Imagine a super hyped-up train you see rolling, all about this thing called Generative AI (GenAI). Yep, another hyped-up train is coming and I’m trying to catch this beast. I’ve let too many “could’ve beens” slip by in the past, and I’m not about to let this one go. Missed chances? Overthinking everything? Been there, done that.
A buddy of mine once hit me with a line that stuck: “Scared money don’t make money.”, coming from him, it’s probably a movie phrase. And, honestly? He was right. It wasn’t fear holding me back; it was me, overanalyzing every single detail. Always wondering, “But who’s gonna want this? Is there even a market for it?” Then it hit me – with billions of people in the world, there’s a little bit of everything for everyone. From the smallest ideas to the biggest, most intricate inventions, there’s someone out there looking for exactly that.
So, I decided it was time for a deep dive – not just any dive, but a plunge into the depths of AI, ML (that’s Machine Learning for the uninitiated), and DL (Deep Learning). Picture me, night owl style, eyes wide open, this will be my second job (3rd shift). It’s been a wild ride – pumping back Redbulls in the day, 7 PM Starbucks run, a bit crazy, and totally game-changing for me. Skipping gym hours, and putting in the work on some ideas. But here’s where it gets real – deciding to actually bring my ideas to life felt like signing up for a fitness challenge. You’re not in it for the likes or the applause. You’re in it to test your mettle, to see what you’re truly capable of. So, I rolled up my sleeves and dove headfirst into creating something from scratch, driven not by what people might think but by my own drive and curiosity.
Building something from the ground up is kinda like painting a masterpiece. It starts with a spark – an idea that keeps you up, tossing and turning. Then you sketch it out, bit by bit, until you’re knee-deep in the nitty-gritty – coding, tweaking, facing setbacks, and celebrating those little wins. It’s an emotional rollercoaster, a mix of frustration and triumph, and learning from every bump along the way.
And let me tell you, the GenAI hype train has been my trusty sidekick through it all. This isn’t just about hopping on the latest trend. It’s about believing in the magic of what you’re working on. It’s about envisioning the future with every piece of code, every setback that turns into a stepping stone. The AI universe is vast market, pick one. It’s a frontier brimming with potential just waiting to be tapped. And I’m here for it, ready to dig in, to innovate, and to leave my mark.
So, here’s to not just dreaming about it, but in 2024 I’m making it happen. I’m in the kitchen cooking and looking for other chefs and coders!
I’m willing to look at other ideas, if you’re interested in what I’m doing, hit me up on LinkedIn.
Check out my exploration work. This is not my main app idea, but me exploring capabilities and learning what is possible! Below, I created a exploration-proof-of-concept (EPOC) in about two week-ish, mostly doing my weekend warrior thing.
Lessons Learned:
- Easy—Only a couple hours to connect to OpenAI or any LLMs. Their APIs are very intuitive.
- Token and Chat history, that’s something you have to solve.
- Vector Databases: This took longer to learn, getting clean data is hard.
- I spent more time doing Data Engineering work than actually playing with GenAI. Writing code to fix issues, and write for use cases.
- Prompt Engineering and data prep is the longest job! The LLM will do it’s job, as long as you feed it the information it needs.
