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Cybersecurity is the “practice of protecting critical systems and sensitive information from digital attacks” ( ). The field itself is evolving on a daily basis with advancements in technology and hackers being one step ahead to developing new malware. If you have any interest in security and technology, then this may be the field for you. I will talk about the five best cybersecurity books for beginners to get a better overview of what cybersecurity is all about. These books may help you figure out if this is the career choice for you. IBM List of Cybersecurity Books Covered in This Article Cybersecurity for Beginners Social Engineering: The Science of Human Hacking The Art of Invisibility Hacking for Beginners Blue Team Handbook: Incident Response Edition 1. Cybersecurity for Beginners by Raef Meeuwisse "If you aren’t concerned about Cybersecurity, you don’t know enough about it" This book provides an overview of Cybersecurity where every chapter talks about different topics within the industry. The chapters can be read in any particular order because no knowledge from earlier chapters are needed to understand the later ones. Meeuwisse does a great job with covering the basics of Cybersecurity, making this one of the best cybersecurity books for beginners. He provides definitions for all of the important terms that a reader needs to understand throughout the entire book. Meeuwisse also explains the purpose of having the case study examples in this book. I have listed the topics that are covered in his book below in case you are still hesitant. Topics Covered Skills required to create a Cybersecurity team Basic Cybersecurity concepts A couple case study examples Human involvement Attack and Defense methods Cybersecurity Risks Organization security The Future of Cybersecurity Check out the book . here 2. Social Engineering: The Science of Human Hacking by Christopher Hadnagy Hadnagy provides an overview of different social engineering techniques and explains how and why they work; he also provides real world examples for each technique to help make it easier to understand. Hadnagy believes that anybody who reads this book will have learned something about social engineering. Regardless of your background, this is a great book if you want to learn about Social engineering. Social engineering is a very important topic, in my opinion, and a good place to start. Topics Covered OSINT Advanced communication modeling and profiling tools Pretexting Rapport-building Types of social engineering attacks Check out the book here . 3. The Art of Invisibility by Kevin Mitnick "To be invisible online, you more or less need to create a separate identity, one that is completely unrelated to you. … you must also rigorously defend the separation of your life from that anonymous identity" Kevin Mitnick is considered to be the world’s famous and most wanted hacker and in his book, The Art of Invisibility, he illustrates “what is happening without your knowledge and the ‘art of invisibility’” ( ). mitnicksecurity In this book he provides both “online and real-life tactics and inexpensive methods to protect you and your family, in easy step-by-step instructions” ( ). He discusses various tactics that can protect your privacy and what you can do to leave no digital trace. These are the topics that are covered in Mitnick’s book and also a book review by Scott Schober. mitnicksecurity Topics Covered Encryption Privacy Password WiFi security HTTPS Tracking activity Check out the book here . 4. Hacking for Beginners: A Step by Step Guide for you to Learn the Basics of Cybersecurity and Hacking by Ramon Nastase If you are interested in hacking then this book is perfect for you and another one of the best cybersecurity books for beginners. This book will teach readers how hackers think, why they hack computer systems, and how they do it. This book is geared towards those who have an interest in penetration testing because you will learn about the different attacks that exist and the techniques used to hack into a system. The following list are the topics covered in Nastase’s book. Topics Covered The 5 step process of hacking Installing and using Kali Linux Scanning devices in a network Cyberattacks VPN Firewall Check out the book here . 5. Blue Team Handbook: Incident Response Edition by Don Murdoch If you have an interest in Blue Team - i.e. working in a SOC, incident response, etc. then this book is a good start for you. Murdoch gives an overview of what it is like to be a Cybersecurity incident responder. Murdoch thoroughly explains in detail why and how every tool is used. Being part of the blue team means that you have an inside out view of an organization. Members of the blue team work together to protect the organization against threats and critical assets. Topics Covered Incident response steps/template Understanding the hacker and the tools that they use Host-based analysis Network-based analysis Check out the book here . Final Thoughts on These Cybersecurity Books for Beginners These are the five best cybersecurity books for beginners that I believe you should start with if you want to pursue a career in Cybersecurity. Each one of these books gives a run-through of different aspects within Cybersecurity. If a particular topic within Cybersecurity sparks an interest, then I recommend starting with a book on said topic. Although I have only listed these five books, there are still more that exist in many other areas. There are so many aspects within Cybersecurity to choose from so these books are just the beginning.

5 Best Cybersecurity Books for Beginners

Los 5 mejores libros de ciberseguridad para principiantes

This thread by David, Natasha, Amy and Limarc occurred in general channel. Slogging hackernoon's David May 24, 2021, 4:06 PM 📼 2 😂 2 This Thread is Being Recorded Natasha May 24, 2021, 6:02 PM :rolling_on_the_floor_laughing: 2 mostly, people are like... how do I make it stop? https://www.reddit.com/r/Zoom/comments/hwg6ty/this_meeting_is_being_recorded/ David May 24, 2021, 6:04 PM 😂 1 David May 25, 2021, 6:16 PM I imagine this decision was driven by their legal team, i.e. someone does something stupid or illegal on a zoom call, and then they claim that is zoom's fault b/c they didnt know they were being recorded. Amy May 25, 2021, 9:52 PM the first minute of this video hahahha Limarc May 26, 2021, 9:11 AM Amy what's weirder is that the zoom recording doesn't record the audio of that message. LOL If the point is to avoid legal actions, shouldn't there be proof that the recording played xD

