might not notice anything amiss, a closer look shows this group for what it is: a full-on scam factory. Profiles are fake, motives are even faker, and the whole thing is operating under the not-so-watchful eye of Meta. closer look this group Despite numerous reports—complaints about everything from fake profiles to the scams happening right in plain sight—Meta has responded with a resounding, “We did not take any action.” Yeah, you read that right. fake profiles One of the biggest tech companies in the world, with access to the kind of AI most of us can only dream of, is apparently powerless against a bunch of digital con artists. It’s almost laughable, except it’s not. Meta’s failure to act sends a chilling message: scammers are safe here. As long as they don’t get too loud about it, they can operate under the radar with little to no fear of getting booted off the platform. So what happens when someone, already humiliated and out a chunk of cash, turns to Meta for help? They’re met with silence—or worse, with a dismissive shrug. Why It's Time for Governments to Step In Meta's apparent refusal to address the rising tide of scams on its platform sends a troubling message: scammers have a safe haven under their watch. Rather than cracking down on fraud, Meta’s inaction seems to shield the very criminals preying on innocent users. Victims, already humiliated and financially drained, find no justice when they report fake profiles and fraudulent activity—just silence. The negligence isn't just a technological glitch; it’s a moral failure. It's time for governments to intervene, hold Meta accountable, and put an end to this unchecked lawlessness. Australia’s Albanese Government is stepping up to the plate with draft legislation aimed at slapping hefty penalties—up to $50 million—on banks, telecoms, and social media platforms like Facebook if they fail to fight back against fraud. Assistant Treasurer Stephen Jones is leading the charge, declaring that Australia will become one of the toughest places in the world for scammers to operate. He emphasized, "The best protections anywhere in the world should be available to people here in Australia." The truth is, Australians are losing too much money to scams. Although we've avoided the international trend where scam losses double yearly, we’re still seeing far too many victims. Jones' words signal a shift in accountability—finally putting pressure on social media giants like Facebook, which have let scams flourish for far too long. Former Sunrise host David Koch knows the frustration all too well. For years, he’s called out scammers using his image and fake quotes to deceive people, with Facebook doing little to stop it. “I had a bloke on the weekend contact me through Facebook, abusing me because he lost $30,000 to a scam that used my picture and dodgy comments,” says Koch. Sunrise host David Koch The reality is this: Facebook has devolved into a breeding ground for scams. The platform, once intended to connect us, has become a cesspool for fraudsters, from fake ads to phishing schemes, all targeting users daily. Even worse, Facebook’s ad system seems to amplify these scams, giving fraudsters an even bigger stage. Rather than protecting users, Meta seems more focused on cashing in ad revenue, no matter how deceptive the ads may be. Scammers are thriving on the very platform that claims to keep us safe. If governments don't intervene, Meta’s complicity will only continue to endanger users worldwide. It’s time for someone to wake up and realize this isn’t just a technical oversight—it’s a moral issue. Meta’s refusal to take down groups like “SCAMMERS LIST UPDATE” doesn’t just allow scammers to thrive, it almost feels like an endorsement. And as much as we’d love to think we’re safe online, the truth is that until companies like Meta are held accountable, scam culture will continue to thrive in plain sight. At this point, maybe it’s time to ask the government to step in. We’ve let these platforms self-regulate long enough, and it’s clear that isn’t working. Letting scammers run rampant under the guise of “user-generated content” is more than irresponsible—it’s complicit. Meta may think a new name wipes the slate clean, but if this group is any indication, the mess is far from over.

Meta's Blind Spot: How Scammers Run Free On Facebook While Victims Pay the Price

September 15, 2024 MEXC is excited to announce the launch of its Catizen (CATI) Spot and Futures trading. Initial Listing Time CATI/USDT Spot Trading: Sep 20, 2024, 10AM UTC
__CATI/USDT Futures Trading: __Sep 20, 2024, 10:20AM UTC What is Catizen (CATI)? Catizen (CATI) is a successful Telegram mini app, quickly gaining 34 million users and becoming the top-earning app with 800,000 paid subscribers and an average revenue of $33 per user. Players can start the game directly from chat, combining cats in their virtual café to level up. Catizen blends traditional gameplay with strategic gamification and Play-to-Airdrop features, offering a unique Web3 experience with rewards. Hop On the MEXC CATI Treasure Express and Take Home Your Rewards! Eligible for

Event & Time

Total Prize Pool

How to Participate



New User Registration

Deposit & Trade to EarnSep 15 10:00 -Oct 1 10:00 UTC

700,000 CATI + 70,000 USDT

Deposit to Qualify: Deposit 300 CATI or 100 USDT to get started.Complete Either a Trading Task or Both!Spot: Trade $100 USDT worth of CATI and earn 50 CATI__Futures:__ Trade $100 USDT worth of CATI and earn 50 CATI +10 USDT Bonuses*Registration at the start of the event is required to participate.



All Registered Users

Refer FriendsSep 15 10:00 -Oct 1 10:00 UTC

300,000 CATI

New users referred by MEXC users will be eligible for a 50 CATI airdrop reward, as long as they have completed __Deposit & Trade to Earn__Each user can earn up to p500 CATI rewards*Registration of new users at the start of the event is required to participate.



The Perpetual Futures Trading Competition Sep 20 10:20 -Sep 25 10:30 UTC

10,000 USDT

CATI/USDT Perpetual Contract and accumulate a trading volume ≥ 30,000 USDTTrading Volume Ranked Top 200*No registration is required. Reward Distribution: All rewards will be distributed before Oct 10, 2024 10AM UTC Related announcement link: Celebrating the Listing of Catizen (CATI) : Deposit & Trade to Share 1,000,000 CATI and 70,000 USDT Futures Bonus!
[Initial Futures Listing] MEXC Will List CATI USDT-M Perpetual Futures And Launch Trading Event With 10,000 USDT Bonus Pool (10:20, September 20 UTC) About MEXC MEXC has earned 5 World-Leading Advantages. Now it is proud to offer all users a compelling value proposition that includes: Lowest Trading Fees, Most Hot Token, Best Trading Liquidty, Highest APY by MX Airdrop and Lowest Withdrawl Fees. "We believe in the power of community. With over 10 million MEXCers standing with us, each one of you matters,.” said Tracy, COO of MEXC. “As we move forward, our mission remains clear: to deliver unparalleled value and service, ensuring that we remains the top choice for traders worldwide.” This month, MEXC is honored to be recognized by Simplicity Group, following their comprehensive analysis of over 4,800 data points on token performance post-listing on major centralized exchanges. This acknowledgment underscores our unwavering dedication to providing a transparent, efficient, and user-centric trading environment. This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here September 15, 2024 MEXC is excited to announce the launch of its Catizen (CATI) Spot and Futures trading. Initial Listing Time CATI/USDT Spot Trading: Sep 20, 2024, 10AM UTC __CATI/USDT Futures Trading: __Sep 20, 2024, 10:20AM UTC CATI/USDT Spot Trading: Sep 20, 2024, 10AM UTC CATI/USDT Spot Trading: CATI/USDT Spot Trading: __ CATI/USDT Futures Trading: __Sep 20, 2024, 10:20AM UTC CATI/USDT Futures Trading: What is Catizen (CATI)? Catizen (CATI) is a successful Telegram mini app, quickly gaining 34 million users and becoming the top-earning app with 800,000 paid subscribers and an average revenue of $33 per user. Catizen (CATI) Catizen (CATI) gaining 34 million users gaining 34 million users Players can start the game directly from chat, combining cats in their virtual café to level up. Catizen blends traditional gameplay with strategic gamification and Play-to-Airdrop features, offering a unique Web3 experience with rewards. Hop On the MEXC CATI Treasure Express and Take Home Your Rewards! Eligible for

Event & Time

Total Prize Pool

How to Participate



New User Registration

Deposit & Trade to EarnSep 15 10:00 -Oct 1 10:00 UTC

700,000 CATI + 70,000 USDT

Deposit to Qualify: Deposit 300 CATI or 100 USDT to get started.Complete Either a Trading Task or Both!Spot: Trade $100 USDT worth of CATI and earn 50 CATI__Futures:__ Trade $100 USDT worth of CATI and earn 50 CATI +10 USDT Bonuses*Registration at the start of the event is required to participate.



All Registered Users

Refer FriendsSep 15 10:00 -Oct 1 10:00 UTC

300,000 CATI

New users referred by MEXC users will be eligible for a 50 CATI airdrop reward, as long as they have completed __Deposit & Trade to Earn__Each user can earn up to p500 CATI rewards*Registration of new users at the start of the event is required to participate.



