The Human Brain Project

Total Page:16

File Type:pdf, Size:1020Kb

The Human Brain Project NEUROSCIENCE Building a vast digital simulation of the brain could transform neuroscience and medicine and reveal new ways of making more powerful computers By Henry Markram IT’S TIME TO CHANGE THE WAY WE STUDY THE BRAIN. Reductionist biology—examining to investigate the parts and then reas- individual brain parts, neural circuits semble them to re-create the whole. and molecules—has brought us a long Putting things together to devise a way, but it alone cannot explain the complete simulation of the human workings of the human brain, an in- brain is the goal of an undertaking formation processor within our skull that intends to construct a fantastic that is perhaps unparalleled any- new scientific instrument. Nothing ) where in the universe. We must con- quite like it exists yet, but we have be- struct as well as reduce and build as gun building it. One way to think of well as dissect. To do that, we need a this instrument is as the most power- new paradigm that combines both ful flight simulator ever built—only analysis and synthesis. The father of rather than simulating flight through AND www.humanconnectomeproject.org reductionism, French philosopher open air, it will simulate a voyage ( René Descartes, wrote about the need through the brain. This “virtual brain” IN BRIEF Imaging Neuro of Laboratory Computer simulation will intro­ By the year 2020 digital brains A sim brain can act as a stand­in duce ever greater verisimilitude in­ may be able to represent the inner for the genuine article, thus foster­ Imaging Biomedical for Center Martinos to digital depictions of the work­ workings of a single brain cell or ing a new understanding of autism ings of the human brain. even the whole brain. or per mitting virtual drug trials. COURTESY OF ARTHUR W. TOGA TOGA W. ARTHUR OF COURTESY BUCKNER RANDY 50 Scientific American, June 2012 © 2012 Scientific American June 2012, ScientificAmerican.com 51 © 2012 Scientific American will run on supercomputers and incorpo­ Henry Markram directs the Blue Brain Project at the Swiss Federal rate all the data that neuroscience has Institute of Technology in Lausanne. He has done extensive work on how neurons interconnect, communicate and learn. He also discovered generated to date. fundamental principles of brain plasticity and is co-discoverer of the A digital brain will be a resource for the intense world theory of autism and the theory of how the brain entire scientific community: researchers computes as a liquid that is constantly perturbed. will reserve time on it, as they do on the biggest telescopes, to conduct their experi­ ments. They will use it to test theories of at them simply as sets of symptoms. The ing to—at least, not all of it. We intend to how the human brain works in health and breadth of this perspective would allow reproduce the myriad connections among in disease. They will recruit it to help them us to move forward to develop a genera­ brain cells by different means. develop not only new diagnostic tests for tion of treatments that selectively target The key to our approach is to craft the autism or schizophrenia but also new ther­ the underlying abnormalities. basic blueprint according to which the apies for depression and Alzheimer’s dis­ The second reason is that computing is brain is built: the set of rules that has guid­ ease. The wiring plan for tens of trillions of fast approaching barriers to further devel­ ed its construction over evolution and neural circuits will inspire the design of opment. Computers cannot do many tasks does so anew in each developing fetus. In brainlike computers and intelligent robots. that animal brains do effortlessly, despite theory, those rules are all the information In short, it will transform neuroscience, the inexorable increase in processing pow­ we need to start building a brain. The medicine and information technology. er. For instance, although computer scien­ skeptics are right: the complexity they tists have made huge progress in visual generate is daunting—hence our need for BRAIN IN A BOX recognition, the machines still struggle to supercomputers to capture it. But unravel­ scientists could be running the first simu­ make use of context in a scene or to use ar­ ing the rules themselves is a far more trac­ lations of the human brain by the end of bitrary scraps of information to predict fu­ table problem. If we pull it off, there is no this decade, when supercomputers will be ture events in the way the brain can. logical reason why we cannot apply the powerful enough to support the massive Moreover, because more powerful com­ blueprint in the same way that biology number of calculations needed. The in­ puters require more energy, supplying their does and build an “in silico” brain. strument will not require that all myster­ needs will one day no longer be feasible. The kind of rules we are talking about ies of the brain be unraveled first. Instead The performance of today’s supercomput­ are ones that govern the genes that lead to it will furnish a framework to accommo­ ers is measured in petaflops—quadrillions the types of cells there are in the brain and date what we do know, while enabling us of logic operations per second. The next the underlying plan for the way those cells to make predictions about what we do not. generation, due around 2020, will be 1,000 are distributed and how they are connect­ Those predictions will show us where to times faster and will be measured in exa­ ed. We know that such rules exist because target our future experiments to prevent flops—quintillions of operations per sec­ we discovered some of them while laying wasted effort. The knowledge we generate ond. By itself, the first exa­scale machine the groundwork for the HBP. We started will be integrated with existing knowl­ will probably consume around 20 mega­ doing that almost 20 years ago by measur­ edge, and the “holes” in the framework watts, roughly the energy requirement of a ing the characteristics of individual neu­ will be filled in with increasingly realistic small town in winter. To create increasing­ rons. We collected vast amounts of data detail until, eventually, we will have a uni­ ly powerful computers that perform some about the geometric properties of different fied working model of the brain—one that of the simple but useful things that hu­ neuronal types and digitally reconstructed reproduces it accurately from the whole mans are capable of in an energy­efficient hundreds of them in three dimensions. brain down to the level of molecules. way, we need a radically new strategy. Using a painstaking method called patch Building this instrument is the goal of We could do worse than take inspira­ clamping, which involves placing the tip the Human Brain Project (HBP), an initia­ tion from the human brain, which per­ of a microscopic glass pipette up against tive involving about 130 universities forms a range of intelligent functions on a a cell membrane to measure the voltage around the world. The HBP is one of six mere 20 or so watts—a million times fewer across its ion channels, we also recorded projects competing for a glittering prize, than an exa­scale machine and equivalent the neurons’ electrical properties. up to €1 billion to be provided over 10 to a weak lightbulb. For that, we need to In 2005 modeling a single neuron took years by the European Union to each of understand the multilevel organization of a powerful computer and a three­year two winners, who will be announced in the brain, from genes to behavior. The Ph.D. project. It was clear that more ambi­ February 2013. knowledge is out there, but we need to tious goals would soon become achiev­ We need the simulator for at least two bring it together—and our instrument will able, however, and that we could model reasons. In Europe alone, brain diseases provide the platform on which to do that. larger elements of brain circuitry even if affect 180 million people, or roughly one Critics say that the goal of modeling our knowledge of those elements was in­ in three—a number that is set to grow as the human brain is unachievable. One of complete. At the Brain Mind Institute at the population ages. At the same time, their principal objections is that it is im­ the Swiss Federal Institute of Technology pharm aceutical companies are not invest­ possible to reproduce the connectivity in Lausanne, we launched one of the ing in new treatments for the ailing ner­ among the brain’s 100 trillion synapses be­ HBP’s predecessors, the Blue Brain Proj­ vous system. A holistic view of the brain cause we cannot measure it. They are cor­ ect. We would build what we call “unifying would enable us to reclassify such diseas­ rect that we cannot measure the web of computer models”—models that integrate es in biological terms rather than looking connections, which is why we are not go­ all existing data and hypotheses about a 52 Scientific American, June 2012 © 2012 Scientific American given brain circuit, while reconciling con­ watched, the neurons began to speak to equations on supercomputers. We also flicts in that information and highlighting one another. “Spikes,” or action poten­ need to create software that will construct where knowledge is lacking. tials—the language of the brain—spread a brain that conforms to the inherent biol­ through the column as it began to work as ogy. We call it the “brain builder.” SYNTHESIS BIOLOGY an integrated circuit.
