Generative AI is changing the way people find information online, making it crucial to understand how it works and how you can optimize for it.
In this comprehensive guide, Ignite Visibility’s VP of Product and Marketing, Danny Conlon, will walk you through generative AI and the steps you can take to prepare for it with generative engine optimization.
What You’ll Learn
- What is Generative AI?
- Potential Applications of Generative AI
- Benefits of Using Generative AI
- Risks and Challenges That Come with Using Generative AI
- Generative AI vs Generative Engines
What is Generative AI?
Generative AI, or Gen AI, comprises several artificial intelligence (AI) models that take existing content online using machine learning (ML) to develop new content for users.
Generative AI can subsequently produce all types of media using input data, from text and audio to images and video. Over time, it can better understand what users want to produce, continually improving results based on input data.
What sets generative AI apart from other types of AI is that its purpose is to generate new content as opposed to creating conversations and recognizing patterns.
- Conversational AI: This form of AI helps AI assistants, chat bots, and other conversational platforms generate responses for users through the use of natural language processing (NLP). In turn, these AI models can “chat” with users based on the text they provide.
- Predictive AI: Analytics platforms and other software could use predictive AI that determines potential outcomes based on historical data and ML. By looking at previous information, predictive AI could help analysts and others make more informed decisions with specific recommendations.
It’s important to note that many AI powered platforms combine more than one type of AI. ChatGPT for example uses both conversational and generative AI.
Our Expert Insights into Generative AI
As generative AI continues to integrate into popular tools and search platforms, it’s going to change how people conduct online searches for all types of information.
By optimizing for generative AI, you can ensure your content gets in front of audiences relying on it and maximize your online visibility, supplementing search engine optimization and other digital marketing efforts.
Action Item: AI models grow based on continuous improvement, through every interaction. As marketers, be prepared to use structured data and metadata to help AI models understand the context of your content. By channeling your efforts and creating content that is meaningful, rather than just stuffed with keywords, AI models will accurately interpret your content, ranking it higher in search engine results.
Potential Applications of Generative AI
Generative AI has several applications that making it increasingly popular. Here are some of them:
Content Creation
Many programs use generative AI to develop all types of new content. For example, platforms like ChatGPT can generate almost anything. However, we recommend staying away from AI-generated content for seo purposes. Instead use it to help you generate topic ideas, blog outlines, keywords to research, etc.
Image Generation
In addition to text, programs such as DALL-E and Midjourney can generate images using existing image content. For example, people may use these platforms to generate paintings or other artwork along with photorealistic images based on prompts.
Music and Audio
Meanwhile, programs like ElevenLabs and PlayHT can generate audio in different forms. This audio content could include AI voiceovers for videos that mimic real speech using text-to-speech software, while programs like Soundraw might develop new music tracks.
Business & Enterprise
Organizations may implement various generative AI programs to automate processes and increase operational efficiency. Examples of these applications include:
- Data analysis tools that produce new predictive data based on previous metrics
- Customer service platforms that produce content to answer customer questions or provide guidance
- Product design through generated concepts and other content
Data Augmentation
An additional application may involve data augmentation. Here, generative AI would create new training examples for ML models that can then go toward improving existing datasets, optimizing overall data quality and efficiency.
Rank HIGHER on ChatGPT and Google Gemini
In the video below, SEO Expert, John Lincoln, explains how to use generative engine optimization to ranking higher On ChatGPT and Google Gemini:
The Benefits of Generative AI
Generative AI offers a few key advantages that make it worth using in many applications, including:
Increased Efficiency and Productivity
Using generative AI tools, it’s possible for individuals and businesses alike to optimize efficiency and productivity.
An example: Customer service tools using generative AI can guide customers more effectively along the buyer’s journey by providing them with helpful information and direction when navigating a website.
Enhanced Creativity
Using image generators and other tools, people can augment their creativity through improved creative expression, often by finding more inspiration with the help of these programs. Certain programs could also inspire innovative ideas.
