Chatting about ChatGPT: how may AI and GPT impact academia and libraries?
Purpose This paper aims to provide an overview of key definitions related to ChatGPT, a
public tool developed by OpenAI, and its underlying technology, Generative Pretrained …
public tool developed by OpenAI, and its underlying technology, Generative Pretrained …
Opportunities for neuromorphic computing algorithms and applications
Neuromorphic computing technologies will be important for the future of computing, but
much of the work in neuromorphic computing has focused on hardware development. Here …
much of the work in neuromorphic computing has focused on hardware development. Here …
The impact of ChatGPT on foreign language teaching and learning: Opportunities in education and research
WCH Hong - Journal of Educational Technology and Innovation, 2023 - jeti.thewsu.org
The revolutionary online application ChatGPT has brought immense concerns to the
education field. Foreign language teachers being some of those most reliant on writing …
education field. Foreign language teachers being some of those most reliant on writing …
Towards spike-based machine intelligence with neuromorphic computing
Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …
inspired computing for machine intelligence—promises to realize artificial intelligence while …
Robust spike-based continual meta-learning improved by restricted minimum error entropy criterion
S Yang, J Tan, B Chen - Entropy, 2022 - mdpi.com
The spiking neural network (SNN) is regarded as a promising candidate to deal with the
great challenges presented by current machine learning techniques, including the high …
great challenges presented by current machine learning techniques, including the high …
Exploring neuromorphic computing based on spiking neural networks: Algorithms to hardware
Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …
attention lately due to its promise of reducing the computational energy, latency, as well as …
[HTML][HTML] Enabling spike-based backpropagation for training deep neural network architectures
Spiking Neural Networks (SNNs) have recently emerged as a prominent neural computing
paradigm. However, the typical shallow SNN architectures have limited capacity for …
paradigm. However, the typical shallow SNN architectures have limited capacity for …
A review of learning in biologically plausible spiking neural networks
Artificial neural networks have been used as a powerful processing tool in various areas
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …
Optimal ann-snn conversion for fast and accurate inference in deep spiking neural networks
Spiking Neural Networks (SNNs), as bio-inspired energy-efficient neural networks, have
attracted great attentions from researchers and industry. The most efficient way to train deep …
attracted great attentions from researchers and industry. The most efficient way to train deep …
Memristive devices based on two-dimensional transition metal chalcogenides for neuromorphic computing
Abstract Two-dimensional (2D) transition metal chalcogenides (TMC) and their
heterostructures are appealing as building blocks in a wide range of electronic and …
heterostructures are appealing as building blocks in a wide range of electronic and …