Miloš Švaňa

ai, python, software engineering, decision-making and more

Category: Uncategorized

  • Why use mathematics to make decisions

    I don’t have to tell you that making good decisions is important both in business and your personal life. What you may not know is that we have a scientific field developing decision-making methods based on mathematics with the singular goal of helping you make better decision.

    But why on Earth should you bother with complicated mathematical formulas instead of relying on our gut instincts? True, gut instincts are useful. If you simply need to buy something to eat, pulling out Excel to determine the optimal decision is an overkill. And even worse, if you find yourself in a fight, you simple don’t have the time for a detailed analysis.

    But our intuitions and reflexes are not silver bullets. They can make mistakes, especially when solving problems our ancestors from 10 thousand years ago didn’t have to deal with. In such situations, formal decision-making methods based on some interesting mathematics can help you make better choices. Here are six reasons why.

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  • Would I do a PhD again?

    In May 2024 I successfully defended my dissertation and ended a 5-year-long adventure that was doing a PhD. Knowing what I know now, would I do it again?

    Answering this question is anything but straightforward. So instead of doing it directly, I want to talk about different aspects of doing a PhD including traveling, teaching, money, writing paper, and dealing with bureaucracy. I hope this reflection helps those of you who are currently thinking about starting a PhD, but are unsure if it’s the right path for you.

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  • The art of testing LLM-powered apps

    Testing is crucial for producing reliable software. As an industry, we know a lot about testing, or at least about testing conventional software. The recent democratization of AI and LLMs enabled developers and software companies to easily integrate text or image generation features into their products. LLMs possess unique properties that make testing LLM-powered software quite challenging. Why is this the case, and how can we test such software properly?

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