scholarly journals Transforming the Generative Pretrained Transformer Into Augmented Business Text Writer

Author(s):  
Faisal Khalil ◽  
Prof. Dr. Gordon Pipa

Abstract This study uses transformers architecture of Artificial neural networks to generate artificial business text for a given topic or theme. The implication of the study is to augment the business report writing, and general business writings process with help of Generative pretrained transformers (GPT) networks. Main focus of study is to provide practical use case for GPTs models with help of big data. Our study model has 355 million model parameters and trained for three months on GPU enable devices using 2.3 billion text tokens(is available as open-source data now). Text tokens are collected with help of rigorous preprocessing, which includes; shortlisting of Subreddits of Fortune 500 companies and industries, listed on US-based social news aggregation online portal called "Reddit". After shortlisting, millions of submission of users during the five years, are parsed to collect the URLs out of it. 1.8 million working URLs are scrutinized. Business text is parsed, cleaned, and converted into word embeddings out of URLs. The result shows that both models; conditional interactive and random sampling, generate text paragraphs that are grammatically accurate and stick to the given topic.

2021 ◽  
Vol 40 (4) ◽  
Author(s):  
Nathan Tallman

Digital preservation systems and practices are rooted in research and development efforts from the late 1990s and early 2000s when the cultural heritage sector started to tackle these challenges in isolation. Since then, the commercial sector has sought to solve similar challenges, using different technical strategies such as software defined storage and function-as-a-service. While commercial sector solutions are not necessarily created with long-term preservation in mind, they are well aligned with the digital preservation use case. The cultural heritage sector can benefit from adapting these modern approaches to increase sustainability and leverage technological advancements widely in use across Fortune 500 companies.


Author(s):  
Jaime Kucinskas

From the halls of the Ivy League to the C-suite at Fortune 500 companies, this book reveals the people behind the mindfulness movement, and the engine they built to propel mindfulness into public consciousness. Based on over a hundred interviews with meditating scientists, religious leaders, educators, businesspeople, and investors, this book shows how this highly accomplished, affluent group has popularized meditation as a tool for health, happiness, and social reform over the past forty years. Rather than working through temples or using social movement tactics like protest to improve society, they mobilized by building elite networks advocating the benefits of meditation across professions. They built momentum by drawing in successful, affluent people and their prestigious institutions, including Ivy League and flagship research universities, and Fortune 100 companies like Google and General Mills. To broaden meditation’s appeal, they made manifold adaptations along the way. In the end, does mindfulness really make our society better? Or has mindfulness lost its authenticity? This book reveals how elite movements can spread, and how powerful spiritual and self-help movements can transform individuals in their wake. Yet, spreading the dharma came with unintended consequences. With their focus on individual transformation, the mindful elite have fallen short of the movement’s lofty ambitions to bring about broader structural and institutional change. Ultimately, this idealistic myopia unintentionally came to reinforce some of the problems it originally aspired to solve.


2018 ◽  
Vol 80 (6) ◽  
pp. 457-461
Author(s):  
Carlos A. Morales-Ramirez ◽  
Pearlyn Y. Pang

Open-source data are information provided free online. It is gaining popularity in science research, especially for modeling species distribution. MaxEnt is an open-source software that models using presence-only data and environmental variables. These variables can also be found online and are generally free. Using all of these open-source data and tools makes species distribution modeling (SDM) more accessible. With the rapid changes our planet is undergoing, SDM helps understand future habitat suitability for species. Due to increasing interest in biogeographic research, SDM has increased for marine species, which were previously not commonly found in this modeling. Here we provide examples of where to obtain the data and how the modeling can be performed and taught.


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