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Many people — particularly those outside the tech world — were introduced to OpenAI in November 2022, when the company launched its now-ubiquitous ChatGPT tool. However, it has been around for a lot longer than that. OpenAI captured headlines again more recently due to plans for a corporate restructuring that would mean it leaves behind its nonprofit roots. OpenAI’s Journey OpenAI started in 2015 as a nonprofit research organization dedicated to developing artificial intelligence tools that would benefit humanity as a whole, unrestricted by the need to turn a profit. Elon Musk and current OpenAI CEO Sam Altman were involved then, but Musk left in 2018. A year later, OpenAI added a for-profit subsidiary, turning the company into a hybrid for-profit and nonprofit entity in what it called a “capped profit” structure. Leaders at the time believed this change would keep OpenAI true to its roots while allowing it to use market power to grow its operations and revenue. The “capped” part of the structure’s name refers to limitations whereby the profits returned to the company’s investors can only be roughly 100 times what they put into the organization. Now, OpenAI’s structure seems set to change again, this time to a for-profit benefit corporation. This type of business focuses on sustainability and social responsibility in addition to profitmaking. One of the biggest differences about this development is that it would result in OpenAI’s nonprofit board losing control. For now, the nonprofit board has full control over the company’s for-profit arm. Another change is that Altman would receive equity for the first time — which could be worth billions. Moreover, the transition to a for-profit benefit company would remove the cap on investors’ returns. However, an interesting clarification came from an OpenAI representative who said the company’s nonprofit component would still exist and remain a core part of its goals. When will this restructuring occur? That’s anyone’s guess since those involved are still hashing out the details with legal professionals. However, as soon as the news reached major reporting outlets, some people started thinking about what it could mean for OpenAI and artificial intelligence in general. What Will the Restructuring Mean? Some people who have analyzed the matter said OpenAI’s restructuring might mean it will begin operating more like a startup. Investors would probably like that, but could it result in fewer checks and balances affecting products and processes? Contrary to its name, the company has never been upfront about its operations — employees must sign nondisclosure agreements that stop them from raising concerns to federal regulators. Additionally, a group of people working in the AI industry — including former OpenAI employees — signed an open letter explaining that those working on pioneering innovations in artificial intelligence have strong financial incentives to resist oversight and not share knowledge of what their products could or could not do with governments or civil society entities. Numerous employees have recently left OpenAI, with some, speaking anonymously, saying that the catalyst was a lack of trust in Altman and his ability to make AI work safely. Many have kept quiet because of a reported agreement people must sign when leaving the company that prevents them from speaking disparagingly about it. Some former workers who did not sign such paperwork have spoken out about their worries about the businesses’ increasingly powerful AI and the people who want it built not proceeding carefully enough. If OpenAI’s nonprofit board loses its current control, that may make the company’s leaders feel more equipped to proceed with whatever projects garner the most attention. Rushing to get these offerings on the market could also mean it doesn’t take safety as seriously as it should. OpenAI’s Impact on the Future of Artificial Intelligence Now that many AI tools are widely available, more people are insisting on controls that limit their potential applications. Others worry about the future, not necessarily because they believe that artificial intelligence will become smarter than humans, but due to privacy concerns, the prospect of job losses, and the potential for people to misuse AI. The shift to a for-profit model might also raise questions about priorities between profit and ethical AI development. Because of these concerns, transparency becomes even more crucial for the growing number of for-profit AI companies as they try to attract stakeholders — particularly as 60% of people cite transparency as the most important brand trait, according to one study. Embracing transparency can help build trust and reassure stakeholders that OpenAI remains committed to its foundational goals, even as its business model evolves. However, that sentiment could become problematic since OpenAI already has a reputation for being tight-lipped about its activities. People appreciate transparent companies, and it is arguably even more important to show that trait when the business specializes in a technology that the public views as largely foreign and new. For the average person who is merely curious about AI and how to use it, however, they likely won’t feel the impacts of OpenAI’s likely restructuring — at least not at first. Regular consumers will mostly pay attention to which products the company releases next. If those offerings become extremely profitable, such results will signal to its leaders that they should keep doing more of the same. It’s worth highlighting how OpenAI and the industry, in general, are already highly influential, with economic analysts saying generative AI will cause a 7% increase in global gross domestic product, resulting in a difference worth trillions of dollars. A related aspect is how relatively quickly people have gotten to know some of its tools and used them to do business and everyday tasks differently. Many individuals — even those who do not consider themselves tech-savvy — use AI numerous times throughout a typical week. That is almost certainly because of how accessible ChatGPT has become. Its popularity has helped OpenAI come into the mainstream, which arguably has implications for wider society — regardless of the ultimate impact of the eventual restructuring. An Uncertain But AI-Driven Future It’s too early to know the impacts of OpenAI transitioning to a for-profit benefit corporation. However, people can expect some aspects of its internal operations, stakeholder impact, and leadership to change in the coming months and years. We know with more confidence that artificial intelligence will continue playing a role in many people’s lives and shaping the tools they are now accustomed to using. Since OpenAI has enjoyed so much momentum in an increasingly crowded industry, its main task for the foreseeable future is to maintain it. If that happens, it will continue playing a significant role in artificial intelligence’s future, even if people don’t know what that looks like yet. Many people — particularly those outside the tech world — were introduced to OpenAI in November 2022, when the company launched its now-ubiquitous ChatGPT tool. However, it