Recommended publications
  • The Human Brain Project
    HBP The Human Brain Project Madrid, June 20th 2013 HBP The Human Brain Project HBP FULL-SCALE HBP Ramp-up HBP Report mid 2013-end 2015 April, 2012 HBP-PS (CSA) (FP7-ICT-2013-FET-F, CP-CSA, Jul-Oct, 2012 May, 2011 HBP-PS Proposal (FP7-ICT-2011-FET-F) December, 2010 Proposal Preparation August, 2010 HBP PROJECT FICHE: PROJECT TITLE: HUMAN BRAIN PROJECT COORDINATOR: EPFL (Switzerland) COUNTRIES: 23 (EU MS, Switzerland, US, Japan, China); 22 in Ramp Up Phase. RESEARCH LABORATORIES: 256 in Whole Flagship; 110 in Ramp Up Phase RESEARCH INSTITUTIONS (Partners): • 150 in Whole Flagship • 82 in Ramp Up Phase & New partners through Competitive Call Scheme (15,5% of budget) • 200 partners expected by Y5 (Project participants & New partners through Competitive Call Scheme) DIVISIONS:11 SUBPROJECTS: 13 TOTAL COSTS: 1.000* M€; 72,7 M€ in Ramp Up Phase * 1160 M€ Project Total Costs (October, 2012) HBP Main Scheme of The Human Brain Project: HBP Phases 2013 2015 2016 2020 2023 RAMP UP (A) FULLY OPERATIONAL (B) SUSTAINED OPERATIONS (C) Y1 Y2 Y3a Y3b Y4 Y5 Y6 Y7 Y8 Y9 Y10 2014 2020 HBP Structure HBP: 11 DIVISIONS; 13 SUBPROJECTS (10 SCIENTIFIC & APPLICATIONS & ETHICS & MGT) DIVISION SPN1 SUBPROJECTS AREA OF ACTIVITY MOLECULAR & CELLULAR NEUROSCIENCE SP1 STRATEGIC MOUSE BRAIN DATA SP2 STRATEGIC HUMAN BRAIN DATA DATA COGNITIVE NEUROSCIENCE SP3 BRAIN FUNCTION THEORETICAL NEUROSCIENCE SP4 THEORETICAL NEUROSCIENCE THEORY NEUROINFORMATICS SP5 THE NEUROINFORMATICS PLATFORM BRAIN SIMULATION SP6 BRAIN SIMULATION PLATFORM HIGH PERFORMANCE COMPUTING (HPC) SP7 HPC
    [Show full text]
  • © CIC Edizioni Internazionali
    4-EDITORIALE_FN 3 2013 08/10/13 12:22 Pagina 143 editorial The XXIV Ottorino Rossi Award Who was Ottorino Rossi? Ottorino Rossi was born on 17th January, 1877, in Solbiate Comasco, a tiny Italian village near Como. In 1895 he enrolled at the medical fac- ulty of the University of Pavia as a student of the Ghislieri College and during his undergraduate years he was an intern pupil of the Institute of General Pathology and Histology, which was headed by Camillo Golgi. In 1901 Rossi obtained his medical doctor degree with the high- est grades and a distinction. In October 1902 he went on to the Clinica Neuropatologica (Hospital for Nervous and Mental Diseases) directed by Casimiro Mondino to learn clinical neurology. In his spare time Rossi continued to frequent the Golgi Institute which was the leading Italian centre for biological research. Having completed his clinical prepara- tion in Florence with Eugenio Tanzi, and in Munich at the Institute directed by Emil Kraepelin, he taught at the Universities of Siena, Sassari and Pavia. In Pavia he was made Rector of the University and was instrumental in getting the buildings of the new San Matteo Polyclinic completed. Internazionali Ottorino Rossi made important contributions to many fields of clinical neurology, neurophysiopathology and neuroanatomy. These include: the identification of glucose as the reducing agent of cerebrospinal fluid, the demonstration that fibres from the spinal ganglia pass into the dorsal branch of the spinal roots, and the description of the cerebellar symp- tom which he termed “the primary asymmetries of positions”. Moreover, he conducted important studies on the immunopathology of the nervous system, the serodiagnosis of neurosyphilis and the regeneration of the nervous system.
