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Custom iPhone ringtone: How to create one from any MP3

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Turn A YouTube Video Into A Ringtone
Make a ringtone out of anything!
Image: D. Griffin Jones/Cult of Mac

If you don’t have your phone on silent, you may as well have a fun, custom iPhone ringtone. After all, custom Home Screens and Lock Screens are all the rage — you can create a ringtone that matches your aesthetic.

Between wearing an Apple Watch and leaving my phone muted, I almost never hear my ringtone, but needs and preferences vary. If you don’t wear an Apple Watch and you carry your phone in a bag or purse, a ringtone is the only way you’ll hear a call coming in.

It’s not super straightforward, but here’s how you can make a custom iPhone ringtone out of an MP3 using just your phone. Keep reading below or watch our video.

How to make a custom iPhone ringtone

Sure, you can always pick from one of Apple’s built-in ringtones in Settings > Sounds & Haptics > Ringtone. But if you want to create your own custom iPhone ringtone, follow these instructions:

Download YouTube video as MP3 using cobalt.tools
Download any YouTube video as an MP3 using cobalt.tools
Screenshot: D. Griffin Jones/Cult of Mac

Time needed: 10 minutes

 How to make a custom iPhone ringtone

  1. Save an MP3 file from a YouTube video

    First, the custom iPhone ringtone you want needs to be in MP3 format.
    If you can find it on YouTube, that’s great. Copy the URL, go to cobalt.tools, tap Audio, paste the link, and hit >>. Tap the Download button to save the MP3.
    Otherwise, make sure the custom ringtone you want is downloaded on your iPhone in the Files app.

  2. Download GarageBand

    To make a ringtone out of your MP3, you need to download GarageBand, Apple’s app designed to make and edit music. (Don’t worry, you don’t need to record anything. This is all part of the process.)
    It’s completely free on the App Store.Creating an new GarageBand project

  3. Create a new song

    Next, open GarageBand, swipe over to the Audio Recorder tool, and tap Voice. You don’t need to touch any of the controls — hit the third button on the left of the toolbar that looks like a stack of blocks.Creating a custom ringtone on iPhone by pasting an MP3 file into GarageBand

  4. Add your MP3

    To add the MP3 you want to use as your custom iPhone ringtone, you need to switch over to the Files app. In the Recents tab, the most recent two files should be “My Song” (or whatever you called the GarageBand project you just created) and the MP3 you downloaded earlier.
    With one finger, tap and hold on the icon for the MP3 file, then tap Copy. Switch back to GarageBand, tap on the empty timeline, then tap Paste.

  5. Trim the audio clip

    If there’s a part of the song you want to trim out — silence at the beginning, a section you don’t want at the end — it’s easy to edit that out.
    Tap the left side of the clip and drag the edge inward to cut out the beginning. It should be outlined in yellow. Then, tapping the middle of the clip, you can drag it back to start at the beginning.
    Do the same on the right edge to cut out the end. Ringtones are automatically trimmed down to 30 seconds long, so if your MP3 is longer than that, you might as well find the best stopping point yourself.
    You can pinch with two fingers to zoom in for more precision. Preview your edits with the Play button in the toolbar.

  6. Rename your file and save it as a custom iPhone ringtone

    Tap the ▼ button to the left of the toolbar and tap My Songs. Tap and hold on My Song, the one you just created, and tap Rename.
    Tap and hold on it again, and tap Share > Ringtone. Then tap Export. Tap Use sound as… to pick if you want it for your phone ringtone, text tone or for a specific contact.

You can create multiple custom iPhone ringtones to use for various people

And that’s how you create a custom ringtone on your iPhone. If you want to switch it back at any point, you can customize it in Settings > Sounds & Haptics > Ringtone.

You can repeat the directions above to create a bunch of different ringtones. The more you create, the more options that’ll appear in the list. You also can use a really short sound effect as a notification alert for incoming texts, new email, reminders and more.

You can also assign a custom ringtone to a specific contact. Open Contacts (or the Contacts tab of Phone), tap on a contact and tap Edit. Below their contact information like phone number, email and pronouns, you can set a custom ringtone and text tone for them from the ones you’ve created.

More ways to customize your phone



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How manufacturers can create a sustainable business model

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In the wake of the sustainability deal signed by nations at COP28, environmental, social and corporate governance (ESG) has never been as important to organizations as it is now. However, for many companies, abiding by ESG regulations feels like an administrative burden, instead of an initiative designed to deliver business value.

