Abstract:
The rapid development of large language models over the past few years has led us to experiment with reasoning and recognize the potential usefulness of models in science. In the last two years, models have emerged that are gradually overcoming successive barriers in advanced deduction and are able to emulate the work of scientists to a certain extent. In this lecture, I will discuss the latest benchmarks verifying these achievements. I will say whether a successful mathematical education is possible when combining AI, “flipped classroom” and modern tools like Jupyter Notebooks. I will discuss whether we are actually close to AI surpassing mathematicians and what this means in practical science. We will see how various new techniques, including reasoning token models and multi-agent models, achieve high effectiveness in some types of reasoning, but still fail completely in others. I will try to argue why this is the case and whether the end of scientific institutions is upon us.
Zoom:
Zoom link: [
LINK]
Meeting ID: 813 0444 2723
Passcode: 812303
Location: lecture hall, Al. Lotników 32/46 ground floor/Zoom
