iOi Summit AI Hackathon

Meet the AI Hackathon Sponsors

Updates:

On August 28th and 29th, 2018, teams from around the country will be meeting in San Francisco at NAR’s first iOi Hackathon to determine how artificial intelligence and machine learning impact the future of real estate. Teams can start building their ideas on August 1, and will present them as part of the iOi Summit on August 29th. It is imperative that all participants in the hackathon adhere to our Code of Conduct and frequently review the terms and conditions.

Hackathon registration is currently closed, and the teams are hard at work on their projects. iOi Summit attendees can see the winning project when announced on 8/30. Thank you to all applicants.

Hackathon Theme and Potential Project Ideas

The Problem(s)

Artificial intelligence and machine learning are already impacting real estate. From chatbots to natural language processing to predictive search, products are evolving. What is possible outside these realms? This hackathon aims to find new and novel approaches to how artificial intelligence and machine learning will impact real estate. Some example problems to explore:

  • How can we improve the ways in which agents serve their clients?
  • What are the opportunities for improving home search in the real estate industry?
  • How can agents maximize their marketing opportunities with less effort and without opening themselves up to legal issues?
  • How will data display be impacted by these technologies?

We aim to think deeply in this hackathon about these problems and how AI/ML can be applied to solve them.

Potential Projects (Solutions)

Realistic Agent Avatars

Advances in audio and video manipulation are improving every day. Videos of presidents, world leaders and celebrities are made to look like they are saying things that they aren’t actually saying using AI and ML software. Audio mimicry, where a person’s voice can be used to read text that is input, is being used in realistic sounding ways, with cadence and pronunciation being impersonated. Applications like Lyrebird use tweets to create realistic sounding audio of people reading them. Researchers at the University of Washington as well as German researchers are creating video avatars that can be manipulated by using direct audio input. Using b-roll video of the REALTOR and a copy of their synthesized voice, you could create a streamlined method for them to create promotional videos. What if these video and audio projects could be combined to allow for agents to create presentations on properties or CMAs on the fly with just text input? How could listing data be used to create enhanced presentations?

Use Computer Vision for Video or Image Parsing and Natural Language Generation

Parsing Images to Create Accurate Image Descriptions of Images for ADA Compliance

As part of ADA Compliance, all NAR members must make sure that they are updating the image descriptions for screen readers so that people with vision impairments can get correct information about listings. Doing so accurately and completely can take some time, especially when there could be anywhere from 10-20 images per listing. Using computer vision and natural language generation, these image descriptions could be auto-populated. This would allow a member to upload photos to their MLS, have the images parsed and for each image, description details that auto populate the HTML “alt” attribute.

Parsing Video for Creating Listing Details in Real Time

Another step that can be challenging for members is getting listing details entered into more than one MLS. One member could belong to several MLSs and need to create the property details for each one. In this idea, using video, you could create the property details via your phone’s camera. The NeuralTalk project in the Netherlands provides an example of how this could work. Moving along inside a property and filming as you move, the software could identify objects and features in a property and create a text file for use or automatically create a draft listing for the agent to review and edit. The video could also be used to generate images for the property listing.

Create a home price prediction model using only photos and listing details of the property and area

Automated Valuation Models (AVMs) have been around for years, but people have been concerned about their accuracy and usability. Some have been wildly inaccurate and caused issues with real estate professionals and their clients. What potential is there to create a home price prediction model that uses photos, both indoor and outdoor, to predict property price? Research papers on this possibility can be found here and here.

Hackathon Rules & Scoring

Rules

  1. All project work must not start BEFORE August 1, 7:00am Pacific, and be completed by August 29, 4:00 pm Pacific.
    1. You must provide your Github repository for the project starting on August 1 in order to be considered for the hackathon.
      1. Note: The repository does not have to be public, but it has to be shared with a member of the organizing team for confirmation.
  2. Your team must use open source software and projects and clearly identify which repositories on Github you are using. Exceptions:
    1. If you do have a proprietary APIs or software you will be using, it must be approved before August 1 by the organizers.
    2. The APIs provided by the Hackathon organizers may be proprietary, but have been cleared before hand.
  3. Teams can have a maximum of five people.
  4. All team members do not have to be present on the days of the hackathon to win, but at least one active member of the team must be onsite for the duration of the hackathon.
  5. You are not required to build any of the project ideas listed above. You can have an original idea for this hackathon, as long as the project applies to AI/ML in real estate.

Scoring for Hackathon

  • Use at least 1 provided API (10 pts)
    • We will provide you a list of potential APIs via email once you’ve signed up.
    • There is no bonus for using more than one API.
  • Creativity (10 pts)
    • How new and novel is the approach to the problem?
  • Functionality (10 pts)
    • Does the final product do what the team claims it does and how much of the functionality is present?
  • Practicality (10 pts)
    • What real estate use case is this for and how necessary is it for streamlining that use case?
  • User Experience (10 pts)
    • Is this application easy to use and accessible for all users?

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