The Perpetual Futures Trading Competition Sep 20 10:20 -Sep 25 10:30 UTC

10,000 USDT

CATI/USDT Perpetual Contract and accumulate a trading volume ≥ 30,000 USDTTrading Volume Ranked Top 200*No registration is required. Eligible for

Event & Time

Total Prize Pool

How to Participate New User Registration

Deposit & Trade to EarnSep 15 10:00 -Oct 1 10:00 UTC

700,000 CATI + 70,000 USDT

Deposit to Qualify: Deposit 300 CATI or 100 USDT to get started.Complete Either a Trading Task or Both!Spot: Trade $100 USDT worth of CATI and earn 50 CATI__Futures:__ Trade $100 USDT worth of CATI and earn 50 CATI +10 USDT Bonuses*Registration at the start of the event is required to participate. All Registered Users

Refer FriendsSep 15 10:00 -Oct 1 10:00 UTC

300,000 CATI

New users referred by MEXC users will be eligible for a 50 CATI airdrop reward, as long as they have completed __Deposit & Trade to Earn__Each user can earn up to p500 CATI rewards*Registration of new users at the start of the event is required to participate. The Perpetual Futures Trading Competition Sep 20 10:20 -Sep 25 10:30 UTC

10,000 USDT

CATI/USDT Perpetual Contract and accumulate a trading volume ≥ 30,000 USDTTrading Volume Ranked Top 200*No registration is required. Eligible for Event & Time Total Prize Pool How to Participate Eligible for Eligible for Event & Time Event & Time Total Prize Pool Total Prize Pool How to Participate How to Participate New User Registration Deposit & Trade to EarnSep 15 10:00 -Oct 1 10:00 UTC 700,000 CATI + 70,000 USDT Deposit to Qualify: Deposit 300 CATI or 100 USDT to get started.Complete Either a Trading Task or Both!Spot: Trade $100 USDT worth of CATI and earn 50 CATI__Futures:__ Trade $100 USDT worth of CATI and earn 50 CATI +10 USDT Bonuses*Registration at the start of the event is required to participate. New User Registration New User Registration Deposit & Trade to EarnSep 15 10:00 -Oct 1 10:00 UTC Deposit & Trade to EarnSep 15 10:00 -Oct 1 10:00 UTC Deposit & Trade to Earn Sep 15 10:00 -Oct 1 10:00 UTC Deposit & Trade to Earn Sep 15 10:00 -Oct 1 10:00 UTC 700,000 CATI + 70,000 USDT 700,000 CATI + 70,000 USDT Deposit to Qualify: Deposit 300 CATI or 100 USDT to get started.Complete Either a Trading Task or Both!Spot: Trade $100 USDT worth of CATI and earn 50 CATI__Futures:__ Trade $100 USDT worth of CATI and earn 50 CATI +10 USDT Bonuses*Registration at the start of the event is required to participate. Deposit to Qualify: Deposit 300 CATI or 100 USDT to get started.Complete Either a Trading Task or Both! Spot: Trade $100 USDT worth of CATI and earn 50 CATI__ Futures: __ Trade $100 USDT worth of CATI and earn 50 CATI +10 USDT Bonuses*Registration at the start of the event is required to participate. Deposit 300 CATI Deposit 300 CATI 100 USDT 100 USDT Spot: Spot: Futures: All Registered Users Refer FriendsSep 15 10:00 -Oct 1 10:00 UTC 300,000 CATI New users referred by MEXC users will be eligible for a 50 CATI airdrop reward, as long as they have completed __Deposit & Trade to Earn__Each user can earn up to p500 CATI rewards*Registration of new users at the start of the event is required to participate. All Registered Users All Registered Users Refer FriendsSep 15 10:00 -Oct 1 10:00 UTC Refer FriendsSep 15 10:00 -Oct 1 10:00 UTC Refer Friends Sep 15 10:00 -Oct 1 10:00 UTC Refer Friends Sep 15 10:00 -Oct 1 10:00 UTC 300,000 CATI 300,000 CATI New users referred by MEXC users will be eligible for a 50 CATI airdrop reward, as long as they have completed __Deposit & Trade to Earn__Each user can earn up to p500 CATI rewards*Registration of new users at the start of the event is required to participate. New users referred by MEXC users will be eligible for a 50 CATI airdrop reward, as long as they have completed __ Deposit & Trade to Earn __Each user can earn up to p500 CATI rewards*Registration of new users at the start of the event is required to participate. Deposit & Trade to Earn The Perpetual Futures Trading Competition Sep 20 10:20 -Sep 25 10:30 UTC 10,000 USDT CATI/USDT Perpetual Contract and accumulate a trading volume ≥ 30,000 USDTTrading Volume Ranked Top 200*No registration is required. The Perpetual Futures Trading Competition Sep 20 10:20 -Sep 25 10:30 UTC The Perpetual Futures Trading Competition Sep 20 10:20 -Sep 25 10:30 UTC The Perpetual Futures Trading Competition The Perpetual Futures Trading Competition Sep 20 10:20 -Sep 25 10:30 UTC Sep 20 10:20 -Sep 25 10:30 UTC 10,000 USDT 10,000 USDT CATI/USDT Perpetual Contract and accumulate a trading volume ≥ 30,000 USDTTrading Volume Ranked Top 200*No registration is required. CATI/USDT Perpetual Contract and accumulate a trading volume ≥ 30,000 USDT Trading Volume Ranked Top 200*No registration is required. CATI/USDT Perpetual Contract CATI/USDT Perpetual Contract accumulate a trading volume ≥ 30,000 USDT Reward Distribution: All rewards will be distributed before Oct 10, 2024 10AM UTC Reward Distribution: All rewards will be distributed before Oct 10, 2024 10AM UTC Related announcement link: Celebrating the Listing of Catizen (CATI) : Deposit & Trade to Share 1,000,000 CATI and 70,000 USDT Futures Bonus! [Initial Futures Listing] MEXC Will List CATI USDT-M Perpetual Futures And Launch Trading Event With 10,000 USDT Bonus Pool (10:20, September 20 UTC) Celebrating the Listing of Catizen (CATI) : Deposit & Trade to Share 1,000,000 CATI and 70,000 USDT Futures Bonus! Celebrating the Listing of Catizen (CATI) : Deposit & Trade to Share 1,000,000 CATI and 70,000 USDT Futures Bonus! [Initial Futures Listing] MEXC Will List CATI USDT-M Perpetual Futures And Launch Trading Event With 10,000 USDT Bonus Pool (10:20, September 20 UTC) [Initial Futures Listing] MEXC Will List CATI USDT-M Perpetual Futures And Launch Trading Event With 10,000 USDT Bonus Pool (10:20, September 20 UTC) About MEXC MEXC has earned 5 World-Leading Advantages . Now it is proud to offer all users a compelling value proposition that includes: Lowest Trading Fees, Most Hot Token, Best Trading Liquidty, Highest APY by MX Airdrop and Lowest Withdrawl Fees. 5 World-Leading Advantages 5 World-Leading Advantages "We believe in the power of community. With over 10 million MEXCers standing with us, each one of you matters,.” said Tracy, COO of MEXC. "We believe in the power of community. With over 10 million MEXCers standing with us, each one of you matters,.” said Tracy, COO of MEXC. “As we move forward, our mission remains clear: to deliver unparalleled value and service, ensuring that we remains the top choice for traders worldwide.” “As we move forward, our mission remains clear: to deliver unparalleled value and service, ensuring that we remains the top choice for traders worldwide.” This month, MEXC is honored to be recognized by Simplicity Group , following their comprehensive analysis of over 4,800 data points on token performance post-listing on major centralized exchanges. Simplicity Group Simplicity Group This acknowledgment underscores our unwavering dedication to providing a transparent, efficient, and user-centric trading environment. This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here here

