Topic: machine learning

Harvard University has released a comprehensive four-volume textbook series on machine learning systems, covering foundational concepts, scaling techniques, agentic AI, and physical AI. This resource is significant as it provides an in-depth exploration of the field, catering to both academic study and practical application needs.

Nathan Lambert and Sebastian Raschka, machine learning experts, discuss the state of artificial intelligence in 2026, focusing on large language models, coding advancements, scaling laws, China's role, autonomous agents, GPU technology, and the potential for general AI. The discussion highlights key trends and challenges shaping AI development globally.