Creaitiv

creaitiv

The creative process in design has always been about pushing boundaries, exploring new frontiers, and reimagining what’s possible. As we continue to integrate advanced computational methods into the design workflow, one particularly exciting avenue is the exploration of latent spaces within generative systems. Latent spaces, the abstract realms where generative models operate, offer unprecedented opportunities for designers to engage with their creations in new and interactive ways. In this article, I will introduce "Browsing the Latent Space" (BLS), an interactive tool that leverages the potential of latent space visualization and interpolation within 3D generative systems. This tool, developed as part of a broader research initiative, enhances the design exploration process by providing designers with intuitive and powerful ways to understand, manipulate, and generate new designs. Redefining Design Exploration with Latent Spaces Generative systems have gained significant traction across various creative domains, from art and music to design and architecture. However, interactions with these systems are often limited to a somewhat random and unpredictable process—running a model, waiting for an output, and hoping it aligns with the designer's intent. But what if there was a way to delve deeper into the mechanics of these systems, to understand and even control how they generate their outputs? This is where the concept of latent spaces comes into play. A latent space is a lower-dimensional representation of the data that a generative model has learned during its training process. It captures the underlying patterns and structures within the data, which can be manipulated to create new designs. By visualizing and interacting with this space, designers can gain valuable insights into how the generative system interprets their inputs, leading to more informed and creative design decisions. Experimenting with Generative Systems: The Case of 3D Chairs In our research, we focused on chairs as a case study for exploring the creative possibilities of latent space. Chairs, a staple of design practice, offer a rich ground for experimentation, especially within the context of generative systems. Drawing inspiration from the culture of remixing and iterative design, we sought to enhance the creative process by providing designers with tools to explore, remix, and create new chair designs using latent space. We utilized the GET3D generative model—a powerful tool capable of generating high-quality 3D models. By tapping into the latent space of this model, we were able to visualize and manipulate the features that define the chairs. This approach not only gives designers a better understanding of the generative system but also allows for the creation of entirely new designs that lie between existing ones in the latent space. Visualizing Latent Space: From Abstract Data to Tangible Designs One of the key innovations in our approach is the visualization of latent space. High-dimensional data, such as that produced by generative models, can be difficult to interpret and navigate. To overcome this challenge, we employed a dimensionality reduction technique to project the latent space into a two-dimensional map. This map provides a visual representation of how different chair designs are distributed based on their features, such as texture and shape. The visualization allows designers to zoom, pan, and explore the latent space interactively. They can see how similar designs are grouped together, revealing the underlying structure that the generative model has learned. This not only aids in understanding the model's behavior but also opens up new possibilities for creative exploration. Interpolation: Creating New Designs from Existing Ones Beyond visualization, the BLS tool also includes an interpolation feature that enables designers to create new chair designs by blending existing ones. Interpolation in the latent space involves generating new points between known data points (in this case, existing chair designs) and observing the resulting designs. This process allows designers to explore smooth transitions between different design features, leading to the creation of innovative and unique outputs. For example, a designer can select two or more chairs from the latent space and use the interpolation tool to generate intermediate designs that blend the characteristics of the selected chairs. This process is akin to navigating through a vast design landscape, where each step reveals new possibilities and combinations that were previously unexplored. A New Paradigm for Design Exploration The "Browsing the Latent Space" tool represents a significant advancement in how designers can interact with generative systems. By providing intuitive access to the latent space, we empower designers to move beyond the limitations of traditional design exploration methods. This approach not only enhances creativity but also offers a deeper understanding of how generative models function, leading to more informed and innovative design practices. As we continue to refine and expand this tool, we envision it becoming an essential part of the designer's toolkit. Future iterations could include real-time cloud-based model inference, more sophisticated dimensionality reduction algorithms, and the application of this approach to other generative systems beyond 3D chairs. Conclusion: The Future of Creative Exploration The integration of latent space exploration into the design process marks a new era of creativity and innovation. By unlocking the potential of generative systems, designers can push the boundaries of what’s possible, creating designs that are not only novel but also deeply informed by the underlying mechanics of the models they use. The future of design lies in our ability to harness these advanced computational tools, and the "Browsing the Latent Space" tool is just the beginning. As we continue to explore and refine these technologies, the possibilities for creative exploration are limitless. For a hands-on experience with the BLS tool or to learn more about the underlying research, visit the project website at [insert link here] or read the full research article titled "Browsing the Latent Space: A New Approach to Interactive Design Exploration for Volumetric Generative Systems." https://tcabezon.github.io/ls-exploration-tool/?embedable=true For more details or to interact with the BLS tool, refer to the project website:https://tcabezon.github.io/ls-exploration-tool/ or the research article: "Browsing the Latent Space: A New Approach to Interactive Design Exploration for Volumetric Generative Systems" that includes the whole research process that is behind this project. The creative process in design has always been about pushing boundaries, exploring new frontiers, and reimagining what’s possible. As we continue to integrate advanced computational methods into the design workflow, one particularly exciting avenue is the exploration of latent spaces within generative systems. Latent spaces, the abstract realms where generative models operate, offer unprecedented opportunities for designers to engage with their creations in new and interactive ways. In this article, I will introduce "Browsing the Latent Space" (BLS), an interactive tool that leverages the potential of latent space visualization and interpolation within 3D generative systems. This tool, developed as part of a broader research initiative, enhances the design exploration process by providing designers with intuitive and powerful ways to understand, manipulate, and generate new designs. Redefining Design Exploration with Latent Spaces Generative systems have gained significant traction across various creative domains, from art and music to design and architecture. However, interactions with these systems are often limited to a somewhat random and unpredictable process—running a model, waiting for an output, and hoping it aligns with the designer's intent. But what if there was a way to delve deeper into the mechanics of these systems, to understand and even control how they generate their outputs? This is where the concept of latent spaces comes into play. A latent space is a lower-dimensional representation of the data that a generative model has learned during its training process. It captures the underlying patterns and structures within the data, which can be manipulated to create new designs. By visualizing and interacting with this space, designers can gain valuable insights into how the generative system interprets their inputs, leading to more informed and creative design decisions. Experimenting with Generative Systems: The Case of 3D Chairs In our research, we focused on chairs as a case study for exploring the creative possibilities of latent space. Chairs, a staple of design practice, offer a rich ground for experimentation, especially within the context of generative systems. Drawing inspiration from the culture of remixing and iterative design, we sought to enhance the creative process by providing designers with tools to explore, remix, and create new chair designs using latent space. We utilized the GET3D generative model—a powerful tool capable of generating high-quality 3D models. By tapping into the latent space of this model, we were able to visualize and manipulate the features that define the chairs. This approach not only gives designers a better understanding of the generative system but also allows for the creation of entirely new designs that lie between existing ones in the latent space. Visualizing Latent Space: From Abstract Data to Tangible Designs One of the key innovations in our approach is the visualization of latent space. High-dimensional data, such as that produced by generative models, can be difficult to interpret and navigate. To overcome this challenge, we employed a dimensionality reduction technique to project the latent space into a two-dimensional map. This map provides a visual representation of how different chair designs are distributed based on their features, such as texture and shape. The visualization allows designers to zoom, pan, and explore the latent space interactively. They can see how similar designs are grouped together, revealing the underlying structure that the generative model has learned. This not only aids in understanding the model's behavior but also opens up new possibilities for creative exploration. Interpolation: Creating New Designs from Existing Ones Beyond visualization, the BLS tool also includes an interpolation feature that enables designers to create new chair designs by blending existing ones. Interpolation in the latent space involves generating new points between known data points (in this case, existing chair designs) and observing the resulting designs. This process allows designers to explore smooth transitions between different design features, leading to the creation of innovative and unique outputs. For example, a designer can select two or more chairs from the latent space and use the interpolation tool to generate intermediate designs that blend the characteristics of the selected chairs. This process is akin to navigating through a vast design landscape, where each step reveals new possibilities and combinations that were previously unexplored. A New Paradigm for Design Exploration The "Browsing the Latent Space" tool represents a significant advancement in how designers can interact with generative systems. By providing intuitive access to the latent space, we empower designers to move beyond the limitations of traditional design exploration methods. This approach not only enhances creativity but also offers a deeper understanding of how generative models function, leading to more informed and innovative design practices. As we continue to refine and expand this tool, we envision it becoming an essential part of the designer's toolkit. Future iterations could include real-time cloud-based model inference, more sophisticated dimensionality reduction algorithms, and the application of this approach to other generative systems beyond 3D chairs. Conclusion: The Future of Creative Exploration The integration of latent space exploration into the design process marks a new era of creativity and innovation. By unlocking the potential of generative systems, designers can push the boundaries of what’s possible, creating designs that are not only novel but also deeply informed by the underlying mechanics of the models they use. The future of design lies in our ability to harness these advanced computational tools, and the "Browsing the Latent Space" tool is just the beginning. As we continue to explore and refine these technologies, the possibilities for creative exploration are limitless. For a hands-on experience with the BLS tool or to learn more about the underlying research, visit the project website at [insert link here] or read the full research article titled "Browsing the Latent Space: A New Approach to Interactive Design Exploration for Volumetric Generative Systems." https://tcabezon.github.io/ls-exploration-tool/?embedable=true https://tcabezon.github.io/ls-exploration-tool/?embedable=true For more details or to interact with the BLS tool, refer to the project website: https://tcabezon.github.io/ls-exploration-tool/ or the research article: "Browsing the Latent Space: A New Approach to Interactive Design Exploration for Volumetric Generative Systems" that includes the whole research process that is behind this project. https://tcabezon.github.io/ls-exploration-tool/ "Browsing the Latent Space: A New Approach to Interactive Design Exploration for Volumetric Generative Systems"

Unlocking Creative Potential: Exploring Latent Spaces in 3D Generative Design

ক্রিয়েটিভ পটেনশিয়াল আনলক করা: 3D জেনারেটিভ ডিজাইনে সুপ্ত স্থানগুলি অন্বেষণ করা

Kreatives Potenzial freisetzen: Erkunden latenter Räume im generativen 3D-Design

Desbloqueo del potencial creativo: exploración de espacios latentes en el diseño generativo 3D

