Why Choose Computer Engineering in 2023?

In 2023, generative artificial intelligence has changed the public conversation about computing. Tools that can produce text, images, and code have made many people ask what software work will look like in the future.

That question is actually a good reason to study Computer Engineering.

What changed this year

ChatGPT launched November 30, 2022 and reached 100 million users within two months — the fastest consumer technology adoption on record. GPT-4 followed on March 14, 2023 with substantially stronger reasoning and the ability to process images. Google released Bard in February. Meta released LLaMA in February, making large language model weights available to researchers and enabling an explosion of open-source fine-tuning and experimentation. GitHub Copilot crossed 1 million paid users by early 2023 and is now embedded in editors used by professional developers daily.

These are not peripheral events. They represent a measurable shift in how code is written, how text is generated, and what kinds of tasks people expect software to handle. Asking whether to study computing in this environment is, in a sense, answering the question in reverse.

Why the fundamentals matter more, not less

When tools become more capable, understanding the systems behind them becomes more valuable, not less. AI applications still depend on algorithms, data structures, databases, networks, cloud infrastructure, processors, security, and software engineering. The transformer architecture that underlies GPT-4 is built on linear algebra and probability. The infrastructure running ChatGPT depends on distributed systems, GPU clusters, and low-latency networking. Someone has to design, build, evaluate, optimise, and maintain those systems.

Computer Engineering provides foundations across these areas. Students learn programming, but the degree is not only about learning how to type code. It is about understanding computation: how information is represented, how algorithms use resources, how operating systems manage hardware, how computers communicate, and how complex systems are designed.

What changes for graduates

AI coding assistants may change the way programmers work, just as higher-level languages changed it before. Engineers will likely spend less time on routine code generation and more time deciding what should be built, verifying that AI-generated results are correct, integrating systems, and solving harder architectural problems. The ability to read code critically and reason about correctness becomes more important, not less, when the first draft comes from a model that is sometimes wrong in subtle ways.

The field also remains much broader than AI. Cybersecurity, robotics, cloud computing, embedded systems, data engineering, computer graphics, networking, and hardware design all need strong engineers who understand fundamentals.

Students considering the department should expect difficulty. Mathematics matters. Debugging requires patience. New technologies appear constantly, and graduation is not the end of learning. But that continuous change is one of the best parts of the profession. A strong Computer Engineering education gives you a framework for understanding technologies that may not even exist when you begin university.

In 2023, nobody can predict exactly how computing careers will look ten years from now. That uncertainty is not a reason to avoid the field. It is a reason to learn the fundamentals well enough to adapt.