Crayonis in the Non Fungible Tokens Industry

Crayon

crayon

Companies that leverage advanced technologies like Artificial Intelligence (AI) and cloud computing are being watched as industry leaders -- especially by companies that are ready to leverage new tech. Crayon, a global leader in IT optimization and AI services, has helped countless organizations navigate the complexities of digital transformation and achieve significant business outcomes. One of the key leaders driving Crayon's success is Aaron Sandeen, Executive Leader and VP of Technical Services. With extensive experience in the technology sector, Aaron’s expertise spans across AI integration, cloud optimization, and strategic IT consulting. His leadership and vision have positioned the company as a trusted advisor in the tech industry. Crayon is recognized as a leader in integrating generative AI into workplace technologies. Can you share a specific example where your AI solutions have significantly transformed a client’s operations? What were the challenges, and how did your innovative approach address them? Generative AI is the hot topic with customers right now! Although AI and Machine Learning (ML) are not new concepts for businesses, they are often associated with unattainable, lengthy, and expensive IT projects. Many times, businesses don’t really know how to use or implement projects like these. GenAI has brought the AI/ML game to the masses. Crayon has a 10+ year history of partnering with customers to deliver production AI & ML solutions, and over the past 18 months, we’ve helped dozens and dozens of customers implement GenAI solutions that drive impact. Recently, we partnered with a consumer goods company experiencing massive organic growth and new brand acquisitions. Such rapid success can cause chaos in managing brands, products, descriptions, media assets, offers, pricing, distribution channels, and more. GenAI allows for the writing of one product description and a system that leverages our customer's branding to match the description to dozens of marketplaces where they do business. Instead of repetitively writing thousands of different descriptions and corresponding images necessary to meet the unique requirements of all distribution partners, GenAI can do the heavy lifting. This is just one example of practical applications for GenAI! With your robust expertise in cloud services, including multicloud solutions from Microsoft and AWS, how does Crayon approach cloud optimization differently than other tech consultants? What strategies have you found most effective in helping businesses achieve seamless integration and enhanced productivity? Crayon partners with leaders to understand their business needs, prioritize impactful use cases, and leverage capabilities to deliver value. Using cloud capabilities is table stakes to running their business effectively. We help operationalize these capabilities while identifying cost savings within their existing IT spending to fund other innovative capabilities that AWS and Azure provide. We're obsessed with helping our customers get the most out of technology, reduce risks, and innovate. Crayon’s real value comes from developing deep relationships with our customers, increasing our intelligence about their business and their technology assets, and always advocating for what is best for them. AI readiness is crucial for businesses looking to fully integrate AI into their core operations. What does Crayon’s consultative approach involve, and how do you ensure that your clients are not just adopting but are truly ready to leverage AI for maximum impact? Crayon starts by meeting our customers where they are in the AI journey. Some leaders are new to the AI conversation while others have robust data and AI teams already driving value. We focus on understanding their business, identifying challenges, and defining specific actionable use cases—all while educating about capabilities, benefits, risks, and costs so we can make informed investment decisions together. Next is a clearly defined and focused Proof of Value (POV) project. Upon successful completion of the POV, we roll the solution into production and move to the next priority use case. Success leads to more success! Digital transformation is a significant undertaking for any organization. From your perspective as a customer-first tech leader, what are the common hurdles companies face during this transition, and how does Crayon support them through these challenges to ensure long-term business transformation? It’s hard to believe that Digital Transformation has been around for more than 20 years now! At its core, Digital Transformation is how organizations use technology to change how they operate to be more competitive and successfully scale their business. Sounds simple enough, but there are some significant challenges, including technical readiness, implementation, and change management. Crayon assists leaders in analyzing their current systems, identifying risks, maximizing cost savings, and freeing up precious resources (people and dollars) to invest in building the new! Next, we help accelerate the change by providing skilled experts to deliver high-quality projects and increase our customers’ skills through the process. Most importantly, we know that culture eats strategy for breakfast, and change is not always fun, so we focus on the impact, clear communication, and collaboration, and share what we’ve learned in helping thousands of organizations around the world. Looking ahead, what emerging technologies or industry trends do you believe will be critical for IT optimization over the next five years? How is Crayon preparing to keep its clients at the forefront of these developments? These next five years are going to be an innovator’s dream! AI is going to be better, faster, smarter, more affordable, and accessible. Essentially, it will be found everywhere. These technologies will be crucial for IT optimization, offering new levels of efficiency and innovation. More than ever before, it is going to be critical for businesses to get serious about privacy and security. As always, Crayon will continue to bring a high level of expertise to our customers, talk about the art of the possible, and make sure our customers are secure and prepared for the future. Companies that leverage advanced technologies like Artificial Intelligence (AI) and cloud computing are being watched as industry leaders -- especially by companies that are ready to leverage new tech. Crayon , a global leader in IT optimization and AI services, has helped countless organizations navigate the complexities of digital transformation and achieve significant business outcomes. Crayon One of the key leaders driving Crayon's success is Aaron Sandeen, Executive Leader and VP of Technical Services. With extensive experience in the technology sector, Aaron’s expertise spans across AI integration, cloud optimization, and strategic IT consulting. His leadership and vision have positioned the company as a trusted advisor in the tech industry. Crayon is recognized as a leader in integrating generative AI into workplace technologies. Can you share a specific example where your AI solutions have significantly transformed a client’s operations? What were the challenges, and how did your innovative approach address them? Crayon is recognized as a leader in integrating generative AI into workplace technologies. Can you share a specific example where your AI solutions have significantly transformed a client’s operations? What were the challenges, and how did your innovative approach address them? Generative AI is the hot topic with customers right now! Although AI and Machine Learning (ML) are not new concepts for businesses, they are often associated with unattainable, lengthy, and expensive IT projects. Many times, businesses don’t really know how to use or implement projects like these. GenAI has brought the AI/ML game to the masses. Crayon has a 10+ year history of partnering with customers to deliver production AI & ML solutions, and over the past 18 months, we’ve helped dozens and dozens of customers implement GenAI solutions that drive impact. Recently, we partnered with a consumer goods company experiencing massive organic growth and new brand acquisitions. Such rapid success can cause chaos in managing brands, products, descriptions, media assets, offers, pricing, distribution channels, and more. GenAI allows for the writing of one product description and a system that leverages our customer's branding to match the description to dozens of marketplaces where they do business. Instead of repetitively writing thousands of different descriptions and corresponding images necessary to meet the unique requirements of all distribution partners, GenAI can do the heavy lifting. This is just one example of practical applications for GenAI! With your robust expertise in cloud services, including multicloud solutions from Microsoft and AWS, how does Crayon approach cloud optimization differently than other tech consultants? What strategies have you found most effective in helping businesses achieve seamless integration and enhanced productivity? With your robust expertise in cloud services, including multicloud solutions from Microsoft and AWS, how does Crayon approach cloud optimization differently than other tech consultants? What strategies have you found most effective in helping businesses achieve seamless integration and enhanced productivity? Crayon partners with leaders to understand their business needs, prioritize impactful use cases, and leverage capabilities to deliver value. Using cloud capabilities is table stakes to running their business effectively. We help operationalize these capabilities while identifying cost savings within their existing IT spending to fund other innovative capabilities that AWS and Azure provide. We're obsessed with helping our customers get the most out of technology, reduce risks, and innovate. Crayon’s real value comes from developing deep relationships with our customers, increasing our intelligence about their business and their technology assets, and always advocating for what is best for them. AI readiness is crucial for businesses looking to fully integrate AI into their core operations. What does Crayon’s consultative approach involve, and how do you ensure that your clients are not just adopting but are truly ready to leverage AI for maximum impact? AI readiness is crucial for businesses looking to fully integrate AI into their core operations. What does Crayon’s consultative approach involve, and how do you ensure that your clients are not just adopting but are truly ready to leverage AI for maximum impact? Crayon starts by meeting our customers where they are in the AI journey. Some leaders are new to the AI conversation while others have robust data and AI teams already driving value. We focus on understanding their business, identifying challenges, and defining specific actionable use cases—all while educating about capabilities, benefits, risks, and costs so we can make informed investment decisions together. Next is a clearly defined and focused Proof of Value (POV) project. Upon successful completion of the POV, we roll the solution into production and move to the next priority use case. Success leads to more success! Success leads to more success! Digital transformation is a significant undertaking for any organization. From your perspective as a customer-first tech leader, what are the common hurdles companies face during this transition, and how does Crayon support them through these challenges to ensure long-term business transformation? Digital transformation is a significant undertaking for any organization. From your perspective as a customer-first tech leader, what are the common hurdles companies face during this transition, and how does Crayon support them through these challenges to ensure long-term business transformation? It’s hard to believe that Digital Transformation has been around for more than 20 years now! At its core, Digital Transformation is how organizations use technology to change how they operate to be more competitive and successfully scale their business. Sounds simple enough, but there are some significant challenges, including technical readiness, implementation, and change management. Crayon assists leaders in analyzing their current systems, identifying risks, maximizing cost savings, and freeing up precious resources (people and dollars) to invest in building the new! Next, we help accelerate the change by providing skilled experts to deliver high-quality projects and increase our customers’ skills through the process. Most importantly, we know that culture eats strategy for breakfast, and change is not always fun, so we focus on the impact, clear communication, and collaboration, and share what we’ve learned in helping thousands of organizations around the world. Most importantly, we know that culture eats strategy for breakfast, and change is not always fun, so we focus on the impact, clear communication, and collaboration, and share what we’ve learned in helping thousands of organizations around the world. Looking ahead, what emerging technologies or industry trends do you believe will be critical for IT optimization over the next five years? How is Crayon preparing to keep its clients at the forefront of these developments? Looking ahead, what emerging technologies or industry trends do you believe will be critical for IT optimization over the next five years? How is Crayon preparing to keep its clients at the forefront of these developments? These next five years are going to be an innovator’s dream! AI is going to be better, faster, smarter, more affordable, and accessible. Essentially, it will be found everywhere. These technologies will be crucial for IT optimization, offering new levels of efficiency and innovation. More than ever before, it is going to be critical for businesses to get serious about privacy and security. As always, Crayon will continue to bring a high level of expertise to our customers, talk about the art of the possible, and make sure our customers are secure and prepared for the future.

