Alex Lebrun: Why the EU's AI Regulation is a Disaster; How Zuck Prepares for Meetings | E1027
41Alex Lebrun is the Co-Founder and CEO of Nabla, an AI assistant for doctors. Prior to Nabla, he led engineering at Facebook AI Research. Alex founded Wit.ai, an AI platform that makes it easy to build apps that understand natural human language. Wit.ai was acquired by Facebook in 2015. Prior to Wit, Alex was the Founder and CEO of VirtuOz, the world pioneer in customer service chatbots, acquired by Nuance Communications in 2013.
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Timestamps:
0:00 Intro
0:20 Who is Alex Lebrun?
3:27 How Mark Zuckerberg Prepares for Meetings
6:56 Does founding a startup get easier over time?
10:05 The AI Hype Cycle
15:48 Evaluating Emad Mostaque’s Predictions
17:14 AI Startups vs Incumbents
18:17 AI Models: Pre-Trained vs Fine-Tuned
27:03 Open-Source vs Closed-Source: Which will dominate AI?
28:27 National Data Sets
36:14 Will AI replace doctors?
59:43 Do French startups sell too soon?
1:05:25 AI in China
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In Today’s Episode with Alex Lebrun We Discuss:
1. Third Time Lucky and Lessons from Zuckerberg:
How did Alex make his way into the world of startups with the founding of his first company?
What worked with Alex’s prior companies that he has taken with him to Nabla? What did not work that he has left behind?
What were the single biggest takeaways for Alex from working with Mark Zuckerberg? How does Mark prepare for meetings? How does Mark negotiate so well?
2. Open vs Closed:
Why does Alex believe the winning AI models will always be open?
Why are open models not as transparent as people think they are?
What are the biggest downsides to both open and closed models?
Does Alex agree with Emad @ Stability that we will have “national data sets”?
3. Incumbent vs Startup:
Who wins in the AI race; startups or incumbents?
How important is access to proprietary data in winning in AI today?
How does Alex respond to many VCs who suggest so many AI startups are merely “a thin layer on top of a foundational model”? Is that a fair critique?
Which startups are best placed to challenge incumbents? Which incumbents have been most impressive in adopting AI into existing product suites?
4. Models 101: Size, Quality, Switching Costs:
Why will the best companies switch the models that they use often?
Will any models in action today be used in a year?
How important is the size of the model? How will this change with time?
In what way is new EU regulation around models going to harm European AI companies?
5. Location Matters: Who Wins:
When looking at China, US and Europe, who is best placed to win the AI war?
What are the biggest challenges Europe and China face?
Why is the US best placed to win the AI race? What does it have to overcome first?
If Alex were a politician, what would he do to ensure his country were best positioned?
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