In 2024, Artificial Intelligence (AI) is everywhere: from apps on our phones to systems driving cars, from movie recommendations on Netflix to chatbots answering our questions. But what exactly lies behind terms like AI, ML, GEN AI, LLM, and RAG? If you're curious or want to better understand these acronyms, you're in the right place. In this blog, we'll provide clarity with concrete examples and simple explanations.
In the world of Artificial Intelligence, there are several acronyms that frequently appear. Let's clarify what they mean and how they impact our digital everyday life:
AI is the branch of computer science that aims to simulate human intelligence. It encompasses activities such as reasoning, learning, problem-solving, and creativity. Think of AI as an artificial brain capable of "thinking" and acting autonomously.
Machine Learning is a subset of AI that enables systems to learn from data, identify patterns, and make decisions without the need for detailed programming. In practice, instead of telling the computer what to do, we provide it with data, and it learns on its own!
Generative AI is the branch of AI that creates new content—texts, images, music, and even code. It doesn’t just answer questions, but produces original content from existing information.
LLMs are advanced AI models trained on massive amounts of text. They are capable of generating content, translating languages, and providing informative responses. Imagine an infinite library that can answer any question in real time.
RAG is a technique that combines the power of LLMs with the ability to retrieve information from a knowledge base. It's like having a constantly updated library, ready to provide accurate and precise information to create more comprehensive responses.
To truly understand how AI works, it’s useful to know a few key principles that drive its functioning:
Grounding is the process that allows AI to respond based on concrete facts, avoiding vague or abstract answers. Imagine AI as an expert who never digresses and always provides concrete responses.
Just as an athlete trains to improve, an AI model also "trains" by using vast amounts of data. During training, AI is corrected through feedback, refining its capabilities to become more accurate and reliable.
The prompt is the input you provide to AI to obtain a response. It’s like asking a question or giving instructions to AI, which then responds based on what was requested.
AI is not only transforming technology but is also revolutionizing entire sectors. Here are some high-potential areas we are focusing on:
We are living in an extraordinary era where Artificial Intelligence is set to rewrite the rules in many sectors. From improvements in customer service to higher business productivity, content creation, and advanced data analysis, the applications of AI are virtually endless.
At Syscons, we continuously monitor these innovations to make the best use of these technologies’ potential. AI is no longer a technology of the future; it is a concrete reality that is improving every aspect of our lives and work. Stay updated on upcoming developments to not miss the latest news!
But now, I ask you: do you think this blog was written by a human or by an Artificial Intelligence? 😊