Data Skeptic
Modeling evolutionary processes goes way beyond the Hardy-Weinberg Equilibrium we all learned in biology class. Natural selection comes from many sources like resources availability, mate preferences, competition. Modeling entire populations of organisms of different species is the holy grail of digital evolution. Join our discussion with evolutionary biologist and software engineer Ben Haller to learn about his work on SLiM and how it helps other biologists model population genetics over time.
info_outline Behavioral GeneticsData Skeptic
It’s almost impossible to think about animal behavior without thinking of dogs! Our canine friends are a subspecies of wolf that has been co-evolving with us for tens of thousands of years. The transition from wolf to pet has required intense natural and artificial selection for behaviors that allow dogs to live alongside humans, but behavior is not so simple. Join us for a discussion with Dr. Jessica Hekman and learn about dog welfare, behavioral genetics, and the quest to understand the dogs in our lives.
info_outline Signal in the NoiseData Skeptic
In this episode, we are joined by Barbara Webb and Anna Hadjitofi. Barbara runs the Insect Robotics lab at the University of Edinburgh, and Anna is a PhD student at the School of Informatics at the university. She is interested in studying and understanding the neural mechanism of the honeybee waggle dance. They join us to discuss the paper: Dynamic antennal positioning allows honeybee followers to decode the dance.
info_outline Pose TrackingData Skeptic
Many researchers and students have painstakingly labeled precise details about the body positions of the creatures they study. Can AI be used for this labeling? Of course it can! Today's episode discusses Social LEAP Estimates Animal Poses (SLEAP), a software solution to train AI to perform this tedious but important labeling work.
info_outline Modeling Group BehaviorData Skeptic
Our guest in this episode is Sebastien Motsch, an assistant professor at Arizona State University, working in the School of Mathematical and Statistical Science. He works on modeling self-organized biological systems to understand how complex patterns emerge.
info_outline Advances in Data LoggersData Skeptic
Our guest in this episode is Ryan Hanscom. Ryan is a Ph.D. candidate in a joint doctoral evolution program at San Diego State University and the University of California, Riverside. He is a terrestrial ecologist with a focus on herpetology and mammalogy. Ryan discussed how the behavior of rattlesnakes is studied in the natural world, particularly with an increase in temperature.
info_outline What You Know About Intelligence is Wrong (fixed)Data Skeptic
We are joined by Hank Schlinger, a professor of psychology at California State University, Los Angeles. His research revolves around theoretical issues in psychology and behavioral analysis. Hank establishes that words have references and questions the reference for intelligence. He discussed how intelligence can be observed in animals. He also discussed how intelligence is measured in a given context.
info_outline Animal Decision MakingData Skeptic
On today’s episode, we are joined by Aimee Dunlap. Aimee is an assistant professor at the University of Missouri–St. Louis and the interim director at the Whitney R. Harris World Ecology Center. Aimee discussed how animals perceive information and what they use it for. She discussed the connection between their environment and learning for decision-making. She also discussed the costs required for learning and factors that affect animal learning.
info_outline Octopus CognitionData Skeptic
We are joined by Tamar Gutnick, a visiting professor at the University of Naples Federico II, Napoli, Italy. She studies the octopus nervous system and their behavior, focusing on cognition and learning behaviors. Tamar gave a background to the kind of research she does — lab research. She discussed some challenges with observing octopuses in the lab. She discussed some patterns observed by the octopus lifestyle in a controlled setting. Tamar discussed what they know about octopus intelligence. She discussed the octopus nervous system and why they are unique compared to other animals. She...
info_outline Optimal ForagingData Skeptic
Claire Hemmingway, an assistant professor in the Department of Psychology and Ecology and Evolutionary Biology at the University of Tennessee in Knoxville, is our guest today. Her research is on decision-making in animal cognition, focusing on neotropical bats and bumblebees. Claire discussed how bumblebees make foraging decisions and how they communicate when foraging. She discussed how they set up experiments in the lab to address questions about bumblebees foraging. She also discussed some nuances between bees in the lab and those in the wild. Claire discussed factors that drive an animal's...
info_outlineFake news attempts to lead readers/listeners/viewers to conclusions that are not descriptions of reality. They do this most often by presenting false premises, but sometimes by presenting flawed logic.
An argument is only sound and valid if the conclusions are drawn directly from all the state premises, and if there exists a path of logical reasoning leading from those premises to the conclusion.
While creating a theorem does feel to most mathematicians as a creative act of discovery, some theorems have been proven using nothing more than search. All the "rules" of logic (like modus ponens) can be encoded into a computer program. That program can start from the premises, applying various combinations of rules to inference new information, and check to see if the program has inference the desired conclusion or its negation. This does seem like a mechanical process when painted in this light. However, several challenges exist preventing any theorem prover from instantly solving all the open problems in mathematics. In this episode, we discuss a bit about what those challenges are.