From Living in the Woods to AI Startup Founder (Ben Taylor) - KNN Ep. 78
Updated: 4 days ago
Ben Taylor has over 18 years of machine-learning experience. After studying chemical engineering Taylor worked for Intel/Micron in applied semiconductor building process control and fault models. After that, he worked as a quant at a hedge fund on a 600 GPU cluster. Taylor then joined a young Sequoia-backed HR startup called HireVue to run their data group. In 2017 Taylor co-founded Zeff.ai with David Gonzalez to pursue deep learning for image, audio, video, and text for the enterprise. Zeff was acquired by DataRobot in 2020 where Taylor now works as their Chief AI Evangelist.
In this episode we learn why Ben Lived in a tent in the woods during college, how introspection has changed his career and his relationships with people, and why AI is far more philosophical than you think.
[00:00:00] Ben: There's also a maturity that comes in one's career where you realize, I think when you're young in your career, it's all about the ego of your salary. Like what is my salary? What is my salary? And cuz I learned at the hedge fund that like salary is not gonna make you happy.
[00:00:22] Ken: This episode of Ken's Nearest Neighbors is powered by Z by HP. HP's high compute, workstation-grade line of products and solutions. Today, I had the pleasure of interviewing Ben Taylor. Ben is over 18 years of machine learning experience. So after studying chemical engineering, Ben worked for Intel/Micron in applied semiconductor building process control and fault models.
After that, he worked as a quant at a hedge fund on a 600 GPU cluster, Ben then joined a young Sequoia-backed HR startup called HireVue to run their data group. In 2017 Taylor co-founded Zeff.ai with David Gonzalez to pursue deep learning for image, audio, video, and text for the enterprise. Zeff was acquired by DataRobot in 2020, where Ben now works as their Chief AI Evangelist.
In this episode, we learned why Ben lived in a tent in the woods during college, and how introspection has changed his career and his relationships with people. Finally, we touch on why AI is far more philosophical than you might think. I hope you enjoy the episode. I know. I enjoy talking to Ben. Ben, thank you so much for coming into the Ken's Nearest Neighbors Podcast.
We've talked a lot you kind of offline, we've also talked on LinkedIn and in Harpreet's Data Science Happy Hour, I've really been just like in odd. Some of the things you've said, it's really kind of changed my way of viewing artificial intelligence some of the time. And I wanted to be able to bring you in and have that same experience for the listeners of the podcast. So I hope I didn't make you turn too rad, but thank you for joining me today.
[00:01:57] Ben: Thanks for that kind intro. I'm excited to talk to you. I think we can get through some fun topics.
[00:02:02] Ken: I agree. Well, you know, one of the funnest topics for me is Origin stories. Like I'm a sucker for the Marvel movies. And I love hearing the origin stories of everyone that comes on the show and the first place, I think that the kind of data science, AI story starts is with your experience exploring data or your experience your first experience getting exposed to data, you know, was it something that, you know, that was very memorable or was it just the slow progression into this field for yourself?
[00:02:37] Ben: Yeah. I have a lot of fun with this one. I was on a panel recently and someone asked how we, they asked people on the panel, how they got into data science. And the typical response is, Oh, I was introduced to it in college or whatever. And I said, I started when I was a baby. And when I pulled on that thread, so in high school you know, you're trying to figure out what you're good at.
And I was average at math, like algebra and stuff, but when I got into calculus, I was kicking ass. Like I, if you met me in high school, I was convinced I was some Savan like God's gift to earth for math. And to lean into that, I ruined the curve in the AP math class, like, and it was really weird. So I'd always get a perfect score on the math test.
And if I didn't, I still don't know how I did this. If I didn't like two hours later, or even the next day, I would suddenly have this epiphany, like I missed number 8, Section 3, the answer's this, and I'd go tell the teacher and she'd be like, you're right. That is the answer. And she'd like, gimme full credit.
I don't have a ... like, I don't know what was happening in high school, but high school, like I was firing all cylinders with math. I would spend hours like doing these calculus proofs for fun on like a Saturday. And I was snowboarding at the time. I had a snowboard sponsor when I was 16. For freestyle snowboarding, I was very aggressive breaking bones, getting hit injuries and stuff.
And I was trying to figure out the inertia on some video analysis. And this is back in 2000, like 1998 when like video analysis is not a thing for like a computer, but I was like looking at these screenshots and like putting boxes around my body and trying to figure out like the inertia. And so I remember talking to my calculus teacher and she kind of answered some of my questions.
So she sent me to the local college. So I'm going into like physics TA like rooms and asking them questions, these advanced calculus questions, which is super funny. Cause I went to, went to college and I thought I'd be a math professor until I saw how little they made. And then I decided that I would direct that math energy into medical school.
Cause my dad was a doctor. And so I started down the path of biological engineering, which morphed into chemical engineering with a biomedical emphasis and that's a pretty ha math heavy. Discipl. You do a lot of math kinetics, which is like chemical reactions, math balances, or mass balances, momentum, balances, fluid fluid dynamics.
So a lot of it's very math based. But for me, the thing that really lit the spark was I fell in love with I was introduced to genetic algorithms in 2003 and I just thought that was the coolest thing. Like the fact that the computer could get smarter, like you and I could go out to dinner and the computer's a little smarter than it was before we left.
Like I just thought that was crazy. And so after that, I just chased high performance computing. And so I joke that people think I'm an AI nerd, but deep down under the hood, I'm a high performance computing nerd. So if I can get a big computer screaming and crying, working on a problem, which led to deep learning, right?
So I did a deep learning startup and we had, we did big problems on big computers and we would make them cry for days or weeks on end. Sorry. That was a long, long intro. Longer than I'm used to doing.
[00:05:58] Ken: No, I love that. I think that the additional nuance to me is fascinating. Something that really stands out to me is that you had aptitude for calculus, right?
You had aptitude for math, and that drove a lot of decision making. I think for me, something people I hear a lot is they're, you know, people were passionate about X, Y, Z, and that led them into something. And obviously we're passionate about math and passionate about these insights that you were able to apply math too, but it kind of seems like those two things go in tandem, right?
As they play off of each other, you're you have aptitude and therefore you're passionate and it kind of creates this cool cascade. And, you know, again, I hear this advice of people saying, follow your passions, whatever it might be. But in my mind, you really do have to have some of this aptitude as well, because those things play off of each other really nicely.
[00:06:51] Ben: Yeah, and it definitely strengthens it, right. So if you're super passionate on a topic, you're gonna become an expert. Like it. It's not gonna take that much time. One, one thing I forgot to mention for your listeners, which is maybe a little odd about me. If I had to define Ben Taylor, I'd like to think of myself as being an obsessive rule breaker, hopefully with some passion in between.
But when I went to college, I actually lived in the woods. So I lived in the woods in the snow, Logan, Utah. It has the lowest temperature in the lower 48 states. And I did that for two fall semesters and I didn't do it to get attention. I did it because I was working for the forest service and I didn't wanna waste money on rent.
And my parents were being real sticklers on me paying for everything. And so I'm like, well, if I'm gonna pay for everything, I'm gonna get like an Everest tent and I'm just gonna live in the woods in the snow. And I did it and it ended up making, it ended up making national news. So like. I was newspaper articles.
My phone would ring, I'd pick it up at like six or seven in the morning, and they'd say homeless, Ben you're live on the air and it'd be like Knoxville, Tennessee, or somewhere. And they'd pepper made questions. So, but that, that theme I've been able to kind of keep that in my career where I really don't care if someone's done it.
I like, I don't care if there's a white paper. I don't care if someone's done it. What I really care about is what I want to do. And so for some of my most successful AI projects, they've really kind of seated on this very selfish interest and maybe this reckless ambition that I it's almost like I'm naive to failure.
Like, I, you definitely need to have a healthy respect for failure, but I think if you think too much about failure, then it will kind of overwhelm you and honestly it'll scare you out of some of these projects.
[00:08:31] Ken: Is that something that you think has always been innate to you or it's something that was learned perhaps from the snowboarding and the philosophy there?
[00:08:38] Ben: I think I think it was helpful with snowboarding. So for my peers, I was always going bigger than everyone else. So there there's definitely that hyperventilating, right? Like I'm up on the hill, they've got the video camera rolling, the VHS tapes and they yell, It's time to go. And I'm sure I've worn a heart rate monitor since, and my heart rate's 170 beats per minute.
Like it scares the hell outta me, but when it came to like other kid kids, I was around, I would always go much, much bigger. Like we're talking like double, like twice as big as they would. I was, you know, doing single flips, stuff like that, but I was also getting into like double flips, like trying these double front flips at the time Ben Hinkley was this professional snowboarder.
He was starting to do those. I wanted to do them. I was breaking a lot of snowboards. And so, yeah, I think maybe that's such a cheesy thread for me to pull out of snowboarding, like the whole like go big or go home, like, but maybe that does exist in a way in my career that I get much more excited about the projects where.
Failure is terrifying or like, you know, the consequences are, are huge that these projects cannot fail. And those are the ones I get the most excited about. I really wanna lean into those, but I I was telling my wife recently, I like to find projects where on the scale of a being a dumb ass from a zero and a genius to attend, I don't know where it's gonna land, but I'm gonna fight like hell together.
