• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • IEEE.org
  • IEEE Xplore
  • IEEE Standards
  • IEEE Spectrum
  • More Sites

IEEE Potentials Magazine

The magazine for high-tech innovators

  • Home
  • Theme
    • Features
    • Columns/Departments
  • About Us
  • Contact
  • Associated Links
    • Potentials at IEEE Students
    • Potentials Media Guide
  • Highlighted Articles
  • Call For Papers
  • Recent Issues
    • Nov/Dec 2025
    • Sept/Oct 2025
    • July/Aug 2025
    • May/June 2025
    • March/April 2025
    • Jan/Feb 2025

The Way Ahead: Invent the future

January 1, 2020 by Elisa H. Barney Smith

Welcome to the new year! What new things are you going to do this year? How about inventing the future? The theme of this issue is new mobility. When I was a student, self-driving vehicles were a matter of science fiction, but today, the idea sounds plausible. As this issue shows, self-driving vehicles could be a near-term reality, thanks to many technologies that have been and are being deployed.

Alan Kay, the developer of object-oriented programming, is known for saying, “The best way to predict the future is to invent it.” As students, you are learning what has already been achieved, but I’m sure your professors want you to cultivate the ability to invent the future. I often hear students wondering why they need to learn some topic, especially if new methods have already been developed, like learning arithmetic when we have calculators and computers. Neural networks and deep learning are all the rage now and enabling the growth of new technologies, many of which are being used in self-driving vehicles, especially for computer vision in navigation and obstacle avoidance. These networks learn using a technique called back propagation, which was established in its initial form by multiple people in the 1960s but was first applied to neural networks in the 1980s.

For more about this article see link below. 

https://ieeexplore.ieee.org/document/8943245

Filed Under: Past Columns / Departments

Primary Sidebar

Current Issue

Get the entire issue now.

About the Magazine

IEEE Potentials Magazine is the publication dedicated to undergraduate and graduate students and young professionals. IEEE Potentials explores career strategies, the latest in research, and important technical developments. Through its articles, it also relates theories to practical applications, highlights technology’s global impact, and generates international forums that foster the sharing of diverse ideas about the profession.

POPULAR ARTICLE

Privacy implications of facial recognition technology

Facial recognition technology (FRT) has experienced enormous growth and rapid deployment across different sectors of the society in recent years, mostly motivated by safety, security, and commercial applications. However, major privacy questions arise around this technology, and regulators are still working to provide clear set of rules governing its use. This paper focuses on privacy implications of FRT usage. Specifically, we first present the definition of FRT, followed by an analysis of the vulnerability and risks that can potentially arise and how they might be concerning in such context. Finally, we discuss efforts needed to mitigate privacy concerns related to FRT, from both technical and regulatory perspectives.

Read More…

Search

Past Issues

Footer

IEEE Potentials Magazine is a member benefit for IEEE Student members.

The magazine is archived in IEEE Xplore, and articles from all issues are available for download.

Home | Sitemap | Contact & Support | Accessibility | Nondiscrimination Policy | IEEE Ethics Reporting | IEEE Privacy Policy | Terms

© Copyright 2025 IEEE - All rights reserved. A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.