Features

Today, digital twins are not limited to just physical objects. With the rise of virtual and augmented reality technologies, digital twins can now replicate entire environments and systems in a virtual space. This has opened up new possibilities for testing and simulation, allowing companies to reduce costs and risks associated with physical prototypes.

Like so much at the frontier of science and engineering, quantum computing looks and sounds like science fiction. IBM’s Quantum System Two boasts a vacuum-sealed “quantum chandelier” on its insides, glimmering both literally and figuratively. And, for the layperson, the typical reaction is a mix of confusion and amazement. But for the engineer, quantum computing represents something different: an opportunity to shape the future in ways previously thought impossible.

Engineering summer programs take place during the seasonal summer vacation, and offer aspiring engineers the chance to gain some hands-on engineering experience. They also come with networking and mentorship opportunities.

Edge technologies bring data storage and data processing closer to where data is generated. That simple shift has big benefits. While cloud computing relies on sending data back and forth between a centralized server, edge computing performs computation closer to the source, reducing latency and bandwidth usage. As applications increasingly rely on ultra-fast, near-instantaneous connections, edge technologies are an essential tool for enabling them.

Climate change is real. Its effects are drastic, and worsening. Global efforts to cut emissions and reduce fossil fuel consumption have met with mixed results. To mitigate the most catastrophic outcomes of climate change, some engineers are turning to outside-the-box ideas like solar radiation management.

Data science is an interdisciplinary field that leverages scientific methods, processes, algorithms, and systems to extract insights and knowledge from both structured and unstructured forms of data. It’s commonly associated with big data and artificial intelligence, combining statistics, data analysis, machine learning, and related techniques to understand and analyze actual phenomena with data.

AI’s integration into the architectural landscape is a testament to the industry’s readiness for technological evolution, and it continues to shape the future of architectural design. “It goes hand in hand with computer science developments. It’s a long legacy,” says Dr. Daniel Koehler, assistant professor at the University of Texas at Austin School of Architecture.

Mechanical engineering is one of the oldest and broadest engineering disciplines. Its domain stretches across complex mechanical systems’ design, analysis, manufacturing, and maintenance. While mechanical engineering has played (and continues to play) an enormous role in the evolution of the automobile, it represents just one area of a massively important discipline.

Launched into the mainstream with ChatGPT, today’s generative AI models have applications in every field and discipline; tomorrow’s impacts will be wide-reaching. Given its broad applications, the challenges within AI are many. Its transformative power works in both directions and the potential risks are roughly commensurate with the potential rewards.

Apple’s A16 Bionic processor has 16 billion transistors. There is no way for a human to design such a chip manually. In electronic design automation (EDA), a field that includes the design of chips and circuit boards, today’s engineers rely on software tools to aid them.