Newark, CA, United States of America

Dylan Jackson


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2021

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1 patent (USPTO):Explore Patents

Title: Innovations of Dylan Jackson in Music Generation

Introduction

Dylan Jackson is an innovative inventor based in Newark, CA. He has made significant contributions to the field of music technology, particularly in the area of AI-generated music. His work focuses on enhancing the quality and classification of music through advanced metrics and visualization techniques.

Latest Patents

Dylan holds a patent for a music generation system that includes methods and apparatus for providing metrics for the quality, attributes, and relationships of music, including AI-generated music. This patent describes music classification and visualization methods that transform music files into graphical representations. It also involves generating a similarity matrix for the music files using structural similarity techniques and creating visualizations of the relationships among the music files using multidimensional scaling techniques. Additionally, qualitative scoring methods for AI-generated music are outlined, which classify the music using a multi-genre classifier and generate a qualitative score based on confidence in the classification combined with the similarity metric.

Career Highlights

Dylan is currently employed at Amazon Technologies, Inc., where he continues to develop innovative solutions in music technology. His work has the potential to revolutionize how music is classified and appreciated in the digital age.

Collaborations

Dylan collaborates with talented coworkers, including Liang Li and Wayne Chi, who contribute to his projects and enhance the creative process.

Conclusion

Dylan Jackson's contributions to music generation and AI technology demonstrate his commitment to innovation in the field. His patent and ongoing work at Amazon Technologies, Inc. highlight the importance of advancements in music classification and visualization.

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