Levente Szabados, who graduated as a programmer in the 90s, is a pioneering deep tech (scientific technology) leader with extensive experience in artificial intelligence, deep learning, data science, and cognitive sciences. He is the co-founder and scientific advisor of Neuron Solutions, a company that provides AI-related consulting, training, and customized system development services. He is also a respected academic, currently a lecturer at SRH Hochschule in Heidelberg, Frankfurt School of Finance and Management, and a guest lecturer at Aivancity in Paris. True to his motto, "The mind is my profession," Levente combines his professional aspirations with his interest in Buddhist teachings and cognitive sciences.

You will have the opportunity to meet him in our upcoming course, where he will provide a closer look into the world of AI and share insights about his personal career journey.

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Why did you start learning programming?

I got my first computer in the 80s, and I was captivated by the world of computing from an early age. I decided back then that this would be my life's path. Although I briefly explored other directions, AI ultimately drew me back into the field of IT. For me, the study of the human mind is the most exciting, and artificial intelligence applications aim to model this.

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Why do you think it's good to work in this field?

From a practical standpoint, one only needs to look at how extensively digital tools are integrated into the operations of companies and organizations across industries. For instance, agriculture, which might not be immediately associated with technology, is reliant on an astonishing array of digital tools, including AI applications, for precise spraying and irrigation support. If artificial intelligence systems can play such a significant role even in a potato field, it is easy to imagine how important it is, for example, in the financial or energy sectors. The world simply could not move forward without computer scientists.

Moreover, beyond practical reasons, I find this field incredibly fascinating. Alan Turing once said that in programming, we model human thinking and try to transfer it to machines. This applies not only to AI but to programming in general. Examining the human mind is a wonderful thing, so programming is also an excellent field for self-improvement. During algorithmization, we break down a problem into elementary steps and seek solutions based on some mental strategy.

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What has been the most exciting project you've worked on so far?

I took part in a research to help diagnose the early signs of Alzheimer's disease. By studying the brainwaves of mice and rats, we tried to identify patterns that could predict the development of the disease. Certain chemical interventions could produce Alzheimer's-like symptoms in these animals, and we investigated whether we could detect these signs of change in the functioning of the nervous system. It was fascinating to create a tool that treated patterns in the functioning of the nervous system as a predictive task, while also revealing connections that researchers could not even think of before.

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In your opinion, what are the most important skills for junior developers in the current job market?

The most valuable hard skill, in my opinion, is understanding a specific language or software not just at the surface level but also from the point of view of how the inventors of the system thought. This is often a secondary skill that isn't explicitly taught, but I believe it greatly aids in understanding why certain dialects exist in a language.

In terms of soft skills, the most important one is the ability to quickly adapt and gain a foothold in a new area. The tech world is constantly evolving, so developers also need to adapt over time. Success doesn't come from what we already know but from our ability to learn quickly.

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As part of our course, you will talk about the application of AI in software development. Why do you think this is an important topic for today's programmers?

AI is no longer the future; it is the present. The emergence of large language models not only affects how we create content, it clearly affects how we write code, as well as how we view the role of software development. Greater autonomy of software agents based on language models can bring a paradigm shift to software development, and it is very important to be a part of it.

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What advice would you give to a beginner on starting their career?

Do, do, do. Learning to program in theory is a painful and slow process. You truly understand a system when you interact with it and make mistakes a few times. The difference between an experienced programmer and a less experienced one isn't that the former doesn't make mistakes, but that they wear a helmet when they do.

I would give the same advice for learning: you have to take action, try out ideas, and experiment. What's also important is not to stop at the point where something works. Learn why it works. I often tell data scientists, „Our work is interesting in two situations. One is when something doesn't work, and you need to understand why. The other is when something works, and you need to understand why."

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Why is education important to you?

There is a huge shortage of IT professionals on the market, which I also observe, and surveys support this claim. Companies often find themselves unable to start an IT project because they lack the necessary talent. We can only fill this gap with education.

Additionally, I believe that knowledge is not something that exists solely in one person's mind. It is maintained through dialogue and reflection among many people. If people stop talking about a particular technology, it essentially dies out. A prime example of this is the Fortran language: there is practically no conversation about it, which is why there are very few professionals willing to maintain systems written in Fortran, even though they are still running critical banking transaction systems today. We can prevent this phenomenon by involving new people in the conversation, and the best way to do that is through teaching.

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