Machine what? Neural networks? Deep learning? Generative models? And why does it all sound like a Nolan movie with a script by Alan Turing?
If artificial intelligence sounds like indecipherable jargon with graphics full of little arrows, data structures and names that sound like spells (“bidirectional auto-regressive transformer”), breathe easy: you don’t need to be a space engineer to understand what’s going on.
Here among us, we know that when in a meeting someone says “We’ll solve it with deep learning and a pre-trained LLM”, more than one of us activates his survival instinct and thinks: “Don’t talk to me about that, I do Excel”.
And that’s fine. Because as Mariano Sigman and Santiago Bilinkis quote in “Artificial. The new intelligence and the contours of the human”, following the maxims of Douglas Adams:
- Everything that already existed when you were born is normal and commonplace, and is simply a natural part of how the world works.
- Everything that is invented between your 15th and 35th birthday is new, exciting and revolutionary and something to which you could perhaps devote your career.
- Anything created after the age of 35 goes against the natural order of things!
But don’t worry. Today we’re here to give you back that feeling of being 25, of learning something new that can change your life, and incidentally, allow you to throw out phrases like “I feel like GPT-4.5 is already approaching an AGI, and his LLM improved the RAG considerably.”
(Don’t worry, in 2 minutes you will understand what it means).
What is AI… in English?
Artificial intelligence is basically teaching a machine to detect patterns, like you do when you look at the dark sky and say: “It’s going to rain”. The difference is that AI can do it with millions of data at the same time.
🧠 Machine Learning (ML)
It is when we give it many examples and the machine learns by itself. Example: you show it a thousand images of cats and it ends up understanding what a cat is. Although sometimes it confuses a small dog with a cat.
🧠💪 Deep Learning (DL)
It’s ML on steroids. It uses neural networks, a structure inspired by how your brain works, to understand more complex things. Example: analyzing your voice in an audio message and detecting whether you are happy, tired or angry.
🗣️ NLP – Natural Language Processing
It allows the machine to understand you when you speak or type. Example: it’s what makes Siri, Alexa or ChatGPT understand your questions and not just answer anything (most of the time 😅).
🎨 Generative models
They create content: text, images, music or code. Example: you say “make me a love song in the style of Shakira” and in seconds you have the first verse.
🧠✨ AGI – Artificial General Intelligence
It is the dream AI, capable of learning any task like a human. It’s not here yet, but we’re getting closer. It would be like having Einstein, Da Vinci and your virtual assistant all in one (no coffee needed).
🤖 GPT (Generative Pre-trained Transformer)
It is a family of language models developed by OpenAI, such as ChatGPT. What does it do? It learns by reading large amounts of text and then generates coherent content based on what you ask it to do.
Example: You tell him “write me an invitation with a professional tone” and he does it. You ask him for a sad poem or a funny resignation letter, and he does that too. Basically, it’s a model he learned by reading all over the internet (more or less).
📚 LLM (Large Language Model)
It stands for “Large Scale Language Model”. GPT, Bard, Claude and company are examples of this.
What does this mean? That they were trained with millions (billions!) of words and phrases to be able to understand human language. Imagine an LLM as a great living library: he knows a lot, but sometimes he gets confused or “hallucinates” (makes things up), like that friend who has a good memory but puts drama in everything, you know who I am talking about, don’t you?
🔍 RAG (Retrieval-Augmented Generation)
It is a technique that improves the accuracy of models such as GPT by combining their ability to generate text with external information. Example: It is as if the model says “wait a second, I’m going to search my updated database” before giving you an answer.
This reduces the risk of making up data. It is widely used in companies so that the answers are based on their own documents and reliable sources.
And what is all this good for in a company?
The AI is not there to complicate your life, quite the opposite. It’s like adding an extra mind to the team, one that never sleeps, doesn’t get distracted and doesn’t ask for augmentation (although it does ask for GPU and training).
💼 Where do you see it working?
- Predicting sales and customer behavior.
- Automating tedious tasks (bye bye copy-paste forever!).
- Analyzing massive data to make better decisions.
- Improving customer service with faster and more helpful responses.
- Detecting patterns and opportunities you may miss.
It’s like having a “digital Sherlock Holmes” at the service of your team.
What if I don’t know where to start?
Don’t worry. You don’t have to be Elon Musk (controversial) or know how to program in Python. You just need to be clear about your needs. Do you want to sell more, serve better, free up time for more important tasks? You set the problem, we help you with the solution.
SMS Sudamérica’s role in this grounding
At SMS Sudamérica we believe that artificial intelligence does not have to feel like science fiction.
We don’t come with a dictionary of techno-words. We come with simple questions, real examples and tailor-made solutions.
Because it’s not about you understanding each model, it’s about you knowing how it can help you make better decisions today, work smarter and free up your time.
Want to understand what AI makes sense for your business? We tell it to you clearly, without any spin or smoke and mirrors. We design solutions that work and accompany you step by step.
At SMS, we turn the AI from an enigma into your ally. Whether you’re in sales, marketing, development, logistics or leadership, there’s a way to use it that empowers you.
Now you can say at your next after office… “I feel that GPT-4.5 is already close to an AGI, and their LLM improved the RAG considerably” and look like the tech crack of the group! 😎
🚀 Ready to understand and apply AI without the headache? Contact us! We make it simple, useful… and even fun.
Note by: María Dovale Pérez