This Thread is Being Recorded

A lot of tech companies struggle with creating an effective and efficient on-call schedule internally for their product and service, which results in  longer downtimes when something goes wrong. They often over-burden their team members with repeated on-call duty, resulting in team fatigue. Here’s how to create an on-call schedule that your team might just love. On-call doesn’t have to suck the life out of your employees. There’s another side to it. A better one. An on-call schedule ensures that someone competent is available to bring services up and running if they go down so that the customers don’t have trouble using your product or service. Though on-call isn’t a new concept in the world of DevOps and IT Ops, the execution and roles have greatly evolved over the years. How Has On-Call Evolved Over the Years? In the past, being on-call and resolving issues as they occur used to be the sole responsibility of Sysadmins and Operation Engineers. With the evolution of DevOps, Software Developers now find themselves part of an on-call rotation and this has worked well for most companies. On-call schedules used to be created on spreadsheets (some still use this method) and intimated to the team without looking into their specific availability. The person on-call had to be available at that time or day. It lacked flexibility, it was a nightmare to find a replacement if the person on-call had an emergency and it was a hassle to find someone who could help resolve an issue if the person on-call wasn't able to resolve it on their own. Thanks to ops platforms like Fyipe which has an inbuilt, on-call scheduling feature, we don’t have to worry about creating schedules in spreadsheets anymore or informing the person on-call. What still remains an issue, however, is the negative attitude towards being on-call. No-one wanted to be on-call then and no-one wants it now but it’s an absolute necessity. Being on-call doesn’t have to suck! An effective on-call schedule can help reduce friction and help keep your engineers happy. Happy on-call team means happy customers! The only way this is possible without draining your team is to ensure the schedule takes care of their work-life balance and doesn’t deplete any single engineer completely. Why Do You Need to Have Someone On-Call? Being on-call is the first step an organization takes towards improving its availability and reliability for its customers or users. On-call engineers are the last line of defense to defend against customer-impacting outages and ensure that the issues are resolved as quickly as possible. You need to be there when your customers need you. On-call ensures this. “If the idea of being 'on-call' sucks to your team, it means they are responding negatively to a symptom. The cause is less systemic and more a reflection of the team/organization's basic engineering prowess. An organization should have a “No Downtime” engineering and ops process in place. Having an on-call schedule for your team is an last line of defense against downtimes. emergency Who Should Be Part of Your On-Call Team? Here’s an interesting story. About 11 years ago, Google came up with a new strategy for production management. It realized that as R&D was pushing more and more features to production, Operation Engineers were having a tough time keeping production as stable as possible. The two teams were working in opposite directions, which lead to increased tension due to their different skill sets, backgrounds, incentives, and metrics and ultimately resulted in a clash between them. In order to bridge the gap between the two teams, Ben Treynor, one of Google’s ops leaders, thought of an innovative solution that led to the creation of a new team at Google called Site Reliability Engineering (SRE). The team comprised of 50% Sysadmins and 50% Software Engineers. This improved the operations efficiency multi-fold. Many companies have followed along similar lines and we have seen them succeed over the years with this strategy. It makes sense to include engineers, who have worked on the code, on the on-call team because of the following reasons: They have a deeper understanding of the code or feature they have worked on and hence, if the issue is created due to code errors, they are able to fix it faster. This is extremely efficient. Engineers get exposure to ops processes as well. This presents them with a holistic overview by helping them understand the implications of a certain coding practice in the production environment and thus helps them produce better quality code. How Should You Create an On-Call Schedule? Creating a schedule for on-call rotation primarily depends on several factors: Team Size Geographical distribution of the team Feature or service wise distribution of teams Creating rotation plans based on team size When You are a Solo Flyer (Team Size = 1) When you are a single person team, creating an on-call schedule is a no brainer. It is highly likely that you are just starting your journey as a startup and you are the only person responsible for everything in your company. Hence, you need to be available when you are alerted and be on-call 24 x 7 x 365. Starting a company is tough and you might be drained when you leave for the day. This might even result in you missing alerts or calls. Our advice is to have an ex-colleague / workmate as backup and add them as a secondary on-call person so that if you don’t wake up and acknowledge the alert, he or she will jump on a call, fix it or notify you / call you immediately. It’s also highly recommended you use on-call software because it calls you in a loop until the issue is acknowledged or resolved. When Your Team Size = 2 Change the schedule for primary on-call every other day i.e. alternate. Let your peer choose between MWF (Monday, Wednesday and Friday) or TTS (Tuesday, Thursday and Saturday) and you can have your pick on the even or odd of the four Sundays you want to be on-call. Person A will be primary and will be alerted first and Person B will be called when Person A misses notifications or fails to acknowledge an incident. Approach 1: Primary on-call members will be the ones who will be alerted first. If they do not pick up the call or respond to alerts then secondary on-call members are alerted. You can also rotate as well. You can be the primary on-call person and your partner would act as a secondary on-call for the week. The following week, this will change and your partner will be primary and you would act as the secondary on-call person. Approach 2: weekly Let’s say that A is the primary on-call person, B is the secondary on-call person and C is the backup for week 1. So when an alert is triggered, person A receives the first alert. This alert can be in the form of a call, SMS, email or even on Slack depending on the set preference. We found the best approach to on-call rotation is to do it weekly. When Your Team Size = 3 Let’s say there are 3 three people in the on-call team — A, B and C. The purpose of having a secondary on-call is to ensure that your partner is alerted in case you miss it and one of you can start working on the issue. Ideally, A should be available to acknowledge the alert and start working on it. But, if for some reason A misses the alert, the alert is received by B who can then start working on the issue. If neither A or B receives the alert or are unavailable, the alert finally goes to C, the backup. In week 2, B who was the secondary on-call person in week 1 replaces A as the primary on-call person and C replaces B to become the secondary on-call person. A now becomes the backup on-call person for week 2. In week 3, C replaces B, who was the primary on-call person for week 2, to become the primary on-call for week 3. A jumps up to become the secondary on-call and B becomes the backup for week 3. In week 4, A becomes the primary on-call person, B becomes secondary and C becomes back up again and so the cycle repeats. When Your Team Size = 4 or More If your team size is 4 members or more, we have seen that the best strategy is to have weekly rotations. Let’s say there are 6 people on the team, A, B, C, D, E, and F. The rotation must be decided such that it remains fair to everyone while reducing the stress of being available all the time. This can be done by ensuring that everyone works as primary, secondary and backup on-call for the same amount of time. Let’s say A works as the primary on-call, B works as secondary on-call and C works as the backup. Week 1: Primary on-call: A Secondary on-call: B Backup: C Free from all on-call responsibility: D, E and F A will be relieved of being on-call since he acted as primary for a week with maximum responsibility. It's time for B to replace A and become the primary for this week and C replaces B as secondary on-call. Week 2: Since the backup position is empty and D hasn’t had any responsibilities yet, D will act as the backup for this week. Primary on-call: B Secondary on-call: C Backup: D Free from all on-call responsibility: A, E and F B is relieved from all on-call responsibilities since B worked as primary on-call for the week. D becomes secondary on-call and E becomes backup. Week 3: Primary on-call: C Secondary on-call: D Backup: E Free from all on-call responsibility: A, B and F Now D replaces C and becomes the primary on-call. E becomes secondary and F becomes the backup. Week 4: Primary on-call: D Secondary on-call: E Backup: F Free from all on-call responsibility: A, B and C As we can see, each week a person moves up a notch in the responsibility cycle from backup to secondary and from secondary to primary on-call. As this happens, the person with maximum responsibility moves out of the cycle and stays out until everyone has fulfilled the responsibility of being a backup on-call. Once this is done, people who exited the cycle first enter the cycle first and this continues. Some teams follow the same rotation but do it every day instead of every week. This works perfectly when the team size is large, say 30 or more and everyone is aware of the schedule. In smaller teams, however, this creates a lot of tension among engineers who hate constant distractions. This also tends to affect their work-life balance. Tip: With a weekly rotation, engineers are mentally and physically prepared that they need to be available for a week and can work on their tasks in the other 3 weeks of the month. This has proven to be a better plan for a most of our clients who have teams this size. Feature-wise distribution of teams It makes sense to have a member from the team responsible for rolling out a feature to also be responsible for maintaining it. An on-call person who is already aware of how the feature is designed and of the code style is much faster in resolving the issue and avoiding it in the future as well. Having someone on-call as a backup from the team, who developed the feature, helps in faster resolution of issues. Hence, an on-call team must always include at least one person as a backup / secondary on-call from the team who was responsible for rolling out the feature. : Sometimes a team works on multiple features and so an on-call schedule based on features might clash. In this a case it’s important that a single person doesn't act as the primary on-call for two features. It must also be ensured, if possible, that there is at least one person in both on-call schedules who isn’t common to both the schedules. Important This makes it fail-safe such that even in the worst-case scenario, there will be two different people on-call for two different features. Accounting for Geographical Distribution of Teams Enterprise companies have a huge team that may be geographically distributed. Companies of this size are based on following the sun model. This ensures that the on-call schedule doesn’t exceed the office hours and helps in ensuring a work-life balance. Let’s say a team is distributed into two subgroups working in two geographical regions, the US and India. Proper on-call scheduling and rotation ensure that the Indian team receives the alert when the team in the US is off their work schedule and similarly the team in the US would receive the alert when the team in India is offline. Alerts customized like this prevent burnout for members in either of the regions but here’s a problem that arises when only members in the teams of a particular region are scheduled to receive alerts and work on issues based on the time of the day. Alerts customized according to the time zone prevent burnout for members in either of the regions. : Sometimes the teams may require information such as logs, which would only be available with the team in the other time zone, in order to work on the issue. In such a scenario, it becomes extremely difficult to have someone from the team in the other time zone go back to the office in the middle of the night and help with the information required so that the issue can be resolved in time. Warning We have found that the best way to ensure that such situations are avoided is to have someone on the team in the other time zone be on-call but this can be further optimized by deciding the schedule based on the priority of the incident. In case of low or moderate priority events, the alert to the team in the other time zone could be avoided. In such a scenario, a member of the same time zone would act as a backup. Approach: In case of high priority incidents, alerts can be sent to team members in the other time zone as well. High priority — critical incidents When its day in the US and night in India and an issue occurs. Scenario 1: Primary on-call: Member 1 of the team in the US Secondary on-call: Member 2 of the team in the US Backup: Member 3 of the team in India Secondary Backup: Member 2 of the team in India (in case the backup misses the alert) When its day in India and night in the US. Scenario 2: Primary on-call: Member 1 of the team in India Secondary on-call: Member 2 of the team in India Backup: Member 3 of the team in the US Secondary Backup: Member 2 of the team in the US (in case the backup misses the alert) Low priority — low impact incidents When its day in the US and night in India and an issue occurs. Scenario 1: Primary on-call: Member 1 of the team in the US Secondary on-call: Member 2 of the team in the US Backup: Member 3 of the team in the US When its day in India and night in the US. Scenario 2: Primary on-call: Member 1 of the team in India Secondary on-call: Member 2 of the team in India Backup: Member 3 of the team in India Using the above methodology, you would now be able to design an on-call rotation schedule that works best for your team. But there are some more things you should consider while creating an on-call team. Tips to Build an Awesome On-Call Culture Have only those people on the team who are independently capable of working and resolving issues related to code, servers, and other network issues. Having members in the role of SRE, like Google, is probably a much better idea than having just a Sysadmin or DevOps person on call. Make sure you take a poll from your team members before finalizing a schedule. It's always better to find a middle ground that serves both the firm and the engineers well. Even after implementation, regular feedback ensures the team doesn’t have trouble following it. Ensure the schedule takes care of the work-life balance of your employees. Ensure that they get enough sleep and have a healthy work environment. Make sure the person on-call isn’t burdened with anything else while he or she is on call. This reduces efficiency and is counterproductive. Help your team develop a culture of empathy. Your team should care for each other and should learn it from you. Sometimes a person who was supposed to be on call might have some emergency due to which they might not be available to be on-call. In such a scenario, someone from the team should eagerly come up and volunteer to shoulder the responsibility and cover that person. They shouldn’t be forced into it. Your schedule should have the flexibility for people who fall ill, or for someone who might have a child or is about to have one. The schedule designer must take note of these situations and adapt accordingly until the time they are fit to start again. It’s always a good idea to keep a list of people who can replace the on-call person in case of emergencies. We at help hundreds of businesses across the globe run efficiently and reduce downtime to improve the customer experience every day. Fyipe Previously published at https://blog.fyipe.com/how-to-create-an-on-call-schedule-that-doesnt-suck/

