Transcript: Jacob Colker - Co-Managing Director AI2 Incubator

Host: Hey Jacob, thanks for coming on the show.

Guest: Thanks for the opportunity to share a story.

Host: Uh, so I live in Seattle in South Lake Union. So, you know, Allen Institute is, uh, uh, is if if you are into startups and investing and venture, like you know that Allen Institute has been there for a while.

Uh, before, you know, all the buzz of generative AI and chat GPT was, uh, you know, it's now capturing people's attention, but, you know, uh, the, uh, AI trend and incubating startups, uh, in AI has been going on at Allen Institute for a while.

So, it's pretty exciting to talk to you, uh, because of the timing we are in.

Um, but before getting into all that stuff, I just want to start with, uh, you know, what is your, uh, early background, uh, and education, uh, and how did you first get into tech?

Guest: I've been a builder in most of my entire life. I'm very fortunate to have been able to partner with, uh, a number of incredible technologists and, uh, folks in the industry.

I I'm typically the, you know, sales, marketing, hustling, early stage, traction type person on the team and and I've I've just again been very fortunate to partner with just brilliant technical minds. Uh, I did not go to school for engineering.

I went to school for media and communication and, uh, and my own resume and my own journey has been, you know, a little bit, uh, non-traditional in that, uh, you know, I played music for a long time and, uh, you know, went through a period of social entrepreneurship.

But I think the thread that pulls it all together is that I've always just been a creator, been a builder and, uh, that type of that type of energy, that type of personality works really well in a startup environment.

Uh, so that that was my path was through just building and creating and eventually navigating that, uh, that energy and that focus to doing that in in the spirit of entrepreneurship, uh, which really turned out to be a tremendous, um, uh, opportunity and and a really good fit for my brain and my personality type.

Host: So, uh, I mean, you said you studied for, uh, media and communications and then, uh, I was going through your resume and, uh, looks like you partly also worked for Democratic Party. That that felt like an interesting, uh, pivot.

Guest: Well, I think, uh, you know, a startup, especially at the pre-seed stage, which is where we spend so much of our time, is still very much just an idea with some very passionate people. And, uh, that is also very true in in in politics.

You know, a lot of the times when a candidate is, uh, just getting started or a social movement or or something, it's really just a set of ideals, uh, and and some early people willing to work very long hours to, uh, to to activate a community or, you know, try and solve some social injustice or try and get somebody elected.

Uh, so I I think there are a lot of parallels between the world of politics and the world of entrepreneurship.

Um, you know, again, you're you're selling the ideals of an individual or of a organization or of a movement and not of necessarily a product, but the activities and the energy and the execution, um, is is is in the same ballpark at least.

Not obviously not exactly the same thing, but it's it's similar movements and and similar activities involved.

Host: I mean, I think, uh, when you're young, uh, you're full of energy and you want to change things, you know, fight the system or, you know, do something like that. Uh, but you then quickly built it into tech. So, what was it like with that experience? Was the idealism gone or, uh, did something on that front change or, uh, was it like a natural progression?

Guest: Yeah, I mean, I I I would argue that, um, Google through Google Maps, access to information, you know, the ability to create communication channels like Gmail.

Google has arguably done more good for the world than a lot of government programs, right?

And so I think to me, uh, as I learned more about myself as a human being and as I matured and and and saw the world for what it really was, you know, I I think those same ideals of wanting to make the world better, wanting to create opportunity for people.

Uh, in a lot of ways, the efficiency of a, you know, an enterprise, um, a for-profit enterprise who moves lightning fast to make things happen, can arguably have a lot more impact on the world than a lot of government programs.

And so, you know, my goal was to have an impact and you're right, when you're young and full of ideals and wanting to change the world and all those things, um, politics can be an inspiring place to start.

Uh, but but I I think entrepreneurship is just generally more efficient at being able to create change in a way that's very positive for society. Uh, and that's what ultimately pulled me into tech. Uh, I I don't think I changed that much as a human.

I think I just found a better set of tools to achieve the impact and and those tools are, um, you know, a lot more rampant in the world of entrepreneurship than they are in in the world of government. Unfortunately.

Host: So you then started sparked.com?

Guest: Yeah. Yeah, so Sparked was a product that, um, came out of, uh, social entrepreneurship and and politics.

The iPhone had just come out and, uh, we were trying to figure out how to do a better job of activating and organizing thousands of volunteers on campaigns and and for social initiatives.

And suddenly overnight you've got a device that has, you know, wireless data, cellular data in your pocket that has GPS, that has a camera that has all these incredible features and functionality.