Crayon’s Blueprint: Pioneering AI and Cloud Innovations for Transformative Business Efficiency

Generative AI (GenAI) is quickly becoming our everyday teammate, helping out behind the scenes in ways we might not even realize. In 2023, a McKinsey survey revealed that one-third of organizations actively use it in at least one business area, such as sales or accounting. But the most significant potential for business lies in software development. Costs of product development Imagine you have a great idea. To create a product out of it, you need to analyze the market, find a product-market fit, and hire strong specialists, including developers, designers, etc. The more complex the project, the more time you need. On average, planning and architecture, along with development and design, can take up to 6-7 months, while testing requires another 2-4 weeks. This process is not only time-consuming but also pricey. The exact cost depends heavily on the type of product and its niche. On average, a simple product, such as a basic web or mobile application with minimal features, can cost a business between $20,000 and $60,000. More advanced applications, integrated with third-party APIs, backend services, and databases, require from $60,000 to $90,000. A complex product, which includes feature-rich applications with advanced functionality, high-security demands, and potentially AI/ML components, calls for more than $100,000. Not every team can afford this level of spending. Given the current venture climate, it may be wise to explore as many cost-reducing strategies as possible. In this context, AI, especially Generative AI (GenAI), can be one of the most helpful tools. It is designed to generate new original content, from text to images, and even code, based on the patterns it learns from the data it is fed. Below, I'll delve into how GenAI can assist you at different stages of product development. Data analysis Generative AI can gather and analyze first-party customer data collected through their ecosystem, as well as reviews and insights on market trends from focus groups, social listening campaigns, and more. With this information, AI can identify customer pain points and product requests, which is crucial for testing your idea and finding a market fit for a future product. Among the AI models capable of this, Viable stands out due to its ability to aggregate and analyze feedback from various platforms, such as emails, chat logs, product reviews, and social media. Another example is Crayon, which leverages machine learning algorithms to analyze market trends and customer feedback, helping to identify customer needs. Soft development When it comes to product development, GenAI facilitates a range of tasks, from code generation to testing and even assisting in software design. Tools like GitHub Copilot, powered by OpenAI's Codex, assist developers by suggesting complete lines of code or entire functions based on the comments or partial code they write. For instance, in 2023, Shopify significantly boosted its productivity, efficiency, and code quality by integrating GitHub Copilot into their engineering processes. The tool helped generate complex Liquid code snippets (Shopify’s templating language), automate routine tasks, and offer best practices for code structure. It proved especially useful in accelerating the development of new themes and features, as well as in debugging existing code. There are also tools like DeepCode and Amazon CodeGuru that review existing code and suggest improvements or identify vulnerabilities. They can spot complex patterns and offer fixes to improve both performance and security. In addition to debugging code, generative AI can pretest upcoming software updates, reducing potential errors. Companies like Diffblue are integrating AI into automatic test generation, which can analyze existing code bases to create unit tests automatically, ensuring that new updates do not break existing functionalities. Design Product development is not only about code; creating an appealing interface is crucial as well. Tools like Stable Diffusion and Midjourney can generate visuals based on instructions from human designers. Many businesses leverage these tools to boost their productivity. For example, Airbnb utilizes AI to transform sketches into product code, drastically reducing the time from design to prototype. In the fashion and retail industry, Under Armour employs Adobe Sensei to enhance product images and quickly create engaging marketing content. Another major retailer, Home Depot, uses the Sensei AI model on their e-commerce platform to streamline search functions and adjust recommendations. Sales and marketing Once you have your product, generative AI can refine marketing strategies by performing A/B testing on elements like page layouts, SEO strategies, etc. It utilizes predictive analytics and data-driven insights to maximize investment returns. GenAI also excels at personalizing the customer experience and optimizing sales. According to McKinsey, generative AI significantly improves upon traditional AI methods in the early stages of sales, such as lead identification and targeting. Instead of basic web scraping and prioritization, it uses algorithms to detect patterns in customer and market data. This allows for better segmentation and targeting of audiences, efficiently identifying high-quality leads and enhancing the effectiveness of lead activation campaigns. In some cases, this can lead to a significant increase in sales, according to Visual Capitalist. Basic rules Thanks to its broad capabilities, GenAI is sometimes seen as a universal solution to solve all issues, either to ride the wave of hype or to impress investors. However, just as microscopes are not designed to hammer nails, GenAI is not a one-size-fits-all tool. You have to test different products until you find those that fit your goals. To maximize the benefits of this technology, it is also crucial to inspire people to use AI and dive deeper into its applications, or even hire someone with experience to lead a team and set an example. Given that this tool is still new, it might be beneficial to regularly meet to track progress, discuss blind spots, address issues, and find ways to improve collective work. Only by following these basic rules product development with AI may lead to success. Generative AI ( GenAI ) is quickly becoming our everyday teammate, helping out behind the scenes in ways we might not even realize. In 2023, a McKinsey survey revealed that one-third of organizations actively use it in at least one business area, such as sales or accounting. But the most significant potential for business lies in software development. GenAI Costs of product development Costs of product development Imagine you have a great idea. To create a product out of it, you need to analyze the market, find a product-market fit, and hire strong specialists, including developers, designers, etc. The more complex the project, the more time you need. On average, planning and architecture, along with development and design, can take up to 6-7 months, while testing requires another 2-4 weeks. This process is not only time-consuming but also pricey. The exact cost depends heavily on the type of product and its niche. On average , a simple product, such as a basic web or mobile application with minimal features, can cost a business between $20,000 and $60,000. More advanced applications, integrated with third-party APIs, backend services, and databases, require from $60,000 to $90,000. A complex product, which includes feature-rich applications with advanced functionality, high-security demands, and potentially AI/ML components, calls for more than $100,000. On average On average Not every team can afford this level of spending. Given the current venture climate, it may be wise to explore as many cost-reducing strategies as possible. In this context, AI, especially Generative AI (GenAI), can be one of the most helpful tools. It is designed to generate new original content, from text to images, and even code, based on the patterns it learns from the data it is fed. Below, I'll delve into how GenAI can assist you at different stages of product development. Data analysis Data analysis Generative AI can gather and analyze first-party customer data collected through their ecosystem, as well as reviews and insights on market trends from focus groups, social listening campaigns, and more. With this information, AI can identify customer pain points and product requests, which is crucial for testing your idea and finding a market fit for a future product. Among the AI models capable of this, Viable stands out due to its ability to aggregate and analyze feedback from various platforms, such as emails, chat logs, product reviews, and social media. Another example is Crayon, which leverages machine learning algorithms to analyze market trends and customer feedback, helping to identify customer needs. Soft development Soft development When it comes to product development, GenAI facilitates a range of tasks, from code generation to testing and even assisting in software design. Tools like GitHub Copilot, powered by OpenAI's Codex, assist developers by suggesting complete lines of code or entire functions based on the comments or partial code they write. For instance, in 2023, Shopify significantly boosted its productivity, efficiency, and code quality by integrating GitHub Copilot into their engineering processes. The tool helped generate complex Liquid code snippets (Shopify’s templating language), automate routine tasks, and offer best practices for code structure. It proved especially useful in accelerating the development of new themes and features, as well as in debugging existing code. boosted boosted There are also tools like DeepCode and Amazon CodeGuru that review existing code and suggest improvements or identify vulnerabilities. They can spot complex patterns and offer fixes to improve both performance and security. In addition to debugging code, generative AI can pretest upcoming software updates, reducing potential errors. Companies like Diffblue are integrating AI into automatic test generation, which can analyze existing code bases to create unit tests automatically, ensuring that new updates do not break existing functionalities. Design Product development is not only about code; creating an appealing interface is crucial as well. Tools like Stable Diffusion and Midjourney can generate visuals based on instructions from human designers. Many businesses leverage these tools to boost their productivity. For example, Airbnb utilizes AI to transform sketches into product code, drastically reducing the time from design to prototype. In the fashion and retail industry, Under Armour employs Adobe Sensei to enhance product images and quickly create engaging marketing content. Another major retailer, Home Depot, uses the Sensei AI model on their e-commerce platform to streamline search functions and adjust recommendations. Sales and marketing Sales and marketing Once you have your product, generative AI can refine marketing strategies by performing A/B testing on elements like page layouts, SEO strategies, etc. It utilizes predictive analytics and data-driven insights to maximize investment returns. GenAI also excels at personalizing the customer experience and optimizing sales. According to McKinsey , generative AI significantly improves upon traditional AI methods in the early stages of sales, such as lead identification and targeting. Instead of basic web scraping and prioritization, it uses algorithms to detect patterns in customer and market data. This allows for better segmentation and targeting of audiences, efficiently identifying high-quality leads and enhancing the effectiveness of lead activation campaigns. In some cases, this can lead to a significant increase in sales, according to Visual Capitalist. According to McKinsey According to McKinsey according according Basic rules Basic rules Thanks to its broad capabilities, GenAI is sometimes seen as a universal solution to solve all issues, either to ride the wave of hype or to impress investors. However, just as microscopes are not designed to hammer nails, GenAI is not a one-size-fits-all tool. You have to test different products until you find those that fit your goals. To maximize the benefits of this technology, it is also crucial to inspire people to use AI and dive deeper into its applications, or even hire someone with experience to lead a team and set an example. Given that this tool is still new, it might be beneficial to regularly meet to track progress, discuss blind spots, address issues, and find ways to improve collective work. Only by following these basic rules product development with AI may lead to success.

Your Ideal Coworker: How To Develop an Innovative Product With a Help of Generative AI