Nevertheless, customer awareness of corporate sustainability and climate-responsible business is increasing, and so are the number of businesses consumers can pick and choose from, leaving manufacturing firms struggling to differentiate themselves. If they want to attract customers and investors, and in turn stay ahead of increasing competition, manufacturers must look beyond merely fulfilling sustainability regulations, and make tackling sustainability issues an imperative part of their business model.

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How to use Garmin Coach to create a training plan on your Garmin watch

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If you own one of the best Garmin watches and you want to start training for a race, then you have a pretty useful tool in your armory in the shape of Garmin Coach.

Garmin Coach is Garmin’s own training platform built for runners and cyclists. of all abilities that know they need a training plan and don’t know where to start. Best of all, once created, that plan will then live on your watch, serving up the runs you need to when it’s time to train. 

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Entertainment

The White House tells NASA to create a new time zone for the Moon

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On Tuesday, The White House published a policy memo directing NASA to create a new time standard for the Moon by 2026. Coordinated Lunar Time (LTC) will establish an official time reference to help guide future lunar missions. It arrives as a 21st-century space race emerges between (at least) the US, China, Japan, India and Russia.

The memo directs NASA to work with the Departments of Commerce, Defense, State, and Transportation to plan a strategy to put LTC into practice by December 31, 2026. International cooperation will also play a role, especially with signees of the Artemis Accords. Established in 2020, they’re a set of common principles between a growing list of (currently) 37 countries that govern space exploration and operating principles. China and Russia are not part of that group.

“As NASA, private companies, and space agencies around the world launch missions to the Moon, Mars, and beyond, it’s important that we establish celestial time standards for safety and accuracy,” OSTP Deputy Director for National Security Steve Welby wrote in a White House press release. “A consistent definition of time among operators in space is critical to successful space situational awareness capabilities, navigation, and communications, all of which are foundational to enable interoperability across the U.S. government and with international partners.”

Einstein’s theories of relativity dictate that time changes relative to speed and gravity. Given the Moon’s weaker gravity (and movement differences between it and Earth), time moves slightly faster there. So an Earth-based clock on the lunar surface would appear to gain an average of 58.7 microseconds per Earth day. As the US and other countries plan Moon missions to research, explore and (eventually) build bases for permanent residence, using a single standard will help them synchronize technology and missions requiring precise timing.

“The same clock that we have on Earth would move at a different rate on the moon,” NASA space communications and navigation chief Kevin Coggins told Reuters. “Think of the atomic clocks at the U.S. Naval Observatory (in Washington). They’re the heartbeat of the nation, synchronizing everything. You’re going to want a heartbeat on the moon.”

Photo of the Moon, captured by NASA, in exquisite detail.Photo of the Moon, captured by NASA, in exquisite detail.

NASA

The White House wants LTC to coordinate with Coordinated Universal Time (UTC), the standard by which all of Earth’s time zones are measured. Its memo says it wants the new time zone to enable accurate navigation and scientific endeavors. It also wants LTC to maintain resilience if it loses contact with Earth while providing scalability for space environments “beyond the Earth-Moon system.”

NASA’s Artemis program aims to send crewed missions back to the Moon for the first time since the Apollo missions of the 1960s and 70s. The space agency said in January that Artemis 2, which will fly around the Moon with four people onboard, is now set for a September 2025 launch. Artemis 3, which plans to put humans back on the Moon’s surface, is now scheduled for 2026.

In addition to the US, China aims to put astronauts on the Moon before 2030 as the world’s two foremost global superpowers take their race to space. Although no other countries have announced crewed missions to the lunar surface, India (which put a module and rover on the Moon’s South Pole last year), Russia (its mission around the same time didn’t go so well), the United Arab Emirates, Japan, South Korea and private companies have all demonstrated lunar ambitions in recent years.

In addition to enabling further scientific exploration, technological establishment and resource mining, the Moon could serve as a critical stop on the way to Mars. It could test technologies and provide fuel and supply needs for eventual human missions to the Red Planet.

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Using LangGraph to create multi-agent LLM coding AI frameworks

Using LangGraph to create multi-agent LLM coding frameworks

LangGraph has been used to create a multi-agent large language model (LLM) coding framework. This framework is designed to automate various software development tasks, including coding, testing, and debugging. The system is built upon the LangGraph module, which enhances the LangChain ecosystem by enabling the creation of AI agents. The framework features specialized agents, each with a distinct role in the software development process.