How to Build an Effective and Sustainable On-Call Schedule For Your Team

By & , originally published on Chris Lukassen Sjoerd Kranendonk Scrum.org By now, most organizations are using Scrum, however, many of them feel like the agility of their organization has degraded, and they might be right! Often, using Scrum starts out as a way to improve development efforts coordinated within an IT division or department, but that is not the most effective organization structure to potentially get maximum benefit from Scrum. Inclusive Scrum is about looking at the full value chain and organizing your Product development effort around that. Whereas low agility Scrum might actually hurt your agility. Three symptoms that indicate low-agility Scrum Most of the time this means your Scrum Teams are exclusively made up of members of the IT department. Your Scrum Teams have a Definition of Ready that demands a full ‘design’ before an item can be planned in the Sprint. After your Scrum Teams deliver a backlog item as ‘Done’ it has to wait for business implementation before actually being of added value Your Sprints are two weeks, but your actual time from idea to validation is over two months Sound familiar? As a result many in “the business” just shrug when you mention Scrum, to them little has changed. Apart from teams making more noise and a ludicrous of wall decoration in the shape of self adhesive colorful square pieces paper, little has changed. Three reasons why you should look at the full value chain (business agility) RESPONSIVENESS — The ability to create real cross-functional teams minimizes handovers, queues and wait times. Your Time to Learn will potentially shrink to less than your Sprint length, increasing agility and reducing risk. QUALITY OF FEEDBACK — These teams can take true ownership of the problem-solution fit as they can talk to and validate against actual users and customers. The quality & fidelity of feedback goes up because distance is minimized. Time wise: less time between each step in the process and thus less time between decision and validation (feedback). Distance wise: Less distance between decider/builder/consumer; less handovers, less knowledge lost in translation. Both reduced time and reduced distance increase the quality of feedback and potentially the amount of knowledge. Solving customer problems is about feeling empathy and seeing the pain of the customer — the difference between first hand feedback and reading about a user’s actions in a Jira ticket is mind boggling. Additional benefits are highly motivated teams as they now experience the impact of their work instead of just get reports about it. VALUE STEERING — Only when the full value chain is taken into account can short and long term decisions be made about investments and potential returns. Only when the full cost of an investment (spending time on a Backlog Item) per time unit can be known, can we truly make the best possible decisions on what to invest in next. Where to place our educated bets. Case Study: UX in Scrum Many teams we’ve worked with have struggled with the role and place of UX (User Experience) in Scrum. When should UX work take place? Where should the UX specialist be involved? In Sprint? As part of Product Backlog Refinement? Should the UX-specialist be part of the ‘design sub-team’ working a sprint ahead to make sure the Backlog is continually refined (together with the business analyst and a shared architect)? This ‘seperate team’ pattern results in the ‘delivery sub-team’ being reduced to axe-grinding, code-wielding (programmers & testers), do we want this? Or could the UX specialist be part of a self-organizing Scrum Team, as part of the Development Team, working closely with their development co-teamies, a Product Owner (if present) and Stakeholders? backlog lumberjacks As with any other part of the product development process, we should try to apply the UX tools of the trade just-in-time and with just-enough detail depending on the situation. Some research work will be part of Product Backlog Refinement, while more detailed Ux-development will be conducted in close concert with actual technical development and i.e. A/B validation can take place during the in-Sprint testing phase (or as soon after Sprint end as possible). Let’s look at 3 approaches to research UX requirements Research outside of the Scrum Team Research as part of Backlog Refinement (before items are planned) In Sprint Research 1. Research outside of the Scrum Team A common scenario is where UX research is done outside of the Scrum Team, or at least outside of the Development Team. UX experts engage with (potential) customers to discover why they should be using the product. What “job” is the product hired to do? These engagements often reveal interesting insights in the world of the user, recurring patterns, filters, assumptions and biases. This type of research is done by talking to the customers or even better; observing customers to build empathy and really engage in their perspective. By separating the UX research from the implementation, most of this “warm”, experiential information gets lost in translation during the handover. By compressing several days of interaction and observation into a Backlog Refinement or capturing it in written documentation, this loss is inevitable. Even worse, when this information sits in the Backlog for a longer period of time until it is acted upon, the data has turned stale and possibly is no longer the most accurate description of the customer’s needs. Through these handovers and longer time between research and implementation, this approach has a very low ability to adapt or profit from emerging insights. The Sprint Review has UX as a stakeholder to provide feedback to the Scrum Team on how they interpreted their findings and analysis of customer needs. Based on the Product Increment shown, the UX specialist can design and conduct further research that feeds back in the Product Backlog for at least one Sprint later. The distance between initial research and (UX) feedback is about 3–4 Sprints at a minimum hence fidelity & quality are low. The focus is mostly on how much the current Product Increment is different from what the user actually wants/needs. 2. Research as part of Backlog Refinement Much of the waste of handovers can be reduced if research done by members of Scrum Team. The fewer the handovers, the closer to actual development in both time and communication distance. Still, the separation of development and research leads to small handovers and wait times for instance with extra questions and emerging insights. Sprint Review is with real users providing feedback on slightly adapted versions of test designs and recent interpretations of their previous responses. Distance between initial research and user feedback is at least one Sprint, mostly two or more. Fidelity is ok. Focus is mostly on refining the Product Backlog to increase usability and value based on the working product. 3. In-Sprint Research As we say in Dutch, ‘zit dicht op de bal’ (keep the ball close). This means that not only can the actual development team be involved in the research, potentially the research is part of actual development, so the subjects (stakeholders) partaking in the research are on-hand in the Sprint and emerging insights can immediately be retested or collaborated on as they pop up. No handovers and little to no wait time when adapting from emerging insights. Sprint Review is with real users working on innovations and improvements in unrealized value, since the features delivered have already (partially) been proven to fit customer needs and adjusted during development. Distance between research and user feedback is between a day and a few Sprints. Mostly within one Sprint. Fidelity is high as adjustments to better fit user needs were mostly already made within the Sprint. Focus is almost exclusively on next steps. Conclusion: optimize the whole with Inclusive Scrum Scrum doesn’t solve your problem, or as Ken Schwaber once explained: “Scrum is like your mother in-law; very good in pointing out your mistakes.” Many organizations feel like Scrum slowed them down, because it exposes problems that have long been hidden. By applying an “Inclusive Scrum” mindset, the whole of the system — including UX — is optimized for complex work, not just the development. How is your team doing? Where can you start the discussion around better collaboration and improving flow & quality? Do you need help? Let us know in the comments! Want to know more? This article is a collaboration effort. It was conspired, developed and written by Chris Lukassen & Sjoerd Kranendonk , two Professional Scrum Trainers with a love for great products and the people developing them. In our work we often encounter organizations and teams that struggle with Scrum as a value maximization framework. Mostly this boils down to Scrum Teams being sub-optimally aligned with the actual Product and parts of the process still being done in a waterfall mindset. If this sounds familiar, please feel free to comment below or contact us and we will be glad to help. References Originally published at sjoerdly.com .

Is Scrum Hurting Your Agility?

In one of my , I gave a quick crash course of the difference between the red and blue team in cybersecurity so definitely check that out for further detail. It is important to know what the red and blue team does before you can understand purple teaming. However, for a quick recap the red team plays defense and the blue team plays offense. In this article, I will go into detail as to everything you need to know about purple teaming in cybersecurity. latest articles “The Purple Team should not be a group that fills both Red and Blue roles - but rather a function that enhances existing Red and Blue capabilities.” - Daniel Miessler What is Purple Teaming? Image was taken from here The of the purple team is to maximize the effectiveness of the Red and Blue team. The intention is to provide a deeper and stronger understanding and assurance to an organization. goal Objectives Works with both the red and blue team to identify weaknesses in an organization Ensures maximum delivery from both teams It is , rather it is a cybersecurity function or process that combines both the red and blue team. Purple teaming combines the vulnerabilities and threats found by the red team and the defense tactics and controls found by the blue team. Think of it as a between the defenders and attackers working on the same side. not a physical team collaborative mindset So, Why Do We Need It? It is a known fact that the red and blue team should come together and work as one. The job of the red team is to simulate attacks using real-world attack techniques while the blue team is to understand what defense can be done to detect and prevent such techniques. When put together, they will proactively defend against any and all cyber attacks. We need purple teaming to help us stay ahead of cyber threats and attacks as the attacks are becoming more sophisticated. How does it Help? Many times organizations have experienced cyber attacks where their monitoring solution did not detect it. The attacker may have used an attack technique that gets missed by the monitoring solution. This is why sharing the data obtained from the purple teaming process will help organizations understand a threat actor’s tactic, technique and procedure. When the two teams work together, they are able to build a stronger security infrastructure. They help organizations prepare, prevent, and detect suspicious activities and actions. An effective purple team will increase an organization’s confidence in detecting threats and displaying quantifiable improvements of defenses over time. When Do We Need Purple Teaming? "The increase in collaboration between teams will naturally lead to the centralization of shared repositories of knowledge” - Booz Allen Unfortunately, there are times when the Red and Blue teams within an organization’s security team are not in sync and would require assistance from the purple team. These are just two examples: The red team thinks they are better than the blue team and don’t share pertinent information with the blue team Since the red and blue team are not designed to work together on a continuous basis, information may not be shared with each other all the time Communication between the red and blue team is crucial and with no proper communication, the organization may be even more vulnerable to cyber threats and attacks. Purple teaming is in place to help red and blue teams in an organization break down the barrier and cooperate with one another and to discuss the various attacks and defenses. The red team will examine the blue team’s findings for potential weaknesses that could be exploited by hackers while the blue team can take a look at the new attacks founded by the red team. It will help strengthen an organization’s security posture and strengthen the employee’s skills. Best Practices It’s time to talk about the best practices that should be followed - remember that everyone is on the same team and have the same goal: defend against cyber attacks. Here are some of the best practices to following: : plan ahead before you begin purple team testing Do not skip planning : track each step and assess every task before moving on to the next; going over each mitigation will help both red and blue team have a better understanding Track and revise the process : make sure you have established roles within the team and have set responsibilities for each role Define appropriate roles Final Thoughts: Purple Teaming in Cybersecurity Purple Teaming does not focus exclusively on attacking or defending, they do both. They are designed to spot-check an organization’s security posture to ensure that both the red and blue teams work together. It encourages both teams to share feedback and insights with one another. The within an organization is for the red and blue team to have regular communication with one another, to have a constant flow of information sharing. Without purple teaming, regular security audits, threat hunting, and more, organizations would not stand a chance against threat actors. key to success

What is Purple Teaming in Cybersecurity? 

