Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference

Probabilistic inference from real-time input data is becoming increasingly popular and may be one of the potential pathways at enabling cognitive intelligence. As a matter of fact, preliminary research has revealed that stochastic functionalities also underlie the spiking behavior of neurons in cortical microcircuits of the human brain. In tune with such observations, neuromorphic and other unconventional computing platforms have recently started adopting the usage of computational units that generate outputs probabilistically, depending on the magnitude of the input stimulus. In this work, we experimentally demonstrate a spintronic device that offers a direct mapping to the functionality of such a controllable stochastic switching element. We show that the probabilistic switching of Ta/CoFeB/MgO heterostructures in presence of spin-orbit torque and thermal noise can be harnessed to enable probabilistic inference in a plethora of unconventional computing scenarios. This work can potentially pave the way for hardware that directly mimics the computational units of Bayesian inference

Editorial

The first issue of for(e)dialogue is composed of a collection of papers given at the New Directions in Media Research (NDiMR) postgraduate conference in June 2015 at the University of Leicester. NDiMR is a one-day postgraduate focused conference organised by PhD students from the Department of Media and Communication. This conference has a similar aim and purpose of this journal as a whole which is to provide postgraduate students, PhD students and early career researchers with a platform and opportunity to develop and share their research and critically contribute to discussions of theory and methodology on a variety of Media and Communication issues. The NDiMR conference has been held annually since 2012, each year growing in size and attracting more delegates and presenters from across the world. However, this is the first time that some of the events’ presentation papers have been collected for a published conference proceedings

Traditional Chinese medicine works: a politicised scientific debate in the COVID-19 pandemic

The COVID-19 pandemic provoked public attention to medical treatments across the world. In China, a debate on the efficacy of traditional Chinese medicine (TCM) took place amid the government’s active promotion of it for COVID-19 patients. Rather than addressing such a debate from the perspective of medical science or health communication, this paper explores how TCM was politicised on Chinese social media. The research is based on a case study, collecting data from the most popular Chinese community question-answering (CQA) site – Zhihu. By triangulating content analysis (CA) and thematic analysis (TA), we reveal how nationalist sentiments and dissenting opinions are expressed through approval or criticism of TCM among the Zhihu community. The research findings uncover the political momentum behind the debate by shedding light on how Zhihu users engage with public affairs through medical commentaries. This paper thus contributes to understanding the politicised discourse of TCM in China in the wake of the global pandemic