LangGraph is at the forefront of a new era in software development, offering a graph-based approach that automates many tasks developers face daily. As a developer, you’ll find LangGraph to be a powerful ally. It provides a suite of specialized AI agents, each designed to boost the efficiency of your workflow:

– The Programmer Agent helps you write code that meets your specific needs.
– The Tester Agent creates test cases and expected outcomes to ensure your code works correctly.
– The Executor Agent runs your code in a Python environment once it’s ready.
– The Debugger Agent uses its expertise to find and fix bugs if your code encounters problems.

Constructing Multi-Agent LLM Coding Frameworks with LangGraph

These AI agents are part of a larger ecosystem known as LangChain, which supports the creation of AI agents for various development roles. The architecture of this multi-agent framework is a marvel of modern technology. It uses LangGraph’s state graphs, nodes, and edges to coordinate the activities of the AI agents. They operate independently but in a way that’s synchronized, much like a well-oiled team of developers.

One of the standout features of this framework is its user-friendly interface, thanks to integration with Streamlit. This means that developers of all skill levels can easily interact with the system. You can input your specifications and watch as the AI agents perform their tasks, from generating code to debugging it.

Here are some other articles you may find of interest on the subject of  AI agents :

Building AI frameworks

The adaptability of this framework to your questions and needs is another significant advantage. It can create, refine, and troubleshoot code, customizing its responses to fit the unique requirements of your project. This level of efficiency and adaptability showcases the potential of large language models (LLMs) to reshape software development.

Moreover, the framework’s code is available on GitHub, fostering a collaborative environment. This openness allows you to experiment with the framework, contribute to its growth, or integrate it into your own projects.

LangGraph and its multi-agent LLM coding framework represent a significant shift in the software development landscape. They demonstrate the impressive capabilities of AI automation and the expanding potential of LLMs. Looking ahead, it’s clear that tasks in software development are set to become more streamlined and advanced, thanks to these AI-driven innovations.

What is the LangGraph module?

Now, let’s delve deeper into how LangGraph works and why it’s such a significant advancement for developers like you. At its core, LangGraph uses a graph-based structure to represent the state of a software project. This structure is made up of nodes and edges, which together form a comprehensive map of the code and its various components. By analyzing this map, the AI agents can understand the context of the code and perform their tasks more effectively.

For instance, when you’re writing new code, the Programmer Agent can suggest improvements or alternative approaches by examining the existing graph. If you’re testing your code, the Tester Agent can use the graph to predict potential issues and generate relevant test cases. And when it comes to debugging, the Debugger Agent can quickly identify where the problems lie within the graph and offer solutions.

The beauty of LangGraph lies in its ability to learn and adapt. As you and other developers interact with the framework, it continuously evolves, becoming more attuned to the nuances of software development. This learning capability means that over time, the AI agents become even better at assisting you, making your job easier and more efficient.

But LangGraph isn’t just about individual tasks. It’s about the bigger picture of software development. By automating routine and complex tasks alike, it frees you up to focus on creative problem-solving and innovation. This shift in focus can lead to better quality software, developed faster and with fewer errors.

Furthermore, the collaborative aspect of LangGraph cannot be overstated. With its code available on GitHub, you’re not just using a tool; you’re joining a community. You have the opportunity to shape the future of the framework, share your insights, and learn from others. This collective effort can accelerate the improvement of LangGraph and, by extension, the entire field of software development.

As AI continues to advance, it’s clear that technologies like LangGraph will play an increasingly important role in how we create software. They offer a glimpse into a future where the boundaries of what’s possible are continually expanding. For developers, this means an exciting journey ahead, full of new challenges and opportunities to innovate.

So, as you consider the impact of LangGraph on your work, think about the possibilities it opens up. With AI by your side, you’re not just coding; you’re crafting the future of technology. And that’s an exciting place to be.

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Create interactive virtual worlds from text prompts using Genie 1.0

Create interactive virtual worlds from text prompts using Genie 1

Google has introduced Genie 1.0, an AI system that represents a significant advancement toward Artificial General Intelligence (AGI). Genie 1.0 is a generative interactive environment that can create a variety of virtual worlds from text descriptions, including synthetic images, photographs, and sketches. It operates on an unsupervised learning model trained on low-resolution internet videos, which are then upscaled. This system is considered a foundational world model, crucial for the development of AGI, due to its ability to generate action-controllable environments.

