Part 5/13:
He explains that while models like GPT-4 might show incremental improvements, the increase comes at the cost of higher computational load and hallucination problems—where the AI confidently states falsehoods. Consequently, the supposed "advancements" are often the result of more resource-intensive approaches that don't genuinely advance AI comprehension or applicability.