Using Machine Learning To Build Better Teams

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Event

Using Machine Learning to Build Better Teams

12 November 2018

New York

Added 30-Oct-2018

Gain insights on how machine learning based productivity working for Uber, Starbucks, WeWork, and Pinterest can help your teams as well.

 

Interested in getting hands on with image recognition? See our pre-event workshop.

Event Schedule

6:00 PM Networking & Food, Beer
6:30 PM Kickoff & Sponsors (IBM, Betaworks Studios)
6:40 PM Eric Typaldos, Hive - The productivity platform powering the speed of Uber, Starbucks, WeWork and Pinterest.

7:20 PM TBD
8:00 PM Extended Q&A and Open Member Discussion

Presentation Summary:

While AI powered tools can help teams automate processes and common tasks, it does not eliminate the need to manage the people on the team. Bottlenecks can still occur when employees are over resourced or delayed in providing deliverables. How can we utilize this technology to build better and more effective teams? In this session, Eric will discuss the common issues faced by teams, how they manage projects, and how machine learning can predict and eliminate these issues. He'll review current solutions and approaches, as well as highlight future use cases and how machine learning will change the modern workplace.

Speaker Bio:

As CTO and co-founder of Hive, Eric Typaldos builds the platform that helps teams overcome today’s and tomorrow’s challenges in the workplace. After spending his career empowering enterprises and government organizations to be more productive and collaborative, Eric knows what truly drives happy, high-performing businesses — and he bakes this thinking into Hive.

Eric’s technical expertise with enterprise collaboration was first used at the White House, where he built max.gov, the federal government’s platform, used by over 750,000 employees.

That success led to a career in Oracle’s federal consulting practice with a focus on collaboration in government, education, and healthcare across federal government and Fortune 500 projects.

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