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Glossary topic

Artificial Intelligence

9 terms in Growth Glossary.

AI Models

Large Language Models (LLMs): Text in, Text Out (note, Code is also a language). Examples include GPT4, GPT3, Charlie 1, Claude 3.5 Diffusion Models: Typically text to multimedia like images, video, audio. Examples include Stable Diffusion, Flux, Stable Video, midjourney Text to Speech (TTS): Going from Text to Audio. Examples include ElevenLabs Audio to Text: Going from Audio or Video with audio to text. Examples include OpenAI Whisper Multimodal Models are different in that they typically can understand multiple modalities of data as inputs, and create multiple modalities. Most multimodal models are currently just different models stitched together with Langchain or other language driven architectures.

Topics

ai Artificial Intelligence

Which are the most common AI Models?+

Large Language Models (LLMs): Text in, Text Out (note, Code is also a language). Examples include GPT4, GPT3, Charlie 1, Claude 3.5

Diffusion Models: Typically text to multimedia like images, video, audio. Examples include Stable Diffusion, Flux, Stable Video, midjourney

Text to Speech (TTS): Going from Text to Audio. Examples include ElevenLabs

Audio to Text: Going from Audio or Video with audio to text. Examples include OpenAI Whisper

Multimodal Models are different in that they typically can understand multiple modalities of data as inputs, and create multiple modalities. Most multimodal models are currently just different models stitched together with Langchain or other language driven architectures.

ChatGPT

Don’t just wonder what ChatGPT is—ask ChatGPT itself and experience the answer firsthand!

Topics

ai Artificial Intelligence

What is ChatGPT?+

ChatGPT is an advanced conversational AI developed by OpenAI, designed to understand and generate human-like text. It uses a machine learning model called GPT (Generative Pre-trained Transformer) to assist with a wide variety of tasks, including answering questions, providing explanations, generating creative content, and more.

At its core, ChatGPT is a language model trained on vast amounts of text data to predict the next word in a sentence, allowing it to generate coherent and contextually relevant responses. Its versatility makes it useful for personal, professional, and educational purposes.

ChatGPT is only on the web?+

No, ChatGPT isn't limited to the web! While the web-based platform is the most common way to access it, ChatGPT is also available through other channels, including:

Mobile Apps: OpenAI provides official mobile apps for both iOS and Android, allowing you to use ChatGPT conveniently on your smartphone or tablet.

Third-Party Integrations: Many applications and services integrate ChatGPT into their tools, such as customer service platforms, productivity apps, or developer tools.

APIs for Developers: OpenAI offers an API that allows developers to embed ChatGPT into custom applications, software, or even IoT devices.

Desktop Access via Browsers: While technically still "web-based," accessing ChatGPT through a browser on a desktop is a common and convenient option.

ChatGPT Plus and Plugins: For enhanced functionality, the paid versions offer plugin access and other features that can expand its use across different tasks.

ChatGPT is available for macOS 14+ with Apple Silicon

You can now quickly access ChatGPT from anywhere on your computer with the Option + Space shortcut to share screenshots, upload files, and use Advanced Voice Mode to chat with your computer and get hands-free answers while you work.

Can ChatGPT generate a custom font for me?+

Follow this guide to generate your custom font with AI (and Calligraphr)

Cues

Cues are typically embedded in the prompt to guide the model’s output without prescribing a specific framework. They are helpful for fine-tuning the response to fit particular needs or contexts. Cues are more specific signals or prompts used within those methods to refine or direct the response further. Cues are elements within those strategies that further direct or fine-tune the response.

Topics

ai Artificial Intelligence

What is a cue?+

Cues are typically embedded in the prompt to guide the model’s output without prescribing a specific framework. They are helpful for fine-tuning the response to fit particular needs or contexts.

Cues are more specific signals or prompts used within those methods to refine or direct the response further.

Cues are elements within those strategies that further direct or fine-tune the response.

Some examples of cues?+

Factual Information:

Cue: “According to recent studies...”

Example Prompt: “According to recent studies, how does sleep affect cognitive performance?”

