The Asia Tech Podcast was joined by Paul Meinshausen, a co-founder of Aampe. Aampe uses automated, rapid learning to personalize notifications. Paul’s career started doing statistical analysis for the U.S. Department of Defense – which included a deployment to Afghanistan. His role was to try to understand why people do things and get them to do some things less and some things more. It was here that Paul learned a lot about the limits of behavioral science in complex environments.
Some of the topics that Paul and I discussed included:
- Building a startup in India and exiting
- What are the real reasons apps get developed?
- With low barriers to entry and almost unlimited competition, user engagement design needs to evolve
- The era of spending large sums of money on Facebook ads to acquire ads is over
- Continuous, automated experimentation is just as important as machine learning on raw data
- Not understanding the subtle differences can cause investment in the wrong level of data science
- Companies like Facebook and Google have succeeded as much due to massive experimentation as to traditional machine learning
- The implication of the scarcity of time and attention
- What personalization means for media companies
- The state of tech and startups in Southeast Asia
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DISCLAIMER: The views and opinions expressed by the podcast creators, hosts, and guests do not necessarily reflect the official policy and position of Podcast Network Asia. Any content provided by the people on the podcast are of their own opinion, and are not intended to malign any religion, ethnic group, club, organization, company, individual, or anyone or anything.