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Frida Polli, CEO and co-founder of pymetrics

April 18, 2023
Written By
April 18, 2023
Season 4, Episode 1
37:16
Written By

Kicking off the fourth season of the {Closed} Session podcast with a great topic and guest: Frida Polli, CEO and co-founder of pymetrics, which was recently acquired by Harver, joins us to talk about the critical role that technology and specifically AI and neuroscience can play in eliminating bias in hiring and beyond.

Guest, Frida Polli, CEO and co-founder of pymetrics (acquired recently by Harver)

Twitter: @fridapolli

Instagram: https://www.instagram.com/fridapolli/

LinkedIn: https://www.linkedin.com/in/frida-polli-phd-03a1855

Harver: https://www.linkedin.com/company/harver

Twitter: https://twitter.com/harverhrm

Transcript

Announcer:

Welcome to The Closed Session, How to Get Paid in SiliconValley with your host, Tom Chavez and Vivek Vaidya.

Vivek Vaidya:

Hello and welcome to season four of The Closed Sessionpodcast where we talk about company building, entrepreneurship, and we examinethe latest trends and insights in technology and business. The special episodeto start off season four, we are going to be discussing with a special guest,who I'm going to introduce to you momentarily, the critical role thattechnology and specifically AI and neuroscience can play in eliminating bias inhiring and beyond. Our guest today is Dr. Frida Polli. She's the chief datascience officer at Harver. Harver recently acquired her company, Pymetrics,which uses AI and neuroscience to help companies make fair and efficient hiringdecisions. Dr. Polli is a leading expert in the intersection of AI andbehavioral science with a PhD in neuroscience and an MBA from HarvardUniversity. We're thrilled to have her here today to share her insights andexperiences with us. Welcome, Frida.

Dr. Frida Polli:

Thank you. Thank you so much for that wonderfulintroduction. Glad to be here.

Vivek Vaidya:

Do you prefer Dr. Frida, Dr. Polli,-

Dr. Frida Polli:

No.

Vivek Vaidya:

... Frida? What do you-

Dr. Frida Polli:

No. Frida's fine. I will only make you call me Dr. Polliif I'm mad at you.

Vivek Vaidya:

Oh, okay. There we go. There we go. My wife also has a PhDin English literature and so far, I haven't had to call her Dr. Gupta.

Dr. Frida Polli:

There you go. Good.

Vivek Vaidya:

So I guess I'm doing something right.

Dr. Frida Polli:

Perfect.

Vivek Vaidya:

As we start, Frida, can you share your journey? What madeyou start-

Dr. Frida Polli:

Sure.

Vivek Vaidya:

... Pymetrics and then what led to the acquisition byHarver and everything else-

Dr. Frida Polli:

Sure.

Vivek Vaidya:

... that happened in between?

Dr. Frida Polli:

Yeah, happy to. I was a very content academicneuroscientist at Harvard and MIT for about a decade. Really enjoyed the sciencewe were doing. Ultimately realized that it didn't have as much real-worldapplication as I had initially hoped or thought it would, not for any fault ofthe particular lab I was working in, but just because cognitive neuroscienceunfortunately, it's just hard to translate the learnings into the clinic. So Ibecame a little bit disillusioned because I like to do as much as I like tolearn and so transitioned out of academia through the MBA program at Harvardand really didn't know what kind of entrepreneur I was going to be. I thought Iwas going to do something in the life sciences. Then as I sat there at HBS, Ihad a front row seat to recruiting for two years, because that's what MBAstudents do, and I just saw all of the flaws inherent in the process.

One of the biggest flaws is that people weren't reallyable to understand who a person really was from a what we call soft skillperspective. They had their hard skills, what their resume said, but theywanted to understand, is this person a team player or more of an individualcontributor? Are they motivated by intrinsic or extrinsic rewards? Are theyrisk-taking or more risk-averse? There was really no way to understand any ofthose things. People were resorting to what I call [inaudible 00:03:13] on resumesas well as coffee chats and recommendations from your section mates and justall these very archaic and not very scalable methods. The proverbial light bulbwas, oh, but we know how to measure all these traits in people using thesecognitive science techniques. So that's how the idea for Pymetrics came to be.

Then we were off to the races because HBS was a greattesting ground for a lot of our early tech. Then raised outside money in 2013,built the company, had tons of successes, worked with some incredible clients,many of whom just saw massive reduction in not only the traditional type ofbias that you might think, gender bias and racial bias, but inherent to a lotof our processes is socioeconomic bias. You only recruit from certain schools.You only recruit from certain employers, while unfortunately, those tend to beless socioeconomically diverse pools. So a lot of elimination of socioeconomicbias as well. And in conjunction with that, very strong gains in retention,employee performance, not to mention obviously efficiency. But I think that atthe end of the day, if you can improve retention and employee performance whilealso greatly improving all types of diversity, that's just a huge win.

So incredibly successful. I think the pandemic really wasa wrinkle that no one in HR expected that was a bit turbulent for many HRcompanies. So at that point we realized, oh, we're still subscale where we'dlike to be... We were fortunate that somebody saw the value in the technologyand really wanted to buy it so that they could offer it as part of a broaderplatform and that's why the acquisition in August of 2022 happened. But again,incredibly great ride that we had and incredible outcomes that we saw with thistechnology. So we're just very excited to continue to grow the platform withina broader company.

Vivek Vaidya:

Yeah. That was going to be my follow-up question, is youare continuing the build-out and growth of-

Dr. Frida Polli:

Absolutely.

Vivek Vaidya:

... the Pymetrics platform within Harver as well.

Dr. Frida Polli:

Absolutely, yeah.

Vivek Vaidya:

That's awesome. That's awesome. Congratulations.

Dr. Frida Polli:

Yeah, and now I'm their chief data science officer so Iget to do a lot more cool data science stuff, again, on a bigger scale, whichis always really exciting to work on new projects. So couldn't be happier. Ithink the HR field has changed so much in the 10 years that I was a part of itand was just very exciting to see that. I honestly think there's a tremendousamount more growth to come. We might get into this later. I think some of thechallenges that lie ahead of not only HR, but any field that is consideringusing artificial intelligence or algorithmic decision-making is how do you dealwith the concerns that the public has, that regulators have in terms of how canyou really know if something is lacking and biased, how do you test that, howdo you protect consumer privacy?

There's just all sorts of data privacy and bias issuesthat I think this nascent field is really going to have to address in a muchmore thorough way than it has been historically. I think those are some of thechallenges that I think we're going to see play out, that we've already seenplay out, but I think will continue to play out in the next five to 10 years orso.

Vivek Vaidya:

Yeah. I've had a couple of my own personal experienceswith bias in hiring and whatnot. One of the more interesting things for me,this happened actually in early 2019. 2019 was when there was a lot ofattention that started to get paid to bias in hiring, specifically gender biasand racial bias as well. We were trying to hire people as were so many othercompanies. I was using a platform that showed candidate profiles. You type inyour search. I'm looking for JavaScript ReactJS, whatever your technicalcriteria were, and out popped a list of candidates. Some of those candidateshad uploaded their photographs. Sometimes you can tell gender and/or notsocioeconomic, racial ethnicity, whatever by the names and whatnot. So therewas a checkbox at the top-right which said, eliminate bias, so remove bias.