MEXC To Launch CATI Spot And Futures Trading

MEXC ще стартира CATI Спот и фючърсна търговия

MEXC führt CATI-Spot- und Futures-Handel ein

MEXC lanzará negociación de futuros y spot de CATI

MEXC-k CATI Spot eta Futures Trading abiaraziko du

A MEXC elindítja a CATI azonnali és határidős kereskedést

MEXC תשיק את CATI ספוט ומסחר בחוזים עתידיים

MEXC、CATIスポットおよび先物取引を開始

MEXC CATI Spot жана Futures соодасын ишке киргизет

MEXC uzsāks CATI tūlītējo un nākotnes darījumu tirdzniecību

MEXC Akan Melancarkan Dagangan Spot Dan Niaga Hadapan CATI

MEXC lanserar CATI Spot And Futures Trading

MEXC CATI اسپاٹ اور فیوچر ٹریڈنگ کا آغاز کرے گا۔

Brazil is the biggest economy in Latin America and together with Mexico it has 57% of nominal GDP in the region. And this is the long-term trend for the future - according to PWC report “The world in 2050” Brazil will be the 5th country in the world with GDP at PPPs after US, China, India and Indonesia. Moreover, Brazil has a prospective fintech market and, in comparison with other Latin American jurisdictions, low barriers to setting up a company or issuing crypto ETFs. Recently, BlackRock launched an Ethereum ETF in Brazil and listed it on the biggest local stock exchange, B3. Brazil also offers flexible conditions for immigrants, including living conditions and a fast naturalization procedure. In this article, I describe existing options for crypto nomads to relocate to Brazil, including living conditions and crypto regulations in the country. How move to Brazil? Although some authors call Brazil “bureaucratic” like other South American areas, it has a flexible immigration system. If you want to move there you have a wide range of options for digital nomads, which include: -Digital Nomad Visa -Student visa -Working visa -Family visa -Investor visa -Refugee status The basic options for digital nomads are a nomad visa and an investment visa. These options are pretty affordable. To get a residence permit of digital nomad you need to prove your monthly income of $1,500+ or put $18,000 in your bank account and this gives you a residence permit. Brazil is one of the few with such a visa in Latin America, which was launched recently in 2022. The number of rejections with properly executed documents is minimal. For an investor visa, an applicant should create a company with a capital of 500,000 BRL (about $100,000) or purchase a property from 1,000,000 BRL (about $200,000). An investor gets a permanent residence permit and can apply for Brazilian citizenship within 3 years. There are some exemptions for the required amount of real estate purchase in North-West provinces of Brazil - it may start from $100,000. Also, the minimal required investment in innovative businesses starts at $30,000. Brazil has a developed education system for student visa applicants with 98 public universities, and 8 of the 20 best Latam universities are located in the country. The only obstacle is that most programs of study are in Portuguese, although you can also find a proper university with Spanish or English programs. Living Conditions and Costs Brazil is the largest country in Latam and has 26 states, from Roraima and Amazonas on the north to Rio Grande de Sul on the South. The cost of living will vary depending on your income and preferences. Probably the most popular place among expats is Florianopolis. It’s safe and has beautiful nature and a climate. Other expats prefer 2 largest cities in the country - Rio de Janeiro and Sao Paulo.  Also on the coast there some other cities which attract immigrants - Recife, Vitoria, Salvador, Porto Allegre, Curitiba and some others. The capital of Brazil is a citiy Brasilia located close to the center of its territory and there is also a group of immigrants living there. Сosts of living in Brazil are quite affordable - depending on the place and district you choose, rent can cost from $300 up to $2000. For a single person, the minimum monthly cost of living may start at $1000. It is much cheaper than living in developed countries in Europe and the US. At the same time, compared to other Latin American countries such as Peru, Colombia, and Argentina, Brazil is somewhat more expensive. Also by this indicator, it loses to the affordable for nomadic countries of Asia, such as Vietnam and Thailand. If we talk about the difficulties faced by nomads in Brazil - there is quite a high crime rate in some areas, and there is a possibility of becoming a victim of theft or robbery. To avoid this, it is enough to choose a safer area of residence and not to appear in dangerous districts at night, also move on car. Another issue to be warned about is the language barrier—outside of the tourist spots, almost nobody speaks English. So you have to communicate with locals via Google Translate or in Spanish/Portuguese.  Last but not least, Brazil is a country with magnificent landscapes and reliefs - there are jungles, hills, plains, mountains, deserts and of course the sea. How to get a Brazilian passport? The standard naturalization procedure in Brazil is possible for those who have lived there for at least four years. However, obtaining citizenship is faster for investors or relatives of Brazilian citizens (spouses or parents)—it’s enough to live for three years. In Brazil, citizenship can be obtained not only by right of blood but also by right of soil. And to speed up this process, it is enough to move to the country and give birth to a child. Children born in Brazil receive citizenship immediately, while their parents can apply for it one year after birth. The processing time ranges from several months to two years. So, nomads having children born in Brazil get an opportunity to speed up the process of getting citizenship within 1-2 years. Fintech and Economy Brazil is a country of contrasts, also in the field of economy. Its GDP is about half that of all Latin American countries. At the same time, it has a high level of inequality and a large number of poor people. However, the situation is gradually improving, and the new president, Lula Da Silva, has made improving the welfare of citizens one of his main tasks. Local banks and fintech companies also capitalize on the economy's growth and innovating. Probably the biggest is the PIX system of fast money transfers and settlements. The system uses instant payments via QR codes, and commissions for PIX transfers are lower than they used to be. Taxation Among Brazil's few disadvantages for nomads, besides street crime, is the tax system. It is quite complicated, and the tax rates are comparable to those in Europe.  Brazilian residents are taxed on worldwide income, and the PIT rate is progressive up to 27.5%. Most nomads with incomes above $3000 will pay it at this rate, so it is better to calculate your budget immediately. Opening a business in Brazil is quite simple. You can open a company if you have already moved there and received a residence permit. However, the total rate of all corporate taxes in the country is about 35%. This includes a 15% profit tax, 9% of the social security fund, and a 10% tax increase if your company earns more than $45,000 annually. In addition, there are special taxes. For example, there is a tax on foreign payments (IOF) - you pay 4,38% for all card payments abroad. However, this tax probably will be canceled in 2029. Inheritance and gift tax rate in Brazil are up to 8%, and real estate tax of about 1-1.5% of its value. However, some taxes can make crypto nomads happy—the capital gain tax is only 15-20%, and that is the tax rate on the profit from an individual's sale of crypto. Crypto Regulation in Brazil Recently, Brazil became the first country in the world to approve a Spot ETF on Solana. Moreover, in September, BlackRock launched an Ethereum ETF on the local stock exchange—B3. One could easily put Brazil on the same footing as Hong Kong and the US on this basis—they allow crypto ETFs there, too. Even based on this news alone, the conclusion is that this country is one of the most innovative in fintech and cryptocurrencies in the world. And it's true. If we talk in general about crypto regulation in Brazil, business operations and transactions with crypto have been legal since 2019 through bylaws. In 2022, outgoing president Jair Bolsonaro signed a law passed by the parliament that introduced a licensing procedure for cryptocurrency exchanges and other VASPs in the country. The Central Bank and the local SEC CNV should be responsible for it. The law is still not fully implemented. Crypto business and VASP activity are legal in the country, but some details of their operations are still not defined in the law. This includes the licensing regime for crypto entities. Currently, to provide crypto services in Brazil, you need to open a company. However, licenses are required for transactions with fiat. Big local players like Mercado Pago, Mercado Bitcoin, and Ripio have fintech licenses. Also, local crypto card providers need them. Regulators promise that new legal acts for virtual assets will be in place as soon as this year. But its introduction may be postponed. Conclusion I think it's worth seeing Brazil to see if it's the right country for you. But in general, it has both economic prospects—a growing economy and a large crypto market—and a number of pleasant advantages for living—good climate and nature, relatively low prices, and easy legalization and naturalization. Brazil is the biggest economy in Latin America and together with Mexico it has 57% of nominal GDP in the region. And this is the long-term trend for the future - according to PWC report “The world in 2050” Brazil will be the 5th country in the world with GDP at PPPs after US, China, India and Indonesia. report report Moreover, Brazil has a prospective fintech market and, in comparison with other Latin American jurisdictions, low barriers to setting up a company or issuing crypto ETFs. Recently, BlackRock launched an Ethereum ETF in Brazil and listed it on the biggest local stock exchange, B3. Brazil also offers flexible conditions for immigrants, including living conditions and a fast naturalization procedure. In this article, I describe existing options for crypto nomads to relocate to Brazil, including living conditions and crypto regulations in the country. How move to Brazil? How move to Brazil? Although some authors call Brazil “bureaucratic” like other South American areas, it has a flexible immigration system. If you want to move there you have a wide range of options for digital nomads, which include: -Digital Nomad Visa -Student visa -Working visa -Family visa -Investor visa -Refugee status The basic options for digital nomads are a nomad visa and an investment visa. These options are pretty affordable. To get a residence permit of digital nomad you need to prove your monthly income of $1,500+ or put $18,000 in your bank account and this gives you a residence permit. Brazil is one of the few with such a visa in Latin America, which was launched recently in 2022. The number of rejections with properly executed documents is minimal. For an investor visa, an applicant should create a company with a capital of 500,000 BRL (about $100,000) or purchase a property from 1,000,000 BRL (about $200,000). An investor gets a permanent residence permit and can apply for Brazilian citizenship within 3 years. There are some exemptions for the required amount of real estate purchase in North-West provinces of Brazil - it may start from $100,000. Also, the minimal required investment in innovative businesses starts at $30,000. Brazil has a developed education system for student visa applicants with 98 public universities, and 8 of the 20 best Latam universities are located in the country. The only obstacle is that most programs of study are in Portuguese, although you can also find a proper university with Spanish or English programs. Living Conditions and Costs Living Conditions and Costs Brazil is the largest country in Latam and has 26 states, from Roraima and Amazonas on the north to Rio Grande de Sul on the South. The cost of living will vary depending on your income and preferences. Probably the most popular place among expats is Florianopolis. It’s safe and has beautiful nature and a climate. Other expats prefer 2 largest cities in the country - Rio de Janeiro and Sao Paulo.  Also on the coast there some other cities which attract immigrants - Recife, Vitoria, Salvador, Porto Allegre, Curitiba and some others. The capital of Brazil is a citiy Brasilia located close to the center of its territory and there is also a group of immigrants living there. Сosts of living in Brazil are quite affordable - depending on the place and district you choose, rent can cost from $300 up to $2000. For a single person, the minimum monthly cost of living may start at $1000. It is much cheaper than living in developed countries in Europe and the US. At the same time, compared to other Latin American countries such as Peru, Colombia, and Argentina, Brazil is somewhat more expensive. Also by this indicator, it loses to the affordable for nomadic countries of Asia, such as Vietnam and Thailand. If we talk about the difficulties faced by nomads in Brazil - there is quite a high crime rate in some areas, and there is a possibility of becoming a victim of theft or robbery. To avoid this, it is enough to choose a safer area of residence and not to appear in dangerous districts at night, also move on car. Another issue to be warned about is the language barrier—outside of the tourist spots, almost nobody speaks English. So you have to communicate with locals via Google Translate or in Spanish/Portuguese.  Last but not least, Brazil is a country with magnificent landscapes and reliefs - there are jungles, hills, plains, mountains, deserts and of course the sea. How to get a Brazilian passport? How to get a Brazilian passport? The standard naturalization procedure in Brazil is possible for those who have lived there for at least four years. However, obtaining citizenship is faster for investors or relatives of Brazilian citizens (spouses or parents)—it’s enough to live for three years. In Brazil, citizenship can be obtained not only by right of blood but also by right of soil. And to speed up this process, it is enough to move to the country and give birth to a child. Children born in Brazil receive citizenship immediately, while their parents can apply for it one year after birth. The processing time ranges from several months to two years. So, nomads having children born in Brazil get an opportunity to speed up the process of getting citizenship within 1-2 years. Fintech and Economy Fintech and Economy Brazil is a country of contrasts, also in the field of economy. Its GDP is about half that of all Latin American countries. At the same time, it has a high level of inequality and a large number of poor people. However, the situation is gradually improving, and the new president, Lula Da Silva, has made improving the welfare of citizens one of his main tasks. Local banks and fintech companies also capitalize on the economy's growth and innovating. Probably the biggest is the PIX system of fast money transfers and settlements. The system uses instant payments via QR codes, and commissions for PIX transfers are lower than they used to be. Taxation Taxation Among Brazil's few disadvantages for nomads, besides street crime, is the tax system. It is quite complicated, and the tax rates are comparable to those in Europe.  Brazilian residents are taxed on worldwide income, and the PIT rate is progressive up to 27.5%. Most nomads with incomes above $3000 will pay it at this rate, so it is better to calculate your budget immediately. Opening a business in Brazil is quite simple. You can open a company if you have already moved there and received a residence permit. However, the total rate of all corporate taxes in the country is about 35%. This includes a 15% profit tax, 9% of the social security fund, and a 10% tax increase if your company earns more than $45,000 annually. In addition, there are special taxes. For example, there is a tax on foreign payments (IOF) - you pay 4,38% for all card payments abroad. However, this tax probably will be canceled in 2029. Inheritance and gift tax rate in Brazil are up to 8%, and real estate tax of about 1-1.5% of its value. However, some taxes can make crypto nomads happy—the capital gain tax is only 15-20%, and that is the tax rate on the profit from an individual's sale of crypto. Crypto Regulation in Brazil Crypto Regulation in Brazil Recently, Brazil became the first country in the world to approve a Spot ETF on Solana. Moreover, in September, BlackRock launched an Ethereum ETF on the local stock exchange—B3. One could easily put Brazil on the same footing as Hong Kong and the US on this basis—they allow crypto ETFs there, too. Even based on this news alone, the conclusion is that this country is one of the most innovative in fintech and cryptocurrencies in the world. And it's true. approve a approve a launched launched If we talk in general about crypto regulation in Brazil, business operations and transactions with crypto have been legal since 2019 through bylaws. In 2022, outgoing president Jair Bolsonaro signed a law passed by the parliament that introduced a licensing procedure for cryptocurrency exchanges and other VASPs in the country. The Central Bank and the local SEC CNV should be responsible for it. The law is still not fully implemented. Crypto business and VASP activity are legal in the country, but some details of their operations are still not defined in the law. This includes the licensing regime for crypto entities. Currently, to provide crypto services in Brazil, you need to open a company. However, licenses are required for transactions with fiat. Big local players like Mercado Pago, Mercado Bitcoin, and Ripio have fintech licenses. Also, local crypto card providers need them. Regulators promise that new legal acts for virtual assets will be in place as soon as this year. But its introduction may be postponed. Conclusion I think it's worth seeing Brazil to see if it's the right country for you. But in general, it has both economic prospects—a growing economy and a large crypto market—and a number of pleasant advantages for living—good climate and nature, relatively low prices, and easy legalization and naturalization.

