Introduction
While learning Generative AI, one thing slowly became clear to me:
working with models alone is not enough in the real world.
Models can generate responses, but turning those ideas into real
applications requires much more than just AI.
Why Cloud Matters for GenAI
As I explored more real-world use cases, I realized that deployment,
scalability, and security play a major role.
This is where cloud services become important.
Without cloud infrastructure, AI applications cannot scale
or run reliably in production environments.
Starting with AWS Fundamentals
Alongside learning Generative AI concepts, I decided to start learning
AWS fundamentals to understand how cloud supports AI-driven systems.
I began with basic services such as:
- EC2 for compute
- S3 for storage
- IAM for access and security
These services helped me understand how infrastructure is set up
and how applications are managed in the cloud.
Early Learning Stage
I am still at an early stage of my cloud journey.
Right now, my focus is on understanding core concepts
rather than building complex systems.
The goal is to learn step by step and build a strong foundation.
Why I Am Sharing This
I plan to share my learnings as I move forward so that
other beginners can also understand how cloud and AI
work together in practice.
This blog is part of my learning journey, and I will continue
to write as I explore more AWS services and real-world use cases.
Conclusion
Generative AI becomes much more powerful when combined
with cloud infrastructure.
Learning AWS fundamentals alongside GenAI is helping me
understand how real applications are built, deployed,
and secured in the real world.
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