Dr. Frida Polli:

Geez. Okay.

Vivek Vaidya:

When I checked it, it did not show me any names and itremoved people's pictures. Okay, that's progress. Then I said, okay, now let meuncheck it, right?

Dr. Frida Polli:

Right.

Vivek Vaidya:

Because I-

Dr. Frida Polli:

Oh, my God.

Vivek Vaidya:

... have some experience with mapping people's names totheir racial identities and whatnot.

Dr. Frida Polli:

Sure, sure.

Vivek Vaidya:

So now, this is where it got interesting, if I pick peopleat random, I got a biased result.

Dr. Frida Polli:

[inaudible 00:08:27], yeah.

Vivek Vaidya:

I had to look at at their names. I had to look at theirphotographs to actually create diversity in the candidate group.

Dr. Frida Polli:

Correct, yeah.

Vivek Vaidya:

That was for me a light bulb moment. Actually, one of thecompanies in our super{set} portfolio is a company called Eskalera, which usesdiversity, equity, and inclusion principles to measure things like employeeengagement. We've had Dane Holmes, who's the CEO of Eskalera, as one of ourguests. So I'm curious, how does your technology work? How does the Pymetricstechnology work in-

Dr. Frida Polli:

Sure.

Vivek Vaidya:

... one level more detail than you've described so far?

Dr. Frida Polli:

Yeah. Let me just start with your example. I think thatthe bias of all kinds, whether it's gender, socioeconomic, racial, disabilitybias, really can creep in at any stage in the funnel. I think what you're describingis that the sourcing, because at that point you were sourcing candidates, wasquite biased. If you did a random selection, you were more likely to get onegender or one ethnicity, right?

Vivek Vaidya:

Correct.

Dr. Frida Polli:

That is one type of bias. The next type can be inselection. Let's say you had no sourcing bias. Let's say you had equal numberof men and women, equal number of different ethnicities. A product that showsselection bias would be oversampling one gender, oversampling one ethnicity,which unfortunately can happen often for a variety of different reasons. I'llgive you some examples. Some of the more old-fashioned, but still quite in use,meaning, they're used by about 50% of companies, cognitive tests are quiteracially problematic in the sense that they use questions like, what is acul-de-sac as an test of IQ?

Well, I would put forth that asking someone what acul-de-sac is isn't measuring their IQ, it's measuring, again, theirsocioeconomic background. Because race and socioeconomic background are sotightly tied, some of these tests really have strong biases against candidatesof color such that for certain tests, some that are quite well-known, onlythree African Americans and four Latinos pass for every 10 Caucasians. That'sselection bias. That's saying, look, we're passing through a lot more of thiscategory than that category and that's just an example. The argument that thesetest providers will make, which is a spurious one, is like, oh, well, but thesecognitive tests predict performance so well that they're fine, which by theway, legally is true. So if you have this type of bias, but you can prove that,well, the candidates I picked performed better, they're legally defensible iswhat it's called.

We think that's a spurious argument because as I justmentioned to you, Pymetrics has had many examples of improving diversity of allkinds and also showing that people perform better. So we think that relying onthese older tools that have a tremendous amount of often racial bias is justnot fit for the times. We can move beyond that. And again, it's been shown withjust pure cognitive tests as well. What we do and the way we can show, approvebasically everything I've just said is we built a technique whereby it's an ensemblemethod. So instead of building an algorithm, we essentially build thousands ofalgorithms when we're doing the training. This is not rocket science. Anyonecan do this really. Then what we'll do is we'll plot these thousands ofalgorithms across two axes. One is lack of bias, essentially, where one is aperfect number and zero is what you're trying to avoid, and also accuracy, somemeasure of accuracy or model performance.

What we'll do is we'll just select from that upper rightquadrant where the algorithm is as close to one as possible in terms of genderand race ratios, and also as high-performing as possible by using that method,and then we'll further refine the algorithm. But that's not that hard to do.The method I just described is quite simple, but very few people are doingthis. What they're doing is they're building one algorithm and if thatalgorithm shows bias, oh, well, they're not doing a whole lot to fix that. Butbecause it's predictive of performance, they're saying, well, it's defensible.It's like, sure, but that's like saying, "Well, I developed this one drug.Yeah, it has terrible side effects, but it works. It's like, well, why don'tyou try?

But now with AI, we can test thousands of molecules andpick the drug that has the best performance and the best safety profile. Wehaven't really transitioned that model of thinking to these types ofalgorithmic building processes. So it's not hard. It's literally just liketesting the safety profile and the performance of a drug. At the same time, Iwould say the vast majority of companies in the HR space, at least the moretraditional ones, have not adopted these methods. I think society is the worstfor it.

Vivek Vaidya:

Yeah. The way you're describing it sounds like it's aclever application of algorithms and approaches that are already out there inthe assembly.

Dr. Frida Polli:

100%.

Vivek Vaidya:

It's the assembly that's the novel part that you did atPymetrics. A lot of-

Dr. Frida Polli:

Yeah. Look, the truth of the matter is I think some of thechallenges are less in the algorithms and more in the data.

Vivek Vaidya:

Yeah, I was going to do that.

Dr. Frida Polli:

Yeah. So basically, what we did at Pymetrics is wedeveloped a novel data source. I was telling you that part of the light bulbmoment was realizing you can measure risk tolerance or you can measure teambehavior. You can measure all these things. So that's where our data is noveland proprietary in the sense that we collected that data. That data is uniqueto us and we were very careful in using that data that we knew that it was verylinked to things that were important on the job, but that it also didn't havegender and ethnic bias in it, if that makes sense. So we shied away from anydata sources that we knew were more problematic. You couldn't do that entirely,but we tried to do that as much as possible.

The challenge with a lot of people using, let's say,existing data sets, let's say you get an existing dataset that has resume dataor experience data, whatever, that already has so many proxy variables builtin. Men and women have different experiences, so do different races. So thenwhen you try to use what we call our debiasing technique, this dualoptimization method, it's quite true that once you eliminate the "bias,"you can often get rid of the performance of the algorithm. But that's a baddata problem. It's not an algorithm problem.

Vivek Vaidya:

Correct.

Dr. Frida Polli:

It's like you've just been a bit lazy and you haven'treally tried to look at some of the patterns in your data and say, what typesof data should I be using that will help me solve this problem?

Vivek Vaidya:

100%.

Dr. Frida Polli:

Then you get all these silly comments in my opinion thatare like, oh, well. Literally, I just saw one on LinkedIn yesterday where it'slike, "Oh, well, yeah, you can have an algorithm that's unbiased, but youcan also have a random number generator too," meaning basically, itdoesn't predict everything.

Vivek Vaidya:

[inaudible 00:15:31], yeah.

Dr. Frida Polli:

Yeah. And you're like, no, that's just because that's beenyour experience because you've been using bad data and that's been yourexperience in trying to remove the bias, but that is not what de facto happensif you have a good data set and robust machine learning methods.

Vivek Vaidya:

Yeah, no, this discussion reminds me of a quote that I useoften these days, is more data beats better algorithms, but better data beatsmore data.