Libérer le potentiel créatif : explorer les espaces latents dans la conception générative 3D

रचनात्मक क्षमता को अनलॉक करना: 3D जनरेटिव डिज़ाइन में अव्यक्त स्थानों की खोज करना

創造力の解放: 3D ジェネレーティブ デザインにおける潜在空間の探究

창의적 잠재력 해제: 3D 생성 디자인에서 잠재 공간 탐색

Desbloqueando o potencial criativo: explorando espaços latentes no design generativo 3D

Раскрытие творческого потенциала: исследование скрытых пространств в 3D-генеративном дизайне

Yaratıcı Potansiyelin Kilidini Açmak: 3B Üretken Tasarımda Gizli Alanları Keşfetmek

Mở khóa tiềm năng sáng tạo: Khám phá không gian tiềm ẩn trong thiết kế tạo hình 3D

释放创造潜力：探索 3D 生成设计中的潜在空间

Interwoven Realms: The Dance of Reason and Creativity in Human Understanding

From Business Mindset to Creativity

ব্যবসায়িক মানসিকতা থেকে সৃজনশীলতা পর্যন্ত

Vom Business Mindset zur Kreativität

De la mentalidad empresarial a la creatividad

De l’esprit d’entreprise à la créativité

व्यावसायिक मानसिकता से रचनात्मकता तक

ビジネスマインドセットから創造性へ

비즈니스 마인드에서 창의성까지

Da mentalidade empresarial à criatividade

От делового мышления к творчеству

İş Zihniyetinden Yaratıcılığa

Từ tư duy kinh doanh đến sáng tạo

从商业思维到创造力

In the same way that a young city slicker impresses the folks back home with stories of life in the Metropole, AI seems to be creative for those who encounter it. One has to admit that the width of knowledge that AI seems to have is impressive. And the way it seems to be able to transfer writing styles and connect concepts feels unlimited. To debunk the creativity of AI, we need to take a peak under the hood of how the LLM algorithms work. LLMs are large multilayered neural networks that relate tokens to each other. Their design mimics the structure of our brain with the nodes being our neurons and the relations between the tokens and the synapsis between our neurons. Like Hebb said: Neurons that fire together, wire together. In the case of LLMs, this is done by a system of weights that represent the relationship between tokens. Tokens that represent similar concepts will have a smaller distance than tokens that represent concepts that are unrelated. Like in the image, concepts of time will have a shorter weight factor among each other than other concepts. Intelligence is the ability to look at a novel problem and come up with a solution. One important breakthrough in the early design of LLM's was increasing the amount of layers. Similar to the brain, this allows complex concepts to be stored and related to each other. If you think about it, words can be defined by other words. Being able to define new concepts based on a set of basic concepts is something we humans do in all our activities. When you ask a question to an LLM, it translates the input you gave it and searches for concepts related to the set of tokens that you provided. It then transforms this back into a textual answer. Because of the large amount of information that was used to train these models, it looks like they are omni-sapient. On top of that, the models are able to transform the answers in multiple ways. You want the answer in German? No problem. Want it as a Haiku in the style of Shakespeare? No problem again. Yet, the models can only answer from their large pool of data. Their algorithms are not able to be creative. In Sean Carroll's Mindscape podcast, Francois Chollet brilliantly exposed this characteristic of generative AI. You probably have heard the trick question: "What is heavier: A kilogram of iron or a kilogram of feathers?" Ask this question and all LLM's will answer it correctly. But if you modify the question to be something like: "What is heavier: A kilogram of iron or two kilograms of feathers?" Some of the LLMs will be fooled and still answer that they weigh the same. The reason is that this case is not available in the information that was used to train their models. In a strange fashion, LLMs are like the student who memorizes facts for an exam but is not capable of deducing something new based on all she has learned. Thus, I decided to check this hypothesis by asking 4 LLMs that I currently use a modified version of the Farmer crossing the river with a Wolf, a Goat, and a box of Cabbage. The original riddle goes like this: A farmer wants to cross a river and take with him a wolf, a goat, and a cabbage. There is a boat that can fit him plus either the wolf, the goat, or the cabbage. If the wolf and the goat are alone on one shore, the wolf will eat the goat. If the goat and the cabbage are alone on the shore, the goat will eat the cabbage. How can the farmer bring the wolf, the goat, and the cabbage across the river? I changed the riddle so that the boat could fit him plus two items (instead of one). Initially, all LLM's confused the riddle with the original version. I had to point to them that the conditions were different, and got quite amusing answers. Chat GPT 4.o ChatGPT 4.o model does understand the number of trips required to cross the river, yet it commits the capital mistake of leaving the wolf and goat on the other side. The farmer will be taking the wolf and the cabbage home, but no goat. Copilot, through Bing, decides to go the safe way and cross with one item at a time, better safe than sorry, but resulting in an unnecessary amount of trips. As a consolation for his extra effort, the farmer will take all 3 items home. Perplexity starts in a great way, returning with the goat after the first crossing and saving its cabbage. Yet somehow, a second goat magically appears on the other side for whom the farmer has to cross alone again. This, of course, risked coming back to an empty box of cabbage and a wolf with a full belly. Finally, Claude 3.5 creates a second imaginary wolf. At least the farmer knows better than to leave the goat alone and takes it along on all his crossings. Francois Chollet argues that current LLM algorithms are boxed and not really capable of original thinking. He has created a challenge, the $1M ARC-AGI prize. Its premise is to have a set of novel riddles that are not yet solved in public, and thus, absent from training data and to have systems compete with each other trying to solve them. The riddles are only known to the organizers, and the competing systems have to be provided on a laptop with no access to the internet. In other words, if you want to use an LLM it needs to run locally. I find these arguments compelling. But maybe it is because I was never good at memorization, and also because I love riddles. And on the way to ARC-AGI, I will be peppering the models at my disposition with questions to see if they are getting closer to reasoning. In the same way that a young city slicker impresses the folks back home with stories of life in the Metropole, AI seems to be creative for those who encounter it. One has to admit that the width of knowledge that AI seems to have is impressive. And the way it seems to be able to transfer writing styles and connect concepts feels unlimited. To debunk the creativity of AI, we need to take a peak under the hood of how the LLM algorithms work. LLMs are large multilayered neural networks that relate tokens to each other. Their design mimics the structure of our brain with the nodes being our neurons and the relations between the tokens and the synapsis between our neurons. Like Hebb said: Neurons that fire together, wire together. In the case of LLMs, this is done by a system of weights that represent the relationship between tokens. Tokens that represent similar concepts will have a smaller distance than tokens that represent concepts that are unrelated. Like in the image, concepts of time will have a shorter weight factor among each other than other concepts. Intelligence is the ability to look at a novel problem and come up with a solution. Intelligence is the ability to look at a novel problem and come up with a solution. One important breakthrough in the early design of LLM's was increasing the amount of layers. Similar to the brain, this allows complex concepts to be stored and related to each other. If you think about it, words can be defined by other words. Being able to define new concepts based on a set of basic concepts is something we humans do in all our activities. When you ask a question to an LLM, it translates the input you gave it and searches for concepts related to the set of tokens that you provided. It then transforms this back into a textual answer. Because of the large amount of information that was used to train these models, it looks like they are omni-sapient. On top of that, the models are able to transform the answers in multiple ways. You want the answer in German? No problem. Want it as a Haiku in the style of Shakespeare? No problem again. Yet, the models can only answer from their large pool of data. Their algorithms are not able to be creative. Yet, the models can only answer from their large pool of data. Their algorithms are not able to be creative. Yet, the models can only answer from their large pool of data. Their algorithms are not able to be creative. In Sean Carroll's Mindscape podcast, Francois Chollet brilliantly exposed this characteristic of generative AI. You probably have heard the trick question: "What is heavier: A kilogram of iron or a kilogram of feathers?" "What is heavier: A kilogram of iron or a kilogram of feathers?" Ask this question and all LLM's will answer it correctly. But if you modify the question to be something like: "What is heavier: A kilogram of iron or two kilograms of feathers?" "What is heavier: A kilogram of iron or two kilograms of feathers?" two kilograms Some of the LLMs will be fooled and still answer that they weigh the same. The reason is that this case is not available in the information that was used to train their models. In a strange fashion, LLMs are like the student who memorizes facts for an exam but is not capable of deducing something new based on all she has learned. Thus, I decided to check this hypothesis by asking 4 LLMs that I currently use a modified version of the Farmer crossing the river with a Wolf, a Goat, and a box of Cabbage. The original riddle goes like this: A farmer wants to cross a river and take with him a wolf, a goat, and a cabbage. A farmer wants to cross a river and take with him a wolf, a goat, and a cabbage. There is a boat that can fit him plus either the wolf, the goat, or the cabbage. There is a boat that can fit him plus either the wolf, the goat, or the cabbage. If the wolf and the goat are alone on one shore, the wolf will eat the goat. If the goat and the cabbage are alone on the shore, the goat will eat the cabbage. If the wolf and the goat are alone on one shore, the wolf will eat the goat. If the goat and the cabbage are alone on the shore, the goat will eat the cabbage. How can the farmer bring the wolf, the goat, and the cabbage across the river? How can the farmer bring the wolf, the goat, and the cabbage across the river? I changed the riddle so that the boat could fit him plus two items (instead of one). the boat could fit him plus two items (instead of one). Initially, all LLM's confused the riddle with the original version. I had to point to them that the conditions were different, and got quite amusing answers. Chat GPT 4.o ChatGPT 4.o model does understand the number of trips required to cross the river, yet it commits the capital mistake of leaving the wolf and goat on the other side. The farmer will be taking the wolf and the cabbage home, but no goat. Copilot, through Bing, decides to go the safe way and cross with one item at a time, better safe than sorry, but resulting in an unnecessary amount of trips. As a consolation for his extra effort, the farmer will take all 3 items home. Perplexity starts in a great way, returning with the goat after the first crossing and saving its cabbage. Yet somehow, a second goat magically appears on the other side for whom the farmer has to cross alone again. This, of course, risked coming back to an empty box of cabbage and a wolf with a full belly. Finally, Claude 3.5 creates a second imaginary wolf. At least the farmer knows better than to leave the goat alone and takes it along on all his crossings. Francois Chollet argues that current LLM algorithms are boxed and not really capable of original thinking. He has created a challenge, the $1M ARC-AGI prize. Its premise is to have a set of novel riddles that are not yet solved in public, and thus, absent from training data and to have systems compete with each other trying to solve them. The riddles are only known to the organizers, and the competing systems have to be provided on a laptop with no access to the internet. In other words, if you want to use an LLM it needs to run locally. I find these arguments compelling. But maybe it is because I was never good at memorization, and also because I love riddles. And on the way to ARC-AGI, I will be peppering the models at my disposition with questions to see if they are getting closer to reasoning.

