Artificial Intelligence and Real Estate with Nathan Brannen
May 10, 2023
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Nathan Brannen, CPO at Restb.ai, talks about AI in real estate: current state of data, computer vision in real estate, future of the industry, and improving AI's potential.
MLS data is valuable for AI applications and offers opportunities for data access and utilization, including compliance and data enrichment.
Standardization of MLS data fields, lookups, and dictionaries is crucial for efficient data processing and integration of AI technologies into different MLS systems.
Deep dives
The Value of MLS Data in AI
MLS data is valuable for AI applications because it provides access to structured data that can be used to train models. Compared to many other markets, the MLS data landscape is actually quite good, offering opportunities to access and utilize data for various purposes. This includes compliance, data enrichment, and the ability to populate fields in the MLS system automatically. AI can help automate tasks that would otherwise require manual review, saving time and allowing agents and professionals to focus on more important activities.
Challenges in MLS Data Standardization
One of the main challenges in MLS data is the lack of complete standardization between different MLS systems. This extends to both the data itself and how it is accessed. Standardizing fields, lookups, and data dictionaries is crucial for efficient data processing and interoperability. Currently, there is a lack of standardized naming conventions and formats for fields and data, which creates challenges when integrating AI technologies into different MLS systems. However, efforts are being made to address these issues and move towards greater standardization.
Applications of AI in Real Estate
AI has a wide range of applications in the real estate industry. One key area is computer vision, which involves training AI models to understand and analyze images of properties. This can be used for compliance purposes, such as detecting unauthorized branding or identifying specific features in listing photos. AI can also be used for valuation, assessing the condition and quality of properties based on visual data. By analyzing photos and videos, AI can provide granular insights and standardized measurements that were previously difficult to obtain, enabling more accurate valuations and personalized search experiences.
The Role of AI in Minimizing Bias
While bias is an important concern in AI, the use of AI in real estate, particularly in analyzing photos, can actually help minimize bias. AI models can provide a more neutral and standardized analysis of property data, free from subjective biases. By focusing on specific visual indicators and standardized measurements, AI can help identify potential bias in appraisals or valuations, providing an additional layer of assessment to ensure fair and accurate outcomes. The use of standardized data and granular insights from AI can support more informed decision-making and reduce the impact of bias in real estate transactions.
Nate is at the forefront of AI and real estate as the chief product officer ar Restb.ai. Evan and Nate discuss how AI is transforming the real estate industry. Topics range from the current state of real estate data, computer vision applications in real estate, what the future of real estate looks like, and what needs to improve for AI to reach it's potential in the space.
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