Summarization:

Cue: “In summary,”

Example Prompt: “In summary, what are the main arguments presented in the article about climate change?”

Opinion or Perspective:

Cue: “In your opinion,”

Example Prompt: “In your opinion, what are the most significant challenges facing remote work?”

Step-by-Step Instructions:

Cue: “First, then, finally,”

Example Prompt: “Explain how to bake a cake. First, list the ingredients, then outline the preparation steps, and finally describe the baking process.”

Comparison:

Cue: “Compare and contrast,”

Example Prompt: “Compare and contrast the key features of electric cars versus hybrid cars.”

Definition or Explanation:

Cue: “Define,” or “Explain,”

Example Prompt: “Define blockchain technology and explain its potential impact on financial transactions.”

Clarification:

Cue: “In simple terms,”

Example Prompt: “In simple terms, how does the internet work?”

Creative Response:

Cue: “Imagine if,”

Example Prompt: “Imagine if humans could live on Mars. Describe what daily life might look like.”

Positive Emphasis:

Cue: “Highlight the benefits of,”

Example Prompt: “Highlight the benefits of using renewable energy sources over fossil fuels.”

Neutral Tone:

Cue: “Objectively discuss,”

Example Prompt: “Objectively discuss the pros and cons of implementing universal basic income.”

Historical Context:

Cue: “Historically,”

Example Prompt: “Historically, how have major technological advancements influenced job markets?”

Speculative Scenario:

Cue: “What if,”

Example Prompt: “What if artificial intelligence could fully replicate human emotions? How might this affect human-robot interactions?”

GAI (Generative AI)

ChatGPT and similar tools like Bard, Anthropic’s Claude, and Bing Chat utilize generative AI (GAI) technology to quickly produce coherent language in various styles, formats, and tones. GAI technology leverages large language models (LLMs) trained on huge datasets to generate human-like text, making it useful for content creation, communication, and creative writing tasks. GAI-powered chatbots can produce comprehensive, cohesive essays, catchy social media blurbs, or detailed outlines in seconds.

Topics

ai Artificial Intelligence

What is GAI+

What are the sources of Chatgpt and other GAI bots?+

OpenAI, the organization behind ChatGPT, has not publicly disclosed the specifics of the individual datasets used, however, it’s known that the model was trained on a diverse range of text sources, which includes a broad spectrum of publicly available information on the internet.

On May 16, Reddit announced a partnership with OpenAI to provide its content to the widely-used chatbot, ChatGPT. This news led to a 12% increase in Reddit’s shares during extended trading. The collaboration highlights Reddit’s strategy to expand beyond its advertising revenue, coming on the heels of a recent partnership with Google to make its content available for training Google’s AI models or Google’s SERPs. Similarly, ChatGPT has also teamed up with LinkedIn Pulse and Quora, integrating their articles into its training dataset.

GEO (Generative Engine Optimization)

Generative Engine Optimization (GEO) is an emerging term in the digital marketing landscape. Similar to Search Engine Optimization (SEO) and App Store Optimization (ASO), GEO involves optimizing content specifically for AI-driven search engines, known as generative engines. These engines, powered by large language models (LLMs) like ChatGPT, synthesize information from multiple sources to deliver comprehensive and personalized responses to user queries.

Topics

ai Artificial Intelligence SEO

What is GEO?+

Are traditional SEO strategies such as Surround Sound SEO and Micro-monopoly affecting GEO?+

Generative engines excel at creating cohesive and innovative content by synthesizing vast amounts of information. By building a micromonopoly, you create a specialized niche where your content becomes the authoritative source. Surround Sound SEO complements this by ensuring your content appears across multiple top-ranking pages, rather than just aiming for the top spot on search engines.

Combining the principles of building a micromonopoly with the theory of Surround Sound SEO offers a robust strategy to enhance Generative Engine Optimization (GEO). This approach not only helps you dominate a niche but also ensures that your content is highly visible and consistently utilized by generative engines.

llms.txt

While robots.txt and sitemap.xml are designed for search engines, LLMs.txt is optimized for reasoning engines. It provides information about a website to LLMs in a format they can easily understand.