Recently, we’ve launched a new series of machine learning articles performed by Artur Kuzin, our Lead Data Scientist. Today, Artur is showing up with a new story of his, speaking about the participation as a mentor in the “IEEE’s Camera Model Identification” competition and sharing his recent experience in team management and problem-solving. Problem statement This winter I’ve participated as a mentor in the “IEEE’s Signal Processing Society — Camera Model Identification” competition. The problem was to identify the camera that the image was taken with. There were ten camera models as classes in the image collection: two iPhones, seven Android phones, and one DSLR camera. The problem was to identify the camera that the image was taken with. There were ten camera models as classes in the image collection: two iPhones, seven Android phones, and one DSLR camera. Main idea Usually, you have distinguishing all kinds of objects on the image from each other (i.e., cats vs dogs, porn vs bikini, cars vs buses). At the same time, there shouldn’t be any difference in how and on which device an image of a cat (or a car) was taken. Deep Learning solutions With this competition it was exactly the opposite: regardless of what were the objects on photos, we needed to identify the device. Which means, we had to consider such things as sensor noise, image processing artifacts, optical defects, etc. Team interaction The majority of kaggle teams is formed of participants with similar leaderboard scores, with every team member having his own working solution pipeline. Earlier, I wrote a with a good example of this approach. But this time we had it the other way: we separated pipeline on consecutive and independent parts, so each team member was focusing on his own part. post Solution It was allowed to use external datasets in this competition. Our team member wrote a web scraper based on library. It was also necessary to use a web browser emulator in order to handle a page structure on Flickr correctly. All in all, we downloaded more than 500 Gb of images from Yandex.Fotki, Flickr, and Wikimedia Commons. Data mining. Artur Fattakhov BeautifulSoup selenium That was my only code-level contribution in this project. I chose following criteria for filtering: 1) typical image size (camera-wise), 2) JPEG compression level, 3) information on camera model in EXIF, 4) information on processing software in EXIF. Data filtering. A vast majority of Moto-X images had to be left out because there were several different hardware versions in that class. Learning and validation module development was delegated to . Unfortunately, validation on holdout of kaggle dataset was inconsistent: our neural network scored close to 1.0 accuracy (and we had about 0.96 on the leaderboard). Validation scheme. Ilya Kibardin Therefore, we decided to validate on additional data (urls were provided by Gleb Posobin: ). We also included to this additional dataset 10% of kaggle training set in order to make classes more balanced. https://www.kaggle.com/c/sp-society-camera-model-identification/discussion/47235 Best checkpoints were selected by the lowest cross-entropy value on the manipulated and unaffected data. Somewhere in the middle in the course of the competition, made publicly available his complete solution on a kaggle forum. That was a real game changer because the models appeared to be quite good and everybody immediately started using it. The situation changed again when Ivan Romanov posted pytorch version of the same solution: it was fast and easy to parallelize on multiple GPUs. The sad part that these guys ended up being #30 and #45 in the final leaderboard, but they will always remain unbeaten in our hearts. Training approach. Andres Torrubia Our team member Ilya elaborated Misha’s code ( ) in the following way: https://www.kaggle.com/c/sp-society-camera-model-identification/discussion/48679 Preprocessing. The learning step consisted of the fine-tuning of the complete neural network, without any frozen layers since the problem is very different from ImageNet. Learning. Scheduling. 1. Start with Adam with learning rate 1e-4. If loss shows no improvement during 2–3 epochs — learning rate halves. This should be performed until convergence is achieved.2. Use SGD instead of Adam; learning rate is cyclic from 1e-3 to 1e-6 (three cycles). I asked Ilya to apply my recent approach from “ ” competition: we fine-tuned nine models, chose three best checkpoints from them, used every selected checkpoints to calculate predictions with Test Time Augmentation (TTA) and averaged these predictions by geometric mean. The final ensemble. Amazon from Space First stage aftermath This approach led us to the second place in the overall ranking, and #1 in the student category. We successfully passed the first stage and made it to the second stage of the competition that took place during the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing in Canada. It is quite remarkable that the #3 team also was considered a student team. From their score, it seems that we have outperformed their solution by only one correct prediction. Final IEEE Signal Processing Cup 2018 After we received our confirmation letters, Ilya and Artur F. began to prepare for the second stage, while Valery, Andrey and myself decided that we could not participate in it. Unfortunately, Ilya and Artur’s visas were denied by the Canadian embassy. But luckily for us, organizing committee understood our situation and allowed us to participate in the competition remotely. Second stage details There was no leaderboard on the second stage: by the rules of the competition, we had only one attempt to submit our solution. Also, there was no information on camera models in the training set. So, basically, that was a double fail: no external data and non-representative local validation. Class distribution on the second stage. Solution At first, we tried to use the pipeline from the first stage. Every model quickly gained high accuracy (around 0.97), but their prediction was not overlapping on the test sample (around 0.87). It seemed to me that our models were heavily overfitting. So I came up with the new plan:1. Use best models from the first stage for feature extraction;2. Perform feature extraction with following PCA reducing;3. Train LightGBM classifier. I proposed this plan for the following reasons. The nets were already trained to outside the specific image context. Therefore, it would be enough just to train something lightweight on top of it. However, since the data on this stage may be very different from the data on the first stage, it would be better if the classifier was non-linear, like gradient boosting on decision trees. I have successfully applied this idea in previous competitions (I’ve also shared some ). DenseNet appeared to outperform Resnext and SE-Resnext on local validation. As a result, our final solution looked like this: extract important features code The number of the training samples for the manipulated part was multiplied by seven because I have extracted features from every manipulated transform of a data separately. Afterword At the end, we took the second place in the final stage, but there were a number of important circumstances. First, the jury evaluated solutions not by accuracy but by a presentation. The winner of the final created not only a presentation but also a live demo of their algorithm. And second, we still have no idea about the final score of every team (committee does not give this information away even being asked directly). Fun fact: the vast majority of Russian-speaking data scientists are members of the Open Data Science community. That is a very friendly environment, and during the first stage, every team from our community added [ods.ai] to the team name. It turned out that there were a lot of them on the top of the leaderboard! After that such kaggle legends as inversion and Giba joined our community to figure out what we were up to. I really enjoyed participating as a mentor in a competition. I was able to give several valuable advice on baseline refinement and performing of local validation — all of that was based on my experience in prior competitions. I think, this practice in team forming has proved itself and should be applied in the future contests: Kaggle Master/Grandmaster as a solution architect and 2–3 Kaggle Experts as coders and researchers. In my opinion, that’s a definite win-win situation: experienced Kaggle users don’t have to spend much time writing code while the beginners achieve a better result, avoid common mistakes and gain experience really fast.

IEEE’s camera identification challenge — different approach to teaming up

MIAMI, Florida, October 25th, 2024/Chainwire/--Valhalla Floki’s PlayToEarn Massively Multiplayer Online Role-Playing Game (MMORPG) blockchain game, has teamed up with the Hong Kong International Cricket Sixes as its official partner, marking the much-anticipated return of the tournament after a seven-year break. From November 1 to November 3, top international teams will face off in this fast-paced cricket format at the Tin Kwong Road Recreation Ground. The Cricket Sixes has been a celebrated event since its debut in 1992, with legendary players like Sachin Tendulkar, MS Dhoni, Shane Warne, and Sanath Jayasuriya gracing the field over the years. Valhalla’s partnership with the Sixes reflects the synergy between competitive sports and the blockchain gaming world. “We are thrilled to be part of the Hong Kong International Cricket Sixes. The excitement and energy of this iconic event resonate with our own commitment to innovation and community in gaming,” said Mr. Brown Whale, Valhalla's lead. “This collaboration allows us to engage with cricket fans and show how PlayToEarn gaming can elevate both entertainment and the spirit of competition.” The matches will be broadcast across multiple regions by Star Sports Network, and in India, viewers can catch the action on Fancode, one of the country’s largest sports OTT platforms. On the ground, key branding assets will include ground perimeter boards, mid wicket logo mats, and the presentation backdrop, ensuring strong visibility for both Valhalla and the Sixes event. This year’s tournament will feature 12 teams divided into four groups. In Group C, India, led by stars like Robin Uthappa and Kedar Jadhav, will face off against Pakistan and the UAE. Group A includes South Africa, New Zealand, and host nation Hong Kong. Group B brings together Australia, England, and Nepal, while Sri Lanka, Bangladesh, and Oman make up Group D. The top two teams from each group will progress to the quarterfinals, with 29 matches set to take place over three action-packed days. About Hong Kong Sixes The Hong Kong Cricket Sixes is a six-a-side international cricket tournament held at the Kwong Road recreational ground from 1st to 3rd Nov. The 2024 edition will be conducted after a 7 year gap and 12 of the best cricketing nations will battle it out for top honors. Uses can learn more at www.hkcricket.org About Valhalla Valhalla is a blockchain-based MMORPG inspired by Norse mythology, offering players the chance to discover, tame, and battle with creatures called Veras. The game features a player-driven economy and a hexagonal battlefield designed for dynamic combat. Users can learn more at Valhalla.game. Website | YouTube | Telegram | Instagram | TikTok | Discord | Facebook | Reddit | Twitch Contact Community Relations Officer Pedro Vidal FLOKI marketing@floki.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here MIAMI, Florida, October 25th, 2024/Chainwire/--Valhalla Floki’s PlayToEarn Massively Multiplayer Online Role-Playing Game (MMORPG) blockchain game, has teamed up with the Hong Kong International Cricket Sixes as its official partner, marking the much-anticipated return of the tournament after a seven-year break. From November 1 to November 3, top international teams will face off in this fast-paced cricket format at the Tin Kwong Road Recreation Ground. The Cricket Sixes has been a celebrated event since its debut in 1992, with legendary players like Sachin Tendulkar, MS Dhoni, Shane Warne, and Sanath Jayasuriya gracing the field over the years. Valhalla’s partnership with the Sixes reflects the synergy between competitive sports and the blockchain gaming world. “We are thrilled to be part of the Hong Kong International Cricket Sixes. The excitement and energy of this iconic event resonate with our own commitment to innovation and community in gaming,” said Mr. Brown Whale, Valhalla's lead. “We are thrilled to be part of the Hong Kong International Cricket Sixes. The excitement and energy of this iconic event resonate with our own commitment to innovation and community in gaming,” said Mr. Brown Whale, Valhalla's lead. “This collaboration allows us to engage with cricket fans and show how PlayToEarn gaming can elevate both entertainment and the spirit of competition.” “This collaboration allows us to engage with cricket fans and show how PlayToEarn gaming can elevate both entertainment and the spirit of competition.” The matches will be broadcast across multiple regions by Star Sports Network, and in India, viewers can catch the action on Fancode, one of the country’s largest sports OTT platforms. On the ground, key branding assets will include ground perimeter boards, mid wicket logo mats, and the presentation backdrop, ensuring strong visibility for both Valhalla and the Sixes event. This year’s tournament will feature 12 teams divided into four groups. In Group C, India, led by stars like Robin Uthappa and Kedar Jadhav, will face off against Pakistan and the UAE. Group A includes South Africa, New Zealand, and host nation Hong Kong. Group B brings together Australia, England, and Nepal, while Sri Lanka, Bangladesh, and Oman make up Group D. The top two teams from each group will progress to the quarterfinals, with 29 matches set to take place over three action-packed days. About Hong Kong Sixes The Hong Kong Cricket Sixes is a six-a-side international cricket tournament held at the Kwong Road recreational ground from 1st to 3rd Nov. The 2024 edition will be conducted after a 7 year gap and 12 of the best cricketing nations will battle it out for top honors. Uses can learn more at www.hkcricket.org www.hkcricket.org www.hkcricket.org About Valhalla Valhalla is a blockchain-based MMORPG inspired by Norse mythology, offering players the chance to discover, tame, and battle with creatures called Veras. The game features a player-driven economy and a hexagonal battlefield designed for dynamic combat. Users can learn more at Valhalla.game . Valhalla Valhalla Valhalla.game Valhalla.game Website | YouTube | Telegram | Instagram | TikTok | Discord | Facebook | Reddit | Twitch Website Website YouTube YouTube Telegram Telegram Instagram Instagram TikTok TikTok Discord Discord Facebook Facebook Reddit Reddit Twitch Twitch Contact Community Relations Officer Pedro Vidal FLOKI marketing@floki.com 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

Valhalla Partners With Hong Kong International Cricket Sixes For a Thrilling Comeback