It's right. And she was like, why, why would you ever want to find yourself in a project where the outcome could be that you're a dumb ass and I'm, I don't know. I think those projects are interesting.
[00:10:19] Ken: Well, you know, I find personally the connection with sport and the connection with my career and my risk tolerance to be very meaningful. You know, like the things that I've taken away from playing golf is that like, I am very comfortable with failure. Because in a golf tournament, one person wins out of a field of a hundred, 150 people. That's something that is bled into my life is that, Hey, like a lot of the things that I do, I'm probably gonna fail at, but that doesn't necessarily mean that it, that I'm a bad person or that I'm inadequate.
It's that there's like a lot of other opportunities out there. And, you know, particularly in like the data science domain, when I was looking for jobs a long time ago, like I was like, Oh, you know, like 2% rate landing an interview, like in golf. If I was winning 2% of tournaments on the PGA tour, I'd be like a top 25 player in the world.
You know what I mean? And the idea that, that philosophy and that experience, it just bleeds in. I'm a huge believer that our experiences physic. Shape our mental capacity. I like, as a lot of people know, I love David Goggins and he's like, look, all discipline is built in the physical domain. And then it transfers over to the mental domain because the physical, physical domain is where we experience things first.
Right? Like when we're kids, we don't have language, right. We have to experience like discipline in these types of things, through a physical domain or a physical outlet. And I don't know that that was something that just like really struck me. And it just made the connection now of how, like the physical experiences I've had have really shaped a lot of the things that, that I do and how I view the world. I probably wouldn't have wouldn't have come to that realization while I was doing them.
[00:12:10] Ben: No, that's fascinating. And with the child learning a language, you do learn a, the language you learned before you learn to speak is you're learning the language of the world around you. So like physics, if a ball's gonna fall off the table, how things relate, size comparisons.
Like your, your brain is very busy before you ever hear be before you figure out language. And so that, I'm a huge fan of Goggins too. It like, if you wanna feel like a loser, go look at Goggins Instagram. And you're like, Ugh, like it, there was freezing rain last night. And I was thinking I could go on a six mile run in the freezing rain, but I didn't, I went to bed.
[00:12:49] Ken: And David Goggins would've gone.
[00:12:50] Ben: Yeah. Would've gone. Yeah. And then when David Goggins is standing in my living room shredded, and I'm not, he'll be like, I don't compromise and I'll be like, I know, I know you don't compromise. I'm pathetic.
[00:13:03] Ken: But you know, David Goggins, he does say that not everyone has to be David Goggins. And that's a beautiful part of it. And you know, like, I, sorry, go ahead.
[00:13:13] Ben: Oh, I was gonna laugh because I did a recent AI project. I did an AI project recently where I was able to combine fitness. With AI. So we did this backpacking trip and the wind river ranged and we had Invidia and snowflake out there and it was a 20 mile.
Like it was 10 miles in ... to where we had to go. And I did that trip twice to get ready for the main trip, because I had to have as much Intel as I could. It's really high stakes. Like I can't have someone get hurt on this trip, but I also can't fail. I can't not get the content that I'm expecting to get.
So it was just funny being out there, hiking with a fully loaded pack. Cause I didn't have to, I could have had like water bottles or something, but I wanted to have the full experience to make sure that I knew what I was getting into. So when it actually came time to do the full experience, I think hiking out, I had a, had to help someone out and I think I was carrying close to a hundred pound pack on the hike out, but it was an strenuous hike compared to the main hike like it. I was ready for it. So for me it was, yeah. Anyway, not to distract, but I just thought that was funny just.
[00:14:21] Ken: Can you give more details on that project? To me, I love hearing about like unique projects.
[00:14:29] Ben: So I have a lot of fun bringing AI into everyday life because AI can, it can make you a lot of money with loss prediction, credit card, fraud detection, like there's so many practical use cases, but they aren't. They make a lot of money. They pay the bills. They're they make executives happy, but they're not inspiring necessarily. There are a lot of AI projects that are very inspiring that actually speak to a large audience. And so a few of those, I did one where I built up an AI fitness coach. So camera's always looking at me, knows if I'm working, doing pushups pullups or sit ups.
So then I have now. Pushed all my accountability onto an AI system. So there's perfect accountability. I don't have to enter something into an app. It just knows if I'm doing what I agreed to do. One of the projects that showed up was could we build out an AI training set to predict if AI, if fish will roll on a dry flight cast.
So I like fly fishing. A lot of people like fly fishing. So if I cast a fly onto a river, am I gonna catch a fish? And for people that like the sport, this actually kind of creates this anxiety, this intuition that like, you, it actually puts you on edge if you know the sport, because there's this adrenaline high that you're gonna get.
If the answer's yes. And so if I show you a 15 second clip on whether or not official role in this drive fly, it's a tricky problem. It's not called catching. It's called fishing. There's a reason it's called fishing because people, sometimes they don't catch anything. And so the goal was to go. It was called 10,000 cast.
Go get all of these cast filmed video sequences and labeled to teach an AI system to predict if official role in dry flick cast. So that, that was the seed of the project. But we went out there with a film crew, 10 people, lots of variables, which kind of adds to the chaos, right? The variables are COVID.
Someone could have COVID you got 10 people planning into Jackson hole weather. One of the pre-trips weather kicked my ass. It was like freezing, hail and thunder. Like that's not gonna work. And then just, you know, physically someone getting hurt, like what if it's bear country? And then what if we don't catch a fish?
Like what if you had a whole crew go out, spend all this money and you came back and no one caught a single fish. Like those, those are all variables that you're dealing with, which I think is hilarious because most companies would not. Bet on that type of a project because there's too many variables, like one of those hits and the whole thing fails. So, and if you start adding up all of those variables, the probability of it failing is high, but there's yeah. Anyway, project turned out great.
[00:17:13] Ken: Awesome. How many fish did you catch? I figure like sample size would be relatively...
[00:17:17] Ben: Yeah. It's definitely a biased. Yeah. It's definitely a biased data set. I think the group caught close to a hundred fish. The first week, that was my thought. Yeah. But the data set's definitely gonna be skewed low, but the fun thing with it is we're gonna launch it in the middle of November. But the fun thing with, with it is it actually. It kind of brings up this more human discussion on why are we able to predict this versus that?
And what's all the information that we're pulling out of the video and what's the information that you would pull out being a human expert. But it, so when I give talks, I like to have emotional openers. So another project I'm working on right now is I've got this messy house AI project. So I've got a fisheye lens camera installed.
It can see my entire living room and TV area. And I'm building out a data set to predict when the room is messy or when it's a house rule has been violated. So like eating in the TV room or my kids watch these terrible YouTube channels that I absolutely my wife and I hate them. And so that would be another label.
And so this fish islands camera, if it sees any of these things violated and the TV's turned off, and then as a parent, then instead of being the dictator saying, you have to clean, why are you doing this? I can kind of take the attitude of, Ah, clean if you want. Like you guys haven't had TV for a week. I don't care.
So I'm, that's another project that I'm working on right now, which I think is really fun, cuz it feels more human for anyone. Who's a parent. They're like, that's amazing. I want that. Like how do I get that for me?
[00:18:47] Ken: I love that idea of taking like, it's like really like a weird, in a sense, but you're taking the, you're using AI to take like the blame off of yourself of being like a stern parent or something like that. Also it's like I, you know, the computer in the sky is the...
[00:19:04] Ben: Well, it's funny because everyone laughs at the project when they hear about it, but it actually goes into a black mirror territory and the black mirror territory is let's imagine a world where I was never, I never disciplined my kids. Like it was all just like house rules, systems that were being implemented or even a droid.
We were talking about this before we jumped on is like TikTok and some of these other social apps, they definitely impact your development. How is that gonna impact your development? If your parents are never mad at you, if your parents never. Put you in timeout, it's always the house that's like bringing down these consequences and then your, your parents more diplomatic, like, Oh man, like weshould really vote on these house rules. Shouldn't we? Or like that's a question mark. I don't know how that's gonna affect your development. I can't imagine...
[00:19:52] Ken: You can see benefits and drawbacks obviously.
[00:19:55] Ben: Yeah. I'm just excited to never pick up a little Caesar's pepperoni off the couch ever again. Cuz that's gross.
[00:20:04] Ken: Yeah, I could see that.
[00:20:07] Ben: Yeah. It has like grease stains under it and it's on our, like our nice new couch and we're like really? Cuz our seven year old he takes all Elvis pepperoni off and just throws them wherever he's sitting, eating his pizza.
[00:20:18] Ken: Does he not like them? He is missing out.
[00:20:19] Ben: Yeah, he, yeah, he doesn't like them. He thinks they're spicy.
I think that's something with kids. Their spice tolerance changes as they get older. Yeah, none of my kids can handle spice.
[00:20:31] Ken: Well, you know, I experienced that with coffee is that it tasted way more bitter when I was a kid. Okay. And I've been a, like, now it, I drink it. I don't like love the taste, actually. I haven't in a month, I gave up caffeine this month. I'm exploring that.