Have you ever found yourself staring at an image spotted somewhere on the internet and wondering whether it results from human or artificial creative labor? Since the breakthrough in image generation technology, I’ve been captivated by interior designs, nature scenery, fashion photographs, and futuristic cityscapes made with AI that look like professional artwork. As someone with a creative eye yet no artistic skills, I was excited about the opportunity to transform ideas from my mind into visuals based solely on text input. I tried out several popular text-to-image tools, like MidJourney and DreamStudio on the web and ARTA on mobile. Still, while they all provided a good starting point and a straightforward user experience, the generation outcomes often fell short of my expectations and differed from what I envisioned — until I learned to tell AI what to draw in the language it understands. If you’re new to AI-generated art and need assistance streamlining the creative process, I’ll provide a step-by-step guide below to help you compose concise and well-structured text prompts that the AI models can effectively interpret and translate into the desired images. In the bottom line, I will share an example of both a correct and an incorrect prompt to illustrate how significantly they can impact the generation output in practice. First things first, two common prompt-writing mistakes you should avoid when using any text-to-image generator are being too wordy and using complex grammar. In fact, the more words you incorporate and the more complicated your grammar, the more difficult it is for AI to understand your prompt and adequately depict your concept. Therefore, communicate concisely, carefully choosing keywords, and list your ideas explicitly and separately rather than trying to cram them into one sentence. Step 1. Choose the Content Type Ask yourself how you want your image to look overall. Do you see it as a photograph, illustration, painting, sketch, or other artwork type? This initial decision puts you in control of the final result and helps align all the elements with this general framework. For instance, choosing a sketch will typically produce pencil images, while opting for a painting will add colors and likely create a more vintage appearance. Step 2. Define the Subject AI image generators require a specific subject for rendering, so you must indicate the main subject of your future image, whether a person, an animal, or a landscape. Stick to one subject per prompt and opt for concrete nouns like girl, dog, train, rose, ocean, temple, etc., for more accurate results. You can most likely render something using abstract keywords like love, peace, or joy, but the results may appear very inconsistent in what they depict. Step 3. Add Subject Description Now, it’s time to detail the concept with modifiers – adjectives or attributive nouns that add to the sense of a head subject. Modifiers can completely change the perspective of your image and boost its overall quality, so the more descriptive you are, the better the generated output. Define what the subject looks like, what the subject is doing, and other characteristics essential to representing your concept. Step 4. Describe the Context To help AI create the exact atmosphere and surroundings you need, give attention to aspects like lightning (studio, soft, cinematic, volumetric, accent lighting, sunlight, frontlight, backlight, ambient, moonlight, etc.), color theme (pastel, vibrant, neon pink, dark, etc.), environment/scene (in the sky, indoor, underwater, at night, etc.), and background (forest, beach, solid color, nebula, etc.). Additionally, consider the mood and vibe you want to convey. Simple feeling modifiers can set the scene’s atmosphere, whether you opt for positive (energetic, cozy, romantic, satisfaction, etc.) or negative (depressive, loneliness, regret, fear, etc.) ones. Step 5. Define Perspective Add a point of view to determine the angle from which you are looking at the image, such as side, overhead, or front. Other essential modifiers for creating photo-like images involve lenses and cameras. Here are a few examples: close-up, macro, lens flare, wide angle, microscopic, bokeh, isometric, depth of field, ultra-wide angle, fisheye lens, and panorama. Step 6. Add Art Style, Art Mediums, and Artists Proceed to aesthetic settings and define the overall artistic style. Also, specify the art medium. These aspects can greatly contribute to the value of the generated output, making it more consistent and expressive. Here are some of the common keywords: geometrical art, pop art, watercolor, line drawing, line art, 3D sculpture, crayon drawing, painting, oil painting, pastel drawing, medieval art, photography, digital art, stained glass, cave painting, polaroid, vector art, retro, illustration, comics, editorial fashion photography, Japanese anime style, surreal, travel photography, pencil sketch, steampunk, cartoon, futurism, vaporwave, art deco, interior design, psychedelic, street art. Consider including artistic influences. Adding the name of a specific artist whose signature artwork aligns with your chosen art genre can enhance the final image. Note, however, that finding the right artist is crucial so as not to mess up the output. Some artists affect the generation only subtly, while others can alter it significantly depending on their distinctive manner. For example, Claude Monet can infuse impressionism into landscapes, while mentioning Salvador Dali adds a surrealistic touch. Step 7. Add “Magic” Words Certain words can make a dramatic difference in the outcomes of the generation. The keywords like highly detailed, ultra-realistic, 4K, 8K, UHD, and HDR are the game changers for the overall quality of the image. Adding “studio lighting” will introduce appealing textures to the image, while “accent lighting” can draw attention to specific features. Describing the image as “professional” can enhance color contrast and detail, while mentioning “vivid colors” will bring life to your image. Using terms like ultra-wide angle, panoramic, or long-shot will help guide the camera. Packing your prompt with phrases related to artistic techniques and materials (such as trending on artstation, precise line-art, golden ratio, fine art, etc.) and those associated with artistic value (such as most beautiful image ever seen, epic composition, etc.) can also bring sophisticated improvements. Step 8. Consider Adding Negative Prompts Negative prompts are parameters that inform the generation model about what you do not want to see in the final image. They help prevent AI from generating specific elements, fix image abnormalities, and improve overall quality. Here are some universal examples: blurry, cropped, cloned face, duplicate, error, ugly, wrong proportions, deform, fused fingers, extra arms, law quality res, watermark, and more. Step 9. Define Correct Word Order and Keyword Weight Input The order is almost as important as the vocabulary, guiding the AI in generating the desired output. Combine keywords to direct the focus of your prompt and note key phrases that influence image preference. Emphasize essential keywords with a full colon and decimal number, use parentheses for added importance, and brackets for less importance. Typically, the earlier a word appears in the sentence, the more importance it is given. If the AI model didn’t take in some key phrase and failed to depict it in the generated image, try rearranging the order of words, placing the missing element earlier in the prompt. Bad vs. Good Prompt Example Bad prompt: portrait of a woman looking directly at the camera, neck tattoo, urban pink background. Good prompt: head and shoulders realistic photo portrait of a beautiful woman looking at the camera, white skin, pink lips, red hair, blue eyes, black tattoos on her neck, neon punk, highly detailed, pink neon city background. Creating effective prompts requires both artistic imagination and technical skills. By including the necessary building blocks and following the proper prompt structure you ensure that the text-to-image generation model understands your vision and produces optimal output. However, don’t be afraid to experiment; the more you practice, the more adept you become, and the more remarkable your creations will be. Have you ever found yourself staring at an image spotted somewhere on the internet and wondering whether it results from human or artificial creative labor? Since the breakthrough in image generation technology, I’ve been captivated by interior designs, nature scenery, fashion photographs, and futuristic cityscapes made with AI that look like professional artwork. Have you ever found yourself staring at an image spotted somewhere on the internet and wondering whether it results from human or artificial creative labor? Since the breakthrough in image generation technology, I’ve been captivated by interior designs, nature scenery, fashion photographs, and futuristic cityscapes made with AI that look like professional artwork. As someone with a creative eye yet no artistic skills, I was excited about the opportunity to transform ideas from my mind into visuals based solely on text input. I tried out several popular text-to-image tools, like MidJourney and DreamStudio on the web and ARTA on mobile. Still, while they all provided a good starting point and a straightforward user experience, the generation outcomes often fell short of my expectations and differed from what I envisioned — until I learned to tell AI what to draw in the language it understands. If you’re new to AI-generated art and need assistance streamlining the creative process, I’ll provide a step-by-step guide below to help you compose concise and well-structured text prompts that the AI models can effectively interpret and translate into the desired images. In the bottom line, I will share an example of both a correct and an incorrect prompt to illustrate how significantly they can impact the generation output in practice. First things first, two common prompt-writing mistakes you should avoid when using any text-to-image generator are being too wordy and using complex grammar. In fact, the more words you incorporate and the more complicated your grammar, the more difficult it is for AI to understand your prompt and adequately depict your concept. Therefore, communicate concisely, carefully choosing keywords, and list your ideas explicitly and separately rather than trying to cram them into one sentence. Step 1. Choose the Content Type Ask yourself how you want your image to look overall. Do you see it as a photograph, illustration, painting, sketch, or other artwork type? This initial decision puts you in control of the final result and helps align all the elements with this general framework. For instance, choosing a sketch will typically produce pencil images, while opting for a painting will add colors and likely create a more vintage appearance. Step 2. Define the Subject AI image generators require a specific subject for rendering, so you must indicate the main subject of your future image, whether a person, an animal, or a landscape. Stick to one subject per prompt and opt for concrete nouns like girl, dog, train, rose, ocean, temple, etc., for more accurate results. You can most likely render something using abstract keywords like love, peace, or joy, but the results may appear very inconsistent in what they depict. Step 3. Add Subject Description Now, it’s time to detail the concept with modifiers – adjectives or attributive nouns that add to the sense of a head subject. Modifiers can completely change the perspective of your image and boost its overall quality, so the more descriptive you are, the better the generated output. Define what the subject looks like, what the subject is doing, and other characteristics essential to representing your concept. Step 4. Describe the Context To help AI create the exact atmosphere and surroundings you need, give attention to aspects like lightning (studio, soft, cinematic, volumetric, accent lighting, sunlight, frontlight, backlight, ambient, moonlight, etc.), color theme (pastel, vibrant, neon pink, dark, etc.), environment/scene (in the sky, indoor, underwater, at night, etc.), and background (forest, beach, solid color, nebula, etc.). Additionally, consider the mood and vibe you want to convey. Simple feeling modifiers can set the scene’s atmosphere, whether you opt for positive (energetic, cozy, romantic, satisfaction, etc.) or negative (depressive, loneliness, regret, fear, etc.) ones. Step 5. Define Perspective Add a point of view to determine the angle from which you are looking at the image, such as side, overhead, or front. Other essential modifiers for creating photo-like images involve lenses and cameras. Here are a few examples: close-up, macro, lens flare, wide angle, microscopic, bokeh, isometric, depth of field, ultra-wide angle, fisheye lens, and panorama. Step 6. Add Art Style, Art Mediums, and Artists Proceed to aesthetic settings and define the overall artistic style. Also, specify the art medium. These aspects can greatly contribute to the value of the generated output, making it more consistent and expressive. Here are some of the common keywords: geometrical art, pop art, watercolor, line drawing, line art, 3D sculpture, crayon drawing, painting, oil painting, pastel drawing, medieval art, photography, digital art, stained glass, cave painting, polaroid, vector art, retro, illustration, comics, editorial fashion photography, Japanese anime style, surreal, travel photography, pencil sketch, steampunk, cartoon, futurism, vaporwave, art deco, interior design, psychedelic, street art. Consider including artistic influences. Adding the name of a specific artist whose signature artwork aligns with your chosen art genre can enhance the final image. Note, however, that finding the right artist is crucial so as not to mess up the output. Some artists affect the generation only subtly, while others can alter it significantly depending on their distinctive manner. For example, Claude Monet can infuse impressionism into landscapes, while mentioning Salvador Dali adds a surrealistic touch. Step 7. Add “Magic” Words Certain words can make a dramatic difference in the outcomes of the generation. The keywords like highly detailed, ultra-realistic, 4K, 8K, UHD, and HDR are the game changers for the overall quality of the image. Adding “studio lighting” will introduce appealing textures to the image, while “accent lighting” can draw attention to specific features. Describing the image as “professional” can enhance color contrast and detail, while mentioning “vivid colors” will bring life to your image. Using terms like ultra-wide angle, panoramic, or long-shot will help guide the camera. Packing your prompt with phrases related to artistic techniques and materials (such as trending on artstation, precise line-art, golden ratio, fine art, etc.) and those associated with artistic value (such as most beautiful image ever seen, epic composition, etc.) can also bring sophisticated improvements. Step 8. Consider Adding Negative Prompts Negative prompts are parameters that inform the generation model about what you do not want to see in the final image. They help prevent AI from generating specific elements, fix image abnormalities, and improve overall quality. Here are some universal examples: blurry, cropped, cloned face, duplicate, error, ugly, wrong proportions, deform, fused fingers, extra arms, law quality res, watermark, and more. Step 9. Define Correct Word Order and Keyword Weight Input The order is almost as important as the vocabulary, guiding the AI in generating the desired output. Combine keywords to direct the focus of your prompt and note key phrases that influence image preference. Emphasize essential keywords with a full colon and decimal number, use parentheses for added importance, and brackets for less importance. Typically, the earlier a word appears in the sentence, the more importance it is given. If the AI model didn’t take in some key phrase and failed to depict it in the generated image, try rearranging the order of words, placing the missing element earlier in the prompt. Bad vs. Good Prompt Example Bad prompt: portrait of a woman looking directly at the camera, neck tattoo, urban pink background. Good prompt: head and shoulders realistic photo portrait of a beautiful woman looking at the camera, white skin, pink lips, red hair, blue eyes, black tattoos on her neck, neon punk, highly detailed, pink neon city background. Creating effective prompts requires both artistic imagination and technical skills. By including the necessary building blocks and following the proper prompt structure you ensure that the text-to-image generation model understands your vision and produces optimal output. However, don’t be afraid to experiment; the more you practice, the more adept you become, and the more remarkable your creations will be.

