[DEV TESTING] Generative AI

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We looked at a couple different areas of AI, but the one that's gotten the most attention,

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and frankly is the most mainstream, is generative AI.

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And generative AI comes in many forms.

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Some applications generate written text, and you've probably used some of these tools,

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like Chats GPT, Google's Gemini, or Anthropic Cloud, while others are great for producing

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new images, like Midjourney, Dolly, and Stable Diffusion.

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Then there's others that are great for generating programming code, like GitHub Copilot.

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Then there's applications that will generate video or music tracks.

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Generative AI covers a broad spectrum of software tools and platforms, and the list seems to

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grow daily.

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Generative AI capabilities are appearing in tools that you probably already work with,

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products from Microsoft and Adobe, services that you might be familiar with, like Grammarly

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or even ContentStack.

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The key component of generative AI lies in the interaction.

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You input commands, typically through a brief prompt detailing your requirements, and the

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AI creates entirely new content, hence the word generative, which reflects the AI's ability

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to not merely retrieve existing data, but to actually create novel outcomes.

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Chatbots leverage something called Large Language Models, or LLMs, similar to the models we

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talked about earlier.

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They're trained on vast amounts of text data, and they're capable of generating human-like

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responses by leveraging deep learning and transformer architectures.

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Think of a transformer architecture as a conductor of an orchestra.

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The transformer has something called a self-attention mechanism, which allows it to focus on different

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sections of the orchestra, or input data, simultaneously, rather than one at a time.

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This enables the conductor to understand how each section contributes to the overall performance,

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adjusting focus dynamically to highlight or blend certain musical elements.

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In transformers, this translates to processing input data in parallel, allowing the model

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to assess the relevance of different data elements and grasp complex relationships.

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Additionally, there is an encoder and a decoder within the architecture.

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It functions in a similar way as a translator.

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The encoder absorbs and comprehensively represents the original language, while the decoder interprets

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and recreates this into new language, whether it be for a translation, a summarization,

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or generating text.

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This has proven exceptionally effective for natural language processing, serving as the

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foundational structure for most contemporary large language models.

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So you might ask, do AI tools that create images, music, or video also use large language

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models?

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Kind of, but they're referred to as foundation models, as they're multimodal, not just a

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tool for working with language.

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The underlining mechanism of any generative AI tool remains fairly consistent across different

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applications, whether it's creating text, images, code, whatever the case may be.

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A quick sidebar.

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An important concept to understand when working with any of these generative AI tools is this

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idea of a knowledge cutoff date.

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Because training these models is so computationally expensive, and it requires an enormous amount

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of data, the vendors often set a cutoff date, which is to say they'll stop using data up

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until a certain point in time, typically as close as they can get till today.

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But it's usually months earlier.

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So if you were to ask ChatGPT to summarize an event that occurred in the past few months,

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regardless of how significant the event, it might not be able to do it.

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To know what the date is of a knowledge cutoff, just ask the chatbot.

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Now that we have a general understanding of what's happening in the background with these

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AI tools, and we understand some foundational concepts like machine learning, deep learning,

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computation models, and LLMs, we can begin to explore how we can get the most out of

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these tools, and it often starts with a prompt.