[00:20:46] Ben: Oh, nice. I've heard when you reintroduce it can be really powerful. Like if you have no coffee for a month or yeah. I think someone was talking about this on Joe Rogan and you bring it back it's cuz it's something I kind of take for granted. Cause I have two or three cups a day, every day.
[00:21:05] Ken: You know, I, for some reason like wired into my biology, I just like, I get really anxious if drink caffeine. I feel energetic, I feel fine. And then the afternoon, the night of that day, I just get this like weird feeling like I have stuff to do, but I'm too tired to do it and I, yeah, it just eats me alive.
And so yeah, I've been just experimenting with. You know, something that you talked about quite a lot is like, you, you, you experiment, you like test things. You no real risk involved in that. Aside from me, maybe not sending out quite as many emails. So like no harm, no foul. If it doesn't work.
[00:21:43] Ben: You just reminded me. There's an Instagram account that trolls, the worst of LinkedIn it's called The Best of LinkedIn. And so the worst cringe post on LinkedIn will get shared there and they try to obfuscate the person's face or their name. I had one of my posts show up there and it was a post over coffee, cuz I had some memory from startup land where I think it was like eight or nine at night where it's some restaurant and I'm asking for coffee and the waitress kind of says like really coffee, like it's, you know, it's late.
And I laughed and said, ah, we're in a startup like, like cuz we were grinding so hard, like 11 at night till two in the morning. And like. I could drink coffee at 11:00 PM and go straight to sleep cuz I'm sleep deprived. And so I posted some startup flex talking about drinking co like that. I essentially posted that story and it's funny, ended up on best of LinkedIn on Instagram and people are commenting. Like she should have hit you in the head with the coffee pot or it it's funny.
[00:22:45] Ken: Hey, at least you can admit it. I respect that. Yeah, I think it's...
[00:22:49] Ben: I've had some cringy posts out there. Actually, I think one, I used to be a lot more controversial. One of my most viewed posts was you can find out on the internet, it's called the title of it is this is why your data scientist sucks.
And really the gist of the blog post was how, how to hire your first data scientist, like more catered to a business audience. If that was the title. I think it would've had like a blip of engage. So I changed the title, but I also kind of wrote it where if you are, if you're a business person, if you're an executive, and if you agree with my points, I actually want you to fire your data scientists like cuz cuz that, that is actually a critical part of the company.
A lot of times people hire a new kid outta school. They're very promising. They have no experience. They're not as expensive as someone who's been around the block. And so I wrote this article this way. And so many people took personal offense. Like I don't know you so and so working at IBM or you know, other company like so many people took so much offense and it's interesting cuz 60% of the people loved it, but 40% of the people hated it.
And I've still had people tweet at me saying that this article is toxic. It should be deleted from the internet. And it's really old. It's like eight years old, which is funny to me cuz it's like, eh, you like we're adults. Like. It's hard for me to imagine that a blog post saying, this is why your data scientist sucks, could like be that upsetting to some people.
[00:24:22] Ken: Yeah. You know, that is something that I find personally conflicting. So there's a trade off between to a certain extent, authenticity and shareability and viewability. Right. Just as you, just, as you had described, like how to hire your first data scientist, that title would get essentially like very low engagement compared to the other post.
Yeah. Like if you wanna spread a message, it kind of has to be a little bit controversial. And, you know, I've had some feedback on my YouTube channel right. Where it's like, Ken, you know, your, your thumbnails and titles are clickbait or something along those lines. Right. And it's like, you know, I want what I'm saying, because I think it does provide value to reach as many people as possible, right.
And I have to make that trade off in my head to say, Hey, you know, even if it is little click baby, like when someone watches it, are they gonna get value from it? Is it gonna be completely off base from what they're seeing? No. Right. Like I'm trying to spice up the message and make it appealing and, you know, for better or for worse on LinkedIn, on YouTube, we're also playing into algorithms, right.
It's not just, are people gonna view this? Is it gonna get shared and for better, or for worse generally for worse things that are more controversial get shared more frequently. Yeah. And so I have this really aggressive battle with the. Whenever I post a video is to say, Hey, what is gonna get the most viewership?
Because I think what I'm saying is hopefully providing value and are people, you know, like gonna be turned off by the messaging, or is this gonna be divisive or is this gonna, you know, upset 40% of the people? And I don't know the answer to that, right? Yeah. It's a, again, this constant experiment, but...
[00:26:22] Ben: Sometimes you can offer value to people if you upset them, too. And so I've set some posts that have rattled people and I know at least one instance where that individual went and quit their job. And then a year later they, you know, had an opportunity to meet them. And they actually attributed that decision to me. I said something online that I think jarred them, or it was just like this raw truth that kind of shook them.
And they quit their job and it was kind of startling for me when I met them. And I, they said, you're the reason I quit my job last year. I was like, Ugh, like, was that, was that good? Like, cause you, you know, what if someone said like, and I've been unemployed ever since, or I've hated my new cuz changing jobs is always, there's always your risk associated with it.
Like you might like your new boss and then they're fired two months later. And now what, now you hate your other boss or like there's so much certainty switching jobs. But I think it all comes back to authenticity. So if you're just being really authentic and wrong I did have someone gimme feedback launch that I was being too negative.
That was, I think that was like seven years ago. And so I've tried to kind of have a little bit more positivity and probably I'm at a different place just in my career and just in life generally that I'm a more positive person now. I remember someone complaining seven years ago that like all of my posts were antagonistic. All of my posts were negative. You know, I was always going after someone or something to criticize them.
[00:27:54] Ken: Yeah. Well, I will say before we touch on that, can you tell can you say what the advice was or what the post was about that made this person quit their job? I'm personally interested.
[00:28:06] Ben: Yeah, I think so if I had to guess, I sometimes I'll just tell career stories, just like, Hey, this is what happened to me. And I remember I got a job at Intel micron, which is so funny. Like I'm driving up to the fab, it's a $6 billion fab and I'm driving my car before getting that job. I made $14,000 a year and now I'm making $68,000 a year.
And for people with masters in chemical engineering, that's like amazing at the time. Cuz it was 2008. So I'm driving up to the fab feeling like I've made it. This is great. And the technology inside was amazing. Like for a full week, I was staring at the ceiling cuz it's all autonomous, it's all automated.
The fab is a hundred percent automated with robots. And I worked in a room called the billion dollar room. And so I was overwhelmed with this is awesome. Like all of this is awesome. And I remember I ran into a neighbor and I promised this was a succinct LinkedIn post. I ran into a neighbor and they said, Oh yeah, like I'm on my third job after college.
And I remember hearing that gave me anxiety, just the idea of quitting. My first job gave me anxiety. I just felt so vulnerable. Cuz you now have a house payment like you, you have, you're not used to being in the market. Like you got your first job. And so it's funny. After, after meeting that individual, I ended up quitting.
I quit iron flash, went to the hedge fund, came back to iron flash, went to, I view like I learned market security over job security. So I actually learned that quitting a job quitting your job is not a big deal. and I think I even gave the recommendation that everyone should quit. If everyone should quit their first job out of school within the first two years, because they can never give you the raise that another employer would give you.
And that was maybe, maybe that was a post that was a little too honest, a post that hiring managers would not want you to know or think about cuz it like it. You know, if I heard you at DataRobot I don't really want you to be thinking about that. You know, I don't want you to be thinking about, you'll actually get more if you jump ship in two years. So maybe as a post like that.
[00:30:06] Ken: This episode of Ken's Nearest Neighbors is brought to you by Z by HP. HP's high compute, workstation-grade line and products and solution. Z is specifically made for high performance data science solutions. And I personally use the ZBook Studio and the Z4 Workstation. I really love that the Z line can come standard with Linux and they also can be configured with the data science software stack. With the software stack, you can get right into the work of doing data science on day 1 without the overhead of having to completely reconfigure your new machine.
Now back to our show. Well, on the flip side of that, I think that that's like a, has the potential to be a market correction post, right. Where it's like, yes, in the current date and time, other companies might be willing to pay you significantly more in that time period for shifting. But if companies are aware of that and hiring managers are aware of that, they might be willing to change the pay structure within their own organizations.
And, you know, frankly, I think the biggest tech companies out there are doing that. Yeah. Where it's like, you know, if you land a job at a Facebook or a Google, you know that you're going elsewhere, you're not gonna have a competitive pricing because you're. Getting paid about as much as you could possibly be paid in those roles. And so it's interesting to think about it in the dynamic of that other side as well, right?
[00:31:27] Ben: Yeah. And the there's also a maturity that comes in one's career where you realize, I think when you're young in your career, it's all about the ego of your salary. Like what is my salary? What is my salary? Cause I learned at the hedge fund that like, salary's not gonna make you happy.
Like there there's so many. No, I was gonna say, there's so many other parts of the job, you know, are you gonna get divorced working at this job because your family doesn't see you or like, are you actually happy? and so I became very sensitive to the, kind of the tr the live to work versus the work to live mindset.
