Speakers

Sara Walker

Professor, School Of Earth and Space Exploration

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Sara Walker is an astrobiologist and theoretical physicist interested in the origin of life and how to find life on other worlds. While there are many things to be solved, she is most interested in whether or not there are ‘laws of life’ - related to how information structures the physical world - that could universally describe life here on Earth and on other planets.

At Arizona State University she is Deputy Director of the Beyond Center for Fundamental Concepts in Science, Associate Director of the ASU-Santa Fe Institute Center for Biosocial Complex Systems and Associate Professor in the School of Earth and Space Exploration. She is also Co-founder of the astrobiology-themed social website SAGANet.org, and is a member of the Board of Directors of Blue Marble Space. She is active in public engagement in science, with appearances at the World Science Festival, and on "Through the Wormhole" and NPR's Science Friday

Talk Title: The Natural History of Information

Abstract: Currently there exists no general theory for what life is. This makes it challenging to anticipate how a more fundamental understanding of life could inform the design (or evolution) of artificial life forms and/or artificial intelligences, or what the role of these will play in the future evolution of Earth and its biosphere. For artificial systems, designed in software, the role of information is clear, whereas for biological and other physical systems it is less so. Unifying the long history of biological evolution with what is happening currently on our planet, or with what might happen in the future due to the technological advances we are mediating, will require new paradigms for understanding what information is and does in natural systems. In this talk, I discuss quantitative approaches aimed at developing a new theory for understanding life based on the idea that life is fundamentally about information (life itself is an abstraction) and how that information interacts with the physical world. I discuss how this leads to new approaches to understand the abstraction that was the last universal common ancestor of known life on Earth, through the evolution of our biosphere to its current technologically mediated form and beyond.

Rebecca Kramer-Bottiglio

John J. Lee Associate Professor of Mechanical Engineering, School of Engineering and Applied Science, Yale University

Title: From Particles to Parts—Building Artificial Life from Multifunctional Composites

Abstract: Soft robots have the potential to adapt their morphology, properties, and behavioral control policies towards different tasks or changing environments. This adaptive capability is often inspired by biological systems. For example, octopus tentacles can access nearly infinite trajectories, yet also form joint-like structures to adapt articulated limb control strategies. Caterpillars display undulation and inchworm gaits but can rapidly curl themselves into a wheel and propel themselves away from predators. The armadillo can change from a walking gait on legs to a rolled-up ball as a defense mechanism. During this talk, I will present recent work towards particulate composites that address distributed sensing, variable stiffness properties, and variable trajectory motions inspired by these capabilities in animals. I will contextualize the materials within robotic skins, which are thin, elastic membranes with embedded robotic function. Robotic skins can be wrapped around arbitrary deformable objects to induce the desired motions and deformations, therefore enabling a multitude of robots with different morphologies and functions. Finally, I will show how merging these material discoveries with robotic skins can be used to achieve new shape-shifting capabilities in next-generation soft robots.

Bio: Rebecca Kramer-Bottiglio is the John J. Lee Assistant Professor of Mechanical Engineering and Materials Science at Yale University. Working at the intersection of materials, manufacturing, and robotics, her group is deriving new multifunctional materials that will allow next-generation robots to adapt their morphology and behavior to changing tasks and environments. A recipient of early career awards from NSF, NASA, AFOSR, and ONR, she was named to Forbes’ 30 under 30 list for her approach to manufacturing liquid metals through printable dispersions and scalable sintering methods, and she received the PECASE award for her development of robotic skins that turn inanimate objects into multifunctional robots. She serves as an Associate Editor of Soft Robotics, Frontiers in Robotics and AI, Multifunctional Materials, and Transactions on Robotics, and is an IEEE Distinguished Lecturer.

