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Daniel C. Dennett is one of the most influential philosophers of our time, perhaps best known in cognitive science for his multiple drafts (or “fame in the brain”) model of human consciousness, and to the secular community for his 2006 book Breaking the Spell. Author and co-author of two-dozen books, he’s the Austin B. Fletcher Professor of Philosophy, and Co-Director of the Center for Cognitive Studies at Tufts University, where he taught our very own Point of Inquiry host Lindsay Beyerstein.

Beyerstein and Dennett catch up to discuss Dennett’s newest book, From Bacteria to Bach and Back: The Evolution of Minds. It’s a fresh look at Dennett’s earlier work on the subject of consciousness, taken in new directions as he seeks a “bottom-up view of creation.” Join Dennett and Beyerstein as they discuss the how’s and why’s of consciousness, not just from an evolutionary and neurological standpoint, but also through the lenses of computer science and human culture.

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Researchers explore an intriguing phenomenon in quantum systems, drawing inspiration from a recent quantum computing experiment.


Earlier this year, researchers at the Flatiron Institute’s Center for Computational Quantum Physics (CCQ) announced that they had successfully used a classical computer and sophisticated mathematical models to thoroughly outperform a quantum computer on a task that some thought only quantum computers could solve.

Billionaire entrepreneur Elon Musk said on Tuesday (October 29) that Neuralink, the company he co-founded, should look to develop a brain implant which would alleviate neck and back pain. Neuralink develops makes Brain-Computer Interfaces (BCIs) which can be implanted in human brain. Musk’s latest comment came in a post he made on X (formerly Twitter), the social media platform he owns.

I am increasingly convinced that @Neuralink should prioritize making an implant that can eliminate back & neck pain.

Would greatly improve people’s happiness while awake, as well as enhance quality of sleep.

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What is information in biology? information is essential for analyzing data and testing hypotheses. But what is information in evolution, population genetics, levels of selection, and molecular genetics? Is computational biology transformational?

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Terrence William Deacon is an American neuroanthropologist. He taught at Harvard for eight years, relocated to Boston University in 1992, and is currently Professor of Anthropology and member of the Cognitive Science Faculty at the University of California, Berkeley.

“Our vision is for chip designers and engineering students, not just suppliers and manufacturers, to co-locate here, to create a value added ecosystem beyond just what it takes to build chips, and that’s how we’re going to create more value in the Phoenix economy,” Mack said.

A further three plants are also planned for the Phoenix site, which could bring TSMC’s total investment in the area to over $120 billion. Tech giant Apple has announced it will buy semiconductors from the fabrication plants.

The plants are anticipated to create 10,000 permanent jobs, and another 80,000 are expected to be created in the surrounding development.

As technology advances, the limitations of conventional electronic computers are becoming increasingly apparent, especially when tackling complex computational challenges. NP-complete problems, which grow exponentially with size, represent some of the toughest puzzles in computer science. These issues have significant implications across various fields, including biomedicine, transportation, and manufacturing. In the quest for more effective…

A new proof shows that an upgraded version of the 70-year-old Dijkstra’s algorithm reigns supreme: It finds the most efficient pathways through any graph.

It doesn’t just tell you the fastest route to one destination.


In an interview toward the end of his life, Dijkstra credited his algorithm’s enduring appeal in part to its unusual origin story. “Without pencil and paper you are almost forced to avoid all avoidable complexities,” he said.

Dijkstra’s algorithm doesn’t just tell you the fastest route to one destination. Instead, it gives you an ordered list of travel times from your current location to every other point that you might want to visit — a solution to what researchers call the single-source shortest-paths problem. The algorithm works in an abstracted road map called a graph: a network of interconnected points (called vertices) in which the links between vertices are labeled with numbers (called weights). These weights might represent the time required to traverse each road in a network, and they can change depending on traffic patterns. The larger a weight, the longer it takes to traverse that path.

Researchers at Berkeley Lab have advanced the understanding of magnetic skyrmions by developing techniques to image their 3D structures.

These nanoscale objects show promise for revolutionizing microelectronics through enhanced data storage capabilities and reduced energy consumption.

A difficult-to-describe nanoscale structure called the magnetic skyrmion holds potential for creating advanced microelectronic devices, including those with vast data storage capacities and significantly lower power requirements.

This finding, achieved independently by a team at Pennsylvania State University published in the same journal, holds immense potential for the development of nanophotonic devices.

Manipulating the flow of light in materials at small scales is crucial for creating efficient nanophotonic chips, the building blocks for future optical devices. In the realm of electronics, scientists can control the movement of electrons using magnetic fields.

The Lorentz force, exerted by the magnetic field, dictates the electron’s trajectory. However, this approach is inapplicable to photons – the fundamental particles of light – as they lack an electrical charge.