And so we built Sparked initially as a platform to, uh, allow nonprofits or political parties or whatnot to engage tens of thousands of their supporters in actions that were more than just sign a petition, but actions where they would take a photo or use a GPS or or do these things.

Um, door knocking in politics used to be done using clipboards and pieces of paper and obviously it's a lot more efficient when you can do that and and track on a GPS, you know, hundreds of volunteers in a in a field effort, right?

So that was the genesis for for that idea and then, um, we evolved that quite a bit to, you know, a distributed, uh, crowdsourcing platform on mobile phones. And you know, that sounds dated. I suppose I'm starting to, uh, get older in life.

So, you know, I'm I'm rolling my eyes at how old that sounds just repeating that out loud. But, you know, Wikipedia was still pretty early.

Um, there was a a lot of this idea of crowdsourcing was becoming a thing and, uh, and at the time it was a very novel idea to be able to do that in a distributed way across hundreds of thousands of cell phones.

Um, that company, uh, evolved to, uh, be able to engage these, uh, people who were passionate about a particular brand.

And then eventually, uh, the company was sold and, um, then I was an entrepreneur a few other times, uh, before I really found my calling on the other side of the table in terms of helping entrepreneurs to frankly not make a lot of the mistakes that I made as a first time, uh, and a second time entrepreneur.

Um, I I really found the world of venture capital and incubation to be the absolute perfect fit for who I was as a human being.

And, uh, and I just feel really really lucky that I've had the opportunity to work in this industry for a number of years at this point. Uh, it's it's an incredible opportunity.

Host: You then, uh, went on to work at Lighter Capital, uh, which is a revenue-based financing product, uh, which which which sounds a lot similar to what, uh, I think Pipe was doing, right?

Guest: Not sure.

Um, Lighter was a a a wonderful is a wonderful organization in that, um, they fill a gap in the marketplace between, um, the the handful of organizations or startups in in any one particular market that are capable of raising venture capital, and the long tail of folks that are building great products in that space.

So, you know, there are hundreds of folks in the cloud hosting space outside of Dropbox and box.net and and so on and so forth.

But unless you're one of the top, let's say 10, startups or companies in a particular field, you're unlikely to be able to raise venture capital.

Now those are great businesses, uh, who are making quite a bit of money in a lot of cases, uh, and are founders who have, you know, just as as many dreams as the rest of us do, but, um, if they're not eligible for venture capital because they're not necessarily a market leader in the space, you know, how do you grow your business?

Um, before Lighter Capital, it was bank loans with personal guarantees, which meant financial ruin for some people.

Um, Lighter's product was very innovative in that, uh, instead of taking somebody's FICO score, uh, which is not actually a determinant as to whether or not a business is healthy or not, um, but instead they took the churn rate in a comp a SAS products, um, record book, and they underwrote effectively a loan against the churn rate, uh, the historical churn rate in the business, which is a much better predictor of whether a SAS product is going to grow or not, is going to be able to pay back a loan or not.

Um, and, uh, and and really introduced a new, um, a new funding instrument for, uh, a large group of entrepreneurs that were not being served by the current opportunities in the market. So, uh, Lighter is a a a very cool product.

Um, it's not for everybody, but, you know, uh, then again, neither is venture capital or any other instrument and and, uh, you know, Lighter is a net positive addition to the world in that it gives entrepreneurs another opportunity, another source of of ways to grow their business without, uh, having to sign a personal guarantee or take additional dilution, which is quite cool.

Host: Uh, it it's it reminded me of the company Pipe.

Uh, I don't know if you've heard, uh, it's uh, it's similarly, I mean, I think in 2019, it was a very hot startup, uh, which introduced revenue-based financing product for startups, which was a little bit, uh, precarious because at different stages, the revenue predictability is different.

And if your risk is completely focused on super early stage, that could mean that, uh, the model might not actually work out. Um, so I was referring to, uh, that scenario. Um, but then at some point, uh, you started working in on Allen Institute.

Uh, how did that, uh, uh, you know, came about?

Guest: Well, um, or actually creating, right? Uh, you were one of the founding members if I understand correctly. You know, the the word founder is a funny word.

Uh, it is often given a tremendous amount of respect and and and in a lot of cases, that's deserved. In in our case, uh, I was the first person to walk through the door, but I would be nothing without the rest of our team here.

And this place exists because of the hard work of a number of people and I am but one spoke in a wheel of folks.

