Znanstvena metoda: Strukture znanstvenega znanja, znanstvene aktivnosti in raziskovalni procesi. Uporaba znanstvene metode v kognitivnih znanostih, zlasti pri empiričnem in teoretičnem razumevanju uma in inteligence. Vpliv umetne inteligence in velikih jezikovnih modelov (LLM; npr. GPT) na sodobno znanstveno raziskovanje ter na modeliranje, analizo in razlago kognitivnih procesov.
Uvod: Uvod v kognitivne znanosti kot interdisciplinarni študij uma in inteligence, ki povezuje psihologijo, nevroznanost, umetno inteligenco, filozofijo in lingvistiko. Raziskovanje uma, zavesti, čustev, podzavesti in kvalij ter pregled različnih pristopov v psihologiji in filozofiji uma.
Povezava med kognitivnimi znanostmi, umetno inteligenco in inteligentnimi sistemi, z uporabo velikih jezikovnih modelov (LLM; npr. GPT) za modeliranje in preučevanje kognitivnih funkcij.
Kognitivni paradoksi in koncepti: Pregled ključnih paradigm v kognitivni znanosti, kot so Turingov test in njegove variacije (TT, TTT, TTTT), ter razprava o Searlovi kitajski sobi in izbranih klasičnih delih. Problem telo–duh in sodobne teorije zavesti. Razprava o velikih jezikovnih modelih (LLM; npr. GPT): ali lahko takšni modeli izkazujejo oblike inteligence, generativne sposobnosti ali elemente kognitivnega delovanja.
Raziskovanje lahkega in težkega problema zavesti ter vpliv sodobnih AI in LLM pristopov na te razprave. Pregled aktualnih trendov in prihodnjega razvoja umetne inteligence ter njihove vloge v kognitivnih znanostih.
Kognitivne arhitekture: Teoretične osnove kognitivnih arhitektur in vloga velikih jezikovnih modelov pri modeliranju kognitivnih procesov. Pregled različnih kognitivnih arhitektur, vključno s sistemi tipa 1 in tipa 2. Arhitekture podsistemov kognicije ter integrirane celovite arhitekture.
Nizko- in visokonivojske arhitekture ter njihova vloga pri simulaciji kognitivnih funkcij, tudi z uporabo sodobnih LLM pristopov.
Kognitivne tehnike in metode: Metode kognitivne nevroznanosti, kot so funkcionalno slikanje možganov, EEG in druge tehnike za proučevanje kognitivnih procesov. Modeliranje kognicije z uporabo logike, pravil, konceptov, analogij, asociacij in povezav. Kognitivni agenti ter vloga umetne inteligence in velikih jezikovnih modelov pri razvoju inteligentnih kognitivnih sistemov. Praktična uporaba izbranih kognitivnih tehnik in orodij, kot so simulacije in napovedne analize, omogočene z AI in LLM.
Praktično usposabljanje: Praktična uporaba izbranih tehnik in orodij kognitivnih znanosti, vključno z uporabo velikih jezikovnih modelov (LLM; npr. GPT) za reševanje kognitivnih izzivov. Razvijanje kognitivnih modelov in sistemov ter uporaba LLM za simulacijo, analizo in interpretacijo kognitivnih procesov v realnem času.
Scientific Method: Structures of scientific knowledge, scientific activities, and research processes. Application of the scientific method in cognitive sciences, particularly in the empirical and theoretical understanding of the mind and intelligence. The impact of artificial intelligence and large language models (LLMs; e.g., GPT) on contemporary scientific research and on the modeling, analysis, and interpretation of cognitive processes.
Introduction: Introduction to cognitive sciences as an interdisciplinary study of the mind and intelligence, integrating psychology, neuroscience, artificial intelligence, philosophy, and linguistics. Exploration of the mind, consciousness, emotions, the subconscious, and qualia, as well as an overview of different approaches in psychology and the philosophy of mind. The relationship between cognitive sciences, artificial intelligence, and intelligent systems, with the use of large language models (LLMs; e.g., GPT) for modeling and examining cognitive functions.
Cognitive Paradoxes and Concepts: Overview of key paradigms in cognitive science, such as the Turing Test and its variations (TT, TTT, TTTT), and discussion of Searle’s Chinese Room and selected classical works. The mind–body problem and contemporary theories of consciousness. Discussion of large language models (LLMs; e.g., GPT): whether such models can exhibit forms of intelligence, generative capabilities, or elements of cognitive functioning. Examination of the easy and hard problems of consciousness and the influence of modern AI and LLM approaches on these debates. Overview of current trends and future developments in artificial intelligence and their role in cognitive sciences.
Cognitive Architectures: Theoretical foundations of cognitive architectures and the role of large language models in modeling cognitive processes. Overview of different cognitive architectures, including Type 1 and Type 2 systems. Architectures of cognitive subsystems and integrated comprehensive architectures. Low- and high-level architectures and their role in simulating cognitive functions, including the use of contemporary LLM approaches.
Cognitive Techniques and Methods: Methods of cognitive neuroscience, such as functional brain imaging, EEG, and other techniques used to study cognitive processes. Cognitive modeling using logic, rules, concepts, analogies, associations, and connections. Cognitive agents and the role of artificial intelligence and large language models in the development of intelligent cognitive systems. Practical application of selected cognitive techniques and tools, such as simulations and predictive analyses enabled by AI and LLMs.
Practical Training: Practical application of selected techniques and tools in cognitive sciences, including the use of large language models (LLMs; e.g., GPT) to address cognitive challenges. Development of cognitive models and systems and the use of LLMs for real-time simulation, analysis, and interpretation of cognitive processes.