    [Show full text]
  • Human Brain Project: Henry Markram Plans to Spend €1Bn Building a Perfect Model of the Human Brain | Science | the Observer 08/11/13 14:39
    Human Brain Project: Henry Markram plans to spend €1bn building a perfect model of the human brain | Science | The Observer 08/11/13 14:39 Human Brain Project: Henry Markram plans to spend €1bn building a perfect model of the human brain Henry Markram, co-director of the Human Brain Project, based in Lausanne, Switzerland, has been awarded €1bn by the EU. Photograph: Jean-Christophe Bott/EPA In a spartan office looking across Lake Geneva to the French Alps, Henry Markram is searching for a suitably big metaphor to describe his latest project. "It's going to be the Higgs boson of the brain, a Noah's archive of the mind," he says. "No, it's like a telescope that can span all the way across the universe of the brain from the micro the macro level." We are talking about the Human Brain Project, Markram's audacious plan to build a working model of the human brain – from neuron to hemisphere level – and simulate it on a supercomputer within the next 10 years. When Markram first unveiled his idea at a TEDGlobal conference in Oxford four years ago, few of his peers took him seriously. The brain was too complex, they said, and in any case there was no computer fast enough. Even last year when he presented a more detailed plan at a scientific meeting in Bern, showing how the requisite computer power would be available by 2020, many neuroscientists continued to insist it could not be done and dismissed his http://www.theguardian.com/science/2013/oct/15/human-brain-project-henry-markram Pagina 1 di 13 Human Brain Project: Henry Markram plans to spend €1bn building a perfect model of the human brain | Science | The Observer 08/11/13 14:39 claims as hype.
    [Show full text]
  • PDF, WIPO Forum 2013 Brochure
    WIPO Forum 2013 From inspiration to innovation: The game-changers September 24, 2013 – 3.30 p.m. International Conference Center Geneva (CICG) Geneva, Switzerland WIPO Forum 2013 What would you change to ensure that future generations see widespread improvements in nutrition, in shelter, and in new therapies to heal troubled minds and bodies? Important breakthroughs are already while opening up the possibility of new on our doorstep and the WIPO Forum markets and new solutions—including 2013 is bringing together four vision- some that may still lie beyond the limits ary innovators, each disrupting cur- of our imagination. rent paradigms in a quest to improve some of the most basic elements of the For forward-looking policy makers, human experience: food, shelter, and here’s the question: How do we foster health. Their individual achievements a creative environment that promotes are astonishing. the kind of ground-breaking work done by the WIPO Forum 2013 panelists, That they share so much in com- while ensuring that the improvements mon is no less surprising. The work lift up our entire communities? What do of each of these change-makers has the innovators of the future need from challenged long-established industrial us—now? The first step in finding the styles, methods or modes of thought, answer is asking the question. Please join us for an interactive session on September 24 at the WIPO Forum 2013 on From inspiration to innovation: The game- changers and hear our panelists’ stories. 2 From inspiration to innovation: The game-changers Anthony Atala. For years, the needs of organ-transplant patients have far out- stripped the number of donors.
    [Show full text]
  • The Ethics of Exponential Life Extension Through Brain Preservation
    A peer-reviewed electronic journal published by the Institute for Ethics and Emerging Technologies ISSN 1541-0099 26(1) – March 2016 The Ethics of Exponential Life Extension through Brain Preservation Michael A. Cerullo Brain Preservation Foundation [email protected] Journal of Evolution and Technology - Vol. 26 Issue 1 – March 2016 - pgs 94-105 Abstract Chemical brain preservation allows the brain to be preserved for millennia. In the coming decades, the information in a chemically preserved brain may be able to be decoded and emulated in a computer. I first examine the history of brain preservation and recent advances that indicate this may soon be a real possibility. I then argue that chemical brain preservation should be viewed as a life-saving medical procedure. Any technology that significantly extends the human life span faces many potential criticisms. However, standard medical ethics entails that individuals should have the autonomy to choose chemical brain preservation. Only if the harm to society caused by brain preservation and future emulation greatly outweighed any potential benefit would it be ethically acceptable to refuse individuals this medical intervention. Since no such harm exists, it is ethical for individuals to choose chemical brain preservation. Introduction One essential part of the definition of life is the drive to preserve existence. Thus it is not surprising that life extension has been a key concern of humanity throughout recorded history (Cave 2012). In the recent past, extending the human life span beyond the “natural” limit was seen as selfish, dangerous, and immoral (Fukuyama 2002; Kass 2003; President’s Council on Bioethics 2003; Pijnenburg and Leget 2006; Blow 2013).