Here's How to Prove AI Is Not Creative

As a head of ops and growth, I’ve seen countless startups struggle, including edtech companies. Over time, I’ve developed a rescue plan for the companies in this industry. The majority of edtech marketplaces make the same mistake: While teams focus on flashy features and creative gimmicks, they often neglect the fundamental financial, marketing, and teacher operations that are critical for this type of company. In this article, I cover the main metrics to watch at edtech companies. I also mention some of the first steps you can take to fix any problems that can come up. Examine Trial-to-Pay Conversion Rate The trial-to-pay conversion rate indicates how effectively the platform converts trial users into paying customers. In the edtech industry, a conversion rate of around 25-30% is considered healthy. To optimize this metric, map the user journey and analyze conversion rates at each stage. Where do users drop out? Identify the funnel stages with the most significant drop-offs and focus on improving them. If there's a drop between trial sign-up and first user engagement, enhance onboarding or content accessibility. During the trial lessons, work on your sell point. The tutor’s goal is to show how the lessons help students achieve their goals and meet their needs. A good idea is to prepare a presentation that will show how students will benefit from your courses. Gamification — like adding rewards and badges for completing onboarding — also works well to improve the conversion rate. If students drop off between the end of the trial and the subscription decision, re-evaluate pricing or simplify the payment process. Lower CAC rate Customer Acquisition Cost (CAC) determines how much it costs for your marketplace to onboard one student. To calculate it, edtech marketplaces need to consider two main components: the cost of marketing and the cost of sales. If an edtech marketplace spent $3,000 on digital ads and $1,000 on sales calls and managed to onboard 100 new students, the CAC is $40. To understand if CAC is too high, calculate the LTV:CAC ratio. The 3:1 ratio is a golden standard. If the CAC is high, you are wasting too much money to bring in customers. To lower CAC, an edtech startup should work on marketing and sales. Below are some ideas on how to approach them. Marketing Run as many tests as possible to find the most effective marketing channels, creatives, and messages for the target audience. Offer more free content (webinars or free training) to lead potential clients to trial sign-ups. Encourage referrals by offering discounts or other bonuses for students who invite friends to try your services. Sales Regularly review and update sales scripts to align with new market conditions and customer preferences. Provide a free product trial and collect feedback after users complete it to gather more information on how to improve your services. Prioritize sales efforts on leads that have shown high engagement or interest in the platform. Proactively call and email users near the trial expiry to walk through the value delivered. Offer different subscription packages: monthly or by the number of lessons. Determine what works better. Offer payment plans and installment options to ensure ease of payment. Check if the Take Rate Is Adequate Take rate is the commission that online learning platforms charge teachers or course creators for connecting them with students. Edtech marketplace Preply, for example, charges teachers 18–33% per lesson. The more hours the teacher works, the lower the commission. Sorry for stating the obvious, but setting a low take rate to attract more teachers will result in financial losses. There must be a balance between offering a competitive take rate and ensuring your financial viability. To ensure your take rate doesn’t lead to financial troubles: Calculate all expenses associated with running your edtech platform, including hosting fees, marketing, customer support, and administrative costs. Compare take rates with other edtech marketplaces. Estimate your transaction volume over a given period: course sales, lesson bookings, etc. Develop a simple financial model considering your costs, expected transaction volume, and potential take rates. Find the take rate that enables you to cover expenses, generate a reasonable profit, and remain competitive and appealing to teachers. You might need to adjust your take rate as your platform grows and your costs change. Make Sure Your Platform Is Tutor-Oriented The goal of any edtech company is to cultivate a passion for lifelong learning in students. In edtech marketplaces, student engagement and your profits are directly tied to the performance of tutors. This is where a rockstar teacher operations manager comes in. Hire a separate person to handle teacher operations. They will be responsible for onboarding, training, and managing teachers’ performance. First up, onboarding. Create a short, easy-to-understand course on how to work on your platform and what teaching methods to use to teach students. Provide tutors with tools to create interactive teaching materials, including videos, quizzes, and other resources to improve the learning experience. Always measure each teacher's effectiveness and keep them busy to 100% of their capacity. Implement KPIs that track the average number of lessons taught by each teacher. Offer bonuses for completing a certain number of lessons as a good motivation. Make the process of getting money out of the platform as easy as possible. Try to provide teachers with the ability to withdraw their earnings when they want. Invest in the professional development and growth of your teachers. By supporting your teachers' continuous learning, you increase the quality of teaching on the platform and also demonstrate your commitment to tutors’ long-term success. As a head of ops and growth, I’ve seen countless startups struggle, including edtech companies. Over time, I’ve developed a rescue plan for the companies in this industry. The majority of edtech marketplaces make the same mistake: While teams focus on flashy features and creative gimmicks, they often neglect the fundamental financial, marketing, and teacher operations that are critical for this type of company. In this article, I cover the main metrics to watch at edtech companies. I also mention some of the first steps you can take to fix any problems that can come up. Examine Trial-to-Pay Conversion Rate The trial-to-pay conversion rate indicates how effectively the platform converts trial users into paying customers. In the edtech industry, a conversion rate of around 25-30% is considered healthy. To optimize this metric, map the user journey and analyze conversion rates at each stage. Where do users drop out? Identify the funnel stages with the most significant drop-offs and focus on improving them. If there's a drop between trial sign-up and first user engagement, enhance onboarding or content accessibility. During the trial lessons, work on your sell point. The tutor’s goal is to show how the lessons help students achieve their goals and meet their needs. A good idea is to prepare a presentation that will show how students will benefit from your courses. Gamification — like adding rewards and badges for completing onboarding — also works well to improve the conversion rate. If students drop off between the end of the trial and the subscription decision, re-evaluate pricing or simplify the payment process. Lower CAC rate Customer Acquisition Cost (CAC) determines how much it costs for your marketplace to onboard one student. To calculate it, edtech marketplaces need to consider two main components: the cost of marketing and the cost of sales. If an edtech marketplace spent $3,000 on digital ads and $1,000 on sales calls and managed to onboard 100 new students, the CAC is $40. To understand if CAC is too high, calculate the LTV:CAC ratio. The 3:1 ratio is a golden standard. If the CAC is high, you are wasting too much money to bring in customers. To lower CAC, an edtech startup should work on marketing and sales. Below are some ideas on how to approach them. Marketing Run as many tests as possible to find the most effective marketing channels, creatives, and messages for the target audience. Run as many tests as possible to find the most effective marketing channels, creatives, and messages for the target audience. Offer more free content (webinars or free training) to lead potential clients to trial sign-ups. Offer more free content (webinars or free training) to lead potential clients to trial sign-ups. Encourage referrals by offering discounts or other bonuses for students who invite friends to try your services. Encourage referrals by offering discounts or other bonuses for students who invite friends to try your services. Sales Regularly review and update sales scripts to align with new market conditions and customer preferences. Regularly review and update sales scripts to align with new market conditions and customer preferences. Provide a free product trial and collect feedback after users complete it to gather more information on how to improve your services. Provide a free product trial and collect feedback after users complete it to gather more information on how to improve your services. Prioritize sales efforts on leads that have shown high engagement or interest in the platform. Proactively call and email users near the trial expiry to walk through the value delivered. Prioritize sales efforts on leads that have shown high engagement or interest in the platform. Proactively call and email users near the trial expiry to walk through the value delivered. Offer different subscription packages: monthly or by the number of lessons. Determine what works better. Offer different subscription packages: monthly or by the number of lessons. Determine what works better. Offer payment plans and installment options to ensure ease of payment. Offer payment plans and installment options to ensure ease of payment. Check if the Take Rate Is Adequate Take rate is the commission that online learning platforms charge teachers or course creators for connecting them with students. Edtech marketplace Preply, for example, charges teachers 18–33% per lesson. The more hours the teacher works, the lower the commission. 18–33% 18–33% Sorry for stating the obvious, but setting a low take rate to attract more teachers will result in financial losses. There must be a balance between offering a competitive take rate and ensuring your financial viability. To ensure your take rate doesn’t lead to financial troubles: Calculate all expenses associated with running your edtech platform, including hosting fees, marketing, customer support, and administrative costs. Calculate all expenses associated with running your edtech platform, including hosting fees, marketing, customer support, and administrative costs. Compare take rates with other edtech marketplaces. Compare take rates with other edtech marketplaces. Estimate your transaction volume over a given period: course sales, lesson bookings, etc. Estimate your transaction volume over a given period: course sales, lesson bookings, etc. Develop a simple financial model considering your costs, expected transaction volume, and potential take rates. Develop a simple financial model considering your costs, expected transaction volume, and potential take rates. Find the take rate that enables you to cover expenses, generate a reasonable profit, and remain competitive and appealing to teachers. Find the take rate that enables you to cover expenses, generate a reasonable profit, and remain competitive and appealing to teachers. Find the take rate that enables you to cover expenses, generate a reasonable profit, and remain competitive and appealing to teachers. You might need to adjust your take rate as your platform grows and your costs change. Make Sure Your Platform Is Tutor-Oriented The goal of any edtech company is to cultivate a passion for lifelong learning in students. In edtech marketplaces, student engagement and your profits are directly tied to the performance of tutors. This is where a rockstar teacher operations manager comes in. Hire a separate person to handle teacher operations. They will be responsible for onboarding, training, and managing teachers’ performance. First up, onboarding. Create a short, easy-to-understand course on how to work on your platform and what teaching methods to use to teach students. Provide tutors with tools to create interactive teaching materials, including videos, quizzes, and other resources to improve the learning experience. Always measure each teacher's effectiveness and keep them busy to 100% of their capacity. Implement KPIs that track the average number of lessons taught by each teacher. Offer bonuses for completing a certain number of lessons as a good motivation. Always measure each teacher's effectiveness and keep them busy to 100% of their capacity. Implement KPIs that track the average number of lessons taught by each teacher. Offer bonuses for completing a certain number of lessons as a good motivation. Make the process of getting money out of the platform as easy as possible. Try to provide teachers with the ability to withdraw their earnings when they want. Invest in the professional development and growth of your teachers. By supporting your teachers' continuous learning, you increase the quality of teaching on the platform and also demonstrate your commitment to tutors’ long-term success.

