Now, when a question arises, it is not spoken or typed into a computer. Instead, thoughts are transformed into a radiant vector. The moment this happens, the library comes alive. The books (or documents) that resonate with the query light up, leading straight to the most relevant pieces of information. This real-time matching and guidance are orchestrated by what is known as a 'vector database.' The magic deepens when this is applied to the AECO world. Picture an architect standing in this library, wondering, "Which designs have been optimized for tropical climates?" As the question forms, related project blueprints and design documents shimmer in response, ensuring the architect does not waste hours but gets instantaneous resources. In digital, real-world applications, this means that the vastness of AECO documentation — from initial drafts to finalized O&M manuals — can be transformed into a responsive, intuitive database. Questions from, "Show contracts that involve sustainable materials," to "Where are the protocols for earthquake-resistant infrastructures?" get swift, precise answers, eliminating the tediousness of manual searches and ushering in an era of streamlined information retrieval. In essence, embeddings and vector databases weave the tapestry of the future, where information is not just sought but is intuitively and vividly presented, ensuring that the AECO industry remains not just on the cutting edge but also marvelously efficient. Boundaries of the System Harnessing the power of embeddings and vector databases has undeniably brought a huge change in how vast amounts of information are accessed and processed. Yet, like all pioneering technologies, this method comes with its unique set of challenges. First, there is the question of text chunking and how to determine the ideal size of text to be fed into the system for vector conversion? If too small a slice is taken, the risk is losing context, making the resulting vector a poor representative of the actual content. Think of it as trying to understand the plot of a novel by reading a random paragraph–there is some information, but not the whole story. Conversely, if the text chunks are too large, not only is the system flooded with unnecessary data, but also risks exceeding the token limit, especially when further processing it with GPT. While embeddings can determine thematic relevance, they are not inherently designed for precise data retrieval. They shine when answering queries like, "How can BIM benefit our agency?”, and pulling insights from presentations, roadmaps, and guiding documents. However, for more data-specific questions such as, "How many BIM projects were completed last year?", the embedding method might falter. It is a matter of qualitative versus quantitative data retrieval– while embeddings excel at the former, they are less adept at the latter. To navigate these challenges, it is essential to see embeddings and vector databases as evolving tools. As the AECO industry and its informational needs grow, so too will the sophistication and adaptability of these technologies. Balancing the size of text chunks, refining the vector database for more precise queries, and integrating
other AI systems can further optimize and refine this promising avenue of information management. A Bright Horizon Navigating the vastness of AECO documentation has been a historic challenge. But with the integration of GPT and embeddings, the brink of an information revolution is close. The potential to instantly access the right knowledge not only streamlines processes but also fosters a culture of informed decision making. While the system has its limitations, its introduction marks a significant step forward, setting the stage for a more informed, efficient, and agile AECO industry. Unlocking Potentials Implementing GPT combined with embeddings offers the AECO sector unprecedented advantages: • Efficiency: Searching becomes instantaneous. A project manager could request, "Show all protocols for seismic safety in high-rise buildings," and get immediate results. • Precision: Instead of sifting through irrelevant data, stakeholders receive only pertinent documents, minimizing information overload. • Learning: New employees can get up-to-speed quickly, asking questions about company protocols or past projects, and receiving precise answers. Use Cases • Design Phase: Architects can effortlessly retrieve design standards or past project references that match current project specifications. • Construction: Contractors can instantly access material safety data sheets or machinery operation manuals without hands-on searches. • Operations: Facility managers can query specific O&M procedures, ensuring optimal building operations and safety Dr. Jeff Chen, Ph.D., LEED AP is Director of Digital Transformation, Symetri . Dr. Chen leads digital technology integration services for all aspects of client businesses to drive efficiency, reduce environmental impacts, and increase sustainability. George Broadbent is Vice President of Asset Management, Symetri . Prior to his current role, George was Director of Asset Management. He has more than 25 years of diversified professional experience in Asset Management, Electronic Content Management, System Architecture and Vital Records Planning and Management.
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October 2023 csengineermag.com
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