Google has made a striking advancement in the realm of artificial intelligence with the unveiling of Genie 1.0, a system that edges us closer to the elusive goal of Artificial General Intelligence (AGI). This new AI is capable of transforming simple text descriptions into interactive virtual environments, marking a significant stride in the evolution of AI technologies.

At the core of Genie 1.0’s functionality is the ability to bring written scenes to visual life. This goes beyond the typical AI that we’re accustomed to, which might recognize speech or offer movie recommendations. Genie 1.0 is designed to construct intricate virtual worlds, replete with images and sketches, all from the text provided by a user. It relies on an advanced form of machine learning known as unsupervised learning, which empowers it to identify patterns and make informed predictions without needing explicit instructions.

One of the most fascinating features of Genie 1.0 is its proficiency in learning from imperfect sources. It can take low-resolution videos from the internet, which are often grainy and unclear, and enhance them to a more refined 360p resolution. This showcases the AI’s ability to work with less-than-ideal data and still produce improved results.

Google Genie 1.0 another step closer to AGI?

Here are some other articles you may find of interest on the subject of Artificial General Intelligence (AGI) :

Understanding Artificial General Intelligence (AGI)

The driving force behind Genie 1.0 is a robust foundational world model, boasting an impressive 11 billion parameters. This model is a cornerstone for AGI development, as it facilitates the generation of dynamic and manipulable environments. Such environments are not just static but can be altered and interacted with, paving the way for a multitude of potential uses.

The versatility of Genie 1.0 is evident in its ability to process a wide array of inputs, suggesting that its future applications could go far beyond the creation of simple 2D environments. Although it currently functions at a rate of one frame per second, there is an expectation that its performance will improve over time. As Google continues to enhance Genie with future iterations, we can expect a broadening of its capabilities.

The practical uses for Genie 1.0 are vast and varied. In the field of robotics, for instance, combining Google’s robotics data with Genie could lead to the creation of more sophisticated AI systems. The gaming industry also stands to benefit greatly from Genie, as it has the potential to revolutionize game development, offering novel experiences and serving as a platform for training AI agents in simulated environments.

While Genie 1.0 promises to significantly influence creative endeavors by enabling the generation of unique content from minimal input, it’s important to remain mindful of the concerns that accompany advanced AI systems. Skepticism about AI is not uncommon, and as technologies like Genie continue to advance, they will undoubtedly spark further debate about their impact and the ethical considerations they raise.

Exploring Genie 1.0’s Advanced Capabilities

Google’s Genie 1.0 represents a pivotal development in the journey toward AGI. Its innovative method of creating interactive virtual worlds and its ability to learn from low-resolution data highlight the immense possibilities within AI. As we look to the future, the continued refinement and application of systems like Genie will undoubtedly play a crucial role in shaping the trajectory of both technology and society.

Artificial General Intelligence, or AGI, is a type of intelligence that mirrors human cognitive abilities, enabling machines to solve a wide range of problems and perform tasks across different domains. Unlike narrow AI, which is designed for specific tasks such as language translation or image recognition, AGI can understand, learn, and apply knowledge in an array of contexts, much like a human being. The development of AGI is a significant challenge in the field of artificial intelligence, as it requires a system to possess adaptability, reasoning, and problem-solving skills without being limited to a single function.

At the heart of Genie 1.0’s functionality lies its ability to interpret and visualize text descriptions, transforming them into detailed virtual environments. This process is driven by unsupervised learning, a machine learning technique that allows AI to recognize patterns and make decisions with minimal human intervention. Unsupervised learning is crucial for AGI, as it enables the system to handle data in a way that mimics human learning, where explicit instructions are not always provided.

Genie 1.0’s proficiency in enhancing low-resolution videos to a clearer 360p resolution demonstrates its capacity to improve upon imperfect data. This is a significant step forward, as it shows that AI can not only work with high-quality data but also refine and utilize information that is less than ideal, which is often the case in real-world scenarios.

The Potential and Challenges of Google Genie

The foundational world model that powers Genie 1.0, with its 11 billion parameters, is a testament to the complexity and potential of this AI system. The ability to generate dynamic environments that users can interact with opens up a world of possibilities for various industries. For example, in robotics, Genie 1.0 could be used to create more advanced simulations for training AI, while in gaming, it could lead to more immersive and responsive virtual worlds.