How to Write Text Prompts for AI Image Generators to Get Optimal Results with Ease

Blackhatworld.com. It's like a digital wasteland where the scavengers of the internet gather to peddle their worthless junk. I mean, seriously, it's a jungle out there, and not in a good way. The forum, also operating as a , is a haven for digital marketing scams and quacks, counting their revenue. freelance platform like Fiverr It's like they've adopted a "see no evil, hear no evil" policy as long as the advertising dollars keep rolling in. The worst part is that these self-proclaimed SEO gurus are polluting the minds of unsuspecting newbies. First off, let's talk about the sheer volume of these services that claim to be the magic potion for boosting your website's ranking. It's like a never-ending parade of snake oil salesmen, each promising the moon and stars but delivering nothing more than a black hole of disappointment. AND ALL FOR !!!! You'd think with the number of self-proclaimed SEO experts on there, Google's algorithm would've been cracked wide open by now. Spoiler alert: it hasn't. And then there's the issue of . It's like the wild west of the internet, with scammers riding into town and looting unsuspecting victims left and right. The worst part? It feels like the platform turns a blind eye to it, if not outright encourages it. scams It's as if they have a neon sign saying, "Scammers welcome, no background checks required." What's even more infuriating is that the scammers seem to have some kind of mystical protection on the forum. It's like they've cast a shield of invisibility, and the moderators are either oblivious or complicit. You try reporting a scammer, and it's like yelling into the void. No one cares, or worse, they might just ban you for daring to speak out against the sacred cow of shady practices. After all, the scammers are paying a fee to advertise their scams on the forum! And let's not forget how the platform knowingly promotes these scams. It's like they've adopted a "see no evil, hear no evil" policy as long as the advertising dollars keep rolling in. It's a classic case of to the festering sore that is their marketplace, all in the pursuit of profit. turning a blind eye I get it; the internet can be a sketchy place, but Blackhatworld.com takes it to a whole new level. It's like they've built a haven for digital charlatans, and they're just sitting back, counting their ad revenue while the unsuspecting users fall victim to the countless scams. I swear, some of the so-called experts on there must have learned SEO from a fortune cookie or a particularly misleading game of telephone! You've got users spouting off advice that's not just questionable—it's downright laughable. It's as if they and decided to tear it up, burn it, and then dance around the ashes while chanting some SEO voodoo incantations. read the SEO rulebook Then there are the brilliant minds who think that backlinks from sketchy, irrelevant sites are the secret sauce to SEO glory. It's like they're playing a dangerous game of link-building Russian roulette, hoping that one day Google will reward them for their dedication to the fine art of link spamming. The worst part is that these self-proclaimed SEO gurus are polluting the minds of unsuspecting newbies who stumble onto the forum seeking guidance. Imagine being a digital Padawan looking for Yoda-level wisdom and instead getting handed a lightsaber made of cardboard with "SEO MAGIC" scrawled on it in crayon. It's a tragedy in the making. So, if you're ever feeling masochistic and decide to dive into the SEO advice section of Blackhatworld.com, brace yourself for a rollercoaster of facepalms and head-scratching moments. It's a wild ride through the twilight zone of SEO wisdom, where the blind are leading the blind, and everyone's just hoping they don't fall off the cliff of search engine oblivion. Good luck out there because you're going to need it.

Blackhatworld.com: Where The Blind Leads The Blind 

Discover the Impact of AI in Sales and Marketing and How It Drives Business Growth In 1956, the concept of (AI) emerged, but it wasn't until the recent launch of OpenAI's ChatGPT that AI truly captured the world's attention. Today, AI dominates conversations across industries. artificial intelligence As of 2022, , with projections soaring to $1,811.8 billion by 2030. the global AI market stood at $136.6 billion AI plays a pivotal role in sales, bridging gaps and boosting revenue. Consider 's movie recommendations or 's tailored product suggestions. In this article, we delve into AI's role in sales, provide use cases, highlight industry examples, and explore the ethical considerations and challenges of adopting AI. We also look ahead to how AI will revolutionize sales in the future. Netflix Amazon How AI Enhances Sales A reveals that sales representatives spend only 33% of their time actively selling. AI steps in to streamline operations and elevate sales performance. HubSpot report AI leverages machine learning to understand customer demographics and interests, enabling tailored experiences. Amazon's predictive analytics exemplifies this approach. Personalization: AI-driven sales forecasting improves accuracy, as seen with Alphabet Inc.'s predictive models enhancing insights into buying patterns. Sales Forecasting: AI tools offer instant analysis of sales calls, identifying weaknesses and improving sales techniques. Microsoft's Dynamics 365 Sales Insights tool demonstrates this. Sales Coaching: Use Cases of AI in Sales & Marketing AI is a game-changer in sales and marketing, with key use cases: AI streamlines lead identification, saving sales reps from the tedious task of searching for potential customers. Lead Generation: AI helps determine which leads are most promising by analyzing user behavior and conversion likelihood. Lead Scoring: AI fairly assigns credit for sales and analyzes data to identify significant touchpoints. Sales Attribution: AI offers real-time feedback during conversations, suggesting responses. Sales Rep Response Suggestion: Risks of AI in Sales & Marketing AI adoption presents risks: Acquiring and training talent for AI can be expensive and challenging for smaller companies. Talent Shortage: Developing AI models requires massive data sets, raising concerns about data privacy and security. Data Requirement: Biased data can lead to AI-driven discriminatory practices, as demonstrated by Amazon's hiring AI system. Bias: Despite advancements, AI still lacks the human touch necessary for complex customer interactions. Lack of Human Touch: AI Sales Tools Some AI sales tools include: An AI-powered chat platform for real-time interactions with potential clients. Drift: Analyzes sales calls to produce successful call blueprints. Gong: Generates high-quality leads and provides sales rep suggestions. Node: Automates data entry, allowing reps to focus on closing deals. People.ai: Gathers competitive insights using AI and machine learning. Crayon: Measuring, Tracking, and Forecasting Sales Performance with AI AI transforms sales performance measurement and forecasting: AI analyzes data to make accurate predictions, supporting informed business decisions. Predictive Analytics: AI extracts valuable insights from vast data sets, improving sales strategies. Data Processing: AI accurately predicts sales pitch outcomes, aiding in prospect prioritization. Lead Scoring: AI chatbots facilitate interactions and provide real-time suggestions to enhance sales. Chatbots: The Future of AI in Sales AI adoption is growing rapidly, with a projected CAGR of 38% from 2021 to 2030. AI is poised to revolutionize sales, enhancing forecasting, lead generation, and personalization. Sales reps will handle complex sales more efficiently, armed with tailored information and improved techniques. Final Thoughts Adopting AI can significantly boost sales performance by automating tasks and promoting productivity. AI transforms core business concepts, such as sales forecasting and lead generation, while addressing ethical concerns is vital for building trust and ensuring responsible AI use in sales and marketing.

Adopting AI in Sales and Marketing

How to Harness the Power of APIs for Your Projects

A VISIT TO THE HAMLEYS.

