Introduction
No one said this blog will have only tutorials or deep tech talks, right? Since I was a kid, I have been creating stuff. Actually, my very first memories are playing around in my dad’s workshop, extracting electronic components from old radios and TVs. I think this fed my curiosity, and that’s the main reason I ended up studying Electronics and Automation engineering. However, later I realized that an electronics workshop is a little impractical to have on-the-go, and I fell in love with programming. Luckily, some of my childhood friends did the same, and fast-forward a few years, I’m surrounded by great people, some of whom are very talented engineers and founders.
This has inspired me to an endless pursuit of knowledge that has ultimately shaped who I am as a person and as an engineer. That is, I usually call myself an “all sorts engineer.” And here I am, after transitioning to software engineering, trying to build something meaningful that inspires me. So, a few weeks ago AIdentify was born, and recently I launched the waitlist.
What’s AIdentify’s purpose?
First of all, it serves the purpose of being something that motivates me and which I truly think will generate value, as well as provide me with great challenges along the way. It’s the materialization of an idea, of a muse I have, and something that I will build from the ground up.
The core concept is simple, deep fakes are everywhere these days, with systems such as DALL-E or SORA, AI-generated visual content is very present in our lives. This brings a set of challenges such as identifying the legitimacy and authenticity of the content which will, for sure, be present in many industries such as art, journalism, or social media apps.
Do you want to know if that viral video is real? Do you want to make sure you are not being cat-fished? AIdentify will provide the tools for both individuals and companies to check these things, among other features. You won’t be able to just AIdentify the content, but you will have insights from our visual explainer that will allow you to know why the content is fake (or real).
There are a lot of things in the backlog and ideas that I want to implement, but I will share them when the right time comes. For now, let’s set realistic expectations.
Build in public
I want to build AIdentify in public, and I’ll share my journey in this blog (on a weekly or bi-weekly basis) and using X on a daily basis. Why did I choose to build this in public? First of all, because I have learned a ton of things from “public builders” and I want to give back to the community. Secondly, I’m a FOSS advocate, and I want to let you guys know which tech stack I use, and hopefully, give back to the Open Source community as well (I have a post talking about Open Source coming very soon). Finally, I think that building in public allows building traction, getting constant feedback or tips from users or fellow creators, and I want to immerse myself entirely in the community.
I’ll share my successes and failures, and what I learn from each. As Phil Knight said: “Fail fast.”
Roadmap
This is too pretentious to be called a roadmap, but I couldn’t find a better word. In the near future, I will have a limited number of users try our AIdentification systems for static images. The idea is to provide this functionality through UI and via API, as well as the visual explanations. Later, video AIdentification will be released. Similarly, I’ll be working to improve model accuracy. As you can see, this cannot be called a roadmap, but I’ll redefine it as I progress.
This is basically all, for now. AIdentify is slowly coming together, and I cannot be more excited. Be sure to follow me on X so you know when the next posts are published. See you along the way!