Despite its current limitation of processing one frame per second, the expectation is that Genie 1.0 will become faster and more efficient with time. This improvement will expand its applications and make it even more valuable across different sectors.

However, the advancement of AI technologies like Genie 1.0 also brings about ethical considerations. As AI systems become more capable, questions arise about their impact on privacy, employment, and decision-making. It is crucial to address these concerns proactively, ensuring that the development of AI benefits society while minimizing potential risks.

In summary, Google’s Genie 1.0 is a significant step towards achieving AGI, with its innovative approach to creating interactive virtual environments and learning from various data sources. As this technology continues to evolve, it will likely have a profound impact on multiple industries and raise important ethical questions that must be carefully considered.

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How to Create a Website with ChatGPT

website chatGPT

This guide will show you how to create a website with the help of ChatGPT. In the dynamic and ever-evolving landscape of the digital age, the capacity to swiftly transform abstract ideas into tangible outcomes is more than just advantageous—it’s essential, particularly within the realm of web development. For those who harbor a profound interest in the aesthetics and functionality of web design, yet find themselves hindered by a lack of extensive coding expertise, there’s exciting news.

The emergence of advanced AI technologies, notably ChatGPT and its most recent upgrade, CH GPT-4, has revolutionized the process of web creation. This breakthrough allows for the conversion of mere images depicting website designs into fully operational, interactive websites. This comprehensive guide is designed to escort you through the nuanced process of recreating websites with the assistance of ChatGPT. It promises to demystify the complexities involved, enabling you to actualize your digital aspirations efficiently and with a remarkable reduction in technical obstacles.

The Magic of Website Recreation with ChatGPT

Imagine having the power to recreate any website from just a screenshot. That’s exactly what ChatGPT offers. By providing detailed prompts to ChatGPT, you can guide it to generate the HTML and CSS code necessary for your website design. This process highlights the importance of precision in your prompts to achieve results that closely match your vision.

Your Step-by-Step Companion

  1. Capture Your Vision: It all starts with a screenshot of the website design you wish to recreate. This image serves as the foundation for your project.
  2. Craft Detailed Prompts: Use these prompts to guide ChatGPT in generating the code. This involves specifying your design requirements, from layout to color schemes.
  3. Test and Tweak: Platforms like CodePen are your playground for testing the generated code. This step is crucial for refining your website’s look and functionality.

Beyond Basic Design: Customization and Interactive Elements

A website isn’t just about good looks; it’s about functionality and user experience. This guide delves into how to enhance your website:

  • Content Customization: Learn how to tailor the content and layout section by section, ensuring your site communicates your message effectively.
  • Design Enhancement: Utilize external tools for selecting color palettes that elevate your website’s aesthetics.
  • Interactive Components: Add functionality like real-time forms using services such as Formspark, making your site not only visually appealing but also interactive and user-friendly.

Seamless Hosting Solutions

The journey doesn’t end with design and development. Hosting your website is the next crucial step. This guide introduces you to platforms like Tiny Host for free hosting solutions and WebSpace Kit for those looking to upgrade to a professional domain. It covers everything from selecting the right hosting service to transferring your website files, ensuring a smooth transition from development to live site.

Empowering Your Web Development Journey

Whether you’re a budding web developer or a creative individual looking to manifest your digital ideas, the integration of AI through ChatGPT opens up a new realm of possibilities. By breaking down the barriers to web development, ChatGPT empowers you to create, customize, and launch websites that resonate with your personal or professional brand.

Leveraging the capabilities of CH GPT-4, this comprehensive guide provides a step-by-step approach to transforming a mere image into a fully operational website. From the initial design conception to the intricacies of hosting, you’re equipped with the knowledge to navigate the web development process with confidence and creativity.

Embrace the synergy of creativity and technology. Let this guide be your roadmap to exploring the potential of AI in web development, unlocking the door to endless possibilities in the digital space.

Source Website Learners

Here are some more useful ChatGPT guides:

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How to use Midjourney 6 consistent style feature to create themes of images

How to use Midjourney 6 consistent style feature

Creating series of similar images is now easy using AI art generator is such as Midjourney 6 thanks to a new feature called consistent style.  Imagine having the power to illustrate a seamless visual story, where every image echoes a singular artistic vision. This is the magic that Midjourney’s consistent style feature brings to the table for artists, designers, and content creators. It’s a tool that simplifies the process of giving a series of images a unified look and feel. Let’s delve into how you can harness this feature to enhance your art direction and storytelling, creating a series of images that are not only captivating but also maintain a consistent style.

