Znanstvena metoda:
Strukture znanstvenega védenja, znanstvene aktivnosti in procesi.
Uporaba znanstvene metode v kognitivnih znanostih, zlasti pri razumevanju uma in inteligence.
Vpliv umetne inteligence in velikih jezikovnih modelov (LLM), kot je GPT, na znanstveno raziskovanje in kognitivne procese.
Uvod:
Uvod v kognitivne znanosti kot interdisciplinarni študij uma in inteligence, ki združuje psihologijo, nevroznanost, umetno inteligenco, filozofijo in lingvistiko.
Raziskovanje uma, zavesti, čustev, podzavesti, kvalij, ter različnih pristopov k psihologiji in filozofiji uma.
Povezava med kognitivnimi znanostmi, umetno inteligenco ter inteligentnimi sistemi, z vključitvijo GPT in LLM tehnologij za modeliranje kognitivnih funkcij.
Kognitivni paradoksi in koncepti:
Pregled ključnih paradigm v kognitivni znanosti, kot so Turingov test, variacije testa (TT, TTT, TTTT), in razprava o Searlovi kitajski sobi ter Einsteinovi knjigi.
Problem telo-duh in sodobne teorije zavesti. Razprava o LLM, kot je GPT: ali lahko takšni modeli razvijejo zavest, generativno sposobnost in inteligenco?
Raziskovanje lahkega in težkega vprašanja zavesti ter vpliv velikih jezikovnih modelov na te razprave.
Pregled trenutnih trendov in prihodnosti AI ter njihove vloge v kognitivnih znanostih.
Kognitivne arhitekture:
Teoretične osnove kognitivnih arhitektur in vloga LLM pri modeliranju kognitivnih procesov.
Pregled različnih kognitivnih arhitektur, vključno s sistemi tipa 1 in tipa 2.
Arhitekture podsistemov kognicije in integrirane celovite arhitekture.
Nizko in visokonivojske arhitekture ter njihova vloga pri simulaciji kognitivnih funkcij, z uporabo LLM in GPT modelov.
Kognitivne tehnike in metode:
Metode kognitivne nevroznanosti, kot so funkcionalno slikanje možganov, EEG in druge tehnike, ki se uporabljajo za proučevanje kognitivnih procesov.
Modeliranje kognicije: uporaba logike, pravil, konceptov, analogij, asociacij in povezav.
Kognitivni agenti in vloga umetne inteligence ter velikih jezikovnih modelov, kot so GPT, pri modeliranju inteligentnih kognitivnih sistemov.
Praktična uporaba izbranih kognitivnih tehnik in orodij, kot so simulacije in napovedne analize, ki jih omogočajo AI in GPT.
Praktično usposabljanje:
Praktična uporaba izbranih tehnik in orodij kognitivnih znanosti, vključno z uporabo LLM in GPT za reševanje kognitivnih izzivov.
Razvijanje kognitivnih modelov in sistemov ter aplikacije GPT za simulacijo in analizo kognitivnih procesov v realnem času.
Scientific Method:
Structures of scientific knowledge, scientific activities, and processes.
Application of the scientific method in cognitive science, particularly in understanding the mind and intelligence.
The impact of artificial intelligence and large language models (LLMs), such as GPT, on scientific research and cognitive processes.
Introduction:
Introduction to cognitive science as an interdisciplinary study of the mind and intelligence, combining psychology, neuroscience, artificial intelligence, philosophy, and linguistics.
Exploration of the mind, consciousness, emotions, the subconscious, qualia, and various psychological and philosophical approaches to the mind.
The connection between cognitive science, artificial intelligence, and intelligent systems, with the inclusion of GPT and LLM technologies for modeling cognitive functions.
Cognitive Paradoxes and Concepts:
Review of key paradigms in cognitive science, such as the Turing Test and its variations (TT, TTT, TTTT), and discussions of Searle’s Chinese Room and Einstein’s book.
The mind-body problem and contemporary theories of consciousness. Discussions on LLMs like GPT: Can such models develop consciousness, generative ability, and intelligence?
Exploration of the easy and hard problems of consciousness and the impact of large language models on these debates.
Review of current trends and the future of AI and their role in cognitive sciences.
Cognitive Architectures:
Theoretical foundations of cognitive architectures and the role of LLMs in modeling cognitive processes.
Overview of different cognitive architectures, including Type 1 and Type 2 systems.
Subsystem architectures of cognition and integrated comprehensive architectures.
Low- and high-level architectures and their role in simulating cognitive functions using LLMs and GPT models.
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, such as GPT, in modeling intelligent cognitive systems.
Practical application of selected cognitive techniques and tools, such as simulations and predictive analyses enabled by AI and GPT
.
Practical Training:
Practical application of selected cognitive science techniques and tools, including the use of LLMs and GPT to solve cognitive challenges.
Developing cognitive models and systems and applying GPT to simulate and analyze cognitive processes in real-time.