Edtech Marketplaces Don’t Need Creative Gimmicks - They Need Data: Here’s What to Track

As AI wows us with how good it is at mimicking us, it’s starting to redefine creative processes that we have shaped over centuries. Until we completely do an overhaul of artists’ rights and intellectual property safety laws, it looks like artists will suffer. This time it’s voice artists. Last month, OpenAI took down a voice used by its ChatGPT that sounded uncannily like Hollywood actress Scarlet Johansson. The bot giant halted using the voice after the actress threatened to sue the company. Their explanation about how they got the voice in the first place is that they used another actress for it. It will take time for us to accept AI as a part of creative processes as a society. Meanwhile, big tech ensures that AI races on, mimicking human creativity within seconds. Where is the time to redefine this new reality and protect the artist? Where are these AI companies getting these voices from? Isn’t the source important? “In a time when we are all grappling with deepfakes and the protection of our own likeness, our own work, our own identities, I believe these are questions that deserve absolute clarity,” NPR quoted Johansson. In a time when we are all grappling with deepfakes and the protection of our own likeness, our own work, our own identities, I believe these are questions that deserve absolute clarity
Scarlet Johansson She has a point. There are other voice artists too who went through the shock of hearing their voices from sources they hadn’t lent them to. These incidents show the lack of legal safeguards when it comes to using creative work that aids AI tools. Why is Voice Significant? It might seem hard to imagine how AI that mimics human voice behavior will impact human society because we tend to take it for granted but as tech giants vie to provide much more lifelike voice assistants, we could soon find out. As Visar Berisha, an Arizona State University professor who studies AI speech technology, told NPR, “Communication by voice is really intimate, really impactful. It allows the AI to express subtleties, things that are perceived as sincere, urgent, joy, concern. And all of these serve to foster a deeper connection between the user and the machine. You can see how these interactions can potentially become addictive.” The movie ‘Her’ has naturally become part of this discussion. In the movie, when the protagonist falls for the flirtatious AI operating system, sporting the voice of Scarlet Johansson incidentally, it’s just the voice that tugs at his heartstrings, and we understand why it happens. So, undeniably, there is something in the voice. That voice has an impact on human society is evident from how attractive it is as an investment for businesses. American entrepreneur and investor Naval Ravikant recently launched Airchat, a voice-centric social media app. AI customer reps are filling the market. AI companies, like Hume AI, are starting to introduce EVI, or Empathic Voice Interface, where the AI changes its responses based on the user’s tone. AI & the Music Industry AI is changing more in the voice area, namely the music industry. It isn’t a surprise to find singers crooning away while AI adds effects to their real voices. Already AI is changing one of the biggest and most popular voice entertainment arenas, hip-hop and rap music. An ongoing diss-track rap battle between Kendrick Lamar and Drake has brought out the impact that technology has on hip-hop with curated releases on social platforms and AI-generated songs. It’s not just voice. Creative people are steadily losing to AI. Recently the psychedelic rock band Pink Floyd faced flak from fans when they chose an AI-generated video as the winner of their The Dark Side of The Moon 50th anniversary competition over all the human-made entries. We all laughed in 2022 when Midjourney first came out and said, ‘Oh, that’s cute.’ Now people are losing their jobs to Midjourney
Artist in Michigan told New York Times As a movie concept artist in Michigan told New York Times, “We all laughed in 2022 when Midjourney first came out and said, ‘Oh, that’s cute.’ Now people are losing their jobs to Midjourney.” What will happen when the taboo of AI drops, which seems inevitable? As an article in Wired says, “The manner that technology has already changed rap beef begs the question of where it will go next. One day, the taboo around AI in hip-hop will disappear, and entire battles will be orchestrated by LLM rappers trained on the raps of individual artists. Quants will develop metrics for who the winners are. If we are offended by a lyric about a member of our family, we’ll blame the machines. It may sound like the stuff of science-fiction, but the gap between this future reality and 2024 might be smaller (in time and manner) than the gap between Canibus vs. LL Cool J (1998) and Kendrick vs. Drake.” AI is Sneaking in but Here to Stay Last month, Gannett, an American media company that owns hundreds of newspapers, added AI-generated summaries to its articles. Five of this year’s Pulitzer winners used AI in their research. It feels a little like leaving the back door open for AI to sneak in, but we can be certain it will eventually reach the porch. It seems inevitable that these kinds of incidents will rewrite existing copyright laws. Recently, there have been many copyright infringement lawsuits against companies that are making use of tens of thousands of copyrighted books to train generative AI systems. One of them has called it “systematic theft on a mass scale,” not too far from the truth. The Good Side of Voice AI It’s not all evil though. AI voice-cloning technology can also be helpful to some people. People who have lost their speech are using AI voice cloning to get it back. Trained on a 15-second time capsule of her teenage voice, a 21-year-old woman in the US enjoys a synthetic but real-sounding AI voice. Country singer Randy Travis has been able to release his latest song with the help of AI, after he lost his speech to a stroke in 2013. We can’t ignore the glory of such incidents either. Co-creative Partners with AI Researchers are saying that we should lean towards co-creativity, i.e. where humans and machines interact to co-create, or ‘human-centered AI’ and ‘hybrid intelligence.’ They argue this will “ensure both high degrees of automatization through AI and human control” and support “a relationship that optimally empowers each other.” Still, is it that easy? Letting AI into our creative processes to ‘co-create’ articles, stories, images, videos, and music might make things more convenient but the feeling is uneasy. Purists could forever view it as cheating. It will take time for us to accept AI as a part of creative processes as a society. Meanwhile, big tech ensures that AI races on, mimicking human creativity within seconds. Where is the time to redefine this new reality and protect the artist? On the panicky side, as our dependency on AI increases, will we lose our ability to create independently? Imagine an analog world where we grope about, as if in the dark, to come up with basic sentences or paint a simple picture. Already usage of AI is demanding that we give it due acknowledgement in creative works. Navanwita Bora Sachdev, Editor, The Tech Panda As AI wows us with how good it is at mimicking us, it’s starting to redefine creative processes that we have shaped over centuries. Until we completely do an overhaul of artists’ rights and intellectual property safety laws, it looks like artists will suffer. AI redefine creative processes This time it’s voice artists. Last month, OpenAI took down a voice used by its ChatGPT that sounded uncannily like Hollywood actress Scarlet Johansson . The bot giant halted using the voice after the actress threatened to sue the company. Their explanation about how they got the voice in the first place is that they used another actress for it. Scarlet Johansson halted using how they got the voice It will take time for us to accept AI as a part of creative processes as a society. Meanwhile, big tech ensures that AI races on, mimicking human creativity within seconds. Where is the time to redefine this new reality and protect the artist? It will take time for us to accept AI as a part of creative processes as a society. Meanwhile, big tech ensures that AI races on, mimicking human creativity within seconds. Where is the time to redefine this new reality and protect the artist? It will take time for us to accept AI as a part of creative processes as a society. Meanwhile, big tech ensures that AI races on, mimicking human creativity within seconds. Where is the time to redefine this new reality and protect the artist? It will take time for us to accept AI as a part of creative processes as a society. Meanwhile, big tech ensures that AI races on, mimicking human creativity within seconds. Where is the time to redefine this new reality and protect the artist? It will take time for us to accept AI as a part of creative processes as a society. Meanwhile, big tech ensures that AI races on, mimicking human creativity within seconds. Where is the time to redefine this new reality and protect the artist? Where are these AI companies getting these voices from? Isn’t the source important? Where are these AI companies getting these voices from? Isn’t the source important? “In a time when we are all grappling with deepfakes and the protection of our own likeness, our own work, our own identities, I believe these are questions that deserve absolute clarity,” NPR quoted Johansson. NPR quoted In a time when we are all grappling with deepfakes and the protection of our own likeness, our own work, our own identities, I believe these are questions that deserve absolute clarity Scarlet Johansson In a time when we are all grappling with deepfakes and the protection of our own likeness, our own work, our own identities, I believe these are questions that deserve absolute clarity In a time when we are all grappling with deepfakes and the protection of our own likeness, our own work, our own identities, I believe these are questions that deserve absolute clarity In a time when we are all grappling with deepfakes and the protection of our own likeness, our own work, our own identities, I believe these are questions that deserve absolute clarity In a time when we are all grappling with deepfakes and the protection of our own likeness, our own work, our own identities, I believe these are questions that deserve absolute clarity Scarlet Johansson She has a point. There are other voice artists too who went through the shock of hearing their voices from sources they hadn’t lent them to. These incidents show the lack of legal safeguards when it comes to using creative work that aids AI tools. other voice artists too Why is Voice Significant? Why is Voice Significant? Why is Voice Significant? It might seem hard to imagine how AI that mimics human voice behavior will impact human society because we tend to take it for granted but as tech giants vie to provide much more lifelike voice assistants, we could soon find out. As Visar Berisha, an Arizona State University professor who studies AI speech technology, told NPR , “Communication by voice is really intimate, really impactful. It allows the AI to express subtleties, things that are perceived as sincere, urgent, joy, concern. And all of these serve to foster a deeper connection between the user and the machine. You can see how these interactions can potentially become addictive.” NPR NPR The movie ‘ Her ’ has naturally become part of this discussion. In the movie, when the protagonist falls for the flirtatious AI operating system, sporting the voice of Scarlet Johansson incidentally, it’s just the voice that tugs at his heartstrings, and we understand why it happens. So, undeniably, there is something in the voice. Her That voice has an impact on human society is evident from how attractive it is as an investment for businesses. American entrepreneur and investor Naval Ravikant recently launched Airchat, a voice-centric social media app . AI customer reps are filling the market. Naval Ravikant voice-centric social media app AI companies, like Hume AI, are starting to introduce EVI, or Empathic Voice Interface, where the AI changes its responses based on the user’s tone. starting to introduce AI & the Music Industry AI & the Music Industry AI & the Music Industry AI is changing more in the voice area, namely the music industry. It isn’t a surprise to find singers crooning away while AI adds effects to their real voices. Already AI is changing one of the biggest and most popular voice entertainment arenas, hip-hop and rap music. An ongoing diss-track rap battle between Kendrick Lamar and Drake has brought out the impact that technology has on hip-hop with curated releases on social platforms and AI-generated songs. It’s not just voice. Creative people are steadily losing to AI. Recently the psychedelic rock band Pink Floyd faced flak from fans when they chose an AI-generated video as the winner of their The Dark Side of The Moon 50th anniversary competition over all the human-made entries. when they chose We all laughed in 2022 when Midjourney first came out and said, ‘Oh, that’s cute.’ Now people are losing their jobs to Midjourney Artist in Michigan told New York Times We all laughed in 2022 when Midjourney first came out and said, ‘Oh, that’s cute.’ Now people are losing their jobs to Midjourney We all laughed in 2022 when Midjourney first came out and said, ‘Oh, that’s cute.’ Now people are losing their jobs to Midjourney We all laughed in 2022 when Midjourney first came out and said, ‘Oh, that’s cute.’ Now people are losing their jobs to Midjourney We all laughed in 2022 when Midjourney first came out and said, ‘Oh, that’s cute.’ Now people are losing their jobs to Midjourney Artist in Michigan told New York Times As a movie concept artist in Michigan told New York Times , “We all laughed in 2022 when Midjourney first came out and said, ‘Oh, that’s cute.’ Now people are losing their jobs to Midjourney.” told New York Times What will happen when the taboo of AI drops, which seems inevitable? As an article in Wired says , “The manner that technology has already changed rap beef begs the question of where it will go next. One day, the taboo around AI in hip-hop will disappear, and entire battles will be orchestrated by LLM rappers trained on the raps of individual artists. Wired says Quants will develop metrics for who the winners are. If we are offended by a lyric about a member of our family, we’ll blame the machines. It may sound like the stuff of science-fiction, but the gap between this future reality and 2024 might be smaller (in time and manner) than the gap between Canibus vs. LL Cool J (1998) and Kendrick vs. Drake.” AI is Sneaking in but Here to Stay AI is Sneaking in but Here to Stay AI is Sneaking in but Here to Stay Last month, Gannett, an American media company that owns hundreds of newspapers, added AI-generated summaries to its articles. Five of this year’s Pulitzer winners used AI in their research. AI-generated summaries used It feels a little like leaving the back door open for AI to sneak in, but we can be certain it will eventually reach the porch. It seems inevitable that these kinds of incidents will rewrite existing copyright laws. Recently, there have been many copyright infringement lawsuits against companies that are making use of tens of thousands of copyrighted books to train generative AI systems. One of them has called it “systematic theft on a mass scale,” not too far from the truth. tens of thousands of copyrighted books The Good Side of Voice AI The Good Side of Voice AI The Good Side of Voice AI It’s not all evil though. AI voice-cloning technology can also be helpful to some people. People who have lost their speech are using AI voice cloning to get it back. Trained on a 15-second time capsule of her teenage voice, a 21-year-old woman in the US enjoys a synthetic but real-sounding AI voice. Country singer Randy Travis has been able to release his latest song with the help of AI, after he lost his speech to a stroke in 2013. a 21-year-old woman release his latest song We can’t ignore the glory of such incidents either. Co-creative Partners with AI Co-creative Partners with AI Co-creative Partners with AI Researchers are saying that we should lean towards co-creativity, i.e. where humans and machines interact to co-create, or ‘human-centered AI’ and ‘hybrid intelligence.’ They argue this will “ensure both high degrees of automatization through AI and human control” and support “a relationship that optimally empowers each other.” are saying Still, is it that easy? Letting AI into our creative processes to ‘co-create’ articles, stories, images, videos, and music might make things more convenient but the feeling is uneasy. Purists could forever view it as cheating. It will take time for us to accept AI as a part of creative processes as a society. Meanwhile, big tech ensures that AI races on, mimicking human creativity within seconds. Where is the time to redefine this new reality and protect the artist? On the panicky side, as our dependency on AI increases, will we lose our ability to create independently? Imagine an analog world where we grope about, as if in the dark, to come up with basic sentences or paint a simple picture. Already usage of AI is demanding that we give it due acknowledgement in creative works. we give it due acknowledgement Navanwita Bora Sachdev, Editor, The Tech Panda Navanwita Bora Sachdev, Editor, The Tech Panda Navanwita Bora Sachdev , Editor, The Tech Panda Navanwita Bora Sachdev