Dr. Frida Polli:

Totally, 100%.

Vivek Vaidya:

You see it in this whole movement with data-centric AIthese days that's going on.

Dr. Frida Polli:

Yeah.

Vivek Vaidya:

100% agree with you that the underlying data that you useand the amount of effort you put in to procure and source that data is what'sgoing to differentiate-

Dr. Frida Polli:

And clean that data. Look at the data and make sure thatyou don't have massive proxy variable problems. Again, I think unfortunately,it just comes down to, and again, you can find all sorts of reasons for whythis happens, but a lot of times I think when there's just this push for like,oh, grow the business, grow revenue, people are not very careful necessarily inwhat they're doing and they're just throwing everything at the wall and justseeing what works. That's when you get into these problems and then people sellthat tool or sell that algorithm, whatever, and then they get into thesesituations where they don't like what they're doing, but then they have to comeup with these arguments of like, oh, well, if you remove the bias, you're alsoremoving the signal. It's like, well, that wouldn't have been true if you'ddone things differently in the design process, but yes, where you are now, thatprobably is true. So again, it's just, unfortunately, not enough thinking goinginto what you're doing in the design process.

Vivek Vaidya:

Yeah, and I think now with GenAI and tools like ChatGPT, Ithink it's going to shine even an brighter light on these data issues becausethe data that you use to train these LMS and whatnot,-

Dr. Frida Polli:

100%.

Vivek Vaidya:

... and fine tune them also-

Dr. Frida Polli:

100%.

Vivek Vaidya:

... is going to result in differentiation.

Dr. Frida Polli:

100%, yeah. No, for sure. In the process of buildingPymetrics, we also were fairly helpful, I think, in passing the first law inthe nation actually that has any kind of oversight of AI. It goes by theAutomatic Employment Decision Tool, moniker, it's Local Law 144. New YorkCity's Bias Audit Law is probably what people know it by. The reason Imentioned that is because I think that it is, well, it's for another podcast,but it was quite a struggle to get the law implemented. It was a four-yearprocess. However, in this process, come to have met a lot of AI auditing firmsand my best quote from one of them recently was when the whole ChatGPT startedmaking the headlines, this one auditor that we know is like, "I'm going toconsider sheep farming because this space is getting so crazy." I just hadthis image of him off herding his sheep on some mountain where no one couldreach him.

Because I think a lot of people that are thinking throughthese things carefully are quite concerned about ChatGPT. You saw the openletter about ChatGPT and just all of the problems that this technology, verypowerful and exciting, no doubt, technology could unleash on the world. Soyes,-

Vivek Vaidya:

Actually,-

Dr. Frida Polli:

... back to your point.

Vivek Vaidya:

... since you brought it up,-

Dr. Frida Polli:

Sure.

Vivek Vaidya:

... as a practitioner, what are your views on the open letter?

Dr. Frida Polli:

I agree with it.

Vivek Vaidya:

Yeah?

Dr. Frida Polli:

Honestly. I do because again, maybe you think I'm anegative Nelly or whatever, but I just think that, again, I don't know how,maybe this is getting into controversial territory, but there's the wholeTimnit Gebru, Margaret Mitchell scandal that happened at Google and all of theflaws that they had pointed out in these large language models and these arethe same ones that we're adopting in ChatGPT. So just from that perspective, wealready know that there are issues in these large language models and so thatshould give us pause. But then we've seen, and there's been reporting on, therewas a great piece by Kevin Roose in the New York Times basically talking abouthow he, I don't know if you saw it, but he basically purposefully had a verylong discussion with one-

Vivek Vaidya:

I heard that.

Dr. Frida Polli:

... of these [inaudible 00:19:56], yeah. Exactly. The AIstarted telling him, "You should leave your wife. You're not happy."Then last week, I think it was reported that some person that was majorlydepressed had a chat with the ChatGPT, this was in Belgium, that told him thatyes, he was concerned about climate change and the AI basically told him,"Yes. Well, the world would be better off without another human," andthe guy-

Vivek Vaidya:

Oh, wow.

Dr. Frida Polli:

... killed himself. Now,-

Vivek Vaidya:

I didn't read that.

Dr. Frida Polli:

... again, we can't be like, well, it was the AI's fault.But at the end of the day, this technology is very powerful, especially onhumans that are already susceptible. Kevin Roose is not going to leave his wifebecause the ChatGPT tells him to, but unfortunately, people who are invulnerable places are much more susceptible. So just think from thatperspective, we don't have enough guardrails, I don't think, to protect veryvulnerable humans. So that's one concern I have. Then the whole deep fake issueis another just, I think, quagmire that we are not ready for. We already haveso many people that believe in QAnon without deep fakes. Can you imagine thecraziness that will be unleashed in terms of deep fakes misinformation? So frommy perspective, I think it's an incredibly exciting technology and I don'tthink it's ready for prime time. That's my perspective. We should have somekind of a moratorium. We should have some kind of whatever. Again, I'm an AIenthusiast in general. I'm a technologist. I'm a technophile, but I do agreewith the open letter that I think more guardrails, I think, are warranted.

Vivek Vaidya:

Yeah. I think people tend to take these binary views. Ifyou say anything in support of a thing like the open letter, then oh, you're atechnophobe. You don't believe in AI. You're hindering innovation and all ofthat. Whereas what you're calling for really is balance.

Dr. Frida Polli:

Right.

Vivek Vaidya:

Right?

Dr. Frida Polli:

Yeah.

Vivek Vaidya:

And you're not saying that technology-

Dr. Frida Polli:

Exactly.

Vivek Vaidya:

... should not be used, but it should be used withguardrails and the right checks and balances.

Dr. Frida Polli:

Correct.

Vivek Vaidya:

My wife and I were big espionage, mystery, these kinds ofbuffs.

Dr. Frida Polli:

Yes.

Vivek Vaidya:

There's a show on NBCUniversal on Peacock called TheCapture.

Dr. Frida Polli:

Yeah. Okay.

Vivek Vaidya:

To your point about deep fakes, the second season ofCapture has just this mind-blowing concept where they show you what's possibleand it's scary.

Dr. Frida Polli:

Yeah, it's very scary. And again, we're going all over theplace, but just in the last week, there was the news of the leaked classifieddocuments, people wondering if they're true. The whole point is we are in suchan era of mistrust and disinformation that I think unfortunately, this type oftechnology will only allow that to be possible on steroids. If there was ever atime that we already have way too much of that, I think that's why we need tobe even more cautious when democracy, one could argue, is being certainlyimperiled by some of the disinformation and things like that.

Vivek Vaidya:

What role do you think entrepreneurs like us and startupscan play in combating this?

Dr. Frida Polli:

I'll just speak from my own experience.

Vivek Vaidya:

Yeah.

Dr. Frida Polli:

I think the challenge that entrepreneurs have in myopinion is that I think a lot of entrepreneurs want to "do the rightthing." I think a lot of us want to design things the right way, put onguardrails. I think the challenge is that the venture model is what it is. Theventure model doesn't say grow moderately and don't break things. The venturemodel says grow fast and break things or move fast and break things. Again,it's just because, well, that's their model. That's how they make money. It'snot that they're bad people, it's just that their model of how they make moneyis not necessarily always compatible with designing products in a way that ismore careful. So I think that's the tension, honestly, just truthfully. I don'thave a magic answer as to how we solve for that, but I think that there's aninherent tension in the funding model wanting one thing and the entrepreneurbeing pushed in that direction without necessarily thinking that's the rightway to go.