We looked at a couple different areas of AI, but the one that's gotten the most attention, and frankly is the most mainstream, is generative AI. And generative AI comes in many forms. Some applications generate written text, and you've probably used some of these tools, like Chats GPT, Google's Gemini, or Anthropic Cloud, while others are great for producing new images, like Midjourney, Dolly, and Stable Diffusion. Then there's others that are great for generating programming code, like GitHub Copilot. Then there's applications that will generate video or music tracks. Generative AI covers a broad spectrum of software tools and platforms, and the list seems to grow daily. Generative AI capabilities are appearing in tools that you probably already work with, products from Microsoft and Adobe, services that you might be familiar with, like Grammarly or even ContentStack. The key component of generative AI lies in the interaction. You input commands, typically through a brief prompt detailing your requirements, and the AI creates entirely new content, hence the word generative, which reflects the AI's ability to not merely retrieve existing data, but to actually create novel outcomes. Chatbots leverage something called Large Language Models, or LLMs, similar to the models we talked about earlier. They're trained on vast amounts of text data, and they're capable of generating human-like responses by leveraging deep learning and transformer architectures. Think of a transformer architecture as a conductor of an orchestra. The transformer has something called a self-attention mechanism, which allows it to focus on different sections of the orchestra, or input data, simultaneously, rather than one at a time. This enables the conductor to understand how each section contributes to the overall performance, adjusting focus dynamically to highlight or blend certain musical elements. In transformers, this translates to processing input data in parallel, allowing the model to assess the relevance of different data elements and grasp complex relationships. Additionally, there is an encoder and a decoder within the architecture. It functions in a similar way as a translator. The encoder absorbs and comprehensively represents the original language, while the decoder interprets and recreates this into new language, whether it be for a translation, a summarization, or generating text. This has proven exceptionally effective for natural language processing, serving as the foundational structure for most contemporary large language models. So you might ask, do AI tools that create images, music, or video also use large language models? Kind of, but they're referred to as foundation models, as they're multimodal, not just a tool for working with language. The underlining mechanism of any generative AI tool remains fairly consistent across different applications, whether it's creating text, images, code, whatever the case may be. A quick sidebar. An important concept to understand when working with any of these generative AI tools is this idea of a knowledge cutoff date. Because training these models is so computationally expensive, and it requires an enormous amount of data, the vendors often set a cutoff date, which is to say they'll stop using data up until a certain point in time, typically as close as they can get till today. But it's usually months earlier. So if you were to ask ChatGPT to summarize an event that occurred in the past few months, regardless of how significant the event, it might not be able to do it. To know what the date is of a knowledge cutoff, just ask the chatbot. Now that we have a general understanding of what's happening in the background with these AI tools, and we understand some foundational concepts like machine learning, deep learning, computation models, and LLMs, we can begin to explore how we can get the most out of these tools, and it often starts with a prompt.

Generative Ai

image_1.svg

Test Lesson

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If you've been in the world of digital design or development, you've undoubtedly have

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come across some reference to taxonomies.

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And if you haven't, that's okay, but taxonomies are critical to allowing users to effectively

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navigate and find content.

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And taxonomies aren't anything new.

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I have a few books here that are from the 50s, and even these weren't cutting edge

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at the time.

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A classic example is a biological classification system.

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In biology, organisms are grouped based on shared characteristics.

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This starts broadly at kingdoms like animals or plants, and then narrows down to species

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like humans, which are Homo sapiens.

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This hierarchical structure helps scientists make sense of the vast diversity of life and

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understand the relationships between different organisms.

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Let's look at maybe a more practical example.

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Think about a grocery store.

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Here, products are organized into categories like produce, dairy, bakery, and so on.

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Within each category, there are subcategories like fresh fruits, fresh vegetables, and dried

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fruits.

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Apples and oranges would fall under the fresh fruits subcategory of the produce category.

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This system helps customers find what they need quickly and efficiently.

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Apples and oranges are clearly in the fresh fruits section of the produce aisle.

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As developers and designers, we need to create digital spaces that are navigable and intuitive,

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and that's where taxonomies come in.

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A well-structured taxonomy organizes content in a logical hierarchy, much like our grocery

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store example.

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It helps users find information quickly and enhances the overall user experience.

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A good taxonomy for a digital experience can be invaluable.

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It improves usability by grouping related content, enhances SEO by clarifying structure

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for things like search engines, and even aids in content management on the back end.

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Essentially, it's about creating a map that guides the users to the information that they're

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looking for with the least amount of friction.

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So what does a good taxonomy look like?

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It looks like a hierarchical tree-like structure, but be aware it takes expertise.

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While a taxonomy can be used in more simplistic circumstances, a system that is too granular

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will be overly complicated.

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You want a system that is simple enough to easily navigate, granular enough to make meaningful

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distinctions, and flexible enough to accommodate future changes in the items needing to be

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classified.

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This requires ongoing maintenance of the system.

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So how do taxonomies work in ContentStack?

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Here we're working with Compass Travel, a site for a travel agency.

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To create a new taxonomy, choose Settings.

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Down towards the bottom, choose Taxonomy.

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You can either import a CSV or JSON file of an existing taxonomy, or create a new one

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by clicking the New Taxonomy button.

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Create a name of the taxonomy and enter a description if you'd like.

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I'll name mine Region as it will represent all the regions travelers may want to visit.

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Start adding terms by clicking the New Term button.

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I'll enter EMEA to represent Europe, the Middle East, and Africa.

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I'll add a child term under EMEA by clicking the Add Child Term button.

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The term name will be Africa, and I'll continue adding terms for Europe and the Middle East.

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Next, I'll add a child term under Africa by clicking the Same Add Term button.

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I'll add South Africa.