Brazil: Hot Spot for Nomads and Biggest Fintech Market in LatAm

Disclaimer: This article discusses the technical aspects of working with Spotify's API to create a playlist cover generator. While I'll be referencing a tool I developed for this purpose, the focus is on the development process and insights gained. The Genesis of the Idea As a developer and music enthusiast, I've always been fascinated by the potential of music APIs. The idea to create a Spotify playlist cover maker came from a simple desire to make playlist customization more accessible to users. In this article, I'll walk you through the development process, challenges faced, and lessons learned while working with Spotify's API. Understanding Spotify's API Before diving into development, it's crucial to understand Spotify's API. The Spotify for Developers platform provides comprehensive documentation and tools for working with their API. Key resources I found helpful: Spotify Web API Documentation
Authorization Guide
Endpoints Reference Tech Stack Selection For this project, I chose: Frontend: React.js with Tailwind CSS
Backend: Node.js with Express
Database: MongoDB
Image Processing: Sharp.js
API Integration: Spotify Web API This stack allowed for a dynamic UI, seamless Spotify integration, flexible data storage, and powerful image processing capabilities, all essential for creating a robust Spotify cover generator. Key Development Challenges 1. Spotify API Authentication Authentication is a crucial first step. Spotify uses OAuth 2.0, and here's a basic example of how to handle it: const SpotifyWebApi = require('spotify-web-api-node');

const spotifyApi = new SpotifyWebApi({
  clientId: process.env.SPOTIFY_CLIENT_ID,
  clientSecret: process.env.SPOTIFY_CLIENT_SECRET,
  redirectUri: process.env.SPOTIFY_REDIRECT_URI
});

app.get('/login', (req, res) => {
  const scopes = ['user-read-private', 'playlist-read-collaborative'];
  res.redirect(spotifyApi.createAuthorizeURL(scopes));
});

app.get('/callback', (req, res) => {
  const { code } = req.query;
  spotifyApi.authorizationCodeGrant(code).then(
    function(data) {
      spotifyApi.setAccessToken(data.body['access_token']);
      spotifyApi.setRefreshToken(data.body['refresh_token']);
      res.redirect('/');
    },
    function(err) {
      console.log('Something went wrong!', err);
      res.send(err);
    }
  );
}); 2. Fetching Playlist Data Once authenticated, you can fetch playlist data. Here's an example: async function getPlaylistData(playlistId) {
  try {
    const data = await spotifyApi.getPlaylist(playlistId);
    return {
      name: data.body.name,
      description: data.body.description,
      images: data.body.images,
      tracks: data.body.tracks.items.map(item => item.track.name)
    };
  } catch (error) {
    console.error('Error fetching playlist:', error);
    throw error;
  }
} 3. Image Processing For creating custom covers, I used Sharp.js. Here's a basic image processing function: const sharp = require('sharp');

async function processImage(buffer, text) {
  try {
    const image = sharp(buffer);
    const processedBuffer = await image
      .resize({
        width: 300,
        height: 300,
        fit: sharp.fit.cover,
        position: sharp.strategy.entropy
      })
      .composite([
        {
          input: Buffer.from(`<svg>...</svg>`),
          top: 10,
          left: 10
        }
      ])
      .toBuffer();
    
    return processedBuffer;
  } catch (error) {
    console.error('Error processing image:', error);
    throw error;
  }
} This function forms the core of the image manipulation in my playlist cover creator. Lessons Learned Rate Limiting is Crucial: Spotify's API has rate limits. Implementing proper error handling and retries is essential.
Keep Authentication Updated: Access tokens expire. Implement a robust token refresh mechanism to ensure uninterrupted access to the API.
Respect User Privacy: Only request the permissions you need. Spotify's Authorization Scopes guide is a must-read.
Optimize for Performance: Caching responses and optimizing API calls can significantly improve your application's performance. Looking Ahead As I continue to enhance the playlist cover generator, I'm exploring ideas like: Implementing AI-generated cover suggestions
Adding support for collaborative playlists
Creating a mobile app version For developers interested in music-related projects, Spotify's API offers a wealth of possibilities. I encourage you to explore their API Guidelines and Terms of Service for more information. Conclusion Working with Spotify's API to create a custom playlist cover tool has been an enriching experience. It's a testament to how developers can leverage powerful APIs to create tools that enhance users' music experiences. What innovative ideas do you have for using music APIs? What challenges have you faced in your API integration projects? Let's discuss in the comments! Tags: JavaScript, Web Development, Spotify API, Image Processing, React, API Integration Disclaimer: This article discusses the technical aspects of working with Spotify's API to create a playlist cover generator. While I'll be referencing a tool I developed for this purpose, the focus is on the development process and insights gained. Disclaimer: This article discusses the technical aspects of working with Spotify's API to create a playlist cover generator. While I'll be referencing a tool I developed for this purpose, the focus is on the development process and insights gained. tool I developed The Genesis of the Idea As a developer and music enthusiast, I've always been fascinated by the potential of music APIs. The idea to create a Spotify playlist cover maker came from a simple desire to make playlist customization more accessible to users. In this article, I'll walk you through the development process, challenges faced, and lessons learned while working with Spotify's API. Spotify playlist cover maker Understanding Spotify's API Before diving into development, it's crucial to understand Spotify's API. The Spotify for Developers platform provides comprehensive documentation and tools for working with their API. Spotify for Developers Key resources I found helpful: Spotify Web API Documentation Authorization Guide Endpoints Reference Spotify Web API Documentation Authorization Guide Endpoints Reference Tech Stack Selection For this project, I chose: Frontend: React.js with Tailwind CSS Backend: Node.js with Express Database: MongoDB Image Processing: Sharp.js API Integration: Spotify Web API Frontend: React.js with Tailwind CSS Backend: Node.js with Express Database: MongoDB Image Processing: Sharp.js API Integration: Spotify Web API This stack allowed for a dynamic UI, seamless Spotify integration, flexible data storage, and powerful image processing capabilities, all essential for creating a robust Spotify cover generator . Spotify cover generator Key Development Challenges 1. Spotify API Authentication Authentication is a crucial first step. Spotify uses OAuth 2.0, and here's a basic example of how to handle it: const SpotifyWebApi = require('spotify-web-api-node');

const spotifyApi = new SpotifyWebApi({
  clientId: process.env.SPOTIFY_CLIENT_ID,
  clientSecret: process.env.SPOTIFY_CLIENT_SECRET,
  redirectUri: process.env.SPOTIFY_REDIRECT_URI
});

app.get('/login', (req, res) => {
  const scopes = ['user-read-private', 'playlist-read-collaborative'];
  res.redirect(spotifyApi.createAuthorizeURL(scopes));
});

app.get('/callback', (req, res) => {
  const { code } = req.query;
  spotifyApi.authorizationCodeGrant(code).then(
    function(data) {
      spotifyApi.setAccessToken(data.body['access_token']);
      spotifyApi.setRefreshToken(data.body['refresh_token']);
      res.redirect('/');
    },
    function(err) {
      console.log('Something went wrong!', err);
      res.send(err);
    }
  );
}); const SpotifyWebApi = require('spotify-web-api-node');