Vivek Vaidya:

But don't you think that-

Dr. Frida Polli:

That's my perspective.

Vivek Vaidya:

Yeah. One of the things that we say at super{set}, you cando well by doing good. One of the ways that we think you can thread this needleis by creating what we call ethical tech. We're sponsors of this project calledthe Ethical Tech Project and privacy and responsibly gathered data, responsibledata practices, responsible data stewardship, I think is part of the solution,at least from our perspective. How do you think that plays out?

Dr. Frida Polli:

Well, I couldn't agree more, I just don't think that'snecessarily the norm. I think what you're describing, you guys have clearlybeen very careful, thoughtful, and that's amazing. I don't disagree with any ofthat. I'm just saying that from my experience and experience of others, I don'tthink that every single investor that is investing in technology necessarilyhas that kind of lens. That's all I'm trying to say. So therefore, when theoption presents itself to maybe remove breaks, or not necessarily even breakson growth, but just breaks on doing different things, trying out differentproducts, that you might otherwise caution against, I think that the decisionisn't always made to put on those breaks. Again, it's not just tech investing.I think it's just in general, right?

Vivek Vaidya:

Yeah.

Dr. Frida Polli:

There is this conflict and I think it can be carefullythreaded. We obviously did that at Pymetrics, but I think it's not always theeasiest path-

Vivek Vaidya:

Sure.

Dr. Frida Polli:

... and I think that it can present challenges.

Vivek Vaidya:

Like you, we're also optimists, right?

Dr. Frida Polli:

Yeah. I'm a total optimist.

Vivek Vaidya:

Yeah. No, I think-

Dr. Frida Polli:

Again, you guys have that very specific belief system,design philosophy, whatever you want to call it. I just don't think that everysingle person that builds tech or designs tech or invests in tech has that forbetter or worse, whatever reason that is, and therefore, I don't think everyonebenefits from that. Does that make sense?

Vivek Vaidya:

Yeah. That's true. That's true. So then one question,related one, do you see the regulatory landscape changing in the coming yearsas this unfolds?

Dr. Frida Polli:

I do.

Vivek Vaidya:

Yeah. In what ways?

Dr. Frida Polli:

Yes, I do. Well, it's already changing. I talked to youabout New York City's Bias Audit Law. There's like three or four other billsunderway in California, New Jersey, in DC, and that's just the US. Then youhave the EU AI Act, which most people think is going to go into effect eitherthis year or next year, which will be much more comprehensive and sweeping.Canada is either passing or has passed some laws. It's just happeningeverywhere. I think part of it is, I don't want to say it's a reaction, but itis a reaction to... So what we saw, what I saw in the 10 years of buildingPymetrics is that on the one hand, and I was shouting from the rooftops, AI isamazing, it can debias human processes, I was the biggest advocate and I wasconstantly being asked for, well, prove it.

Vivek Vaidya:

Yeah.

Dr. Frida Polli:

Honestly, there isn't a way to prove it unless there aresome standards. You can't prove something because if I prove it this way andyou prove it that way and nobody has to adhere to any kind of standards, thenit's like, oh, what's my word against yours? So people just become veryskeptical, remain skeptical.

Vivek Vaidya:

Right.

Dr. Frida Polli:

I think it's just like climate change. Any kind ofreporting standard structure in order for folks to gain confidence in thesesystems, that's my long held belief, there has to be some slight level ofoversight. Doesn't mean you have to start talking about making things legal orillegal. I think we start with mandated reporting, which is the lightest touchoversight. You start with that just to even get a sense of the ground truths.Because so many conversations I would have with people or employers orjournalists or whatever would be like, well, I'd say, "Oh, well, Pymetricsis less biased." "Well, how do you know?" And I'm like,"Well, how do you know that the process you're describing is unbiased andyou don't even know what the ground truth is?" So if you don't even knowwhat the ground truth is, it's hard to then say something is better or worse.

Just as a historical precedent, before we started havingpollution standards in the US, they did literally a 10-year study of airquality, and that's a little bit like what we need in, I think, the algorithmicspace, which is we have zero idea as to how these things perform, what bias isin them. So we need to at least have the mechanism in place where we caninterrogate, investigate, report on so that we can gain a sense for what isground truth. Once we know what ground truth is, then we can start talkingabout, okay, does this need to be changed? Is this okay? Because right nowwe're literally just flying this massive airline jet blind.

Vivek Vaidya:

Right. Yeah.

Dr. Frida Polli:

So that's my perspective is that we just need tounderstand ground truth and the best way to do that is just collect data andget some reporting on it.

Vivek Vaidya:

Yeah. It's fascinating. As you were saying, giving theexample of air pollution, there are so many of these examples and precedentsyou can find in other industries where these-

Dr. Frida Polli:

Completely.

Vivek Vaidya:

... similar problems have been studied and approaches havebeen defined. It's time to apply those same frameworks to AI at large.

Dr. Frida Polli:

Totally. But I think the problem is, and again, withoutnaming names, I think that we saw this in New York. Big tech companies came inand lobbied extensively and I mean extensively to not have this bill pass. Andliterally, this bill just asked for reporting. We're not making things illegal.We're literally just saying, "Hey, report on the levels of gender andethnic bias that are present in your algorithms," and there was so muchlobbying and so much pushback. We saw this happening with bird's eye view. It'sjust very unfortunate. The whole mantra is like, oh, we're self-regulating.We're fine. We'll do it ourselves, which by the way, has been the mantra of anyindustry that has known that some of its products has had potentially somenegative externalities and didn't want any kind of oversight.

Again, it's a very tried-and-true playbook. I think it'sjust very unfortunate because as a technophile and as somebody that lovestechnology and wants technology to flourish, I think this is setting up for abattle between people that fear basically the concern and the fear and the negativeviewpoints of technology to just continue to increase when you have folks onthe other side resisting any effort at light oversight and understanding ofwhat their technology does. So I think it's a poor dynamic to be setting up.

Vivek Vaidya:

Yeah, and I think it just exacerbates the are you with usor against us kind of dynamic when-

Dr. Frida Polli:

Completely, yeah.

Vivek Vaidya:

... there are so many people just advocating for there tobe these standards and these fair practices and whatnot, whereas the otherparties are saying, "No, not going to do it." Then if you challengethem, then you're just against it all, right?

Dr. Frida Polli:

Completely. Yeah, you're anti-business. You'reanti-capitalism. You're all sorts of things.

Vivek Vaidya:

Yeah.

Dr. Frida Polli:

Literally, we would have these accusations thrown at us,and I'm like I've been running a for-profit enterprise for the last-

Vivek Vaidya:

Right, exactly.