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Notice you can click the information icon in the top right to get details about that

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term, including when it was created, modified, and any entries where it was referenced.

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Next, we want to associate this taxonomy to a content type.

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To do that, we'll navigate to the content models so we can choose the content type.

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In this case, I'll select Article.

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In the Content Type Builder, scroll to the location where you'd like the taxonomy to

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appear and click the plus sign to add a new element.

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Choose Taxonomy.

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Then click Add Taxonomy.

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In the menu, choose your taxonomy, in this case, its region, and then click Apply.

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If you want to apply another taxonomy, click the Add Taxonomy button again.

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Why would you want more than one taxonomy?

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Well, in this example, we have a taxonomy of regions, which contains all the different

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regions in the world.

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You may want another taxonomy to classify all the different tourist attractions, like

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museums, monuments, restaurants, and other local attractions.

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When you're finished, click Save and Close.

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Let's navigate to the entries to add a new one.

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Click the New Entry button and choose the content type you added the taxonomy to, which

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in this case is Article.

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Obviously, you'd spend time to complete this entry, but importantly, scroll to the

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location where you added the taxonomy, and sure enough, you can open your taxonomy to

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select a term.

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To see taxonomy on the front end, I'm going to use Live Preview for this article about

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Buenos Aires.

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First, I'll scroll down to the Taxonomies section.

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Here, you'll notice I'm using terms from the two taxonomies that I created, the region

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taxonomy that we created together and a topics taxonomy I created on my own.

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Now, I'll click the Live Preview button, and once it loads, I can scroll down the article

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to see the terms associated with the article.

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If I decide to add the term Must See Spots from the topics taxonomy, you'll see the

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page automatically update.

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To sum up, whether it's classifying life forms, organizing grocery aisles, or structuring

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content on a website, taxonomies help us make sense of complex sets of information.

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As web designers and developers, it's crucial to understand how to work with taxonomies

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00:06:25.580 --> 00:06:31.340
to create easy-to-use, efficient, and effective web experiences.

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00:06:31.340 --> 00:06:38.220
Remember, taxonomies are the backbone of any organized system, digital or otherwise.



If you've been in the world of digital design or development, you've undoubtedly have come across some reference to taxonomies. And if you haven't, that's okay, but taxonomies are critical to allowing users to effectively navigate and find content. And taxonomies aren't anything new. I have a few books here that are from the 50s, and even these weren't cutting edge at the time. A classic example is a biological classification system. In biology, organisms are grouped based on shared characteristics. This starts broadly at kingdoms like animals or plants, and then narrows down to species like humans, which are Homo sapiens. This hierarchical structure helps scientists make sense of the vast diversity of life and understand the relationships between different organisms. Let's look at maybe a more practical example. Think about a grocery store. Here, products are organized into categories like produce, dairy, bakery, and so on. Within each category, there are subcategories like fresh fruits, fresh vegetables, and dried fruits. Apples and oranges would fall under the fresh fruits subcategory of the produce category. This system helps customers find what they need quickly and efficiently. Apples and oranges are clearly in the fresh fruits section of the produce aisle. As developers and designers, we need to create digital spaces that are navigable and intuitive, and that's where taxonomies come in. A well-structured taxonomy organizes content in a logical hierarchy, much like our grocery store example. It helps users find information quickly and enhances the overall user experience. A good taxonomy for a digital experience can be invaluable. It improves usability by grouping related content, enhances SEO by clarifying structure for things like search engines, and even aids in content management on the back end. Essentially, it's about creating a map that guides the users to the information that they're looking for with the least amount of friction. So what does a good taxonomy look like? It looks like a hierarchical tree-like structure, but be aware it takes expertise. While a taxonomy can be used in more simplistic circumstances, a system that is too granular will be overly complicated. You want a system that is simple enough to easily navigate, granular enough to make meaningful distinctions, and flexible enough to accommodate future changes in the items needing to be classified. This requires ongoing maintenance of the system. So how do taxonomies work in ContentStack? Here we're working with Compass Travel, a site for a travel agency. To create a new taxonomy, choose Settings. Down towards the bottom, choose Taxonomy. You can either import a CSV or JSON file of an existing taxonomy, or create a new one by clicking the New Taxonomy button. Create a name of the taxonomy and enter a description if you'd like. I'll name mine Region as it will represent all the regions travelers may want to visit. Start adding terms by clicking the New Term button. I'll enter EMEA to represent Europe, the Middle East, and Africa. I'll add a child term under EMEA by clicking the Add Child Term button. The term name will be Africa, and I'll continue adding terms for Europe and the Middle East. Next, I'll add a child term under Africa by clicking the Same Add Term button. I'll add South Africa. Notice you can click the information icon in the top right to get details about that term, including when it was created, modified, and any entries where it was referenced. Next, we want to associate this taxonomy to a content type. To do that, we'll navigate to the content models so we can choose the content type. In this case, I'll select Article. In the Content Type Builder, scroll to the location where you'd like the taxonomy to appear and click the plus sign to add a new element. Choose Taxonomy. Then click Add Taxonomy. In the menu, choose your taxonomy, in this case, its region, and then click Apply. If you want to apply another taxonomy, click the Add Taxonomy button again. Why would you want more than one taxonomy? Well, in this example, we have a taxonomy of regions, which contains all the different regions in the world. You may want another taxonomy to classify all the different tourist attractions, like museums, monuments, restaurants, and other local attractions. When you're finished, click Save and Close. Let's navigate to the entries to add a new one. Click the New Entry button and choose the content type you added the taxonomy to, which in this case is Article. Obviously, you'd spend time to complete this entry, but importantly, scroll to the location where you added the taxonomy, and sure enough, you can open your taxonomy to select a term. To see taxonomy on the front end, I'm going to use Live Preview for this article about Buenos Aires. First, I'll scroll down to the Taxonomies section. Here, you'll notice I'm using terms from the two taxonomies that I created, the region taxonomy that we created together and a topics taxonomy I created on my own. Now, I'll click the Live Preview button, and once it loads, I can scroll down the article to see the terms associated with the article. If I decide to add the term Must See Spots from the topics taxonomy, you'll see the page automatically update. To sum up, whether it's classifying life forms, organizing grocery aisles, or structuring content on a website, taxonomies help us make sense of complex sets of information. As web designers and developers, it's crucial to understand how to work with taxonomies to create easy-to-use, efficient, and effective web experiences. Remember, taxonomies are the backbone of any organized system, digital or otherwise.

