Globant and the California College of the Arts (CCA) got together to present CON.VERGE, their first conference for business executives and thought-leaders. Jana Eggers leads a neuroscience-based artificial intelligence company focused on turning big data into smart actions. Her tech experience comes from positions at Intuit, Blackbaud, Lycos, American Airline’s Sabre, and Spreadshirt. She is a mathematician with a computer science. During her talk during the event, Digital Disrupters - Visionary Thinking, she elaborated on how Artificial Intelligence offers a new approach on how we analyze the data. Check out her presentation for more details.

1. Onboarding AI
NEUROSCIENCE-BASED
ARTIFICIAL INTELLIGENCE

2. Page 2
We’ve outgrown the capabilities
of historical data analysis tools
We’ve tapped out
conversion increases
Expert systems are
exception systems
Consumers are tired of searching
and bad recommendations.
Enterprises spend millions in effort
and costs to eke out at a 2% lift.
They focus on the past
and require step-by-step training.
Enterprise data is locked in silos,
not shared across boundaries.

3. AI offers a new approach
Page 3
• What is AI? Algorithms focused on learning from data
• Ram Charan, Jan 2015: Algorithms are the single greatest
instrument of change in today’s business world
• Why now? Data and compute power
• >90% of the world’s data was created in the last 2 years
• What’s new? Deep learning and neuroscience discoveries
• Google, Oct 2015: Machine learning is a core, transformative
way by which we’re rethinking everything we’re doing

4. AI is emerging, AND, it will grow up fast
Page 4

5. AI
Subfields

6. School “Supernodes”
MIT, Stanford, CMU,
Berkeley
Strong US / non-US
network divide
Academia

7. “Supernodes”
Google, Bell Labs, SRI
Business

8. IOHO: Benefits of a neuroscience approach to AI
Page 8
Popular approaches
Neural networks, Bayesian networks
● Large amounts of historical data required
● Supervised versus unsupervised tradeoffs
● Black box
Nara Logics Platform
● Adaptive inference works as well on big
and small data
● Automatic data expansion via context
and mining
● Exposes reasons for recommendations
Input layer Hidden Layer Output Layer

9. SAMPLE PROBLEMS SOLVED
Page 9
eCommerce Omni-channel personalized product and offer
recommendations
Healthcare Matching patients with doctors, and doctors with experts
Talent
Management
Assigning team members to projects
IT &
Call Centers
Prioritization and case assignment
Financial
Services
Matching demand with portfolio holdings; ecosystem
development
Travel &
Lifestyle
Personalized recommendations for restaurants, hotels,
movies, wine, and apps
The key is question: What are we matching?

10. Page 10
Industry vs.
>34%
* 103% for top 3
Increase in
Prediction Accuracy
benchmark
optimizations
Increase in
Operational Efficiency Priceless
manual
efforts
Increase in Conversion
for eCommerce customers >25%2%

11. Page 11
Successfully onboarding the
ghost in the machine

12. Robots are extraverts, Algorithms are introverts
Page 12
“The bigger lesson from the
experiment suggests that service
robots will need some way
to interpret human behavior and
social cues.”
Action #1
Design the full expectations and
interactions with your algorithms.

13. AI Algorithms can seem silly at first
Page 13

14. Mathematicians
Physicists
Computer Scientists
Data
Compute Power
Neuroscientists
Product Owners
IA & UX
Business Problems
Funding
Ethicists
Social Scientists
Lawyers
Entrepreneurs
Suits
Kids & Grandmas
You
You You
You
You
You
@jeggers

15. Start small
Page 15
It isn’t rocket science.
It is space program execution.
Action #3:
Start with a stepwise plan
towards a vision.

16. Beware of Kasparov’s mistake
Page 16
Action #4
Expect bugs,
including in your data.

17. Don’t underestimate the complexity
Page 17
Action #5
Bring in expertise for the problem
definition, for the ethics involved,
for the algorithms built.

18. Successfully onboarding the ghost
Page 18
1. Algorithms are introverts… Build a job description
2. AI is emerging tech… Be a coach and mentor
3. Start small… Regularly evaluate the job being done
4. Learn from Kasparov… Expect mistakes
5. Complexity requires expertise… Provide professional
development

19. Onboarding AI: Questions?
NEUROSCIENCE-BASED
ARTIFICIAL INTELLIGENCE