Speaker: Chris Bishop
LinkedIn: https://www.linkedin.com/mynetwork/
Talk Title: AI + humans = perfect timing
Schedule:
6:00pm - 6:30pm - Intro, Dinner & Refreshments.
6:30pm - 7:00pm - Chris Bishop Talk
7:00pm - 7:10pm - Q&A
7:10pm - 7:40pm - Ilan Man Talk
7:40pm - 7:50pm - Q&A
7:50pm - 8:30 - Networking
Bio:
Christopher Bishop is passionate about the power of emerging technologies to deliver positive transformation at the intersection of business & culture. He is especially excited about the potential of AI & machine learning to provide solutions to problems. Chris first became fascinated by AI after being hired by IBM in 1998 just as their seminal supercomputer Deep Blue beat the world chess champion, Garry Kasparov. Chris went on to work at Big Blue for fifteen years in a variety of strategy & communications roles. He wrote about the challenges & opportunities that AI represents in his summary of the AI Now | 2017 Symposium at the MIT Media Lab Brave new world: implications for AI. For more background on Chris & his perspective on AI, please visit his site - ai guys.
Topic discussion:
Your soggy, onboard 3-pound glucose-driven computer is no match for the increasingly powerful deep learning systems that can consume & rationalize with blinding speed the ridiculous amounts of data we are creating. 90% of the information that exists in the world today has been created in the last two years.
But we can consider ourselves very lucky because AI & machine learning tools can help us make sense of the information tsunami. Smart companies will certainly exploit the power of the new generation of tools to generate attributable revenue. But advanced deep learning AI instances will also give humans the power to address what have historically been intractable social problems.
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Speaker: Ilan Man
LinkedIn: https://www.linkedin.com/in/ilanman/
Talk Title: From ideation to production: applying machine learning in the real world.
Bio:
Ilan is the head of Data, leading the Analytics, Data Science & Data Engineering efforts at Paperless Post. A statistician by training, Ilan enjoys applying technical models to solve real-world problems. When he has time, he tries to simplify complex topics in easy-to-understand ways on his blog www.ilanman.io. He lives in Prospect Heights with his wife & 16-month old.
Topic discussion:
Applying Data Science or Machine Learning in the real world requires a delicate balance between scientific rigor & practical business deliverables. In this talk, I'll share some learnings from productionalizing a number of ML models at Paperless Post. We'll cover 3 broad & overlapping themes:
1. Think outside the textbook
- Be creative with your models
- Know when to bend the rules
2. Remember your constraints
- Data sources & infrastructure
- Business requirements must be top of mind
3. Listen to your surroundings
- Non-ML domain experts can add a lot of value
- Leverage your team
