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Title: Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future

Abstract

The Artificial Intelligence (AI) revolution foretold of during the 1960s is well underway in the second decade of the twenty first century. Its period of phenomenal growth likely lies ahead. AI-operated machines and technologies will extend the reach of Homo sapiens far beyond the biological constraints imposed by evolution: outwards further into deep space, as well as inwards into the nano-world of DNA sequences and relevant medical applications. And yet, we believe, there are crucial lessons that biology can offer that will enable a prosperous future for AI. For machines in general, and for AI's especially, operating over extended periods or in extreme environments will require energy usage orders of magnitudes more efficient than exists today. In many operational environments, energy sources will be constrained. The AI's design and function may be dependent upon the type of energy source, as well as its availability and accessibility. Any plans for AI devices operating in a challenging environment must begin with the question of how they are powered, where fuel is located, how energy is stored and made available to the machine, and how long the machine can operate on specific energy units. While one of the key advantages of AI usemore » is to reduce the dimensionality of a complex problem, the fact remains that some energy is required for functionality. Hence, the materials and technologies that provide the needed energy represent a critical challenge toward future use scenarios of AI and should be integrated into their design. Here we look to the brain and other aspects of biology as inspiration for Biomimetic Research for Energy-efficient AI Designs (BREAD).« less

Authors:
 [1];  [2];  [3];  [3]
  1. Univ. of California, Irvine, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. George Mason Univ., Arlington, VA (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1559484
Report Number(s):
SAND-2019-6754J
Journal ID: ISSN 1662-453X; 676429
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Frontiers in Neuroscience (Online)
Additional Journal Information:
Journal Name: Frontiers in Neuroscience (Online); Journal Volume: 13; Journal ID: ISSN 1662-453X
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; AI; biomimetic; energy; edge computing; neurobiology; neuromorphic computing

Citation Formats

Krichmar, Jeffrey L., Severa, William Mark, Khan, Muhammad S., and Olds, James L. Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future. United States: N. p., 2019. Web. doi:10.3389/fnins.2019.00666.
Krichmar, Jeffrey L., Severa, William Mark, Khan, Muhammad S., & Olds, James L. Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future. United States. doi:10.3389/fnins.2019.00666.
Krichmar, Jeffrey L., Severa, William Mark, Khan, Muhammad S., and Olds, James L. Thu . "Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future". United States. doi:10.3389/fnins.2019.00666. https://www.osti.gov/servlets/purl/1559484.
@article{osti_1559484,
title = {Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future},
author = {Krichmar, Jeffrey L. and Severa, William Mark and Khan, Muhammad S. and Olds, James L.},
abstractNote = {The Artificial Intelligence (AI) revolution foretold of during the 1960s is well underway in the second decade of the twenty first century. Its period of phenomenal growth likely lies ahead. AI-operated machines and technologies will extend the reach of Homo sapiens far beyond the biological constraints imposed by evolution: outwards further into deep space, as well as inwards into the nano-world of DNA sequences and relevant medical applications. And yet, we believe, there are crucial lessons that biology can offer that will enable a prosperous future for AI. For machines in general, and for AI's especially, operating over extended periods or in extreme environments will require energy usage orders of magnitudes more efficient than exists today. In many operational environments, energy sources will be constrained. The AI's design and function may be dependent upon the type of energy source, as well as its availability and accessibility. Any plans for AI devices operating in a challenging environment must begin with the question of how they are powered, where fuel is located, how energy is stored and made available to the machine, and how long the machine can operate on specific energy units. While one of the key advantages of AI use is to reduce the dimensionality of a complex problem, the fact remains that some energy is required for functionality. Hence, the materials and technologies that provide the needed energy represent a critical challenge toward future use scenarios of AI and should be integrated into their design. Here we look to the brain and other aspects of biology as inspiration for Biomimetic Research for Energy-efficient AI Designs (BREAD).},
doi = {10.3389/fnins.2019.00666},
journal = {Frontiers in Neuroscience (Online)},
number = ,
volume = 13,
place = {United States},
year = {2019},
month = {6}
}

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Works referenced in this record:

Cognition from the bottom up: on biological inspiration, body morphology, and soft materials
journal, August 2014


Solving Constraint Satisfaction Problems with Networks of Spiking Neurons
journal, March 2016


How to stop data centres from gobbling up the world’s electricity
journal, September 2018


A Review of Current Neuromorphic Approaches for Vision, Auditory, and Olfactory Sensors
journal, March 2016


Genetic algorithms: principles of natural selection applied to computation
journal, August 1993