const spotifyApi = new SpotifyWebApi({
  clientId: process.env.SPOTIFY_CLIENT_ID,
  clientSecret: process.env.SPOTIFY_CLIENT_SECRET,
  redirectUri: process.env.SPOTIFY_REDIRECT_URI
});

app.get('/login', (req, res) => {
  const scopes = ['user-read-private', 'playlist-read-collaborative'];
  res.redirect(spotifyApi.createAuthorizeURL(scopes));
});

app.get('/callback', (req, res) => {
  const { code } = req.query;
  spotifyApi.authorizationCodeGrant(code).then(
    function(data) {
      spotifyApi.setAccessToken(data.body['access_token']);
      spotifyApi.setRefreshToken(data.body['refresh_token']);
      res.redirect('/');
    },
    function(err) {
      console.log('Something went wrong!', err);
      res.send(err);
    }
  );
}); 2. Fetching Playlist Data Once authenticated, you can fetch playlist data. Here's an example: async function getPlaylistData(playlistId) {
  try {
    const data = await spotifyApi.getPlaylist(playlistId);
    return {
      name: data.body.name,
      description: data.body.description,
      images: data.body.images,
      tracks: data.body.tracks.items.map(item => item.track.name)
    };
  } catch (error) {
    console.error('Error fetching playlist:', error);
    throw error;
  }
} async function getPlaylistData(playlistId) {
  try {
    const data = await spotifyApi.getPlaylist(playlistId);
    return {
      name: data.body.name,
      description: data.body.description,
      images: data.body.images,
      tracks: data.body.tracks.items.map(item => item.track.name)
    };
  } catch (error) {
    console.error('Error fetching playlist:', error);
    throw error;
  }
} 3. Image Processing For creating custom covers, I used Sharp.js. Here's a basic image processing function: const sharp = require('sharp');

async function processImage(buffer, text) {
  try {
    const image = sharp(buffer);
    const processedBuffer = await image
      .resize({
        width: 300,
        height: 300,
        fit: sharp.fit.cover,
        position: sharp.strategy.entropy
      })
      .composite([
        {
          input: Buffer.from(`<svg>...</svg>`),
          top: 10,
          left: 10
        }
      ])
      .toBuffer();
    
    return processedBuffer;
  } catch (error) {
    console.error('Error processing image:', error);
    throw error;
  }
} const sharp = require('sharp');

async function processImage(buffer, text) {
  try {
    const image = sharp(buffer);
    const processedBuffer = await image
      .resize({
        width: 300,
        height: 300,
        fit: sharp.fit.cover,
        position: sharp.strategy.entropy
      })
      .composite([
        {
          input: Buffer.from(`<svg>...</svg>`),
          top: 10,
          left: 10
        }
      ])
      .toBuffer();
    
    return processedBuffer;
  } catch (error) {
    console.error('Error processing image:', error);
    throw error;
  }
} This function forms the core of the image manipulation in my playlist cover creator . playlist cover creator Lessons Learned Rate Limiting is Crucial: Spotify's API has rate limits. Implementing proper error handling and retries is essential. Keep Authentication Updated: Access tokens expire. Implement a robust token refresh mechanism to ensure uninterrupted access to the API. Respect User Privacy: Only request the permissions you need. Spotify's Authorization Scopes guide is a must-read. Optimize for Performance: Caching responses and optimizing API calls can significantly improve your application's performance. Rate Limiting is Crucial : Spotify's API has rate limits. Implementing proper error handling and retries is essential. Rate Limiting is Crucial Keep Authentication Updated : Access tokens expire. Implement a robust token refresh mechanism to ensure uninterrupted access to the API. Keep Authentication Updated Respect User Privacy : Only request the permissions you need. Spotify's Authorization Scopes guide is a must-read. Respect User Privacy Optimize for Performance : Caching responses and optimizing API calls can significantly improve your application's performance. Optimize for Performance Looking Ahead As I continue to enhance the playlist cover generator, I'm exploring ideas like: Implementing AI-generated cover suggestions Adding support for collaborative playlists Creating a mobile app version Implementing AI-generated cover suggestions Adding support for collaborative playlists Creating a mobile app version For developers interested in music-related projects, Spotify's API offers a wealth of possibilities. I encourage you to explore their API Guidelines and Terms of Service for more information. Conclusion Working with Spotify's API to create a custom playlist cover tool has been an enriching experience. It's a testament to how developers can leverage powerful APIs to create tools that enhance users' music experiences. custom playlist cover tool What innovative ideas do you have for using music APIs? What challenges have you faced in your API integration projects? Let's discuss in the comments! Tags: JavaScript, Web Development, Spotify API, Image Processing, React, API Integration Tags: JavaScript, Web Development, Spotify API, Image Processing, React, API Integration

From Idea to Implementation: Building a Spotify Playlist Cover Generator

من الفكرة إلى التنفيذ: إنشاء مولد أغلفة قائمة تشغيل Spotify

De la idea a la implementació: creació d'un generador de cobertes de llistes de reproducció de Spotify

Fra idé til implementering: Opbygning af en Spotify Playlist Cover Generator

De la idea a la implementación: creación de un generador de portadas para listas de reproducción de Spotify

از ایده تا اجرا: ساختن یک سازنده پوشش لیست پخش Spotify

Գաղափարից մինչև իրականացում. Spotify երգացանկերի ծածկույթի գեներատորի ստեղծում

アイデアから実装まで: Spotify プレイリスト カバー ジェネレーターの構築

Kobanda na likanisi tii na kosalela: Kotonga Générateur ya couverture ya playlist ya Spotify

Санаанаас хэрэгжүүлэх хүртэл: Spotify тоглуулах жагсаалтын хавтас үүсгэгчийг бүтээх

Från idé till implementering: Bygg en Spotify Playlist Cover Generator

Mula sa Ideya hanggang sa Pagpapatupad: Pagbuo ng Spotify Playlist Cover Generator