Η Valhalla συνεργάζεται με το Hong Kong International Cricket Sixes για μια συναρπαστική επιστροφή

Valhalla se asocia con Hong Kong International Cricket Sixes para un regreso emocionante

Valhalla s'associe à Hong Kong International Cricket Sixes pour un retour palpitant

वल्लाह ने रोमांचक वापसी के लिए हांगकांग इंटरनेशनल क्रिकेट सिक्सेस के साथ साझेदारी की

Valhalla se udružila s Hong Kong International Cricket Sixes za uzbudljiv povratak

ヴァルハラが香港国際クリケットシックスと提携し、スリリングなカムバックを果たす

Valhalla Bekerjasama Dengan Hong Kong International Cricket Sixes Untuk Kemunculan Kembali yang mendebarkan

Valhalla o Dirišana Le Hong Kong International Cricket Sixes Bakeng sa go Boa mo go Kgahlišago

Abafatanyabikorwa ba Valhalla hamwe na Hong Kong mpuzamahanga ya Cricket itandatu yo kugaruka gushimishije

Valhalla spolupracuje s Hongkongskými medzinárodnými kriketovými šestkami pre vzrušujúci návrat

I-Valhalla isebenzisana nabadlali beQakamba baMazwe ngaMazwe baseHong Kong ukuze bafumane iMbuyiselo echulumancisayo

I-Valhalla Isebenzisana Nabadlali Abayisithupha Bekhilikithi Yamazwe Ngamazwe base-Hong Kong Ukuze Kubuyelwe Okujabulisayo

Sounds (“Music”) and Images (“Art”) have been somewhat conquered by GenAI; it’s never been easier to create slop that’s “close enough” to the real thing. Creatives have taken notice, with 73% of them now believing that AI will significantly impact their industry. Fashion has up until now been somewhat disconnected from these conversations. Sure, it’s a creative sector, but it also has glamor… and a certain exclusivity that makes AI’s infinite abundance seem gauche in comparison. But times are changing, and even the Milanese are now asking if machines could craft the kind of cultural cachet luxury designers have spent lifetimes building.’ Three researchers — Page Moreau from the University of Wisconsin-Madison, Emanuela Prandelli from Bocconi University, and Martin Schreier from WU Vienna — recently added complexity to this debate with a research paper titled, “Generative Artificial Intelligence and Design Co-Creation in Luxury New Product Development: The Power of Discarded Ideas.” Their research explores whether generative AI can compete with human designers when it comes to luxury fashion… and how consumers may react to machine-made chic. Can AI Design Fashion Luxury? The researchers teamed up with AwayToMars, Missoni, and IBM Watson to create and sell t-shirts designed either by human designers or by AI. The AI, IBM Watson, was trained on designs previously discarded by AWTM, using machine learning to generate new design ideas based on recurring features and patterns. They conducted a controlled experiment with over 1,000 participants and analyzed real sales data of the t-shirts over 20 weeks. The results? Consumers preferred AI-designed t-shirts — but only if they didn’t know they were designed by AI. When the source was revealed, consumer enthusiasm waned. Sales data showed a whopping 127% increase for AI-designed shirts compared to human-designed ones. Turns out, when fashion is sold without disclaimers, AI might just have a better eye for the cutting edge. What Does This Mean for the Fashion Industry? AI-designed products can outsell human creations. In fact, AI-generated t-shirts outsold their human-designed counterparts by more than twofold in the study. This means that any sense of superiority capitalistically-inclined designers may have needed to be adjusted to a new reality. Consumer perception of AI is still a barrier. When consumers were informed that designs were AI-generated, their willingness to pay for the garments decreased (“Knowing that a luxury fashion item was designed by AI reduced consumers’ responses towards it.”) This reflects an ongoing distrust of AI’s creative capability. Some may be tempted to hide the use of AI in the face of these results, but consumers also value transparency, and laws are being proposed to improve that transparency. This no doubt will be the toughest nut to crack in the near future. AI can enhance brand identity. The AI-designed shirts more effectively embodied Missoni’s signature zigzag patterns and brand codes compared to the human designs. This can be well-received by customers and can reinforce a brand identity if used properly. “Trash” is more useful than we think. The AI drew inspiration from designs that had been previously discarded — transforming “waste” into wearable art. This highlights how AI’s capacity to learn from mass data can unlock the value of overlooked ideas. This is without a doubt my favorite part of the study. How Do We Move Forward? This is a lot to take in; enough to give fashion executives some vertigo. While they get their bearings, there are a few things the fashion community can push for. We need to implement mandatory AI disclosure in product descriptions. Transparency is crucial. Consumers should know if an item was designed by AI, even if it impacts their perception negatively. If 44% of participants disliked AI-designed fashion when informed, brands need to confront this distrust head-on to avoid backlash. “AI aversion” (as another study called it) suggests that transparency is necessary but should be handled with care. Brands might want to frame AI’s role in a positive light by focusing on efficiency, sustainability, or co-creation to mitigate negative perceptions. Fashion Houses need to expertly blend AI with humans. The AI designs from the study could have been reviewed and improved by designers, I’m sure. Allowing designers to steer AI’s outputs could preserve the “luxury touch” that customers associate with human creativity while benefiting from AI’s efficiency. This may even lead to better margins and perhaps (?) better pay for artisans who surely deserve it. Fashion houses need to establish strict, all-encompassing guidelines to future-proof their expertise. This includes establishing standards for what training data is used… and what data cannot/should not be used. AI in creative industries often relies on massive datasets, some of which are sourced unethically. Ensuring AI is trained ethically on licensed or voluntarily contributed data is key to gaining consumer trust. Nothing says luxury like ethics… right? Right? Above all, consumers need to be educated. Brands should invest in educating consumers on the strengths of AI for design — including sustainability and efficiency, where algorithms are likely well-placed to have an impact. Highlighting how AI uses discarded materials creatively, as seen with Missoni, could positively shift consumer sentiment. Where the Research Paper Falls Short While Moreau, Prandelli, and Schreier’s study brings some interesting insights to light, it is not without flaws. For one, all participants were business school students — hardly representative of the global, diverse consumer base of luxury fashion. It also didn’t explore whether consumers would prefer designs if AI had been marketed as an “assistant” rather than a “creator”. Furthermore, the research only touched upon visual identity, ignoring other sensory elements such as fabric texture and craftsmanship, which are crucial in luxury fashion. For future research, I’d love to see how AI fares when tasked with creating high-fashion couture pieces rather than simple t-shirts. How does it navigate avant-garde aesthetics or evolving cultural nuances? Probably not very well. Are Designers Doomed? Generative AI in luxury fashion is like a bold new fabric. One that can dazzle but also fray under scrutiny. If handled with care, AI could provide a much-needed spark of innovation while pushing the boundaries of design. The key lies in its careful integration, transparency, and cooperation with human experts. A future where AI complements, rather than replaces, human creativity isn’t just desirable… it might be our only shot at saving the soul of luxury. Good luck out there. Sounds (“Music”) and Images (“Art”) have been somewhat conquered by GenAI; it’s never been easier to create slop that’s “ close enough ” to the real thing. Creatives have taken notice, with 73% of them now believing that AI will significantly impact their industry . Sounds Images close enough 73% of them now believing that AI will significantly impact their industry Fashion has up until now been somewhat disconnected from these conversations. Sure, it’s a creative sector, but it also has glamor… and a certain exclusivity that makes AI’s infinite abundance seem gauche in comparison. But times are changing, and even the Milanese are now asking if machines could craft the kind of cultural cachet luxury designers have spent lifetimes building.’ Three researchers — Page Moreau from the University of Wisconsin-Madison, Emanuela Prandelli from Bocconi University, and Martin Schreier from WU Vienna — recently added complexity to this debate with a research paper titled, “ Generative Artificial Intelligence and Design Co-Creation in Luxury New Product Development: The Power of Discarded Ideas . ” Page Moreau Emanuela Prandelli Martin Schreier Generative Artificial Intelligence and Design Co-Creation in Luxury New Product Development: The Power of Discarded Ideas Generative Artificial Intelligence and Design Co-Creation in Luxury New Product Development: The Power of Discarded Ideas . Their research explores whether generative AI can compete with human designers when it comes to luxury fashion… and how consumers may react to machine-made chic. Can AI Design Fashion Luxury? The researchers teamed up with AwayToMars , Missoni , and IBM Watson to create and sell t-shirts designed either by human designers or by AI. The AI, IBM Watson, was trained on designs previously discarded by AWTM, using machine learning to generate new design ideas based on recurring features and patterns. They conducted a controlled experiment with over 1,000 participants and analyzed real sales data of the t-shirts over 20 weeks. AwayToMars Missoni The results? Consumers preferred AI-designed t-shirts — but only if they didn’t know they were designed by AI . When the source was revealed, consumer enthusiasm waned. Sales data showed a whopping 127% increase for AI-designed shirts compared to human-designed ones. but only if they didn’t know they were designed by AI Turns out, when fashion is sold without disclaimers, AI might just have a better eye for the cutting edge. What Does This Mean for the Fashion Industry? AI-designed products can outsell human creations. In fact, AI-generated t-shirts outsold their human-designed counterparts by more than twofold in the study. This means that any sense of superiority capitalistically-inclined designers may have needed to be adjusted to a new reality. AI-designed products can outsell human creations. In fact, AI-generated t-shirts outsold their human-designed counterparts by more than twofold in the study. This means that any sense of superiority capitalistically-inclined designers may have needed to be adjusted to a new reality. AI-designed products can outsell human creations. Consumer perception of AI is still a barrier. When consumers were informed that designs were AI-generated, their willingness to pay for the garments decreased (“Knowing that a luxury fashion item was designed by AI reduced consumers’ responses towards it.”) This reflects an ongoing distrust of AI’s creative capability. Some may be tempted to hide the use of AI in the face of these results, but consumers also value transparency, and laws are being proposed to improve that transparency. This no doubt will be the toughest nut to crack in the near future. Consumer perception of AI is still a barrier. When consumers were informed that designs were AI-generated, their willingness to pay for the garments decreased ( “Knowing that a luxury fashion item was designed by AI reduced consumers’ responses towards it.”) This reflects an ongoing distrust of AI’s creative capability. Some may be tempted to hide the use of AI in the face of these results, but consumers also value transparency, and laws are being proposed to improve that transparency. This no doubt will be the toughest nut to crack in the near future. Consumer perception of AI is still a barrier. “Knowing that a luxury fashion item was designed by AI reduced consumers’ responses towards it.”) AI can enhance brand identity. The AI-designed shirts more effectively embodied Missoni’s signature zigzag patterns and brand codes compared to the human designs. This can be well-received by customers and can reinforce a brand identity if used properly. AI can enhance brand identity. The AI-designed shirts more effectively embodied Missoni’s signature zigzag patterns and brand codes compared to the human designs. This can be well-received by customers and can reinforce a brand identity if used properly. AI can enhance brand identity. “Trash” is more useful than we think. The AI drew inspiration from designs that had been previously discarded — transforming “waste” into wearable art. This highlights how AI’s capacity to learn from mass data can unlock the value of overlooked ideas. This is without a doubt my favorite part of the study. “Trash” is more useful than we think. The AI drew inspiration from designs that had been previously discarded — transforming “waste” into wearable art. This highlights how AI’s capacity to learn from mass data can unlock the value of overlooked ideas. This is without a doubt my favorite part of the study. “Trash” is more useful than we think. How Do We Move Forward? This is a lot to take in; enough to give fashion executives some vertigo. While they get their bearings, there are a few things the fashion community can push for. We need to implement mandatory AI disclosure in product descriptions. We need to implement mandatory AI disclosure in product descriptions. Transparency is crucial. Consumers should know if an item was designed by AI, even if it impacts their perception negatively. If 44% of participants disliked AI-designed fashion when informed, brands need to confront this distrust head-on to avoid backlash. “AI aversion” ( as another study called it ) suggests that transparency is necessary but should be handled with care. as another study called it Brands might want to frame AI’s role in a positive light by focusing on efficiency, sustainability, or co-creation to mitigate negative perceptions. Fashion Houses need to expertly blend AI with humans. Fashion Houses need to expertly blend AI with humans. The AI designs from the study could have been reviewed and improved by designers, I’m sure. Allowing designers to steer AI’s outputs could preserve the “luxury touch” that customers associate with human creativity while benefiting from AI’s efficiency. This may even lead to better margins and perhaps (?) better pay for artisans who surely deserve it. Fashion houses need to establish strict, all-encompassing guidelines to future-proof their expertise. Fashion houses need to establish strict, all-encompassing guidelines to future-proof their expertise. This includes establishing standards for what training data is used… and what data cannot/should not be used. AI in creative industries often relies on massive datasets, some of which are sourced unethically. Ensuring AI is trained ethically on licensed or voluntarily contributed data is key to gaining consumer trust. Nothing says luxury like ethics… right? Right? Above all, consumers need to be educated. Above all, consumers need to be educated. Brands should invest in educating consumers on the strengths of AI for design — including sustainability and efficiency, where algorithms are likely well-placed to have an impact. Highlighting how AI uses discarded materials creatively, as seen with Missoni, could positively shift consumer sentiment. Where the Research Paper Falls Short While Moreau , Prandelli , and Schreier ’s study brings some interesting insights to light, it is not without flaws. For one, all participants were business school students — hardly representative of the global, diverse consumer base of luxury fashion. Moreau Prandelli Schreier It also didn’t explore whether consumers would prefer designs if AI had been marketed as an “assistant” rather than a “creator”. Furthermore, the research only touched upon visual identity, ignoring other sensory elements such as fabric texture and craftsmanship, which are crucial in luxury fashion. For future research, I’d love to see how AI fares when tasked with creating high-fashion couture pieces rather than simple t-shirts. How does it navigate avant-garde aesthetics or evolving cultural nuances? Probably not very well. Are Designers Doomed? Generative AI in luxury fashion is like a bold new fabric. One that can dazzle but also fray under scrutiny. If handled with care, AI could provide a much-needed spark of innovation while pushing the boundaries of design. The key lies in its careful integration, transparency, and cooperation with human experts. A future where AI complements, rather than replaces, human creativity isn’t just desirable… it might be our only shot at saving the soul of luxury. Good luck out there.