has been around for a lot longer than that. OpenAI captured headlines again more recently due to plans for a corporate restructuring that would mean it leaves behind its nonprofit roots. OpenAI’s Journey OpenAI started in 2015 as a nonprofit research organization dedicated to developing artificial intelligence tools that would benefit humanity as a whole, unrestricted by the need to turn a profit. Elon Musk and current OpenAI CEO Sam Altman were involved then, but Musk left in 2018. A year later, OpenAI added a for-profit subsidiary, turning the company into a hybrid for-profit and nonprofit entity in what it called a “capped profit” structure. Leaders at the time believed this change would keep OpenAI true to its roots while allowing it to use market power to grow its operations and revenue. The “capped” part of the structure’s name refers to limitations whereby the profits returned to the company’s investors can only be roughly 100 times what they put into the organization. roots while allowing it to use roots while allowing it to use Now, OpenAI’s structure seems set to change again, this time to a for-profit benefit corporation. This type of business focuses on sustainability and social responsibility in addition to profitmaking. One of the biggest differences about this development is that it would result in OpenAI’s nonprofit board losing control. For now, the nonprofit board has full control over the company’s for-profit arm. Another change is that Altman would receive equity for the first time — which could be worth billions. Moreover, the transition to a for-profit benefit company would remove the cap on investors’ returns. However, an interesting clarification came from an OpenAI representative who said the company’s nonprofit component would still exist and remain a core part of its goals. nonprofit component would still exist nonprofit component would still exist When will this restructuring occur? That’s anyone’s guess since those involved are still hashing out the details with legal professionals. However, as soon as the news reached major reporting outlets, some people started thinking about what it could mean for OpenAI and artificial intelligence in general. What Will the Restructuring Mean? Some people who have analyzed the matter said OpenAI’s restructuring might mean it will begin operating more like a startup. Investors would probably like that, but could it result in fewer checks and balances affecting products and processes? Contrary to its name, the company has never been upfront about its operations — employees must sign nondisclosure agreements that stop them from raising concerns to federal regulators. must sign nondisclosure agreements must sign nondisclosure agreements Additionally, a group of people working in the AI industry — including former OpenAI employees — signed an open letter explaining that those working on pioneering innovations in artificial intelligence have strong financial incentives to resist oversight and not share knowledge of what their products could or could not do with governments or civil society entities. Numerous employees have recently left OpenAI, with some, speaking anonymously, saying that the catalyst was a lack of trust in Altman and his ability to make AI work safely. Many have kept quiet because of a reported agreement people must sign when leaving the company that prevents them from speaking disparagingly about it. Some former workers who did not sign such paperwork have spoken out about their worries about the businesses’ increasingly powerful AI and the people who want it built not proceeding carefully enough. businesses’ increasingly powerful AI businesses’ increasingly powerful AI If OpenAI’s nonprofit board loses its current control, that may make the company’s leaders feel more equipped to proceed with whatever projects garner the most attention. Rushing to get these offerings on the market could also mean it doesn’t take safety as seriously as it should. OpenAI’s Impact on the Future of Artificial Intelligence Now that many AI tools are widely available, more people are insisting on controls that limit their potential applications. Others worry about the future, not necessarily because they believe that artificial intelligence will become smarter than humans, but due to privacy concerns, the prospect of job losses, and the potential for people to misuse AI. The shift to a for-profit model might also raise questions about priorities between profit and ethical AI development. Because of these concerns, transparency becomes even more crucial for the growing number of for-profit AI companies as they try to attract stakeholders — particularly as 60% of people cite transparency as the most important brand trait, according to one study. Embracing transparency can help build trust and reassure stakeholders that OpenAI remains committed to its foundational goals, even as its business model evolves. 60% of people cite transparency 60% of people cite transparency However, that sentiment could become problematic since OpenAI already has a reputation for being tight-lipped about its activities. People appreciate transparent companies, and it is arguably even more important to show that trait when the business specializes in a technology that the public views as largely foreign and new. For the average person who is merely curious about AI and how to use it, however, they likely won’t feel the impacts of OpenAI’s likely restructuring — at least not at first. Regular consumers will mostly pay attention to which products the company releases next. If those offerings become extremely profitable, such results will signal to its leaders that they should keep doing more of the same. It’s worth highlighting how OpenAI and the industry, in general, are already highly influential, with economic analysts saying generative AI will cause a 7% increase in global gross domestic product, resulting in a difference worth trillions of dollars. A related aspect is how relatively quickly people have gotten to know some of its tools and used them to do business and everyday tasks differently. Many individuals — even those who do not consider themselves tech-savvy — use AI numerous times throughout a typical week. will cause a 7% increase will cause a 7% increase That is almost certainly because of how accessible ChatGPT has become. Its popularity has helped OpenAI come into the mainstream, which arguably has implications for wider society — regardless of the ultimate impact of the eventual restructuring. An Uncertain But AI-Driven Future It’s too early to know the impacts of OpenAI transitioning to a for-profit benefit corporation. However, people can expect some aspects of its internal operations, stakeholder impact, and leadership to change in the coming months and years. We know with more confidence that artificial intelligence will continue playing a role in many people’s lives and shaping the tools they are now accustomed to using. Since OpenAI has enjoyed so much momentum in an increasingly crowded industry, its main task for the foreseeable future is to maintain it. If that happens, it will continue playing a significant role in artificial intelligence’s future, even if people don’t know what that looks like yet.

