Kaustubh (@_ofkaus) and Prashant (@primaprashant) sit down with Hazumu Yamazaki (@HazumuY), co-founder and co-CEO of Empath, to talk about challenges in building an AI product - from getting initial users to serving 3100 customers in 50 countries, from starting with zero data of their own to creating their data supply chain, and more.
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00:00 - Intro
01:17 - What's Empath all about?
02:31 - How Hazumu's PhD research led to Empath
04:37 - Market research and validation for emotion recognition API
07:47 - Getting initial users and longer B2B sales cycle
09:55 - Founding team
11:11 - Becoming sustainable
12:16 - Improving productivity of online meetings with JamRoll
16:55 - Interesting feature requests like lie detection
18:15 - Problems with emotion recognition in videos
21:48 - Collecting data for a new AI startup
23:47 - Adding labels to the collected data
24:45 - Recognizing emotions in different languages
26:05 - Sarcasm and hidden contexts in conversations
27:49 - What distinguishes Empath from publicly available models
30:06 - Tech stack at Empath
32:02 - Adoption of AI Japan
33:40 - Advice for the initial stages of building an AI product
35:11 - Organizations that support AI startups in Japan
37:10 - Going global
38:54 - How to make a great pitch
41:23 - Funding rounds
42:00 - Biggest challenge in reaching the next milestone
43:46 - Long term vision for Empath