Fikirden Uygulamaya: Spotify Çalma Listesi Kapak Oluşturucu Oluşturma

There are many factors that make Ethereum a fundamentally different cryptocurrency from Bitcoin, and these crucial differences are playing out in real-time on Wall Street. Unlike the US Securities and Exchange Commission’s approval of Bitcoin ETFs in January, July’s acceptance of spot Ethereum ETFs came as something of a surprise. The commission had long viewed Bitcoin as an exception in the crypto landscape, acknowledging other coins as ‘securities’ compared to BTC’s status as a commodity. Despite this, Tuesday, July 23, 2024, saw the launch of nine spot Ether exchange-traded funds on Wall Street. One month on, are market commentators ready to call the debut a success? Ether’s Mixed Results Investor sentiment for the new ETFs has been mixed. The brightest spot Ether ETF, BlackRock’s iShares Ethereum Trust ETF, has been well on course to surpass $1 billion in net inflows just one month on from its launch. Elsewhere, other funds have been less lucrative in terms of welcoming inflows. In fact, the fund with the second highest level of inflows is Fidelity’s Ethereum Fund, with less than $400 million recorded one month after launching. The elephant in the room is Grayscale’s Ethereum Trust, which has recorded significant outflows due to its relatively high fee structure. With nearly $2.5 billion in outflows from this ETF, the total cumulative flow for Ether ETFs is negative by almost $500 million. Bitcoin Comparisons are Hasty According to estimates from Bloomberg ETF analyst Eric Balchunas, the demand for spot Ethereum ETFs could settle at around 15% to 20% of what we’ve seen for Bitcoin ETFs. There are many reasons why Ethereum commanding around one-fifth of Bitcoin’s ETF market inflows is logical. Firstly, as the oldest and most popular cryptocurrency in the world, Bitcoin has fewer technological capabilities than Ether, making it more comparable to gold. Meanwhile, Ethereum’s newer, more advanced blockchain frameworks mean it can host decentralized finance (DeFi) projects and other emerging technologies, making it more comparable to oil. At least this is the view of the Industrial and Commercial Bank of China (ICBC). Despite this, Bitcoin’s ETFs have also been vulnerable to substantial outflows of late, owing to a larger contraction of the cryptocurrency market and Wall Street’s recent stock sell-offs in early August. Crucially, Bitcoin’s status as ‘digital gold’ and the cyclical nature of the coin’s halving events, making the asset marginally more predictable, mean that its ETFs are more likely to see major institutional inflows like the $600 million Goldman Sachs and Morgan Stanley invested in spot Bitcoin ETFs. Battling ETH’s Downturn While the launch of Bitcoin’s ETFs brought a subsequent cryptocurrency rally towards a fresh all-time high value for BTC, no such good fortune appears forthcoming for Ether. In fact, the cryptocurrency has fallen 26% since its exchange-traded funds launched on Wall Street, with the coin’s supply increasing by 60,555 over the same period. Unlike Bitcoin’s fixed supply, which means no more than 21 million BTC can ever be minted, no such limits exist for Ether, meaning that its scarcity won’t play the same role in determining its value as Bitcoin. Although it’s worrying to see Ether struggle in the wake of net outflows for spot Ethereum ETFs, Aurelie Barthere, principal research analyst at analytics platform Nansen, highlights that Bitcoin has also been falling significantly over the same period, indicating that Ether’s downturn is more likely related to falling risk appetite among investors. It’s also worth noting that Wall Street’s market crash in early August was another challenge that Bitcoin didn’t have to encounter during its strong post-ETF rally in early 2024. Ethereum’s Unique Challenges Unlike Bitcoin, which enjoys a market dominance of more than 56% throughout the cryptocurrency landscape, Ethereum’s status as the world’s biggest altcoin is far from assured in the long term. Since its 2015 launch, Ethereum has relied on its status as a popular, technically advanced blockchain that developers use to host their DeFi projects. This has made ETH a cryptocurrency that’s closely linked to the burgeoning NFT landscape and blockchain innovations like smart contracts and P2P lending. However, now that the asset is approaching its 10th birthday, there are many newer, more advanced blockchains that offer faster transaction speeds and lower costs than Ethereum. Because of this, Ethereum is constantly having to evolve to fend off the chasing pack, a challenge that Bitcoin has never needed to counter. One specific threat can be found in Solana. With far lower transaction fees, less network congestion, and its innovative Proof-of-History consensus mechanism, Solana could be a tangible long-term threat to Ethereum, making investing in its ETFs a riskier prospect. Despite this, we may actually see Ethereum’s spot ETF act as a driving force for maintaining its status as a leader in blockchain technology. With long-term Wall Street adoption, even if it’s at 20% the scale of Bitcoin, Ethereum’s institutional acceptance could help to see off its plucky challengers throughout the crypto landscape. “Institutional investors familiar with ETFs as a financial instrument may be more inclined to invest in Ethereum through these funds,” highlights Maxim Manturov, head of investment research at Freedom24. “This could lead to substantial capital inflows and further growth and development of the Ethereum ecosystem.” Have Spot Ethererum ETFs Been a Success? The flows surrounding spot Ethereum ETFs one month from their launch make for difficult reading. However, it’s worth noting that the exchange-traded funds had the misfortune of launching just weeks before a major market crash occurred. For investors looking to embrace Ether on Wall Street, we may see spot Ethereum ETFs act as a strong foundation for growth that sees Ethereum fend off its technical competitors and reaffirm its status as the cryptocurrency landscape’s most functional altcoin. With expectations of a cryptocurrency market bull run in late 2024 and early 2025 still high, the success of spot Ethereum ETFs could be realized a little later down the line. For now, we’re still waiting for investors to really embrace this risky altcoin play. There are many factors that make Ethereum a fundamentally different cryptocurrency from Bitcoin, and these crucial differences are playing out in real-time on Wall Street. Ethereum Unlike the US Securities and Exchange Commission’s approval of Bitcoin ETFs in January, July’s acceptance of spot Ethereum ETFs came as something of a surprise. The commission had long viewed Bitcoin as an exception in the crypto landscape, acknowledging other coins as ‘securities’ compared to BTC’s status as a commodity. viewed Bitcoin as an exception viewed Bitcoin as an exception Despite this, Tuesday, July 23, 2024, saw the launch of nine spot Ether exchange-traded funds on Wall Street. One month on, are market commentators ready to call the debut a success? Ether’s Mixed Results Investor sentiment for the new ETFs has been mixed. The brightest spot Ether ETF, BlackRock’s iShares Ethereum Trust ETF, has been well on course to surpass $1 billion in net inflows just one month on from its launch. on course to surpass $1 billion on course to surpass $1 billion Elsewhere, other funds have been less lucrative in terms of welcoming inflows. In fact, the fund with the second highest level of inflows is Fidelity’s Ethereum Fund, with less than $400 million recorded one month after launching. The elephant in the room is Grayscale’s Ethereum Trust, which has recorded significant outflows due to its relatively high fee structure. With nearly $2.5 billion in outflows from this ETF, the total cumulative flow for Ether ETFs is negative by almost $500 million. Bitcoin Comparisons are Hasty According to estimates from Bloomberg ETF analyst Eric Balchunas, the demand for spot Ethereum ETFs could settle at around 15% to 20% of what we’ve seen for Bitcoin ETFs. settle at around 15% to 20% settle at around 15% to 20% There are many reasons why Ethereum commanding around one-fifth of Bitcoin’s ETF market inflows is logical. Firstly, as the oldest and most popular cryptocurrency in the world, Bitcoin has fewer technological capabilities than Ether, making it more comparable to gold. Meanwhile, Ethereum’s newer, more advanced blockchain frameworks mean it can host decentralized finance (DeFi) projects and other emerging technologies, making it more comparable to oil. At least this is the view of the Industrial and Commercial Bank of China (ICBC). this is the view this is the view Despite this, Bitcoin’s ETFs have also been vulnerable to substantial outflows of late, owing to a larger contraction of the cryptocurrency market and Wall Street’s recent stock sell-offs in early August. substantial outflows substantial outflows Crucially, Bitcoin’s status as ‘digital gold’ and the cyclical nature of the coin’s halving events, making the asset marginally more predictable, mean that its ETFs are more likely to see major institutional inflows like the $600 million Goldman Sachs and Morgan Stanley invested in spot Bitcoin ETFs. $600 million Goldman Sachs $600 million Goldman Sachs Battling ETH’s Downturn While the launch of Bitcoin’s ETFs brought a subsequent cryptocurrency rally towards a fresh all-time high value for BTC, no such good fortune appears forthcoming for Ether. In fact, the cryptocurrency has fallen 26% since its exchange-traded funds launched on Wall Street, with the coin’s supply increasing by 60,555 over the same period. fallen 26% fallen 26% Unlike Bitcoin’s fixed supply, which means no more than 21 million BTC can ever be minted, no such limits exist for Ether, meaning that its scarcity won’t play the same role in determining its value as Bitcoin. Although it’s worrying to see Ether struggle in the wake of net outflows for spot Ethereum ETFs, Aurelie Barthere, principal research analyst at analytics platform Nansen, highlights that Bitcoin has also been falling significantly over the same period, indicating that Ether’s downturn is more likely related to falling risk appetite among investors. related to falling risk appetite related to falling risk appetite It’s also worth noting that Wall Street’s market crash in early August was another challenge that Bitcoin didn’t have to encounter during its strong post-ETF rally in early 2024. Ethereum’s Unique Challenges Unlike Bitcoin, which enjoys a market dominance of more than 56% throughout the cryptocurrency landscape, Ethereum’s status as the world’s biggest altcoin is far from assured in the long term. more than 56% more than 56% Since its 2015 launch, Ethereum has relied on its status as a popular, technically advanced blockchain that developers use to host their DeFi projects. This has made ETH a cryptocurrency that’s closely linked to the burgeoning NFT landscape and blockchain innovations like smart contracts and P2P lending. However, now that the asset is approaching its 10th birthday, there are many newer, more advanced blockchains that offer faster transaction speeds and lower costs than Ethereum. Because of this, Ethereum is constantly having to evolve to fend off the chasing pack, a challenge that Bitcoin has never needed to counter. One specific threat can be found in Solana. With far lower transaction fees , less network congestion, and its innovative Proof-of-History consensus mechanism, Solana could be a tangible long-term threat to Ethereum, making investing in its ETFs a riskier prospect. far lower transaction fees far lower transaction fees Despite this, we may actually see Ethereum’s spot ETF act as a driving force for maintaining its status as a leader in blockchain technology. With long-term Wall Street adoption, even if it’s at 20% the scale of Bitcoin, Ethereum’s institutional acceptance could help to see off its plucky challengers throughout the crypto landscape. “Institutional investors familiar with ETFs as a financial instrument may be more inclined to invest in Ethereum through these funds,” highlights Maxim Manturov, head of investment research at Freedom24 . “This could lead to substantial capital inflows and further growth and development of the Ethereum ecosystem.” Freedom24 Freedom24 Have Spot Ethererum ETFs Been a Success? The flows surrounding spot Ethereum ETFs one month from their launch make for difficult reading. However, it’s worth noting that the exchange-traded funds had the misfortune of launching just weeks before a major market crash occurred. For investors looking to embrace Ether on Wall Street, we may see spot Ethereum ETFs act as a strong foundation for growth that sees Ethereum fend off its technical competitors and reaffirm its status as the cryptocurrency landscape’s most functional altcoin. With expectations of a cryptocurrency market bull run in late 2024 and early 2025 still high, the success of spot Ethereum ETFs could be realized a little later down the line. For now, we’re still waiting for investors to really embrace this risky altcoin play.

One Month On, Have Spot Ethereum ETFs Been a Success?