Inside OpenAI's Path to Becoming a For-Profit Powerhouse

The internet has long been a powerful resource, partially because it connects people. Relatedly, it allows like-minded individuals to come together and communicate about shared interests. Some parties have taken such activities to the next level, deciding to collaborate on common goals. This phenomenon has led to a rise in so-called cyber militias. Hacktivism, online armies, and online/digital activism are other synonyms for this emerging trend. What Is the Purpose of Cyber Militias? Although some of the earliest cyber militias banded together for political reasons, some participants have broadened their causes to include social and environmental aims. That characteristic explains why cyber activism has become more popular over the last several years. Wars, climate change, and civil unrest are some of the many factors that dominate people’s lives. Many are not in positions where they can safely attend protests or take other in-person actions. However, the internet is a highly accessible resource that individuals can harness for mobilization, communication, and solidarity. Relatedly, a 2023 analysis found that 92% of jobs require digital skills. Suppose people already have those capabilities because they use them in their work. Some might understandably want to apply them during their downtime if they feel compelled to act in response to things they see occurring in their society. The Internet as a Content Vehicle Another likely reason why cyber militias have cropped up relatively recently is that the internet makes it incredibly easy to distribute information to the masses in seconds. Traditional activism required printing flyers and taking the time to post them in prominent areas or give them to people at events. However, individuals can use the internet to do the equivalent of that in seconds. For example, estimates suggest that approximately 126 million Americans saw Russia-affiliated content during the 2016 United States presidential campaign, and that figure concerned Facebook alone. That massive reach also highlights how people can participate in cyber militias from anywhere and potentially influence the goings-on in other countries. Importantly, a worrisome part of internet-related content distribution is that anyone can get involved, and there is no guarantee of the validity of whatever they say. If the online content comes from a reporter at a well-known national or international news outlet, the employer's reputation strengthens the information distributor’s credibility. However, the accessibility and reach of social media combine to allow virtually anyone to spread information online. Things have gotten even more complicated with the increasing availability of AI-based video and picture tools. These products can create people’s faces from scratch or swap them. That means individuals cannot necessarily believe everything they see. However, a connected problem is that far too few internet users take the time to check facts and get the whole picture. Additionally, if people can push content far and wide, it greatly increases the chances of the masses seeing it. Hacker-Activists Disrupting Websites and Infrastructure Most cyber militias do not solely operate by publishing or creating content on a large scale that may not be wholly truthful or trustworthy. Instead, they also plan coordinated hacks that make websites or online services inoperable. Since so many essential parts of daily activities also have online components, hackers have disrupted those, too. Ukraine has one of the most recent examples of a cyber militia, with many volunteers joining its forces from all over the world. In July 2024, this group collectively targeted numerous Russian banks and ATMs, with the effects spreading to many payment systems and financial apps. Some hacktivists also plan their actions to ensure ripple effects across some industries that are not historically well-prepared to defend against cyberattacks. One example came when online activists targeted universities in the United Kingdom for their support of the Israeli government’s actions against the Palestinians. Most people know that the healthcare industry is a frequent attack target, and many decision-makers have responded accordingly. However, many educational institutions still have significant room for improvement, and hackers capitalize on that. Plus, many college campuses are like miniature cities, featuring branded eateries, convenience stores, health services offices, and more. A well-orchestrated cyberattack can go far beyond canceled classes. Ransomware demands given to higher education entities can surpass $300,000 on average, emphasizing the tremendous associated expenses for an ill-prepared organization. Inspiring Transitions From Behind Screens to on the Streets Although some cyber militias only feature people who make impacts while sitting at their keyboards, some efforts have caused a shift whereby some participants realized they must go beyond that kind of activism and populate public spaces. One reason for this is that some individuals are eager to take part but need help figuring out how to get started. The internet can connect them to the necessary resources, help them see how specific protest topics relate to their lives, and inspire them to join the crowds of those standing up for causes. For example, earlier in 2024, Kenyans protested against a controversial tax bill. Although those events began in the capital city, they quickly spread to other parts of the country. The internet was a large part of why that progression occurred. Someone with a background in internet mobilization and activism explained how the online component was instrumental in reaching marginalized groups. Additionally, the internet and various associated technologies have increased the speed at which people can create content and how effectively they can engage others. Another related aspect concerns the facilitation of online crowdfunding through dedicated portals. Some interested parties who are committed to the respective causes cannot feasibly attend in-person protests, even if the internet initially interests them. However, it is easy to send online payments to support causes and help participants obtain the supplies needed for the desired impact. Actions Can Occur Beyond Battlefields Most traditional discussions of militias relate to groups of citizens who come together to support official militaries and supplement their efforts. Conversely, militias can also rise when people want to oppose the military or government. These things remain valid, but the modern difference is that the internet and devices that connect to it have become powerful tools for getting heard and noticed during times of increasing upheaval. The internet has long been a powerful resource, partially because it connects people. Relatedly, it allows like-minded individuals to come together and communicate about shared interests. Some parties have taken such activities to the next level, deciding to collaborate on common goals. This phenomenon has led to a rise in so-called cyber militias. Hacktivism, online armies, and online/digital activism are other synonyms for this emerging trend. The internet has long been a powerful resource, partially because it connects people. Relatedly, it allows like-minded individuals to come together and communicate about shared interests. Some parties have taken such activities to the next level, deciding to collaborate on common goals. This phenomenon has led to a rise in so-called cyber militias. Hacktivism, online armies, and online/digital activism are other synonyms for this emerging trend. What Is the Purpose of Cyber Militias? What Is the Purpose of Cyber Militias? Although some of the earliest cyber militias banded together for political reasons, some participants have broadened their causes to include social and environmental aims. That characteristic explains why cyber activism has become more popular over the last several years. Wars, climate change, and civil unrest are some of the many factors that dominate people’s lives. Many are not in positions where they can safely attend protests or take other in-person actions. However, the internet is a highly accessible resource that individuals can harness for mobilization, communication, and solidarity. Relatedly, a 2023 analysis found that 92% of jobs require digital skills. Suppose people already have those capabilities because they use them in their work. Some might understandably want to apply them during their downtime if they feel compelled to act in response to things they see occurring in their society. found that 92% of jobs require found that 92% of jobs require The Internet as a Content Vehicle Another likely reason why cyber militias have cropped up relatively recently is that the internet makes it incredibly easy to distribute information to the masses in seconds. Traditional activism required printing flyers and taking the time to post them in prominent areas or give them to people at events. However, individuals can use the internet to do the equivalent of that in seconds. For example, estimates suggest that approximately 126 million Americans saw Russia-affiliated content during the 2016 United States presidential campaign, and that figure concerned Facebook alone. That massive reach also highlights how people can participate in cyber militias from anywhere and potentially influence the goings-on in other countries. approximately 126 million Americans saw approximately 126 million Americans saw Importantly, a worrisome part of internet-related content distribution is that anyone can get involved, and there is no guarantee of the validity of whatever they say. If the online content comes from a reporter at a well-known national or international news outlet, the employer's reputation strengthens the information distributor’s credibility. However, the accessibility and reach of social media combine to allow virtually anyone to spread information online. Things have gotten even more complicated with the increasing availability of AI-based video and picture tools. These products can create people’s faces from scratch or swap them. That means individuals cannot necessarily believe everything they see. create people’s faces from scratch create people’s faces from scratch However, a connected problem is that far too few internet users take the time to check facts and get the whole picture. Additionally, if people can push content far and wide, it greatly increases the chances of the masses seeing it. Hacker-Activists Disrupting Websites and Infrastructure Most cyber militias do not solely operate by publishing or creating content on a large scale that may not be wholly truthful or trustworthy. Instead, they also plan coordinated hacks that make websites or online services inoperable. Since so many essential parts of daily activities also have online components, hackers have disrupted those, too. Ukraine has one of the most recent examples of a cyber militia, with many volunteers joining its forces from all over the world. In July 2024, this group collectively targeted numerous Russian banks and ATMs, with the effects spreading to many payment systems and financial apps. effects spreading to many payment systems effects spreading to many payment systems Some hacktivists also plan their actions to ensure ripple effects across some industries that are not historically well-prepared to defend against cyberattacks. One example came when online activists targeted universities in the United Kingdom for their support of the Israeli government’s actions against the Palestinians. Most people know that the healthcare industry is a frequent attack target, and many decision-makers have responded accordingly. However, many educational institutions still have significant room for improvement, and hackers capitalize on that. Plus, many college campuses are like miniature cities, featuring branded eateries, convenience stores, health services offices, and more. A well-orchestrated cyberattack can go far beyond canceled classes. Ransomware demands given to higher education entities can surpass $300,000 on average , emphasizing the tremendous associated expenses for an ill-prepared organization. can surpass $300,000 on average can surpass $300,000 on average Inspiring Transitions From Behind Screens to on the Streets Although some cyber militias only feature people who make impacts while sitting at their keyboards, some efforts have caused a shift whereby some participants realized they must go beyond that kind of activism and populate public spaces. One reason for this is that some individuals are eager to take part but need help figuring out how to get started. The internet can connect them to the necessary resources, help them see how specific protest topics relate to their lives, and inspire them to join the crowds of those standing up for causes. For example, earlier in 2024, Kenyans protested against a controversial tax bill. Although those events began in the capital city, they quickly spread to other parts of the country. The internet was a large part of why that progression occurred. Someone with a background in internet mobilization and activism explained how the online component was instrumental in reaching marginalized groups. Additionally, the internet and various associated technologies have increased the speed at which people can create content and how effectively they can engage others. the online component was instrumental in the online component was instrumental in Another related aspect concerns the facilitation of online crowdfunding through dedicated portals. Some interested parties who are committed to the respective causes cannot feasibly attend in-person protests, even if the internet initially interests them. However, it is easy to send online payments to support causes and help participants obtain the supplies needed for the desired impact. Actions Can Occur Beyond Battlefields Most traditional discussions of militias relate to groups of citizens who come together to support official militaries and supplement their efforts. Conversely, militias can also rise when people want to oppose the military or government. These things remain valid, but the modern difference is that the internet and devices that connect to it have become powerful tools for getting heard and noticed during times of increasing upheaval.

