Dr. Olubayo Adekanmbi, the Founder and Chief Executive Officer of Data Science Nigeria, stated that the practice of engineering, from the aspect of the transformative power of new technology, has been implored to enhance capacity for the usage of Artificial Intelligence (AI) in areas and aspects of product design, manufacturing and the building design. The Founder and Chief Executive Officer of Data Science Nigeria disclosed this information at a webinar titled “Generating anything with Artificial Intelligence: Building impactful solutions with large language models”.
The webinar was coordinated by the Nigerian Academy of Engineering (NAEng) and was held in Lagos. According to the announcement made by Adekanmbi on the interest of investors in generative AI, there have been an increase with an estimated $14.1 billion funding in 86 deals in 2023 which is above the 2019 funding worth $1.2 billion for 59 deals. Emphatically, architectural plans can be built and auto-generated by building developers and architects, depending on budgets, climate conditions and building location.
ChatGPT is a software that permits users to inquire questions.
In addition, he explained that the plans can be generated possibly through the building of design and AI applications in aspect of engineering. Furthermore, in relation to his statement, he made it known that generative AI can be deployed by professionals with required capacity and skills to assist and enhance the skills of the engineers and further aid the project developers to use and optimise the facilities, such as, water systems, heat pumps, the build-out of solar farms and many other infrastructure projects.
Adekanmbi mentioned that designers and engineers can implement generative AI in aspects of product design and manufacturing to promote the development of parts and design, including the components. On the implementation of Chat Generative Pre-training Transformer (ChatGPT), it is regarded as a software that permits the user to inquire questions through the use of natural or conversational language. Also, senior engineers were informed that the prediction of a word in a sequence of words is the most primary training of language models.
There are ethical issues associated with Generative AI.
More so, the system is commonly known as masked-language-modelling or a next-token-prediction. Relatively, ensuring to test various outputs and proper grammar, giving as much context as possible, use of concise language and inputting a clear and specific prompt are regarded as the rules and regulations that speed-up engineering. Nevertheless, he warned that there are ethical issues that are associated with Generative AI. Also, the concerns include intellectual property (IP) issues, privacy concerns, inaccuracy, biased responses and lack of transparency.
Prof. Peter Onwualu, the President of the Nigerian Academy of Engineering implored members to exercise and practice the knowledge acquired during the forum. He also urged them to get engaged in the sector, particularly into the academy’s engineering innovation competition. Members were further called on to introduce board professional engineers in fields to collaborate with the academy for inclusiveness. In addition, there are various major differences between Deep Learning (DL), Machine Learning (ML) and Artificial Intelligence (AI), although they are used interchangeable.
AI is designed to carried out specific tasks, such as playing chess.
Succinctly, concentric circles is the only visual relationship among the technologies. Historically, AI has been known to use human intelligence for the accomplishment of task; this is known at the basic or elementary level. Importantly, AI is designed to carried out specific tasks, such as playing chess, trading stocks or even navigating a vehicle. This also made the engineering innovation creative and efficient in productivity. Also, the effective and progressive state of AI in the engineering sector involves the intervention of humans in the processes and sorting out new situations.