Psychology of the Unconscious by C. G. Jung, is part of the HackerNoon Books Series. You can jump to any chapter in this book . THE MILLER PHANTASIES here CHAPTER II - THE MILLER PHANTASIES We know, from much psychoanalytic experience, that whenever one recounts his phantasies or his dreams, he deals not only with the most important and intimate of his problems, but with the one the most painful at that moment. [57] Since in the case of Miss Miller we have to do with a complicated system, we must give our attention carefully to the particulars which I will discuss, following as best I can Miss Miller’s presentation. In the first chapter, “Phénomènes de suggestion passagère ou d’autosuggestion instantanée,” Miss Miller gives a list of examples of her unusual suggestibility, which she herself considers as a symptom of her nervous temperament; for example, she is excessively fond of caviar, whereas some of her relatives loathe it. However, as soon as any one expresses his loathing, she herself feels momentarily the same loathing. I do not need to emphasize especially the fact that such examples are very important in individual psychology; that caviar is a food for which nervous women frequently have an especial predilection, is a fact well known to the psychoanalyst. Miss Miller has an extraordinary faculty for taking 43other people’s feelings upon herself, and of identification; for example, she identifies herself to such a degree in “Cyrano” with the wounded Christian de Neuvillette, that she feels in her own breast a truly piercing pain at that place where Christian received the deadly blow. From the viewpoint of analytic psychology, the theatre, aside from any esthetic value, may be considered as an institution for the treatment of the mass complex. The enjoyment of the comedy, or of the dramatic plot ending happily is produced by an unreserved identification of one’s own complexes with the play. The enjoyment of tragedy lies in the thrilling yet satisfactory feeling that something which might occur to one’s self is happening to another. The sympathy of our author with the dying Christian means that there is in her a complex awaiting a similar solution, which whispers softly to her “hodie tibi, cras mihi,” and that one may know exactly what is considered the effectual moment Miss Miller adds that she felt a pain in her breast, “Lorsque Sarah Bernhardt se précipite sur lui pour étancher le sang de sa blessure.” Therefore the effectual moment is when the love between Christian and Roxane comes to a sudden end. If we glance over the whole of Rostand’s play, we come upon certain moments, the effect of which one cannot easily escape and which we will emphasize here because they have meaning for all that follows. Cyrano de Bergerac, with the long ugly nose, on account of which he undertakes countless duels, loves Roxane, who, for her part unaware of it, loves Christian, because of the beautiful verses which really originate from Cyrano’s 44pen, but which apparently come from Christian. Cyrano is the misunderstood one, whose passionate love and noble soul no one suspects; the hero who sacrifices himself for others, and, dying, just in the evening of life, reads to her once more Christian’s last letter, the verses which he himself had composed. “Roxane, adieu, je vais mourir! C’est pour ce soir, je crois, ma bien-aimée! J’ai l’âme lourde encore d’amour inexprimé. Et je meurs! Jamais plus, jamais mes yeux grisés, Mes regards dont c’était les frémissantes fêtes, Ne baiseront au vol les gestes que vous faites; J’en revois un petit qui vous est familier Pour toucher votre front et je voudrais crier—. Et je crie: Adieu!—Ma chère, ma chérie, Mon trésor—mon amour! Mon coeur ne vous quitta jamais une seconde, Et je suis et je serai jusque dans l’autre monde Celui qui vous aime sans mesure, celui—” Whereupon Roxane recognizes in him the real loved one. It is already too late; death comes; and in agonized delirium, Cyrano raises himself, and draws his sword: “Je crois, qu’elle regarde.... Qu’elle ose regarder mon nez, la camarde! (Il lève son épée.) Que dites-vous?... C’est inutile! Je le sais! Mais on ne se bat pas dans l’espoir du succès! Non! Non! C’est bien plus beau, lorsque c’est inutile! —Qu’est-ce que c’est que tous ceux-là?—Vous êtes mille? Ah! je vous reconnais, tous mes vieux ennemis! Le mensonge! (Il frappe de son épée le vide.) 45Tiens, tiens, ha! ha! les Compromis, Les Préjugés, les Lâchetés!... (Il frappe.) Que je pactise? Jamais, jamais!—Ah, te voilà, toi, la Sottise! —Je sais bien qu’à la fin vous me mettrez à bas; N’importe: je me bats! je me bats! je me bats! Oui, vous m’arrachez tout, le laurier et la rose! Arrachez! Il y a malgré vous quelque chose Que j’emporte, et ce soir, quand j’entrerai chez Dieu, Mon salut balaiera largement le seuil bleu. Quelque chose que sans un pli, sans une tache, J’emporte malgré vous, et c’est—mon panache.” Cyrano, who under the hateful exterior of his body hid a soul so much more beautiful, is a yearner and one misunderstood, and his last triumph is that he departs, at least, with a clean shield—“Sans un pli et sans une tache.” The identification of the author with the dying Christian, who in himself is a figure but little impressive and sympathetic, expresses clearly that a sudden end is destined for her love just as for Christian’s love. The tragic intermezzo with Christian, however, is played as we have seen upon a background of much wider significance, viz., the misunderstood love of Cyrano for Roxane. Therefore, the identification with Christian has only the significance of a substitute memory (“deckerinnerung”), and is really intended for Cyrano. That this is just what we might expect will be seen in the further course of our analysis. Besides this story of identification with Christian, there follows as a further example an extraordinarily plastic 46memory of the sea, evoked by the sight of a photograph of a steamboat on the high seas. (“Je sentis les pulsations des machines, le soulèvement des vagues, le balancement du navire.”) We may mention here the supposition that there are connected with sea journeys particularly impressive and strong memories which penetrate deeply into the soul and give an especially strong character to the surface memories through unconscious harmony. To what extent the memories assumed here agree with the above mentioned problem we shall see in the following pages. This example, following at this time, is singular: Once, while in bathing, Miss Miller wound a towel around her hair, in order to protect it from a wetting. At the same moment she had the following strong impression: “Il me sembla que j’étais sur un piédestal, une véritable statue égyptienne, avec tous ses détails: membres raides, un pied en avant, la main tenant des insignes,” and so on. Miss Miller identified herself, therefore, with an Egyptian statue, and naturally the foundation for this was a subjective pretension. That is to say, “I am like an Egyptian statue, just as stiff, wooden, sublime and impassive,” qualities for which the Egyptian statue is proverbial. One does not make such an assertion to one’s self without an inner compulsion, and the correct formula might just as well be, “as stiff, wooden, etc., as an Egyptian statue I might indeed be.” The sight of one’s own unclothed body in a bath has undeniable effects for the phantasy, which can be set at rest by the above formula. [58] 47The example which follows this, emphasizes the author’s personal influence upon an artist: “J’ai réussi à lui faire rendre des paysages, comme ceux du lac Léman, où il n’a jamais été, et il prétendait que je pouvais lui faire rendre des choses qu’il n’avait jamais vues, et lui donner la sensation d’une atmosphère ambiante qu’il n’avait jamais sentie; bref que je me servais de lui comme lui-même se servait de son crayon, c’est à dire comme d’un simple instrument.” This observation stands in abrupt contrast to the phantasy of the Egyptian statue. Miss Miller had here the unspoken need of emphasizing her almost magic effect upon another person. This could not have happened, either, without an unconscious need, which is particularly felt by one who does not often succeed in making an emotional impression upon a fellow being. With that, the list of examples which are to picture Miss Miller’s autosuggestibility and suggestive effect, is exhausted. In this respect, the examples are neither especially striking nor interesting. From an analytical viewpoint, on the contrary, they are much more important, since they afford us a glance into the soul of the writer. Ferenczi has taught us in an excellent work what is to be thought about suggestibility, that is to say, that these phenomena win new aspects in the light of the Freudian libido theory, in so much as their effects become clear through “Libido-besetzungen.” This was already indicated above in the discussion of the examples, and in the greatest detail regarding the identification with Christian. The identification becomes effective by its receiving an influx of energy from the strongly accentuated 48thought and emotional feeling underlying the Christian motif. Just the reverse is the suggestive effect of the individual in an especial capacity for concentrating interest (that is to say, libido) upon another person, by which the other is unconsciously compelled to reaction (the same or opposed). The majority of the examples concern cases where Miss Miller is put under the effects of suggestion; that is to say, when the libido has spontaneously gained possession of certain impressions, and this is impossible if the libido is dammed up to an unusual degree by the lack of application to reality. Miss Miller’s observations about suggestibility inform us, therefore, of the fact that the author is pleased to tell us in her following phantasies something of the history of her love. [59] About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. C. G. Jung (2021). Psychology of the Unconscious. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/65903/pg65903-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

THE MILLER PHANTASIES

REMEDIES FOR THE PRECEDING DIFFICULTIES.

Off on a Comet! a Journey through Planetary Space by Jules Verne, is part of the HackerNoon Books Series. You can jump to any chapter in this book . INTERRUPTED EFFUSIONS here CHAPTER III. INTERRUPTED EFFUSIONS Composed of mud and loose stones, and covered with a thatch of turf and straw, known to the natives by the name of “driss,” the gourbi, though a grade better than the tents of the nomad Arabs, was yet far inferior to any habitation built of brick or stone. It adjoined an old stone hostelry, previously occupied by a detachment of engineers, and which now afforded shelter for Ben Zoof and the two horses. It still contained a considerable number of tools, such as mattocks, shovels, and pick-axes. Uncomfortable as was their temporary abode, Servadac and his attendant made no complaints; neither of them was dainty in the matter either of board or lodging. After dinner, leaving his orderly to stow away the remains of the repast in what he was pleased to term the “cupboard of his stomach.” Captain Servadac turned out into the open air to smoke his pipe upon the edge of the cliff. The shades of night were drawing on. An hour previously, veiled in heavy clouds, the sun had sunk below the horizon that bounded the plain beyond the Shelif. The sky presented a most singular appearance. Towards the north, although the darkness rendered it impossible to see beyond a quarter of a mile, the upper strata of the atmosphere were suffused with a rosy glare. No well-defined fringe of light, nor arch of luminous rays, betokened a display of aurora borealis, even had such a phenomenon been possible in these latitudes; and the most experienced meteorologist would have been puzzled to explain the cause of this striking illumination on this 31st of December, the last evening of the passing year. But Captain Servadac was no meteorologist, and it is to be doubted whether, since leaving school, he had ever opened his “Course of Cosmography.” Besides, he had other thoughts to occupy his mind. The prospects of the morrow offered serious matter for consideration. The captain was actuated by no personal animosity against the count; though rivals, the two men regarded each other with sincere respect; they had simply reached a crisis in which one of them was which of them, fate must decide. de trop; At eight o’clock, Captain Servadac re-entered the gourbi, the single apartment of which contained his bed, a small writing-table, and some trunks that served instead of cupboards. The orderly performed his culinary operations in the adjoining building, which he also used as a bed-room, and where, extended on what he called his “good oak mattress,” he would sleep soundly as a dormouse for twelve hours at a stretch. Ben Zoof had not yet received his orders to retire, and ensconcing himself in a corner of the gourbi, he endeavored to doze—a task which the unusual agitation of his master rendered somewhat difficult. Captain Servadac was evidently in no hurry to betake himself to rest, but seating himself at his table, with a pair of compasses and a sheet of tracing-paper, he began to draw, with red and blue crayons, a variety of colored lines, which could hardly be supposed to have much connection with a topographical survey. In truth, his character of staff-officer was now entirely absorbed in that of Gascon poet. Whether he imagined that the compasses would bestow upon his verses the measure of a mathematical accuracy, or whether he fancied that the parti-colored lines would lend variety to his rhythm, it is impossible to determine; be that as it may, he was devoting all his energies to the compilation of his rondo, and supremely difficult he found the task. “Hang it!” he ejaculated, “whatever induced me to choose this meter? It is as hard to find rhymes as to rally fugitive in a battle. But, by all the powers! it shan’t be said that a French officer cannot cope with a piece of poetry. One battalion has fought—now for the rest!” Perseverance had its reward. Presently two lines, one red, the other blue, appeared upon the paper, and the captain murmured: “Words, mere words, cannot avail,
           Telling true heart’s tender tale.” “What on earth ails my master?” muttered Ben Zoof; “for the last hour he has been as fidgety as a bird returning after its winter migration.” Servadac suddenly started from his seat, and as he paced the room with all the frenzy of poetic inspiration, read out: “Empty words cannot convey
           All a lover’s heart would say.” “Well, to be sure, he is at his everlasting verses again!” said Ben Zoof to himself, as he roused himself in his corner. “Impossible to sleep in such a noise;” and he gave vent to a loud groan. “How now, Ben Zoof?” said the captain sharply. “What ails you?” “Nothing, sir, only the nightmare.” “Curse the fellow, he has quite interrupted me!” ejaculated the captain. “Ben Zoof!” he called aloud. “Here, sir!” was the prompt reply; and in an instant the orderly was upon his feet, standing in a military attitude, one hand to his forehead, the other closely pressed to his trouser-seam. “Stay where you are! don’t move an inch!” shouted Servadac; “I have just thought of the end of my rondo.” And in a voice of inspiration, accompanying his words with dramatic gestures, Servadac began to declaim: “Listen, lady, to my vows—
     O, consent to be my spouse;
     Constant ever I will be,
     Constant....” No closing lines were uttered. All at once, with unutterable violence, the captain and his orderly were dashed, face downwards, to the ground. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jules Verne (1998). Off on a Comet! a Journey through Planetary Space. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/1353/pg1353-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