Would You Still Love a $500 T-Shirt If You Knew AI Designed It?

Sal jy steeds van 'n $500 T-hemp hou as jy geweet het dat KI dit ontwerp het?

AI ዲዛይኑን ካወቁ አሁንም የ500 ዶላር ቲሸርት ይወዳሉ?

¿Aún te gustaría una camiseta de 500 dólares si supieras que fue diseñada por una IA?

اگر می دانستید که هوش مصنوعی آن را طراحی کرده است، آیا هنوز عاشق یک تی شرت 500 دلاری هستید؟

यदि आपको पता हो कि 500 डॉलर की टी-शर्ट को AI ने डिज़ाइन किया है, तो क्या आप उसे अब भी पसंद करेंगे?

Ti piacerebbe ancora una maglietta da 500 dollari se sapessi che è stata progettata dall'intelligenza artificiale?

AI がデザインした 500 ドルの T シャツをまだ気に入っていますか?

კიდევ გიყვართ 500 დოლარიანი მაისური, თუ იცოდით, რომ ხელოვნური ინტელექტის დიზაინია?

AI가 디자인했다고 해도 500달러짜리 티셔츠를 여전히 좋아할까요?

ایا تاسو به بیا هم د 500 ډالرو ټي شرټ خوښ کړئ که تاسو پوهیږئ چې AI یې ډیزاین کړی؟

Xana Wa Ha Swi Rhandza Xikipa Xa R1 000 Loko U Swi Tiva Leswaku AI Yi Xi Endlile?

Bạn có còn thích áo phông giá 500 đô la không nếu biết nó được thiết kế bởi AI?

Hey there! In case you missed it, the #AI-chatbot writing contest has been going strong for a little over two months now, since it kicked off on August 6, 2024. In the spirit of the AI season, Coze and HackerNoon teamed up to invite all AI enthusiasts, developers, and writers to build personalized AI chatbots on Coze for a shot at over $7000 in prizes. AI chatbots are becoming an essential part of our digital lives. But for too long, the power to shape AI has been limited to a few. Now, it's your turn to decide. Need an AI bot to help train your puppies, like the one Daria Leonova built? You can have that! Or maybe you're a finance guru like Kickboxer J and want a bot to analyze financial info. The choice is yours, and with Coze, you can make it happen—even if you don’t have any coding skills. That’s right! Coze is a no-code platform, so anyone can jump in and create awesome chatbots After you build your chatbot, share it on HackerNoon with the #ai-chatbot tag using this template before 11:59 PM (EST) on November 6, 2024. And just like that, you’ll be in the running for some fantastic prizes: Prize Breakdown
The  #AI-chatbot writing contest will award up to 11 writers as follows:



Entry Type

Prizes



Best Coze Use-Case/App Story

$3000 | 1 month Coze Premium Plus | 10M Coze Tokens



Top 2 Coze Experience Stories

$1000 each | 1 month Coze Premium each | 5M Coze tokens each



Top 2 AI Chatbot Stories

$500 each | 1 month Coze Premium each | 5M Coze tokens each



Best NoCode Story

$500 | 1 month Coze Premium | 5M Coze tokens



Coze Power Writers’ Rewards

1 month Coze Premium for 5 contributors How to Enter Step 1: Watch the Compete Coze Tutorial for Building an AI Chatbot https://www.youtube.com/watch?v=x2z9dQEEQq0&embedable=true Step 2: Build Your AI Chatbot on Coze Follow the steps in the tutorial above and get creative with your own AI chatbot. Step 3: Share Your Process on HackerNoon with the #ai-chatbot Tag After you create your chatbot, write a HackerNoon article based on your experience using the #ai-chatbot tag. You can take on one of two roles: be a teacher by providing step-by-step guides for creating Coze AI bots and deploying them on platforms like Telegram and Discord, or be an innovator by sharing how you built your unique AI chatbot. Ready to get started?
Join the #ai-chatbot writing contest now using this template: https://app.hackernoon.com/new?template=ai-chatbot-template
We can’t wait to see what you create! Extra Steps: Learn more about Coze: https://www.coze.com/docs/welcome.html
More tutorials: https://www.youtube.com/@CozeHQ
Join the contest discussion on Discord: coze-hackernoon-writing-contest.
Share your article in the Coze "share-your-bot" channel for more reach. Contest Rules and Guidelines Must be 18+ to enter (no location restrictions)​
Create a HackerNoon account
Create a Coze account
You can enter the contest by adding the #ai-chatbot tag to your story
No AI-generated entries. (Read: the acceptable way to use AI on HackerNoon) FAQs Can I write under a pen name? Yes!You can use your real name, or a pseudonym when setting up your HackerNoon profile. When does the submissions window close? The submission window closes on November 6, 2024  [11:59 PM EST] How are the winners selected? After the contest ends, we’ll review submitted entries and shortlist the stories that receive the most eyeballs (real humans, not bots!).
Next, the shortlisted stories will be voted on by HackerNoon staff.
The top Coze use-case/app story, the top 2 Coze experience stories, the top 2 AI Chatbot stories, and the top no-code stories will be selected and announced. Ready to give it a shot? Start a draft now, or use this template to enter the #AI-chatbot writing contest. Good luck and may the force be with you! Hey there! In case you missed it, the #AI-chatbot writing contest has been going strong for a little over two months now, since it kicked off on August 6, 2024. In the spirit of the AI season, Coze and HackerNoon teamed up to invite all AI enthusiasts, developers, and writers to build personalized AI chatbots on Coze for a shot at over $7000 in prizes. #AI-chatbot writing contest AI chatbots are becoming an essential part of our digital lives. But for too long, the power to shape AI has been limited to a few. Now, it's your turn to decide. Need an AI bot to help train your puppies , like the one Daria Leonova built? You can have that! Or maybe you're a finance guru like Kickboxer J and want a bot to analyze financial info . The choice is yours, and with Coze, you can make it happen—even if you don’t have any coding skills. Need an AI bot to help train your puppies Daria Leonova Kickboxer J a bot to analyze financial info That’s right! Coze is a no-code platform, so anyone can jump in and create awesome chatbots Coze After you build your chatbot, share it on HackerNoon with the #ai-chatbot tag using this template before 11:59 PM (EST) on November 6, 2024. And just like that, you’ll be in the running for some fantastic prizes: #ai-chatbot this template 11:59 PM (EST) on November 6, 2024. Prize Breakdown The  #AI-chatbot writing contest will award up to 11 writers as follows: Entry Type