Topics

ai Artificial Intelligence SEO

Isn't my website already ready for LLMs?+

While websites serve both human readers and LLMs, the latter benefit from more concise, expert-level information gathered in a single, accessible location. This is particularly important for use cases like development environments, where LLMs need quick access to programming documentation and APIs.

What is llms.txt?+

llms.txt markdown is human and LLM readable, but is also in a precise format allowing fixed processing methods (i.e. classical programming techniques such as parsers and regex).

llms.txt vs. sitemap.xml and robots.txt+

llms.txt is designed to coexist with current web standards. While sitemaps list all pages for search engines, llms.txt offers a curated overview for LLMs. It can complement robots.txt by providing context for allowed content. The file can also reference structured data markup used on the site, helping LLMs understand how to interpret this information in context.

The approach of standardizing on a path for the file follows the approach of /robots.txt and /sitemap.xml. robots.txt and llms.txt have different purposes—robots.txt is generally used to let automated tools know what access to a site is considered acceptable, such as for search indexing bots. On the other hand, llms.txt information will often be used on demand when a user explicitly requests information about a topic, such as when including a coding library’s documentation in a project or when asking a chatbot with search functionality for information.

It serves a fundamentally different purpose than existing web standards like sitemap.xml and robots.txt.

/sitemap.xml lists all indexable pages, but doesn’t help with content processing. AI systems would still need to parse complex HTML and handle extra info, cluttering up the context window.

/robots.txt suggests search engine crawler access, but doesn’t assist with content understanding either.

/llms.txt solves AI-related challenges. It helps overcome context window limitations, removes non-essential markup and scripts, and presents content in a structure optimized for AI processing.

How do I add llms.txt on my website?+

If your website runs on a well known CMS i.e. Wordpress, there are plugins that will create the llms.txt files the same way they create sitemap.xml. Use that plugin and see if the result is satisfactory.

You can access your llms.txt file in:

[yourwebsite]/llms.txt

How to create the llms.txt file?+

To create effective llms.txt files, consider these guidelines: Use concise, clear language. When linking to resources, include brief, informative descriptions. Avoid ambiguous terms or unexplained jargon. Run a tool that expands your llms.txt file into an LLM context file and test a number of language models to see if they can answer questions about your content.

Methods

Methods are systematic approaches or frameworks for crafting prompts that yield more structured, relevant, or insightful responses from ChatGPT. They help users get the desired output by applying a predefined strategy or format. Methods are broader strategies or frameworks that provide a structured approach to interacting with ChatGPT. Methods define the overall strategy or approach for engaging with ChatGPT.

Topics

ai Artificial Intelligence

What's the method (in prompting)?+

Methods are systematic approaches or frameworks for crafting prompts that yield more structured, relevant, or insightful responses from ChatGPT. They help users get the desired output by applying a predefined strategy or format.

Methods are broader strategies or frameworks that provide a structured approach to interacting with ChatGPT.

Methods define the overall strategy or approach for engaging with ChatGPT.

What's the relation of methods vs. cues?+

Cues and methods complement each other. Methods provide a broad framework for the interaction, while cues are used within these frameworks to guide the response's specifics, ensuring that it aligns with the user’s needs and expectations.

non-linear marketing

Non-linear marketing is a transformative approach where businesses interact with their audiences in a more dynamic, adaptable way rather than following a traditional, fixed sequence of steps. Unlike the linear model (where customers are guided through a set path, such as a click-through to a form), non-linear marketing allows for flexible paths in lead generation, capture, and nurturing. AI-driven methods, such as chat interactions, exemplify this by enabling conversations where both the business and the customer can deviate from a fixed script, accommodating a more natural flow of questions, answers, and information.

Topics

ai Artificial Intelligence

What is Non-Linear Marketing?+

Why Has Non-Linear Marketing Recently Entered Marketing Jargon?+

Non-linear marketing has become popular recently due to the rise of AI and conversational technologies that can engage customers in flexible, personalized ways. These technologies allow businesses to support more interactive, fluid customer journeys that adapt to individual behaviors rather than forcing them through a rigid series of steps. This shift is significant as AI-powered conversations are becoming more prevalent in customer engagement, making it essential for marketers to integrate and understand non-linear marketing approaches.

