A colossal structure in the distant Universe is defying our understanding of how the Universe evolved.
In light that has traveled for 6.9 billion years to reach us, astronomers have found a giant, almost perfect ring of galaxies, some 1.3 billion light-years in diameter. It doesn’t match any known structure or formation mechanism.
The Big Ring, as the structure has been named, could mean that we need to amend the standard model of cosmology.
A groundbreaking discovery reveals how a hidden gene transfer between fungi and plants triggered Earth’s first ecosystems. This ancient process played a key role in the adaptation of plants to life on land.
Symbiotic transfer of lipids to mutualist fungi may have helped plants to colonize land 450 million years ago.
Patreon: https://bit.ly/3v8OhY7
Michael Levin is a Distinguished Professor in the Biology Department at Tufts University, where he holds the Vannevar Bush endowed Chair, and he is also associate faculty at the Wyss Institute at Harvard University. Michael and the Levin Lab work at the intersection of biology, artificial life, bioengineering, synthetic morphology, and cognitive science. Michael also appeared on the show in episode #151, which was all about synthetic life and collective intelligence. In this episode, Michael and Robinson discuss the nature of cognition, working with Daniel Dennett, how cognition can be realized by different structures and materials, how to define robots, a new class of robot called the Anthrobot, and whether or not we have moral obligations to biological robots.
The Levin Lab: https://drmichaellevin.org/
OUTLINE
00:00 Introduction.
02:14 What is Cognition?
08:01 On Working with Daniel Dennett.
13:17 Gatekeeping in Cognitive Science.
25:15 The Multi-Realizability of Cognition.
31:30 What are Anthrobots?
39:33 What Are Robots, Really?
59:53 Do We Have Moral Obligations to Biological Robots?
Robinson’s Website: http://robinsonerhardt.com
Robinson Erhardt researches symbolic logic and the foundations of mathematics at Stanford University. Join him in conversations with philosophers, scientists, weightlifters, artists, and everyone in-between.
Mark Howe (Graybiel Lab Alumni), Boston University.
“Probing Neuromodulator Signals for Learning and Action”
Talk was a part of the McGovern Institute’s 25th Anniversary Symposium.
The worlds of quantum mechanics and neural networks have collided in a new system that’s setting benchmarks for solving previously intractable optimization problems. A multi-university team led by Shantanu Chakrabartty at Washington University in St. Louis has introduced NeuroSA, a neuromorphic architecture that leverages quantum tunneling mechanisms to reliably discover optimal solutions to complex mathematical puzzles.
Published March 31 in Nature Communications, NeuroSA represents a significant leap forward in optimization technology with immediate applications ranging from logistics to drug development. While typical neural systems often get trapped in suboptimal solutions, NeuroSA offers something remarkable: a mathematical guarantee of finding the absolute best answer if given sufficient time.
“We’re looking for ways to solve problems better than computers modeled on human learning have done before,” said Chakrabartty, the Clifford W. Murphy Professor and vice dean for research at WashU. “NeuroSA is designed to solve the ‘discovery’ problem, the hardest problem in machine learning, where the goal is to discover new and unknown solutions.”
With a complete fly connectome in hand, researchers are taking the next step to model how brain circuits fuel function.
Researchers identified a region of the thalamus that predicts and nullifies the effects of movement on visual perception, enabling precise representation of the world.
At AACR in Chicago, Ernexa unveiled new data on its novel stem cell approach to treating ovarian cancer.