    [Show full text]
  • Nonlinear Dendritic Coincidence Detection for Supervised Learning APREPRINT
    NONLINEAR DENDRITIC COINCIDENCE DETECTION FOR SUPERVISED LEARNING APREPRINT Fabian Schubert Claudius Gros Institute for Theoretical Physics Institute for Theoretical Physics Goethe University Frankfurt Goethe University Frankfurt Frankfurt am Main Frankfurt am Main [email protected] [email protected] July 13, 2021 ABSTRACT Cortical pyramidal neurons have a complex dendritic anatomy, whose function is an active research field. In particular, the segregation between its soma and the apical dendritic tree is believed to play an active role in processing feed-forward sensory information and top-down or feedback signals. In this work, we use a simple two-compartment model accounting for the nonlinear interactions between basal and apical input streams and show that standard unsupervised Hebbian learning rules in the basal compartment allow the neuron to align the feed-forward basal input with the top-down target signal received by the apical compartment. We show that this learning process, termed coincidence detection, is robust against strong distractions in the basal input space and demonstrate its effectiveness in a linear classification task. Keywords Dendrites · Pyramidal Neuron · Plasticity · Coincidence Detection · Supervised Learning 1 Introduction In recent years, a growing body of research has addressed the functional implications of the distinct physiology and anatomy of cortical pyramidal neurons [Spruston, 2008, Hay et al., 2011, Ramaswamy and Markram, 2015]. In particular, on the theoretical side, we saw a paradigm shift from treating neurons as point-like electrical structures towards embracing the entire dendritic structure [Larkum et al., 2009, Poirazi, 2009, Shai et al., 2015]. This was mostly due to the fact that experimental work uncovered dynamical properties of pyramidal neuronal cells that simply could not be accounted for by point models [Spruston et al., 1995, Häusser et al., 2000].
    [Show full text]
  • Neuroscience Thinks Big Bring Them Together in a Unified View
    PERSPECTIVES VIEWPOINT new computing technologies. Neuroscience is like the infant brain — it is flooded with data and theories but lacks the ability to Neuroscience thinks big bring them together in a unified view. We pin our hopes on more and more data with- (and collaboratively) out realizing that experiments can only give us a small fraction of what we need. The Eric R. Kandel, Henry Markram, Paul M. Matthews, Rafael Yuste and attempt to reconstruct the human brain as a computer model can provide a new focus Christof Koch for neuroscience and for clinical and tech- Abstract | Despite cash-strapped times for research, several ambitious collaborative nological research. It will help us to ‘clean neuroscience projects have attracted large amounts of funding and media up’ conflicting reports and teach us how to apply knowledge from animal studies to attention. In Europe, the Human Brain Project aims to develop a large-scale understanding the human brain. Ultimately, computer simulation of the brain, whereas in the United States, the Brain Activity it will allow us to discover the fundamental Map is working towards establishing a functional connectome of the entire brain, principles governing brain structure and and the Allen Institute for Brain Science has embarked upon a 10‑year project to function and to predictively reconstruct understand the mouse visual cortex (the MindScope project). US President Barack the brain from fragments of experimental data. Without this kind of understanding, Obama’s announcement of the BRAIN Initiative (Brain Research through Advancing we will continue to struggle to develop new Innovative Neurotechnologies Initiative) in April 2013 highlights the political treatments and brain-inspired computing commitment to neuroscience and is expected to further foster interdisciplinary technologies.
