00:23:02 · Danny Fortson, George Sivulka
[00:23:02] S2: Right. Back to the coral reef. [00:23:03] S4: And so back to the coral reef. And I was like, well, at least I got to be on a boat in Micronesia for a little bit. Yeah, I made the right call. So The natural question then, especially for an academic is like, so what? Okay, I committed so thoroughly to this direction. Really want to do it. It's here. What's the next step? And I thought to myself for a long time about maybe an equivalent technological transformation, and I thought it would be... Was actually the computer. And when the computer was finally invented as technology, it was not valuable until people built products on top of it. Yeah. You know, I I would actually say the calculator, the TI 84, all the the terminal itself, right, the the earliest operating systems were not really that valuable or that human first until Microsoft invented Excel. [00:23:55] S2: Yeah.
00:23:55 · Danny Fortson, George Sivulka
[00:23:55] S2: Yeah. [00:23:56] S4: And once we had Excel, then billions of people around the world were able to use a computer to do complex multi step work. And so I was looking at this technology and I hadn't invented it, And I was a little angry and I was like, well, what's the most important software or the most important product that I could build on top of that? And I had no idea, but I was heck... Like, I was hell bent on finding it. I just wanted to go and build the most important product. And I thought that it wasn't gonna be a chatbot. I didn't think it was gonna be the LLM itself. I thought that was all technology, but that the product layer would be complex and human first, explainable, and let you do complex work. And we've iterated many times. We actually were some of the first people to build the most used AI architectures in the world. We have, like, invented and reinvented a million search engines and chatbots, and from that perspective, we pivoted a [00:24:47] S2: lot. Right. [00:24:48] S4: But we've always been trying to get to the point we're at today where the market... You know, there's a lot of noise in it, but people are actually driving immense large language model usage, and they're actually getting value from the technology because we've built, I think, the Excel for words. As Excel is to numbers, heavy as matrix is to words. [00:25:06] S2: Today's episode of the Times Tech Podcast is sponsored by ServiceNow.
00:25:06 · Danny Fortson, S3, S5, S6, S7, S0, S8, S9, S10, S1
[00:25:06] S2: Today's episode of the Times Tech Podcast is sponsored by ServiceNow. [00:25:10] S3: ServiceNow describes itself as an AI control tower for business reinvention, connecting people, systems, data, and AI so work flows more smoothly across an organization. [00:25:21] S2: The platform integrates with different clouds, models, and data sources, bringing them together in one place to help your team. [00:25:28] S3: To learn more about how ServiceNow puts AI to work for people, visit servicenow.com. [00:25:36] S5: People are disappearing again just like before. [00:25:41] S6: Nocturne. Streaming on Apple TV on the October 30. Lief Schreiber. [00:25:47] S7: Walter has a way of getting people. When he does, they don't come back. Steven Graham. The world is full of dark places. Sassy Beats. [00:25:55] S0: How's he getting messages at? [00:25:56] S8: He's locked under six feet of concrete. [00:25:58] S9: She's still alive. [00:25:59] S10: I'm a fighter. [00:26:00] S6: Nocturne. Streaming on Apple TV on the October 30. Subscription required. [00:26:06] S1: Still waiting in line? Again? That's time you'll never get back. Save time and money with stamps.com. Over 4,000,000 businesses have skipped the line with stamps.com. Join them to save up to 90% off carrier rates from your computer or phone right now. Print postage for certified mail, registered mail, and packages in seconds, then schedule a pickup right from your home or office. For a limited time, go to .com and use code podcast for a free welcome gift. Taxes and fees apply.
00:26:06 · S1, Danny Fortson
[00:26:06] S1: Still waiting in line? Again? That's time you'll never get back. Save time and money with stamps.com. Over 4,000,000 businesses have skipped the line with stamps.com. Join them to save up to 90% off carrier rates from your computer or phone right now. Print postage for certified mail, registered mail, and packages in seconds, then schedule a pickup right from your home or office. For a limited time, go to .com and use code podcast for a free welcome gift. Taxes and fees apply. [00:26:38] S2: You mentioned that the bank example with the investment example. But when you talk about this thing that can kind of just, you know, that's really agile and smart and can just, you know, that... It's a classic thing where this... It's kind of a magic technology that just works. What else is it being used for? Who... Who's using this, and how are they using it?
00:26:38 · Danny Fortson, George Sivulka
[00:26:38] S2: You mentioned that the bank example with the investment example. But when you talk about this thing that can kind of just, you know, that's really agile and smart and can just, you know, that... It's a classic thing where this... It's kind of a magic technology that just works. What else is it being used for? Who... Who's using this, and how are they using it? [00:27:00] S4: Yeah. One one of my favorite examples are not even the day to day, but when really large events in the world happen and people need to respond to it. A really good example would be when Silicon Valley Bank happened. A lot of different firms, whether you were a company or an investor in New York or all across the world, really quickly needed to know their exposure to the banking crisis. And this is particularly relevant in Silicon Valley because everyone's like, what portion of my portfolio might not have money, might not be able to make payroll? Or in New York, what portion of my portfolio is actually going to be severely impacted and they have to pay off some debt, etcetera? And it would be impossible to look over all of the documents in an organization and to pull out, okay, across all of our investments, x company has exposure to a regional bank. It would take millions of dollars, you know, probably hundreds of thousands of legal hours for for most of the large corporations in America. And with Hebia, they were able to answer that question instantaneously. And not only for Silicon Valley Bank, but for any regional bank.
00:27:00 · George Sivulka, Danny Fortson
[00:27:00] S4: Yeah. One one of my favorite examples are not even the day to day, but when really large events in the world happen and people need to respond to it. A really good example would be when Silicon Valley Bank happened. A lot of different firms, whether you were a company or an investor in New York or all across the world, really quickly needed to know their exposure to the banking crisis. And this is particularly relevant in Silicon Valley because everyone's like, what portion of my portfolio might not have money, might not be able to make payroll? Or in New York, what portion of my portfolio is actually going to be severely impacted and they have to pay off some debt, etcetera? And it would be impossible to look over all of the documents in an organization and to pull out, okay, across all of our investments, x company has exposure to a regional bank. It would take millions of dollars, you know, probably hundreds of thousands of legal hours for for most of the large corporations in America. And with Hebia, they were able to answer that question instantaneously. And not only for Silicon Valley Bank, but for any regional bank. [00:28:08] S2: By asking Hebiya the question that you wanted the answer to? [00:28:12] S4: Yes. And it and it decomposed it into, okay. Let's go and run a large language model agent that reads through all of our instruments, all of those documents with its credit agreements or portfolio information, pulls out or flags whether or not there's exposure. And I can actually get a quantifiable number [00:28:30] S2: Right.