Not least of whom are the dozens and dozens of entrepreneurs who have partnered with us and built very cool companies that are doing very well in a lot of cases and those are the real heroes of our story.

Uh, I might have been the first through the door to turn the light switch on and and, you know, uh, screw in the desks and mount the monitors to the tables and do some of the early work.

Um, but it is it is the the folks, um, particularly our entrepreneurs who do the hard work day in and day out that make this collective community that as cool as as it has grown to be.

Um, the incubator started, uh, really as, uh, it was part of the plan from day one for the Allen Institute for AI. Paul Allen and Oren Etzioni co-founded this place in 2014. Uh, and and having a commercialization arm was always part of the plan.

Um, Paul Allen, obviously very entrepreneurial. He co-founded a little company called Microsoft that you might have heard of. Um, but also was heavily involved in investing in startups for for decades after that.

Uh, is incredibly was incredibly entrepreneurial and Oren Etzioni, uh, was the founding CEO and co-founder of of the Allen Institute for AI or AI2 as we call it for short.

Oren in his own life had built and sold, uh, successfully sold five companies on his own, including Faircast to Bing and and a number of other, uh, companies over the years.

And so both Paul and Oren were incredibly entrepreneurial people in addition to having a tremendous respect for the field of AI and a desire to want to push to the bleeding edge of what's possible.

Um, and so, you know, while the Institute was created in 2014, uh, there were some early commercialization efforts.

So Oren led the efforts to, uh, explore the creation of kits.ai and xnor.ai, which were some of the early successes to come out of here.

And then at a certain point, um, Paul and Oren decided that they wanted to double down on creating an incubator, a commercialization arm with the research Institute.

Uh, and in the timing of the century, I I happened to have coffee with Oren at the right week and had expressed a desire to want to do that and, um, Oren and Paul were gracious enough to give me a chance.

Um, but like I said, you know, I might have been the first person through the door, but we would be nothing without the rest of our team here and and again nothing without the entrepreneurs that have come through the door after that.

This place is a very, very cool place. This incubator in particular is one of the most exciting things that I've ever been a part of. Um, and all of that is is made possible by the the folks that are building these companies.

Host: So talk to me a little bit about, uh, the decoupling from the research Institute and the incubator.

Like are you taking about taking the latest research and productizing in the incubator or are you taking pitches from outside founders who are, you know, you worked at Facebook or some, uh, other, uh, places and they want to do some AI company and are pitching you.

Uh, what was the what is the process like?

Guest: You know, we we are a little bit of a mix of a few different things. Um, at the end of the day what we do in the incubator is we co-found companies with entrepreneurs. We are a partner with entrepreneurs.

Um, we happen to, uh, be a partner that has access to, you know, 200 PhDs and researchers and engineers and professors and support staff through, um, our relationship with the Allen Institute for AI.

Uh, the incubator also has a number of people on the core team here who have, you know, many, many years of experience of building companies. Um, and and when we partner with an entrepreneur, uh, we are a minority co-founder in their company.

Um, Y Combinator and Techstars take, you know, 7 to 9% common stock when they get involved, we take 9% common stock when we get involved.

Y Combinator and Techstars will have, you know, hundreds of startups over the course of a year that go through their various programs around the country or or in Silicon Valley.

Um, we'll work with, you know, a couple dozen entrepreneurs at most over the arc of a year, which turns out to be roughly five or six companies a year that will end up, uh, getting incorporated and getting funded through the incubator.

And we're rolling up our sleeves and doing a lot of hard work, uh, to create those those companies. You know, we have, um, a long list of ways that we support our our various partners on our on our website. So AI2 incubator.com/howwehelp.

You can read about all the different ways that we get involved. But basically, to sum up the key points is our job as a co-founder is to help you build the best team possible.

Uh, we, uh, have, uh, thousands of people per year that come through the incubator as introductions or referrals or everything else.

And 100% of the teams that we've built over the years have met a co-founder or several technical first hires through us. Uh, so team building is a really important thing that we do.

We then work really hard to help you create the best product possible and that might include acceleration of the technical stack or advice on applied AI or access to, you know, various learnings, uh, and and things that we've, you know, got the ability to do around foundation models or large language models or or any other, you know, keywords you want to use.

But this is an incredible place where you can find a tremendous amount of technical expertise as well as startup business expertise.

Um, and then we help you raise millions of dollars in seed funding in addition to the ability to write up to half a million dollar, uh, pre-seed check, do the entire pre-seed check round in house ourselves.