Understanding Taxonomy

Copy of Test Lesson

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AI Assistant can simplify and improve the creation of your content by integrating popular

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large language models directly within the Content Stack platform.

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This means you don't have to juggle between our platform and separate applications to

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leverage advanced AI writing capabilities.

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It's like having a clever coworker at your disposal eager to help you elevate your writing

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efficiency and quality.

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This seamless integration ensures your website has compelling content and conveys your message

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distinctly to your audience, all the while keeping your workflow streamlined and efficient.

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To get started, we need to install AI Assistant through Marketplace.

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To do this, make sure you're at the Organization level within Content Stack.

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If you're not sure, just click the Content Stack icon in the top left-hand corner.

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Then, once you're at the Organization level, on the left-hand side, you'll notice there's

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a Marketplace icon.

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Once you click that, Marketplace will load.

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And you'll notice there's a Collections section, and here you can choose Apps.

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Once you select Apps, apps on the right-hand side will load in tiles, and AI Assistant

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should appear in the top row, but if it doesn't, feel free to perform a search with the Search

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text field.

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When you hover over AI Assistant, you'll notice you get an Install button.

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Go ahead and click it to start the installation process.

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The first thing that you have to do is you have to select the stack in which you want

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to install AI Assistant.

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In this case, I want to choose Compass Starter.

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I'll go ahead and accept the terms and conditions, and then I'll click Install.

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Once you click Install, the Configuration screen will load.

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You have two options for the platform configuration.

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You can choose Managed by Content Stack, or if you want to use your own credentials to

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use your own provider, you can select Custom Credentials and provide that information,

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like your API key, what provider you're using, and the API model.

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For this example, we're going to choose Managed by Content Stack.

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A quick sidebar, when using the Content Stack-powered API key, it's important to know that we maintain

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strict privacy standards that follow GDPR guidelines, so you can use AI Assistant with

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peace of mind.

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Now let's go ahead and click Save and Proceed.

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This will bring us to the Advanced Configuration section.

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For our purposes in this video, we don't need to configure anything further, so we'll

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just click Next.

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When you do that, you should get confirmation that the configuration was successful.

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Now all you have to do is move down to the bottom right and click the Save button.

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Now the configuration has been updated and AI Assistant has been installed on your stack.

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To confirm that, click Open Stack, which will in fact open the stack that you installed

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AI Assistant to.

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So now what we want to do is move over to the Entries section.