The Rise of Cyber Militias

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Authors:
(1) Dorian W. P. Amaral, Department of Physics and Astronomy, Rice University and These authors contributed approximately equally to this work;
(2) Mudit Jain, Department of Physics and Astronomy, Rice University, Theoretical Particle Physics and Cosmology, King’s College London and These authors contributed approximately equally to this work;
(3) Mustafa A. Amin, Department of Physics and Astronomy, Rice University;
(4) Christopher Tunnell, Department of Physics and Astronomy, Rice University. Table of Links Abstract and 1 Introduction 2 Calculating the Stochastic Wave Vector Dark Matter Signal 2.1 The Dark Photon Field 2.2 The Detector Signal 3 Statistical Analysis and 3.1 Signal Likelihood 3.2 Projected Exclusions 4 Application to Accelerometer Studies 4.1 Recasting Generalised Limits onto B − L Dark Matter 5 Future Directions 6 Conclusions, Acknowledgments, and References A Equipartition between Longitudinal and Transverse Modes B Derivation of Marginal Likelihood with Stochastic Field Amplitude C Covariance Matrix D The Case of the Gradient of a Scalar 3.2 Projected Exclusions To derive our limits, we construct the one-sided log-likelihood-ratio test statistic, defined as where βˆ is that value of β which maximises the likelihood given the observed data set p, characterising the best-fit model. This statistic is defined as a piecewise function as we only expect excess signals to be disfavoured when excluding a value of β in a one-sided test. This corresponds to values of β greater than the best-fit value. Values below this are deemed under-fluctuations and considered consistent with observation. This statistic tells us how consistent the data are with a signal defined by β compared to the best-fit model, with zero representing perfect consistency and large values indicating high inconsistency. Ultimately, we compute 90% CL limits (αconf = 0.90) via a series of Monte Carlo (MC) simulations, following the above procedure in each MC run[8]. For a given choice of β, we We show the 90% CL limit arising from our three-peak analysis in Fig. 4. Also shown are the corresponding results from two single-peak analyses focusing solely on the Compton and either one of the sum or difference peaks. These results follow the same MC procedure as above but take as the full likelihood only the Compton or the sum/difference likelihood given in Eq. (3.2). We see that the three-peak analysis produces a limit that is largely latitude-independent, rising slightly towards the pole. This is because the sensitivity axis at this latitude only has a component parallel to the Earth’s rotation axis and is thus only able to pick out the Compton peak. This latitude-independent limit is in contrast with the analyses that focus on only single peaks, which are both highly sensitive to where the experiment is placed. For the study focusing on the Compton peak, the constraining power is optimal at the pole, where all of the power is contained in the Compton frequency bin, and it rapidly declines towards the equator, where the Compton peak disappears. Note that this and the three-peak results join at this point, with no difference between the approaches. Conversely, for an analysis focusing on one of the sum or difference peaks, the situation is the opposite. In this case, the results of this and the three-peak methods do not converge since half the power is contained in a single one of the sum or difference peaks at the equator; the threepeak analysis captures all of this power, whereas the single-peak analysis misses half of the power. Thus, the strength of our analysis is that the constraining power is retained no matter where an experiment is placed, such that its latitude is rendered largely irrelevant from the viewpoint of constraining a ULDM signal. We emphasize that the interpretation of Fig. 4 is as a set of exclusion lines whereby background pseudodata is generated and the assumed DM signal strength is constrained. The key point is that the level of this constraint depends on the assumption one makes on the nature of the DM signal given a non-detection. Taking this signal to be only a single peak in Fourier space then leads to constraints that are generally dependent on the latitude of the experiment, rapidly weakening towards latitude extremes. On the other hand, employing the full signal model consisting of three peaks yields stronger constraints that are almost independent of the experiment placement. Throughout the above analysis, we assumed that the sensitivity axis pointed in the zenith direction. However, we can relax this assumption and consider what our results would look like if this axis pointed in some different direction, say for instance directions perpendicular to the zenith—namely, the East/West and North/South directions[9]. If North/South-pointing, all of the curves in Fig. 4 would be flipped about the line ϕ = 45◦ . While the strongest limit for the Compton peak would now occur at the equator instead of the pole (and vice versa for both the sum and difference peaks), crucially we would still retain a largely latitude-independent constraint for our three-peak analysis. This is because, throughout the experiment, the directionality of the detector makes a cone, making it sensitive to the vector DM power in all the three directions. If, instead, the axis pointed towards the East/West, we would only see the sum and the difference peaks. This is because, throughout the experimental expedition, the directionality of the detector is restricted to lie on a plane (which would necessarily be perpendicular to the rotation axis of the Earth). Therefore, it is always insensitive to the power contained across the perpendicular direction, which is tied to the standalone Compton peak. One final possibility is when the directionality of the detector traces out a line throughout the experiment. This is only possible when it points parallel to the Earth’s rotation axis (at any given latitude). In this case, we would naturally be oblivious to the Earth’s rotation and hence to the sum and difference peaks, and we would only be able to resolve the Compton peak. In summary, the best-case scenario is when the detector’s sensitivity axis traces out a cone. In this case, we capture all the three peaks since we are sensitive to the vector DM power across all three directions (Earth’s rotation axis and the two orthogonal directions). This paper is available on arxiv under CC BY 4.0 DEED license. [8] While asymptotic formulae exist for computing exclusion limits, we have opted for an MC approach to ensure proper coverage [81]. Since we are following a hybrid frequentist-Bayesian approach, we found this to be an especially pertinent check. Authors: (1) Dorian W. P. Amaral, Department of Physics and Astronomy, Rice University and These authors contributed approximately equally to this work; (2) Mudit Jain, Department of Physics and Astronomy, Rice University, Theoretical Particle Physics and Cosmology, King’s College London and These authors contributed approximately equally to this work; (3) Mustafa A. Amin, Department of Physics and Astronomy, Rice University; (4) Christopher Tunnell, Department of Physics and Astronomy, Rice University. Authors: Authors: (1) Dorian W. P. Amaral, Department of Physics and Astronomy, Rice University and These authors contributed approximately equally to this work; (2) Mudit Jain, Department of Physics and Astronomy, Rice University, Theoretical Particle Physics and Cosmology, King’s College London and These authors contributed approximately equally to this work; (3) Mustafa A. Amin, Department of Physics and Astronomy, Rice University; (4) Christopher Tunnell, Department of Physics and Astronomy, Rice University. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Calculating the Stochastic Wave Vector Dark Matter Signal 2.1 The Dark Photon Field 2.1 The Dark Photon Field 2.2 The Detector Signal 2.2 The Detector Signal 3 Statistical Analysis and 3.1 Signal Likelihood 3 Statistical Analysis and 3.1 Signal Likelihood 3.2 Projected Exclusions 3.2 Projected Exclusions 4 Application to Accelerometer Studies 4 Application to Accelerometer Studies 4.1 Recasting Generalised Limits onto B − L Dark Matter 4.1 Recasting Generalised Limits onto B − L Dark Matter 5 Future Directions 5 Future Directions 6 Conclusions, Acknowledgments, and References 6 Conclusions, Acknowledgments, and References A Equipartition between Longitudinal and Transverse Modes A Equipartition between Longitudinal and Transverse Modes B Derivation of Marginal Likelihood with Stochastic Field Amplitude B Derivation of Marginal Likelihood with Stochastic Field Amplitude C Covariance Matrix C Covariance Matrix D The Case of the Gradient of a Scalar D The Case of the Gradient of a Scalar 3.2 Projected Exclusions To derive our limits, we construct the one-sided log-likelihood-ratio test statistic, defined as where βˆ is that value of β which maximises the likelihood given the observed data set p, characterising the best-fit model. This statistic is defined as a piecewise function as we only expect excess signals to be disfavoured when excluding a value of β in a one-sided test. This corresponds to values of β greater than the best-fit value. Values below this are deemed under-fluctuations and considered consistent with observation. This statistic tells us how consistent the data are with a signal defined by β compared to the best-fit model, with zero representing perfect consistency and large values indicating high inconsistency. Ultimately, we compute 90% CL limits (αconf = 0.90) via a series of Monte Carlo (MC) simulations, following the above procedure in each MC run[8]. For a given choice of β, we We show the 90% CL limit arising from our three-peak analysis in Fig. 4. Also shown are the corresponding results from two single-peak analyses focusing solely on the Compton and either one of the sum or difference peaks. These results follow the same MC procedure as above but take as the full likelihood only the Compton or the sum/difference likelihood given in Eq. (3.2). We see that the three-peak analysis produces a limit that is largely latitude-independent, rising slightly towards the pole. This is because the sensitivity axis at this latitude only has a component parallel to the Earth’s rotation axis and is thus only able to pick out the Compton peak. This latitude-independent limit is in contrast with the analyses that focus on only single peaks, which are both highly sensitive to where the experiment is placed. For the study focusing on the Compton peak, the constraining power is optimal at the pole, where all of the power is contained in the Compton frequency bin, and it rapidly declines towards the equator, where the Compton peak disappears. Note that this and the three-peak results join at this point, with no difference between the approaches. Conversely, for an analysis focusing on one of the sum or difference peaks, the situation is the opposite. In this case, the results of this and the three-peak methods do not converge since half the power is contained in a single one of the sum or difference peaks at the equator; the threepeak analysis captures all of this power, whereas the single-peak analysis misses half of the power. Thus, the strength of our analysis is that the constraining power is retained no matter where an experiment is placed, such that its latitude is rendered largely irrelevant from the viewpoint of constraining a ULDM signal. We emphasize that the interpretation of Fig. 4 is as a set of exclusion lines whereby background pseudodata is generated and the assumed DM signal strength is constrained. The key point is that the level of this constraint depends on the assumption one makes on the nature of the DM signal given a non-detection. Taking this signal to be only a single peak in Fourier space then leads to constraints that are generally dependent on the latitude of the experiment, rapidly weakening towards latitude extremes. On the other hand, employing the full signal model consisting of three peaks yields stronger constraints that are almost independent of the experiment placement. Throughout the above analysis, we assumed that the sensitivity axis pointed in the zenith direction. However, we can relax this assumption and consider what our results would look like if this axis pointed in some different direction, say for instance directions perpendicular to the zenith—namely, the East/West and North/South directions[9]. If North/South-pointing, all of the curves in Fig. 4 would be flipped about the line ϕ = 45◦ . While the strongest limit for the Compton peak would now occur at the equator instead of the pole (and vice versa for both the sum and difference peaks), crucially we would still retain a largely latitude-independent constraint for our three-peak analysis. This is because, throughout the experiment, the directionality of the detector makes a cone, making it sensitive to the vector DM power in all the three directions. If, instead, the axis pointed towards the East/West, we would only see the sum and the difference peaks. This is because, throughout the experimental expedition, the directionality of the detector is restricted to lie on a plane (which would necessarily be perpendicular to the rotation axis of the Earth). Therefore, it is always insensitive to the power contained across the perpendicular direction, which is tied to the standalone Compton peak. One final possibility is when the directionality of the detector traces out a line throughout the experiment. This is only possible when it points parallel to the Earth’s rotation axis (at any given latitude). In this case, we would naturally be oblivious to the Earth’s rotation and hence to the sum and difference peaks, and we would only be able to resolve the Compton peak. In summary, the best-case scenario is when the detector’s sensitivity axis traces out a cone. In this case, we capture all the three peaks since we are sensitive to the vector DM power across all three directions (Earth’s rotation axis and the two orthogonal directions). This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv [8] While asymptotic formulae exist for computing exclusion limits, we have opted for an MC approach to ensure proper coverage [81]. Since we are following a hybrid frequentist-Bayesian approach, we found this to be an especially pertinent check.