And so like, there's definitely jobs out there where you feel like you live to work, but I also didn't like, so I, and flash, it was definitely this clock in clock out attitude. So you're forced to take time off. Like at lunch, we had an hour long break. And so during the hour long break, don't bug me. I'm not gonna think about work.
There's not a single brain cycle about work. And I think for me that doesn't really work. I do like working for tech startups where work does consume me. It doesn't mean I don't live. Like I still, you know, go snowboarding. I've got a wonderful family and kids that I invest time with. But I constantly think about work.
Like the there's not a single weekend, I'm not working, but it doesn't mean that we don't still go do something as a family. Like, so I would, but everyone's different like that for me, that's the type of job that I want. I don't want a job where I'm not mentally consumed by that job outside of work. I want a job that consumes me.
[00:33:01] Ken: I think that understanding that about yourself is really important early on in your career. And to your point about switching careers, that's how you determine it. You know, like every time I've worked. At a company I didn't enjoy. I was never engaged. I had to believe or live it as transactional as possible.
Like I come in at this hour, I leave it this hour, every company that I've worked at that I enjoy. I'm very much in your camp where I can't differentiate a lot of the different components in my life. Like everything, including work has just kind of smushed together. And fortunately, like, I can make time for other things, but I don't view things as different compartments.
Right? Like my work is who I am, the relationships that I'm a part of is who I am. The hobbies that I have is who I am. And they're all just like this weird mess inside of me. Which makes things difficult sometimes. Right. But I've found that like, because they're so interconnected and now because I have a lot of control over those things, I'm like immensely happy because I'm constantly working on things and a part of things that I really enjoy.
Like there's very few parts of my life. Now that one, I don't feel like I have control over. And two, I feel like I don't want to be doing. And like, you know, if you can find that in work and you're like that type of person, that's incredible. If you can find happiness and compartmentalizing and saying, I work here when I'm in work, I'm in work mode when I'm not in work, I'm not at work mode.
I turn it off. I do family mode and these other things great. But I mean the amount of introspection that I had to come to to realize that, Hey, like, you know, it's bad in a sense that like, if my relationship is not going well, my work suffers. Like that is not a good thing. But at the same time, if all those things are firing on all cylinders, I can do work that I would've never imagined in a million years that I was capable of.
[00:35:06] Ben: Yeah. And so, that's huge. Yeah. It's huge to line passion with passion with work like that. So I've one of the best talks I've given in my career. I gave a talk at data science go couple years ago where cuz I geek out about storytelling. So like I can go back and review a talk recording and no, I crushed this talk like compared to other talks, this talk, hit it outta the park and that talk.
I was talking about this concept of being normal, to curious, to passionate, to obsessed. So I was telling the audience that like when it comes to obsession and AI am like, like I am gone. I'm just totally obsessed. So I'm telling the audience that look be this morning, giving you this talk. I woke up at two 30 in the morning.
I wake up every day at two 30 in the morning and it feels like Christmas every single day. And I'm programming every single day because that's how obsessed I am. Cuz at the time that was right, like. I was just so enamored with deep learning and, you know, the data center that we had and the problems we were working on and the contacts we had, like, it really does help grease the wills for something great.
Cuz I like to say, find yourself doing something where you genuinely would want to wake up early on a Saturday to put some cycles into it or on a Sunday. Cuz if the answer, if you don't want to, then you're really not that passionate about work. But you do wanna watch out for like the grinder scenarios.
Like I definitely see that in the tech space, like super, super hardcore grinding cultures where if you don't work a hundred hours a week, you're not committed and that can be pretty soul crushing. I think just urgency in startup in startup plan, we definitely dealt with this urgency versus strategic thinking, like tension that exists.
You know, our, you can chase urgency and still screw up a startup because you are chasing customer, customer complaints are doing things that aren't actually the right strategic decision. But then if you don't execute, if you're just being a strategic thinker, that's not gonna be a good either for the startup.
And so I kind of love that tension. Like urgency comes knocking where sometimes being an employee, you don't, you never face the storm being a founder. You live in the storm. And every founder I talk to, they have a pit in their stomach and they quickly get past the ego because it's like mentally, it's just, the load is unbelievable.
Like the load of payroll, like you being an employee, you can quit your job. And that's actually a luxury like, congratulations, like have a bad day, go quit. Like maybe take a week off, take a month off, then go get a job. But being a founder, if you quit, that impacts investors. That impacts employees that impacts like, co-founders like. It's a very different scenario to find yourself in that quitting is not it's not as easy.
[00:37:59] Ken: You know, more recently I found myself in the almost opposite scenario. So I've been for the last like couple years, I've really focused on my health. Like I legitimately wanna live to two, 300 years old and I don't think it's, it's like outside hugely outside the realm of possibility with some of the things I've been reading, right.
But, you know, I effectively stop drinking. I like exercise every day, do all these things. And I realized that that was giving me like a lack of urgency. Right? If you live for 200 years and you're healthy, when do you get married? You don't have to get married in your first a hundred years. Even you still have two thirds of your life to spend with someone else.
To me, that's like, you know, Oh, like I can do this tomorrow. If I'm living for this long, whatever it might be. Yeah. And I had this epiphany and it's like super obvious advice. It's like, Okay, would you still do the same things that you're doing today? If it was your last day? Right. And when I thought about that in the frame of like the lack of urgency I had, because I'm expecting or wanting to live for a long time, that really hit me hard is like, what aren't I doing today?
Like that, that I would be doing if I had the proper motivation to do it. And what long term, long stream consequences or like benefits would I have if I took that action now, rather than, than later in 50 years or whatever it might be. And I kind of revised it and I write this down every day is like, What would you be doing if you knew that this was like the first day of the last week that you have to live?
Because to me that gives a proper sense of urgency of everything I need to get done. Like honestly, if it was the first day of my last week to live, I would still probably do a lot of the things that I do work on a lot of the same projects that I work on now, because I generally think it's meaningful. I generally enjoy doing it.
It wouldn't change my life that much, but it would still provide some urgency for me to get things done in the proper way. And I think finding that balance for each individual person, it's like pretty hard. I mean, something that, you know, after 30 years, 31 years, I still am like barely figuring out to me. That's something if I had known that earlier, I would've, I would've loved to been able to view the world through like a tentatively urgent. Without the dire consequences and worry about those.
[00:40:24] Ben: Yeah, no, that's really interesting. I think, I think something that humans don't talk enough about is death. Like death is coming, we're all terminal. We're all gonna die at different times, but there's also the uncertainty that you could die tomorrow in a car crash. Like there's you, you actually can't guarantee, even if you're very, very healthy and you do everything right. You can't guarantee that something, some freak accident couldn't happen.
Yeah. Like you falling down the stairs, like when you begin looking at the statistics, the likelihood of you dying, falling down the stairs, choking being in a car accident or these different things are surprisingly high. Even though if you look at Americans, a quarter of us will die from heart disease and other things like there are some big things that are out there, but you look at these little threats that could take you away.
It, yeah, I think that's something it'd be nice. If more people would kind of take that lens on. Cuz when you're gone, what was your purpose? Like it actually, you just reminded me if isn't there a Japanese island where they, they outlive everyone. Like they, they average people on the island to go over a hundred.
They, I was, they were talking about how a big part of that is that everyone has a purpose. Like they, they, everyone has a mission. They don't retire away. They, they all have a purpose. They all have something they're gonna do tomorrow. And so having a purpose, that's actually a big deal for your longevity.
Like what is your mission in life? What are you gonna do tomorrow? And it can't just be surfing. Or this actually reminds me of the whole universal income. When AI takes over the world, do you want to go surf every day and drink beer on the beach? And in the reality is that actually won't make you happy.
That'll that might be great for a week, maybe even for a month, but like long term, you will not be happy unless you're creating, unless you're innovating, unless you're being challenged, unless you're having. Everything. Can't be perfect. Like it's really interesting if everything was perfect in your life.
I think that would be bad. Cuz you need reference. You need, you need reference to pain. You need reference to sorrow, you need reference. Yeah. It's just fascinating. Like you need that chaos. You need to have yeah. You like, you're not gonna enjoy the steak unless you know, eat the oatmeal. You have to have that diversity in experience.
but the other thing I've realized is I think sometimes as parents, you over obsess about like, are you raising your kids, right? Are you doing the right things? Are you setting them up for success? And I think there's part of this stochastic motion that you you don't know, like you really don't know, like if I've got a kid who's dyslexic and you do, we do our best to help him read and stuff.
But like one of the beautiful things about hum humanity is the chaos. Like the, your experience, your, your, your background. You could find someone else that has, we might agree their background is more negative or they don't have as many opportunities, but they could actually have a bigger impact on society.
Like you, there's no way to predict the recipe for positive impact. Which I think is kind of beautiful. Like that's stochastic chaos that exists in humanity. There's something that this sits on AGI in the future, where there be a singularity that is a singular consciousness and it actually makes sense that there would not be, cuz it won't accomplish goals very well.
You need just like you and I would have differences of ideas and opinions. We will innovate better together than one of us would on our own. And that would be true of like a, you know, a singular AI system. It needs to, it needs to have separate entities that actually have a little bit of, you know, have their own diversity of experience.
