Seth Lloyd discusses the concept of e-spying and data mining by large tech companies like Amazon, Facebook, Google, and Microsoft. He highlights the significant computational power devoted to collecting and analyzing personal data, totaling about an exaflop, which is equivalent to the combined computing power of the world’s 500 most powerful supercomputers. Lloyd explains that … Read more
Terrence J. Sejnowski discusses the advancements in deep learning and their impact on machine learning. Deep learning has evolved significantly over the past few decades, thanks to increased computer power and large datasets from the internet. Deep neural networks with multiple layers have proven effective in tasks like object recognition and speech recognition, revolutionizing these … Read more
Rodney A. Brooks discusses the complexity and nuances of the terms “think” and “intelligence,” which are often used to discuss machines and their capabilities. These terms encompass various aspects, mechanisms, and levels of understanding, making it challenging to answer questions like, “Can machines think?” or predict when machines will reach human-level intelligence. Brooks provides examples, … Read more
James J. O’Donnell reflects on the diverse ways in which the term “thinking” is used in human language, ranging from mundane decisions to complex introspections and emotions. He questions whether machines can experience confusion, cognitive dissonance, dreaming, wonder, forgetfulness, self-esteem, or other human-like mental states. O’Donnell believes that such characteristics are beyond the capabilities of … Read more
Cesar Hidalgo challenges the notion of machines that “think” and argues that thinking involves processing information within a larger context, not just the individual level. He introduces the concept of “little thinking,” which occurs at the individual level and is context-dependent. In contrast, “large thinking” involves processing information within systems where units like machines or … Read more
Rolf Dobelli dismisses the widespread fear that artificial intelligence (AI) will pose a significant danger to humanity. He distinguishes between two types of AI development: Humanoid Thinking (AI that extends human thinking) and Alien Thinking (radically new AI thinking). Most AI today falls under Humanoid Thinking, designed to solve specific problems set by humans. These … Read more
Nicholas Humphrey discusses the concept of introspective access and how it distinguishes conscious agents like humans from machines. Introspective access refers to the ability to be aware of and communicate one’s thoughts and mental states. Humphrey highlights that while humans possess this capacity and can describe what’s happening in their minds, machines do not yet … Read more
Irene Pepperberg argues that machines excel at computation but lack true thinking abilities, particularly in terms of vision and creativity. Machines rely on algorithms and programs created by humans to solve complex problems, provide directions, or perform tasks efficiently. However, Pepperberg emphasizes that machines do not possess the capacity for vision in the sense of … Read more
W. Tecumseh Fitch argues that despite advances in computing power, current computers don’t possess true thinking abilities like organic minds. He introduces the concept of nano-intentionality, the ability of living cells to change their material form in response to their environment, which he claims is an essential feature of organic minds but absent in silicon-based … Read more
Daniel C. Dennett discusses the concept of the Singularity, where AI surpasses human intelligence. He argues that the Singularity, while an intriguing idea, distracts from a more immediate concern: the growing dependence on artificial agents that can’t truly think but are becoming integral to various aspects of our lives. Dennett highlights the increasing reliance on … Read more