{"id":151785,"date":"2025-06-24T19:43:47","date_gmt":"2025-06-24T19:43:47","guid":{"rendered":"https:\/\/teknomers.com\/en\/ive-finished-the-pau-and-i-want-to-focus-on-ai-what-should-i-study-four-experts-answer-the-question\/"},"modified":"2025-06-24T19:43:48","modified_gmt":"2025-06-24T19:43:48","slug":"ive-finished-the-pau-and-i-want-to-focus-on-ai-what-should-i-study-four-experts-answer-the-question","status":"publish","type":"post","link":"https:\/\/teknomers.com\/en\/ive-finished-the-pau-and-i-want-to-focus-on-ai-what-should-i-study-four-experts-answer-the-question\/","title":{"rendered":"I’ve finished the PAU and I want to focus on AI. What should I study? Four experts answer the question."},"content":{"rendered":"\n

\u201cI want to dedicate myself to artificial intelligence.\u201d This phrase is increasingly being heard among those who have just completed their university entrance exams, perhaps with the same conviction previously associated with fields like medicine or engineering. However, this statement holds a \u00a0trap\u00a0: dedicating oneself to AI can mean many things<\/strong>, and not all paths require the same qualifications. Four specialized voices\u2014Pilar Manch\u00f3n<\/a>, Antonio Ortiz<\/a>, Andr\u00e9s Torrubia<\/a>, and Jon Hern\u00e1ndez<\/a>\u2014help us dissect this declaration. Their insights clarify what to study, what skills to develop, and what pitfalls to avoid so that one doesn\u2019t lose their way.<\/p>\n

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Where to Start: Understanding What it Means to Dedicate Yourself to AI<\/strong><\/h2>\n

We invite you to dive into a nuanced report. There is no single correct answer here: each expert offers a distinct perspective, and in this contrast lies what is truly interesting. Not everyone envisions the future of this discipline the same way, nor do they agree on what to study, how to train, or where to begin. Nevertheless, they highlight signs, warnings, and evolving certainties that can guide those looking to carve their own path in a world that is still being defined and is likely to demand a prominent role in the future.<\/p>\n

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\"Pilar\n <\/div>\n<\/div>\n

The first step before choosing a career is to understand that \u201cAI\u201d is not a single profession. Within this field, there are many different profiles<\/strong>, from those who specialize in maximizing tools like ChatGPT or Gemini without needing to know the underlying mathematics, to those aiming to delve deep into the system’s core. Pilar Manch\u00f3n, Senior Director of Engineering at Google, summarizes it well: \u201cThere are options for everyone, depending on whether you feel more comfortable being a user of these tools [\u2026] versus those who want to get into the system\u2019s inner workings, wanting to know exactly how it works and inventing a way that makes it more efficient.\u201d<\/p>\n

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\n \"Antonio
\n \"Antonio\n <\/div>\n<\/div>\n

A similar distinction is made by Antonio Ortiz, an AI communicator and co-founder of Weblogs SL<\/a>, who currently hosts the podcast ‘Monos Estoc\u00e1sticos<\/a>‘. Ortiz emphasizes that it should not be assumed that everyone wanting to work in this field must become an architect of models or a specialist in machine learning. \u201cIf someone says, \u2018I need to dedicate myself to artificial intelligence,\u2019 does that mean I have to become an expert in machine learning, learn to train an LLM, work with NVIDIA graphs, and focus on designing a transformer model?\u201d he queries.<\/p>\n

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This complexity is also highlighted by Jon Hern\u00e1ndez, an AI communicator with a YouTube channel followed by over 380,000 people<\/a>. His self-taught experience allows him to draw a clear line between those who create AI and those who harness it as a tool. \u201cI think we need to differentiate between two paths, right? One is dedicating oneself to artificial intelligence itself [\u2026] The other is how to leverage artificial intelligence<\/strong> in this huge opportunity that has opened up for everyone.\u201d<\/p>\n

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\n \"Jon
\n \"Jon\n <\/div>\n<\/div>\n

It\u2019s clear that \u201cdedicating oneself to AI\u201d does not imply a singular path or a single professional profile. For some, the journey will involve understanding how models are built from the ground up. For others, it may be about exploring the limits of existing tools. But before diving in, there\u2019s an unavoidable question: what should one study?<\/p>\n

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Choosing what to study is no easy task. However, there seems to be an undeniable principle for those who wish to delve into AI: a solid foundation is essential. This is the belief of Andr\u00e9s Torrubia, co-founder of the Institute of Artificial Intelligence<\/a>. He summarizes it emphatically: \u201cTo this day, I would recommend to those taking university entrance exams to study the fundamental subjects that will never change: mathematics, physics, and programming paradigms, knowing that increasingly, a lot of programming will be handled by an artificial intelligence system.\u201d<\/p>\n

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\n \"Andres
\n \"Andres\n <\/div>\n<\/div>\n

A view echoed by Antonio Ortiz: \u201cArtificial intelligence is software,\u201d he reminds us. \u201cSo whatever discipline, whether vocational training or university, should help you build better software.\u201d Ortiz advocates for broad-spectrum studies that do not close doors and allow for a solid foundation in software development: \u201cI would recommend investing in foundational knowledge<\/strong> and building a strong intellectual base, rather than seeking shortcuts by learning just the techniques that the market demands now.\u201d<\/p>\n

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Jon Hern\u00e1ndez adds another dimension to the conversation: the importance of personal motivation. \u201cI believe we should advise young people to study what they like and are passionate about,\u201d he asserts. His argument is that beyond trends or current job prospects, the decisive factor will be knowing how to apply artificial intelligence in one’s area of interest: \u201cIf they have the necessary passion to do so and, importantly, apply artificial intelligence to what they are studying, I think they will become the best professionals in that field.\u201d He even suggests a curious idea: \u201cThe most demanded profession in five years will be philosophers.\u201d<\/p>\n

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What University Provides (and What It Doesn\u2019t)<\/h2>\n

University remains a powerful avenue for entering the world of artificial intelligence, but it is not the only option. Pilar Manch\u00f3n defends formal education as a valuable tool, especially for what it offers beyond academic content: \u201cYou gain not only flexible curricula where you can study practically anything but also, through this experience, you interact with the world<\/strong> [\u2026], socializing with others.\u201d However, she notes that while this route is \u201cnecessary, it is not sufficient.\u201d<\/p>\n

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Andr\u00e9s Torrubia offers a similar yet more structured approach: \u201cUniversity provides three things that start with the letter C,\u201d he explains:<\/p>\n