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What is Generative Models

Generative AI and Multifactor Productivity in Business
Generative models are a specific type of machine learning model that is run on neural networks, which are capable of learning to identify underlying patterns found in large data sets, that can be used to generate new data.
Published in Chapter:
The Impact of OpenAI and MFP on the Labour Market Dynamics of Trinidad and Tobago
Roshnie Anita Doon (Global Labor Organization, Germany)
Copyright: © 2024 |Pages: 39
DOI: 10.4018/979-8-3693-1198-1.ch008
Abstract
Open Artificial Intelligence (AI) is a research and operation company that seeks to ensure that persons around the world can reap the benefits of AI. Its focus is on developing a range of models that have the potential to revolutionize the labour market productivity of business enterprises across industries in Trinidad and Tobago. The use of AI-based tools can not only optimize every stage of the management and production process but from the perspective of Multi-Factor Productivity (MFP) can boost its efficiency. Even with such benefits, increased use of AI can displace workers, intensify educational and skills mismatch, and stimulate inequality between unskilled and highly skilled workers. This chapter examined the impact of Open AI and MFP on the Labor Dynamics of Trinidad and Tobago, using a secondary research methodology. This chapter delves into the connection between AI tools and MFP, its integration into the management and production process, and the impact that it has on the labour dynamics of domestic industries, and the future of work in Trinidad and Tobago.
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More Results
Generation of Synthetic Data: A Generative Adversarial Networks Approach
A set of operations that involve the distribution of the data set itself and can generate synthetic data. This can be divided into two approaches: generative (joint distribution) and discriminative (conditional distribution).
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Generative AI in Higher Education
AI models designed to generate new data instances similar to their training data. They are widely used in creative applications such as art and music generation and in data augmentation.
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