Episode 108: Computer Vision, Product Management, and Enterprise Investing with Tom Rikert

Show Notes(02:00) Tom shared formative experiences of his upbringing.(04:17) Tom described his educational experience at MIT and his research thesis in Computer Vision.(07:08) Tom talked about his interest in computer vision and computational neuroscience.(08:38) Tom recalled lessons from his first job out of school as a software engineer at Silicon Graphics, building high-performance visualization systems.(11:32) Tom reflected on his time as a product lead at Autodesk, launching a location services platform for global wireless carriers and a developer ecosystem for GIS applications.(13:48) Tom reflected on his MBA experience at Harvard Business School.(16:54) Tom reflected on his first stint at Google - leading a sales operations team in AdWords and building YouTube's monetization systems.(20:06) Tom recalled lessons learned as a first-time founder of a social commerce startup called Renown Labs.(23:11) Tom walked over his time as the Director of Product at the SaaS social media marketing startup Wildfire (which was acquired by Google in August 2012).(27:00) Tom explained his career transition from tech operating into venture investing - after joining the enterprise investment team at a16z as a partner in 2012.(29:55) Tom revisited his thesis, discussing the rise of Enterprise Hackers back in 2013.(32:25) Tom talked about his decision to join NextWorld Capital as a partner in 2014, leading investments across enterprise applications, the Internet of Things, and AI.(34:50) Tom unpacked his investment thesis on enterprise technology that helps the blue-collar working class.(36:50) Tom shared his mental checklist used to evaluate investment opportunities in enterprise AI at NextWorld.(40:39) Tom shared the founding story of Masterful AI - where he has been a co-founder and CEO since 2019.(43:08) Tom expanded upon the 2-year incubation period from the inception to the announcement of the Masterful AI platform.(45:17) Tom unpacked major inefficiencies of ML development and explained how the Masterful platform works at a high level.(48:18) Tom shared exciting initiatives in Masterful's product roadmap.(50:09) Tom highlighted the principles that stood the test of time in computer vision over the past two decades.(51:41) Tom shared valuable hiring lessons to attract the right people who are excited about Masterful AI's mission.(55:07) Tom discussed his team's challenges in finding early design partners across various industries.(58:24) Tom shared fundraising advice to founders who are seeking the right investors for their startups.(01:01:01) Tom reflected on his career traversing across product management, venture capital, and startup founder.(01:05:20) Closing segment.Tom's Contact InfoLinkedInTwitterMediumWebsiteMasterful AI's ResourcesWebsite | Twitter | LinkedInDocs | Slack Community"Building Things with Machine Learning" PodcastMentioned ContentArticles"The Enterprise Hacker Rises" (a16z Blog, Dec 2013)"Joining NextWorld Capital" (Personal Blog, Nov 2014)"The Next Big Opportunity In Enterprise Starts In The Field" (TechCrunch, July 2015)"My visit to the Obama White House: AI, the future of jobs, and a VC’s Letter to the next administration" (NextWorld Insights, Jan 2017)"AI hype has peaked so what’s next?" (TechCrunch, Sep 2017)"AI is bringing superpowers to the specialist" (LinkedIn, Oct 2018)"Introducing Masterful AI" (Masterful Blog, Nov 2021)PeopleAndrew Ng (Founder of DeepLearning.AI, Founder and CEO of Landing AI, Co-Founder of Coursera)Chris Dixon (General Partner at a16z)BookAI Superpowers (by Kai-Fu Lee)Note

My conversation with Tom was recorded back in May 2022. Here is the note from Tom regarding updates with Masterful:

The latest at Masterful AI is that we’re launching a new generative AI product.  We saw a need to make generative models more customizable and more reliable, so companies can trust them for real business applications.  We’re starting by enabling companies to tell a more vivid and personalized story about their products at scale.

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email [email protected].

Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below:

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Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email [email protected].

Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below:

If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.