    [Show full text]
  • Abstractions of the Mind Before Data Were So Abundant, Computer Models of the Brain Were Simple
    OUTLOOK COGNITIVE HEALTH NEURAL MODELLING Abstractions of the mind Before data were so abundant, computer models of the brain were simple. Information is now much more plentiful — but some argue that models should remain uncomplicated. BY KELLY RAE CHI testing hypotheses on how the brain deals with amused Eliasmith, it did not surprise him. uncertainty in functions such as attention and Markram is well known for taking a different he first major results of the Blue Brain decision-making. approach to modelling, as he did in the Blue Project, a detailed simulation of a bit of There is a widespread preference for Brain Project. His strategy is to build in every MARIO WAGNER rat neocortex about the size of a grain hypothesis-driven approaches in the brain- possible detail to derive a perfect imitation of Tof coarse sand, were published last year1. The modelling community. Some models might be the biological processes in the brain with the model represents 31,000 brain cells and 37 mil- very small and detailed, for example, focusing hope that higher functions will emerge — a lion synapses. It runs on a supercomputer and on a single synapse. Others might explore the ‘bottom-up’ approach. Researchers such as is based on data collected over 20 years. Fur- electrical spiking of whole neurons, the com- Eliasmith and Pouget take a ‘top-down’ strat- thermore, it behaves just like a speck of brain munication patterns between brain areas, or egy, creating simpler models based on our tissue. But therein, say critics, lies the problem. even attempt to recapitulate the whole brain.
    [Show full text]
  • PROFESSOR HENRY J. MARKRAM, Phd BIOGRAPHICAL SUMMARY
    PROFESSOR HENRY J. MARKRAM, PhD Founder, Brain Mind Institute Founder-Director, Blue Brain Project Founder, Human Brain Project Born: South Africa, 28th March 1962 Nationality: South African & Israeli Permanent Resident: Switzerland Languages: English, Hebrew, Afrikaans, basic German BIOGRAPHICAL SUMMARY Henry Markram is a Professor of Neuroscience at the Swiss Federal Institute for Technology (EPFL). He finished school at Kearsney College and thereafter began his research career in South Africa in the early 1980s. He studied Medicine and Neuroscience at the University of Cape Town, South Africa (1988), later moving to Israel where he obtained a PhD in Neuroscience at the Weizmann Institute (1991). After which, he completed postdoctoral work as a Fulbright Scholar at the National Institute of Health (1992) in the USA and as a Minerva Fellow at the Max-Planck Institute (1994) in Germany. In 1995, he started his own lab at the Weizmann Institute. Later on, in 2000, he spent a year sabbatical conducting research at the University of California, San Francisco and two years later, moved to EPFL to found and direct the Brain Mind Institute. In 2005, he founded the Blue Brain Project (BBP) to develop a radical and innovative approach to Neuroscience – algorithmic and digital reconstruction and simulation of the brain using supercomputers. In 2009, the project completed a cellular level model that provides a detailed picture of the whole column and offers new insights into basic principles of brain design: in particular, the role of neural morphology in the determination of cortical connectivity and the role of “Hebbian Assemblies”. The Blue Brain Project today, is a team of around 100 scientists and engineers and receives 20 million CHF a year in Swiss Federal funding.
