#78 - Three Breakthroughs: 2024 Election—Polling Is Dead, Prediction Markets Are In

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When I saw this, I was like, this is absurd.

That is Naren Ramaswamy, Senior Principal at Alumni Ventures.

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Hello, and welcome to this week's episode of Tech Optimist. I'm Mike Collins. I'm the founder and CEO of Alumni Ventures. I'm here with Naren Ramaswamy, who's one of our teammates here, one of our great young VCs, and we're here to talk about this week in technology and innovation and venture capital and what's on our mind, what are big announcements, what are big breakthroughs. And there was an election last night. And so I think we're going to talk about that because that impacts our ecosystem for sure in a big way. And without taking the political angle, our job as VCs is to hit the ball where it lies. And we have a Republican government for the next 4 years. And so I think we had done good scenario planning here at Alumni Ventures and were kind of prepared either way it was going to go. I think there are some takeaways. I think we can expect Generally good for kind of the venture ecosystem from an M&A perspective. I think there's likely to be a lot more activity on that front, which tends to be good to open up liquidity vectors for companies. I think there are certain segments that I think are going to have less have more runway and freedom to do things such as AI and blockchain. You know, the markets have ripped, frankly, of crypto, you know, the public equities. And I think it's really this sentiment, which may or may not prove to be true, which is— There is going to be more liberal perspectives when it comes to M&A and probably a loosening of some of the kind of regulation or headwinds that the industry has perceived it's experienced. All that is true, and we'll probably dig into all of that stuff more. It's still all pretty fresh, I think, for a lot of us. But I will tell you, here is my takeaway. My point number one is I think polling is dead and prediction markets are in. And so, you know, and I was, you know, frankly, a little skeptical of this that, you know, I kind of said, you know, Polls are not perfect, but they're directionally pretty close. And prediction markets are probably biased because it's all men. And, you know, are people really making an investment decision or is it just, you know, like betting on their home sport team? I think I've probably flipped on this, which is I think that they're That they're now big and deep enough that they are providing real informational information.

Okay, so now what we're going to do before Mike and Noreen really get into this conversation about how polling is dead and prediction markets and what they are, I'm going to sort of explain what prediction markets are compared to traditional polling. So they're both 2 distinct methods for forecasting election outcomes. So real-time responsiveness. Prediction markets can react swiftly to new information or events, providing real-life updates to forecasts. For example, when Hillary Clinton's email leak occurred in 2016, betting odds quickly adjusted to reflect this new information. In contrast, polls take time to collect and analyze the data, which can result in a lag between events and their reflection in polling numbers. So in prediction markets, participants are putting their own money at stake, which can be seen as a more genuine reflection of their beliefs about the outcome. Polls, on the other hand, do not involve any financial risk of respondents. Polls typically draw from a broader demographic, potentially offering a more representative view of the general public sentiment. And prediction markets are limited to those willing and able to place bets, which may not be as representative of the overall population. Polls can focus on specific regions or demographics, providing a more nuanced understanding of the election landscape, whereas prediction markets tend to offer a more aggregate view, although some do allow betting in state-level outcomes. So accuracy and reliability, right? The debate over which method is more accurate is, you know, still ongoing and everything. Like, some researchers suggest that prediction markets are at least as accurate as polls and quicker to incorporate new information. However, others argue that the polls provide more accurate snapshots until very close to the election. So there are some potential issues, um, with prediction markets, um, as far as like regulation and manipulation. So prediction markets are susceptible to manipulation, uh, especially when participation is limited. So large bets for individual actors can significantly shift the odds, while polls While not immune to manipulation, are generally less susceptible to this issue. Prediction markets face regulatory challenges in many jurisdictions, including the U.S., which can limit participation and potentially affect their accuracy. So as far as like complementary approaches, many experts suggest that both prediction markets and polls provide valuable insights and can be used in conjunction to improve election forecasting. Some models incorporate data from both sources along with economic indicators. They create more comprehensive forecasts. In conclusion, while predictive markets offer advantages in terms of real-time responsiveness and financial commitment, polls provide broader demographic representation and regional specificity. Both methods have their strengths and limitations, and their relative accuracy continues to be subject to debate and research in the field of election forecasting.

