1. What is Generative AI?
2. Life Before Generative AI
3. Traditional Applications (Pre-Gen AI)
4. Generative AI-Powered Applications

 

• What is Generative AI?

Generative AI is a type of artificial intelligence that creates new content by learning from existing data. This learning process, often referred to as "training," produces a statistical model that enables the AI to predict responses and generate original content when given a prompt.

 

• Life Before Generative AI

Though generative AI has been around for some time, it only gained widespread attention in 2022, when platforms were inundated with AI-generated text and images, sparking interest worldwide. Recent advancements have made it possible for developers to incorporate generative AI into their applications without needing deep expertise in machine learning.

 

Before the advent of these generative AI applications, let's take a look at how things worked.

 

• Traditional Applications (Pre-Gen AI)

In the past, app design followed a relatively straightforward structure. Apps were built using code to manage user interactions and a database to store data. Though these systems have grown increasingly complex, their core functionality remained the same.

 

• Generative AI-Powered Applications

With generative AI, the landscape of app development has shifted dramatically. AI-powered apps can now deliver advanced user experiences that were once either too complex or too expensive to build. The key component of these applications is the foundation model, typically a large language model (LLM). These LLMs are trained on vast amounts of text and are capable of understanding and producing human-like responses and insights.

 

• Types of Generative AI Applications

 

Generative AI offers a wealth of creative opportunities in app development. Here are a few examples of the types of applications that can be built:

 

      1. Content Creation

Generative AI can automatically create new and creative content. 

  Example:   An app can generate product descriptions for new items by analyzing product images and instruction manuals.

 

      2. Domain-Based Conversations

Apps can now use the chat history with users to offer relevant, context-aware responses. 

  Example:   A chatbot can engage in long conversations with customers, understanding the context from previous interactions instead of needing the user to repeat themselves in each question.

 

      3. Semantic Search

Generative AI enhances search functionality by understanding the intent behind a query, rather than just matching keywords. 

  Example:   A search for "python" in a developer's app might return programming-related results, while a zookeeper’s app would focus on information about the snake.

 

Generative AI has opened the door to countless innovations, transforming how we build and use applications.

 

In the next article of this series: What is a Foundation Model?