So, you know, we build teams, we build product, and we help those teams raise, uh, enough capital to take it to the next level. That's that's what we do.

Uh, it's one of the only VC funds or incubators or venture studios or whatever you want to call it. Like there's a lot of different words out there for similar, uh, types of work that folks like us do.

To our knowledge, we're one of the only places in the world that has, you know, an ecosystem of hundreds of AI PhDs and researchers and engineers and professors and support staff. Like that's a really unique thing that we bring to the table.

Uh, and at a time when, you know, generative AI is, you know, the topic de jour that everybody's talking about.

Um, in a lot of ways we suddenly look like geniuses, but we've been doing this for years and, um, and we're very lucky that that that the the moment is here to, um, help educate the world about all the things that we've been working on for, you know, more than half a decade.

So, you know, it's it's an exciting time. Um, uh, but, you know, truly, we take it very seriously to be and to use the word co-founder. Um, entrepreneurs here, we we fall in love with these teams.

We pour our heart and souls into getting these teams off the ground. We are, you know, crying shoulders to cry on and drinking buddies and all the things involved with the hardship of entrepreneurship because it's hard.

It's hard to get a business off the ground. Um, and we've been there many, many times. Um, and to date, the incubator has now had, you know, over 20 companies that have come through. Um, over 70 AI founders that have come through here.

Those folks have now raised over $150 million. Um, they those companies are worth, you know, 660 million in hard valuation if you count term sheets and so on.

We're closing in on a billion dollars of portfolio valuation, which, you know, half of which was added in the last two years. So, uh, we're we're really excited about the momentum and the energy.

Um, uh, and again, it's a really unique, one of a kind place to build an AI first startup with a group of people who, um, really care. Uh, you know, we we we work really hard.

We we love what we do and and, uh, we care a lot about the products that we create and and we happen to have just a a tremendous amount of AI expertise and, uh, both from an applied AI standpoint and also about how do you build a business model around AI.

Um, and that's really unique.

Host: Uh, see, I mean, uh, we can't not talk about generative AI when I have you on the podcast.

Uh, so, uh, in terms of where we are, um, like, you know, five years back, six years back, uh, it's all about integrating ML, uh, in recommendation systems or, you know, suggesting what's, you know, best for you, what is the next best song to listen to.

Like Spotify was integrating a machine learning into their, you know, playlists, right? We saw, uh, Netflix recommendation system has being hailed as one of the best recommendation systems.

I remember like when I first joined Microsoft, uh, Netflix was announcing, um, a bounty to improve their, you know, machine learning models efficiency from 95% to 98% something like that.

So we saw that era of machine learning and it seems like we are now we are in the new era of machine learning. Can you define to the audience, um, at least how you guys think, uh, about where we are in terms of this journey?

Guest: We are in a very exciting time. Obviously, the chat GPT has captured the world's imagination.

It's captured the imagination of practically every VC fund on the planet and, uh, there are countless stories of ways that these types of technologies are going to change the world and, you know, relentless number of startups that are coming out every week, uh, trying to take advantage of this and activate the the next big thing.

Uh, in times of just tremendous innovation and and opportunity like this, naturally you'll have a lot of stuff that is fluff, uh, and a lot of stuff that you might file under what you would call a hype cycle.

And naturally you're going to have a lot of stuff that really is changing the paradigms, changing the way that that things are done in a variety of different industries.

Uh, I think it's it's it's a time of of trying to maintain some sense of humility to make sure that you're actually solving customers' problems and not just leaning into the hype cycle for the hype cycle's sake or leaning into the technology for the technology's sake.

Um, you know, every couple of months or or so, there's an exciting paper that comes out in AI and we often say, my gosh, this is going to change everything here in the walls of of AI2.

And and then somebody has a sage and wise voice in the back of the room and says, okay, okay, okay, but how are people actually going to use this?

How is this actually going to change a product or an industry or make somebody's life better, either an enterprise, customer or consumer? And I think that's where we're still seeing a little bit of a gap.

You know, some of these tools are very cool and have a tremendous amount of promise, but you're not quite going to use chat GPT to make a recommendation to a Fortune 500 CEO on what the next business move should be, right?

We're not quite there yet, right?

And so I think we are at a very exciting time, but there's still a lot of work to do to close that last gap and really make sure these things are as accurate as they can be, are as impactful as they can be and are actually, you know, products that are are needed by folks and to not lose sight of the fact that, uh, AI is still not something that people buy.

They buy solutions to their problems. You know, nobody has said, you know, hey honey, go to the store on your way home and pick up some bananas, some milk and some AI. People still don't say that.