Is Non-Linear Marketing a New Term?+

The term "non-linear marketing" is relatively new in its current context, especially as it pertains to digital interactions and AI-powered lead generation. Although concepts of flexibility and personalization have long been part of marketing, non-linear marketing specifically reflects a shift away from traditional, sequential funnels to more adaptable engagement models driven by recent advancements in AI and conversational marketing tools.

Are AI chatbots capable of supporting non-linear marketing?+

Yes, AI chatbots are particularly well-suited to support non-linear marketing due to their flexible, conversational capabilities. Here’s how they can enhance non-linear marketing:

1) Adaptable Conversation Flow

AI chatbots can respond dynamically to user inputs, allowing customers to ask questions or request information out of a pre-set sequence. For example, instead of following a rigid, scripted path, chatbots can adjust to the customer's unique inquiries or concerns, maintaining engagement without requiring them to follow a traditional funnel. This flexibility is at the core of non-linear marketing.

2) Real-Time Personalization

Chatbots can collect data during interactions and instantly adjust responses based on the user’s preferences, behavior, or location. This personalized, in-the-moment customization provides a more relevant experience, moving away from a "one-size-fits-all" approach and letting the customer drive their journey more organically.

3) Continuous Lead Nurturing

AI chatbots enable continuous lead nurturing by adapting to a customer's stage in their journey. They can respond to new queries, pick up on previous interactions, and offer different types of information depending on the customer’s current needs, which enhances the non-linear nature of the customer experience. This flexibility means that the interaction can flow according to the customer's needs rather than a preset linear funnel.

4) Handling “Off-Script” Moments

Unlike traditional scripted interactions, AI chatbots can handle deviations without derailing the conversation. For instance, if a customer asks product-specific questions during a more general onboarding process, the chatbot can accommodate these “off-script” moments, provide relevant answers, and then naturally guide the customer back to the core engagement path.

5) Collecting Feedback and Iterating on Engagement Paths

AI chatbots also collect data from each interaction, allowing businesses to understand common deviations or questions that users bring up. This helps marketers refine the bot’s responses and engagement strategies to align even more closely with customer needs, continuously enhancing the non-linear experience.

Prompting

A prompt is a set of instructions or questions provided to a person or a system to elicit a response. In the context of a conversational AI, a prompt is the user’s input, which could be a question, command, or any statement that the AI responds to. In a prompt, I could: * Ask to get an answer * Ask to check the correctness of my prompt (hence refining the answer) * Ask to help me compose the question in case I don't know how to do it in an optimal way (hence to generate the prompt)

Topics

ai Artificial Intelligence prompting

What is a prompt?+

A prompt is a set of instructions or questions provided to a person or a system to elicit a response. In the context of a conversational AI, a prompt is the user’s input, which could be a question, command, or any statement that the AI responds to. In a prompt, I could:

* Ask to get an answer

* Ask to check the correctness of my prompt (hence refining the answer)

* Ask to help me compose the question in case I don't know how to do it in an optimal way (hence to generate the prompt)

What is prompt engineering?+

Prompt engineering is the art and science of designing inputs, known as prompts, to obtain desired outputs from AI models, particularly generative AI.

Do prompts work the same across different AI platforms?+

Most prompts work similarly across major generative AI platforms because fundamental elements like "cues" and "methods" are largely consistent. This means that a prompt used in ChatGPT will typically function similarly in Microsoft Copilot or Google Gemini. However, subtle differences may exist in how each platform interprets certain inputs, so it can be beneficial to adjust prompts slightly to fit the specific nuances of each AI system for the best results.

How can AI assist me in crafting and improving prompts?+

AI can be a valuable tool for working with prompts by:

* Assisting in prompt creation: AI can guide you in structuring your prompt to ensure clarity and relevance for the task at hand. Use the prompt generator method.

