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GenAI Overview | How does a GenAI application work?

Tech stack - Key Components of Software Architecture

A Generative AI (GenAI) application, such as a chatbot agent, relies on a specific set of technologies. This tech stack comprises various components that work together to enable the functionality of the GenAI application. The key components include:


User Interface (UI):

  • Description: This is the front-end part where user interaction happens. It's designed to be user-friendly and intuitive.

  • Technologies: HTML, CSS, JavaScript, and front-end frameworks like React or Angular.


Application Programming Interface (API):

  • Description: APIs act as intermediaries, allowing the user interface to communicate with the server and the GenAI model.

  • Technologies: RESTful APIs, GraphQL.


GenAI Model:

  • Description: The core of a GenAI application, this is where the generative AI algorithm resides.

  • Technologies: Large language models like GPT-3, BERT, or custom-built models using TensorFlow or PyTorch.


Data Storage:

  • Description: This component is responsible for storing data that the GenAI application uses and generates.

  • Technologies: Databases such as PostgreSQL, MongoDB, or cloud storage solutions like AWS S3, Google Cloud Storage.


Server and Runtime Environment:

  • Description: Servers host the back-end logic and the runtime environment where the GenAI model operates.

  • Technologies: Node.js, Python Flask/Django; server infrastructure like AWS EC2, Google Cloud Compute Engine.


Machine Learning Operations (MLOps) Infrastructure:

  • Description: Essential for training, updating, and maintaining the GenAI models.

  • Technologies: Tools like Kubernetes, Docker, and CI/CD pipelines for automated deployment and scaling.


Security and Compliance:

  • Description: Ensures the application is secure and complies with data protection laws.

  • Technologies: SSL/TLS for encryption, OAuth for authentication, and compliance tools for GDPR, HIPAA, etc.

 

How a GenAI Application Works in Realtime: Non-Technical Explanation

 

Consider a GenAI application, such as a chatbot agent, as a digital concierge in a hotel. Here's a simplified explanation of how it operates in real-time:


Interaction Initiation:

  1. Just like a guest approaching a concierge, a user starts by inputting a query or request through the application’s user interface (the digital equivalent of a hotel lobby).


Request Processing:

  1. The request is sent to the server via an API, much like a concierge listening to the guest's request. The server is the back-office where all the processing happens.


GenAI Model Engagement:

  1. The core GenAI model (the brain of the concierge) then interprets the request. This model, trained on vast amounts of data, understands and generates a response, just like a knowledgeable concierge crafting a reply based on their experience.


Response Delivery:

  1. This response is then sent back to the user through the UI, providing information or assistance, similar to how a concierge would give suggestions or solutions to a guest.


Continuous Learning:

  1. Just as a concierge learns from each interaction to improve service, the GenAI model continuously learns from interactions to enhance its responses over time.


In this way, the GenAI application provides real-time, intelligent responses to user queries, leveraging advanced AI and a robust tech stack to deliver an experience akin to interacting with an expert human agent.

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