This inventor holds 2 USPTO granted patents. Top assignee: Brainchip, Inc.. Active years: 2024-2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2024-2026
Title: Milind Joshi: Innovator in Convolutional Spiking Neural Networks
Introduction
Milind Joshi is a prominent inventor based in Edgewater, Australia. He has made significant contributions to the field of neural networks, particularly through his innovative patent that enhances the functionality of convolutional spiking neural networks. His work is pivotal in advancing the capabilities of artificial intelligence systems.
Latest Patents
Milind Joshi holds a patent titled "Event-based extraction of features in a convolutional spiking neural network." This patent describes a sophisticated system that includes a memory for storing data representative of at least one kernel, a plurality of spiking neuron circuits, and an input module for receiving spikes related to digital data. The system is designed to transform kernels and input spike arrays to produce higher resolution outputs. Additionally, it features a packet collection module that organizes collected spikes based on their spatial coordinates, enabling efficient event-based convolution processing.
Career Highlights
Milind Joshi is currently associated with Brainchip, Inc., where he applies his expertise in neural networks to develop cutting-edge technologies. His work at Brainchip focuses on enhancing the performance and efficiency of spiking neural networks, which are crucial for various applications in artificial intelligence.
Collaborations
Milind has collaborated with notable professionals in his field, including Douglas McLelland and Kristofor D Carlson. These collaborations have contributed to the advancement of research and development in neural network technologies.
Conclusion
Milind Joshi's innovative work in convolutional spiking neural networks exemplifies the potential of artificial intelligence technologies. His contributions are shaping the future of neural network applications and enhancing the capabilities of machine learning systems.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
