This document discusses artificial intelligence (AI) and its applications in real estate. It begins by framing AI as algorithms that can perform tasks like classification, regression, knowledge extraction, and optimization. Examples of using these algorithms in real estate include using regression to predict property prices and classification to analyze mortgage applications. The document then discusses how AI benefits enormously from increased data availability. It proposes the idea of a data marketplace and substrate to enable data sharing. Finally, it introduces the concept of "self-owning AI" through programmable legal entities, and examples of how this could enable self-driving cars, forests, and skyscrapers in the future.

1. Trent McConaghy
@trentmc0
Ocean | BigchainDB
An Intro to AI
With Applications in Real Estate

2. Ways to Frame AI

3. “Replicates human cognitive
behavior” [Turing test]

4. “Can do tasks that only a
human could previously do”

5. “Can do a task at speed /
accuracy / capacity not
possible by a human.”

6. “A set of algorithms”
• Classification
• Regression
• Knowledge extraction
• Optimization
• Creative / Structural design
• …

7. AI: Algorithms / Tools

8. Classification, in 2D
Use case: mortgage applications
Salary
Age
Salary
Age
Defaulted
Paid mortgage
Credit profile:

9. Regression, in 1D
age of
building
$ / square
foot
$ / square
foot

10. Regression, in 2D

11. Regression
Use case: predict property price

12. Regression
Use case: “street map” for interiors via 3d
reconstruction [Zillow Home]

13. Knowledge extraction
Use case: closed-form equations for circuits [McConaghy]
CAFFEINE

14. Knowledge extraction
Use Case: closed-form
equations for house prices

15. Knowledge extraction
Use Case: sensitivity analysis
of variables to house prices

16. Optimization
“Find the x that maximizes f(x)”
(With as few evaluations of f(x) as possible)
x
f(x)
Find this

17. Optimization
Use Case: real estate portfolio optimization
Risk
Expectedreturn

18. Structural Design // Machine Creativity
Use Case: jewelry design [Hornby ‘11]

19. Machine Creativity:
Architectural Design
Exploration (1)

20. Machine Creativity:
Architectural Design
Exploration (2)

21. AI: Data

22. 1000x more data
The Unreasonable Effectiveness of Data

23. Mo’ data
(and mo’ compute)
Mo’ accuracy
Mo’ $

25. Data marketplace
Have AI
(Want data)
Have data Have AI
(Want data)
Have AI
(Want data)
Have data
Have data Have AI
(Want data)
Have data Have data Have AI
(Want data)

26. Substrate for 1000 marketplaces
=a data economy
Data
marketplace
DM DM DM
DM DM DM DM
DM DM DM DM
DM DM DM DM
DM
DM
DM
DM
Have AI
(Want data)
Have data Have AI
(Want data)
Have AI
(Want data)
Have data
Have data Have AI
(Want data)
Have data Have data Have AI
(Want data)

27. Self-owning AI?

28. Giving rights to AIs
Via Programmable Legal Entities (PLEs)

29. Self-driving,
self-owning cars

30. Self-owning
roads

31. Self-owning forests
“Terra0”

32. Self-owning
skyscrapers
Photo: Oran Virincy CC-BY 2.0,
https://www.flickr.com/photos/viriyincy/2902963193
Aka
“Create your own
customer”…

33. Conclusion

34. AI Yesterday → Today → Tomorrow
Algorithms .. Data .. Self-owning
Property prediction, “street map” for interiors, creative building
design, real estate data++, self-owning buildings
@trentmc0Trent McConaghy