Midjourney’s consistent style feature is a powerful asset for anyone looking to maintain a specific aesthetic across various images. It works by using reference images that you upload, which capture the essence of the style you’re after. These images act as a blueprint, ensuring that each new image you create mirrors the same stylistic elements, providing a cohesive visual experience that’s crucial for storytelling.

When selecting reference images, it’s important to choose ones that truly represent the style you want to achieve. These could be from photography, existing artwork, or even scenes from films. Once you’ve uploaded these images to Midjourney, they become the foundation of your style, guiding the creation of new images to match your artistic vision.

Creating themes using Midjourney 6 consistent style

The process of creating images with Midjourney involves crafting clear prompts, a technique known as atomic prompting. This means your prompts should be concise and focused, detailing the essential elements that define the style and subject of the images you wish to create. A straightforward approach in your prompts ensures that you achieve your artistic goals with precision and efficiency. Watch the demonstration below kindly created by Cyberjungle to learn more about using the Midjourney consistent style feature.

Here are some other articles you may find of interest on the subject of Midjourney styles to take your AI art generation new directions :

One of the key features for transferring the aesthetic of your reference images to your new creations is the ‘sr’ parameter. By adjusting this parameter, you can control how much influence the reference style has on your images. This allows for a smooth style transfer that enhances your thematic imagery.

Another important setting is the style weight, which you can adjust using the ‘ssw’ parameter. This setting is crucial for finding the right balance between the original content and the injected style. By fine-tuning this setting, you gain detailed control over how much each reference image affects the final output, ensuring a perfect harmony of style and content.

Midjourney also offers intuitive style tuner tools that streamline your workflow. These tools make it easy to make quick decisions about style references, image prompts, and adjustments. The user-friendly interface allows for rapid comparisons and changes, which can significantly enhance the efficiency of your creative process.

For those who draw inspiration from the world of cinema, Midjourney offers the ability to apply the distinctive styles of iconic films to your images. This is particularly useful for creating mood boards or narrative elements that require a specific cinematic feel.

To ensure that your image series maintains a consistent look, it’s helpful to put together a style guide. This guide should document your reference images and style settings, serving as a vital resource for maintaining a consistent aesthetic in both ongoing and future projects.

Midjourney’s consistent style feature is an invaluable tool for creatives. By using reference images, precise prompts, and adjustable style parameters, you can produce images that are not only visually stunning but also thematically aligned. As you become more skilled with these tools, your ability to tell visual stories and create mood boards will grow, taking your work to new heights of artistic achievement.

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How to create laser engraving depth maps from AI generated images

creating depth maps for laser engraving from AI artwork

The world of design and manufacturing is witnessing a significant shift with the introduction of artificial intelligence (AI) into the realm of 3D laser engraving. The ability to create a wide range of amazing designs and concepts in just a few minutes is reshaping the capabilities of manufacturing for small businesses and enthusiasts. If you would like to learn how to create depth maps for laser engraving from AI generated images this quick guide will show you how to build maps for intricate designs that can be etched onto various materials, including wood, metal and more.

The key to achieving high-quality 3D engravings lies in the creation of depth maps from AI-generated images, a process that is both fascinating and complex yet extremely easy to do thanks to AI tools. Imagine being able to transform a flat image into a textured, three-dimensional work of art. Once you have your AI-generated artwork, the next step involves converting it into a depth map for you to create  an engraving.

TilingZoeDepth AI App

This is where the Tiling Zod Dev project comes into play. Created by Bill F. Smith, this project offers the tools needed to turn your images into the maps that will guide the laser during the engraving process. By using Google Colab, a cloud-based platform that can be accessed with a Google account, you can upload your image and execute a series of commands to generate depth maps in both low and high resolutions.

Workflow:

  1. Generate a depth map for the overall image
  2. Split original image into overlapping tiles
  3. Generate depth maps for the tiles
  4. Reassemble into a single depth map by applying gradient masks and average weighting from first depth map
  5. Repeat steps 2-4 at higher resolution
  6. Combine all three depth maps by:
    a) Calculate edge filter from original RGB image
    b) Blur edge filter and use as mask for high resolution depth map
    c) Apply masked high resolution to average of low and medium resolution depth maps

Building depth maps for laser engraving from AI images

Watch the excellent tutorial currently created by Justin Laser  below to learn more about how you can easily create depth maps from AI artwork that you can then laser engrave onto a wide variety of different materials.