Donald Trump's former lawyer, Michael Cohen, infamously used AI to help generate a legal document sent to a federal judge. The AI used, Google's Bard (now with a new name, Gemini), made up fake court cases. And that's not even the worst of it. Two New York lawyers nearly torpedoed their careers by submitting a legal brief peppered with ChatGPT hallucinations. But these legal fumbles are just a small part of the problem. We're drowning in a sea of AI-generated content, and the consequences are a lot more serious than a few embarrassed attorneys. Think about it: What happens when the essay that got a student into medical school was actually written by GPT-4? Or when the analysis that landed someone a job at a top law firm was created by Claude? We could be looking at a future where our doctors, lawyers, and even airline pilots cheated their way through crucial exams with an AI assistant. Certainly, existing institutions aren’t perfect. Even in top med schools, professors say that many students lack basic knowledge. But AI could exacerbate this competency crisis. It's not just about academic integrity anymore – it's about public safety and the foundations of professional competence. And it doesn't stop there. Journalism, already battered by accusations of fake news, faces an existential threat. How can we trust breaking news stories when AI can spit out convincing articles faster than any human reporter? Social media becomes even murkier when bots armed with language models can flood platforms with eerily human-like posts. Current detection methods are failing The problem is clear: we desperately need a way to tell AI-generated content apart from the real deal. But here's the problem – as AI gets smarter, traditional detection methods are getting worse. Current approaches to spotting AI-generated text often rely on analyzing writing patterns, vocabulary usage, or subtle linguistic markers. But as language models become more sophisticated, they're learning to mimic human idiosyncrasies with tremendous accuracy. They can generate text with varied sentence structures, inject colloquialisms, and even make the occasional typo – all to sound more human. The key issue is cost. If you want to detect content generated by a highly-accurate AI model, you’ll need a highly accurate AI model for detection. The problem is that state-of-the-art models are usually too expensive to run at scale. Social media platforms like X are already struggling to break even. How much would it cost to detect AI generated content across 600 million active users? At that scale, using big AI models just isn’t feasible. Danube-3: A tiny AI detector Enter Danube-3, a new tiny AI model built by H2O.ai. While giants like OpenAI are building AI behemoths that require massive computational resources, H2O.ai has taken a different approach. They've created a model so small it can run on your smartphone, yet powerful enough to punch well above its weight class in language tasks. Trained on a staggering 6 trillion tokens, Danube-3 achieves performance levels that rival much larger models. On the 10-shot HellaSwag benchmark – a test of commonsense reasoning – Danube-3 outperforms Apple's much-touted OpenELM-3B-Instruct and goes toe-to-toe with Microsoft's Phi3 4B. This is no small feat for a model designed to run efficiently on edge devices. Danube-3 arrived at an important moment. As AI-generated content floods our digital spaces, this compact model offers a practical countermeasure. Its ability to run on smartphones brings robust AI detection out of data centers and into everyday devices. The education sector certainly stands to benefit. With AI-assisted cheating on the rise, professors could use Danube-3 to sift through stacks of papers, identifying those that warrant a more thorough examination. All that said, Danube-3 isn't a silver bullet. As detection methods improve, so do the AI models generating content. We're witnessing a technological tug-of-war, with each side constantly adapting to outmaneuver the other. While Danube-3 won't single-handedly solve the AI content crisis, it’s a step towards a future where we can coexist with AI on our own terms. Donald Trump's former lawyer, Michael Cohen, infamously used AI to help generate a legal document sent to a federal judge. The AI used, Google's Bard (now with a new name, Gemini), made up fake court cases . fake court cases fake court cases And that's not even the worst of it. Two New York lawyers nearly torpedoed their careers by submitting a legal brief peppered with ChatGPT hallucinations. But these legal fumbles are just a small part of the problem. We're drowning in a sea of AI-generated content, and the consequences are a lot more serious than a few embarrassed attorneys. New York lawyers New York lawyers Think about it: What happens when the essay that got a student into medical school was actually written by GPT-4? Or when the analysis that landed someone a job at a top law firm was created by Claude? We could be looking at a future where our doctors, lawyers, and even airline pilots cheated their way through crucial exams with an AI assistant. Certainly, existing institutions aren’t perfect. Even in top med schools , professors say that many students lack basic knowledge. But AI could exacerbate this competency crisis . It's not just about academic integrity anymore – it's about public safety and the foundations of professional competence. top med schools top med schools competency crisis competency crisis And it doesn't stop there. Journalism, already battered by accusations of fake news, faces an existential threat. How can we trust breaking news stories when AI can spit out convincing articles faster than any human reporter? Social media becomes even murkier when bots armed with language models can flood platforms with eerily human-like posts. flood platforms flood platforms Current detection methods are failing The problem is clear: we desperately need a way to tell AI-generated content apart from the real deal. But here's the problem – as AI gets smarter, traditional detection methods are getting worse. Current approaches to spotting AI-generated text often rely on analyzing writing patterns, vocabulary usage, or subtle linguistic markers. But as language models become more sophisticated, they're learning to mimic human idiosyncrasies with tremendous accuracy. They can generate text with varied sentence structures, inject colloquialisms, and even make the occasional typo – all to sound more human. The key issue is cost. If you want to detect content generated by a highly-accurate AI model, you’ll need a highly accurate AI model for detection. The problem is that state-of-the-art models are usually too expensive to run at scale. Social media platforms like X are already struggling to break even . struggling to break even struggling to break even How much would it cost to detect AI generated content across 600 million active users ? At that scale, using big AI models just isn’t feasible. 600 million active users 600 million active users Danube-3: A tiny AI detector Enter Danube-3 , a new tiny AI model built by H2O.ai. While giants like OpenAI are building AI behemoths that require massive computational resources, H2O.ai has taken a different approach. They've created a model so small it can run on your smartphone , yet powerful enough to punch well above its weight class in language tasks. Danube-3 Danube-3 run on your smartphone run on your smartphone Trained on a staggering 6 trillion tokens, Danube-3 achieves performance levels that rival much larger models. On the 10-shot HellaSwag benchmark – a test of commonsense reasoning – Danube-3 outperforms Apple's much-touted OpenELM-3B-Instruct and goes toe-to-toe with Microsoft's Phi3 4B. This is no small feat for a model designed to run efficiently on edge devices. Danube-3 arrived at an important moment. As AI-generated content floods our digital spaces, this compact model offers a practical countermeasure. Its ability to run on smartphones brings robust AI detection out of data centers and into everyday devices. The education sector certainly stands to benefit. With AI-assisted cheating on the rise, professors could use Danube-3 to sift through stacks of papers, identifying those that warrant a more thorough examination. All that said, Danube-3 isn't a silver bullet. As detection methods improve, so do the AI models generating content. We're witnessing a technological tug-of-war, with each side constantly adapting to outmaneuver the other. While Danube-3 won't single-handedly solve the AI content crisis, it’s a step towards a future where we can coexist with AI on our own terms.

