Technical Documentation Page - Build a Technical Documentation Page

**Tell us what’s happening: The challenge specifys that 1. The .main-section elements should contain at least five code elements total (not each) **

yet it also says Failed:You should have at least five code elements that are descendants of .main-section elements.

and the

    all count as elements i’m not sure where to even fix this

    Your code so far

    WARNING

    The challenge seed code and/or your solution exceeded the maximum length we can port over from the challenge.

    You will need to take an additional step here so the code you wrote presents in an easy to read format.

    Please copy/paste all the editor code showing in the challenge from where you just linked.

    <html lang='en'>
      <head>
    <meta charset="utf-8" />
        <meta name="viewport" content="width=device-width, initial-scale=1.0" />
        <title>AI app</title>
        <link href="styles.css" rel="stylesheet"/>
      </head>
      <header class='title'>AI Documentation</header>
      <nav id='navbar'>
        <header class='AI_Doc'>
          AI documentation
          </header>
          <ul class='list'>
            <li><a href='#Machine_Learning' class='nav-link'>Machine Learning</a></li>
            <li><a href='#Natural_Language_Processing_(NLP)' class='nav-link'>Natural Language Processing (NLP)</a></li>
            <li><a href='#Neural_Networks' class='nav-link'>Neural Networks</a></li>
            <li><a href='#Ethical_AI' class='nav-link'>Ethical AI</a></li>
            <li><a href='#Robotics' class='nav-link'>Robotics</a></li>
            <li><a href='#AI_in_Healthcare' class='nav-link'>AI in Healthcare</a></li>
            <li><a href='#Autonomous_Vehicles' class='nav-link'>Autonomous Vehicles</a></li>
            </ul>
      </nav>
      <body>
      <main id='main-doc'>
        <section class='main-section' id='Machine_Learning'>
          <header>Machine Learning</header>
          <p>Machine learning is a subset of artificial intelligence that empowers computers to learn from data without explicit programming. It involves the development of algorithms that can recognize patterns, make predictions, and improve their performance over time. From recommendation systems that suggest products based on your preferences to fraud detection algorithms that identify unusual patterns in financial transactions, machine learning plays a pivotal role in modern technology.</p>
          <ul>
            <li>Machine learning enables computers to learn patterns from data and make predictions without explicit programming. It underlies many AI applications, from recommendation systems suggesting content to self-driving cars making decisions based on real-time sensor data.
              </li>
              </ul>
        </section>
        <section class='main-section' id='Natural_Language_Processing_(NLP)'>
          <header>Natural Language Processing (NLP)</header>
          <p>Natural Language Processing is a field of AI that focuses on enabling computers to understand, interpret, and generate human language. Through the use of advanced algorithms, computers can process and analyze text and speech, facilitating applications such as language translation, sentiment analysis, and virtual assistants like Siri and Alexa.</p>
                <ul>
            <li>NLP focuses on giving computers the ability to understand, interpret, and generate human language. This technology powers virtual assistants like Siri and chatbots, making interactions between humans and machines more intuitive and natural.
              </li>
              </ul>
        </section>
        <section class='main-section' id='Neural_Networks'>
          <header>Neural Networks</header>
