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Apr 12, 2019 · 15m · top-founders

1357 How He's Betting on the Future of AI

Alex Bates · 8m spoken Nathan Latka · 5m spoken
0:00 / 0:00

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In this episode of The Top Entrepreneurs Podcast, host Nathan Latka interviews technologist and angel investor Alex Bates about founding and exiting his AI startup MTEL, running 'The Sandbox' AI incubator, and the investment dynamics between vertical machine learning and speculative AGI.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Nathan holds 40.3% of the talking time here. How this is scored →

Nathan as informed peer 2.6 Guest teaching 2.6 Guest disagreement 0.8 Nathan pushing back 3.0
05100:0010:002:39–4:50 · Nathan as informed peer 3/10 Overview of The Sandbox AI Incubator and Early Investments Nathan introduces Alex's background and presses to narrow down on specific portfolio companies rather than broad ecosystem activities. Alex calmly clarifies his focus between startup investments and his incubator Sandbox.4:51–8:54 · Nathan as informed peer 4/10 Pivot to Practical Machine Learning Case Studies Nathan explicitly shifts the discussion away from incubator logistics to concrete machine learning case studies, steering Alex to discuss MTEL and its acquisition terms. Alex explains the historical context of the AI winter and vertical machine learning.8:55–11:22 · Nathan as informed peer 3/10 Ecosystem Building, Angel Syndicates, and Operator Ambitions Nathan challenges Alex's strategy of 'casting a net' through angel syndicates and incubators rather than focusing on building a single billion-dollar company. Alex defends his exploration phase and community building goals.11:22–13:53 · Nathan as informed peer 2/10 The State of AI Capital, AGI Realities, and Human Augmentation Alex educates Nathan on the difference between narrow vertical AI applications and speculative AGI, defining AGI when Nathan asks. Nathan asks probing questions about AI hype and the philosophical holy grail of the space.13:54–15:31 · Nathan as informed peer 1/10 The Famous Five and Episode Conclusion Nathan runs through his standard rapid-fire 'Famous Five' concluding questions, which Alex answers directly without friction.2:39–4:50 · Guest teaching 2/10 Overview of The Sandbox AI Incubator and Early Investments Nathan introduces Alex's background and presses to narrow down on specific portfolio companies rather than broad ecosystem activities. Alex calmly clarifies his focus between startup investments and his incubator Sandbox.4:51–8:54 · Guest teaching 3/10 Pivot to Practical Machine Learning Case Studies Nathan explicitly shifts the discussion away from incubator logistics to concrete machine learning case studies, steering Alex to discuss MTEL and its acquisition terms. Alex explains the historical context of the AI winter and vertical machine learning.8:55–11:22 · Guest teaching 2/10 Ecosystem Building, Angel Syndicates, and Operator Ambitions Nathan challenges Alex's strategy of 'casting a net' through angel syndicates and incubators rather than focusing on building a single billion-dollar company. Alex defends his exploration phase and community building goals.11:22–13:53 · Guest teaching 5/10 The State of AI Capital, AGI Realities, and Human Augmentation Alex educates Nathan on the difference between narrow vertical AI applications and speculative AGI, defining AGI when Nathan asks. Nathan asks probing questions about AI hype and the philosophical holy grail of the space.13:54–15:31 · Guest teaching 1/10 The Famous Five and Episode Conclusion Nathan runs through his standard rapid-fire 'Famous Five' concluding questions, which Alex answers directly without friction.2:39–4:50 · Guest disagreement 1/10 Overview of The Sandbox AI Incubator and Early Investments Nathan introduces Alex's background and presses to narrow down on specific portfolio companies rather than broad ecosystem activities. Alex calmly clarifies his focus between startup investments and his incubator Sandbox.4:51–8:54 · Guest disagreement 1/10 Pivot to Practical Machine Learning Case Studies Nathan explicitly shifts the discussion away from incubator logistics to concrete machine learning case studies, steering Alex to discuss MTEL and its acquisition terms. Alex explains the historical context of the AI winter and vertical machine learning.8:55–11:22 · Guest disagreement 1/10 Ecosystem Building, Angel Syndicates, and Operator Ambitions Nathan challenges Alex's strategy of 'casting a net' through angel syndicates and incubators rather than focusing on building a single billion-dollar company. Alex defends his exploration phase and community building goals.11:22–13:53 · Guest disagreement 1/10 The State of AI Capital, AGI Realities, and Human Augmentation Alex educates Nathan on the difference between narrow vertical AI applications and speculative AGI, defining AGI when Nathan asks. Nathan asks probing questions about AI hype and the philosophical holy grail of the space.13:54–15:31 · Guest disagreement 0/10 The Famous Five and Episode Conclusion Nathan runs through his standard rapid-fire 'Famous Five' concluding questions, which Alex answers directly without friction.2:39–4:50 · Nathan pushing back 2/10 Overview of The Sandbox AI Incubator and Early Investments Nathan introduces Alex's background and presses to narrow down on specific portfolio companies rather than broad ecosystem activities. Alex calmly clarifies his focus between startup investments and his incubator Sandbox.4:51–8:54 · Nathan pushing back 4/10 Pivot to Practical Machine Learning Case Studies Nathan explicitly shifts the discussion away from incubator logistics to concrete machine learning case studies, steering Alex to discuss MTEL and its acquisition terms. Alex explains the historical context of the AI winter and vertical machine learning.8:55–11:22 · Nathan pushing back 5/10 Ecosystem Building, Angel Syndicates, and Operator Ambitions Nathan challenges Alex's strategy of 'casting a net' through angel syndicates and incubators rather than focusing on building a single billion-dollar company. Alex defends his exploration phase and community building goals.11:22–13:53 · Nathan pushing back 3/10 The State of AI Capital, AGI Realities, and Human Augmentation Alex educates Nathan on the difference between narrow vertical AI applications and speculative AGI, defining AGI when Nathan asks. Nathan asks probing questions about AI hype and the philosophical holy grail of the space.13:54–15:31 · Nathan pushing back 1/10 The Famous Five and Episode Conclusion Nathan runs through his standard rapid-fire 'Famous Five' concluding questions, which Alex answers directly without friction.