The Energetics of CNS White Matter
journal, January 2012


Whatever next? Predictive brains, situated agents, and the future of cognitive science
journal, May 2013


Communication in Neuronal Networks
journal, September 2003


Balanced Excitatory and Inhibitory Synaptic Currents Promote Efficient Coding and Metabolic Efficiency
journal, October 2013


A million spiking-neuron integrated circuit with a scalable communication network and interface
journal, August 2014


Development of surrogate models using artificial neural network for building shell energy labelling
journal, June 2014


Programmable self-assembly in a thousand-robot swarm
journal, August 2014


Overview of the SpiNNaker System Architecture
journal, December 2013

  • Furber, Steve B.; Lester, David R.; Plana, Luis A.
  • IEEE Transactions on Computers, Vol. 62, Issue 12
  • DOI: 10.1109/TC.2012.142


journal, January 2007

  • Chan, Vincent; Liu, Shih-Chii; van Schaik, Andr
  • IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 54, Issue 1
  • DOI: 10.1109/TCSI.2006.887979

Finding a roadmap to achieve large neuromorphic hardware systems
journal, January 2013


Using biological models to improve innovation systems: The case of computer anti‐viral software
journal, May 2007


Energy Efficient Neural Codes
journal, April 1996


Thermal soaring flight of birds and unmanned aerial vehicles
journal, November 2010


Energy-efficient encoding by shifting spikes in neocortical neurons
journal, August 2013

  • Malyshev, Aleksey; Tchumatchenko, Tatjana; Volgushev, Stanislav
  • European Journal of Neuroscience, Vol. 38, Issue 8
  • DOI: 10.1111/ejn.12338

Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices
journal, December 2016

  • Mao, Yuyi; Zhang, Jun; Letaief, Khaled B.
  • IEEE Journal on Selected Areas in Communications, Vol. 34, Issue 12
  • DOI: 10.1109/JSAC.2016.2611964

Slocum Gliders: Robust and ready
journal, January 2007

  • Schofield, Oscar; Kohut, Josh; Aragon, David
  • Journal of Field Robotics, Vol. 24, Issue 6
  • DOI: 10.1002/rob.20200

Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations
journal, May 2014


Frigate birds track atmospheric conditions over months-long transoceanic flights
journal, June 2016

  • Weimerskirch, Henri; Bishop, Charles; Jeanniard-du-Dot, Tiphaine
  • Science, Vol. 353, Issue 6294
  • DOI: 10.1126/science.aaf4374

Neuromorphic Silicon Neuron Circuits
journal, January 2011

  • Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia
  • Frontiers in Neuroscience, Vol. 5
  • DOI: 10.3389/fnins.2011.00073

Giving machines humanlike eyes
journal, December 2015


DANNA: A neuromorphic software ecosystem
journal, July 2016

  • Disney, Adam; Reynolds, John; Schuman, Catherine D.
  • Biologically Inspired Cognitive Architectures, Vol. 17
  • DOI: 10.1016/j.bica.2016.07.007

The Small World of the Cerebral Cortex
journal, January 2004

  • Sporns, Olaf; Zwi, Jonathan D.
  • Neuroinformatics, Vol. 2, Issue 2
  • DOI: 10.1385/NI:2:2:145

Spray Underwater Glider Operations
journal, June 2016

  • Rudnick, Daniel L.; Davis, Russ E.; Sherman, Jeffrey T.
  • Journal of Atmospheric and Oceanic Technology, Vol. 33, Issue 6
  • DOI: 10.1175/JTECH-D-15-0252.1

Vorticity Control in Fish-like Propulsion and Maneuvering
journal, November 2002


Computer immunology
journal, March 2007


The Internet of Things: A survey
journal, October 2010


Efficient Bipedal Robots Based on Passive-Dynamic Walkers
journal, February 2005


The free-energy principle: a unified brain theory?
journal, January 2010

  • Friston, Karl
  • Nature Reviews Neuroscience, Vol. 11, Issue 2
  • DOI: 10.1038/nrn2787

Retinomorphic Event-Based Vision Sensors: Bioinspired Cameras With Spiking Output
journal, October 2014

  • Posch, Christoph; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabe
  • Proceedings of the IEEE, Vol. 102, Issue 10
  • DOI: 10.1109/JPROC.2014.2346153

Robotic goalie with 3 ms reaction time at 4% CPU load using event-based dynamic vision sensor
journal, January 2013


