00:07:22 · Jae Lee
[00:07:22] S9: Former paper, which is making a lot of impact now. But when it was published in 2017, at least for text and image based, you know, foundation models, probably capital was going to be a moat, whoever raises most amount of money. What we realized was, there's still a lot of unexplored research areas for multimodal video understanding. There, rather than capital, is probably going to be really passionate, smart, but also slightly dumb people that's, like, dumb enough to start it will have really good chance of succeeding. And also, we've realized that with the explosion of that video and and other complex multimedia data is going to be the infrastructural data for the Internet. And we realized that probably developers and enterprises need something better than object detection or or transcription to make sense of all all this video data that the humanity is creating. So it was like a no brainer to start building for video understanding. The model that Twelve Labs is building, it's basically trying to map human language into whatever that's happening in video content. So if you can map precise human language to whatever that's happening within video content, gives you this emergence capabilities like being able to search for things really well or being able to classify things or summarize. You know, we didn't all join the Korean Cyber Command at the same time. So SJ was already like six months ahead of me, then Aiden was six months behind. So like, okay, we decided we're gonna start this company. But then SJ is leaving next year, and then I'm leaving the year after, and then Aiden is six months after. So how do we do it? So it was genuinely very scary. So we had our ideas. I remember SJ was discharged on Thursday, and he came back to the military base Saturday of that week with our laptops and he took us out. In front of our military base, there was a bagel shop called Las Bagel and that was like our office where SJ would bring all of our laptops and we would do our research and do some little bit of prototyping. We did that for six months. And then I got discharged and I did the whole laptop carrying and and taking out Aden. So we did that for like a good year so that everyone is out. And then we had a bunch of friends that were working in AI and crypto and blockchain and and and Web three was just booming.
00:09:35 · Jae Lee
And we had a mutual friend, like the founders had a mutual friend that had, like, a really nice office in Seoul, he was like, oh, you guys can come in and and use our office space. So that's what we did. And then after, three weeks, that company went bankrupt. And then really scary, like, people started coming in and and we had, our desktops and our GPUs all set up there, we got really scared. So we brought everything back out and we found, like, really tiny, tiny office, probably like the size of a dressing room. That's where, like, all five of us kind of spent, the next six months, before, we raised our proper seat ground. Looking back, if we were to do it again, I don't know if we'll be able to do it, but some people say ignorance is bliss. And I think we were just like really naive and just really excited about building this company. I guess not knowing what was ahead allowed us to kind of do what we did.
00:10:29 · S10, S0
Ad[00:10:29] S10: Hi all, I'm Jae from EO. I have a quick question for you. Which is the better prompt? If you're looking to use AI to apply directly to your workflow, I would say this one does the job. This prompt was made using the five essential resources for using ChatGPT at work, a free bundle of AI resources provided by HubSpot, our amazing Parkman. The bundle has the following resources: Tips on implementing ChatGPT at Work in various professional settings The Ultimate Guide for Adopting AI at Work checklist to make sure your AI generated content feels authentic, and more! For this prompt, I used Templates for Setting Clear Guidelines, which gives simple guides to dramatically improve your prompting and results using ChatGPT. The best part is that it has over 100 prompts that you can use right away, so you don't have to start from scratch. So for anyone who's tried really hard to use the power of AI at work, give this toolkit a try. Download for free using the link. Ad[00:11:23] S0: This episode is brought to you by Google Chrome. You think you know a browser, but Gemini in Chrome? That's new. They can help you with practically anything on the web, like restoring a vintage motorcycle from a 50 page restoration block or finally break down that long article you've had open for weeks. Gemini in Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses, setup required, compatibility, and availability varies 18 plus.
00:11:23 · S0, S2, S3, S4, S5
Ad[00:11:23] S0: This episode is brought to you by Google Chrome. You think you know a browser, but Gemini in Chrome? That's new. They can help you with practically anything on the web, like restoring a vintage motorcycle from a 50 page restoration block or finally break down that long article you've had open for weeks. Gemini in Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses, setup required, compatibility, and availability varies 18 plus. Ad[00:11:48] S2: This episode is brought to you by Indeed. You're ready to level up your business, but the pressure to find the right person to make that happen is intense. Indeed sponsored jobs can help carry the load. Ad[00:12:00] S3: It boosts your job post to Ad[00:12:01] S2: help it reach quality talent fast. Cut through the chaos with Indeed sponsored jobs. Get a 75 sponsored job credit at indeed.com/podcast. Terms and conditions apply. Hiring now? Then this is a job for Indeed sponsored jobs. Ad[00:12:18] S4: Your sausage McMuffin with egg didn't change. Your receipt did. The sausage McMuffin with egg value meal includes a hash brown and a small coffee for just $5. Only at McDonald's for a limited time. Ad[00:12:30] S5: Price and participation may vary. Promotion pricing may be lower than meal pricing.
00:12:30 · S5, S6, S8, S10
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00:13:12 · Jae Lee
[00:13:12] S9: When we first started the company and we hired our first employees, they had a hard time explaining what Twelve Labs does to their parents. Really new thing, what is foundation model? What is video understanding? It's a new concept that's hard to understand for, I guess, people that are not in the space. Nowadays, talk about the foundation layer, the tooling layer and the application layer. It all... Everyone's very familiar. When we started Twelve Labs, I think technologically, it made total sense. We knew it was going to happen. But what was uncertain about it was, will the market accept? But knowing that we are at the verge of breakthrough in building an AI that can at least, you know, get to certain level of human understanding of videos. So we were betting on market's acceptance of foundation models. The founders are pretty pretty much broke, right, because we spent two years at at military, and I think we had $2,000, to start with. So barely barely enough to do anything. But figuring out what was going to be impactful that we can do given our current resources that'll put us in the map or at least, you know, let the world know that what we're doing is relevant. So our tactic here was, okay. We're gonna talk to a bunch of customers. And there were early believers in Twelve Labs who took our APIs and built awesome things with us, but we needed more exposure, basically. So as a team, we've decided, to participate in ICCV's, it's International Conference in Computer Vision. They're putting this, like, awesome competition for video understanding. So I... We talked to Aidan. We have nothing to lose and only to gain. The team was extremely supportive of of Aidan spearheading that effort with the team. All I can do to support is... You know, there were some ideas and and directional kind of feedback that I gave to Aiden, but we needed compute and we needed determination to put some serious cash behind. And back then for Twelve Labs, like, $200,000 in in compute was was a lot of money for us. Right? So and just thinking that, okay, we're gonna blow through $200,000 in ten days in compute was really scary. But the team was able to use that capital, that that precious capital, and build something incredible helped us win the competition.