Projected Exclusions for Vector Dark Matter Detection Using Latitude-Independent Three-Peak Analysis

**LONDON, United Kingdom, October 22nd, 2024/Chainwire/--**Aventus, a leading provider of enterprise blockchain solutions and parachain on Polkadot, today confirms the launch of Aventus 2.0, an evolution of the Aventus Network aimed at establishing a stronger foundation for long-term growth and value capture. The update introduces several strategic initiatives designed to enhance network performance and stakeholder utility, including increasing transaction volume and overall network usage, expanding the ecosystem through successful partnerships with Layer 3 appchains, enhancing token holder engagement via a liquidity mining program, and reducing token supply via a burn mechanism. The vision for Aventus 2.0 was developed by MVP Workshop, a Blockchain Product Research & Development Studio who designed Polygon Edge and Astar Network, in collaboration with Scytale Digital and the Aventus Services team. Following the approval of a community governance proposal in which AVT token holders voted in favour of executing this vision, the Aventus Services team will implement the Aventus 2.0 plan over the next four months. This process underscores Aventus’s commitment to stakeholder-driven decision-making, ensuring that major network decisions are made through community consensus. Aventus 2.0 comprises three main components: A Layer 3 appchain model, whereby enterprises are able to operate on the Aventus Network and benefit from the security, scalability, interoperability and decentralised infrastructure offered by the Aventus ecosystem.
A liquidity mining program on Uniswap, including a custom user-friendly dApp, to enhance token holder engagement. Appchains are also able to request grants from Aventus community treasury and launch their own liquidity mining programs to drive liquidity for their own tokens, contributing a portion of their token supply and network fees to the Aventus treasury to support the broader Aventus ecosystem and its development.
A new collator rewards mechanism to ensure a secure and efficient Aventus Network, alongside an automatic burn mechanism for a portion of gas fees to reduce the overall supply of AVT tokens in circulation. Alan Vey, Founder at Aventus, commented: “Aventus 2.0 builds on important learnings from existing Aventus Network clients as well as the invaluable expertise of our partners at MVP Workshop & Scytale Digital, and represents a significant milestone in our journey to enhance the Aventus Network’s capabilities and deliver greater value to stakeholders.” The appchain model is already seeing traction, with existing users of the Aventus Network having recently launched their own Aventus Layer 3 appchains. Barry Helfrich, CIO at Enigmatic Smile, adds: “We needed the Voucher Ledger solution to be secure, fast and stable enough to process the discounts collected by hundreds of millions of users in our rewards ecosystem — no small feat, but Aventus has helped us build such a solution. The team has been helpful, professional and responsive throughout the process. We’re looking forward to continuing our long-standing relationship with them.” The updated network will provide enhanced functionality and improved user experiences, positioning the Aventus Network as a trusted leader in enterprise blockchain solutions and key contributor to enterprise use cases within the Polkadot ecosystem. About Aventus Aventus transforms how customers create trust and unlock growth, crafting pioneering Web3 solutions for brands, from creating more connected, integrated experiences to enhancing traceability, transparency, and product authentication. Founded in 2020, Aventus is the only trusted digital product extension platform that provides a secure and reliable Web3 environment for customers to launch market-leading programs and product activations. With deep industry expertise and a strong understanding of enterprise needs, Aventus delivers one the best feature sets of Web3 with the familiarity of Web2, driving significant brand reputation, trust, and enterprise growth for its customers. Its production-ready, end-to-end Blockchain-as-a-Service software is modular, scalable, and interoperable, giving clients the flexibility they need to respond to rapidly-evolving market opportunities. For more information, users can visit: www.aventus.io, and also their X, LinkedIn and Telegram. Contact Head of Marketing Ellie Hyman Aventus ellie.hyman@aventus.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. **LONDON, United Kingdom, October 22nd, 2024/Chainwire/--**Aventus, a leading provider of enterprise blockchain solutions and parachain on Polkadot, today confirms the launch of Aventus 2.0, an evolution of the Aventus Network aimed at establishing a stronger foundation for long-term growth and value capture. The update introduces several strategic initiatives designed to enhance network performance and stakeholder utility, including increasing transaction volume and overall network usage, expanding the ecosystem through successful partnerships with Layer 3 appchains, enhancing token holder engagement via a liquidity mining program, and reducing token supply via a burn mechanism. The vision for Aventus 2.0 was developed by MVP Workshop, a Blockchain Product Research & Development Studio who designed Polygon Edge and Astar Network, in collaboration with Scytale Digital and the Aventus Services team. Following the approval of a community governance proposal in which AVT token holders voted in favour of executing this vision, the Aventus Services team will implement the Aventus 2.0 plan over the next four months. This process underscores Aventus’s commitment to stakeholder-driven decision-making, ensuring that major network decisions are made through community consensus. Aventus 2.0 comprises three main components: A Layer 3 appchain model, whereby enterprises are able to operate on the Aventus Network and benefit from the security, scalability, interoperability and decentralised infrastructure offered by the Aventus ecosystem. A liquidity mining program on Uniswap, including a custom user-friendly dApp, to enhance token holder engagement. Appchains are also able to request grants from Aventus community treasury and launch their own liquidity mining programs to drive liquidity for their own tokens, contributing a portion of their token supply and network fees to the Aventus treasury to support the broader Aventus ecosystem and its development. A new collator rewards mechanism to ensure a secure and efficient Aventus Network, alongside an automatic burn mechanism for a portion of gas fees to reduce the overall supply of AVT tokens in circulation. A Layer 3 appchain model, whereby enterprises are able to operate on the Aventus Network and benefit from the security, scalability, interoperability and decentralised infrastructure offered by the Aventus ecosystem. A liquidity mining program on Uniswap, including a custom user-friendly dApp, to enhance token holder engagement. Appchains are also able to request grants from Aventus community treasury and launch their own liquidity mining programs to drive liquidity for their own tokens, contributing a portion of their token supply and network fees to the Aventus treasury to support the broader Aventus ecosystem and its development. A new collator rewards mechanism to ensure a secure and efficient Aventus Network, alongside an automatic burn mechanism for a portion of gas fees to reduce the overall supply of AVT tokens in circulation. Alan Vey, Founder at Aventus, commented: “Aventus 2.0 builds on important learnings from existing Aventus Network clients as well as the invaluable expertise of our partners at MVP Workshop & Scytale Digital, and represents a significant milestone in our journey to enhance the Aventus Network’s capabilities and deliver greater value to stakeholders.” Alan Vey, Founder at Aventus, commented: “Aventus 2.0 builds on important learnings from existing Aventus Network clients as well as the invaluable expertise of our partners at MVP Workshop & Scytale Digital, and represents a significant milestone in our journey to enhance the Aventus Network’s capabilities and deliver greater value to stakeholders.” The appchain model is already seeing traction, with existing users of the Aventus Network having recently launched their own Aventus Layer 3 appchains. Barry Helfrich, CIO at Enigmatic Smile, adds: “We needed the Voucher Ledger solution to be secure, fast and stable enough to process the discounts collected by hundreds of millions of users in our rewards ecosystem — no small feat, but Aventus has helped us build such a solution. The team has been helpful, professional and responsive throughout the process. We’re looking forward to continuing our long-standing relationship with them.” Barry Helfrich, CIO at Enigmatic Smile, adds: “We needed the Voucher Ledger solution to be secure, fast and stable enough to process the discounts collected by hundreds of millions of users in our rewards ecosystem — no small feat, but Aventus has helped us build such a solution. The team has been helpful, professional and responsive throughout the process. We’re looking forward to continuing our long-standing relationship with them.” The updated network will provide enhanced functionality and improved user experiences, positioning the Aventus Network as a trusted leader in enterprise blockchain solutions and key contributor to enterprise use cases within the Polkadot ecosystem. About Aventus Aventus transforms how customers create trust and unlock growth, crafting pioneering Web3 solutions for brands, from creating more connected, integrated experiences to enhancing traceability, transparency, and product authentication. Founded in 2020, Aventus is the only trusted digital product extension platform that provides a secure and reliable Web3 environment for customers to launch market-leading programs and product activations. Aventus Aventus With deep industry expertise and a strong understanding of enterprise needs, Aventus delivers one the best feature sets of Web3 with the familiarity of Web2, driving significant brand reputation, trust, and enterprise growth for its customers. Its production-ready, end-to-end Blockchain-as-a-Service software is modular, scalable, and interoperable, giving clients the flexibility they need to respond to rapidly-evolving market opportunities. For more information, users can visit: www.aventus.io , and also their X , LinkedIn and Telegram . www.aventus.io www.aventus.io X X LinkedIn LinkedIn Telegram Telegram Contact Head of Marketing Ellie Hyman Aventus ellie.hyman@aventus.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. here . here