speaking balance: gold is Nathan, purple is the guest (3 minute bins)

0:00 · Nathan 75.4% · guest 24.6%0:00 · Nathan 75.4% · guest 24.6%3:00 · Nathan 35.9% · guest 64.1%3:00 · Nathan 35.9% · guest 64.1%6:00 · Nathan 27.4% · guest 72.6%6:00 · Nathan 27.4% · guest 72.6%9:00 · Nathan 30.7% · guest 69.3%9:00 · Nathan 30.7% · guest 69.3%12:00 · Nathan 26.8% · guest 73.2%12:00 · Nathan 26.8% · guest 73.2%15:00 · Nathan 61.2% · guest 38.8%15:00 · Nathan 61.2% · guest 38.8%
Sharpest disagreement ▶ 11:40 Alex resists calling out overhyped AI startups

When Nathan directly asks which heavily funded AI company stands to lose the most money because their tech is fake, Alex resists naming losers, stating the jury is still out before reframing to discuss speculative AGI.

 Hardest push from Nathan ▶ 9:46 Nathan challenges broad focus over a single venture

Nathan directly challenges Alex's fragmented attention across incubators, funds, and co-founding gigs, pressing him on why he doesn't shoot a harpoon to build a billion-dollar company instead.

 Biggest teaching moment ▶ 12:40 Alex explains AGI concept to Nathan

After Nathan asks what AGI is and how it differs from regular AI, Alex clearly breaks down the distinction between domain-specific vertical AI and cross-industry artificial general intelligence.

 Nathan holds their own ▶ 4:51 Nathan redirects the interview agenda

Nathan cuts through Alex's description of incubator logistics, bluntly stating his audience wants deep machine learning insights and forcing the conversation onto technical case studies.
the scores for every segment, with the reasoning behind each
ChapterTopicNathan as informed peerGuest teachingGuest disagreementNathan pushing backWhy
Overview of The Sandbox AI Incubator and Early Investments 3212 Nathan introduces Alex's background and presses to narrow down on specific portfolio companies rather than broad ecosystem activities. Alex calmly clarifies his focus between startup investments and his incubator Sandbox.
Pivot to Practical Machine Learning Case Studies 4314 Nathan explicitly shifts the discussion away from incubator logistics to concrete machine learning case studies, steering Alex to discuss MTEL and its acquisition terms. Alex explains the historical context of the AI winter and vertical machine learning.
Ecosystem Building, Angel Syndicates, and Operator Ambitions 3215 Nathan challenges Alex's strategy of 'casting a net' through angel syndicates and incubators rather than focusing on building a single billion-dollar company. Alex defends his exploration phase and community building goals.
The State of AI Capital, AGI Realities, and Human Augmentation 2513 Alex educates Nathan on the difference between narrow vertical AI applications and speculative AGI, defining AGI when Nathan asks. Nathan asks probing questions about AI hype and the philosophical holy grail of the space.
The Famous Five and Episode Conclusion 1101 Nathan runs through his standard rapid-fire 'Famous Five' concluding questions, which Alex answers directly without friction.

Statements from this episode (5)

Disclosure
Bates: The Sandbox Takes 5% Equity in Incubated AI Startups
“So we take five, five percent equity and we have different investment models and of course offer, in addition to the free free office space, the whole we have some law firms we partner with to get discounted or free work on patent development. And accounting a…”
Alex Bates Apr 12, 2019 ▶ 4:30
Opinion
Bates: The Biggest Opportunity in AI Is Going Deep into Vertical Domains
“There's mostly vertical plays, and that's where we see the biggest opportunity is going deep into a domain right now, be it biotech or music or other domains like that”
Alex Bates Apr 12, 2019 ▶ 5:23
Disclosure
Bates: MTEL raised $2M split between equity and a royalty structure
“Yeah, we took in two million one of which was equity and one was sort of a royalty arrangement.”
Alex Bates Apr 12, 2019 ▶ 7:36
Insight
Bates: Angel investors lack domain knowledge needed to fund seed AI startups
“One of the challenges we face, and I've seen other companies face, is for angel investors, there's a lack of knowledge to get the confidence to invest in these seed stage startups, and then startups have trouble connecting”
Alex Bates Apr 12, 2019 ▶ 9:16
Opinion
Bates: Alphabet faces internal controversy over speculative DeepMind AGI play
“For AGI, where you've got like Vicarious, you have DeepMind, those are really speculative plays. There's even a lot of controversy within Google and Alphabet now about DeepMind, and they're in Alphabet versus Google, and then there's Google Brain, and there's …”
Alex Bates Apr 12, 2019 ▶ 12:18
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