Talk Summary: State of the art AI approaches can struggle to create solutions which provide accurate results that stand the test of time. They are also plagued by problems such as bias and a lack of explainability. Causal AI addresses these key problems and is at the center of the Geminos Causeway platform, which is built on TypeDB. This webinar will give you an introduction to why causal AI is so important, and how you can start to use it to drive more value for your organisation. Speaker: Stuart Frost Stu is the CEO and founder of Geminos. Their focus is on building AI-driven solutions for mid-sized Smart Manufacturing and Logistics companies, that are frustrated by their inability to digitalize their operations at sensible cost. Stu has 30 years’ experience in founding and leading successful data management and analytics startups, starting at 26 when he founded SELECT Software Tools, and led the company to a NASDAQ IPO in 1996. He then founded DATAllegro in 2003 which was acquired by Microsoft.

1. AI That Knows Why
Causal AI is the Next Big Thing
Geminos Makes It Real!

2. • AI is broken
• Based on patterns in data – mostly correlations
• Bias, lack of explainability & transparency
• Causal AI is the next big step
• Just added to Gartner Hype Cycle
• Geminos provides a comprehensive low-code Causal AI dev platform,
underpinned by causal science
• TypeDB repository
Overview

3. The Problem with Correlation

4. The Problem with Correlation

5. Current State-of-the-Art AI
Subject Matter
Experts
û Explainable
û Adaptive
û Bias?
Solution
Black Box
Correlation-Based
Algorithm
Business
Need
Data
Current State-of-the-Art
Data
Business
Implementation
Solution
Issues
Data
Scientists

6. Current State-of-the-Art AI
Subject Matter
Experts
û Explainable
û Adaptive
û Bias?
Solution
Black Box
Correlation-Based
Algorithm
Business
Need
Data
Current State-of-the-Art
More
Data
Business
Implementation
Solution
Issues
Data
Scientists

7. Validate
and Refine
Models
Remove Bias
Geminos Causeway
ü Explainable
ü Transparent
ü No Bias
Adaptive
Solution
Capture
Problem
Domain
Common Language
Geminos Causeway
Business
Implementation
Collaboration between Data Scientists
and Subject Matter Experts
Hydrate
Models
with Data
Missing Data?
Data
Scientists
Analyse
and Build
Algorithms
Based on Model
Underpinned by Causal Science

8. Validate
and Refine
Models
Remove Bias
Geminos Causeway
ü Explainable
ü Transparent
ü No Bias
Adaptive
Solution
Capture
Problem
Domain
Common Language
Geminos Causeway
Business
Implementation
Collaboration between Data Scientists
and Subject Matter Experts
Hydrate
Models
with Data
Missing Data?
Data
Scientists
Analyse
and Build
Algorithms
Based on Model
Underpinned by Causal Science
Microsoft’s
DoWhy library has
been downloaded
more than 1
million times!!

9. Causal Research and Awards
Judea Pearl – UCLA
Invented Bayesian Networks
2011 Turing Award Winner
for probabilistic and causal
reasoning calculus
Causality Wins
2021 Nobel Prize
in Economic Sciences
Courses on causal inference
popular in hundreds of academic
institutes across the world

10. Causality is the next big thing in AI
Seen as the next step towards AGI
Now being used by major tech companies for their own data science

11. Causal AI hits the Gartner Hype Cycle!
• Huge endorsement of Causal AI
• Will drive a lot of market interest
• Enterprise customers
• Press
• Other analysts
• Geminos & Causalens are the
only credible players

12. Causality IS the next big thing in AI
Seen as the next step towards AGI
Now being used by major tech companies for their own data science
Geminos Makes it Real
Comprehensive, low-code development platform,
underpinned by Causal AI

13. 13
Palm Oil Supply
Chain
Palm Oil is in many foods, cosmetics and household
products
• Largest vegetable oil crop
• 4-10X more efficient than alternatives
Major CPGs such as Unilever, P&G, Pepsi, etc. are
committed to reducing very high-profile problems
such as deforestation, peat burning and forced labor
• They need help understanding the root
causes/effects and how they can intervene to
make a difference
• Major driver of supply chain digital
transformation
• Great fit for a causality-driven approach
Viral marketing opportunity across supply chains and
to other commodities – Coffee, Tea, Sugar, etc.
13

14. 14
Drug Discovery
Use Case
Pharmas are looking for more efficient
ways to develop and discover new
drugs – and new ways of using old
drugs
Causal reasoning combined with
knowledge modeling is becoming more
and more popular
14

15. 15
Intelligence Community
Use Case
IC constantly looking for
news ways to identify
mis/dis-information and
decide how to intervene
Great use case for causal
reasoning
15

16. Commercial Model

17. Thank You
Book a Demo
or Meeting
Learn More
About Causality
AI That Knows Why

18. Forward Looking Statements
This presentation may contain "forward-looking statements" – that is,
statements related to future, not past, events. In this context, forward-
looking statements often address our expected future business and
financial performance and financial condition, and often contain words
such as "expect", "anticipate", "intend", "plan", "believe", "seek",
"see”, "will", "would", “could” or "target". While these forward-looking
statements represent our current judgment on what the future holds,
uncertainties may cause actual future results to be materially different
than those expressed in our forward-looking statements. Because these
forward-looking statements reflect only opinions as to uncertain future
events, we do not undertake to update our forward-looking
statements.