Aventus Network Confirms Launch Of Aventus 2.0, Key To Driving Enterprise Use Cases To Polkadot

Aventus Network confirma el lanzamiento de Aventus 2.0, clave para impulsar casos de uso empresariales en Polkadot

A Rede Aventus confirma o lanzamento de Aventus 2.0, clave para impulsar casos de uso empresarial para Polkadot

एवेंटस नेटवर्क ने एवेंटस 2.0 के लॉन्च की पुष्टि की, जो पोलकाडॉट के लिए एंटरप्राइज़ उपयोग के मामलों को आगे बढ़ाने की कुंजी है

Aventus Network potvrđuje lansiranje Aventusa 2.0, ključnog za usmjeravanje poslovnih slučajeva na Polkadot

Aventus Network-ը հաստատում է Aventus 2.0-ի գործարկումը, որի բանալին ձեռնարկությունների օգտագործման դեպքերն է Polkadot-ի համար:

Aventus Network が、Polkadot へのエンタープライズ ユース ケースを推進する鍵となる Aventus 2.0 のリリースを発表

Réseau Aventus Confirme Lancement Ya Aventus 2.0, Clé Pona Ko Conduire Ba Cas Ya Utilisation Ya Entreprise Na Polkadot

Ny Aventus Network dia nanamafy ny fandefasana ny Aventus 2.0, fanalahidin'ny fitantanana ny raharaha fampiasana orinasa amin'ny Polkadot

Авентусын сүлжээ нь Авентус 2.0-ийг нэвтрүүлж эхэлснийг баталлаа

د Aventus شبکه د Aventus 2.0 لانچ تاییدوي، د پولکاډوټ ته د تصدۍ کارولو قضیې چلولو کلیدي

Aventus Network potvrdzuje spustenie Aventusu 2.0, kľúča k podnecovaniu podnikových prípadov použitia až po Polkadot

ایوینٹس نیٹ ورک نے ایوینٹس 2.0 کے آغاز کی تصدیق کی، پولکاڈٹ کے لیے انٹرپرائز استعمال کے کیسز چلانے کی کلید

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Meet Bitrix24: Seamless Automation for Business Success

Conozca Bitrix24: automatización perfecta para el éxito empresarial

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Bitrix24 のご紹介: ビジネスを成功に導くシームレスな自動化

ພົບກັບ Bitrix24: Seamless Automation ສໍາລັບຄວາມສໍາເລັດທາງທຸລະກິດ

Запознајте го Bitrix24: Беспрекорна автоматизација за деловен успех

Bitrix24: Бизнесийн амжилтад зориулсан автоматжуулалт

Bitrix24 लाई भेट्नुहोस्: व्यापार सफलताको लागि सिमलेस स्वचालन

د Bitrix24 سره لیدنه وکړئ: د سوداګرۍ بریا لپاره بې سیمه اتوماتیک

Встречайте Bitrix24: бесперебойная автоматизация для успеха бизнеса

Zoznámte sa s Bitrix24: Bezproblémová automatizácia pre obchodný úspech

Njihuni me Bitrix24: Automatizimi pa probleme për suksesin e biznesit

Dibana ne-Bitrix24: UkuziSebenzisa okuNgenamthungo kwiMpumelelo yoShishino

Developing an Integrated Data and User Feedback Tool Using AI Product Architecture Software