They want their problems solved and I think our job as innovators is to again maintain some sense of humility and make sure that as we are getting excited about these technologies, which are they seem to be on the precipice of truly breakthroughs and in a lot of cases have already proven themselves to be, but just don't lose sight of the fact that that is still a long ways away from a product that is solving a very specific problem for a very specific customer persona, uh, and and to not get overly caught up in the hype gap between those two things.

Host: So when you think about, uh, you know, a company like Open AI, uh, I mean, everyone knows chat GPT, but what essentially they are doing is creating that foundational model for large, uh, you know, what we are calling as LLMs, right?

Uh, what do you think their business model is going to be?

Because, because this is one of the things that we are seeing with AI companies is like everyone will use an open AI API and call it as .AI in their domain name and say we're an AI company, right? Uh, so I guess it's a two-part question.

Uh, how do you see a company like Open AI or stability AI, uh, and how their business model can be and what do you think can be the moat of companies who are building on top of these, uh, large language models?

Guest: I think literally my feed is 400 articles long every day about, you know, what's Open AI going to do next and, um, you know, I here here's what I'll say.

I think, um, in general, we are very grateful for, uh, the energy and attention over the last, uh, several months, uh, around Open AI.

I think they've done a tremendous job of, um, capturing people's imaginations of what's possible with AI and, and, you know, billions of dollars of earned media, free marketing, uh, for innovators like me.

Um, you know, my parents suddenly know what AI is because they've learned about what's possible and they now understand the basic things that we've been trying to to do for years.

And so we're very grateful to all of that, uh, energy and and awareness that's gone into the market because it makes the lives of our innovators that much easier and, uh, and also it's just a very exciting time where, you know, the tools that Open AI is putting out there and the long list of other folks that are out there are creating the ability for AI tools to get into market with much less friction, much less, uh, pre-roll work, pre-development work, uh, to just get something out to the point at which it can be proved as a viable product.

And so it it is a huge benefit to AI innovators all over the world to have these tools to be able to test with and to be able to improve upon.

Um, there's still work that will need to be done to specialize and personalize and apply, uh, the nuances of each industry and each customer persona, uh, to those products.

It's not enough just to put a skin on top of GPT and call yourself, you know, an an innovative new company.

You've got to figure out how you are going to, you know, specialize that for a particular group of of users and how you are going to include the unique things that are in in exist in each individual industry and and account for those.

Uh, but I think it's a very, very exciting time and I think it's going to be the innovators that can take it that one step further and make sure that they're specializing their products for various industries and not just creating a generic skin on top of GPT.

Those are the ones that are going to be relevant in two years, uh, and and and are are going to have some defensibility and and longevity to those businesses.

Host: And to me, it always looked like the incumbents have much more advantage, uh, in AI in general, like the big tech companies, Google, Microsoft because of the data and the compute and the research that has been going through in all the companies.

Uh, including Facebook. Uh, so I always thought and still think for a large extent, I think the incumbents will compound on that advantage. Uh, what do you think about that?

Guest: Well, in the early 2000s, startups would pitch investors to raise money and their infrastructure was a key factor in their pitch deck. We've got 99% uptime.

You know, we've got, uh, a whole team here that can host our websites and make sure that it doesn't go down.

Um, and then AWS came along and suddenly allowed two people in the proverbial garage to compete with Netflix for the same quality of hosting worldwide.

That was an incredible gift to the community in a lot of ways because, um, you didn't need $4 million to have the world's best hosting system and, you know, IT experts to to make sure that those servers never went down.

You just spun up some machines on AWS and suddenly you're in business. Uh, that was groundbreaking for folks.

And I see a similar AWS type moment happening in in the world today where the historical, uh, story has been that the companies with the most data are going to win the AI game.

Uh, and and I think there's still going to be many scenarios where that will be true. They will have a competitive advantage. The more data you have the better.

But tools like Open AI and and again, the long list of other folks that are offering everything from large language models to you name it that have been pre-trained and have the ability for two people in a proverbial garage to spin up without necessarily having, you know, the data access that that a Google or a Microsoft or an Amazon had previously enjoyed that exclusive access to.

That is an AWS moment that we are seeing. And that is a groundbreaking moment where you know, that idea of having the most data will win isn't necessarily the case anymore.

I mean, it's still relevant and it still matters, but there are definitely holes in that wall that that startups can can can find their way through.

Uh, and and that is, you know, entirely made possible by these new models that are being introduced into the marketplace.