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On the left-hand side, you can click the Entries button.

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Now I have an article that I've been working with called Top Travel Destinations for 2024.

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If I select that to enter the article, I have a couple different options here in terms of

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how I can use AI Assistant to improve this article.

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First of all, I may want to update the title.

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I may want to update it for SEO.

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As you hover over the title section, you'll notice there's an AI Assistant icon.

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Go ahead and click it, and when you do, AI Assistant will load on the right-hand side.

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The section we want to take a look at here is the Replace Field Content, and you'll notice

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we have a couple different commands.

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The command I want to look at is Optimize Text for SEO.

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When you click that, AI Assistant will generate content that is now a more optimized version

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of the title.

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You have a couple options.

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You can try again if you don't like the results.

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You can cancel out of it, or you can accept it.

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For our purposes, I'm going to go ahead and click Accept.

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So that's how you can modify existing content using AI Assistant, but you can also generate

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new content using AI Assistant.

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If I scroll down, you'll notice that there's a summary, which is empty.

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If I want to create a summary, I can do that, but specifically, I want to create a summary

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based upon the content I have in this text field.

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So again, in the Summary section, as I hover over it, I see the AI Assistant icon.

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I can go ahead and click it, and in this case, what I want to do is scroll down towards the

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bottom, and what I want to select in this area where we're going to generate based upon

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another field is a summary.

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So I'll click Summary, and then that panel expands to show me the different fields that

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I can use as the source for this summary.

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And in this case, you'll notice I have a Content text field, so I'm going to select Content.

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When I do, AI Assistant will generate the content.

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You can either accept it, you can try again to have AI Assistant regenerate it, and once

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you're happy with the results, you can click Accept.

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Finally, if we scroll down further, you'll notice that there's a section for some tags.

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I'll go ahead and hover over the Tags section to see the AI Assistant icon.

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When I click it, again, what I want to do is generate content, in this case, SEO tags.

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I want to generate it based upon that same Content text field.

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So when I select that option, AI Assistant will generate tags based upon the contents

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found within that text field.

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Again, I'll go ahead and click Accept.

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So you'll notice that there's a lot of capability within this AI Assistant menu.

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Again, if I scroll up towards the top, if I click the AI Assistant button for Summary,

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I can change this text further by optimizing it for SEO, which we looked at earlier.

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We can change the tone to be more persuasive, straightforward, friendly, or professional.

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We can also change the length to make it longer or shorter.

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And in this case, you also have the option to translate to the current locale language.

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Remember, AI Assistant doesn't just work for creating new content, but you can also

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modify existing content the same way.

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Also know, once you install AI Assistant, it becomes available throughout the entire stack.

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AI Assistant in Content Stack is a powerful tool that enhances your creation process.

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The world of content creation is ever-evolving, and AI and other technologies are optimizing

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the editing experience.

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Tools like AI Assistant allow you to stay at the forefront, captivating your audience

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with every word.

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So go ahead, explore all the possibilities, and let AI Assistant transform the way you

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work and create content in Content Stack.