[00:44:06] Ken: It's randomness, right? I mean, if we look at, I was challenged to read the Selfish Gene by Richard Dawkins for recently.
[00:44:16] Ben: Yeah. You recommend it.
[00:44:19] Ken: Yeah. I mean, I read the Blind Watchmaker and I think that like biological philosophy is very interesting. I mean, I think that for anyone who is like questioning belief systems, it's valuable, but what a lot of people, you know, when they talk about like biology and hardcore science that they don't realize is that the universe is infinite.
So it leaves infinite possibilities for any belief system out there. So like, you know, someone I was talking to, they were really like harsh on organized religion, right. And, you know, that's, you know, I don't particularly conform to any specific organized religion, but I leave the possibility out there open because again, the universe is infinite and it's continuing to expand the probability that there is something that is outside of our current understanding that we will not be able to conceptualize is almost guaranteed, right?
And so my thought is that, Hey, like I won't ever doubt someone else's necessarily a question, a belief system, but I won't completely put it to bed because if it helps them to, to manage the world, it helps give them structure around how they live their life. I don't think that that's always necessarily a bad thing, but I digress.
I think that the point of the book though, is that, why are we here? Right. Yeah. And a lot of evolution is based on perpetuating a species. And like some would believe that humans are around to continue humanity. And the only way that we continue humanity is through these like really through really aggressive randomness and natural selection, right?
Like in order to continue to grow, we can't all become uniform because in our biology, if like wekeep hitting with our family, that is not a good thing, right? Like wereach a bad consequence where there isn't enough diversity. And so it's a continual balance of the improvement and organized randomness and diversity, which I think is really fascinating.
And it's like directly related to what you're describing with the singular intelligence is that would a singular intelligence be able to have any diversity to learn and grow? No, it would be static. And what does anything, what happens to everything that is static, right? it either dies or it gets bored or it is moved towards some form of action if it is a conscious thing. So, you know, long way of saying that I think zoology or what ology, pathology, whatever the disciplinary studies would probably back up your idea that there can be no one singular entity in a singularity setting.
[00:47:06] Ben: Yeah, it also reminds me the importance of ego. So like the, a lot of our most famous, a lot of our biggest innovations are driven by competition. Like you look at like the whole space, race U.S. versus Russia, or even like Watson and Creek. And like some of these big milestones. Moderna versus Pfizer. Like we're trying to get RNA vaccines out, like we're we have competitive parallel innovation. And I think there's like, if you wanted to genetically engineer humans to increase empathy or to remove ego, I think that would be bad.
Like when it comes to our, our future to innovate, which I think is really interesting. Cause I, in the news, you see bad behavior of humans with our emotions. Like I wish we weren't so polarized in the us with our politics. I went, I wish we would all be rational. And so it's interesting if you, if we, you move the emotions from people, I think you escape, what makes us so great.
[00:48:07] Ken: Yeah. Well, I think it's very difficult to see innovation without some ego. And I think, yeah, it's a matter of like being conscious of the ego. I mean, like, and being able to, to manage it. Right. And like, know when ego is important. I think ego is unbelievably valuable in motivation.
Like, it'd be really hard for me to, to, to get up and like record a podcast every day or do my data science work or do any of these things. If I was completely absolved from any ego that I ever felt, right. Like what is the motivation to do these things, right. Yeah. To me that, that almost dissipates.
But for me to say that I'm doing this only to fulfill my own needs to feel important or whatever it is. I don't think that it would be sustainable. If anything I did would be sustainable, if that was my, like my Motus opera..., you know? So that, that does raise a really interesting question about. About balance and ego.
[00:49:05] Ben: Yeah. Well, ego evolves over one's career. I was just thinking at higher view, during my peak ego days, if you had asked who's the smartest person in this room with like a lot of data scientists and engineers around I'd raised my hand, like immediately, but if you ask that now, like, I don't care.
Like I'll let some young, like some young buck or some, you know, someone who's wants to prove to someone else that they're, you know, they, they should matter. It. It's interesting. And we were talking about this before. Just I celebrate being able to ask the stupid questions because I find that if you have a stupid question to ask, there's always someone else in the meeting or someone else in the room, they have the same, like three letter acronyms, but all there's other stupid questions that show up all the time, but people are so scared to ask them because they feel vulnerable.
And yeah. But I didn't want that to come across either that I'm so overly arrogant and I'm not vulnerable. I think you learn that there's some things that really don't, it's more of a priority. Does that makes sense? Like, I didn't want that to come across to your reader, your listeners, that like, I can ask stupid questions because I've earned all the points that can be earned. It's no, it's just a change in priorities.
[00:50:28] Ken: Well, I think that that's a really important thing that, that I've also personally realized is that like, feeling like you're the smartest person in the room, it comes with an immense amount of pressure. Like if you were to raise your hand in that scenario, there's expectations around you to know everything and self-imposed expectations around those types of things, which I feel personally stunt my growth when I'm in those scenarios.
[00:50:56] Ben: You don't wanna be the smartest person in the room. You want be the dumbest person, cuz you're gonna learn a lot. So find yourself surrounded by people that are smarter than you, and you'll learn something every day.
[00:51:06] Ken: Yeah. Well, and the other thing that I think is interesting, which is a little paradoxical about intelligence is how do we define it? Right. We were talking a little bit before offline, is that, you know, what is the smartest person in the room? Like maybe maybe you're the smartest or maybe I'm the smartest when it comes to data science and AI, but when it comes to something else, whether it's like personal understanding, whether it's golf, whether it's fly fishing, I'm a big fly fisherman by the way. So next...
[00:51:33] Ben: Oh, you are nice. That's awesome.
[00:51:35] Ken: I go out there. There's some like shallow water and there's bone fish. So I'm doing a lot more salt water than you to digress.
[00:51:44] Ben: Oh no, I haven't done any salt water fly fishing. It, I do feel like intelligence is. I'm probably gonna hang myself with my thought process right now.
So I'd like to say it's not one dimensional, it's multidimensional, but if I wanted to oversimplify it, let's say it's two dimensional. And so if you are, and what I'm, what I'm going towards is like, just if I wanted to compare people in the animal kingdom. So like a human versus new alien showed up new aliens smarter than us.
The two dimensions I would have would be time and space. So an alien would be able to predict if some, if I have a super intelligence, it'll be able to predict further in the future, then you can, it'll be able to finish your sentence further in the future than you can, but it'll also have a better appreci appreciation of space.
So I think like quantum mechanics and just our understanding of reality, and if I do this decision, it has this impact, but intelligence obviously is more complicated than that. Cause you have emotional intelligence. You have. Things that kind of tie to experienced verticals and et cetera. But if I had to keep it really simple, just, Oh, alien showed up, are they smarter than us?
I think the answer is yes, because they, they were able to cover time. And so they're gonna have a better understanding of physics, but it doesn't mean they're gonna understand human empathy and it doesn't mean they're going to, they don't even necessarily have to be conscious the way that we understand consciousness.
Which I think is really interesting. Cuz you kind of go down this rabbit hole of how, cause I think in on earth we have these layers of intelligence. I'm hungry, I'm fearful of predator. I have compassion, empathy, humor. We actually see these behaviors in a lot of other animals like in dolphins and elephants and curiosity, stuff like that.
But then up in the human layer, you get religion and you get like, you get these very high, like higher intelligent behaviors, consciousness. But it doesn't mean an alien has to have all those things. Like there could be another direction. Right?
[00:53:47] Ken: Well, absolutely. And something I also would make sure we wanna throw in there is a capacity for growth, right? I don't think anyone would say humans are less intelligent, less intelligent than dogs are, for example. Right. But you would probably argue that like a, like a seven year old dog, or maybe even like a two or three year old dog is smarter than an eight month old child in a lot of ways, right? Like in terms of responding to command or maybe not eight month old child, but like a very young child, right. In terms of what their capabilities are.
[00:54:19] Ben: And an elephant, an, a dolphin will be smarter than an adult human with. So an elephant will be smarter on how do you control 10,000 muscles in a... Humans.
We can't even comprehend that. Like how, how on earth could I do that? That doesn't make sense. Or like I saw you controlling like three or two. But then a dolphin's ability to comprehend sonar. Like just that, that input coming into the brain. He like that, that's not something we comprehend.
Like, it's pretty fascinating how a dolphin can actually tell the difference between a golf ball and a ping pong ball and a water. Like they, it's a pretty sophisticated sensory organ. Yeah. I just hope someday in the future, we'll be able to understand like elephant and dolphin dreaming and like what, or even like a dog, like what, you know, I imagine there's a lot of similar structure that they go through.
Like, you've probably, you've seen videos of dogs having like a nightmare, doing something funny, you know, humans at night, we are processing. Our experience trying to organize things. And yeah, it's pretty interesting. Just the miracle of the brain at night as you sleep. I, you know, I think we still don't really appreciate what is actually going on and why it's so important for you to not go insane.
[00:55:41] Ken: Well, when you do an AI project on sleep, I'm all in because I, one of my biggest things, my biggest priorities this year has been sleep. I read that book why we sleep a while ago. And I obsessed, I got this, the oral ring, and...