    [Show full text]
  • The Human Brain Project: Winner of the of the Largest European Scientific Funding Competition
    The Human Brain Project: winner of the of the largest European scientific funding competition MONTREAL - The European Commission has officially announced the selection of the Human Brain Project (HBP) as one of its two FET Flagship projects. The new project will federate European efforts to address one of the greatest challenges of modern science: understanding the human brain. The goal of the Human Brain Project is to pull together all our existing knowledge about the human brain and to reconstruct the brain, piece by piece, in supercomputer-based models and simulations. The models offer the prospect of a new understanding of the human brain and its diseases and of completely new computing and robotic technologies. On January 28, the European Commission supported this vision, announcing that it has selected the HBP as one of two projects to be funded through the new FET Flagship Program. Federating more than 80 European and international research institutions, the Human Brain Project is planned to last ten years (2013-2023). The cost is estimated at 1.19 billion euros. The project will also associate some important North American and Japanese partners. It will be coordinated at the Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, by neuroscientist Henry Markram with co- directors Karlheinz Meier of Heidelberg University, Germany, and Richard Frackowiak of Centre Hospitalier Universitaire Vaudois (CHUV) and the University of Lausanne (UNIL). Canada’s role in this international project is through Dr. Alan Evans of the Montreal Neurological Institute (MNI) at McGill University. His group has developed a high-performance computational platform for neuroscience (CBRAIN) and multi-site databasing technologies that will be used to assemble brain imaging data across the HBP.
    [Show full text]
  • 2020 Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy
    http://gcrinstitute.org 2020 Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy McKenna Fitzgerald, Aaron Boddy, & Seth D. Baum Global Catastrophic Risk Institute Cite as: McKenna Fitzgerald, Aaron Boddy, and Seth D. Baum, 2020. 2020 Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy. Global Catastrophic Risk Institute Technical Report 20-1. Technical reports are published to share ideas and promote discussion. They have not necessarily gone through peer review. The views therein are the authors’ and are not necessarily the views of the Global Catastrophic Risk Institute. Executive Summary Artificial general intelligence (AGI) is artificial intelligence (AI) that can reason across a wide range of domains. While most AI research and development (R&D) deals with narrow AI, not AGI, there is some dedicated AGI R&D. If AGI is built, its impacts could be profound. Depending on how it is designed and used, it could either help solve the world’s problems or cause catastrophe, possibly even human extinction. This paper presents a survey of AGI R&D projects that are active in 2020 and updates a previous survey of projects active in 2017. Both surveys attempt to identify every active AGI R&D project and characterize them in terms of relevance to ethics, risk, and policy, focusing on seven attributes: The type of institution in which the project is based Whether the project publishes open-source code Whether the project has military connections The nation(s) in which the project is based The project’s goals for its AGI The extent of the project’s engagement with AGI safety issues The overall size of the project The surveys use openly published information as found in scholarly publications, project websites, popular media articles, and other websites.
    [Show full text]
  • Complex Activity Patterns Generated by Short-Term Synaptic Plasticity
    ESANN 2017 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 26-28 April 2017, i6doc.com publ., ISBN 978-287587039-1. Available from http://www.i6doc.com/en/. Complex activity patterns generated by short-term synaptic plasticity Bulcs´uS´andor and Claudius Gros Institute for Theoretical Physics - Goethe University Frankfurt Frankfurt am Main - Germany Abstract. Short-term synaptic plasticity (STSP) affects the efficiency of synaptic transmission for persistent presynaptic activities. We consider attractor neural networks, for which the attractors are given, in the absence of STSP, by cell assemblies of excitatory cliques. We show that STSP may transform these attracting states into attractor relics, inducing ongoing transient-state dynamics in terms of sequences of transiently activated cell assemblies, the former attractors. Subsequent cell assemblies may be both disjoint or partially overlapping. It may hence be possible to use the resulting dynamics for the generation of motor control sequences. 1 Introduction Changes in the transmission properties of synapses lead to a modulation of infor- mation processing. Synaptic plasticity, which is present on many time scales, is responsible, for learning and computational processes [1], as well as for memory consolidation [2] and motor pattern generation [3]. Short-term synaptic plas- ticity (STSP) contributes, in this context, to the regulation of brain networks on time scales ranging typically from tens of milliseconds to seconds [4]. It is affected, in the standard Tsodyks-Markram model [5, 2, 1], by two factors: a reservoir ϕ(t) of neurotransmitter vesicles and the Ca-concentration, u(t), which in turn influences the release probability of vesicles.
    [Show full text]