INTERRUPTED EFFUSIONS

Adult coloring books offer a relaxing, meditative way to unwind that has soared in popularity in recent years. But the selection in stores tends to focus on generic patterns and shapes. And, if you have your own idea for some interesting content, you don't have an easy way to make your own coloring book say, for your friends, unless you're willing to hire an artist or create each detailed drawing yourself. Well, what if I told you there was actually a way around that problem? or follow me on for more content like this! Subscribe Twitter Turns out there is. New AI image generation models like , , and provide an easy way to create endless unique adult coloring book pages personalized to any theme or interest. DALL-E 2 Midjourney Stable Diffusion With the right model (or chain of models... more on that later) and the right prompt, you can get perfectly detailed images for your coloring book idea. In this article, we’ll explore how to leverage the power of AI to make custom coloring books adults will love. We'll take a close look at the for this application, explore some example prompts, study the model's inputs and outputs, play around with it using a web UI, and see how we can couple it with an upscaler like Real-ESRGAN, GFPGAN, or Codeformer to get even better results. Hasdx model We'll also see how we can modify the prompt to vary the level of complexity in the image, effectively tailoring our model to the skill level of the adult (or child) who happens to be holding the crayons. Let's get going. Overview and Intro to Hasdx Recent AI models like DALL-E 2, Midjourney, and Stable Diffusion use various AI techniques to generate remarkably realistic and diverse images from text prompts. They are trained on huge datasets of images and text to "learn" associations between words and visual concepts. By entering the right prompt, you can guide these models to create custom illustrations suitable for coloring books. For our adult coloring book project, we will use (originally on Civitai). We'll look specifically at an implementation of Hasdx created by and hosted on . Hasdx cjwbw Replicate I chose Hasdx specifically because it is a fine-tuned version of Stable Diffusion, allowing it to produce high-quality, varied images perfect for coloring books. How Was Hasdx Developed? Why Use It? , developed through a collaboration between academic researchers and non-profit organizations, sparked a revolution in AI image generation. Stable Diffusion As creators began experimenting with Stable Diffusion, specialized models emerged seeking to enhance aspects like image quality and training control. One such model was the HuggingFace model by creator , also available on . By fine-tuning Stable Diffusion on a diverse dataset, 22h developed a versatile general-purpose model skilled at detailed image generation. Vintedois Diffusion V0 1 22h Replicate Around the same period, two checkpoint models gained recognition for their artistic capabilities - and . Sxd-berrymix-merge, made by AI artist EMAD, combined earlier Stable Diffusion checkpoints and applied additional precision training focused on improving facial features, lighting, and color realism. sxd-berrymix-merge handas-3dkx10b As a result, it excels at photorealistic human images. Meanwhile, handas-3dkx10b, created by digital artist handas2077, employed 3D modeling techniques to achieve exceptional accuracy and detail. Identifying an opportunity for synergy, developer merged these models. By combining Vintedois Diffusion's versatility with sxd-berrymix-merge's portrait talents and handas-3dkx10b's precision, bestjammer created Hasdx - a 7.2 GB model balancing general capability with specialized artistry. bestjammer Unlike its complex predecessors, Hasdx emphasized simplicity, flexibility, and high-fidelity results. This made it appealing for creative applications like generating adult coloring book illustrations, where intricate designs can benefit from Hasdx's detail without requiring lengthy prompts. For users across skill levels, Hasdx brought professional-grade image generation within reach. How to Interact With Hasdx Using the Replicate Demo UI If you'd like to follow along with the steps in this guide and try your hand at generating an adult coloring book image with Hasdx alongside me, the fastest and simplest way to get started is to use to Replicate demo UI. Here's how to access it: Head to the model details page for on AImodels.fyi Hasdx In the column on the right, find the Replicate demo link ( ) "Model Link" -> "View on Replicate" Create a Replicate account, and choose the tab on the Hasdx page "Demo" Interact directly with the prompt fields as needed and click "generate" to test your inputs. You can also read more about how to interact with the model in the . complete Hasdx model guide Hasdx Inputs and Outputs When using Hasdx for an adult coloring book project, there are a few key inputs you can adjust. We'll focus on the prompt in the next section, but to be thorough, here's a list of all of the parameters you can play around with. - This is where you provide the text prompt describing what you want the AI to generate. For an adult book, focus on themes and intricate details. prompt - Specify anything you want the image to avoid, like text or distracting background objects. negative_prompt - Hasdx works best at high resolutions like 768x768. Higher sizes capture more detail. width/height - Around 80 steps render details nicely without taking too long. num_inference_steps - Keep this high, like 9-10, so outputs adhere closely to the prompt. guidance_scale - Change the seed to get variation between otherwise identical prompts. seed The key outputs from Hasdx will be high-resolution PNG images matching the prompt details. With the right prompts (shown below), the AI will generate sharp, intricate illustrations perfect for printable adult coloring book pages. If you're using Replicate to interact with the model (as we will be doing in this example), the output will look like this: {
  "type": "array",
  "items": {
    "type": "string",
    "format": "uri"
  },
  "title": "Output"
} Crafting the Prompt The key to generating great images with AI is carefully crafting the text prompt. For coloring books, we want simple black-and-white line drawings with thick outlines. Here is a prompt structure that works well, inspired by Chase Lean's on how to create children's book drawings using Midjourney. Twitter thread adult coloring book, cartoon, [theme], intricate details, advanced patterns, black and white Replace [theme] with whatever you want to illustrate - animals, vehicles, foods, etc. Let's try some examples: adult coloring book, cartoon, delicate flowers, intricate details, advanced patterns, black and white adult coloring book, cartoon, beautiful warrior, intricate details, advanced patterns, black and white adult coloring book, cartoon, art deco buildings, intricate details, advanced patterns, black and white You'll also gain a lot by setting a negative prompt. Here's the one I used: color, photo, fax, screenshot, border, blurry, grainy You can set the other parameters I reviewed above. Here's a full example that I think has a very nice output. adult coloring book, cartoon, beautiful warrior, intricate details, advanced patterns, black and white Prompt: photo, fax, screenshot, border, blurry, grainy Negative prompt: 512 Width: 512 Height: 1 Number of Outputs: 185 Number of Inference Steps: 12 Guidance Scale: DPMSolverMultistep Scheduler: none (blank) Seed: Adjusting the Complexity We can also adjust the complexity of the generated images. For adult books, intricate details and advanced patterns are preferred. Children's books, on the other hand, usually favor simpler images due to the fine motor skill level of their readers. To make more basic illustrations for simpler children's books, consider to have elements that call out simpler styles: changing the prompt b/w outline art for kids coloring book page, rabbit, Kids coloring pages, full white, kids style, white background, whole body, Sketch style, full body (((((white background))))), only use outline. , cartoon style, line art, coloring book, clean line art, white background, Sketch style (Original prompt from ) prompthero Experiment with different style values to get the right level of detail. But remember, most adults enjoy advanced complexity. Upscaling the Image You may find the resulting image generated by Hasdx a little blurry, especially if you need to scale it up to be larger for a book you'd ultimately like to print. Fortunately, you can run your outputs through another model to get an even better file. These models are called upscalers, and there are many popular options: : Offers outstanding results for ideal simulated degradation. This model would work well for restoring synthetic images like the ones we're creating with Hasdx. ESRGAN : Tailored to tackle real-world corruptions, but still capable of cleaning up synthetic images . Real-ESRGAN just like the older ESRGAN model A robust designed to work with both old photos and AI-generated faces. Would work well for cleaning up weird artifacts in portrait-type generations for coloring books. Codeformer: face restoration algorithm , this model is and can help us clean up portraits generated as coloring book images. : GFPGAN Similar to Codeformer good for restoring faces Here's an example that shows how running the first example output through Real-ESRGAN results in a better-quality image: The results are pretty subtle, but once you see the upscaled image and original side-by-side, you can see how the improved lines make coloring the image easier - fewer gray areas and sharper boundaries are great for this type of application. Generating a Complete Book Once you've perfected your prompts and practiced upscaling images, you're basically all set. You can now generate the full set of illustrations for your book by following this general process: Make a list of themes and topics you want to include. Craft a prompt for each one using the formula above, adjusting the style as needed. Consider using a seed to keep styles consistent. Refine any illustrations that don't have enough detail. Use an upscaler to enhance them. Arrange the final images into printable pages using publishing software. And that's it - you now have a custom AI-generated adult coloring book! The enormous range of intricately detailed images these models can create makes it easy to tailor the book to any style and subject matter. Conclusion Using AI to create custom adult coloring books is an exciting new application of generative image models. As we've seen, tools like Hasdx provide an endless source of unique, intricate illustrations to make highly personalized books. Here are some of the big takeaways after walking through this full process: Recent AI models like Stable Diffusion enable generating custom images through carefully crafted text prompts. Fine-tuning produces specialized models like Hasdx tailored for specific creative needs. Hasdx balances general capabilities with a focus on realism and detail. This makes it well-suited for detailed adult coloring book images. The prompt structure gives you precise control over the theme and complexity of the generated illustrations. Negative prompts help avoid undesirable elements. Running Hasdx outputs through upscaling models improves quality for printing. ESRGAN and others sharpen details and lines. The enormous range of possible illustrations makes custom books easy to tailor to individual styles and interests. AI looks poised to become a game-changer in enabling creators to make unique coloring books and other personalized image-based products. The world of generative AI is rapidly evolving. As models continue to improve in capability and accessibility, we're likely to see many more emerging applications like custom adult coloring books. The future looks bright for leveraging AI creativity! Thanks for reading. or follow me on for more content like this! Subscribe Twitter Resources and Further Reading Here are some helpful resources that you may want to take a look at as you work on your AI-based adult coloring book project: - Mixed stable diffusion model optimized for creativity Hasdx model - A comprehensive guide to mixed stable diffusion models Unveiling the Magic of Hasdx - AI image upscaling model Real-ESRGAN - AI face restoration model Codeformer - AI face restoration model GFPGAN - Tool for optimizing text prompts PromptHero - Prompt design tips for midjourney Chase Lean's Twitter thread Also published here

How to Use Hasdx to Create an AI-Generated Adult Coloring Book

একটি এআই-জেনারেটেড অ্যাডাল্ট কালারিং বুক তৈরি করতে হ্যাসডিএক্স কীভাবে ব্যবহার করবেন

So erstellen Sie mit Hasdx ein KI-generiertes Malbuch für Erwachsene

Cómo usar Hasdx para crear un libro de colorear para adultos generado por IA

Comment utiliser Hasdx pour créer un livre de coloriage pour adultes généré par l'IA

एआई-जनरेटेड एडल्ट कलरिंग बुक बनाने के लिए हैस्डएक्स का उपयोग कैसे करें

Hasdx を使用して AI 生成の大人の塗り絵を作成する方法

Hasdx를 사용하여 AI 생성 성인 색칠 공부 책을 만드는 방법

Como usar o Hasdx para criar um livro de colorir adulto gerado por IA

Yapay Zeka ile Üretilmiş Yetişkinlere Yönelik Bir Boyama Kitabı Oluşturmak İçin Hasdx Nasıl Kullanılır

