As crazy it sounds, I get a feeling AI is the already becoming ‘old news’. Don’t get me wrong. The hype around using AI in a practical sense to create value-adding solutions and products is very much alive and if anything, will grow stronger. But there was a time when just about everyone felt the need to weave “AI” into their presentation or the virtual water-cooler session over Zoom. However, this post isn’t for those nerds. This is for those who don’t really care about AI but would like to do just a teeny bit more than smiling silently in the corner. Here are my tips to ‘sound’ like you follow the latest trends of AI without going into too much detail. 

As mentioned above, EVERYBODY is doing something with AI and honestly, it’s nearly impossible to track all of the nitty gritty details if you’re not very intentional. However, there are a few names that you can drop to get a few nods.

OpenAI

Even if you don’t follow anything about AI, you must’ve heard about ChatGPT. OpenAI is the company that made ChatGPT, which is arguably one of the most powerful and versatile generative AI model you can start using right away. For ideas on how to use ChatGPT, check out this post!

NVIDIA

NVIDIA manufactures the microchips that power the AI models like ChatGPT. As of February 2025, the chips that are manufactured by NVIDIA are practically irreplaceable.

Microsoft

Microsoft has embedded multiple AI solutions into its products. The Premium version of MS Teams can now transcribe meetings and generate summarized notes with relatively high accuracy. Additionally, their cloud service Azure powers a lot of AI applications. 

Google

I’d be surprised if you were surprised to see Google on this list. Google integrated AI into almost all of their products in one way or another. They also have their own generative conversational AI models like Bard. Google also has a cloud service (GCP) that powers a ton of AI solutions as well. 

As you may already know, AI is a bit of a complex dish to chew up in one bite and as you dig deeper into the details, you’ll realize that there are a ton of different models and learning types. Lately though, I think the people’s conception of AI has been solidified to ChatGPT or similar systems where you provide a task for the system and it returns a magically written script, picture, 3D animation, and more.

These are absolutely valid experiences with AI but if you’re trying to leave an impression that you kind of know AI, you should also keep in mind that there are other types of AI models. 

AI can understand an image or a video data. 

Think facial recognition systems or autonomous driving systems. 

As you might imagine, this is not the comprehensive list of AI models that are out there today. The list will get even more extensive as you start adding on layers of information like learning methods, data prepping, etc. In short, you could find yourself going down rabbit holes that lead to more rabbit holes quite quickly. However, all of those rabbit holes will eventually reveal fascinating insights to AI solution development so if you’re intrigued, by all means, try traveling that path!

 An early symptom of something being overhyped is that people talk about it like it’ll solve all of the world’s problems. And the reality is quite often, and almost always, far LESS dramatic than that (remember ‘big data’ anybody?). AI is definitely powerful and its impacts are anything but trivial. But it’s not quite the omnipotent magic tool that we all hope or think it is. 

In fact, even the most sophisticated AI systems have not fully eliminated biases, inaccuracies, tendencies to hallucinate or neglect the context, and hence, cannot be trusted in full. ChatGPT for instance has shown to deliver inaccurate or nonexistent information, misinterpret the context of the question, or even blatantly lie about certain facts marking them untrue. In all fairness, things might change in the not too distant future but for now, it’s quite evident that we still need a human in the loop to be the judge of what is right or wrong.   

‘Human in the loop’ becomes more important in fields with high accountability like healthcare. Physicians, nurses, and other experts are still critical in determining the context and making the ‘right’ decision. Additionally, we still need ‘people’ to be held accountable. Remember that AI is only a tool. Have you ever seen a screwdriver being held accountable for a loose screw? 

Again, I’m not saying that you should be a cynic about AI. I’m saying be the person that doesn’t lose the sight of the non-artificial part in this whirlwind of artificial intelligence.

AI is a complicated topic that will, if anything, stay complicated. Unless you are in the field one way or another, it might feel like a topic that’s too intimidating and far fetched. I hope you were able to take a few buzzy words to help you find a spot at the table discussing AI. If you need more insights, please do leave a comment or reach out directly!