Here are some other articles you may find of interest on the subject of laser engraving :

These depth maps are crucial as they dictate how the laser interacts with the material’s surface, creating the stunning 3D effect. After the maps are generated, they can be downloaded for use in the laser engraving machine. It’s important to disconnect from the server after this step to avoid any potential penalties.

The next phase is the actual engraving, where understanding the relationship between the laser and the material is essential. For example, CO2 lasers are typically used for softer materials like wood, while fiber lasers are more suitable for engraving metals. It’s crucial to adjust the laser settings based on the depth map guidelines to ensure the final product has the desired level of detail and precision.

Depth maps have revolutionized the field of laser engraving by enabling a degree of detail and realism that was once difficult to achieve. They bring out the natural beauty of wood grains and the reflective qualities of metals, elevating the aesthetic value of the material.

Things to consider when  creating depth maps for engraving

Creating depth maps from AI-generated artwork for laser engraving involves several critical considerations to ensure the final product meets high standards of detail and quality. This guide covers essential aspects, including selecting the right AI tools, preparing images, converting them into depth maps, and understanding material-laser interactions. Each step plays a crucial role in achieving a textured, three-dimensional engraving that enhances the visual appeal of the material.

1. Selecting AI Tools for Image Generation

  • Quality and Detail: Choose AI applications that can generate high-resolution images with the level of detail necessary for engraving. Look for software that specializes in creating images with depth, such as those capable of producing bas-relief effects.
  • Customization Options: Opt for AI tools that offer extensive customization options, allowing you to adjust features like texture, depth, and lighting to create a more realistic 3D effect.
  • Compatibility: Ensure the AI-generated images are compatible with the software or platform you plan to use for converting them into depth maps.

2. Preparing AI-Generated Artwork

  • Image Resolution: High-resolution images are essential for capturing fine details in the engraving process. Aim for the highest possible resolution within the limits of your software and hardware.
  • Contrast and Brightness: Adjust the contrast and brightness of your images to highlight the details. Depth map conversion tools often rely on these elements to differentiate between various levels of depth.
  • Simplification: Simplify complex images if necessary. Too many details can result in a cluttered depth map, making it difficult for the laser to accurately reproduce the design.

3. Converting Images into Depth Maps

  • Software Selection: Use reliable software or platforms, such as Google Colab with projects like Tiling Zod Dev, that can efficiently convert images into depth maps. These tools should offer options for both low and high-resolution outputs.
  • Depth Map Resolution: Choose the appropriate resolution for your depth map based on the material you’re engraving and the complexity of your design. Higher resolution maps are better for detailed and intricate designs.
  • Understanding Depth Levels: Familiarize yourself with how your chosen software interprets different shades of gray to represent depth. This understanding will help you adjust your original image for optimal depth map creation.

4. Material and Laser Considerations

  • Material Selection: The choice of material (e.g., wood, metal) significantly impacts the engraving process. Understand how different materials react to laser engraving to select the most suitable one for your project.
  • Laser Type: CO2 lasers are generally used for softer materials like wood, while fiber lasers are better for metals. Selecting the right laser type is crucial for achieving the desired engraving effect.
  • Laser Settings: Adjust the laser settings based on the depth map guidelines. Factors like power, speed, and frequency need to be tailored to both the material and the specific details of the depth map.

5. Testing and Adjustments

  • Pilot Runs: Before finalizing the engraving on your chosen material, perform tests on similar, less valuable materials. This allows you to adjust the depth map and laser settings as needed.
  • Iterative Adjustments: Use the results of your tests to make necessary adjustments to the image, depth map, or laser settings. It might take several iterations to achieve the desired outcome.

The integration of AI-generated imagery into 3D laser engraving represents a significant advancement in how we create and appreciate detailed designs. By carefully selecting the appropriate AI tools and understanding the nuances of laser-material interactions, designers and manufacturers can produce works that truly enhance the visual appeal of any material. This process is not just about the technology; it’s about marrying art with innovation to push the boundaries of what’s possible in design and manufacturing.

Image Source :  Justin Laser

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