Cách sử dụng Hasdx để tạo sách tô màu dành cho người lớn do AI tạo

如何使用 Hasdx 创建人工智能生成的成人涂色书

GRETCHEN'S FORTY WINKS

Emily of New Moon by L. M. Montgomery, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . Ilse CHAPTER XI. Ilse EMILY was locked in the spare-room and told that she must stay there until bedtime. She had pleaded against such a punishment in vain. She had tried to give the Murray look but it seemed that—in her case at any rate—it did not come at will. “Oh, don’t shut me up alone there, Aunt Elizabeth,” she implored. “I know I was naughty—but don’t put me in the spare-room.” Aunt Elizabeth was inexorable. She knew that it was a cruel thing to shut an over-sensitive child like Emily in that gloomy room. But she thought she was doing her duty. She did not realize and would not have for a moment believed that she was really wreaking her own smothered resentment with Emily for her defeat and fright on the day of the threatened hair-cutting. Aunt Elizabeth believed she had been stampeded on that occasion by a chance family resemblance coming out under stress, and she was ashamed of it. The Murray pride had smarted under that humbling, and the smart ceased to annoy her only when she turned the key of the spare-room on the white-faced culprit. Emily, looking very small and lost and lonely, her eyes full of such fear as should have no place in a child’s eyes, shrank close against the door of the spare-room. It was better that way. She could not imagine things behind her then. And the room was so big and dim that a dreadful number of things could be imagined in it. Its bigness and dimness filled her with a terror against which she could not strive. Ever since she could remember she had had a horror of being shut up alone in semi-darkness. She was not frightened of twilight out-of-doors, but this shadowy, walled gloom made of the spare-room a place of dread. The window was hung with heavy, dark-green material, reinforced by drawn slat-blinds. The big canopied bed, jutting out from the wall into the middle of the floor, was high and rigid and curtained also with dark draperies. might jump at her out of such a bed. What if some great black hand should suddenly reach out of it—reach right across the floor—and pluck at her? The walls, like those of the parlour, were adorned with pictures of departed relatives. There such a large connection of dead Murrays. The glasses of their frames gave out weird reflections of the spectral threads of light struggling through the slat blinds. Worst of all, right across the room from her, high up on the top of the black wardrobe, was a huge, stuffed white Arctic owl, staring at her with uncanny eyes. Emily shrieked aloud when she saw it, and then cowered down in her corner aghast at the sound she had made in the great, silent, echoing room. She wished that something jump out of the bed and put an end to her. Anything was would “I wonder what Aunt Elizabeth would feel like if I was found here ,” she thought, vindictively. dead In spite of her fright she began to dramatize it and felt Aunt Elizabeth’s remorse so keenly that she decided only to be unconscious and come back to life when everybody was sufficiently scared and penitent. But people died in this room—dozens of them. According to Cousin Jimmy it was a New Moon tradition that when any member of the family was near death he or she was promptly removed to the spare-room, to die amid surroundings of proper grandeur. Emily could them dying, in that terrible bed. She felt that she was going to scream again, but she fought the impulse down. A Starr must not be a coward. Oh, that owl! Suppose, when she looked away from it and then looked back she would find that it had silently hopped down from the wardrobe and was coming towards her. Emily dared not look at it for fear that was just what had happened. the bed curtains stir and waver! She felt beads of cold perspiration on her forehead. had see Didn’t Then something did happen. A beam of sunlight struck through a small break in one of the slats of the blind and fell directly athwart the picture of Grandfather Murray hanging over the mantel-piece. It was a crayon “enlargement” copied from the old daguerreotype in the parlour below. In that gleam of light his face seemed veritably to leap out of the gloom at Emily with its grim frown strangely exaggerated. Emily’s nerve gave way completely. In an ungovernable spasm of panic she rushed madly across the room to the window, dashed the curtains aside, and caught up the slat blind. A blessed flood of sunshine burst in. Outside was a wholesome, friendly, human world. And, of all wonders, there, leaning right against the window-sill was a ladder! For a moment Emily almost believed that a miracle had been worked for her escape. Cousin Jimmy had tripped that morning over the ladder, lying lost among the burdocks under the balm-of-gileads behind the dairy. It was very rotten and he decided it was time it was disposed of. He had shouldered it up against the house so that he would be sure to see it on his return from the hayfield. In less time than it takes to write of it Emily had got the window up, climbed out on the sill, and backed down the ladder. She was too intent on escaping from that horrible room to be conscious of the shakiness of the rotten rungs. When she reached the ground she bolted through the balm-of-gileads and over the fence into Lofty John’s bush, nor did she stop running till she reached the path by the brook. Then she paused for breath, exultant. She was full of a fearful joy with an elfin delight running through it. Sweet was the wind of freedom that was blowing over the ferns. She had escaped from the spare-room and its ghosts—she had got the better of mean old Aunt Elizabeth. “I feel as if I was a little bird that had just got out of a cage,” she told herself; and then she danced with joy of it all along her fairy path to the very end, where she found Ilse Burnley huddled up on the top of a fence panel, her pale-gold head making a spot of brilliance against the dark young firs that crowded around her. Emily had not seen her since that first day of school and again she thought she had never seen or pretended anybody just like Ilse. “Well, Emily of New Moon,” said Ilse, “where are you running to?” “I’m running away,” said Emily frankly. “I was bad—at least, I was a little bad—and Aunt Elizabeth locked me in the spare-room. I hadn’t been bad enough for —it wasn’t fair—so I got out of the window and down the ladder.” that “You little cuss! I didn’t think you’d gimp enough for that,” said Ilse. Emily gasped. It seemed very dreadful to be called a little cuss. But Ilse had said it quite admiringly. “I don’t think it was gimp,” said Emily, too honest to take a compliment she didn’t deserve. “I was too scared to stay in that room.” “Well, where are you going now?” asked Ilse. “You’ll have to go somewhere—you can’t stay outdoors. There’s a thunderstorm coming up.” So there was. Emily did not like thunderstorms. And her conscience smote her. “Oh,” she said, “do you suppose God is bringing up that storm to punish me because I’ve run away?” “No,” said Ilse scornfully. “If there is any God he wouldn’t make such a fuss over nothing.” “Oh, Ilse, don’t you believe there is a God?” “I don’t know. Father says there isn’t. But in that case how did things happen? Some days I believe there’s a God and some days I don’t. You’d better come home with me. There’s nobody there. I was so dod-gastedly lonesome I took to the bush.” Ilse sprang down and held out her sunburned paw to Emily. Emily took it and they ran together over Lofty John’s pasture to the old Burnley house which looked like a huge grey cat basking in the warm late sunshine, that had not yet been swallowed up by the menacing thunderheads. Inside, it was full of furniture that must have been quite splendid once; but the disorder was dreadful and the dust lay thickly over everything. Nothing was in the right place apparently, and Aunt Laura would certainly have fainted with horror if she had seen the kitchen. But it was a good place to play. You didn’t have to be careful not to mess things up. Ilse and Emily had a glorious game of hide and seek all over the house until the thunder got so heavy and the lightning so bright that Emily felt she must huddle on the sofa and nurse her courage. “Aren’t you ever afraid of thunder?” she asked Ilse. “No, I ain’t afraid of anything except the devil,” said Ilse. “I thought you didn’t believe in the devil either—Rhoda said you didn’t.” “Oh, there’s a devil all right, Father says. It’s only God he doesn’t believe in. And if there a devil and no God to keep him in order, is it any wonder I’m scared of him? Look here, Emily Byrd Starr, I like you—heaps. I’ve always liked you. I knew you’d soon be good and sick of that little, white-livered, lying sneak of a Rhoda Stuart. never tell lies. Father told me once he’d kill me if he ever caught me telling a lie. I want you for chum. I’d go to school regular if I could sit with you.” is I my “All right,” said Emily off-handedly. No more sentimental Rhodian vows of eternal devotion for her. phase was over. That “And you’ll tell me things—nobody ever tells me things. And let tell things—I haven’t anybody to tell things to,” said Ilse. “And you won’t be ashamed of me because my clothes are always queer and because I don’t believe in God?” me you “No. But if you knew Father’s God you’d believe in .” Him “I wouldn’t. Besides, there’s only one God if there is any at all.” “I don’t know,” said Emily perplexedly. “No, it can’t be like that. Ellen Greene’s God isn’t a bit like Father’s, and neither is Aunt Elizabeth’s. I don’t think I’d Aunt Elizabeth’s, but He is a God at least, and Ellen’s isn’t. And I’m sure Aunt Laura’s is another one still—nice and kind but not wonderful like Father’s.” like dignified “Well never mind—I don’t like talking about God,” said Ilse uncomfortably. “ do,” said Emily. “I think God is a very interesting subject, and I’m going to pray for you, Ilse, that you can believe in Father’s God.” I “Don’t you dast!” shouted Ilse, who for some mysterious reason did not like the idea. “I won’t be prayed for!” “Don’t you ever pray yourself, Ilse?” “Oh, now and then—when I feel lonesome at night—or when I’m in a scrape. But I don’t want any one else to pray for me. If I catch you doing it, Emily Starr, I’ll tear your eyes out. And don’t you go sneaking and praying for me behind my back either.” “All right, I won’t,” said Emily sharply, mortified at the failure of her well-meant offer. “I’ll pray for every single soul I know, but I’ll leave you out.” For a moment Ilse looked as if she didn’t like this either. Then she laughed and gave Emily a volcanic hug. “Well, anyway, please like me. Nobody likes me, you know.” “Your father like you, Ilse.” must “He doesn’t,” said Ilse positively. “Father doesn’t care a hoot about me. I think there’s times when he hates the sight of me. I wish he like me because he can be awful nice when he likes any one. Do you know what I’m going to be when I grow up? I’m going to be an elo-cu-tion-ist.” did “What’s that?” “A woman who recites at concerts. I can do it dandy. What are you going to be?” “A poetess.” “Golly!” said Ilse, apparently overcome. “I don’t believe can write poetry,” she added. you “I can so, too,” cried Emily. “I’ve written three pieces—‘Autumn’ and ‘Lines to Rhoda’—only I burned —and ‘An Address to a Buttercup.’ I composed it to-day and it is my—my masterpiece.” that “Let’s hear it,” ordered Ilse. Nothing loth, Emily proudly repeated her lines. Somehow she did not mind letting Ilse hear them. “Emily Byrd Starr, you make that out of your own head?” didn’t “I did.” “Cross your heart?” “Cross my heart.” “Well”—Ilse drew a long breath—“I guess you a poetess all right.” are It was a very proud moment for Emily—one of the great moments of life, in fact. Her world had conceded her standing. But now other things had to be thought of. The storm was over and the sun had set. It was twilight—it would soon be dark. She must get home and back into the spare-room before her absence was discovered. It was dreadful to think of going back but she must do it lest a worse thing come upon her at Aunt Elizabeth’s hands. Just now, under the inspiration of Ilse’s personality, she was full of Dutch courage. Besides, it would soon be her bedtime and she would be let out. She trotted home through Lofty John’s bush, that was full of the wandering, mysterious lamps of the fireflies, dodged cautiously through the balm-of-gileads—and stopped short in dismay. The ladder was gone! Emily went around to the kitchen door, feeling that she was going straight to her doom. But for once the way of the transgressor was made sinfully easy. Aunt Laura was alone in the kitchen. “Emily dear, where on earth did you come from?” she exclaimed. “I was just going up to let you out. Elizabeth said I might—she’s gone to prayer-meeting.” Aunt Laura did not say that she had tiptoed several times to the spare-room door and had been racked with anxiety over the silence behind it. Was the child unconscious from fright? Not even while the thunderstorm was going on would relentless Elizabeth allow that door to be opened. And here was Miss Emily walking unconcernedly in out of the twilight after all this agony. For a moment even Aunt Laura was annoyed. But when she heard Emily’s tale her only feeling was thankfulness that Juliet’s child had not broken her neck on that rotten ladder. Emily felt that she had got off better than she deserved. She knew Aunt Laura would keep the secret; and Aunt Laura let her give Saucy Sal a whole cupful of strippings, and gave her a big plummy cooky and put her to bed with kisses. “You oughtn’t to be so good to me because I bad to-day,” Emily said, between delicious mouthfuls. “I suppose I disgraced the Murrays going barefoot.” was “If I were you I’d hide my boots every time I went out of the gate,” said Aunt Laura. “But I wouldn’t forget to put them on before I came back. What Elizabeth doesn’t know will never hurt her.” Emily reflected over this until she had finished her cooky. Then she said, “That would be nice, but I don’t mean to do it any more. I guess I must obey Aunt Elizabeth because she’s the head of the family.” “Where do you get such notions?” said Aunt Laura. “Out of my head. Aunt Laura, Ilse Burnley and I are going to be chums. I like her—I’ve always felt I’d like her if I had a chance. I don’t believe I can ever any girl again, but I her.” love like “Poor Ilse!” said Aunt Laura, sighing. “Yes, her father doesn’t like her. Isn’t it dreadful?” said Emily. “Why doesn’t he?” “He does—really. He only thinks he doesn’t.” “But does he think it?” why “You are too young to understand, Emily.” Emily hated to be told she was too young to understand. She felt that she could understand perfectly well if only people would take the trouble to explain things to her and not be so mysterious. “I wish I could pray for her. It wouldn’t be fair, though, when I know how she feels about it. But I’ve always asked God to bless all my friends so she’ll be in and maybe some good will come of it. Is ‘golly’ a proper word to say, Aunt Laura?” that “No—no!” “I’m sorry for that,” said Emily, seriously, “because it’s very striking.” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. L. M. Montgomery (2020). Emily of New Moon. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/61236/pg61236-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

