International Journal of Computing and Artificial Intelligence

P-ISSN: 2707-6571, E-ISSN: 2707-658X
Printed Journal   |   Refereed Journal   |   Peer Reviewed Journal

2024, Vol. 5, Issue 1, Part A

From brainstorm to boardroom: Enhancing idea viability through ML analysis


Author(s): Gangadhar Reddy B, Dharaneesh G, Jaya Sai Sriram and Eawar sa Harshith

Abstract:
Fueling Innovation: Where Bright Ideas Meet Investment Power
Imagine a world in which aspiring student innovators have a direct connection with potential investors, and their innovative ideas are no longer hiding in obscurity. This project envisages such a reality through its innovative web platform, which acts as a bridge between untapped potential and investment.
Students submit their ideas to the platform, where they meet a unique ally: a pre-trained machine-learning model. This model, armed with relevant data, acts as a discerning judge by carefully analyzing each idea on the basis of crucial factors such as market demand, technical feasibility, financial strength, and team expertise. Only the most promising ideas that exceed a preset bar of success will gain access to a curated pool of registered investors.
For students, this platform will become a launchpad for their dreams. It offers a simple way of presenting their ideas, receiving valuable data-driven feedback, and potentially unlocking the resources needed to implement their vision. Investors, on the other hand, benefit from a targeted selection of high-potential projects, which saves them time and effort when looking for effective investments.
This project transcends mere convenience. It creates a vibrant ecosystem in which creativity thrives and innovation thrives. Students have the power to transform their talent into tangible benefits, while investors can be a catalyst for positive change by supporting ventures that have real potential. This platform, which bridges the gap between ambition and resources, opens the way to a future in which innovative ideas do not only flicker, but ignite.
This expanded version incorporates additional details, such as the role of the pre-trained model and the platform’s impact on both students and investors, as well as more evocative language to enhance the overall message.


DOI: 10.33545/27076571.2024.v5.i1a.84

Pages: 53-58 | Views: 90 | Downloads: 41

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International Journal of Computing and Artificial Intelligence
How to cite this article:
Gangadhar Reddy B, Dharaneesh G, Jaya Sai Sriram, Eawar sa Harshith. From brainstorm to boardroom: Enhancing idea viability through ML analysis. Int J Comput Artif Intell 2024;5(1):53-58. DOI: 10.33545/27076571.2024.v5.i1a.84
International Journal of Computing and Artificial Intelligence

International Journal of Computing and Artificial Intelligence

International Journal of Computing and Artificial Intelligence
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