The core objective of this project is to revolutionize the tipping transaction process through digital means, thereby improving the efficiency and transparency of the entire service industry.
TPRSC support NFC Payment Technology / QR-Code payment method / Face Recognition Payment System.The core objective of this project is to revolutionize the tipping transaction process through digital means, thereby improving the efficiency and transparency of the entire service industry.
Fast Transaction Processing: TPRSC makes cross-border payments faster as it enables almost real-time transaction confirmation through blockchain technology, significantly reducing the time required for traditional bank transfers.
Device Compatibility: TPRSC supports a wide range of devices, from smartphones to desktop computers, almost any device with an internet connection can conduct TPRSC transactions.
Potential appreciation: As the total issuance of TPRSC is limited, its value is likely to increase over time as market acceptance grows.
Nathan has 20 years of hands-on experience in the cybersecurity field. He holds a Ph.D. from the Massachusetts Institute of Technology and previously worked at Palo Alto Networks, where he focused on the development of firewalls and intrusion detection systems.
Lans is an algorithm researcher with a PhD in Artificial Intelligence from the University of Chicago. He has done excellent research in both natural language processing and machine vision, and has worked at Nvidia, where he has driven several deep learning projects.
Samuel is a veteran database administrator with deep technical experience in MySQL and PostgreSQL. He received his degree from the University of Florida and has worked on Uber's data team, managing large-scale data infrastructures.
Jeremy holds a Master's degree in Computer Science from Columbia University. He has over 10 years of experience in big data analytics and machine learning, with a specialization in complex data sets. Prior to joining the Tips Payment and Receive System program, he worked as a Senior Data Scientist at Salesforce, where he led several successful projects.