And and again, if you look at historically what that has done for innovation using AWS as as as as as a metaphor or an example, um, I think we're in another cycle of that and that will play out almost the same way is my perspective.

Host: The interesting thing about this moment like, um, uh, and right now because of, you know, chat GPT integration with being, uh, it almost seems or like at least the popular culture perspective is that Google is, you know, behind, right?

Which which seems a little bit hilarious to me because if you've used any Google app or phone, you know that especially people in tech that AI is being rolled out continuously. It's not telling you that it's AI, right?

When you're typing Gmail and it's recommending your text of what to type next, it's AI, right? If you're taking a, um, picture using Google Pixel, it's in computational photography they're using AI, right?

Um, so it's it's a little bit, I mean, the hype is good, but at the same time I think some of the details get blurred in in the moment of hype, uh, for sure as you mentioned. Uh, but do you think in general, large language models can disrupt search?

I mean ignoring this conflict of, you know, what's happening in the short term.

Guest: You any any true-blooded entrepreneur knows that not all customer segments are created equal. You can't sell a product in a repeatable, scalable way to every person on the planet.

People are nuanced and and and you have to divide your market into customer segments that have unique needs and then develop products and marketing campaigns that speak to each of those audiences appropriately.

In in the same vein, not all searches are created equal. And I think people have these grand statements that, uh, GPT is going to kill Google and suddenly search is no longer relevant.

And I think that that to some extent, there are some searches where that's true, right? You know, how old is Barack Obama?

Well, that's an easy one that, uh, will now be answered by Siri or Alexa or, uh, you know, or GPT inside of being or, you know, frankly within Google.

Even Google has, you know, uh, rearranged their search and result pages to surface that logical information very easily for more basic searches.

Uh, do I think there's still a very, very long tail, long list of of types of searches that that will not be served by GPT? Absolutely.

And and so yes, I think that there will be some of a dent in Google's market share from GPT coming out and probably that will grow over time.

But I think this idea that suddenly Google's toast and GPT is going to take over the world is that's a hype cycle statement that is not rooted in the practicalities of how people actually use products and and how those products actually solve problems for people.

Um, I think that Google for the first time in a while has some real competition and I think that's good because competition, you know, breeds competition. It breeds energy and excitement and it creates innovation and it and it's an exciting time.

But I think anybody that's suddenly counting Google out and and seeing it as as as a suddenly like a failed company is is missing, uh, a company that has innovated their pants off.

Anybody that's counting Google out right now is is is not giving credit to a company that has innovated on a wide variety of products that have changed our lives over the years and and I think it's great that Google has some competition, but I I think they're going to show up with some pretty good products over over the coming years and I'm excited to see the entire industry get better.

Host: Uh, slightly shifting gears.

Um, how much do you guys think about AI becomes sentient, uh, or do you guys consider AI becoming intelligent like a human or, you know, like a dog or a cat or like in a human intelligence sense, like do you see even now, I I know like a regular user thinks that it is intelligent, but what I think is it's not intelligent like a human is.

It's a different type of intelligence. Um, because we really don't know how to replicate human intelligence because we firstly don't understand human intelligence in the first place. So we don't know how to replicate it.

Uh, I'm curious what are the debates that you guys have in terms of, uh, AI becomes sentient and what do you think about AI's intelligence versus human intelligence?

Guest: A lot of the times when when people bring up questions like that, uh, it's often quickly followed by, well, what's going to get replaced by AI? When are humans going to become irrelevant?

And I think just pulling it back to the work that we do at the incubator, um, first of all, I think it's going to be many, many, many, many years before, you know, AGI or any of these types of things.

I mean at the end of the day, AI is just software that learns and gets smarter as it learns. It's not, uh, you know, sentient being and it's going to be a long time before that's possible.

Uh, anybody that works in the field of AI will certainly tell you that AI is pretty good, but it's also still, you know, still has a long way to go and is still not nearly the the killer robots that everybody paints it out to be in in in in the press.

Um, what I will say though is that in in the field of innovation, people often worry that AI and automation are going to replace jobs and there are definitely scenarios where that's true. But we work within, uh, the framework of an and not an or.

What I mean by that is it is not the doctor or the AI. It is the doctor and the AI that ends up being a way better outcome for the patient.

For example, there's a lot of hype over the years about AI replacing radiologists and that computer vision can more quickly and articulately identify, you know, a cancerous cell in in a in a in an x-ray or a mammogram or or something else than a doctor can.

And while that may

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