AI has evolved rapidly over the past few years, with new models, architectures, frameworks, and open-source tools making it possible to tackle workloads that were previously out of reach. What’s changed most is not just capability, but accessibility—AI is now something individuals can experiment with, adapt, and build on directly.
This blog is where I’m documenting that journey, with a focus on creating practical AI applications that solve real problems. I’m especially interested in how AI can be used in everyday areas like personal finance, understanding complex legal documents, and automating decision-making.
In future posts, I’ll explore topics such as AI prototypes, agentic AI workflows, and retrieval-based systems, as well as how to run AI models locally on a laptop. Running models locally avoids dependence on API keys and keeps sensitive data private, which I see as an increasingly important part of modern AI use.
AI has come a long way—and there’s still a lot to test, question, and build. Let’s dive in.
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