Prizes



Best Coze Use-Case/App Story

$3000 | 1 month Coze Premium Plus | 10M Coze Tokens



Top 2 Coze Experience Stories

$1000 each | 1 month Coze Premium each | 5M Coze tokens each



Top 2 AI Chatbot Stories

$500 each | 1 month Coze Premium each | 5M Coze tokens each



Best NoCode Story

$500 | 1 month Coze Premium | 5M Coze tokens



Coze Power Writers’ Rewards

1 month Coze Premium for 5 contributors Prize Breakdown Prize Breakdown The  #AI-chatbot writing contest will award up to 11 writers as follows: The  #AI-chatbot writing contest will award up to 11 writers as follows: Entry Type

Prizes



Best Coze Use-Case/App Story

$3000 | 1 month Coze Premium Plus | 10M Coze Tokens



Top 2 Coze Experience Stories

$1000 each | 1 month Coze Premium each | 5M Coze tokens each



Top 2 AI Chatbot Stories

$500 each | 1 month Coze Premium each | 5M Coze tokens each



Best NoCode Story

$500 | 1 month Coze Premium | 5M Coze tokens



Coze Power Writers’ Rewards

1 month Coze Premium for 5 contributors Entry Type

Prizes Best Coze Use-Case/App Story

$3000 | 1 month Coze Premium Plus | 10M Coze Tokens Top 2 Coze Experience Stories

$1000 each | 1 month Coze Premium each | 5M Coze tokens each Top 2 AI Chatbot Stories

$500 each | 1 month Coze Premium each | 5M Coze tokens each Best NoCode Story

$500 | 1 month Coze Premium | 5M Coze tokens Coze Power Writers’ Rewards

1 month Coze Premium for 5 contributors Entry Type Prizes Entry Type Entry Type Prizes Prizes Best Coze Use-Case/App Story $3000 | 1 month Coze Premium Plus | 10M Coze Tokens Best Coze Use-Case/App Story Best Coze Use-Case/App Story Best Coze Use-Case/App Story $3000 | 1 month Coze Premium Plus | 10M Coze Tokens $3000 | 1 month Coze Premium Plus | 10M Coze Tokens $3000 | Top 2 Coze Experience Stories $1000 each | 1 month Coze Premium each | 5M Coze tokens each Top 2 Coze Experience Stories Top 2 Coze Experience Stories Top 2 Coze Experience Stories $1000 each | 1 month Coze Premium each | 5M Coze tokens each $1000 each | 1 month Coze Premium each | 5M Coze tokens each $1000 each | Top 2 AI Chatbot Stories $500 each | 1 month Coze Premium each | 5M Coze tokens each Top 2 AI Chatbot Stories Top 2 AI Chatbot Stories Top 2 AI Chatbot Stories $500 each | 1 month Coze Premium each | 5M Coze tokens each $500 each | 1 month Coze Premium each | 5M Coze tokens each $500 each | Best NoCode Story $500 | 1 month Coze Premium | 5M Coze tokens Best NoCode Story Best NoCode Story Best NoCode Story $500 | 1 month Coze Premium | 5M Coze tokens $500 | 1 month Coze Premium | 5M Coze tokens $500 | Coze Power Writers’ Rewards 1 month Coze Premium for 5 contributors Coze Power Writers’ Rewards Coze Power Writers’ Rewards Coze Power Writers’ Rewards 1 month Coze Premium for 5 contributors 1 month Coze Premium for 5 contributors How to Enter Step 1: Watch the Compete Coze Tutorial for Building an AI Chatbot https://www.youtube.com/watch?v=x2z9dQEEQq0&embedable=true https://www.youtube.com/watch?v=x2z9dQEEQq0&embedable=true Step 2: Build Your AI Chatbot on Coze Follow the steps in the tutorial above and get creative with your own AI chatbot. Step 3: Share Your Process on HackerNoon with the #ai-chatbot Tag After you create your chatbot, write a HackerNoon article based on your experience using the #ai-chatbot tag. You can take on one of two roles: be a teacher by providing step-by-step guides for creating Coze AI bots and deploying them on platforms like Telegram and Discord, or be an innovator by sharing how you built your unique AI chatbot. teacher innovator Ready to get started? Join the #ai-chatbot writing contest now using this template: https://app.hackernoon.com/new?template=ai-chatbot-template We can’t wait to see what you create! Ready to get started? Ready to get started? Ready to get started? Join the #ai-chatbot writing contest now using this template: https://app.hackernoon.com/new?template=ai-chatbot-template Join the #ai-chatbot writing contest now using this template: https://app.hackernoon.com/new?template=ai-chatbot-template We can’t wait to see what you create! Extra Steps: Learn more about Coze: https://www.coze.com/docs/welcome.html More tutorials: https://www.youtube.com/@CozeHQ Join the contest discussion on Discord: coze-hackernoon-writing-contest. Share your article in the Coze "share-your-bot" channel for more reach. Learn more about Coze: https://www.coze.com/docs/welcome.html https://www.coze.com/docs/welcome.html More tutorials: https://www.youtube.com/@CozeHQ https://www.youtube.com/@CozeHQ Join the contest discussion on Discord: coze-hackernoon-writing-contest . coze-hackernoon-writing-contest coze-hackernoon-writing-contest Share your article in the Coze "share-your-bot" channel for more reach. Contest Rules and Guidelines Must be 18+ to enter (no location restrictions)​ Create a HackerNoon account Create a Coze account You can enter the contest by adding the #ai-chatbot tag to your story No AI-generated entries. (Read: the acceptable way to use AI on HackerNoon) Must be 18+ to enter (no location restrictions)​ Create a HackerNoon account Create a HackerNoon account Create a HackerNoon account Create a Coze account Create a Coze account Create a Coze account You can enter the contest by adding the #ai-chatbot tag to your story #ai-chatbot #ai-chatbot No AI-generated entries. (Read: the acceptable way to use AI on HackerNoon ) the acceptable way to use AI on HackerNoon the acceptable way to use AI on HackerNoon FAQs Can I write under a pen name? Can I write under a pen name? Yes!You can use your real name, or a pseudonym when setting up your HackerNoon profile. Yes! You can use your real name, or a pseudonym when setting up your HackerNoon profile. When does the submissions window close? When does the submissions window close? The submission window closes on November 6, 2024  [11:59 PM EST] The submission window closes on November 6, 2024  [11:59 PM EST] November 6, 2024  [11:59 PM EST] How are the winners selected? How are the winners selected? After the contest ends, we’ll review submitted entries and shortlist the stories that receive the most eyeballs (real humans, not bots!).
Next, the shortlisted stories will be voted on by HackerNoon staff.
The top Coze use-case/app story, the top 2 Coze experience stories, the top 2 AI Chatbot stories, and the top no-code stories will be selected and announced. After the contest ends, we’ll review submitted entries and shortlist the stories that receive the most eyeballs (real humans, not bots!). Next, the shortlisted stories will be voted on by HackerNoon staff. The top Coze use-case/app story, the top 2 Coze experience stories, the top 2 AI Chatbot stories, and the top no-code stories will be selected and announced. After the contest ends, we’ll review submitted entries and shortlist the stories that receive the most eyeballs (real humans, not bots!). Next, the shortlisted stories will be voted on by HackerNoon staff. The top Coze use-case/app story, the top 2 Coze experience stories, the top 2 AI Chatbot stories, and the top no-code stories will be selected and announced. Ready to give it a shot? Ready to give it a shot? Start a draft now, or use this template to enter the #AI-chatbot writing contest. Start a draft now, or use this template to enter the #AI-chatbot writing contest. Start a draft now , or use this template to enter the #AI-chatbot writing contest. Start a draft now use this template #AI-chatbot writing contest. Good luck and may the force be with you!

Got a Cool Idea for an AI Bot? Here’s How It Could Win You $3000 in the #AI-Chatbot Writing Contest

MAHE, Seychelles, October 9th, 2024/Chainwire/--ATLETA Network, modular, multi-layer blockchain for the sports industry, has teamed up with Bybit, one of the leading global crypto exchanges. This marketing strategic partnership will provide new users with a chance to win incredible prizes: a racing car Porsche 718, wrist watches Rolex, iPhone 16 Pro, and more. The ATLETA-Bybit Event kicked off on October 3rd, 2024. All participants have the opportunity to secure major rewards by joining, depositing, and trading. Here’s how it works: Those interested can register for the event using the official link.


Deposit $100.


Open and complete a futures trade in 3 minutes with a trading volume of over $100 ($25 with x4 leverage or $10 with x10).


Hold the funds for at least 7 days without withdrawals. By completing the task, participants automatically enter the ATLETA-Bybit Lucky Draw. The more participants, the bigger and better the prizes: 80 participants: PS5 for 1 lucky winner;


200 participants: PS5 + iPhone 16 Pro for 2 winners;


1,300 participants: PS5 + iPhone 16 Pro + Rolex for 3 winners;