Dr. Frida Polli:

... 10 years. None of those things are true. I don't evenknow picketing person with a sign that's not interested in making money. That'snot true at all. There have been lots of examples of this. There was the FairCredit Reporting Act in the 1970s or '80s, I can't remember, that basicallydecided who was on the hook if credit cards were used in a fraudulent manner.That changed, that allowed for the credit card industry to flourishtremendously because prior to that, everyone was like, "Well, I don'tknow. Maybe I'm on the hook. Maybe the bank's on the hook." Who knows,right?

Vivek Vaidya:

Right.

Dr. Frida Polli:

Once that was put to bed, then the industry was able toflourish, and that's a perfect example where regulation actually helped theindustry flourish. There's many examples like that and I think it's just veryunfortunate, and sorry, now we're getting on a totally different soapbox, butthat any type of regulation is viewed as anti-business because-

Vivek Vaidya:

Support.

Dr. Frida Polli:

... that's not what the facts purport to. Again, it's backto these black and white ways of thinking that are unfortunate.

Vivek Vaidya:

Looking forward and just trying to look optimisticallynow, as you think about the future, and you think about AI, and look, as youwere saying, these technologies are going to flourish,-

Dr. Frida Polli:

100%. As they should.

Vivek Vaidya:

... yeah, and they are going to impact how we changework,-

Dr. Frida Polli:

Yeah, 100%.

Vivek Vaidya:

... what skills do you think will be in high demand as AIbecomes more and more prevalent? How can individuals, entrepreneurs, employeesprepare themselves for these changes that AI is going to bring?

Dr. Frida Polli:

Honestly, I think the biggest skill, and I wouldn't callit a skill, is adaptability. Because I think life is literally constantly,constantly changing and I think the ability to adapt is the most critical"skill" that we can have.

Vivek Vaidya:

Yeah. People are predicting that, oh, all jobs are goingto go away and all of that. That's like two-

Dr. Frida Polli:

No.

Vivek Vaidya:

I don't know.

Dr. Frida Polli:

No.

Vivek Vaidya:

Yeah.

Dr. Frida Polli:

We've been saying that for, I don't know, honestly, almostit feels like 10 years and look at where we are now. There aren't enoughworkers to do the jobs that are needed. We're in a situation where, quitefrankly, if some machines were to take some of those jobs, that would be abenefit-

Vivek Vaidya:

Benefit, yeah.

Dr. Frida Polli:

... because we cannot find people to do those jobs. Ithink what's unfortunate, and I was at Davos a couple of years ago and saw Eric[inaudible 00:34:03] speak to this, which I thought was very telling,basically, AI and machine learning, the technologies are there. What is lackingis the will right now to implement some of those for fear of some of thesenightmare scenarios coming to be, all jobs going away. But unfortunately, thelosses in productivity that are occurring because we're not fully adoptingthese new technologies are not trivial. I think there's just a lot ofresistance. There's a lot of gum in the wheels, whatever the expression is,that is hindering this progress. Again, I'm just going to go back to the factthat I think a lot of this is stemming from fear of the technology, concernsaround how it could be used poorly.

The more technologists are continuing to want to hide whatthey're doing and obfuscate, the less we're going to be able to remove and workon this resistance that exists in the public and the media. So it's just likeit feeds on itself. The public is scared, but then the tech companies don'twant to say anything and so we're at these loggerheads where unfortunately,we're not able to use this technology in the way that we would like. The reasonthat I became interested in regulation is because I want the technology toexpand, not because I want it to contract. Does that make sense?

Vivek Vaidya:

Yeah.

Dr. Frida Polli:

I don't think we're going to be able to expand thetechnology as well as we would like to without-

Vivek Vaidya:

Some form of regulation.

Dr. Frida Polli:

... some meaningful oversight, yeah,-

Vivek Vaidya:

Yeah. The final question for you-

Dr. Frida Polli:

... or oversight.

Vivek Vaidya:

Yeah. Final question for you. What advice would you give abudding entrepreneur right now?

Dr. Frida Polli:

Honestly, I think no matter how the ups and downs ofentrepreneurship, it's still the best job you can have. My husband looks at melike I'm crazy because he is like, "Oh, my God. That was so much work. Yousure you want to do that again?" I was like, "I'm ready." Idon't have the next idea I want to pursue and I have a job right now, but yeah,I think it's the best way that you can have to be employed, honestly. I wouldjust say go forth and prosper. Because I think entrepreneurs are the kind ofcrazy, optimistic dreamers that we absolutely need more of in the world. Andyes, they're going to fuck things up, excuse my French, sometimes,-

Vivek Vaidya:

It's good.

Dr. Frida Polli:

... but for the most part, they're really going to... Ithink they honestly, many times, exhibit the best of what humanity has tooffer, which is optimism, trying to solve a problem, doing the impossibleagainst all odds. I don't know. I think it's a great way to earn a living.

Vivek Vaidya:

Yeah. There you go. You heard it, folks. It's the best jobyou could have and go forth and-

Dr. Frida Polli:

It is.

Vivek Vaidya:

... prosper.

Dr. Frida Polli:

Go forth and prosper.

Vivek Vaidya:

Sage advice from a fellow entrepreneur. Frida, thank youso much for joining me here today on the first episode of season four of TheClosed Session.

Dr. Frida Polli:

Absolutely. I'm so excited to be your first guest, sothank you for having me.

Vivek Vaidya:

That's a wrap for this episode and we'll see you soon.

 

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Marketing in the Age of AI with Rex Briggs

How is AI steering the future of marketing strategy? With the convergence of AI and marketing tactics, Rex Briggs paints a compelling picture of what's possible: AI agents that revolutionize user interactions, and generative techniques that craft persuasive content. Drawing from his deep expertise in marketing measurement, Rex joins Tom Chavez and Vivek Vaidya to explore the cutting-edge of AI-driven marketing strategies. Listen for insights on harnessing AI's potential in modern marketing.

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Tom Chavez in Huffpost Personal for Hispanic Heritage Month

Writing in the Huffington Post: "My Mom Sent Me And My 4 Siblings To Harvard. Here's The 1 Thing I Tell People About Success."

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Developer tools that are worth their while: KEDA and Boundary in action

Running cloud platforms efficiently while keeping them secure can be challenging. In this blog post, learn how two of super{set}’s portfolio companies, MarkovML and Kapstan, are leveraging tools like KEDA for event-driven scale and Boundary for access management to remove friction for developers. Get insights into real-world use cases about optimizing resource usage and security without compromising productivity.

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Watch: Sandeep Bhandari Fireside Chat

Sandeep Bhandari, Former Chief Strategy Officer and Chief Risk Officer at buy now, pay later (BNPL) company Affirm, joins Vivek Vaidya, Founding General Partner of super{set}, in conversation.

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Spotlight Series: Andrew Marshak, Co-founder of Headlamp Health

The {Closed} Session Spotlight Series showcases a different co-founder from the super{set} portfolio every episode. Up now: Andrew Marshak is Co-founder and Head of Product at Headlamp Health (Headlamp.com), a healthtech company bringing greater precision to mental health care.

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Philosophy, Data, and AI Ethics with NYT Best-selling Author + Data Scientist Seth Stephens-Davidowitz

From unpacking Google search patterns to understanding the philosophical underpinnings of big data, Seth Stephens-Davidowitz offers a unique lens. As the NYT Best-selling author of “Everybody Lies” and a renowned data scientist, he delves into the ways data mirrors societal nuances and the vast implications for tech and its intertwining with everyday life.