Improved implementation of the silicon cochlea
journal, May 1992

  • Watts, L.; Kerns, D. A.; Lyon, R. F.
  • IEEE Journal of Solid-State Circuits, Vol. 27, Issue 5
  • DOI: 10.1109/4.133156

Low-bandwidth reflex-based control for lower power walking: 65 km on a single battery charge
journal, June 2014

  • Bhounsule, Pranav A.; Cortell, Jason; Grewal, Anoop
  • The International Journal of Robotics Research, Vol. 33, Issue 10
  • DOI: 10.1177/0278364914527485

Computing beyond Moore's Law
journal, December 2015


Redundancy reduction revisited
journal, January 2001


SLOCUM: an underwater glider propelled by environmental energy
journal, January 2001

  • Webb, D. C.; Simonetti, P. J.; Jones, C. P.
  • IEEE Journal of Oceanic Engineering, Vol. 26, Issue 4
  • DOI: 10.1109/48.972077

On Global Electricity Usage of Communication Technology: Trends to 2030
journal, April 2015


Spiking Optical Flow for Event-Based Sensors Using IBM's TrueNorth Neurosynaptic System
journal, August 2018

  • Haessig, Germain; Cassidy, Andrew; Alvarez, Rodrigo
  • IEEE Transactions on Biomedical Circuits and Systems, Vol. 12, Issue 4
  • DOI: 10.1109/TBCAS.2018.2834558

Perceptual Neural Organization: Some Approaches Based on Network Models and Information Theory
journal, March 1990


Ocean Research Enabled by Underwater Gliders
journal, January 2016


Neural Darwinism: Selection and reentrant signaling in higher brain function
journal, February 1993


Depth-Average Velocity from Spray Underwater Gliders
journal, August 2018

  • Rudnick, Daniel L.; Sherman, Jeffrey T.; Wu, Alexander P.
  • Journal of Atmospheric and Oceanic Technology, Vol. 35, Issue 8
  • DOI: 10.1175/JTECH-D-17-0200.1

Training deep neural networks for binary communication with the Whetstone method
journal, January 2019

  • Severa, William; Vineyard, Craig M.; Dellana, Ryan
  • Nature Machine Intelligence, Vol. 1, Issue 2
  • DOI: 10.1038/s42256-018-0015-y

Designing Collective Behavior in a Termite-Inspired Robot Construction Team
journal, February 2014


Information and Efficiency in the Nervous System—A Synthesis
journal, July 2013


Compressed Sensing, Sparsity, and Dimensionality in Neuronal Information Processing and Data Analysis
journal, July 2012


Humans have more primitive hands than chimpanzees
journal, July 2015


The aerodynamics of insect flight
journal, December 2003

  • Sane, S. P.
  • Journal of Experimental Biology, Vol. 206, Issue 23
  • DOI: 10.1242/jeb.00663

The Cost of Cortical Computation
journal, March 2003


The chips are down for Moore’s law
journal, February 2016


Glider soaring via reinforcement learning in the field
journal, September 2018


Could information theory provide an ecological theory of sensory processing?
journal, March 2011


Edge Computing: Vision and Challenges
journal, October 2016


3D Visual Response Properties of MSTd Emerge from an Efficient, Sparse Population Code
journal, August 2016


Production and Availability of Radioisotopes
journal, November 1949

  • Aebersold, Paul C.
  • Journal of Clinical Investigation, Vol. 28, Issue 6 Pt 1
  • DOI: 10.1172/JCI102192

Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network
journal, May 2018


Sparse coding of sensory inputs
journal, August 2004


Optimal dynamic soaring consists of successive shallow arcs
journal, October 2017

  • Bousquet, Gabriel D.; Triantafyllou, Michael S.; Slotine, Jean-Jacques E.
  • Journal of The Royal Society Interface, Vol. 14, Issue 135
  • DOI: 10.1098/rsif.2017.0496

Toward real-time particle tracking using an event-based dynamic vision sensor
journal, September 2011

  • Drazen, David; Lichtsteiner, Patrick; Häfliger, Philipp
  • Experiments in Fluids, Vol. 51, Issue 5
  • DOI: 10.1007/s00348-011-1207-y

Neuromorphic sensory systems
journal, June 2010


PyNN: a common interface for neuronal network simulators
journal, January 2008


A reconfigurable fabric for accelerating large-scale datacenter services
journal, October 2014

  • Putnam, Andrew; Jan, Gopal; Michael, Gray
  • ACM SIGARCH Computer Architecture News, Vol. 42, Issue 3
  • DOI: 10.1145/2678373.2665678