MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202621094044 A) filed by Dr. Thupakula Bhaskar; Mr. Pravin Vijay Thakare; Ms. Swati Arjun Yadgire; Mrs. Priyanka Vaibhav Narkhede; Mrs. Geeta Yogesh Tidke; Ms. Priti Dinkar Marke; and Mr. P K Kumar on August 03, 2026, for Automated Deep Learning Model Optimization And Deployment System With Adaptive Self-Evolving Model Lifecycle Management.
Inventors include Dr. Thupakula Bhaskar; Mr. Pravin Vijay Thakare; Ms. Swati Arjun Yadgire; Mrs. Priyanka Vaibhav Narkhede; Mrs. Geeta Yogesh Tidke; Ms. Priti Dinkar Marke; and Mr. P K Kumar.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: The present invention discloses an automated deep learning model optimization and deployment system configured to autonomously optimize, validate, secure, deploy, monitor, and continuously improve deep learning models throughout their operational lifecycle. The system integrates adaptive multi-objective optimization, hardware- aware profiling, intelligent deployment orchestration, runtime performance monitoring, cybersecurity verification, blockchain-based deployment auditing, explainable artificial intelligence, and autonomous lifecycle management into a unified architecture. The disclosed system dynamically adapts deployment strategies across cloud, edge, embedded, federated, and hybrid computing environments while automatically responding to performance degradation, infrastructure changes, concept drift, data drift, and cybersecurity threats through autonomous retraining and optimization. The invention significantly improves deployment efficiency, operational reliability, computational resource utilization, model security, scalability, and lifecycle automation across heterogeneous artificial intelligence deployment platforms. Accompanied Drawing [FIGS. 1-2]
Disclaimer: Curated by HT Syndication.