[00:55:56] Ben: Okay. So do you sleep eight hours a night now after reading that book? Or do you try to.
[00:56:01] Ken: So I don't use an alarm clock. I just wake up when I wake up every single day and I try to go to bed at around a normal time. My body, I usually only like sleep seven hours or so. And that's about like...
[00:56:15] Ben: Have you noticed yourself waking up really early, like at 4:00 AM, some mornings you're just, Oh, I'm like awake. I'll go work for a little bit. Do you take naps during the day?
[00:56:25] Ken: I will take naps if I don't feel like I got rested. Well rested enough. I'd say I nap about one or two days a week. I usually am very consistent with when I wake up. Like, it's almost always, like there was a solid two week period where I woke up at 07:14 on the dot every single morning. Like, no variance. It was very strange. But it, you know, it depends on like the other lifestyle lifestyle factors, but pretty good. Usually between 06:30 and 07:30 every single day.
[00:57:00] Ben: Yeah, that's interesting. I was very strict on multiphysics sleeping for at least two years solid if not three. So I'd go to bed at 11, wake up 02:30 to 03:30, take two naps during the day and I'd do that every single day. I haven't done that a long time.
[00:57:18] Ken: It sounds like a lot of effort.
[00:57:20] Ben: It is a lot of effort. I'm they haven't done enough research to really know if it's good for you long term. Like if you have severe sleep deprivation, you are going to be at risk for Alzheimer's long term. But I don't know, maybe they'll come out with a cure for it. So it doesn't really matter.
[00:57:37] Ken: Yeah. Well, I just read this book called I think it's keep sharp by San ...gupta. And he brought up the community you were talking about of like cents in Japan and the purpose thing. Like word for, yeah.
So I was, I was grinning while you're talking about that, but that book is like the majority of it is brain health. And then the second half is about dementia and Alzheimer's and what we know now and what we're looking. and that was really fascinating to me. Hopefully it's not something I to worry about for at least another like 10, 15 years but hopefully, I mean, it. It seems like an area where artificial intelligence could play it tremendously Art role as well.
[00:58:24] Ben: Yeah. the joke there is once AI actually does get its hooks in. So when, when everyone's wearing glasses with a camera where it's, we're consuming all that experience, when we decide to share it for the betterment of humanity the joke is AI will tell everyone to start eating kale and only kale.
And so like when you lift up the Big Mac from McDonald's, your life expectancy will drop in real time and you'll put it down, you'll pick up the kale and you'll see it go to 200. And so you'll have this trade off. Do you just eat kale for the rest of your life and live for a long time.
[00:58:58] Ken: Or just drink athletic greens, right?
[00:59:01] Ben: Yeah. Yeah. it's kind of, it's unfortunate because there's so many, there's so many gut issues that people have. We're just not sharing that experience in real time, in a way, cuz you have a lot of opinions like, Oh, eat this, don't eat this. But to really do that study at scale it might take a country like China to actually pull it off because in us we're so concerned about privacy. I don't think anyone wants to be uploading pictures of their plates, every single meal, but I think China can pull that off. Maybe we'll learn something from it.
[00:59:33] Ken: Well, to that point something, something that's been really difficult for me in exploring and understanding is research related to aging. Right. So I read this book by Dr. Davidson Claire, it's called Lifespan. Why we age and why we don't have to. So that was one of the things that kicked off my recent kick. But the fascinating thing is that in humans, how can we run an aging study ethically? And how long will it take for it to be done?
If a lot of the anti-aging things we're doing, we have to start. In like, you know, thirties and forties, if people are living a long period of time, it's gonna take 40 years for us to understand if that research is valid or not. Yeah. I mean, that makes it really difficult for us to make progress on that specific challenge and problem in human related studies. And so there's this like weird paradox. Like wedon't want to age, but by the time we figure out if any of this stuff would be like truly meaningful most of us will be dead.
[01:00:36] Ben: Yeah, no, that, that's interesting. I think with like some of the ... extension research and some of the stuff they've done in rats, I wonder if you're gonna see more aggressive innovation towards end of life.
Cause if you're like 85 and you're like, man, like my dad didn't live this long, I'm willing to innovate. You're probably willing to take bigger risks, but if you are in your forties and someone's promising you like this gene editing you know, at solution then ethically that. That's, you know? Yeah. So that was my quick reaction to that.
You might see a much more aggressive innovation towards the end of life where people are like, ah, I've got, you know, I've got this thing or I'm I have outlived my parents and I doubt I will live, you know, another five years I'm willing to innovate. Yeah, but I guess the hope is when, when you're that age, that you're actually okay with closing the book on the Ben and Ken show and hopefully you've done some good that actually, this was interesting cuz when it comes to organizer, religion, or being a hardcore atheist, I feel like these two worlds have really come closer together.
And what I mean by that is an organizer glitch in which say there's eternal life, there's this concept of heaven. Like wedie and we go somewhere and there's a good or bad outcome depending on how you live. But I would argue that they're very close together because even if you are hardcore atheist, the good, the positivity that you do in this world, that could impact your friends.
It could impact your friends' children, your children. And in a way you could make the argument that you actually achieved internal life, even if it was like this infinite decay of posi positivity or positive impact. So does that make sense? Like if you do a big innovation, obviously people would celebrate you for recent generations, but 400 years from now, no one knows your name and, but you've still offered some impact, some impact for good somewhere.
And so that, it's interesting to kind of, to force those two worlds together that either camp you're in there is this idea of an infinite legacy or an infinite impact, even if, and if people have to know your name, then you haven't gotten over your ego.
[01:02:50] Ken: Yeah. I mean, that's fair. Maybe I should change the name on my podcast.
[01:02:54] Ben: When I die, people need to know my name.
[01:03:00] Ken: Yeah. You know, I think that when you strip everything away, right. Someone who's a hardcore atheist and someone who is very religious in some sense, they believe very strongly about the same topic area. Right? It's like something that's like, they're very focused on what happens after death, right?
And there's more similarities in people who have strong beliefs that something happens after death, whether it's nothing or whether you go to heaven or whether you're reincarnated or any of these things, then people that just don't care about it, right. And I think that, you know, I, while I'm sure those two groups would not like to be grouped together like that.
I mean, there is, there is something profound there. I mean, we're all humans are in this kind of giant struggle together for understanding for comprehension and the people that are trying to, to make sense of everything are, are all similar. We all share the same struggle of what our meaning is. And some people believe that like, If we really look at it, if an alien is coming in like our scenario before, like, would they view humans as individuals? Or would they look at us like one giant organism that's taking over the planet Earth, right.
[01:04:20] Ben: Yeah. Like a swarm, like a we're an we're ants and we have a queen.
[01:04:25] Ken: Yeah. I mean, like in some sense that is how, that is how we function. And we are in some sense also like a collective intelligence, which to me provides additional meaning in my life is that, Hey, like how do I continue this? How do I make the collective knowledge of the, of the world? or help people understand things better as a group? I find a lot of meaning in that.
[01:04:50] Ben: Yeah. That, that's an interesting perspective to imagine some alien, I'm gonna go jump on a red eye flight tomorrow and go to DC. So to imagine some alien analyze me, why is this little human ant going to DC?
But it's all just part of this, like societal, like song dance. We're just worker bees with our little incentives where humanity is sustained long term which is that that comparison has become more top of mind for me comparing humans to ants like this emergent property of intelligence.
it really, isn't a miracle that can be assigned to a single individual. You, the reason we have the intelligence we have is because of society. It's because of humanity. It's because you and I can share experiences. And if we're out forging for food and you get eaten by a bear, I will go back to the tribe and tell everyone about it.
And not only will they know about it, but their kids and their kids, and it'll become folklore. And now every bear is dead because unfortunately you, you were killed, but it it's all about this experience transfer through through language. So. It'd be fascinating to see what a human could become with no parenting with, with no language development, just, you know, you and 30 years in a cage with some, you know, oatmeal on the floor or what soil, what is that thing that the one thing that you can live on?
I think it's so I think that's correct. yeah. So what would happen to your brain? If we could rebirth you in a room with soil in a white room everything's white, and then we analyze your brain 30 years later. Would you be like the chicken raised indoors where you really don't have a comparison?
You're just kind of cuz there's no, like you sleep, you wake up, you sleep, you wake up. Like I'd be really curious. Like, do you even have the building blocks to be critical of your situation or are you just like this ameba that just like breathe.
[01:06:55] Ken: I mean, I don't think you would. I mean, you look at like defectors of North Korea and their experiences and they know nothing else, right.
Like, this is life is suffering to know. Yeah. For the most part. And they, they know nothing different. They don't know of freedoms. They don't know of these things. And these concepts, when they go to a country that is more free or just completely foreign and like, they couldn't conceptualize that they existed.
And they couldn't conceptualize that you can go into a grocery store and buy ramen noodles. Right. Like, like I think that we are, I wouldn't say completely blank slates, but if you have no human interaction, if your world is completely controlled, there is no, like, we don't doubt a lot of things about our world that if we, that, you know, children running around, they doubt, right. Like why is the sky blue? Why, you know, like those types of things. Yeah. And. Maybe, maybe they there's something to that. But it is a good question on that front.