Lee Cronin

Professor Leroy (Lee) Cronin, Regius Chair of Chemistry, Advanced Research Centre (ARC) Level 5, Digital Chemistry, University of Glasgow

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Lee Cronin was born in the UK and was fascinated with science and technology from an early age getting his first computer and chemistry set when he was 8 years old. This is when he first started thinking about programming chemistry and looking for inorganic aliens. He went to the University of York where he completed both a degree and PhD in Chemistry and then on to do post docs in Edinburgh and Germany before becoming a lecturer at the Universities of Birmingham, and then Glasgow where he has been since 2002 working up the ranks to become the Regius Professor of Chemistry in 2013 aged 39. He has one of the largest multidisciplinary chemistry-based research teams in the world, having raised over $35 M in grants and current income of $15 M. He has given over 300 international talks and has authored over 350 peer reviewed papers with recent work published in Nature, Science, and PNAS. He and his team are trying to make artificial life forms, find alien life, explore the digitization of chemistry, understand how information can be encoded into chemicals and construct chemical computers.

Talk Title: A Top Down Chemically Embodied Artificial Life Computation

Talk Abstract: In my laboratory we are interested in creating the conditions that allow an artificial life form to emerge. But how do we know when our chemical system is really on the path to life? Will bottom-up (prebiotic) and top-down (programmed) be intrinsically different types of artificial life forms? In this lecture I will describe three areas of work in my laboratory: 1) how to measure how alive an artificial life form is; 2) our attempts to emerge a bottom up life form; 3) a top down chemically embodied life form. To achieve the top-down life form we had to build a chemical computer that was able to be digitally programmed, error correcting, and ability to do computations using a chemical-logic-machine. We believe this represents the first example of chemical artificial life.

Melanie Mitchell

Professor, Santa Fe Institute

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Melanie Mitchell is a Professor at the Santa Fe Institute. She attended Brown University, where she majored in mathematics and did research in astronomy, and the University of Michigan, where she received a Ph.D. in computer science. Her dissertation, in collaboration with her advisor Douglas Hofstadter, was the development of Copycat, a computer program that makes analogies.

Mitchell has held faculty or professional positions at the University of Michigan, the Santa Fe Institute, Los Alamos National Laboratory, the OGI School of Science and Engineering, and Portland State University. She is the author or editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems, including Complexity: A Guided Tour (Oxford, 2009), which won the 2010 Phi Beta Kappa Science Book Award. Her newest book, Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux) will be published in October 2019.

Mitchell originated the Santa Fe Institute's Complexity Explorer project, which offers online courses and other educational resources related to the field of complex systems.

Research and Interests
Artificial intelligence, machine learning, computer vision, cognitive science, complex systems.

Talk Title: Conceptual Abstraction and Analogy in Artificial Intelligence

Talk Abstract: In 1955, John McCarthy and colleagues proposed an AI summer research project with the following aim: “An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.” More than six decades later, all of these research topics remain open and actively investigated in the AI community. While AI has made dramatic progress over the last decade in areas such as vision, natural language processing, and robotics, current AI systems still almost entirely lack the ability to form humanlike concepts and abstractions.

Some cognitive scientists have proposed that analogy-making is a central mechanism for conceptual abstraction and understanding in humans. Douglas Hofstadter called analogy-making “the core of cognition”, and Hofstadter and co-author Emmanuel Sander noted, “Without concepts there can be no thought, and without analogies there can be no concepts.” In this talk I will reflect on the role played by analogy-making at all levels of intelligence, and on how analogy-making abilities will be central in developing AI systems with humanlike intelligence. Follow on TwitterFollow on Twitter

Michael Levin

Distinguished Professor in the Biology department and Vannevar Bush Chair; serves as director of the Tufts Center for Regenerative and Developmental Biology

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Research Interests:

