Will ChatGPT AI Revolutionize Engineering and Product Development? Here’s What to Know. 3/28/2023 Read Time : 4 min

ChatGPT is an advanced language model that uses artificial intelligence (AI) and natural language processing (NLP) to provide conversational responses to users. It’s trained on massive amounts of text data, enabling it to understand and generate human-like language. This technology has the potential to revolutionize the way we interact with computers, making communication more intuitive and efficient.

However, despite its impressive capabilities, ChatGPT is still limited in functionality. There are several key areas where its limitations are apparent.

What are ChatGPT’s limitations?

ChatGPT is limited by the quality of the data it’s trained on. While the model is trained on a vast amount of text data, this data is not always representative of real-world language use. The training data may be biased towards certain topics or demographics, leading to limitations in the model's ability to understand other contexts. Additionally, the data may contain errors or inconsistencies that can impact the model's performance.

ChatGPT is also limited by the complexity of language. While the model can generate responses to a wide range of questions and prompts, it’s not always able to understand the nuances of language use. This can lead to misunderstandings or incomplete responses. It may struggle to understand idiomatic expressions or sarcasm, leading to responses that are not appropriate or relevant.

ChatGPT’s ability to process vast amounts of data quickly and accurately can be an asset in fields such as research or data analysis. While it’s an impressive technology, it’s still limited in functionality in several ways. As such, it is important to understand its strengths and weaknesses before using it for a specific use case or domain.  

How could ChatGPT impact engineering? 

ChatGPT is a tool that can assist engineers in their work, but it’s not a substitute for the knowledge, expertise, and creativity that engineers bring to the design and product development process. The AI tool can generate responses for engineering calculations or answer questions about generic engineering knowledge, but those responses should be met with a healthy dose of skepticism and fact checking.

For example, when asked about the best failure theory for ductile materials, ChatGPT gives a thorough explainer of the von Mises yield criterion. But when asked to calculate the moment of inertia on a beam under set conditions, its answer is not in agreement with established values for the moment of inertia about the X-X axis.

While ChatGPT can help engineers answer questions and provide guidance on specific topics, it’s limited by the data it has been trained on and cannot replicate the experience, intuition, and problem-solving skills of a human engineer. Engineers must still be involved in the design process to ensure that the final product meets the requirements, standards, and expectations of the industry and the end-users.

Engineering involves a wide range of skills and activities that go beyond answering specific questions or providing information. Engineers must also be able to analyze data, develop and test prototypes, evaluate trade-offs, and make decisions based on multiple factors, including technical, economic, environmental, and social considerations. These skills require a combination of technical knowledge, critical thinking, and creativity that cannot be replicated by an AI-powered tool.

While ChatGPT is a valuable tool that can help engineers in their work, it is not a substitute for a human engineer. Engineers will continue to play a vital role in the design and development of new products and will need to develop new skills and ways of working that enable them to leverage the power of AI tools while also maintaining their unique value as problem-solvers and innovators.

How Creo leverages AI in the product development process

Creo Generative Design utilizes the power of AI to revolutionize the design process. While not the same type of AI as ChatGPT, generative design uses AI algorithms to generate and evaluate design options, enabling engineers and designers to create more innovative and efficient products in a fraction of the time it would take using traditional design methods.

ChatGPT formats written responses to users’ questions, reducing or removing communication barriers. In the same way, generative design unburdens engineers from mundane trial and error tasks, allowing them to focus instead on higher-level design goals.

One of the key benefits of Creo Generative Design is its ability to rapidly explore and evaluate many design options at once. By defining a set of design constraints and objectives, the software can use AI algorithms to generate hundreds or even thousands of potential design solutions, each optimized for a specific set of criteria. And Creo generative design identifies the best of these options, which can be evaluated and compared., allowing designers to identify the most promising options and iterate on them further.

Another benefit of generative design is its ability to create designs that are optimized for a specific manufacturing process or set of materials. By considering factors such as material properties, manufacturing constraints, and cost considerations, the software can generate designs that are not only efficient and functional but also practical and cost-effective to produce.

Perhaps most importantly, generative design allows designers to explore new design concepts and possibilities that may have been impossible or impractical to consider using traditional design methods. By breaking free from the constraints of traditional design approaches, designers can use the software to generate truly innovative and creative solutions that push the boundaries of what is possible.

Learn more about Creo Generative Design Explore how generative design can help you deliver your best designs in less time. Start Here
Tags: CAD Generative Design Creo
About the Author Katherine Brown-Siebenaler

Katherine Brown-Siebenaler is the Marketing Content Manager for PTC's CAD team. Based in Austin, TX, Katherine is responsible for editing the Creo and Mathcad blogs. She has six years' experience as a content creator for various corporate marketing teams, primarily in SaaS environments. Katherine holds two degrees from the University of Florida, a BS in Journalism and an MA in Mass Communication. She enjoys learning how PTC customers bring software to life in real-world applications every day, leading innovation in their various industries.