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Clem Delangue: The Ultimate Guide to Investing in AI; Elon's Threat to Sue OpenAI | E1013

Clem Delangue is the Co-Founder and CEO @ Hugging Face, the AI community building the future. To date, Clem has raised over $160M from the likes of Sequoia, Coatue, Addition and Lux Capital to name a few. Prior to Hugging Face, Clem was in product and marketing at two different startups both of which were acquired. ------------------------------------------------ Timestamps: (0:00) Intro (1:14) Founding Story of HuggingFace (4:51) AI: The real deal or all hype? (10:57) Do AI Founders need to be in Silicon Valley? (12:49) One Model to Rule Them All (17:16) How to Sell AI to Enterprise (19:34) Elon to Sue OpenAI? (22:44) HuggingFace’s Business Model (27:01) AI Startups vs AI Incumbents (30:38) Why AI Startups are Expensive (33:20) AI Regulation (37:46) Fundraising at HuggingFace (52:27) Quick-Fire Round ------------------------------------------------- In Today’s Episode with Clem Delangue: 1. From Tamagotchi to Leading the World of AI: How did a Tamagotchi startup turn into one of the hottest AI startups in the world? What does Clem know now that he wishes he had known when he started? What are Clem’s biggest pieces of advice to founders on pivoting? 2. AI: Trend or Transformation: To what extent does Clem believe the current hype in AI is justified? What is overblown? What have been some true and groundbreaking developments? How far away does Clem believe AGI is? What is a massive misconception the public has that Clem wishes he could change? 3. Open vs Closed: Which Model Wins: Why does Clem believe the future of AI will be won by open-source? What is his reasoning to suggest closed is fundamentally a weaker model? Does Clem acknowledge that in the short term, enterprises will buy from a closed model with greater ease? How does he plan to tackle this? 4. Regulation: What Happens Now: What regulatory changes need to be made in the world of AI most urgently? Is Elon Musk right to suggest the immediate pausing of developments in AI? What does Clem believe to be the most likely scenario to AI regulation in the next 12 months? 5. Fundraising: Lessons and Reflection on Raising $160M: Do AI startups fundamentally cost more money than normal startups to build? Why does Clem not meet investors in between rounds? What does Clem believe is the most helpful thing an investor can do? What are Clem’s spiciest takes on venture as a financing model? ------------------------------------------------------------ Subscribe on Spotify: https://open.spotify.com/show/3j2KMcZTtgTNBKwtZBMHvl?si=85bc9196860e4466 Subscribe on Apple Podcasts: https://podcasts.apple.com/us/podcast/the-twenty-minute-vc-20vc-venture-capital-startup/id958230465 Follow Harry Stebbings on Twitter: https://twitter.com/HarryStebbings Follow Clem Delangue on Twitter: https://twitter.com/ClemDelangue Follow 20VC on Instagram: https://www.instagram.com/20vc_reels Follow 20VC on TikTok: https://www.tiktok.com/@20vc_tok Visit our Website: https://www.20vc.com Subscribe to our Newsletter: https://www.thetwentyminutevc.com/contact ----------------------------------------------- #ClemDelangue #HuggingFace #HarryStebbings #20vc #artificialintelligence #chatgpt #openai #midjourney

Clément DelangueguestHarry Stebbingshost
May 11, 202358mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Clem Delangue Explains Open AI Ecosystems, Startup Moats, And Fundraising Reality

  1. Clem Delangue, CEO of Hugging Face, discusses the evolution of his company from a consumer ‘Tamagotchi AI’ app to a leading open-source AI platform, and why openness has driven most AI progress. He contrasts two visions of the AI future: one ultra-centralized model (e.g., OpenAI) versus a world of many specialized, often open-source models owned and tuned by individual companies. Delangue argues that long-term advantage comes from building in-house AI capabilities rather than relying solely on black-box APIs, even if the latter are easier at first. He also shares candid views on startup fundraising, the role of VCs, regulation, and why founders must focus on enjoying the act of building rather than expecting things to get easier at later stages.

IDEAS WORTH REMEMBERING

5 ideas

Long-term differentiation in AI requires owning your models, not just calling APIs.

Using a single third-party model via API is like using Wix for your website—great for speed, but weak for deep optimization, cost control, and defensible product differentiation over time.

All serious companies will eventually run their own specialized AI models.

Delangue predicts that, analogous to custom codebases, every meaningful company will maintain models tuned to its data, constraints, and use cases rather than relying solely on a generic ‘one-size-fits-all’ model.

Open science and open source are the real engine of recent AI progress.

Breakthroughs like transformers, BERT, and diffusion models came from openly shared research and code; without this openness, Delangue estimates we’d be decades behind current capabilities.

Founders should optimize for where they are happiest, not just for the Valley.

He rejects the dogma that AI founders must move to Silicon Valley, arguing that great companies can be built from anywhere as long as founders are energized and can visit hubs when needed.

AI-first startups face their biggest constraint in talent, not only in compute.

There are very few people globally who’ve actually built and trained state-of-the-art architectures; competition for these hybrid scientist–engineer profiles is intense and expensive.

WORDS WORTH SAVING

5 quotes

Each stage has a lot of challenges. It doesn’t get easier, it just gets different.

— Clem Delangue

Most of the progress we’re seeing in AI is based on open science and open source.

— Clem Delangue

Using an AI API is like using Wix for your website—it feels great at the beginning, but you can’t really optimize or differentiate with it.

— Clem Delangue

All companies will have their own AI models—basically their own GPT-4.

— Clem Delangue

My assumption is that usage is delayed revenue, especially in a domain like AI.

— Clem Delangue

Origin and evolution of Hugging Face from AI companion app to AI platformOpen-source vs proprietary AI models and the “one model vs many models” debateCentralized AI hubs (Silicon Valley) vs globally distributed AI talentBusiness model, monetization, and network effects at Hugging FaceLegal and regulatory issues in AI (training data, content access, regulation timing)Startup funding dynamics, investor selection, and the true role of VCsChallenges of building AI-first companies: hiring, compute costs, and moats

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