Richard W. Hamming’s The Art of Doing Science and Engineering: Learning to Learn is more than a guide to technical disciplines; it’s a philosophical treatise on how to think effectively and pursue meaningful work. Hamming, known for his groundbreaking contributions to mathematics and computer science, offers insights that blend practical tools with timeless wisdom for anyone striving to make a difference in their field. In this post, I’ve distilled some of the book’s most impactful lessons and tools.
In today’s hyper-connected world, the demand for efficient, reliable, and scalable data transmission across networks is ever-increasing. Traditional approaches to data communication rely heavily on forwarding techniques, where intermediate nodes simply relay data packets. While effective in many scenarios, these methods struggle with packet loss, bandwidth constraints, and dynamic network topologies. Enter Random Linear Network Coding (RLNC)—a revolutionary paradigm that leverages coding theory to enhance network performance.
Bounded rationality is a concept in economics and decision theory that acknowledges the limitations of decision makers in terms of the information they have, their cognitive capabilities, and the finite time they have to make decisions. The term was coined by Herbert A. Simon, an economist and psychologist who noted that while traditional models of decision-making in economics and other fields assumed that individuals acted rationally to maximize their utility, real human behavior often deviates from this ideal due to practical constraints.
