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:
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:
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:
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:
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:
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.