Artists vs. AI: Balancing Innovation with Intellectual Property Rights in Creative Industries 

শিল্পী বনাম এআই: সৃজনশীল শিল্পে বুদ্ধিবৃত্তিক সম্পত্তির অধিকারের সাথে উদ্ভাবনের ভারসাম্য বজায় রাখা 

Künstler vs. KI: Innovation und geistige Eigentumsrechte in der Kreativwirtschaft in Einklang bringen

Artistas versus IA: equilibrio entre la innovación y los derechos de propiedad intelectual en las industrias creativas 

Artistes contre IA : équilibrer l'innovation et les droits de propriété intellectuelle dans les industries créatives 

कलाकार बनाम एआई: रचनात्मक उद्योगों में बौद्धिक संपदा अधिकारों के साथ नवाचार का संतुलन

アーティスト対AI: クリエイティブ産業におけるイノベーションと知的財産権のバランス

예술가 대 AI: 창조 산업에서 혁신과 지적 재산권의 균형 

Artistas versus IA: Equilibrando Inovação com Direitos de Propriedade Intelectual nas Indústrias Criativas 

Художники против ИИ: баланс между инновациями и правами интеллектуальной собственности в творческих отраслях 

Sanatçılar ve Yapay Zeka: Yaratıcı Endüstrilerde İnovasyonu Fikri Mülkiyet Haklarıyla Dengelemek 

Nghệ sĩ và AI: Cân bằng đổi mới với quyền sở hữu trí tuệ trong các ngành công nghiệp sáng tạo 