* Verifying prompt accuracy: AI can evaluate your prompt for potential issues, such as ambiguity, incomplete details, or incorrect phrasing.

* Enhancing and optimizing prompts: AI can suggest improvements or alternative phrasings to make your prompt more effective and aligned with your desired outcome.

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AI Models

Topics

ai Artificial Intelligence

Which are the most common AI Models?+

Large Language Models (LLMs): Text in, Text Out (note, Code is also a language). Examples include GPT4, GPT3, Charlie 1, Claude 3.5

Diffusion Models: Typically text to multimedia like images, video, audio. Examples include Stable Diffusion, Flux, Stable Video, midjourney

Text to Speech (TTS): Going from Text to Audio. Examples include ElevenLabs

Audio to Text: Going from Audio or Video with audio to text. Examples include OpenAI Whisper

Multimodal Models are different in that they typically can understand multiple modalities of data as inputs, and create multiple modalities. Most multimodal models are currently just different models stitched together with Langchain or other language driven architectures.

ChatGPT

Don’t just wonder what ChatGPT is—ask ChatGPT itself and experience the answer firsthand!

Topics

ai Artificial Intelligence

What is ChatGPT?+

ChatGPT is only on the web?+

Can ChatGPT generate a custom font for me?+

Follow this guide to generate your custom font with AI (and Calligraphr)

Cues

Topics

ai Artificial Intelligence

What is a cue?+

Cues are typically embedded in the prompt to guide the model’s output without prescribing a specific framework. They are helpful for fine-tuning the response to fit particular needs or contexts.

Cues are more specific signals or prompts used within those methods to refine or direct the response further.

Cues are elements within those strategies that further direct or fine-tune the response.

Some examples of cues?+

GAI (Generative AI)

Topics

ai Artificial Intelligence

What is GAI+

What are the sources of Chatgpt and other GAI bots?+

GEO (Generative Engine Optimization)

Topics

ai Artificial Intelligence SEO

What is GEO?+

Are traditional SEO strategies such as Surround Sound SEO and Micro-monopoly affecting GEO?+

llms.txt

While robots.txt and sitemap.xml are designed for search engines, LLMs.txt is optimized for reasoning engines. It provides information about a website to LLMs in a format they can easily understand.

Topics

ai Artificial Intelligence SEO

Isn't my website already ready for LLMs?+

What is llms.txt?+

llms.txt markdown is human and LLM readable, but is also in a precise format allowing fixed processing methods (i.e. classical programming techniques such as parsers and regex).

llms.txt vs. sitemap.xml and robots.txt+

How do I add llms.txt on my website?+

How to create the llms.txt file?+

Methods

Topics

ai Artificial Intelligence

What's the method (in prompting)?+

Methods are systematic approaches or frameworks for crafting prompts that yield more structured, relevant, or insightful responses from ChatGPT. They help users get the desired output by applying a predefined strategy or format.

Methods are broader strategies or frameworks that provide a structured approach to interacting with ChatGPT.

Methods define the overall strategy or approach for engaging with ChatGPT.

What's the relation of methods vs. cues?+

non-linear marketing

Topics

ai Artificial Intelligence

What is Non-Linear Marketing?+

Why Has Non-Linear Marketing Recently Entered Marketing Jargon?+

Is Non-Linear Marketing a New Term?+

Are AI chatbots capable of supporting non-linear marketing?+

Prompting

Topics

ai Artificial Intelligence prompting

What is a prompt?+

A prompt is a set of instructions or questions provided to a person or a system to elicit a response. In the context of a conversational AI, a prompt is the user’s input, which could be a question, command, or any statement that the AI responds to. In a prompt, I could:

* Ask to get an answer

* Ask to check the correctness of my prompt (hence refining the answer)

* Ask to help me compose the question in case I don't know how to do it in an optimal way (hence to generate the prompt)

What is prompt engineering?+

Prompt engineering is the art and science of designing inputs, known as prompts, to obtain desired outputs from AI models, particularly generative AI.

Do prompts work the same across different AI platforms?+

How can AI assist me in crafting and improving prompts?+