          <p>Neural networks are computational models inspired by the structure and functioning of the human brain. These interconnected networks of artificial "neurons" are used in deep learning, a subset of machine learning, to solve complex tasks such as image and speech recognition. By iteratively adjusting the weights of connections, neural networks can learn to recognize intricate patterns and relationships in data.</p>
                <ul>
            <li>Neural networks are computational models inspired by the human brain's structure. They excel at tasks like image and speech recognition. Deep learning, a subset of neural networks, has revolutionized AI by achieving remarkable performance in complex tasks.
              </li>
              </ul>
        </section>
        <section class='main-section' id='Ethical_AI'>
          <header>Ethical AI</header>
          <p>Ethical AI is a crucial consideration as artificial intelligence becomes increasingly integrated into our lives. This topic examines the ethical implications of AI technologies, addressing concerns like algorithmic bias, privacy infringement, and the potential for job displacement due to automation. Ensuring that AI systems are fair, transparent, and beneficial to society is a central aspect of ethical AI development.</p>
                <ul>
            <li>Ethical AI addresses the responsible development and deployment of AI technologies. It involves preventing algorithmic bias, ensuring data privacy, and considering the societal impacts of AI, guiding the creation of AI systems that benefit humanity.
              </li>
              </ul>
        </section>
        <section class='main-section' id='Robotics'>
          <header>Robotics</header>
          <p>Robotics combines AI with physical machines to create autonomous systems capable of performing tasks in the real world. From manufacturing robots that assemble products with precision to drones that navigate complex environments, robotics leverages AI to perceive and interact with the surroundings, making it possible for machines to undertake a wide range of functions.</p>
                <ul>
            <li>Robotics combines AI and physical machines to create autonomous systems that interact with the physical world. This includes everything from manufacturing robots that streamline production to drones that map environments and assist in disaster relief efforts.
              </li>
              </ul>
        </section>
        <section class='main-section' id='AI_in_Healthcare'>
          <header>AI in Healthcare</header>
          <p>AI's integration into healthcare is transforming the medical field. Machine learning algorithms can analyze vast amounts of medical data to aid in diagnosing diseases, predicting patient outcomes, and personalizing treatment plans. Moreover, AI-powered tools facilitate drug discovery by identifying potential compounds for various diseases, expediting the research process and enhancing patient care.</p>
                        <div>mgokf
          </div>
        </section>
        <section class='main-section' id='Autonomous_Vehicles'>
          <header>Autonomous Vehicles</header>
          <p>Autonomous vehicles, such as self-driving cars, rely on AI to navigate and operate without human intervention. These vehicles utilize sensors, cameras, and complex algorithms to perceive their surroundings and make real-time decisions. By enhancing road safety, reducing traffic congestion, and providing mobility solutions for individuals with limited mobility, autonomous vehicles are reshaping the future of transportation.</p>
          <p></p>
          <p></p>
          <p></p>
        </section>
      </main>
      </body>
      </html>
    