艺术家与人工智能：创意产业中创新与知识产权的平衡

So it was a fine evening; I was at my work desk with my coffee, which had just been delivered by a Dasher. I was endlessly scrolling through my X account, taking it slowly sip by sip, enjoying the aroma of the seeds. And that’s when I stumbled upon this viral meme. It made me question my reality like Westworld bot. As a person in a creative profession (at least when I do copywriting), I was just staring into the abyss of my overflowing sink. The dishes have piled up high like the despair in my soul, a veritable Mount Everest of ceramic, metal, and leftover spaghetti. The glint of the silverware was mocking my ambitions, the greasy pots, and pans were whispering my impending doom. And that’s when I realized, like Madris Lidaka said, the creative battle with AI was raging on, and I might be losing. Fast. The Problem: The Never-Ending Cycle Let’s get real. Adulting is hard. Like…real hard. But, Adulting with a creative soul? Damn near impossible. Particularly the relentless Sisyphean task of washing dishes. Just when you think you've caught up, the sink laughs in your face and fills up again with one evil laugh. It’s a never-ending cycle, a black hole of mundane tasks that sucks away your precious creative energy. The Hero's Journey (Or Not) Unlike Frodo from LOTR, who had the singular, epic quest of destroying the One Ring, we creative souls face a far more insidious foe. These greasy plates and stained coffee mugs might as well be indestructible horcruxes, anchoring us to a life of drudgery. Each dish scrubbed feels like another step away from our next masterpiece. The hero’s journey? More like a tragic tale of defeat. Because it’s a CYCLE! Stats Time! Did you know that, according to the Bureau of Labor Statistics, the average American spends approximately 1 hour and 27 minutes per day on household chores, with a significant chunk devoted to dishwashing? That’s over 9 hours a week, 468 hours a year. Imagine the novels, songs, and artworks lost to the abyss of dirty dishes. Even if we get into “super-procrastination, “ I still think we can get more work done. The Dark Side of the Dishes Channel your inner Jedi. Feel the Force flow through you. Now, imagine it being choked by a pile of dirty spoons. The lightsaber of your creativity flickers and dims as you scrub away at stubborn stains. The Dark Side isn’t some far-off galactic evil; it’s right here, in your kitchen sink. So You Think You Can Be Creative? Wash Those Dishes First... (Or Maybe Not) Ernest Hemingway didn’t pen “The Old Man and the Sea” while elbow-deep in dishwater. Jane Austen didn’t craft “Pride and Prejudice” between cycles of washing and drying. Of Course, I know they didn’t live during the digital age. But even if they did, what are the chances that we’d have gotten their masterpieces? Yet here we are, torn from our keyboards and sketchpads, reduced to the banal existence of Home Ec students. The muse of creativity isn’t a fan of dish soap, it seems. No, I am not going to attach photos of my room and trigger your OCD. No, I didn’t mean it LITERALLY! We need a hero, and we need it now. Yeah, I know about AI-based dishwashers. They are the knights in shining armor. These machines are the brave knights ready to slay the dragon of dirty dishes. No more pruney fingers, no more lost hours. Just gleaming plates and the sweet, sweet taste of creative freedom. But I wasn’t just talking about dishwashers, had I? My point is to look at the bigger picture. It’s a universal struggle, a relatable cry for help from creative people everywhere. Imagine a world where AI handles the mundane. You wake up, pour yourself a cup of coffee, and head straight to your writing desk. No dishes to distract you, no chores to drain your creativity. In this utopia, you’re free to craft your next novel, compose your next symphony, or paint your next masterpiece. It sounds like something right out of the old cartoon show Richie Rich. Damn, they got everything predicted. The AI tech in your house can be the unsung hero, working tirelessly behind the scenes. However, our creative juice will be overflowing and we could have more masterpieces. So What is the Solution? The Moral of the Story is to Embrace AI, Unleash Creativity AI isn’t here to replace you; it’s here to collaborate. Think of AI technology as a tool to empower your creativity, freeing you from the clutches of dirty dishes. There is a thin line where the intersection of technology and creativity lies. It should be a partnership, a symbiotic relationship where both humans and machines thrive. On the other hand, even if we get Generative AI to do the work for us, I believe that assessing the output would be challenging as creativity is often person-specific or even situation-specific. Here is a research paper from the Journal of Business and Psychology that fully addresses this ambiguity. So, the next time you find yourself drowning in a sea of dirty dishes and feeling the weight of the mundane threatening to crush your creative spirit, remember: there's hope. This isn't just about conquering the sink; it's about a future where technology empowers our creativity. It's about reclaiming those precious stolen hours and letting your creative spirit truly soar. So, fire up your imagination, unleash your artistic talents, and let AI handle the mundane. The world awaits your next masterpiece, one at a time. So it was a fine evening; I was at my work desk with my coffee, which had just been delivered by a Dasher. I was endlessly scrolling through my X account , taking it slowly sip by sip, enjoying the aroma of the seeds. X account And that’s when I stumbled upon this viral meme . It made me question my reality like Westworld bot. viral meme As a person in a creative profession (at least when I do copywriting), I was just staring into the abyss of my overflowing sink. The dishes have piled up high like the despair in my soul, a veritable Mount Everest of ceramic, metal, and leftover spaghetti. The glint of the silverware was mocking my ambitions, the greasy pots, and pans were whispering my impending doom. And that’s when I realized, like Madris Lidaka said, the creative battle with AI was raging on, and I might be losing. Fast. Madris Lidaka The Problem: The Never-Ending Cycle Let’s get real. Adulting is hard. Like…real hard. But, Adulting with a creative soul? Damn near impossible. Particularly the relentless Sisyphean task of washing dishes. Just when you think you've caught up, the sink laughs in your face and fills up again with one evil laugh. It’s a never-ending cycle, a black hole of mundane tasks that sucks away your precious creative energy. The Hero's Journey (Or Not) Unlike Frodo from LOTR, who had the singular, epic quest of destroying the One Ring, we creative souls face a far more insidious foe. These greasy plates and stained coffee mugs might as well be indestructible horcruxes, anchoring us to a life of drudgery. Each dish scrubbed feels like another step away from our next masterpiece. The hero’s journey? More like a tragic tale of defeat. Because it’s a CYCLE! Stats Time! Did you know that, according to the Bureau of Labor Statistics , the average American spends approximately 1 hour and 27 minutes per day on household chores, with a significant chunk devoted to dishwashing? That’s over 9 hours a week, 468 hours a year. Imagine the novels, songs, and artworks lost to the abyss of dirty dishes. Even if we get into “super-procrastination, “ I still think we can get more work done. Bureau of Labor Statistics The Dark Side of the Dishes Channel your inner Jedi. Feel the Force flow through you. Now, imagine it being choked by a pile of dirty spoons. The lightsaber of your creativity flickers and dims as you scrub away at stubborn stains. The Dark Side isn’t some far-off galactic evil; it’s right here, in your kitchen sink. So You Think You Can Be Creative? Wash Those Dishes First... (Or Maybe Not) Ernest Hemingway didn’t pen “The Old Man and the Sea” while elbow-deep in dishwater. Jane Austen didn’t craft “Pride and Prejudice” between cycles of washing and drying. Of Course, I know they didn’t live during the digital age. But even if they did, what are the chances that we’d have gotten their masterpieces? “The Old Man and the Sea” “The Old Man and the Sea” “Pride and Prejudice” “Pride and Prejudice” Yet here we are, torn from our keyboards and sketchpads, reduced to the banal existence of Home Ec students. The muse of creativity isn’t a fan of dish soap, it seems. No, I am not going to attach photos of my room and trigger your OCD. No, I didn’t mean it LITERALLY! No, I didn’t mean it LITERALLY! We need a hero, and we need it now. Yeah, I know about AI-based dishwashers. They are the knights in shining armor. These machines are the brave knights ready to slay the dragon of dirty dishes. No more pruney fingers, no more lost hours. Just gleaming plates and the sweet, sweet taste of creative freedom. But I wasn’t just talking about dishwashers, had I? But I wasn’t just talking about dishwashers, had I? My point is to look at the bigger picture. It’s a universal struggle, a relatable cry for help from creative people everywhere. Imagine a world where AI handles the mundane. You wake up, pour yourself a cup of coffee, and head straight to your writing desk. No dishes to distract you, no chores to drain your creativity. In this utopia, you’re free to craft your next novel, compose your next symphony, or paint your next masterpiece. It sounds like something right out of the old cartoon show Richie Rich. Damn, they got everything predicted. The AI tech in your house can be the unsung hero, working tirelessly behind the scenes. However, our creative juice will be overflowing and we could have more masterpieces. So What is the Solution? So What is the Solution? The Moral of the Story is to Embrace AI, Unleash Creativity AI isn’t here to replace you; it’s here to collaborate. Think of AI technology as a tool to empower your creativity, freeing you from the clutches of dirty dishes. There is a thin line where the intersection of technology and creativity lies. It should be a partnership, a symbiotic relationship where both humans and machines thrive. intersection of technology and creativity On the other hand, even if we get Generative AI to do the work for us, I believe that assessing the output would be challenging as creativity is often person-specific or even situation-specific. Here is a research paper from the Journal of Business and Psycholog y that fully addresses this ambiguity. Journal of Business and Psycholog So, the next time you find yourself drowning in a sea of dirty dishes and feeling the weight of the mundane threatening to crush your creative spirit, remember: there's hope. This isn't just about conquering the sink; it's about a future where technology empowers our creativity. It's about reclaiming those precious stolen hours and letting your creative spirit truly soar. So, fire up your imagination, unleash your artistic talents, and let AI handle the mundane. The world awaits your next masterpiece, one at a time.

AI, Please Wash My Dishes, Let Me Write: A Desperate Plea for Creative Freedom

এআই, দয়া করে আমার থালা-বাসন ধুয়ে ফেলুন, আমাকে লিখতে দিন: সৃজনশীল স্বাধীনতার জন্য একটি মরিয়া আবেদন

KI, bitte wasche mein Geschirr, lass mich schreiben: Ein verzweifelter Appell für kreative Freiheit

AI, por favor lava mis platos, déjame escribir: una súplica desesperada por la libertad creativa

AI, s'il vous plaît, faites ma vaisselle, laissez-moi écrire : un plaidoyer désespéré pour la liberté de création

एआई, कृपया मेरे बर्तन धोएँ, मुझे लिखने दें: रचनात्मक स्वतंत्रता के लिए एक हताश अपील

AIよ、皿を洗って、私に文章を書かせてください: 創造の自由を求める切実な嘆願

AI, 설거지를 해주세요, 글을 쓰겠습니다: 창작의 자유를 위한 간절한 호소

AI, por favor, lave minha louça, deixe-me escrever: um apelo desesperado por liberdade criativa

ИИ, пожалуйста, помойте мою посуду, позвольте мне написать: отчаянный призыв к творческой свободе

AI, Lütfen Bulaşıklarımı Yıka, Bırak Yazayım: Yaratıcı Özgürlük İçin Umutsuz Bir Dilekçe

AI, Hãy rửa bát cho tôi, để tôi viết: Lời cầu xin tuyệt vọng cho sự tự do sáng tạo