[01:08:04] Ben: Well, I think the reverse is also true. I think our grandkids will know more about quantum mechanics by the time they're 10 than our leading researchers today. But that's because the education was, imagine like VR, where it's a game where what you are learning in the moment is different than me because your brain chemistry is different. And I feel like there's so many things we've been taught in college that were really confusing. And the teachers sucked, like when it came to like storytelling or earning my attention.
Like, I love that like the stereotype of the teacher yelling pay attention will earn my attention, earn my attention. I'll pay attention. Like the whole like, pay attention. Like that's just the admission that you're, you're, you're a bad teacher. But in their defense, maybe it's impossible to be a good teacher to 30 students. Maybe you can only be a good teacher, one on one and maybe humans lack the technology or the insight. Yeah, so that, that's something I'm helpful for is imagine our grandkids having like education is just a blast. Like they just can't wake up. They can't wait to wake up, put on the VR headset and have this experiential ride.
And they're all going in different directions. But by the time they're 20, they've essentially acquired five PhD equivalents of expertise. And now they're working on mRNA or like they're working on the next impossible breakthrough that only they can do because they have all of that expertise in their mind. And you and I lived in a world where we thought that was impossible. We didn't think it was possible that anyone could do that.
[01:09:40] Ken: I mean, I would love to see that. I also think that there are, I mean, there there's a lot of kids that are, you know, prodigies or geniuses quote unquote. Right? Yeah. And one of the things that I see very common.
With a lot of them as they specialized in something, right? They love physics. They love programming computers, and they were able to get into this situation where they had a completely specialized learning track, really good mentors, or once they saw some promise, people were willing to invest time to focus and improve the specific areas of interest that they had.
And this like reinforcement and like completely personalized learning is something that in my mind is revolutionary. You know, like if you know, if I had kids and I wanted them to be as successful as possible at something it'd be first, we have to get them to like it. But second, give them the exact amount of like feedback and the exact amount of challenge and those types of things to make it pervade over time.
and to make them truly grow in my mind. The education system was you described with 30 kids. You can't give individual attention to more than two or three people, right? Like the people who are the average student in every 30 person class, the like two people, three people, maybe that are the average student.
Or, it depends on like the distribution of the people in the class. Right. Maybe at best it's five people, right. That are the average of that 30 person class. They're getting the most benefit. Well, the people at the high end of the spectrum who would be incredible achievers and the low under the spectrum are completely underperforming.
They're not having a challenge that matches them at all. Yeah. And I will say one of the things I love about online education, any of these things is you match the speed of learning. You match the rate of learning, you match the challenge to your own unique situation. Yeah. And I'm very optimistic about those things.
[01:11:43] Ben: Right. I've become a huge fan in. I feel like everything can be explained at a fifth grade level. It's really hard to do that for some things like, even in AI, like some of these algorithms and the way we approach things, like, I feel like too often I'm reading a white paper or trying to understand something and it is so confusing, but then you'll stumble across to YouTuber or someone that'll explain it.
You're like, Wow. Like I feel like deep learning was that for me when deep learning was coming out, I think right. 2012 to 2014, like there wasn't a lot of code. If you get access to the code, it was confusing. You're very dependent on it. Very hard to innovate with it.
And it's funny that we have these dead languages now, like in deep learning, like people cafe, cafe, I hated cafe. That like the academic one is just, as soon as it existed, I thought this is terrible and this will die. And it's interesting. Cause you had a lot of people that held their ground.
They're like no cafes. Like that is what the researchers use, but you would declare a deep learning model in like 3000 lines of like a static config file, just like so dumb. And thankfully that died. But I really like SNO. I remember seeing a tutorial on YouTube and as soon as I saw it was like, Okay, deep learning makes perfect sense now.
Like, it just, it makes sense. I get it. I can innovate, but all these other frameworks were confused. The hell out of me. I just, I had no idea what I was looking at or what, how this made sense, so.
[01:13:10] Ken: I have a distinct memory of grad school, the first neural net that I coded. We did it in MATLAB.
[01:13:17] Ben: Oh yeah. Would've been, that would've been helpful for me cuz I had MATLAB background. Like I would've appreciated like the matrix math. what we're actually doing. A actually that's interesting cuz sometimes these tools can become, they can hold you back. So for the longest time, I think the first six years of my career, I used MATLAB for everything and I didn't realize it till later that that was a huge crutch and that this kind of gets on the vulnerability side because I was an expert.
Like I felt like I was a God at math, Matt lab, like you could ask for anything and I code it right up in front of you and you could sit over my shoulder and watch like while I'm coding as fast as I can. And it was later when I joined the hedge fund that I realized that it was actually a crutch. And that's when I transitioned the Python, same with going to Linux.
Like it, that's always hard for you to like rip up your roots and go from Windows to Linux or rip up your roots and go from MATLAB to Python or whatever. The next thing is, it's not fun and you try to resist it, but then once you've done it, you realize. Life is way better. This you're better. You can move faster.
But so that, and I think that gets to like vulnerability. No one wants to feel like an idiot again. And that's the thing that I talked to you about before is I think you should live your career where you're constantly finding out that you are an idiot, like on a regular basis.
[01:14:34] Ken: Well, you talked about how you build structure into that. And you're trying to do that every year, every five years, every quarter, whatever that might be, you know, what are the, some, what are some of the things that you've sort of tried that were new experiences that made you feel like an idiot again?
[01:14:52] Ben: I definitely felt like that with this fly fishing trip, just because the variables, like a lot of the people coming on the trip were coming from Seattle, DC and LA like very problematic, cuz the Trailhead starts at like 9,600 feet.
So being concerned about altitude acclimated, like yeah, like jackass pass, we're going over 11,000 feet. Like, and so there are just a lot of things coming together that were very chaotic, but also I had so many other things going on at work that this yeah, so that that's, it's interesting cuz sometimes you get so busy at work, especially when you're, you're dealing with like 10 different fronts.
Like I don't just do this. I do like I help out with partners and sales and marketing and like you've got all these avenues that you're working on. It's pretty easy for you to get yourself into a very bad situation, quickly a bad situation with consequences. And so yeah, so that was one, but I feel like.
I'd like to find myself constantly getting into projects that scare me. And I think that's something I'd encourage people to do. Like find projects that intimidate you and find projects that scare you. This kind of goes back to this theme. I was pushing a couple years ago called reckless commitment.
Cuz if I'm, if I'm a junior data scientist and I'm saying, I really hope that I can learn all this stuff. One of the things I was telling people four years ago was go and sign up to present at your local deep learning, meet up on reinforced learning or whatever. The next sexiest thing is like attention based or GPT 3.
And when you, I would tell junior people that it would, they they'd get this look of panic on their face or horror. And I'd say you go sign up to give that talk, you know, really sell or pitch into the organizer, why this would be such a great talk and something magical will happen three months from now.
When it's time for you to give the talk, you might hate yourself in the, in the process. You know, you're gonna have a lot of weekends where you don't wanna look like an idiot. When you get up there and you're gonna have people in the audience that are smarter than you on this topic something great will happen because you've essentially offloaded that commitment outside your control.
You're you're essentially screwed now, right? So you're, you're made up, is being advertised. You're screwed. You have to give this talk. And that's also true with these projects. Like if you could find yourself in projects where you've essentially pulled the rip cord, and the only thing you can do now is land.
I think that's good. I would encourage people to do that, but I obviously there will be scenarios where they crash land and they break a leg and like figuratively speaking, it's bad. Like they get fired because they face planted on a project. But at least I don't know. I think I have a different attitude.
Like you gotta, I hate to go big or go home. I need to come up with a different, I need to come up with a different saying than that.
[01:17:40] Ken: Well, something that I find myself constantly telling people is that. You should do projects before you're ready. Like, I get so many questions, you know, I make a lot of kind of earlier stage content.
It's like, when should I start my first project? When should I, you know, how, when will I feel that I'm ready to apply to the first job? And the answer is always before you feel that you're ready. And I think that inevitably that's something that I can't remember a speech that I gave or any of these things that I've done, that I felt like I was ready for.
[01:18:14] Ben: Yeah. Maybe that's where you'll get the most growth. You'll get the most growth if you're not ready. Cuz you'll same with like asking for a promotion. Like if you wait till you're ready, you've waited too long. Yeah. I think that's, I think that's really, really helpful for people. I hate working on things where there's a template.
Like obviously there's a lot of processes. There is a template, the best way to do this. This is how you answer your email. This is how you do all these things. But for the really big projects that I think about for the quarter. I don't wanna work on something where there's a template. I wanna work on something where, how are we gonna do this?
We have no idea how to do this. Like, that's what I wanna work on. We have no idea how to do this and that you see that in data science, innovation, when you're working on like new product features, like wehave no idea how we're gonna do this. There's not a template. That's great. So I that's, the stuff I celebrate is finding projects where you, you just have to figure it out.