    <html lang='en'>
      <head>
    <meta charset="utf-8" />
        <meta name="viewport" content="width=device-width, initial-scale=1.0" />
        <title>AI app</title>
        <link href="styles.css" rel="stylesheet"/>
      </head>
      <header class='title'>AI Documentation</header>
      <nav id='navbar'>
        <header class='AI_Doc'>
          AI documentation
          </header>
          <ul class='list'>
            <li><a href='#Machine_Learning' class='nav-link'>Machine Learning</a></li>
            <li><a href='#Natural_Language_Processing_(NLP)' class='nav-link'>Natural Language Processing (NLP)</a></li>
            <li><a href='#Neural_Networks' class='nav-link'>Neural Networks</a></li>
            <li><a href='#Ethical_AI' class='nav-link'>Ethical AI</a></li>
            <li><a href='#Robotics' class='nav-link'>Robotics</a></li>
            <li><a href='#AI_in_Healthcare' class='nav-link'>AI in Healthcare</a></li>
            <li><a href='#Autonomous_Vehicles' class='nav-link'>Autonomous Vehicles</a></li>
            </ul>
      </nav>
      <body>
      <main id='main-doc'>
        <section class='main-section' id='Machine_Learning'>
          <header>Machine Learning</header>
          <p>Machine learning is a subset of artificial intelligence that empowers computers to learn from data without explicit programming. It involves the development of algorithms that can recognize patterns, make predictions, and improve their performance over time. From recommendation systems that suggest products based on your preferences to fraud detection algorithms that identify unusual patterns in financial transactions, machine learning plays a pivotal role in modern technology.</p>
          <ul>
            <li>Machine learning enables computers to learn patterns from data and make predictions without explicit programming. It underlies many AI applications, from recommendation systems suggesting content to self-driving cars making decisions based on real-time sensor data.
              </li>
              </ul>
        </section>
        <section class='main-section' id='Natural_Language_Processing_(NLP)'>
          <header>Natural Language Processing (NLP)</header>
          <p>Natural Language Processing is a field of AI that focuses on enabling computers to understand, interpret, and generate human language. Through the use of advanced algorithms, computers can process and analyze text and speech, facilitating applications such as language translation, sentiment analysis, and virtual assistants like Siri and Alexa.</p>
                <ul>
            <li>NLP focuses on giving computers the ability to understand, interpret, and generate human language. This technology powers virtual assistants like Siri and chatbots, making interactions between humans and machines more intuitive and natural.
              </li>
              </ul>
        </section>
        <section class='main-section' id='Neural_Networks'>
          <header>Neural Networks</header>
          <p>Neural networks are computational models inspired by the structure and functioning of the human brain. These interconnected networks of artificial "neurons" are used in deep learning, a subset of machine learning, to solve complex tasks such as image and speech recognition. By iteratively adjusting the weights of connections, neural networks can learn to recognize intricate patterns and relationships in data.</p>
                <ul>
            <li>Neural networks are computational models inspired by the human brain's structure. They excel at tasks like image and speech recognition. Deep learning, a subset of neural networks, has revolutionized AI by achieving remarkable performance in complex tasks.
              </li>
              </ul>
        </section>
        <section class='main-section' id='Ethical_AI'>
          <header>Ethical AI</header>
          <p>Ethical AI is a crucial consideration as artificial intelligence becomes increasingly integrated into our lives. This topic examines the ethical implications of AI technologies, addressing concerns like algorithmic bias, privacy infringement, and the potential for job displacement due to automation. Ensuring that AI systems are fair, transparent, and beneficial to society is a central aspect of ethical AI development.</p>
                <ul>
            <li>Ethical AI addresses the responsible development and deployment of AI technologies. It involves preventing algorithmic bias, ensuring data privacy, and considering the societal impacts of AI, guiding the creation of AI systems that benefit humanity.
              </li>
              </ul>
        </section>
        <section class='main-section' id='Robotics'>
          <header>Robotics</header>
          <p>Robotics combines AI with physical machines to create autonomous systems capable of performing tasks in the real world. From manufacturing robots that assemble products with precision to drones that navigate complex environments, robotics leverages AI to perceive and interact with the surroundings, making it possible for machines to undertake a wide range of functions.</p>
                <ul>
            <li>Robotics combines AI and physical machines to create autonomous systems that interact with the physical world. This includes everything from manufacturing robots that streamline production to drones that map environments and assist in disaster relief efforts.
              </li>
              </ul>
        </section>
        <section class='main-section' id='AI_in_Healthcare'>
          <header>AI in Healthcare</header>
          <p>AI's integration into healthcare is transforming the medical field. Machine learning algorithms can analyze vast amounts of medical data to aid in diagnosing diseases, predicting patient outcomes, and personalizing treatment plans. Moreover, AI-powered tools facilitate drug discovery by identifying potential compounds for various diseases, expediting the research process and enhancing patient care.</p>
                        <div>mgokf
          </div>
        </section>
        <section class='main-section' id='Autonomous_Vehicles'>
          <header>Autonomous Vehicles</header>
          <p>Autonomous vehicles, such as self-driving cars, rely on AI to navigate and operate without human intervention. These vehicles utilize sensors, cameras, and complex algorithms to perceive their surroundings and make real-time decisions. By enhancing road safety, reducing traffic congestion, and providing mobility solutions for individuals with limited mobility, autonomous vehicles are reshaping the future of transportation.</p>
          <p></p>
          <p></p>
          <p></p>
        </section>
      </main>
      </body>
      </html>
    

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    Challenge: Technical Documentation Page - Build a Technical Documentation Page

    Link to the challenge:

Hello! I think you are missing literal code elements. For example they look like this in html

<code>This is a code element</code>

The format should look different, like a block quote with a darker background and the code syntax properly written

here is a visual example after rendering
(bottom of the screenshot)
Screenshot 2023-08-24 at 1.36.00 PM

You are the best person in the whole-wide world thank you :heart_hands:, I was staring at that for 2 hrs and fixed in 1 minute

2 Likes

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