Artificial Intelligence (AI) has revolutionized the way we interact with technology, and one of the most intriguing branches of AI is Generative Artificial Intelligence or generative AI. This cutting-edge technology can potentially reshape numerous industries, including construction and engineering. Generative AI models that generate new content in various forms, such as text, images, music, and videos, are gaining substantial traction in the business world. These models can be fine-tuned using an organization’s proprietary data and work in collaboration with human experts to enhance productivity significantly. Estimates suggest that the global economy could gain a staggering $7 trillion annually from this boost in productivity.
One of the most recognizable applications of generative AI is chatbots, which have become ubiquitous for their ability to create human-like conversational text. These AI-driven chatbots can synthesize complex ideas and information from extensive datasets, enabling them to assist in various business tasks such as email and presentation writing, ideation for marketing campaigns, and much more.
The History
Generative AI’s development can be traced back to the early days of AI research, with critical algorithms emerging in the 1980s. Recent advancements in training algorithms, the availability of purpose-built processing units like GPUs, and improved training data sets have contributed to the rapid progress we witness today. The outcome is generative AI models that closely emulate human creativity. The innovation in this field is accelerating at a breathtaking pace, leading to a new era in technology that promises greater productivity and novel solutions to previously insurmountable business problems.
Generative AI for Construction & Engineering Firms
While generative AI has been making waves in various industries, one sector that stands to benefit immensely is the construction and engineering industry. This industry has been slow to embrace digitalization, with productivity growth stagnant at a mere 1% over the past two decades. Given that construction represents a substantial portion of the GDP of countries like the United States and the United Kingdom (around 6%), improving productivity through better data utilization and technology adoption during the design process can lead to more sustainable development.
Generative AI holds the potential to provide solutions to the industry’s growing need for data. Modern construction sites are hubs of technology, and AI that can analyze data rapidly and with greater insight is in high demand. Properly implemented generative AI can yield improvements in energy efficiency, carbon footprint calculations, on-site safety, and security. However, it’s crucial to emphasize that human review remains an essential component of this equation. Regardless of how advanced technology becomes, it still requires highly skilled human minds to fact-check, analyze, and understand the nuances necessary for each stage of construction.
Another important consideration when implementing generative AI in the construction and engineering industry is the quality and timeliness of the data used. Data must be current and comply with the latest laws and regulations to ensure that generative AI contributes positively to the field. Human input is vital to navigate these complexities and ensure the AI’s outputs align with industry standards and expectations.
Oracle’s Adoption of Generative AI
Oracle has made significant strides in harnessing generative AI for the construction and engineering industry. In June, Oracle entered the generative AI market by providing large language models (LLMs) to their customers. Oracle has broadened access to this powerful AI technology across its cloud infrastructure, electronic health record (EHR) software, data analysis tools, Enterprise Resource Planning (ERP) software, and customer service software.
Oracle’s generative AI cloud service, as well as artificial intelligence enhancements in healthcare software and new database capabilities for storing and retrieving unstructured data, further exemplify the company’s commitment to incorporating generative AI into various aspects of its offerings. Oracle Analytics Cloud, a platform for visualizing and collaborating on data, now allows analysts to interact with data using plain language and generate responses through AI. Additionally, the software can automatically extract key information from text and image files.
In Conclusion
Generative AI is poised to revolutionize the construction and engineering industry by enhancing productivity, sustainability, and data analysis capabilities. With Oracle’s foray into generative AI, we can expect more innovative applications and solutions that will help the industry overcome its digitalization challenges and pave the way for a more efficient and sustainable future. However, it’s essential to remember that the human touch remains a crucial component in ensuring the success of generative AI in the construction and engineering sector.