Reduced Costs
Certain industries may also be able to use generative AI to lower costs associated with various operations. Data analytics and generative AI, for example, could help predict how certain changes in processes might positively impact ROI, helping business leaders make more profitable informed decisions.
The Risks and Challenges of Generative AI
While there are many advantages of using generative AI, it isn’t without its potential issues. The following are some challenges that could affect the implementation of these solutions:
1. Inaccuracy Bias
One of the main problems around generative AI is the development of potentially biased or erroneous results. For instance, Google’s recently implemented AI Overviews have been known to produce some questionable results with inaccurate information, while biased data sources could influence generated results and, in turn, make them biased in different ways.
2. Ethical Concerns
Another potential issue relates to the ethics of using generative AI and the content it produces. One example includes the possible copyright infringement of artists, writers, and others whose content contributes to generated content, leading to legal troubles involving certain platforms.
3. Security Risks
The use of generative AI also ties into some security concerns, as people and entities could easily use some programs for malicious purposes.
An example: Hackers and others could use generative AI tools to help conduct cyber attacks, while others could produce deep fakes of real people in an attempt to scandalize them with fake content.
Generative AI and Generative Engines: How Do They Connect?
Generative AI and generative engines work together, with these engines powering generative AI applications. Using different types of algorithms and models, generative engines allow for the production of content through gen AI programs.
There are several generative AI examples out there that perform the work behind generative AI tools, such as:
Generative Adversarial Networks (GANs)
These are made up of two neural networks, a discriminator and a generator. First, these systems work by having the generator develop new data. Then, the discriminator validates this data against the original source to improve its accuracy.
A GAN system may generate realistic images of faces by relying on the generator to create new images and the discriminator to assess their authenticity against the real photos, improving the generated images with the goal of making them indistinguishable from the real human face.
Transformers
Using input data, transformers produce text that’s contextually relevant, making them effective for understanding natural language and producing it for certain platforms.
One popular platform that uses transformers for text generation is ChatGPT, with GPT standing for Generative Pretrained Transformer.
Variational Autoencoders (VAEs)
These engines take existing data to distribute it strategically in new content using an encoder and a decoder. The encoder takes input data and converts it into a latent representation that the decoder then reconstructs, resulting in new output data that’s similar to the input.
An example of the use of these engines is image generation, which uses VAEs to place portions of previous images into new configurations to generate entirely new images. They can also produce other types of high-dimensional data like music and text content.
The Different Generative Engines
The following are a few of the biggest generative AI tools that people can use:
- ChatGPT: This platform uses transformers to understand and produce natural language based on input data, usually in the form of sequential text. The platform can use the data that users input to generate all types of data, including new text, translations, and summaries, with the help of predictive text generation.
- Microsoft Copilot: Many Microsoft products use this engine to produce all kinds of content. Generative AI tools like Microsoft 365 Copilot and GitHub Copilot can produce text content, code, and more with the help of OpenAI’s Codex and other GPT-3 models.
- Google Gemini: Like ChatGPT, users can input data to have Gemini’s transformer engines develop new text, such as translations and summaries. It’s one of several generative AI tools Google continues to roll out, with integrations into major Google platforms like Google Search and Google Assistant. For instance, Search users can input search queries, and Google Gemini will bring back results compiled from previous sources in AI Overviews at the top of the page.
Optimize for Generative AI with Ignite Visibility
With the increased use of generative AI, it’s now more important than ever for marketers to keep up. Generative engine optimization (GEO) is an essential tool in boosting SEO efforts to optimize for generative AI and the engines powering them.
If you would like some help with GEO and connecting with generative AI users, Ignite Visibility is here for you.
With our help, you can:
- Develop high-quality content that appears in generative AI results
- Supplement GEO efforts with reliable SEO strategies that further increase visibility in search engines
- Stay up-to-date with the latest generative AI trends to inform future strategies
- Measure the results of your efforts with in-depth analytics and reporting
To get started on your next strategy, get in touch with our experts today.
