In this reflective analysis, the podcast examines the evolving landscape of artificial intelligence by the end of 2025, noting a significant shift in how researchers perceive machine intelligence. The text highlights how Chain of Thought reasoning and reinforcement learning have moved models beyond simple probability, allowing them to solve complex tasks and challenge previous scaling limits. As software developers increasingly adopt these tools, the industry is transitioning from skepticism toward a broader acceptance of AI as a collaborative partner. Furthermore, the podcast suggests that current architectures are proving more capable of abstract reasoning than critics once predicted, potentially paving a path toward general intelligence. While exploring new technical paradigms, the piece concludes that the most critical hurdle for the future remains the mitigation of existential risks. This overview serves as a defense of the sophistication of large language models against the "stochastic parrot" narrative.