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Forbes: 5 Startup Studio Misconceptions

It's still early for the startup studio asset class - and we hear misconceptions about the studio model every day, ranging from the basic confusion of accelerators versus studios to downright incorrect assumptions on our deep commitment to the build-out of every company. Read Tom Chavez' latest in Forbes.

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Ringside Tales from Serial Startup Champion Omar Tawakol

Like Rocky Balboa and Apollo Creed, the fiercest competitors can sometimes become friends. Omar Tawakol is a prime example. As the founder and CEO of BlueKai, he went head-to-head with Tom, Vivek, and the 'Krux mafia' for dominance in the Data Management Platform arena. A serial entrepreneur with roots in New York and Egypt, Omar eventually steered BlueKai to a successful acquisition by Oracle before creating Voicea, which Cisco acquired. Today, he's pioneering a new venture called Rembrand (rembrand.com), which innovates in product placement through generative fusion AI.

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Spotlight Series: Lindsey Meyl, Co-founder of RevAmp

The {Closed} Session Spotlight Series showcases a different co-founder from the super{set} portfolio in every episode. Today's guest is Lindsey Meyl, Co-founder at RevAmp (rev-amp.ai), a "Datadog for RevOps" platform that offers observability across the revenue engine, monitoring performance, flagging when something is amiss, and determining the root cause of how to fix it.

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Why Proprietary Data Is the Linchpin of AI Disruption

Read Vivek Vaidya's latest in CDO Magazine and learn why in this new AI landscape, those who harness the potential of proprietary data and foster a culture of collaboration will lead the way—those who don't risk obsolescence.

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MedCity News: It’s Time for the Tech Revolution to Come to Mental Health Diagnoses

Headlamp Health co-founder Andrew Marshak writes in the MedCity News that "We need to take inspiration from the progress in oncology over the last few decades and challenge ourselves to adapt its successful playbook to mental illness. It’s time for precision psychiatry."

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What Consumers Think of AI and Their Privacy

Everyone’s talking about AI - so The Ethical Tech Project decided to listen. Joining forces with programmatic privacy and data+AI governance platform Ketch, The Ethical Tech Project surveyed a representative sample of 2,500 U.S. consumers and asked them about AI, the companies leveraging AI, and their sentiment and expectations around AI and privacy. On the latest episode of The {Closed} Session, get an inside look at the survey results in a deep-dive conversation with the team at The Ethical Tech Project.

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Why the AI Revolution Will Be Data-Centric

Pankaj Rajan, co-founder of MarkovML, joins super{set} Chief Commercial Officer Jon Suarez-Davis (jsd) to discuss the role of data in gaining a competitive advantage in the AI revolution. Learn the difference between optimizing models and optimizing data in machine learning applications, and why effective collaboration will make or break the next-gen AI applications being created in businesses.

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Tech Crunch: Boutique startup studio super{set} gets another $90 million to co-found data and AI companies

Startup studio super{set} has a fresh exit under its belt with the sale of marketing company Habu to LiveRamp for $200 million in January. Now, super{set} is adding another $90 million to its coffers as it doubles down on its strategy of building enterprise startups.

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Good Ideas, Good Luck

Coming up with new company ideas is easy: we take the day off, go to the park, and let the thoughts arrive like butterflies. Maybe we grab a coconut from that guy for a little buzz. While this describes a pleasant day in San Francisco, it couldn’t be further from the truth of what we do at super{set}. If only we could pull great ideas out of thin air. Unfortunately, it just doesn’t work that way.

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Developer tools that are worth their while: KEDA and Boundary in action

Running cloud platforms efficiently while keeping them secure can be challenging. In this blog post, learn how two of super{set}’s portfolio companies, MarkovML and Kapstan, are leveraging tools like KEDA for event-driven scale and Boundary for access management to remove friction for developers. Get insights into real-world use cases about optimizing resource usage and security without compromising productivity.

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Jamming with Habu’s Matt Kilmartin on Partnership Strategy

Discover how Habu, a trailblazer in data clean room technology, utilizes strategic partnerships with giants like Microsoft Azure, Google Cloud, and AWS to expand its market reach and foster the potential of an emerging category. Learn from CEO Matt Kilmartin's insights on how collaboration is the secret sauce that brings innovation to life.

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Why Proprietary Data Is the Linchpin of AI Disruption

Read Vivek Vaidya's latest in CDO Magazine and learn why in this new AI landscape, those who harness the potential of proprietary data and foster a culture of collaboration will lead the way—those who don't risk obsolescence.

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Why I'm Joining super{set} as Chief Commercial Officer

Announcing Jon Suarez-Davis (jsd) as super{set}’s Chief Commercial Officer: jsd tells us in his own words why he's joining super{set}

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Infrastructure Headaches - Where’s the Tylenol?

Head of Infrastructure at Ketch, and Kapstan Advisor, Anton Winter explains a few of the infrastructure and DevOps headaches he encounters every day.

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Why the AI Revolution Will Be Data-Centric

Pankaj Rajan, co-founder of MarkovML, joins super{set} Chief Commercial Officer Jon Suarez-Davis (jsd) to discuss the role of data in gaining a competitive advantage in the AI revolution. Learn the difference between optimizing models and optimizing data in machine learning applications, and why effective collaboration will make or break the next-gen AI applications being created in businesses.

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Why Head of Product is Our First Co-Founder

At super{set}, we stand side-by-side and pick up the shovel with our co-founders. Our first outside co-founder at a super{set} company is usually a Head of Product. Let’s unpack each portion of that title....

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Data Eats the World

The wheel. Electricity. The automobile. These are technologies that had a disproportionate impact on the merits of their first practical use-case; but beyond that, because they enabled so much in terms of subsequent innovation, economic historians call them “general-purpose technologies” or GPTs...

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7 Ways to Turn an Internship Into a Job at a Startup

Chris Fellowes, super{set} interned turned full time employee at super{set} portfolio company Kapstan, gives his 7 recommendations for how to turn an internship into a job at a startup.

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MedCity News: It’s Time for the Tech Revolution to Come to Mental Health Diagnoses

Headlamp Health co-founder Andrew Marshak writes in the MedCity News that "We need to take inspiration from the progress in oncology over the last few decades and challenge ourselves to adapt its successful playbook to mental illness. It’s time for precision psychiatry."

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Watch: Sandeep Bhandari Fireside Chat

Sandeep Bhandari, Former Chief Strategy Officer and Chief Risk Officer at buy now, pay later (BNPL) company Affirm, joins Vivek Vaidya, Founding General Partner of super{set}, in conversation.

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Navigating the Startup Journey from Launch to Finish Line

Are you a launcher, or a finisher? The balance of conviction, a guiding vision, and the right team to execute it all make the difference between entrepreneurial success and failure. Tom Chavez delves into his journey as a first-time CEO and the invaluable guidance he received from a key mentor.

