This is the first talk of the 2021 event series AI +X with a collaboration between deeplearning.ai and Workera. AI + X is a series designed to share the latest AI trends, applications, opportunities and challenges in various industries, and to provide guidance on how AI practitioners and non-technical professionals can build AI + X careers.
MC: Sandhya Simhan, Director of Marketing, DeepLearning.AI
5mins: Opening speech: Kian Katanforoosh, Co-founder & CEO, Workera
40mins: Panel discussion:
-Fernando Lucini, Global Lead for Data Science & Machine Learning Engineering, Accenture Applied Intelligence
-Valerie Alleger, Director, Data and Analytics Strategy, EMEA at The Janssen Pharmaceutical Companies of Johnson & Johnson
-Amirali Kia, Director of AI & Computational Biology, Illumina
-Kian Katanforoosh, Founder & CEO, Workera
20 mins: Q&A. We will be taking questions from Slido.
1:13 Opening speech by Kian Katanforoosh on AI + X overview
11:25 We have this thesis that electricity without a lightbulb is useless. Do you agree/disagree?
17:20 Tell us more about how domain expertise drives AI usage in your company.
25:17 Where do you look for these candidates with dual competencies? And do you see a lack of such talent in the current market?
32:15 It’s clear to us now that employees with AI skills are in high demand and will provide great value to the companies. Can you tell us more about why such a career worth pursuing for someone who is already doing well as a subject matter expert? How is it beneficial for them?
34:56 For those audience members who may be in HR, Learning & Development or part of a Data-AI academy within an organization, what advice do you have for them on how to bring AI+X to their organization at scale?
43:20 Valerie, you studied life science engineering. You started as a sales manager in the field. And you are now the Director of Data and Analytics Strategy at Janssen EMEA. You’re a prime example of someone who has successfully added AI to their subject matter expertise and is now leading an organization. Can you tell us about your journey?”
48:33 Who should be considering an AI + X career? How do they know if they are ready or qualified to start now?
50:35 For the AI practitioners, how do they decide which domain to pursue? How much domain knowledge in a specific field does one need to be able to apply AI in that field successfully?
56:55 How is the path of MLE different from AI+X? Where do you recommend them to start? Any resources and guidance?
1:05:26 The biggest challenge seems to be the transition. How to transition from a non-AI role to a AI/ML linked role?
1:07:42 How can one prove their knowledge in AI if they have a different professional background?
1:08:57 How can we do research in developing countries, where there are limited-resources such as poor connection, power fluctuations, GPU facilities, budget, etc.
1:15:26 What are the industries you foresee as being disrupted by AI/Deep learning in the next decade?
1:20:57 How do you take to a skeptical boss or supervisor to say "hey, we should be utilizing AI in our work" and they are not sold on it. How do you tackle that?
1:23:08 How can we work with AI problems in industries that lack a large amount of data compared to tech standards?
1:27:11 How to find companies eager to create career paths in AI? It seems we need first to join a company that invests in your career and that is mostly not the case.