There's not you, you can't go, mentors are really helpful, cuz you can talk to mentors in all parts of your career and they can give you advice on. Normally the advice is tied to a very specific problem. They're not gonna save you on your project. So if you're face planning on your project, they can't jump in and save your whole project.
But they, if you're sad because you're losing an account or you have to fire someone or you're getting fired or you know, issues in marriage, like there, there's so many things that go from career to personal that there's mentors in your life that have experienced that firsthand. And. Getting back to human experience. Why not leverage their mistakes to learn from them rather than you going in on your own?
[01:19:51] Ken: Yeah. I mean, I couldn't agree more. I think something that one of my mentors told me, especially around this domain, is that the fear or the in the inadequate feeling that you get, right. When you're approaching a problem, that's really big.
And it feels intimidating. Those aren't necessarily like warning signs that you shouldn't do it. Those are actually mechanisms that suggest you should do something, right. Like when we feel apprehensive about something, like weget jittery, we get the nerves. Like wecan interpret it either of those ways.
And if you're nervous about something to me, that means like it's a little bit of a risk. That means it probably fits a category of something you should try. Like if you're having those feelings, it is almost always a good thing. Like when you go and give a great speech, when you step on the first tee or when you have like a putt to win a golf tournament, right.
Like, I don't think there's anyone on the PJ tour that is not nervous, but that means they should hit that put and make it, not that they should chicken out and like panic, right. And just how you frame those scenarios can completely change how you live your life.
[01:21:10] Ben: Yeah. Well, the other thought I had there too, is it's so important for you to have these positive reinforcement, because if you're getting ready to go out on stage and the stage lights are there and you can really screw it up, like if you think that way you'll spy roll down and you'll screw it up.
But if you can really I feel like that's a constant challenge in life. Like how do you, how do you avoid the negativity? How do you avoid the doubt? How do you feel the, how do you avoid the imposter syndrome? Cause those are the things that will make you fail. And I think a big part of it's practice.
Like you, you have to give yourself those at bat moments. Like here's an example I used to, I used to hate moderating, which is really funny, like moderating a panel. I absolutely hated it. Introducing people, steering the questions, having to listen to the audience. It was very stressful for me. But like, if you do something enough, it, you just get, you know, it's kind of the miracle of the human brain.
You do whatever you do, you do it enough, you get a little bit better and you'll be a little bit less anxious. And so I think for people that are listening, if they are anxious about something like, Oh, I could never give a talk or I could never do that. Or I could never quit my job. Quit your job. and then the fourth time you quit your job.
It won't be as stressful. It won't be as upsetting, but the first time you quit your job, it is very stressful. Like go breathe into a paper bag and get ready for maybe you're gonna make a mistake. Like, I think I would kind of fight against safety. Like if you're trying to be really, really safe, you're not gonna, you're not gonna live a career. That's that stretches you. Right. Like, I think safety's a problem.
[01:23:00] Ken: Well, I don't know many safe ways to achieve your goals or like how you conventionally define safe. Right. I think like coinciding with achievement is risk. I mean, there's almost always a trade off. Well it, and it...
[01:23:15] Ben: Oh, sorry. Yeah. Finish your thought.
Oh yeah, no, I think. And the achievement is that much greater if, depending on the risk, like if there's no risk, there's no reward like that classic saying like even some of the back country runs, I like to do in the winter. Like the risks are significant. Like I'm climbing up Rocky, reg Rocky ledges, fall hazards left, and right.
And the reward is that much greater because there's no one else at the top, but like it, you know, it sounds really cheesy, but like that, that, that is generally true. Like it, if you're willing to do something, everyone else was is the reward really worth it. And I think this kind of goes into our novelty.
I like to kind of wonder if the sunset was always on, would it not be interesting? Would it not? Would you not take out your phone cuz it's actually boring to you? You know, like yeah, definitely fight for a unique outcome, a unique goal or. Yeah. It's interesting. Cause everyone wants a template on how to do like a career and I've become a big fan of there's just no template like it, like maybe changing jobs frequently or finding good mentors.
Don't be the smartest person in the room. Grow your network as quickly as you can. Your real network, like people that you know, that you can have coffee with that can give you advice, but even give you favors in return. Like that's I had no appreciation for that when I was at Intel and micron. But yeah, man well when are you coming to the 48? When are you gonna come to mainland?
[01:24:54] Ken: I actually have to go to ... Florida next week for work, you know, on the second for work. But I am gonna try and do something. I'm probably gonna try to dots to go ski. One of my buddies just moved to New Mexico. Okay. I was like, yeah, dude, I'll come hang out. I do want to go to Utah though, so.
[01:25:16] Ben: Yeah, let me know. That would be so much to do in the Utah outdoors. It's pretty epic.
[01:25:23] Ken: I know. So I honestly, as I'm looking at ed moving relatively soon in the next six to eight months Utah, New Mexico, Nevada and a couple other places are on the shortlist, so who knows?
[01:25:41] Ben: Well, they, who knows any other thoughts or questions you have, Ken? I think we had a pretty good run unless you, I always wanna share, like, I love sharing mistakes and regrets and I think, yeah, the more I think we can share, I think that's a general issue in with humanity is sometimes we're not willing to be as vulnerable as we should. And the more vulnerable our you are, the more you realize that other people have same, the same problems or issues that you have and the more you can help each other.
[01:26:12] Ken: Well, let's end, let's end on your biggest career regret. I think that that'll be a nice way to send it off and obviously the positive story around the career regret.
[01:26:23] Ben: Yeah. Biggest career regret. Man, that's a tough one because I think if I had to look, if we reviewed my career, a lot of the decisions are lucky. So like the hedge fund was awful. Like I, my wife, you know, we were probably gonna get divorced if I stayed there, but I think the hedge fund was absolutely required to, for me to land that job at higher view, like that experience said a lot to the hiring manager there, the CTO when I joined yeah, I don't really have regrets, like even the painful memories, like the really, really painful memories.
I see them as lessons. You know, friends, I had to fire contracts, I lost fights. I gotten with my co-founder, who's like my brother where we're swearing at each other and, you know, were in a bad spot. Like I, or even just stupid things I've done in my marriage where, you know, I've, you know, made people upset.
Like it's all just part of this development. Like I think the most important thing is to be aware when you are falling short and take in that, that criticism or we talked about like, even reading the comments, like if there's something constructive consume it, but don't let it consume. You take that criticism in and reflect on it.
That's true of everything in life, whether it's careers, marriage, relationships, you should always be open to self-reflection and betterment. And if you're not, then that's a problem that that would be my biggest regret is if I wasn't trying to be better every couple months. That would be a tragedy.
I think maybe to close on something specific, I did realize I was not complimenting people, just that I interacted with. And so that's a regret that I have there. Like I could have done a lot more. I could have, I could have been kinder in the past and I think I was too, too focused on myself. There you go. I got a clear, specific regret. I didn't wanna end with something fluffy that was like no regrets.
[01:28:31] Ken: Well, to be perfectly honest, I was teasing a little bit there. I hate that question because I live very much the same way. Like all of my past experiences they've shaped exactly who I am today, right. And if I had done something different, I might not be who I am. And I generally really like who I am. And so there's one of those things. I mean, other things that I've learned absolutely. But I did do a little bit dirty by asking about the regrets rather...
[01:28:58] Ben: no, that was the fun one. I like authenticity. I like people to lean in and I, and honestly it makes for being, you know, we've, I've got a podcast too on, more intelligent tomorrow where people want real conversations.
They don't want, they even want me to pitch you DataRobot and, or, you know, they don't want something that doesn't feel like a human conversation. They want, they want the novelty in the surprise where they don't know where the conversation's going, but also if there's walls to break through, you're willing to push me off balance. Like that's ideal. Makes good.
[01:29:32] Ken: They'll definitely get that in this one. The last thing is where can people learn more about you you know, hear your podcast, those types of things.
[01:29:40] Ben: Yeah. So Ben Taylor Data, you can find me on LinkedIn with that. You can also find me on Twitter. I tell everyone if you tweet at me, I'll find out a month later, I'm very active on LinkedIn.
I will share my email. So my email is just email@example.com. So if there's something specific to AI, I'm really not. I wouldn't recommend for people to reach out to me for career advice or I used to be very helpful there and I think I'm just kind of I'm in a different spot. I don't wanna close your podcast with, geez, Ben's an asshole.
I just, I feel like if they're reaching out, because they're hoping for a job to be very transparent, DataRobot does hire like principal level, like four year experience. Like if you're in that category, definitely reach out. But also if you need to reach out to me, I'm, that's a little confusing because I'm not hiring actively on the data science or engineering side.
That's a whole different department, but reach out to me on things around the future. AI consciousness, AI intersect with marketing. I love all things marketing. Or something not related to any of those things.
[01:30:54] Ken: I love it. Ben, this was such an awesome conversation. Thank you again for coming on the show and I can't wait till our next conversation.
[01:31:03] Ben: Thanks. I feel bad for like shutting down the junior data scientist. Everyone reach out to me. If I'm too busy, I'll tell you, but everyone reach out. I'm not trying to shut anyone down.
[01:31:12] Ken: There we go.