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Q&A with Accel Founder Arthur Patterson

Arthur Patterson, founder of venture capital firm Accel, sits down for a fireside chat with super{set} founding partner Tom Chavez as part of our biweekly super{set} Community Call. Arthur and Tom cover venture investing, company-building, and even some personal stories from their history together.

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Horizontal Scaling at super{summit}

Vivek gives us the rundown on what the hive is buzzing about after super{summit} 2023: how to 'horizontally scale' yourself.

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An Intro to Product-Led Growth from MarkovML

Want to grow your product organically? This blog post breaks down understanding costs, setting up starter plans, and pricing premium features using MarkovML as an example. Learn how to engage new users and encourage upgrades, enhancing user experience and fueling growth through actionable insights.

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The Information: "TikTok Is Not the Enemy"

Tom writes a nuanced take on the TikTok controversy and outlines ethical data principles that will restore people’s sense of trust and offer them true control over how and when they grant permission for use of their data.

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boombox.io Raises $7M to Build Out Creator Platform for Music Makers

super{set} startup studio portfolio company’s seed funding round was led by Forerunner Ventures with participation from Ulu Ventures Raise will enable boombox.io to accelerate product development on the way to becoming the winning creator platform for musicians globally

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Four Tips for a Distributed Workforce

This month we pass the mic to Sagar Gaur, Software Engineer at super{set} MLOps company MarkovML, who shares with us his tips for working within a global startup with teams in San Francisco and Bengaluru, India

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Why I'm Co-founding @ super{set}

Pankaj Rajan, co-founder at MarkovML, describes his Big Tech and startup experience and his journey to starting a company at super{set}.

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From Suitcases to Startups: Why Immigrants Innovate

How are immigrants like entrepreneurs? Peter Wang of Ketch arrived in the U.S. at age 7 with two suitcases and a box. Read his story in the latest "Pass The Mic."

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Pivots and Possibilities

Discover how lessons from law enforcement shape a thriving tech career. Ketch Sr. Business Development Representative Brenda Flores shares a bold career pivot in our latest "Pass the Mic" story.

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The super{set} Entrepreneurial Guild

Has someone looking to make a key hire ever told you that they are after “coachability”? Take a look at the Google ngram for “coachability” — off like a rocket ship since the Dot Com bubble, and it’s not even a real word! Coaching is everywhere in Silicon Valley...

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Tech Crunch: Answering AI’s biggest questions requires an interdisciplinary approach

Tom Chavez, writing in TechCrunch, calls for new approaches to the problems of Ethical AI: "We have to build a more responsible future where companies are trusted stewards of people’s data and where AI-driven innovation is synonymous with good. In the past, legal teams carried the water on issues like privacy, but the brightest among them recognize they can’t solve problems of ethical data use in the age of AI by themselves."

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Forbes: Why A Collaborative Approach Trumps "Lone Genius" In Company-Building

Off the heels of super{set}'s first exit - the acquisition of data collaboration company Habu by LiveRamp for $200 Million - Tom Chavez writes how the super{set} approach to collaboration in company building leads to successful outcomes.

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Building Tech on a Moving Regulatory Target

In an interview with Ketch co-founder Max Anderson, the focus is on data privacy laws and AI's role. Anderson discusses the global privacy landscape, highlighting Ketch's approach to helping businesses navigate regulations. The conversation also emphasizes data dignity and Ketch's unique role in the AI revolution.

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We don’t critique, we found and build.

The super{set} studio model for early-stage venture It is still early days for the startup studio model. We know this because at super{set} we still get questions from experienced operators and investors. One investor that we’ve known for years recently asked us: “you have a fund — aren’t you just a venture capital firm with a different label?”

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Building Fast, Scaling Globally

Harshil Vyas joined the super{set} Hive (i.e., portfolio companies community) in March 2023 as Co-Founder of Kapstan and employee number one in India. We jumped on a Zoom recently to talk about accelerated timelines, globally distributed workforces, and what is unique about the super{set} model.

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super{set} Celebrates First Exit: LiveRamp to Acquire Data Collaboration Software Startup Habu for $200M

LiveRamp Enters Into Definitive Agreement to Acquire Habu, Reinforcing super{set}'s Unique Company Building Model of Founding, Funding, and Scaling Data+AI Businesses

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How To Avoid Observability MELTdown

o11y - What is it? Why is it important? What are the tools you need? More importantly - how can you adopt an observability mindset? Habu Software Architect Siddharth Sharma reports from his session at super{summit} 2022.

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Why Headlamp Health is Bringing Precision to Mental Health

Co-founder of Headlamp Health, Andrew Marshak, describes the frustratingly ambiguous state of mental health diagnoses - and the path forward for making mental health a precision science.

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Not Just On Veterans Day

This post was written by Ketch Developer Advocate, Ryan Overton, as part of our #PassTheMic series.

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The Information: The People OpenAI Should Consider for Its New Board

Tom Chavez writes in The Information that "OpenAI’s board needs a data ethicist, a philosopher of mind, a neuroscientist, a computer scientist with interdisciplinary expertise and a political strategist."

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Why I Left Google To Co-found with super{set}

Gal Vered of Checksum explains his rationale for leaving Google to co-found a super{set} company.

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Tom Chavez in Huffpost Personal for Hispanic Heritage Month

Writing in the Huffington Post: "My Mom Sent Me And My 4 Siblings To Harvard. Here's The 1 Thing I Tell People About Success."

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Diamonds in the Rough

Obsessive intensity. Pack animal nature. Homegrown hero vibes. Unyielding grit. A chip on the shoulder. That's who we look for to join exceptional teams.

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Overheard @ super{summit}

Vivek Vaidya's takeaways from the inaugural super{summit}

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Redefining Customer Experience in Data-Driven Tech Startups

Ted Flanagan, Chief Customer Officer at super{set}-founded Habu, sat down with Jon Suarez-Davis (jsd) to provide insights into how Habu's strategies in customer experience set it apart in the data collaboration market. Learn how customer experience strategies helped Habu land a $200 million after being acquired by LiveRamp in January 2024.

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super{set} Fund II: $90 million to intensify our serial focus on data+ai company building

Announcing super{set} Fund II

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From Chords, to Code, to Chords Again: The Story Behind Boombox.io

super{set} founding general partner Tom Chavez wasn’t always set on a life of engineering and entrepreneurship – music was his first love. For a time, he was determined to make a career out of it. With boombox.io, Tom has combined the best of both worlds into a product that inspires and delights both the engineer and the musician.

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VCs Write Investment Memos, We Write Solution Memos

When a VC decides to invest in a company, they write up a document called the “Investment Memo” to convince their partners that the decision is sound. This document is a thorough analysis of the startup...

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Detecting Software Bugs with AI

Gal Vered is co-founder and Head of Product at Checksum (checksum.ai), an innovative company that provides end-to-end test automation that leverages AI to test every corner of an app. He sat down with Jon Suarez-Davis (jsd) to discuss the exciting problem that Checksum is solving with AI and what Gal likes best about working in super{set}'s startup studio model.

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High-Velocity Personal Growth

What's the price you put on personal growth? In his most recent note to founders, super{set} Founding General Partner Vivek Vaidya outlines 7 points of advice for startup interviews and negotiations. Vivek explains his compensation philosophy and the balance between cash and the investment in personal and career growth a startup can bring. Here’s the mindset you need to reach your zenith at a startup.