The capacity to generate a complex organism from the single cell of a fertilized egg is one of the most amazing qualities of multicellular animals. The processes involved in laying out a basic body plan and defining the structures that will ultimately be formed depend upon a constant flow of information between cells and tissues. The Levin laboratory studies the molecular mechanisms cells use to communicate with one another in the 4-dimensional dynamical system known as the developing embryo. Through experimental approaches and mathematical modeling, we examine the processes governing large-scale pattern formation and biological information storage during animal embryogenesis. Our investigations are directed toward understanding the mechanisms of signaling between cells and tissues that allows a biological system to reliably generate and maintain a complex morphology. We study these processes in the context of embryonic development and regeneration, with a particular focus on the biophysics of cell behavior. In contrast to other groups focusing on gene expression networks and biochemical signaling factors, we are pursuing, at a molecular level, the roles of endogenous voltages, pH gradients, and ion fluxes as epigenetic carriers of morphological information. Using gain- and loss-of-function techniques to specifically modulate cells' ion flow we have the ability to regulate large-scale morphogenetic events relevant to limb formation, eye induction, etc. We believe this information will result in important clinical advances through harnessing the biophysical controls of cell behavior.

Talk title: Robot Cancer: what the bioelectrics of embryogenesis and regeneration can teach us about unconventional computing, cognition, and the software of life

Talk Abstract: Today's engineered robots are often made from reliable yet dumb parts, which greatly limits their adaptive functionality but ensures that their subsystems do not defect from the overall purpose. In contrast, a key aspect of Life is that biological systems have competency at each level - they are made of collectives of cells, tissues, organs, etc. each of which has local goals, which orchestrates the noise and fragility at lower levels towards highly robust system-level behaviors. The cooperation and competition across scales in living systems results in great plasticity, and in basal cognition - memory and decision-making outside the brain that can provide essential inspiration for artificial life and robotics. In this talk, I will outline the remarkable properties of complex body regeneration in some species, in which cellular collectives remember and work toward a specific anatomical outcome. We have now uncovered some of the mechanisms by which cells represent target morphologies and execute the anatomical homeostasis that enables them to reach these goals despite radical perturbations. The mechanism of this error reduction loop and pattern memory is bioelectrical, and I will describe the new tools with which we can now directly read out these anatomical setpoints in all cell types. Best of all, we can now re-write them in vivo, producing lines of 2-headed flatworms and other drastically altered animal anatomies by brief modulation of the bioelectric patterning software running on genomically un-edited (wild-type) cellular hardware. By cracking the morphogenetic code and understanding how anatomical decisions are implemented by distribute bioelectrical computations in tissues, we get closer to our endgame: a reverse anatomical compiler that will enable top-down design of living form at the level of patterning modules, not by micromanaging the molecular machine code on which much of biology is focused today. I will conclude by sketching out the implications of this field for not only biomedicine but also for new machine learning architectures and for the creation of computer-designed living organisms. The future belongs to a deep consilience of computer science, cognitive science, and biology to understand the plasticity of multi-scale computational systems and greatly broaden the boundaries of life-as-it-could-be.

Luis Zaman

Assistant Professor in Ecology & Evolutionary Biology and Complex Systems, University of Michigan

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I became interested in evolution because of an undergraduate computer science class. It's still amazing to me that we can bottle up evolution in an algorithm, and yet are still just scratching the surface of understanding the biodiversity and complexity it has produced.

One of the challenges is that evolution creates diversity and complexity, which then strongly influences further evolution. Untangling this feedback loop between what evolution produces and what then becomes selectively favorable motivates much of my work. Host-parasite coevolution is a prime instance of this complex feedback loop at what I consider the core of evolutionary biology.

Coming to evolutionary biology via computer science has left its marks on my academic interests. I study host-parasite coevolution using a mixture of computational and microbial experiments. I treat computer systems as another experimental system, much like E. coli and Elephants are two living systems that can be studied in surprisingly similar ways

Title: New Frontiers in Alife: What was old is new again

Talk Abstract: Alife has made fundamental contributions to our understanding of how evolutionary processes work. I will highlight a few of these instances, as well as ongoing work by my group and others embracing digital organisms within more traditional biological boundaries. However, there is a history of artificial life studies that are often overlooked by related disciplines. I don’t mean this as a critique of either field. Instead, I would argue it’s more of an opportunity. Artificial life has always been pushing the boundaries of truly interdisciplinary science, and as traditional fields expand their own horizons, old discoveries from the artificial life community are waiting to be newly embraced. This has been the promise of interdisciplinary fields, and Alife is well positioned to deliver.