AI Assistant can simplify and improve the creation of your content by integrating popular large language models directly within the Content Stack platform. This means you don't have to juggle between our platform and separate applications to leverage advanced AI writing capabilities. It's like having a clever coworker at your disposal eager to help you elevate your writing efficiency and quality. This seamless integration ensures your website has compelling content and conveys your message distinctly to your audience, all the while keeping your workflow streamlined and efficient. To get started, we need to install AI Assistant through Marketplace. To do this, make sure you're at the Organization level within Content Stack. If you're not sure, just click the Content Stack icon in the top left-hand corner. Then, once you're at the Organization level, on the left-hand side, you'll notice there's a Marketplace icon. Once you click that, Marketplace will load. And you'll notice there's a Collections section, and here you can choose Apps. Once you select Apps, apps on the right-hand side will load in tiles, and AI Assistant should appear in the top row, but if it doesn't, feel free to perform a search with the Search text field. When you hover over AI Assistant, you'll notice you get an Install button. Go ahead and click it to start the installation process. The first thing that you have to do is you have to select the stack in which you want to install AI Assistant. In this case, I want to choose Compass Starter. I'll go ahead and accept the terms and conditions, and then I'll click Install. Once you click Install, the Configuration screen will load. You have two options for the platform configuration. You can choose Managed by Content Stack, or if you want to use your own credentials to use your own provider, you can select Custom Credentials and provide that information, like your API key, what provider you're using, and the API model. For this example, we're going to choose Managed by Content Stack. A quick sidebar, when using the Content Stack-powered API key, it's important to know that we maintain strict privacy standards that follow GDPR guidelines, so you can use AI Assistant with peace of mind. Now let's go ahead and click Save and Proceed. This will bring us to the Advanced Configuration section. For our purposes in this video, we don't need to configure anything further, so we'll just click Next. When you do that, you should get confirmation that the configuration was successful. Now all you have to do is move down to the bottom right and click the Save button. Now the configuration has been updated and AI Assistant has been installed on your stack. To confirm that, click Open Stack, which will in fact open the stack that you installed AI Assistant to. So now what we want to do is move over to the Entries section. On the left-hand side, you can click the Entries button. Now I have an article that I've been working with called Top Travel Destinations for 2024. If I select that to enter the article, I have a couple different options here in terms of how I can use AI Assistant to improve this article. First of all, I may want to update the title. I may want to update it for SEO. As you hover over the title section, you'll notice there's an AI Assistant icon. Go ahead and click it, and when you do, AI Assistant will load on the right-hand side. The section we want to take a look at here is the Replace Field Content, and you'll notice we have a couple different commands. The command I want to look at is Optimize Text for SEO. When you click that, AI Assistant will generate content that is now a more optimized version of the title. You have a couple options. You can try again if you don't like the results. You can cancel out of it, or you can accept it. For our purposes, I'm going to go ahead and click Accept. So that's how you can modify existing content using AI Assistant, but you can also generate new content using AI Assistant. If I scroll down, you'll notice that there's a summary, which is empty. If I want to create a summary, I can do that, but specifically, I want to create a summary based upon the content I have in this text field. So again, in the Summary section, as I hover over it, I see the AI Assistant icon. I can go ahead and click it, and in this case, what I want to do is scroll down towards the bottom, and what I want to select in this area where we're going to generate based upon another field is a summary. So I'll click Summary, and then that panel expands to show me the different fields that I can use as the source for this summary. And in this case, you'll notice I have a Content text field, so I'm going to select Content. When I do, AI Assistant will generate the content. You can either accept it, you can try again to have AI Assistant regenerate it, and once you're happy with the results, you can click Accept. Finally, if we scroll down further, you'll notice that there's a section for some tags. I'll go ahead and hover over the Tags section to see the AI Assistant icon. When I click it, again, what I want to do is generate content, in this case, SEO tags. I want to generate it based upon that same Content text field. So when I select that option, AI Assistant will generate tags based upon the contents found within that text field. Again, I'll go ahead and click Accept. So you'll notice that there's a lot of capability within this AI Assistant menu. Again, if I scroll up towards the top, if I click the AI Assistant button for Summary, I can change this text further by optimizing it for SEO, which we looked at earlier. We can change the tone to be more persuasive, straightforward, friendly, or professional. We can also change the length to make it longer or shorter. And in this case, you also have the option to translate to the current locale language. Remember, AI Assistant doesn't just work for creating new content, but you can also modify existing content the same way. Also know, once you install AI Assistant, it becomes available throughout the entire stack. AI Assistant in Content Stack is a powerful tool that enhances your creation process. The world of content creation is ever-evolving, and AI and other technologies are optimizing the editing experience. Tools like AI Assistant allow you to stay at the forefront, captivating your audience with every word. So go ahead, explore all the possibilities, and let AI Assistant transform the way you work and create content in Content Stack.

Ai-assistant(rough-cut)

This course is intended to outline the Contentstack features and techniques for using the Taxonomy features with&nbsp;your content, understand the APIs, and how to leverage Taxonomy within your implementation.&nbsp; Completion of this course earns a 'badge' for this topic.!Required for this course:<ol><li>Account in Contentstack with access to a Stack as an Administrator or Developer. Create a training Stack&nbsp;<a href="https://www.contentstack.com/academy/training-instance" target="_blank">here</a>. Training stacks are available for 90 days. Alternatively, you can bootstrap a&nbsp;<a href="https://www.contentstack.com/docs/developers/cli/bootstrap-starter-apps">Starter App via the CLI</a>&nbsp;or from the&nbsp;<a href="https://app.contentstack.com/#!/marketplace/starters">Marketplace</a>.&nbsp;</li><li>Permissions to create a new Taxonomy and edit Content Types in a Stack.&nbsp;</li></ol>

[DEV TESTING] Taxonomy Foundations

Skills Covered