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Show a child a dog four times and a cat four times, and they’ll know the difference for the rest of their life. Computers aren’t that smart yet. Before a computer can truly tell the difference, it needs to be fed thousands of images of dogs and cats.<img src="https://cms.aihub-oost.nl/uploads/d4aoo6_D3f_Lrtbmi_GQ_8_YAPBJKM_7_Ir_Tiur7_C_Mul_Cck_8984eeaa2f.jpeg" alt="d4aoo6D3fLrtbmiGQ8YAPBJKM7IrTiur7CMulCck.jpeg" srcset="https://cms.aihub-oost.nl/uploads/thumbnail_d4aoo6_D3f_Lrtbmi_GQ_8_YAPBJKM_7_Ir_Tiur7_C_Mul_Cck_8984eeaa2f.jpeg 195w,https://cms.aihub-oost.nl/uploads/small_d4aoo6_D3f_Lrtbmi_GQ_8_YAPBJKM_7_Ir_Tiur7_C_Mul_Cck_8984eeaa2f.jpeg 500w,https://cms.aihub-oost.nl/uploads/medium_d4aoo6_D3f_Lrtbmi_GQ_8_YAPBJKM_7_Ir_Tiur7_C_Mul_Cck_8984eeaa2f.jpeg 750w,https://cms.aihub-oost.nl/uploads/large_d4aoo6_D3f_Lrtbmi_GQ_8_YAPBJKM_7_Ir_Tiur7_C_Mul_Cck_8984eeaa2f.jpeg 1000w," sizes="100vw" width="1500" height="1200">“The distinction between a dog and a cat isn’t that relevant, but if you want to teach a computer to drive a self-driving car, the distinction between a child and a rabbit is a matter of life and death,” says Johannes Schmidt-Hieber, professor of statistics, the youngest professor at the University of Twente, and an AI expert.<h2>Excerpt</h2>Schmidt-Hieber told INN’Twente on Twente.com: “Our brains are much more efficient at image recognition. For example, a computer gets confused if there are multiple objects in an image, whereas our brains automatically filter that information. A student in my group had the computer come up with new dishes based on a large number of recipes. And based on the style of certain painters, the computer can also create new paintings. But it’s always a derivative of what already exists; coming up with its own style is still a bridge too far.”Still, the professor is enthusiastic about the importance of AI. <blockquote>Hospitals have a massive amount of data available. By using AI to link data and compare past experiences—for example, in cancer treatment—you can choose the most successful combination of medications and radiation therapy.</blockquote><h2>Statistics as a Starting Point</h2>Schmidt-Hieber is considered an expert in the field of AI, particularly regarding its mathematical aspects. “Computer science has, of course, been applying artificial intelligence for some time now. With statistics as my starting point, I focus more on how we can interpret the results. Using new mathematical techniques, you can analyze which methods work and which don’t—and why. How large does the neural network need to be to ensure the method works optimally? The workings of the human brain have not yet been fully unraveled, but with computers, this is easier to uncover. That has long been an overlooked aspect; everything was focused on applications. But to truly make progress, we’ll also have to delve into the mathematics behind how it works.”The young professor leads workshops and conferences, primarily for academics. Beyond the academic world, he also sees a lot of interest from the research departments of companies like Google and Microsoft. Given the rapid pace of development, he advocates introducing students to AI and deep learning early on in their education. “They’ll have to work with it in the future, so it’s important for the education system to address this early on.”

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Show a child a dog four times and a cat four times, and they’ll know the difference for the rest of their life. Computers aren’t that smart yet. Before a computer can truly tell the difference, it needs to be fed thousands of images of dogs and cats.