Mainstream artificial intelligence (AI) solutions, while achieving considerable success in areas such as classification, generation, and natural language understanding, still face several notorious, long-standing challenges. These include unexpected classification errors, hallucinations in generative models, and catastrophic forgetting, among others.
Addressing these issues requires...
Large language models (LLMs) face challenges with complex
probabilistic, causal, and counterfactual reasoning, yet they
demonstrate promising capabilities in the automated construction of both
qualitative and quantitative probabilistic and causal models. This talk
provides an overview of current benchmarks for causal reasoning in LLMs,
methods for extracting knowledge from LLMs,...
Reactivity is a fundamental aspect of various processes,
including chemical vapor deposition and catalysis. Computer simulations
have become indispensable in modern industrial development,
serving not only to shorten research and development timelines but also to
deepen our understanding of these processes. The advent of advanced
quantum chemical and force field-based methods,...
Quantum phase transitions and symmetry-protected topological
phases remain at the forefront of quantum physics research. This
presentation highlights recent advancements in these fields, focusing on
two key contributions:
- Realizing the Haldane Phase with Qutrits: We
discuss the successful creation of the spin-1 Haldane phase on a qudit
quantum processor, as detailed in...
In this contribution, I will briefly discuss the differences and
similarities between industrial and academic research and provide an
example of a joint project on magnetic systems and quantum computing.
Furthermore, I will summarize the most relevant research papers published
in our group on quantum computing, including those on embedding, the cost
analysis of pharmaceutical and...
Mainstream artificial intelligence (AI) solutions, while achieving considerable success in areas such as classification, generation, and natural language understanding, still face several notorious, long-standing challenges. These include unexpected classification errors, hallucinations in generative models, and catastrophic forgetting, among others.
Addressing these issues requires...
The ELTE AI Department, in collaboration with Bosch, addresses industrial challenges by leveraging AI expertise to develop innovative solutions, such as autonomous driving and production optimization in factories. One of these projects focuses on welding line detection. In modern industrial settings, accurately identifying and verifying welding lines is essential for ensuring product quality....