Spotting AI Fakes Just Got Easier, Thanks to Danube3

Authors:
(1) Wenxuan Wang, The Chinese University of Hong Kong, Hong Kong, China;
(2) Haonan Bai, The Chinese University of Hong Kong, Hong Kong, China
(3) Jen-tse Huang, The Chinese University of Hong Kong, Hong Kong, China;
(4) Yuxuan Wan, The Chinese University of Hong Kong, Hong Kong, China;
(5) Youliang Yuan, The Chinese University of Hong Kong, Shenzhen Shenzhen, China
(6) Haoyi Qiu University of California, Los Angeles, Los Angeles, USA;
(7) Nanyun Peng, University of California, Los Angeles, Los Angeles, USA
(8) Michael Lyu, The Chinese University of Hong Kong, Hong Kong, China. Table of Links Abstract 1 Introduction 2 Background 3 Approach and Implementation 3.1 Seed Image Collection and 3.2 Neutral Prompt List Collection 3.3 Image Generation and 3.4 Properties Assessment 3.5 Bias Evaluation 4 Evaluation 4.1 Experimental Setup 4.2 RQ1: Effectiveness of BiasPainter 4.3 RQ2 - Validity of Identified Biases 4.4 RQ3 - Bias Mitigation 5 Threats to Validity 6 Related Work 7 Conclusion, Data Availability, and References 1 INTRODUCTION Image generation models, which generate images from a given text, have recently drawn a lot of interest from academia and the industry. For example, Stable Diffusion [37], an open-sourced latent text-to-image diffusion model, has 60K stars on github [1]. And Midjourney, an AI image generation commercial software product launched on July 2022, has more than 15 million users [13]. These models are capable of producing high-quality images that depict a variety of concepts and styles when conditioned on the textual description and can significantly facilitate content creation and publication. Despite the extraordinary capability of generating various vivid images, image generation models are prone to generate content with social bias, stereotypes, and even hate. For example, previous work has found that text-to-image generation models tend to associate males with software engineers, females with housekeepers, and white people with attractive people [3]. It is because these models have been trained on massive datasets of images and text scraped from the web, which is known to contain stereotyped, biased, and toxic contents [21]. The ramifications of such biased content are far-reaching, from reinforcing stereotypes to causing brand and reputation damage and even impacting individual well-being. To mitigate the social bias and stereotypes in image generation models, an essential step is to trigger the biased content and evaluate the fairness of such models. Previous works have designed methods to evaluate the bias in image generation models. For example, [12] generates images from a set of words that should not be related to a specific gender or race (e.g., secretary, rich person). Then, with a pre-trained image-text alignment model named CLIP [35], the authors classify the generated images into gender and race categories. However, these works suffer from several drawbacks. First, their accuracy is relatively low. Detecting race and gender is not an easy task, considering the high diversity of generating style and content. According to their human evaluation results, the detecting method is not accurate (e.g., [12] only achieves 40% on race), leading to concern about the effectiveness and soundness of the method. Second, their scope is limited. Previous work [3] involves human annotation to evaluate the bias in generated images, aiming for an accurate evaluation. However, this manual method needs extensive human effort and is not scalable. Third, there is a lack of comprehensive evaluation across various demographic groups. According to a previous study [3], more than 90% of the images produced by image generation models are of white people, which implies the comprehensive evaluation of the bias in other groups, such as East Asian people and black people. In this paper, we design a novel metamorphic testing framework, BiasPainter, that can automatically, comprehensively and accurately measure the social bias in image generation models. In particular, BiasPainter operates by inputting both images and text (prompts) into these models and then analyzing how the models edit these images. Under this setting, we define a metamorphic relation that when prompted with gender, race, and age-neutral prompts, the gender, race, and age of the original image should not significantly alter after editing. Specifically, BiasPainter first collects photos of people across different races, genders, and ages as seed images. Then, it prompts the model to edit each seed image. The prompts are selected from a pre-defined comprehensive gender/racial/age-neutral prompt list covering professions, objects, personalities and activities. After that, BiasPainter measures the changes from the seed image to the generated image according to race, gender, and age. An ideal case is that race, gender, and age do not change significantly under the editing with a gender, racial, and age-neutral prompt. On the other hand, if a model is prone to change significantly and consistently (e.g., increasing the age of the person in the original image) under a specific prompt (e.g., "a photo of a mean person"), BiasPainter detects a biased association(e.g., between elder and mean). To evaluate the effectiveness of BiasPainter, we conduct experiments on five widely-deployed image generation models and software products, stable-diffusion 1.5, stable-diffusion 2.1, stablediffusion XL, Midjourney and InstructPix2Pix. To consider the stochastic nature of generative AI, we adopt three photos from each combination of gender, race, and age, ending up with 54 seed images, and we adopt 228 prompts to edit each seed image. For each image generation model, we generate 54*228=12312 images to evaluate the bias. The results show that 100% of the generated test cases from BiasPainter can successfully trigger social bias in image generation models. In addition, based on human evaluation, BiasPainter can achieve an accuracy of 90.8% in identifying the bias in images, which is significantly higher than the performance reported in the previous work (40% on race) [12]. Furthermore, BiasPainter can offer valuable insights into the nature and extent of biases within these models and serves as a tool for evaluating bias mitigation strategies, aiding developers in improving model fairness. We summarize the main contributions of this work as follows: • We design and implement BiasPainter, the first metamorphic testing framework for comprehensively measuring the social biases in image generation models. • We perform an extensive evaluation of BiasPainter on five widely deployed commercial conversation systems and research models. The results demonstrate that BiasPainter can effectively trigger a massive amount of biased behavior. • We release the dataset, the code of BiasPainter, and all experimental results, which can facilitate real-world fairness testing tasks and further follow-up research. Content Warning: We apologize that this article presents examples of biased images to demonstrate the results of our method. For the mental health of participating researchers, we prompted a content warning in every stage of this work to the researchers and annotators, and told them that they were free to leave anytime during the study. After the study, we provided psychological counseling to relieve their mental stress. This paper is available on arxiv under CC0 1.0 DEED license. [1] https://github.com/CompVis/stable-diffusion Authors: (1) Wenxuan Wang, The Chinese University of Hong Kong, Hong Kong, China; (2) Haonan Bai, The Chinese University of Hong Kong, Hong Kong, China (3) Jen-tse Huang, The Chinese University of Hong Kong, Hong Kong, China; (4) Yuxuan Wan, The Chinese University of Hong Kong, Hong Kong, China; (5) Youliang Yuan, The Chinese University of Hong Kong, Shenzhen Shenzhen, China (6) Haoyi Qiu University of California, Los Angeles, Los Angeles, USA; (7) Nanyun Peng, University of California, Los Angeles, Los Angeles, USA (8) Michael Lyu, The Chinese University of Hong Kong, Hong Kong, China. Authors: Authors: (1) Wenxuan Wang, The Chinese University of Hong Kong, Hong Kong, China; (2) Haonan Bai, The Chinese University of Hong Kong, Hong Kong, China (3) Jen-tse Huang, The Chinese University of Hong Kong, Hong Kong, China; (4) Yuxuan Wan, The Chinese University of Hong Kong, Hong Kong, China; (5) Youliang Yuan, The Chinese University of Hong Kong, Shenzhen Shenzhen, China (6) Haoyi Qiu University of California, Los Angeles, Los Angeles, USA; (7) Nanyun Peng, University of California, Los Angeles, Los Angeles, USA (8) Michael Lyu, The Chinese University of Hong Kong, Hong Kong, China. Table of Links Abstract Abstract 1 Introduction 1 Introduction 2 Background 2 Background 3 Approach and Implementation 3 Approach and Implementation 3.1 Seed Image Collection and 3.2 Neutral Prompt List Collection 3.1 Seed Image Collection and 3.2 Neutral Prompt List Collection 3.3 Image Generation and 3.4 Properties Assessment 3.3 Image Generation and 3.4 Properties Assessment 3.5 Bias Evaluation 3.5 Bias Evaluation 4 Evaluation 4 Evaluation 4.1 Experimental Setup 4.1 Experimental Setup 4.2 RQ1: Effectiveness of BiasPainter 4.2 RQ1: Effectiveness of BiasPainter 4.3 RQ2 - Validity of Identified Biases 4.3 RQ2 - Validity of Identified Biases 4.4 RQ3 - Bias Mitigation 4.4 RQ3 - Bias Mitigation 5 Threats to Validity 5 Threats to Validity 6 Related Work 6 Related Work 7 Conclusion, Data Availability, and References 7 Conclusion, Data Availability, and References 1 INTRODUCTION Image generation models, which generate images from a given text, have recently drawn a lot of interest from academia and the industry. For example, Stable Diffusion [37], an open-sourced latent text-to-image diffusion model, has 60K stars on github [1]. And Midjourney, an AI image generation commercial software product launched on July 2022, has more than 15 million users [13]. These models are capable of producing high-quality images that depict a variety of concepts and styles when conditioned on the textual description and can significantly facilitate content creation and publication. Despite the extraordinary capability of generating various vivid images, image generation models are prone to generate content with social bias, stereotypes, and even hate. For example, previous work has found that text-to-image generation models tend to associate males with software engineers, females with housekeepers, and white people with attractive people [3]. It is because these models have been trained on massive datasets of images and text scraped from the web, which is known to contain stereotyped, biased, and toxic contents [21]. The ramifications of such biased content are far-reaching, from reinforcing stereotypes to causing brand and reputation damage and even impacting individual well-being. To mitigate the social bias and stereotypes in image generation models, an essential step is to trigger the biased content and evaluate the fairness of such models. Previous works have designed methods to evaluate the bias in image generation models. For example, [12] generates images from a set of words that should not be related to a specific gender or race (e.g., secretary, rich person). Then, with a pre-trained image-text alignment model named CLIP [35], the authors classify the generated images into gender and race categories. However, these works suffer from several drawbacks. First, their accuracy is relatively low. Detecting race and gender is not an easy task, considering the high diversity of generating style and content. According to their human evaluation results, the detecting method is not accurate (e.g., [12] only achieves 40% on race), leading to concern about the effectiveness and soundness of the method. Second, their scope is limited. Previous work [3] involves human annotation to evaluate the bias in generated images, aiming for an accurate evaluation. However, this manual method needs extensive human effort and is not scalable. Third, there is a lack of comprehensive evaluation across various demographic groups. According to a previous study [3], more than 90% of the images produced by image generation models are of white people, which implies the comprehensive evaluation of the bias in other groups, such as East Asian people and black people. In this paper, we design a novel metamorphic testing framework, BiasPainter, that can automatically, comprehensively and accurately measure the social bias in image generation models. In particular, BiasPainter operates by inputting both images and text (prompts) into these models and then analyzing how the models edit these images. Under this setting, we define a metamorphic relation that when prompted with gender, race, and age-neutral prompts, the gender, race, and age of the original image should not significantly alter after editing. Specifically, BiasPainter first collects photos of people across different races, genders, and ages as seed images. Then, it prompts the model to edit each seed image. The prompts are selected from a pre-defined comprehensive gender/racial/age-neutral prompt list covering professions, objects, personalities and activities. After that, BiasPainter measures the changes from the seed image to the generated image according to race, gender, and age. An ideal case is that race, gender, and age do not change significantly under the editing with a gender, racial, and age-neutral prompt. On the other hand, if a model is prone to change significantly and consistently (e.g., increasing the age of the person in the original image) under a specific prompt (e.g., "a photo of a mean person"), BiasPainter detects a biased association(e.g., between elder and mean). To evaluate the effectiveness of BiasPainter, we conduct experiments on five widely-deployed image generation models and software products, stable-diffusion 1.5, stable-diffusion 2.1, stablediffusion XL, Midjourney and InstructPix2Pix. To consider the stochastic nature of generative AI, we adopt three photos from each combination of gender, race, and age, ending up with 54 seed images, and we adopt 228 prompts to edit each seed image. For each image generation model, we generate 54*228=12312 images to evaluate the bias. The results show that 100% of the generated test cases from BiasPainter can successfully trigger social bias in image generation models. In addition, based on human evaluation, BiasPainter can achieve an accuracy of 90.8% in identifying the bias in images, which is significantly higher than the performance reported in the previous work (40% on race) [12]. Furthermore, BiasPainter can offer valuable insights into the nature and extent of biases within these models and serves as a tool for evaluating bias mitigation strategies, aiding developers in improving model fairness. We summarize the main contributions of this work as follows: • We design and implement BiasPainter , the first metamorphic testing framework for comprehensively measuring the social biases in image generation models. BiasPainter • We perform an extensive evaluation of BiasPainter on five widely deployed commercial conversation systems and research models. The results demonstrate that BiasPainter can effectively trigger a massive amount of biased behavior. • We release the dataset, the code of BiasPainter, and all experimental results, which can facilitate real-world fairness testing tasks and further follow-up research. Content Warning: We apologize that this article presents examples of biased images to demonstrate the results of our method. For the mental health of participating researchers, we prompted a content warning in every stage of this work to the researchers and annotators, and told them that they were free to leave anytime during the study. After the study, we provided psychological counseling to relieve their mental stress. Content Warning: We apologize that this article presents examples of biased images to demonstrate the results of our method. For the mental health of participating researchers, we prompted a content warning in every stage of this work to the researchers and annotators, and told them that they were free to leave anytime during the study. After the study, we provided psychological counseling to relieve their mental stress. Content Warning: This paper is available on arxiv under CC0 1.0 DEED license. This paper is available on arxiv under CC0 1.0 DEED license. available on arxiv [1] https://github.com/CompVis/stable-diffusion

How BiasPainter is Turning the Spotlight on Bias in Image Generation Models

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