Emily was locked in the spare-room

A PRISONER OF LOVE

THE MATERIALIZING OF CECIL

A Tempest in the School Teapot

THE DRAWINGS OF LEONARDO DA VINCI BY C. LEWIS HIND

: This essay is intended particularly for children to help them comprehend without using technical jargon. It is not intended for entry-level, intermediate, or senior software engineers. Note In this introductory section, we'll understand what Python is, and how we can set it up. Content Purpose 1. You'll get to understand the nature of this computer language. 2. You will understand what Python can be used for. 3. The versions of Python and it's history 4. Installing Python on your computer system A. What is Python? One thing I want you to understand at your age is that; Python in this case, is not an animal. It is a computer programming language and was created by Dutch programmer called . Yes, I am talking to you if you are under 12 years of age. I created this piece of content to assist you with comprehending the programming language without getting bogged down in technical/coding/programming jargon. Let us proceed. Guido Van Rossum As Guildo Van Rossum was developing this computer programming language, he was also watching a 1970s BBC comedy series called "Monty Python's Flying Circus." He thought he needed a simple name, short, unique, and mysterious. Then, he named this computer programming language "Python". Programming languages are created to give computers instructions, just the same way your parents use the English Language to give you instructions to do one thing or the other. Now, to answer what Python is, we can say; : Python is 1. a solver language (i.e. an interpreted language) This means that the instructions you give to your computer are not solved by the computer; they are solved by Python itself. Therefore, your code will work on any computer that has Python installed on it. If your Dad and Mummy have Python installed on their computers, your python code will work on it. 2. interactive Interactive computer languages are close to human languages, such as the English Language, Chinese, Yoruba Language, etc. This helps you to relate with your computer as if you are talking to your friends and playing hide-and-seek. 3. behaves like real-life objects (i.e. object-oriented programming language). Let's start explaining this by asking a question: What are the objects you can point to in your house? Hint: The objects you can feel and touch. I will answer this and say; LEGO Toy, Baby Dolls, Table, Chair, Bicycle, etc. For example, LEGO is an object that comes in small cubes, which you can use to make a bigger object such as Car, House, etc. Building a house with LEGO, you can create a Window, the Roof, the Wall, and so on, and then join them together to make a House. You can "reuse" your LEGO again and again. You can use your Table again and again. You can use the Chair alone with another Table. You can take it to the playground and sit down on it. You can move it around. behaves like an object too. You can use it to arrange the instructions you are giving to the computer and then "reuse" those instructions multiple times. Python programming language 4. high-level language Earlier, we talked about interpreted language, and we said Python is an interpreted language. This point will be useful in understanding what high-level languages are. Python is a high-level language because the code/instruction you wrote in Python the computer doesn't understand it. It means that; the Python you installed on your computer has the duty of doing two things, which are: it understands the instruction/code that you wrote for the computer to do, and it interprets it to what the computer will understand before the computer can do it and give you results. So, high-level language is a language that cannot be understood directly by our computers. The only language the computer understands is . Python will always convert your own code/instructions to , which is then converted to that the computer understands. Machine Language bytecode Machine Code B. What can Python do? Python is a "General Purpose" computer language. This means you can use it to create anything that comes to your mind. So, Python can be used to do a lot of things. In fact, let's even call it a tool that can be used to create anything you can use on your computer and mobile phone. Just like how you can use your Crayon to color any diagram. Just like you can use LEGO to build anything or any shape you want. However, let's talk about some computer things you can use Python for. You can decide to focus on any of these paths: Web Development You can use Python to create websites and web applications. It has special solutions too, such as Django and Flask, which specifically makes it easier to build web apps such as instagram.com. Data Analysis You can use Python for Data Analysis. Let's explain: Sometimes we collect a lot of numbers and information about things, like how many apples we have or how tall our friends are. Data analysis helps you with all that information. It helps you to find patterns in it too. Just like how we put together puzzle pieces to see the whole picture, we use data analysis to put all the numbers together to see what they tell us. For example, we might find out that we have more red apples than green apples or that our tallest friend is also the oldest. Data analysis helps us to learn more about the world around us by looking at all the information we have. Python has powerful solutions for you to do Data Analysis. Some of those solutions are called Pandas, NumPy, and SciPy. They make it easy to analyze and interpret lots of rough information in pictures you can understand easily. You can use these special solutions to make decisions about the pieces of information. Automation Python can be used to help you to do things that you repeat all the time, such as sending emails, downloading files, and scraping (copying) things from a website on the internet. Python has special solutions for these types of homework, too and it helps you do it by itself. Once you tell the computer how it will do it, it will do it for you, and you can sleep while the computer does the work for you. Examples of such solutions are Selenium and Beautiful Soup, to copy things online and save it automatically. (AI) Artificial Intelligence Python is used a lot in Artificial Intelligence (AI) and Machine Learning. The idea around Artificial Intelligence is to mimic/copy humans’ intelligence. To act the way humans do, such as solving mathematics, writing letters just like the way your Daddy and Mummy will write, and so on. Machine learning is like teaching a computer to learn on its own, just like how we learn new things as we grow up. We teach computers by showing them examples and telling them what to look for. For example, if we wanted to teach a computer how to tell the difference between apples and oranges, we would show it many pictures of apples and oranges and tell it which ones are apples and which ones are oranges. Then, the computer would try to figure out on its own how to tell the difference between them. Machine learning helps computers to learn and get better at doing things without us having to tell them every single step. Therefore, Python is used extensively in Artificial Intelligence (AI) and Machine Learning. There are so many solutions built to help you do Artificial Intelligence and Machine Learning, Some of them are TensorFlow, PyTorch, and Keras to build deep learning models and train them on large datasets. These are a few places where Python can be used. There are other places like Scientific Computing (i.e. Hard Mathematics) and solutions such as SymPy and SciPy are available for that. It helps you solve complex mathematical problems and perform simulations. Hopefully, when you learn Python well, someday, you too will be able to impact your community by creating solutions that specifically solve a problem. C. Python versions There are different versions of Python, like how you might have different versions of your favorite toy. The newest version of Python is called Python 3, which is like having the newest and coolest version of your toy. Older versions of Python are like having an older version of your toy that might not have all the fun features of the new version. It's important to use the newest version of Python so that you can create the coolest things and keep your computer safe. Python 1.x: The first version of Python, released in 1991. Python 2.x: The second major version of Python, released in 2000. Python 2.x was widely used for many years, and many popular special solutions like the ones we described above were built with it. Python 3.x: The current version of Python, was first released in 2008. Python 3.x introduced several changes and improvements over Python 2.x, but is not backward-compatible with it. Many developers have since switched to Python 3.x, but some solutions/systems still use Python 2.x. Note that; the “x” in front of these versions means that there are versions released that fix some problems in that version. D. Installing Python This is the section I think your parents can follow to prepare a perfect computer environment for you to jump into python programming. So call on Mummy & Daddy to help you. However, I will focus on explaining well enough for you to do it yourself. Now, note that computer systems some years ago came with Python already installed. So it is possible your computer has it already installed. But how will you know? Please, follow the steps below to check: For Windows Open “ “ on your windows computer, then type , it will return a response that will actually show the version installed or simply tells you it doesn’t exist and it can’t understand what you typed. Command Prompt python --version For Linux & MacBook Open “ ” on your system, then once it is open, type , what you will see will look like the output below: Terminal python --version tiwa@Olaoluwas ~ % python --version
Python 3.10.2 If you have a response like this, then it means Python is already installed and you can see the version on your system. In my own case, it is version 3.10.2. If you figure out that you do not have Python already installed on your computer system, that is not a problem. Please follow the steps below to install it on your computer: Go to and click on “ button to download Python. Version 3.11.2 is the current vers on as of the time of writing this information. https://www.python.org/downloads/ Download Python 3.11.2” i Go to your downloaded file and double-click on it to install. You will see a screen. Follow the prompts. But most importantly, if you are using Windows system, make sure two boxes titled “ ” and “ ,” on the screen are selected, and then click on “ .” Install launcher for all users (recommended) Add Python 3.x.x to PATH Install Now For Windows, the screen will show you it is successfully installed and most likely show a box saying, “ ” Please click it, then close the screen Disable path length limit. For Linux & Mac, you can’t go wrong. Just click “continue” throughout, and accept the terms and conditions if it is asking you to do so to continue. Testing Python Now, I believe you have successfully installed Python. You can see the example below. we tried to do . Let’s test it: 2 + 2 = 4 Open your Terminal if you use Linux/Mac or Command Prompt if you use Windows. Type . python Once the interpreter environment responds, type . a = 2 Also, type . b = 2 Type . c =  a + b Now, type to get the result of the addition. This should give you 4. You can see the example below. c This is an example of what I listed from number 1 to 6 under “Testing Python”: tiwa@Olaoluwas ~ % python
Python 3.10.2 (main, Mar  1 2022, 17:33:22) [Clang 12.0.5 (clang-1205.0.22.11)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> a = 2
>>> b = 2
>>> c = a + b
>>> c
4
>>> Final Thoughts We're indeed finished with this introduction! I have made sure it is not too technical for a start and what you can call an introduction. I hope you learned that Python is a special kind of language that people use to make computers do cool things. I believe you now understand the nature of this computer language, what Python programming language can be used for, versions of Python, and how to install Python and play additions with it. In summary, I believe this blog will push you to explore more in the path of software development, which includes all aspects of what Python can be used for, as we explained earlier, such as Web Development.

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