This document provides an overview of a community and directory for all things related to artificial intelligence. It summarizes discussions from various speakers on topics like the future of AI, how AI will impact jobs and business, creativity and art, ethics and privacy, and career opportunities in AI. The document also provides advice on how to prepare for a career in AI through attending events, learning from newsletters and podcasts, getting experience, and networking with people working in the field.

1. Community and Directory for All Things AI
Tabitha Goldstaub - Co Founder
@Cognition_X @tabithagold

3. Transformation not technology

4. You got the history of AI from
Dr. Stefanos Zafeiriou,
Imperial

5. Dr. Stephen Cave
3 Principles of AI 1) AI that
enhances us not replaces
us 2) AI we can trust -
transparent and explains its
decisions 3) Responsible
innovation paying attention
to its impact on groups

6. Ed Newton-Rex, Jukedeck
Creativity is not dead!
- Art is about more than work
- People will always be creative
Ultimately AI will contribute to Art

7. Dr. Carsten Sorensen
- Future of business
- “Data” is data about us and privacy will be redefined

8. Calum Chace - on job replacement
Machines don’t care if you’re white collar or
blue collar. They are “collar-blind”.

9. 300% increase in
fundraising this year for
AI companies

10. Hugo Pinto, IBM Innovation
We are about augmenting people
to do a better job - automating
processes and exploring years
and generations of information.
How different will the learning
experience be - with all
knowledge at the distance of a
click or a question?

11. Dr. Daniel Hulme, Satalia & UCL
There are lots of exponential problems
out there! Humans are rubbish at solving
this!
Computers neither but together better...
What is “good”?
Our purpose is to create a world where
people can do what they love?

12. Dr. Rob Fraser, Microsoft
Augmentation vs replacement is all great
but it’s a design choice.
It’s a red pill blue pill choice!

13. Aurora Flint, Python coder (8yrs)
Loved the Tesla cars and the
application for AI on Music.

14. Men and Women plus Machine

15. Data Scientists can come from anywhere...

16. You need to...
Be adaptable
Be curious and like asking questions
Be comfortable experimenting
Have a good intuition for when to stop.
Feel comfortable with failure
Have a passion for understanding a sector
Be excited to and enjoy learning
Like to be at the cutting edge of technology

17. Research Scientist / Engineer
Data Miner
Data Science
Data Engineer
Product Manager
Program Manager
Product Marketing
(Chief) Technology Officer
Software Engineer
Language Technologies
Optimization modeller
Visualisation Engineer
Physics programer
Buss Dev
Sales
Events
Marketing
Social Media
CRM
Production
Public Policy

18. ● Pick a sector
● A Big 4 disruptor
● Disruptors
● The disrupted
● A startup
● Start your own
● Government
Everything is being disrupted.
You can work for:

19. New Data
Metric
Data
Processing
and Quality
Data
Interrogation,
Security and
Access
Analysis,
Hypothesis
and Impact
Applied
Data
Science
Leadership
Communication
Storytelling
Define,
specify and
create
metric /
events Develop
requirements
and monitor
outcomes
Run queries
against
complex data
setsUnderstand
trends and
create a
narrative
Run
analysis and
build
repeatable
data
models
Builds
collaborative
relationships and
is trusted
Skills needed
for a data team

20. Develop
requirements
and monitor
outcomes
Run queries
against
complex data
setsUnderstand
trends and
create a
narrative
Run
analysis and
build
repeatable
data
models
Builds
collaborative
relationships and
is trusted
Define,
specify and
create
metric /
events

21. How do you prepare yourself?

22. Go to conferences,
events and meetups

23. Love your
Newsletters
and Podcasts

24. Learn to talk to an AI

25. Be a
Book
Worm

26. Keep learning all the time

27. Have an opinion on all ethics questions

28. Get experience

29. Get advice for the interview

30. Andrew Ng
Jana Eggers
Fei-Fei Li
Megan Price
Hanna Wallach
Samantha Payne
Yao Zhang
Karen Matthys
Jill Dyche
Yanbing Li
Be inspired by people
Neha Narkhede
Randy Olson
Kirk Borne
Yann LeCun
Nando de Freitas
Gregory Piatetsky
Ben Lorica
Maggie Bowden
Nathan Benaich
Azeem Azar
Daniel Hulme
Look for people like you and not like you

31. Where the training data is coming from?
Who’s in charge of security?
etc….

32. Today you can...
Join the network
Sign up for the Daily Briefing
Start job hunting
Attend our events
Register for the beta
Come work with us
cognitionx.com/join
tabitha@cognitionx.io
beta@cognitionx.io
@cognition_X