Boardwalk Empire: How Generative AI is Revolutionizing Economic Paradigms

The relentless pursuit of technological advancements has ushered in a new era where artificial intelligence (AI) is not only a powerful tool but also a critical economic driver. At the forefront of this transformation is Generative AI, which is catalyzing a paradigm shift across industries. Deep generative models, an integration of generative and deep learning techniques, excel in creating new data beyond analyzing existing ones, revolutionizing sectors from production and manufacturing to finance. By automating design, optimization, and innovation cycles, Generative AI is reshaping core industrial processes. In the financial sector, it is transforming risk assessment, trading strategies, and forecasting, demonstrating its profound impact. This paper explores the sweeping changes driven by deep learning models like Large Language Models (LLMs), highlighting their potential to foster innovative business models, disruptive technologies, and novel economic landscapes. As we stand at the threshold of an AI-driven economic era, Generative AI is emerging as a pivotal force, driving innovation, disruption, and economic evolution on a global scale.

The Shifting Paradigm in AI : Why Generative Artificial Intelligence is the new Economic Variable

The relentless pursuit of technological advancements has ushered in a new era where artificial intelligence (AI) is not only a powerful tool but also a critical economic driver. At the forefront of this transformation is Generative AI, which is catalyzing a paradigm shift across industries. Deep generative models, an integration of generative and deep learning techniques, excel in creating new data beyond analyzing existing ones, revolutionizing sectors from production and manufacturing to finance. By automating design, optimization, and innovation cycles, Generative AI is reshaping core industrial processes. In the financial sector, it is transforming risk assessment, trading strategies, and forecasting, demonstrating its profound impact. This paper explores the sweeping changes driven by deep learning models like Large Language Models (LLMs), highlighting their potential to foster innovative business models, disruptive technologies, and novel economic landscapes. As we stand at the threshold of an AI-driven economic era, Generative AI is emerging as a pivotal force, driving innovation, disruption, and economic evolution on a global scale.

SMDDH: Singleton Mention detection using Deep Learning in Hindi Text

Mention detection is an important component of coreference resolution system, where mentions such as name, nominal, and pronominals are identified. These mentions can be purely coreferential mentions or singleton mentions (non-coreferential mentions). Coreferential mentions are those mentions in a text that refer to the same entities in a real world. Whereas, singleton mentions are mentioned only once in the text and do not participate in the coreference as they are not mentioned again in the following text. Filtering of these singleton mentions can substantially improve the performance of a coreference resolution process. This paper proposes a singleton mention detection module based on a fully connected network and a Convolutional neural network for Hindi text. This model utilizes a few hand-crafted features and context information, and word embedding for words. The coreference annotated Hindi dataset comprising of 3.6K sentences, and 78K tokens are used for the task. In terms of Precision, Recall, and F-measure, the experimental findings obtained are excellent.