人工智能，请帮我洗碗，让我写作：对创作自由的迫切请求

A well-known cybersecurity problem is that attacks get progressively creative, challenging online security professionals and resulting in them frequently seeing attacks on an unprecedented scale. Which examples have pushed the boundaries most? 1. The Dyre Banking Scam Hackers like targeting the most lucrative sectors, so it’s no surprise banks frequently feature in cyberattacks. They’re either the businesses under threat or the subjects meant to entice consumers to take specific actions after receiving emails that seem to come from their banking institutions. A banking-specific scam first detected in 2014 used Dyre malware, which compromised victims’ browsers and stole credentials to log into financial institutions’ platforms and other secured interfaces. The scam started when someone received an email attachment supposedly containing an unpaid invoice. Additionally, the attachments contained malware designed to exploit unpatched vulnerabilities in recipients’ Adobe Reader software. These aspects showed creative thinking on the cybercriminals’ behalf. First, they knew such a vague but relevant-sounding attachment name about an invoice would catch people’s interest. Since life can get so hectic, someone might occasionally forget to pay for things. Spelling mistakes in the file name were hallmark characteristics of this cyberattack, but criminals presumably hoped people wouldn’t notice or care. The scammers also rightfully assumed their targets would not update their Adobe software frequently enough, creating many potential entry points for enterprising hackers. Once someone fell for the trick and downloaded the attachment, the malware copied itself and made the seemingly innocent “Google Update Service” on the person’s computer. It then set registry keys and began logging keystroke data before sending it to hackers. As of 2016, United States government authorities said all major antivirus software vendors’ products had detected this threat. However, the detection requires people to use and update such tools regularly. Bank employees carry out stringent know-your-customer procedures to prevent fraud and establish risk profiles. Those are undoubtedly necessary, but this scam shows how easily things can go wrong when customers fall for malware. 2. The WPP Deepfake Scam As technologies have advanced, cybercriminals’ creativity in exploiting them has, too. Artificial intelligence (AI) has become so believable that consumers have had to learn they can’t necessarily trust everything they see or hear due to elaborate deepfakes. The state of things came to the forefront for Mark Read, the CEO of WPP, a British multinational advertising and public relations company. The executive recently detailed a deepfake scam that exploited numerous platforms and media types. Read explained how hackers set up a new WhatsApp account and used a publicly available image of him as the profile picture. They used it to schedule a meeting on Microsoft Teams with another senior executive who thought they were engaging with Read. During the meeting, the cybercriminals deployed a voice clone and YouTube footage of Read, all while simultaneously interacting in the Microsoft Teams chat window to pose as him and fool the other attendee with material that looked, sounded and read like the leader. The goal was to convince an agency head to set up a new business, after which the scammers would get financial and personal details from them. This scam failed, and Read attributed that result to his company’s vigilance, including that of the targeted executive who did not respond as the hackers’ hoped. The CEO pointed out how everyone must be on guard against increasingly elaborate tricks, including those going beyond someone’s email inbox. Some tech experts suggest the blockchain is ideal for securing people’s vocal characteristics and preventing malicious parties from tampering with authenticated clips. However,  since the voices of well-known figures are on television, the radio, YouTube and even audiobooks, motivated cybercriminals have plenty of data to use. 3. Misleading AI Ads Targeting Small Businesses No company or person is wholly safe from cyber scams, but the effects of successfully orchestrated attacks are more disastrous for some victims than others. Small businesses are excellent examples because such organizations often lack the resources to recover fully and quickly. However, as a 2023 study showed, 73% of small businesses experienced cyberattacks, data breaches or both during the previous year. A 2024 report found cyberattacks were the top concern for 60% of respondents, suggesting those polled understand the threat’s severity. Unfortunately, scammers know small-business owners are excellent targets and may prey on victims’ desire to improve their workflows with new tech. Such was the case with a scam against small businesses that caught Google executives’ attention and resulted in company lawsuits against scammers. The tactics centered on Google Bard — the large language model now known as Gemini. The tech company’s first lawsuit was against bad actors who created social media profiles and advertisements encouraging small-business owners to download Bard. However, Google did not require people to download anything to use it; instead, it integrated the tool into many of its existing products. Those who fell for this scam expected that downloading something would let them use Bard. Instead, it gave them malware that compromised their social media profiles. From April to November 2023, Google filed approximately 300 takedown notices associated with this scam. It sought an order to prevent criminals from setting up similar sites and deactivating those currently on file with domain registrars. This scam stood out for creativity because it capitalized on Google’s brand recognition and people’s interest in trying a new product to make business operations more convenient. Truths Mixed With Lies These creative cyber scams prove those orchestrating them will stop at nothing to achieve their aims. Even when the efforts don’t pay off — as in the WPP deepfake case — they become warnings that people must always be on guard for things not being as they seem. After all, most online scams have truthful elements mixed with falsities. There was a product called Google Bard, but using it did not require downloading software. Mark Read is WPP’s CEO, but he never arranged or participated in that meeting about establishing a new business. These cases highlight the importance of thinking carefully before acting and verifying claims before making decisions that could have catastrophic consequences. A well-known cybersecurity problem is that attacks get progressively creative, challenging online security professionals and resulting in them frequently seeing attacks on an unprecedented scale. Which examples have pushed the boundaries most? A well-known cybersecurity problem is that attacks get progressively creative, challenging online security professionals and resulting in them frequently seeing attacks on an unprecedented scale. Which examples have pushed the boundaries most? 1. The Dyre Banking Scam 1. The Dyre Banking Scam Hackers like targeting the most lucrative sectors, so it’s no surprise banks frequently feature in cyberattacks. They’re either the businesses under threat or the subjects meant to entice consumers to take specific actions after receiving emails that seem to come from their banking institutions. A banking-specific scam first detected in 2014 used Dyre malware, which compromised victims’ browsers and stole credentials to log into financial institutions’ platforms and other secured interfaces. The scam started when someone received an email attachment supposedly containing an unpaid invoice. Additionally, the attachments contained malware designed to exploit unpatched vulnerabilities in recipients’ Adobe Reader software. These aspects showed creative thinking on the cybercriminals’ behalf. First, they knew such a vague but relevant-sounding attachment name about an invoice would catch people’s interest. Since life can get so hectic, someone might occasionally forget to pay for things. Spelling mistakes in the file name were hallmark characteristics of this cyberattack, but criminals presumably hoped people wouldn’t notice or care. The scammers also rightfully assumed their targets would not update their Adobe software frequently enough, creating many potential entry points for enterprising hackers. Once someone fell for the trick and downloaded the attachment, the malware copied itself and made the seemingly innocent “Google Update Service” on the person’s computer. It then set registry keys and began logging keystroke data before sending it to hackers. As of 2016, United States government authorities said all major antivirus software vendors’ products had detected this threat. However, the detection requires people to use and update such tools regularly. said all major antivirus software said all major antivirus software Bank employees carry out stringent know-your-customer procedures to prevent fraud and establish risk profiles. Those are undoubtedly necessary, but this scam shows how easily things can go wrong when customers fall for malware. know-your-customer procedures to prevent fraud know-your-customer procedures to prevent fraud 2. The WPP Deepfake Scam As technologies have advanced, cybercriminals’ creativity in exploiting them has, too. Artificial intelligence (AI) has become so believable that consumers have had to learn they can’t necessarily trust everything they see or hear due to elaborate deepfakes. The state of things came to the forefront for Mark Read, the CEO of WPP, a British multinational advertising and public relations company. The executive recently detailed a deepfake scam that exploited numerous platforms and media types. Read explained how hackers set up a new WhatsApp account and used a publicly available image of him as the profile picture. They used it to schedule a meeting on Microsoft Teams with another senior executive who thought they were engaging with Read. During the meeting, the cybercriminals deployed a voice clone and YouTube footage of Read, all while simultaneously interacting in the Microsoft Teams chat window to pose as him and fool the other attendee with material that looked, sounded and read like the leader. The goal was to convince an agency head to set up a new business, after which the scammers would get financial and personal details from them. This scam failed, and Read attributed that result to his company’s vigilance , including that of the targeted executive who did not respond as the hackers’ hoped. The CEO pointed out how everyone must be on guard against increasingly elaborate tricks, including those going beyond someone’s email inbox. that result to his company’s vigilance that result to his company’s vigilance Some tech experts suggest the blockchain is ideal for securing people’s vocal characteristics and preventing malicious parties from tampering with authenticated clips. However,  since the voices of well-known figures are on television, the radio, YouTube and even audiobooks, motivated cybercriminals have plenty of data to use. preventing malicious parties from tampering preventing malicious parties from tampering 3. Misleading AI Ads Targeting Small Businesses No company or person is wholly safe from cyber scams, but the effects of successfully orchestrated attacks are more disastrous for some victims than others. Small businesses are excellent examples because such organizations often lack the resources to recover fully and quickly. However, as a 2023 study showed, 73% of small businesses experienced cyberattacks , data breaches or both during the previous year. A 2024 report found cyberattacks were the top concern for 60% of respondents, suggesting those polled understand the threat’s severity. 73% of small businesses experienced cyberattacks 73% of small businesses experienced cyberattacks were the top concern for 60% were the top concern for 60% Unfortunately, scammers know small-business owners are excellent targets and may prey on victims’ desire to improve their workflows with new tech. Such was the case with a scam against small businesses that caught Google executives’ attention and resulted in company lawsuits against scammers. The tactics centered on Google Bard — the large language model now known as Gemini. The tech company’s first lawsuit was against bad actors who created social media profiles and advertisements encouraging small-business owners to download Bard. However, Google did not require people to download anything to use it; instead, it integrated the tool into many of its existing products. Those who fell for this scam expected that downloading something would let them use Bard. Instead, it gave them malware that compromised their social media profiles. From April to November 2023, Google filed approximately 300 takedown notices associated with this scam. It sought an order to prevent criminals from setting up similar sites and deactivating those currently on file with domain registrars. 300 takedown notices associated 300 takedown notices associated This scam stood out for creativity because it capitalized on Google’s brand recognition and people’s interest in trying a new product to make business operations more convenient. Truths Mixed With Lies These creative cyber scams prove those orchestrating them will stop at nothing to achieve their aims. Even when the efforts don’t pay off — as in the WPP deepfake case — they become warnings that people must always be on guard for things not being as they seem. After all, most online scams have truthful elements mixed with falsities. There was a product called Google Bard, but using it did not require downloading software. Mark Read is WPP’s CEO, but he never arranged or participated in that meeting about establishing a new business. These cases highlight the importance of thinking carefully before acting and verifying claims before making decisions that could have catastrophic consequences.