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Forbes: Why The Biden-Xi Talks Should Put A Microscope On San Francisco

The prettifying and securing of downtown San Francisco, where super{set} is headquartered, should be the norm - not just for special state visits from the world's dictators. Here are 3 things the city of San Francisco should be doing all year round to make the city better to live, work, and invest in. Read Tom Chavez' latest in Forbes.

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How Engineers Should Talk to Customers with Empathy

Do you get an uneasy feeling anytime you get added to a customer call? Do you ever struggle to respond to a frustrated customer? Peter Wang, Product lead at Ketch, discusses how customer feedback can help drive product development, and how engineers can use customer insights to create better products. Learn best practices for collecting and interpreting customer feedback.

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From Watsonville To The Moon

This post was written by Habu software engineer, Martín Vargas-Vega, as part of our new #PassTheMic series.

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When Inference Meets Engineering

Othmane Rifki, Principal Applied Scientist at super{set} company Spectrum Labs, reports from the session he led at super{summit} 2022: "When Inference Meets Engineering." Using super{set} companies as examples, Othmane reveals the 3 ways that data science can benefit from engineering workflows to deliver business value.

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Hold Fast: Game-Changing Wisdom from Seamus Blackley

Creator of the XBox and serial entrepreneur Seamus Blackley joined Tom Chavez on stage at the 2023 super{summit} in New Orleans, Louisiana, for a free-ranging conversation covering the intersection of creativity and technology, recovering back from setbacks to reach new heights, and a pragmatic reflection on the role of fear and regret in entrepreneurship.

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Podcast: Tom Chavez on How AI Startups Can Show Us What’s Next in Marketing

Tom Chavez joins the "Decoding AI for Marketing" podcast published by MMA Global and hosted by well-respected international marketing & AI experts Greg Stuart (CEO, Author, Investor, Speaker) and Rex Briggs (Founder/CEO, Inventor, Author, Speaker).

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Understanding The AI “Alignment Problem”

Vivek Vaidya recaps his conversation with AI researcher and author of "The Alignment Problem" Brian Christian at the 2023 super{summit}.

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The RevOps Bowtie Data Problem

Go-to-market has entered a new operating environment. Enter: RevOps. We dig into the next solution space for super{set}, analyzing the paradigm shift in GTM and the data challenges a new class of company must solve.

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CalMatters: Why visa reforms benefit not just California’s tech sector but the economy overall

Vivek Vaidya writes that America needs more H-1B workers. Common sense reforms to the program will even the playing field for startups, not Big Tech, to bring innovative talent to American's shores.

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How Boombox Nurtures Customer Collaboration for Success

In a conversation with boombox's co-founder India Lossman, the discussion pivots to the art of fostering customer collaboration in music creation. Lossman unveils how artist-driven feedback shapes boombox's innovative platform, with a glimpse into AI's empowering potential. Understand the synergy between technology and user insights as they redefine the independent music landscape.

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Why CTOs Should Care About Gross Margins, Cost-to-Serve, and Product Management

Why should a tech exec care about profit and loss? Aren’t our jobs to make the product great, and someone else can figure out how to make the numbers add up? That was my attitude for a long time until I finally appreciated the significance of gross margins for SaaS businesses during the early part of my tenure as the CTO of Krux.

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Lessons from the Startup Circus

super{set} Technical Lead and resident front-end engineering expert Sagar Jhobalia recaps lessons from participating in multiple product and team build-outs in our startup studio. Based on a decade of experience, Sagar emphasizes the importance of assembling the right engineering team, setting expectations, and strategically planning MVPs for early wins in the fast-paced startup environment.

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super{set}’s Spectrum Detoxifies The Online Space

We are living in a time of extraordinary concern about the negative consequences of online platforms and social media. We worry about the damage interactive technologies cause to society; about the impact to our mental health; and about the way that these platforms and their practices play to our most destructive impulses. Too often, the experiences we have online serve only to polarize, divide, and amplify the worst of human nature.

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ActiveFence Acquires super{set} Company Spectrum Labs

ActiveFence, the leading technology solution for Trust and Safety intelligence, management and content moderation, today announced its successful acquisition of Spectrum Labs, a pioneer in text-based Contextual AI Content Moderation.

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Forbes: 5 Startup Studio Misconceptions

It's still early for the startup studio asset class - and we hear misconceptions about the studio model every day, ranging from the basic confusion of accelerators versus studios to downright incorrect assumptions on our deep commitment to the build-out of every company. Read Tom Chavez' latest in Forbes.

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The Era of Easy $ Is Over

The era of easy money - or at least, easy returns for VCs - is over. Tom Chavez is calling for VCs to show up in-person at August board meetings, get off the sidelines, and start adding real value and hands-on support for founders.

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Silicon Valley’s Greatest Untapped Resource: Moms

This post was written by MarkovML Co-Founder, Lindsey Meyl, as part of our #PassTheMic series.

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The Four Types of Startup Opportunities

In our last post, we discussed how data is the new general-purpose technology and that is why at super{set} we form data-driven companies from scratch. But new technologies are a promise, not a sudden phase change.

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The Balancing Act For Women in Tech

This post was written by Ketch Sales Director, Sheridan Rice, as part of our #PassTheMic series.

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Spectrum Co-founders Launch Nurdle AI

Justin Davis and Josh Newman, Co-founders of Spectrum Labs (acquired) launch Nurdle to get AI into production faster, cheaper & easier.

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How I Learned to Stop Optimizing and Love the Startup Ride

Reflections after a summer as an engineering intern at super{set}

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Too Dumb to Quit

The decision to start a company – or to join an early stage one – is an act of the gut. On good days, I see it as a quasi-spiritual commitment. On bad days, I see it as sheer irrationality. Whichever it is, you’ll be happier if you acknowledge and calmly accept the lunacy of it all...

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The Product Mindset for Engineers

Ever find yourself scratching your head about product management decisions? Join India Lossman, co-founder of boombox.io, as she unpacks the product mindset for engineers. Unravel the art of synergy between PMs and engineers and delve into strategies to enhance collaboration and craft products that users will adore.

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Jeremy Klein on Leading super{set}'s Data-Driven $90 Million Fund II

Jeremy Klein is a general partner at super{set}. Jeremy helped build super{set} from day one alongside Tom Chavez and Vivek Vaidya, designing super{set}’s structure, recruiting co-founders, and laying the plans for a scalable buildout. super{set} recently announced the closing of its $90 million Fund II. He sat down with Jon Suarez-Davis (jsd) to provide insights into the strategic timing and vision behind launching Fund II, his professional journey from a legal expert to an integral part of super{set}'s fabric, and how his unique background and approach have been instrumental in building super{set} and recruiting top-tier co-founders.

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Former Salesforce SVP of Marketing Strategy and Innovation Jon Suarez-Davis “JSD” Appointed Chief Commercial Officer at super{set}

The Move Accelerates the Rapidly Growing Startup Studio’s Mission to Lead the Next Generation of AI and Data-Driven Market Innovation and Success

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Founder and Father: A Balancing Act

Making It Work With Young Kids & Young Companies

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