10,000 participants: Porsche 718 + PS5 + iPhone 16 Pro + Rolex for 4 winners. Once users complete the task, they can claim an immediate $15 bonus via the Bybit reward hub. After the event concludes, all eligible participants will also receive an additional 5 USDT airdrop. "The ATLETA-Bybit partnership exemplifies the convergence of cutting-edge blockchain technology and user-centric engagement. It’s an opportunity for our community to experience firsthand the possibilities that arise when blockchain innovation meets tangible rewards. As we prepare for our mainnet, this collaboration shows how ATLETA can create unique, value-driven user experiences. Bybit shares our vision for a future where technology empowers people, and together, we are setting new standards in both industries," says Alex Grigorev, the CMO of ATLETA. ATLETA Getting Ready for Mainnet While the ATLETA-Bybit collaboration gains attention, ATLETA is polishing its platform for full-scale deployment. The Olympia Testnet gave the team a real-world look at ATLETA’s smooth cross-chain interoperability and real-time data tracking. The results impressed the team: with over 800 thousand users and 17,5 million transactions, ATLETA feels it is time to deploy the mainnet. ATLETA’s mainnet will offer a suite of features: EVM compatibility that allows for superfluid capital transfusion and application composability; Parachains that can enable all market participants to deploy customized networks on ATLETA; XCM functionality that grants independent connected networks with communications capabilities; BABE + GRANDPA that ensures secure block building and transaction finality. At the heart of this system lies the Nominated Proof-of-Stake (NPoS) mechanism, a balanced randomization engine that provides fair grounds for validators and nominators to collaborate and maintain the network integrity while having the chance to earn rewards. ATLETA’s key features translate into the application layer, where over 5,500 smart contracts have already been deployed to take advantage of the varying feature functionalities: Decentralized Exchange (DEX) to trade assets; On-Chain Explorer to track and inspect historical transactions, blocks, and smart contracts; Digital ID Platform the launchpad and marketplace to participate in IAOs and conduct SportFi activities by trading digital IDs; Staking to incentivize network operators with rewards opportunities for securing the network; Governance for distributing decision-making power amongst stakeholders to guide the direction of the network's development and vote on decisions collectively. "The upcoming mainnet launch is the culmination of months of innovation and relentless pursuit of excellence. It’s where all the potential we’ve built into ATLETA comes to life, and we’re ready to show the world how blockchain can truly transform the sports industry," emphasized Andrey Didovsky, the CEO of ATLETA. About ATLETA ATLETA Network is the first modular, multi-layer, blockchain with native cross-chain interoperability. ATLETA addresses critical challenges of transparency, fairness, and trust in sports. Leveraging blockchain technology, ATLETA enables an immutable, tamper-proof infrastructure for athlete performance data, contracts, and health records. Backed by the Blockchain Sports Ecosystem, which integrates AI analytics, performance tracking, VR, and blockchain technology, ATLETA is contributing to a foundation for a more fair, transparent, and innovative future for sports worldwide. Contact PR Manager Polina Krischanovich ATLETA Network p.krischanovich@atomgroup.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. MAHE, Seychelles, October 9th, 2024/Chainwire/--ATLETA Network, modular, multi-layer blockchain for the sports industry, has teamed up with Bybit, one of the leading global crypto exchanges. This marketing strategic partnership will provide new users with a chance to win incredible prizes: a racing car Porsche 718, wrist watches Rolex, iPhone 16 Pro, and more. The ATLETA-Bybit Event kicked off on October 3rd, 2024. All participants have the opportunity to secure major rewards by joining, depositing, and trading. Here’s how it works: Those interested can register for the event using the official link. Deposit $100. Open and complete a futures trade in 3 minutes with a trading volume of over $100 ($25 with x4 leverage or $10 with x10). Hold the funds for at least 7 days without withdrawals. Those interested can register for the event using the official link. Those interested can register for the event using the official link. Deposit $100. Deposit $100. Open and complete a futures trade in 3 minutes with a trading volume of over $100 ($25 with x4 leverage or $10 with x10). Open and complete a futures trade in 3 minutes with a trading volume of over $100 ($25 with x4 leverage or $10 with x10). Hold the funds for at least 7 days without withdrawals. Hold the funds for at least 7 days without withdrawals. By completing the task, participants automatically enter the ATLETA-Bybit Lucky Draw. The more participants, the bigger and better the prizes: 80 participants: PS5 for 1 lucky winner; 200 participants: PS5 + iPhone 16 Pro for 2 winners; 1,300 participants: PS5 + iPhone 16 Pro + Rolex for 3 winners; 10,000 participants: Porsche 718 + PS5 + iPhone 16 Pro + Rolex for 4 winners. 80 participants: PS5 for 1 lucky winner; 80 participants: PS5 for 1 lucky winner; 200 participants: PS5 + iPhone 16 Pro for 2 winners; 200 participants: PS5 + iPhone 16 Pro for 2 winners; 1,300 participants: PS5 + iPhone 16 Pro + Rolex for 3 winners; 1,300 participants: PS5 + iPhone 16 Pro + Rolex for 3 winners; 10,000 participants: Porsche 718 + PS5 + iPhone 16 Pro + Rolex for 4 winners. 10,000 participants: Porsche 718 + PS5 + iPhone 16 Pro + Rolex for 4 winners. Once users complete the task, they can claim an immediate $15 bonus via the Bybit reward hub. After the event concludes, all eligible participants will also receive an additional 5 USDT airdrop. "The ATLETA-Bybit partnership exemplifies the convergence of cutting-edge blockchain technology and user-centric engagement. It’s an opportunity for our community to experience firsthand the possibilities that arise when blockchain innovation meets tangible rewards. As we prepare for our mainnet, this collaboration shows how ATLETA can create unique, value-driven user experiences. Bybit shares our vision for a future where technology empowers people, and together, we are setting new standards in both industries," says Alex Grigorev, the CMO of ATLETA. "The ATLETA-Bybit partnership exemplifies the convergence of cutting-edge blockchain technology and user-centric engagement. It’s an opportunity for our community to experience firsthand the possibilities that arise when blockchain innovation meets tangible rewards. As we prepare for our mainnet, this collaboration shows how ATLETA can create unique, value-driven user experiences. Bybit shares our vision for a future where technology empowers people, and together, we are setting new standards in both industries," says Alex Grigorev, the CMO of ATLETA. ATLETA Getting Ready for Mainnet While the ATLETA-Bybit collaboration gains attention, ATLETA is polishing its platform for full-scale deployment. The Olympia Testnet gave the team a real-world look at ATLETA’s smooth cross-chain interoperability and real-time data tracking. The results impressed the team: with over 800 thousand users and 17,5 million transactions, ATLETA feels it is time to deploy the mainnet. ATLETA’s mainnet will offer a suite of features: EVM compatibility that allows for superfluid capital transfusion and application composability; EVM compatibility that allows for superfluid capital transfusion and application composability; Parachains that can enable all market participants to deploy customized networks on ATLETA; Parachains that can enable all market participants to deploy customized networks on ATLETA; XCM functionality that grants independent connected networks with communications capabilities; XCM functionality that grants independent connected networks with communications capabilities; BABE + GRANDPA that ensures secure block building and transaction finality. BABE + GRANDPA that ensures secure block building and transaction finality. At the heart of this system lies the Nominated Proof-of-Stake (NPoS) mechanism, a balanced randomization engine that provides fair grounds for validators and nominators to collaborate and maintain the network integrity while having the chance to earn rewards. ATLETA’s key features translate into the application layer, where over 5,500 smart contracts have already been deployed to take advantage of the varying feature functionalities: Decentralized Exchange (DEX) to trade assets; Decentralized Exchange (DEX) to trade assets; On-Chain Explorer to track and inspect historical transactions, blocks, and smart contracts; On-Chain Explorer to track and inspect historical transactions, blocks, and smart contracts; Digital ID Platform the launchpad and marketplace to participate in IAOs and conduct SportFi activities by trading digital IDs; Digital ID Platform the launchpad and marketplace to participate in IAOs and conduct SportFi activities by trading digital IDs; Staking to incentivize network operators with rewards opportunities for securing the network; Staking to incentivize network operators with rewards opportunities for securing the network; Governance for distributing decision-making power amongst stakeholders to guide the direction of the network's development and vote on decisions collectively. Governance for distributing decision-making power amongst stakeholders to guide the direction of the network's development and vote on decisions collectively. "The upcoming mainnet launch is the culmination of months of innovation and relentless pursuit of excellence. It’s where all the potential we’ve built into ATLETA comes to life, and we’re ready to show the world how blockchain can truly transform the sports industry," emphasized Andrey Didovsky, the CEO of ATLETA. "The upcoming mainnet launch is the culmination of months of innovation and relentless pursuit of excellence. It’s where all the potential we’ve built into ATLETA comes to life, and we’re ready to show the world how blockchain can truly transform the sports industry," emphasized Andrey Didovsky, the CEO of ATLETA. About ATLETA ATLETA Network is the first modular, multi-layer, blockchain with native cross-chain interoperability. ATLETA addresses critical challenges of transparency, fairness, and trust in sports. Leveraging blockchain technology, ATLETA enables an immutable, tamper-proof infrastructure for athlete performance data, contracts, and health records. Backed by the Blockchain Sports Ecosystem, which integrates AI analytics, performance tracking, VR, and blockchain technology, ATLETA is contributing to a foundation for a more fair, transparent, and innovative future for sports worldwide. Contact PR Manager Polina Krischanovich ATLETA Network p.krischanovich@atomgroup.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

ATLETA And Bybit Forge Powerful Partnership: A Chance To Win Real Porsche, Rolex or iPhone

ATLETA এবং Bybit Forge শক্তিশালী অংশীদারিত্ব: রিয়েল পোর্শে, রোলেক্স বা আইফোন জয়ের একটি সুযোগ

ATLETA y Bybit forjan una poderosa alianza: una oportunidad de ganar un Porsche, un Rolex o un iPhone auténticos

ATLETA と Bybit が強力なパートナーシップを締結: 本物のポルシェ、ロレックス、iPhone を獲得するチャンス

ATLETA жана Bybit Forge күчтүү өнөктөштүк: чыныгы Porsche, Rolex же iPhone утуп алуу мүмкүнчүлүгү

ATLETA Na Bybit Forge Partenariat Puissant: Chance Ya Ko Gagner Vrai Porsche, Rolex to iPhone

ATLETA sy Bybit dia manangana fiaraha-miasa matanjaka: fahafahana hahazo ny tena Porsche, Rolex na iPhone

ATLETA болон Bybit хүчирхэг түншлэлийг бий болгодог: Бодит Porsche, Rolex эсвэл iPhone ялах боломж

ATLETA uye Bybit Forge Yakasimba Kudyidzana: Mukana Wekuhwina Chaiyo Porsche, Rolex kana iPhone

АТЛЕТА и Бибит стварају моћно партнерство: шанса да освојите прави Порсцхе, Ролек или иПхоне

“ATLETA” we “Bybit” güýçli hyzmatdaşlygy döredýär: “Real Porsche”, “Rolex” ýa-da “iPhone” -y gazanmak mümkinçiligi

Ang ATLETA At Bybit ay Bumuo ng Mabisang Pagtutulungan: Isang Tsansang Manalo ng Tunay na Porsche, Rolex o iPhone

ATLETA và Bybit tạo nên mối quan hệ đối tác mạnh mẽ: Cơ hội trúng thưởng Porsche, Rolex hoặc iPhone thật

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