By Armagan Ercan & Philippe Schommers Since the completion of the Shanghai upgrade, the amount of staked ETH has increased by 91%. But to the uninitiated, staking crypto may come across as intimidating, what with price volatility, security concerns, and the risk of frozen assets stoking fears. So how can crypto enthusiasts better protect themselves when they start their staking journeys? What is staking? The term staking derives from the “proof-of-stake” consensus mechanism used to secure blockchain networks like Ethereum or Gnosis Chain. Users become validators by choosing to stake some of their cryptocurrency with a selected network to validate new transactions, operating as part of a validator node. A validator node will be selected based on the collective amount of crypto they have staked to validate new transactions and be subsequently rewarded with crypto. This, however, requires a consistent online presence, which usually would equate to roughly 6 months of the year in order to be profitable for the operator.  node operators can often be penalised for downtime. Should users not wish to become a validator, they can pay a fee to a staking pool and delegate their stakes to a larger pool through protocols like StakeWise. This way, they can still earn staking rewards without having to maintain a constant online presence. Then why become a validator? Staking plays an important role in securing proof-of-stake networks while offering investors and network participants the chance to earn passive income. A natural flow is established and investors' investments are kept in a more secure network. This process makes it more difficult for malicious actors to attack the blockchain, thus enhancing its stability and security. Although staking cryptocurrencies is attractive for these reasons, it is important to remember that staking potential should not be the only factor in investment decisions. Do your research and understand your investment When becoming a validator, users must also account for penalties for acting against the network's best interests. These include validating fraudulent transactions, using incorrect data or node downtime. By committing these, they risk having their staked crypto “slashed” and taken as forfeit. A network's staking requirements can differ vastly from one project to another. On Ethereum and Gnosis Chain for example, unless voluntarily acting against the best interests of the network, a validator can only ever be penalised as much in one day for being offline than they'd be rewarded in a day by being online. However, other projects might have more stringent requirements, whereby stakers could lose their stake simply by not having a perfect track record. Some do not have any requirements and merely avoid paying out rewards to offline nodes. Regardless of staking requirements, factors like network security, decentralization level and participation barriers, smart contract quality, team experience, and project maturity all contribute to the risk profile. Think of it as investing in a new company. Before deciding to part with an investment, would an investor not first do the due diligence to understand the quality and conditions of what they are putting their money into? Investors or node operators should review the security documents and risk analysis report of the network and decide whether it is battle-tested or not as a result of their own research. Common mistakes A simple yet devastating mistake is improperly securing private keys. If private keys are not secured correctly, then malicious actors can compromise the security of the network and steal staked crypto. There are several solutions such as using secure hardware to store private keys or self-custody/cold wallets. However, the inverse is also relevant as over securing private keys can also lead to losing access to wallets, so users should aim to strike a balance between the two. Similarly, a lot of stakers neglect tax considerations. If staking rewards are treated as income, they will be subject to income tax and if they are seen as capital gains, they will be subject to the relevant capital gains tax. Maximising returns and minimizing risks The main focus should be on security to maximize returns and minimize risks. After that, consider diversifying staking portfolios, compounding rewards regularly, and staying informed about network changes. Liquid staking options which allow stakers to access their staked crypto to use as collateral offer more flexibility but have their own trade-offs. However, no matter what new technology is on offer or how enticing the programme's rewards are, it’s essential to do thorough research and set realistic expectations for returns before starting staking. By Armagan Ercan & Philippe Schommers By Armagan Ercan & Philippe Schommers Armagan Ercan Philippe Schommers Since the completion of the Shanghai upgrade, the amount of staked ETH has increased by 91% . But to the uninitiated, staking crypto may come across as intimidating, what with price volatility, security concerns, and the risk of frozen assets stoking fears. So how can crypto enthusiasts better protect themselves when they start their staking journeys? the amount of staked ETH has increased by 91% the amount of staked ETH has increased by 91% What is staking? The term staking derives from the “proof-of-stake” consensus mechanism used to secure blockchain networks like Ethereum or Gnosis Chain . Users become validators by choosing to stake some of their cryptocurrency with a selected network to validate new transactions, operating as part of a validator node. Gnosis Chain A validator node will be selected based on the collective amount of crypto they have staked to validate new transactions and be subsequently rewarded with crypto. This, however, requires a consistent online presence, which usually would equate to roughly 6 months of the year in order to be profitable for the operator.  node operators can often be penalised for downtime. Should users not wish to become a validator, they can pay a fee to a staking pool and delegate their stakes to a larger pool through protocols like StakeWise . This way, they can still earn staking rewards without having to maintain a constant online presence. StakeWise StakeWise Then why become a validator? Staking plays an important role in securing proof-of-stake networks while offering investors and network participants the chance to earn passive income. A natural flow is established and investors' investments are kept in a more secure network. This process makes it more difficult for malicious actors to attack the blockchain, thus enhancing its stability and security. Although staking cryptocurrencies is attractive for these reasons, it is important to remember that staking potential should not be the only factor in investment decisions. Do your research and understand your investment When becoming a validator, users must also account for penalties for acting against the network's best interests. These include validating fraudulent transactions, using incorrect data or node downtime. By committing these, they risk having their staked crypto “slashed” and taken as forfeit. A network's staking requirements can differ vastly from one project to another. On Ethereum and Gnosis Chain for example, unless voluntarily acting against the best interests of the network, a validator can only ever be penalised as much in one day for being offline than they'd be rewarded in a day by being online. However, other projects might have more stringent requirements, whereby stakers could lose their stake simply by not having a perfect track record. Some do not have any requirements and merely avoid paying out rewards to offline nodes. Regardless of staking requirements, factors like network security, decentralization level and participation barriers, smart contract quality, team experience, and project maturity all contribute to the risk profile. Think of it as investing in a new company. Before deciding to part with an investment, would an investor not first do the due diligence to understand the quality and conditions of what they are putting their money into? Investors or node operators should review the security documents and risk analysis report of the network and decide whether it is battle-tested or not as a result of their own research. Common mistakes A simple yet devastating mistake is improperly securing private keys. If private keys are not secured correctly, then malicious actors can compromise the security of the network and steal staked crypto. There are several solutions such as using secure hardware to store private keys or self-custody/cold wallets. However, the inverse is also relevant as over securing private keys can also lead to losing access to wallets, so users should aim to strike a balance between the two. Similarly, a lot of stakers neglect tax considerations. If staking rewards are treated as income, they will be subject to income tax and if they are seen as capital gains, they will be subject to the relevant capital gains tax. Maximising returns and minimizing risks The main focus should be on security to maximize returns and minimize risks. After that, consider diversifying staking portfolios, compounding rewards regularly, and staying informed about network changes. Liquid staking options which allow stakers to access their staked crypto to use as collateral offer more flexibility but have their own trade-offs. However, no matter what new technology is on offer or how enticing the programme's rewards are, it’s essential to do thorough research and set realistic expectations for returns before starting staking.

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