20VC: How to Build Your Own Data Center & Why Every Startup Should Do It | How ElevenLabs Leapfrogged Us: What I Learned | The AI Talent War: How Your Hiring Process Needs to Change with Cliff Weitzman, Speechify

Cliff Weitzman (0:00)

100% is not. It's the biggest strategic mistake I made in the history of Speechify. The best way to lose is not to be in the race. Be in the race. You don't want to be a fat manager who is like a general sitting in the back saying, take that hill. You want to be the warrior who runs up with their sword and engages the enemy first.

Harry Stebbings (0:15)

This is 20VC with me, Harry Stebbings. Now, I am fed up of the simple question-answer back and forth podcast. Today is a real fricking discussion. Cliff Weitzman, founder and CEO of Speechify, one of the fastest growing text-to-speech startups in the world, on the show, where we have a real debate about whether it's right to scale into enterprise from a phenomenal consumer business, what it takes to build an amazing go-to-market motion when you've already built this amazing consumer business. And then he also tells us some wild fricking stories about spending tens of millions of dollars on Nvidia GPUs and why so many more companies should be doing that over relying on other providers. This and so much more in the episode today. But before we dive in to the show today, today I want to tell you about how the first AI law firm, Crosby, helped us close a big sponsor. As you know, some of the biggest companies in the world advertise on 20VC, my British dulcet tones clearly convert well. I was working to close this big sponsor and they wanted to get through legal review quite quickly to close the deal. Crosby turned red lines around in three hours and caught major issues that would have caused us serious problems in the future. Crosby combines AI, some of the best engineers in the world, from companies like Ramp and Stripe, and some of the best attorneys in the world from top 10 law firms. Customers get the best of both worlds. An elite human attorney reviews every contract, but they move incredibly quickly, returning red lines in under four hours. They help the fastest growing companies like Cognition, Ramp and Clay close deals in hours, not weeks. Learn more at crosby.ai/20vc.

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That's alpha hyphen sense.com. You have now arrived at your destination. Cliff, it is so good to have you back in the studio, dude. I was looking forward to this one because when I was writing it up, it's a very different thread of conversation to how I'd normally go. And so thank you so much for joining me again today, dude.

Cliff Weitzman (3:46)

My pleasure. Glad to be here as always.

Harry Stebbings (3:48)

Now, I wanted to start with your spending tens of millions of dollars on NVIDIA GPUs and you're paying an additional $100,000 per GPU to receive them four months early. Why?

What do you know that the market doesn't know?

Cliff Weitzman (4:01)

So in 2022, we bought a huge rack of GPUs from NVIDIA. And the reason we bought them is for training, right? We have a bunch of models. The newest Speechify Simba 3.2 model is ranked number one in the world for quality. Above all the frontier labs, TenX more affordable and stuff like ElevenLabs. And we used to rent GPUs. And we found that engineers at Speechify would be parsimonious with how they used the GPUs because they were like, oh my god, I'm costing the company tens of thousands of dollars. Like, I don't want to do that. And the analogy my brother and I came up with is imagine you're Michael Jordan and you want to be in the NBA. It's the only thing you care about. And you need to pay $20 an hour just to train in a basketball center. Well, that sucks. You want one that you can go to whenever you want to. In fact, you want a hoop in your house. And so our initial idea was we want a hoop in our house. And so we bought a bunch of our own GPUs. And that deal ended up being really good for us. And we ended up training really good models. So with time, we invested more and more and more and more. So that's the first part. The second part is actually how the economics work out. So if you look at it, the Transformer was invented inside of Google in 2017