Nightfall’s Up to Speed on AI and Deep Learning 4/7/20
In Nightfall’s Up to Speed on AI and Deep Learning, we summarize the latest news, research, technology, and applications of AI and Deep Learning. In this week’s edition:
With the trend towards predictive analytics, machine learning and other data sciences already underway, marketers need to start paying attention to how they can leverage these techniques to form a more data-driven marketing strategy. With this in mind, weve asked AI industry experts why marketing leaders need to start considering AI, and some of the best open-source AI frameworks to keep tabs on.
The artificial intelligence revolution is here, and the way companies respond to it will shape the business landscape for years to come. Nearly 99%of firms are making some kind of investment in AI or big data initiatives, meaning AI has permeated all aspects of business. While AI may be just about everywhere, that doesnt mean its affecting things equally.
AI is moving beyond its infancy to a boisterous adolescence. But beyond the buzzwords and hype, there is a darker emerging concern about how these decisions are made and the implications of relying upon them. This paper looks at the practical realities of explainable AI, in terms business leaders can adopt today.
Despite the huge contributions of deep learning to the field of artificial intelligence, It requires huge amounts of data. This is one thing that both the pioneers and critics of deep learning agree on. That’s why reducing the data-dependency of deep learning is currently among the top priorities of AI researchers.
This research develops a Machine Learning approach able to predict labor shortages for occupations. We compile a unique dataset that incorporates both Labor Demand and Labor Supply occupational data in Australia from 2012 to 2018. This includes data from 1.3 million job advertisements (ads) and 20 official labor force measures.
The COVID-19 epidemic was listed as a public health emergency of international concern by the WHO on January 30, 2020. To curb the secondary spread of the epidemic, many public places were equipped with thermal imagers to check the body temperature. In this demo paper, we proposed a portable non-contact healthy screening system for people wearing masks, which can simultaneously obtain body temperature and respiration state.
This paper deals with solving distributed optimization problems with equality constraints by a class of uncertain nonlinear heterogeneous dynamic multi-agent systems. It is assumed that each agent with an uncertain dynamic model has limited information about the main problem and limited access to the information of the other agents’ states.
Neural Architecture Search (NAS) was first proposed to achieve state-of-the-art performance through the discovery of new architecture patterns, without human intervention. In this work we propose 1) to cast NAS as a problem of finding the optimal network generator and 2) a new, hierarchical and graph-based search space capable of representing an extremely large variety of network types.
Artificial Intelligence has emerged as a powerful tool in the time to fight against Covid-19. The technology is used to train computers to leverage big data-enabled models for pattern recognition, interpretation, and prediction using Machine Learning, NLP and Computer Vision. These applications can be effective to diagnose, envision, and treat Covid-19 disease.
Access to the online databases is free to qualified researchers and medical experts to help them identify a potential treatment for the novel coronavirus. IBM Research is making multiple free resources available to help healthcare researchers, doctors, and scientists around the world accelerate COVID-19 drug discovery.
As companies from numerous industries come together to battle the spread of coronavirus in whatever way they can, tech companies have begun to explore ways in which artificial intelligence might be used to fight and study the virus. Tech leaders are also hopeful that the current global pandemic will inspire further investments into AI for healthcare and greater integration of the technology in general.
Experts at the University of Copenhagen, Denmark, have begun using artificial intelligence to create computer models that calculate the risk of a corona patient’s needing intensive care or a ventilator. As coronavirus patients are hospitalized, it is difficult for doctors to predict which of them will require intensive care and a respirator.