Top 3 Most Creative Cyber Scams in History

ইতিহাসের শীর্ষ 3টি সর্বাধিক সৃজনশীল সাইবার স্ক্যাম

Die 3 kreativsten Cyber-Betrügereien der Geschichte

Las 3 estafas cibernéticas más creativas de la historia

Top 3 des cyberescroqueries les plus créatives de l’histoire

इतिहास के 3 सबसे रचनात्मक साइबर घोटाले

史上最も独創的なサイバー詐欺トップ3

역사상 가장 창의적인 사이버 사기 TOP 3

Os três golpes cibernéticos mais criativos da história

Топ-3 самых креативных кибермошенников в истории

Tarihteki En Yaratıcı 3 Siber Dolandırıcılık

Top 3 vụ lừa đảo qua mạng sáng tạo nhất trong lịch sử

历史上最具创意的三大网络诈骗

Good Managers Know to Not Make These Mistakes

ভাল পরিচালকরা এই ভুলগুলি করতে জানেন না

Dobri menadžeri znaju da ne prave ove greške

Los buenos gerentes saben que no deben cometer estos errores

Kudeatzaile onek badakite akats hauek ez dituztela egiten

I buoni manager sanno che non devono commettere questi errori

優秀なマネージャーはこれらのミスをしないことを知っています

კარგმა მენეჯერებმა იციან, რომ არ დაუშვან ეს შეცდომები

ښه مدیران پوهیږي چې دا غلطۍ نه کوي

Bons gerentes sabem que não devem cometer esses erros

Allin Kamachiqkunam Yachanku Mana Kay Pantaykunata

ንፉዓት ኣካየድቲ ነዚ ጌጋታት ከምዘይፍጽሙ ይፈልጡ እዮም።

Abaphathi Abahle Bayazi Ukungawenzi Lawa Maphutha

In the current age characterized by rapid digital growth, companies are faced with a great dilemma when venturing into Web3 technology: should they go for a white-label solution or develop a product from the ground up? Both have their advantages and disadvantages, and an appropriate selection can make all the difference in the success of a particular enterprise. This article explores both approaches, highlighting their benefits and drawbacks. What Are White Label Solutions? White-label solutions” or “white brands” refer to products and services that are created by one company but sold by another company under a different brand name. This approach enables firms to sell products without having to bear the cost of developing them. The key points about it are that it's ready-made products, customizable branding, and facilities for quick market entry. Advantages of White Label Solutions There are also some benefits of white-label solutions which make most of their tasks easier. More economical: There are no development costs, which is very convenient for non-technical companies, media, or influencers. Less time to reach the market: Less time to enter the market. More on brand management: Emphasis is on sales, marketing, and branding. Use Cases of White Label Solutions Some of these white-label solutions can be used across different sectors: E-commerce: Some retailers don’t sell their products, but rather sell the products of third parties under their brand. Software or web3 dApps: Some companies allow others to rebrand their software or web3 dApps and sell them. Financial services: They are not banks but sell banking services whereby their clients’ products are branded with the brand of the other financial service providers. The Appeal of Building a Web3 Product From Scratch There is absolutely nothing wrong with building a product from scratch. In point of fact, there are some benefits to it including: Customization and Control From the perspective of customization and control, creating your own Web3 product is one of the best options. There is how the product is built and that can be made to the tiniest details. This kind of control makes it possible for you to achieve your objectives as you envision. Market Responsiveness The best way to get a Web3 product is by starting its development from scratch, and it is because of the high chances of creativity that it brings on board. You can use one of the most up-to-date technologies and find new applications that cannot be incorporated into white-label solutions. Long Term Vision Building a web3 product from scratch can go along with developing a long-term vision. This involves planning for future growth. It's critical to create a product that evolves with the market. Crucial Considerations For White-Label Solutions Initial Investment As is the case with any venture, the seed capital required while launching a Web3 project may be high or low. It can also be very expensive to come up with a product from the ground up; this may cost as much as say, $1000 and above. In contrast, a white-label solution is more viable and cheaper because the business does not need to invest a lot of money to develop the application, and it can quickly take it to the market. Maintenance and Upgrades Sustaining and enhancing a Web3 product is not one and done, it costs money. Contract-made solutions sometimes need a team to manage upgrades or to do the patching. This could be really challenging for any non-technical firms and media specifically influencers. However, white-label solutions fix this problem by including maintenance and upgrades as part of the services rendered. Hidden Costs As can be seen, hidden costs can often emerge as a real threat to businesses and companies. These might be charges for extra services, regulatory costs, or even above-market rate hosting costs. These are the possibilities that one should take into account while setting his/her financial plan. Development Timelines While comparing the white label solutions with creating a Web3 product from scratch, one of the most important factors is the time needed to launch the product. Pre-built features are available with white-label solutions which means that you can go live much faster. When developing from scratch, one needs more time coding, testing, and checking for bugs in the system. Market Readiness White-label solutions can be implemented fairly quickly, which is a big plus for any company that is aiming to enter the market for its activities. On the other hand, a custom that is built for Web3 requires much more planning and development which takes time, and thus, products may take time to reach the market. Its findings on technical expertise and resource allocation CCTV have ensured the technical know-how of the personnel and resources have been well directed. Skill Set Requirements The creation of a Web3 product requires a combination of many skills when it is developed from the ground up. While others require special skills in areas such as blockchain, smart contracts as well as decentralized applications (dApps). Also, it is crucial to know about cryptograms and protocols’ security concerning the application. However, white-label solutions are usually already built with more attributes, as a result of which the need for unique skills is eliminated. Outsourcing vs In-House Development Choosing to outsource or to develop internally is the first step to be made. Outsourcing helps to reduce costs and use specialized personnel, but using them means that much control over the project may be lost. Case Study: Playnance UpvsDown White Label Solution Playnance has distinguished itself as one of the leading pioneers of web3 white-label solutions by offering a more accessible model and less costly setup fees, eliminating the financial barrier faced by small businesses. For a significantly lower fee, businesses can implement Playnance's a white-label solution, UpvsDown, with no monthly operating costs. This solution is a Web3 P2P trading game where players predict whether the price of Bitcoin will rise or fall. The smart contract collects fees from the winners each round, and traffic owners (platform, media, or influencer) receive a portion of these fees directly from the winners' pool. This approach empowers traffic owners, influencers and media to seamlessly integrate engaging products like Web3 games into their offerings. By attracting players and generating revenue, these businesses can establish new passive income streams. Conclusion The decision to either build a web3 product from scratch or adopt a white-label solution ultimately depends on a company's preference and material considerations. While both approaches are mutually exclusive, they offer great benefits. In the current age characterized by rapid digital growth, companies are faced with a great dilemma when venturing into Web3 technology: should they go for a white-label solution or develop a product from the ground up? Both have their advantages and disadvantages, and an appropriate selection can make all the difference in the success of a particular enterprise. This article explores both approaches, highlighting their benefits and drawbacks. What Are White Label Solutions? White-label solutions” or “white brands” refer to products and services that are created by one company but sold by another company under a different brand name. This approach enables firms to sell products without having to bear the cost of developing them. The key points about it are that it's ready-made products, customizable branding, and facilities for quick market entry. Advantages of White Label Solutions There are also some benefits of white-label solutions which make most of their tasks easier. More economical: There are no development costs, which is very convenient for non-technical companies, media, or influencers. More economical: There are no development costs, which is very convenient for non-technical companies, media, or influencers. Less time to reach the market: Less time to enter the market. Less time to reach the market: Less time to enter the market. More on brand management: Emphasis is on sales, marketing, and branding. More on brand management: Emphasis is on sales, marketing, and branding. Use Cases of White Label Solutions Use Cases of White Label Solutions Some of these white-label solutions can be used across different sectors: E-commerce: Some retailers don’t sell their products, but rather sell the products of third parties under their brand. E-commerce: Software or web3 dApps: Some companies allow others to rebrand their software or web3 dApps and sell them. Software or web3 dApps: Financial services: They are not banks but sell banking services whereby their clients’ products are branded with the brand of the other financial service providers. Financial services: The Appeal of Building a Web3 Product From Scratch There is absolutely nothing wrong with building a product from scratch. In point of fact, there are some benefits to it including: Customization and Control From the perspective of customization and control, creating your own Web3 product is one of the best options. There is how the product is built and that can be made to the tiniest details. This kind of control makes it possible for you to achieve your objectives as you envision. Market Responsiveness The best way to get a Web3 product is by starting its development from scratch, and it is because of the high chances of creativity that it brings on board. You can use one of the most up-to-date technologies and find new applications that cannot be incorporated into white-label solutions. Long Term Vision Building a web3 product from scratch can go along with developing a long-term vision. This involves planning for future growth. It's critical to create a product that evolves with the market. Crucial Considerations For White-Label Solutions Initial Investment As is the case with any venture, the seed capital required while launching a Web3 project may be high or low. It can also be very expensive to come up with a product from the ground up; this may cost as much as say, $1000 and above. In contrast, a white-label solution is more viable and cheaper because the business does not need to invest a lot of money to develop the application, and it can quickly take it to the market. Maintenance and Upgrades Sustaining and enhancing a Web3 product is not one and done, it costs money. Contract-made solutions sometimes need a team to manage upgrades or to do the patching. This could be really challenging for any non-technical firms and media specifically influencers. However, white-label solutions fix this problem by including maintenance and upgrades as part of the services rendered. Hidden Costs As can be seen, hidden costs can often emerge as a real threat to businesses and companies. These might be charges for extra services, regulatory costs, or even above-market rate hosting costs. These are the possibilities that one should take into account while setting his/her financial plan. Development Timelines While comparing the white label solutions with creating a Web3 product from scratch, one of the most important factors is the time needed to launch the product. Pre-built features are available with white-label solutions which means that you can go live much faster. When developing from scratch, one needs more time coding, testing, and checking for bugs in the system. Market Readiness White-label solutions can be implemented fairly quickly, which is a big plus for any company that is aiming to enter the market for its activities. On the other hand, a custom that is built for Web3 requires much more planning and development which takes time, and thus, products may take time to reach the market. Its findings on technical expertise and resource allocation CCTV have ensured the technical know-how of the personnel and resources have been well directed. Skill Set Requirements The creation of a Web3 product requires a combination of many skills when it is developed from the ground up. While others require special skills in areas such as blockchain, smart contracts as well as decentralized applications (dApps). Also, it is crucial to know about cryptograms and protocols’ security concerning the application. However, white-label solutions are usually already built with more attributes, as a result of which the need for unique skills is eliminated. Outsourcing vs In-House Development Choosing to outsource or to develop internally is the first step to be made. Outsourcing helps to reduce costs and use specialized personnel, but using them means that much control over the project may be lost. Case Study: Playnance UpvsDown White Label Solution Playnance has distinguished itself as one of the leading pioneers of web3 white-label solutions by offering a more accessible model and less costly setup fees, eliminating the financial barrier faced by small businesses. For a significantly lower fee, businesses can implement Playnance's a white-label solution, UpvsDown, with no monthly operating costs. This solution is a Web3 P2P trading game where players predict whether the price of Bitcoin will rise or fall. The smart contract collects fees from the winners each round, and traffic owners (platform, media, or influencer) receive a portion of these fees directly from the winners' pool. This approach empowers traffic owners, influencers and media to seamlessly integrate engaging products like Web3 games into their offerings. By attracting players and generating revenue, these businesses can establish new passive income streams. Conclusion The decision to either build a web3 product from scratch or adopt a white-label solution ultimately depends on a company's preference and material considerations. While both approaches are mutually exclusive, they offer great benefits.

White Label Solutions vs Building a Web3 Product From Scratch

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