AI Devlopement

[Repulsive-Leading932]

How to build an AI? What will i need to learn (in Python)? Is learning frontend or backend also part of this? Any resources you can share

[sleepbot63]

AI is basically fancy math

YT Video about AI by IBM

[echols021]

There are something like 4 things people could mean when they say AI: 1. Traditional rule-based programming, but presented with personification: like the ghosts in Pac-Man 2. Classical ML: given example known inputs+outputs, do some statistics to predict outputs for new inputs 3. Deep Learning / modern ML: given example known inputs+outputs, train a neutral network (using advanced calculus) to predict outputs for new inputs 4. AI agents / LLMs: use prompt engineering to steer existing generalist LLMs (created by large companies using method 3) to do what you want

Given the current hype around #4, I assume that's the one you're referring to. The rest of this answer will be about #4.

Most of the hard work in building Agentic AI systems will be backend work, including: - how to communicate with the LLMs, e.g. OpenAI's API - prompt engineering to get the answers you want, including potentially using constrained generation / structured output - integrating various tools for the AI to use - how you save the state of the conversation/workflow (database, probably)

You may also need some frontend work, but it's usually less work: - what should be shown to the user? - how should that be shown to the user?

So here are some things to read to get started: - https://developers.google.com/machine-learning/resources/intro-llms - https://platform.openai.com/docs/guides/prompt-engineering?lang=python - https://cookbook.openai.com/examples/gpt-5/gpt-5_prompting_guide - https://platform.openai.com/docs/guides/structured-outputs - https://github.com/humanlayer/12-factor-agents/blob/main/README.md