Garrett Lord: commitment

Transcript context

…The leave nothing to chance piece I imagine speaks partly to the value of trust in what you're doing. You win if they can trust that your data's awesome, and great, and consistent, and I could see why that ends up being such an important part of what you're building. And just listening to you describe this, I understand it's obviously a massive opportunity, obviously a massive advantage you guys have, and just the stress that comes with that burden also imagine is very high of just like we can't screw this up. No. Yes, Handshake should be a ... Business does billions dollars revenue as a public company, we should be able to continue to ... I mean, and it also helps our core business. The longer term opportunity that we see is it's connecting, it's building the best job mashing marketplace on the internet. It's probably one of the largest problems in the world like labor supply mashing. It's where people spend most of their time and energy, just hours of their life they spend it at work. The process of searching for a job, applying to a job is going to be completely reinvented with AI. We've been leading the charge there. An AI interviewer that's collecting skills and actually asking about your experiences, doing work simulation experiences that help employers find the best candidates. I mean, I don't know the last time you've done this, but the hiring manager process, reviewing 200 resumes, are you kidding me? I'm going to sit there and review 200 resumes? Not a chance five years from now. Students manually making cover ... Not a chance. So, there will need to be a marketplace that wins in connecting supply and demand, and talent with opportunity, and we think and get psyched about the opportunity for impact here. That's my story, I went to community college, I paid my way through school. I went to a no name school in Upper Peninsula of Michigan. I worked at Palantir as an intern, it totally changed my life, and I started Handshake because I wanted to make it easier for anyone regardless of who you knew, what your parents did, what school you went to, to find a great opportunity. And I think AI, totally step function improvement in matching. And I think that our human data business is really serving as the foundation for improving matching. A lot of things that we're doing in the human data business are being integrated to our core business. I think that's going to improve outcomes for employers, save them in the aggregate like billions of dollars over time. And I think it makes the experience way better for students. So, it's just like we have to meet the moment. We still have the stamina, and the excitement, and the passion internally in our core and in the new business to go charge after this. And that's a lot of the message we've been sharing internally is it's time to amp it up. This is a once in a lifetime opportunity to be positioned as well, and we are going to make the moment as a team. It really is. This very much feels like a once in a lifetime opportunity. Let me ask a few other questions along these lines that are something I've been thinking about, something that a lot of people think about, just while I have you, there's always this question of will we run out of data? Will model stop advancing? Are we going to hit some plateau and there's not actually going to be some AGI moment, SGI moment? So first of all, do you think we'll run out of data? There's a point at which we just can't produce more knowledge and data to feed these models? And along those lines, what do you think is the biggest bottleneck to advancing models faster and further?…

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