The brain of a new machine

  title={The brain of a new machine},
  author={Massimiliano Versace and Ben Chandler},
  journal={IEEE Spectrum},
MoNETA (Modular Neural Exploring Traveling Agent) is the software we're designing at Boston University's department of cognitive and neural systems, which will run on a braininspired microprocessor under development at HP Labs in California. It will function according to the principles that distinguish us mammals most profoundly from our fast but witless machines.MoNETA is a technology that will lead to a true artificial intelligence. 
Visually-guided adaptive robot (ViGuAR)
The neuromorphic architecture of the ViGuAR brain is designed to support visually-guided navigation and learning, which in combination with the path-planning, memory-driven navigation agent - MoNETA5 - should effectively account for a wide range of key features in rodents' navigational behavior.
Synaptic electronics and neuromorphic computing
The architecture of the brain and the learning mechanisms responsible for its plasticity are reviewed, and several memristive devices that have been used to implement electronic synapses are introduced.
The Brain in Silicon: History, and Skepticism
It is argued that these arguments put forward in support of potential advantages of neural hardware over traditional microprocessor architectures are theoretically flawed, and therefore the premises for the success of neuromorphic hardware are weak.
Hamiltonian Neural Network-based Orthogonal Filters - A Basis for Artificial Intelligence
It is claimed here that octonionic modules are basic building blocks to implement AI compatible processors.
Persuading Computers to Act More Like Brains
MoNETA (Modular Neural Exploring Traveling Agent) is being developed with Cog Ex Machina to exploit new hardware devices and their capabilities as well as to demonstrate intelligent, autonomous behaviors in both virtual animats and robots.
Emulating reflex actions through memristors
The paper uses the recently discovered memristors to implement a method to simulate the reflex action of human beings in a robot, using a configuration of memristor developed to form multi-directional circuits.
Managing a real-time massively-parallel neural architecture
The story of the research and development of a framework of scalable management tools that support SpiNNaker, a novel computing architecture designed to model spiking neural networks of biologically-significant sizes, and how users have access to results dynamically and are able to make informed decisions on required actions in real-time.
Cognitive Automation—Survey of Novel Artificial General Intelligence Methods for the Automation of Human Technical Environments
Automatic and flexible decision making based on challenging conditions such as increasing amounts of information, lacking prior knowledge of data, incomplete, missing or contradicting data, becomes the key challenges for future automation technologies.
Review of stability properties of neural plasticity rules for implementation on memristive neuromorphic hardware
This paper summarizes in a concise way using a uniform notation the stability properties of the rules that are covered by the general form in [1], a generalized parametrizable form for many of these rules.
NEBULA: A Neuromorphic Spin-Based Ultra-Low Power Architecture for SNNs and ANNs
  • Sonali Singh, Anup Sarma, C. Das
  • Computer Science
    2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA)
  • 2020
This paper proposes a comprehensive design spanning across the device, circuit, architecture and algorithm levels to build an ultra low-power architecture for SNN and ANN inference, using spintronics-based magnetic tunnel junction devices that have been shown to function as both neuro-synaptic crossbars as well as thresholding neurons and can operate at ultra low voltage and current levels.