I think that that's a, I think that's a big deal. I think, you know, people vote in their self-interest, they vote with dollars, and if the market is liquid enough and deep enough and there's enough good information. I think there is enough data now that prediction markets, which are an innovation, and I was actually listening to an interview with the founder of one of the big ones, Kalshi, is that the name of it? Yeah,

it's actually a Sequoia-backed company. Friends at Sequoia had sort of seen this a few years ago and said, this is going to be Like polling, this is just one example of it, but prediction markets are, like you said, voting with money rather than just hearsay, which is how, you know, this is another example of technology underpinning what has been a speculative, hearsay, laborious manual job of a pollster, which is interesting to see that.

Yeah, I think there's a couple of other takeaways too, which is I just— you can Google it, but there's actually a pretty good interview with the founder that took place last week. And literally, their job for 3 years was to get this thing approved from regulators, right?

Yeah.

So I think there's the layer of this, which is, oh, prediction markets, did better than polls. I think he articulated and brought me around a lot to, you know, that these prediction markets are just a form of, you know, what goes on in the commodities market, right? Exactly. People are betting on weather, people are betting on, you know, the government supply reports. And it's the difference between gambling and hedging and where is the role in government there? There's a role. But I do think, again, putting on my opinion hat, I do think people should have the freedom with complete information and full disclosure to do with their money what they want. Within reason, right? So I thought he created a really compelling argument about his business and the value that it served. And yes, I mean, here's a perfect example is if I was a venture capital firm that was invested in some particular segment of the economy where I could be looking at different outcomes depending on how an election went, You know, should I not be able to hedge my position for the benefit of other stakeholders in that? I thought it was. I thought it was a pretty damn compelling argument. So again, I would encourage people to check out that interview. Not an AV portfolio company, but I think the whole idea of you know again technology innovation. Here's an entrepreneur who's been through huge ups and downs. Grindy, grindy to get this thing legal and approved. And, you know, is definitely having their day in the sun today for sure.

Yeah, definitely in the limelight now with, with the election. And yeah, I'm just fascinated by how this is another technology, ultimately piece of software that sort of come to the limelight. And to your point about It being another investment vehicle. You can think about some venture investors ultimately taking bets on companies. This is something similar and providing an avenue for folks to do that in an informed manner. Um, so yeah, fascinating.

It just broadens the spectrum of your hedgeable tools, right? That is like, you know, and, and one of the, one of the anecdotes he gave, which is Okay, if you live in the hurricane or tornado belt and you can't get insurance anymore, you can in a way hedge yourself on weather, right? Yeah. So again, you know, still pretty crude. Smart negatives. Not the best way to do it, but it's like, you know, these markets tend to be good. And again, obviously we need regulation, full disclosure, So I appreciate the fact that he did the pain of going through the process of doing this the right way. And a lot of times when you have markets and innovation, if you don't do it the right way, bad things happen and it kind of ruins the whole idea, right? Yeah, kind of thing. So it's like, again, this is I think this perception that VCs and entrepreneurs don't like regulation, I think, is wrong. And I think generally what we want and what entrepreneurs want are clear rules and a reasonable process for companies to meet those reasonable rules. That's all. And that grows it, that protects people. that grows the market, that allows innovators to be creative and to bring new things to society.

I mean, regulation has historically lagged behind technological progress. And here to see a founder actually put that in front and say, I'm going to be methodical and responsible about this is great to see.

100%. Okay, Noreen, what do you got?

Um, you know, it's a good segue, the point about regulation, I think, because I wanted to talk about brain-computer interfaces and brain chips. Uh, and we have obviously the FDA process in place, uh, to approve those. But I think this is fascinating because who would have— I mean, we've been thinking in our lifetime, yeah, you know, maybe we can put a chip in our brains and help, uh, understand it. But this is coming way sooner than we think. It's timely because, you know, people have been talking about Neuralink and this is Elon Musk's venture. But we actually have an AV portfolio company called Synchron, which has now finished the first of 2 major FDA clinical trials. And, you know, at the end of that, it's shown that the device itself was safe. And what's cool about this brain-computer interface is that It allows people with paralysis to access technology in a way that they couldn't before. You know, last time we talked about voice agents. Instead of keyboards, you use your voice. Yeah. But here is another way to access technology, do things like you can play games, you can scroll on an iPhone, interact with apps because, and this is not a super invasive surgery. This is the cool innovation is that they actually, it's a small minimally invasive surgery that goes into your neck. and allows you to interact with technology around you. And we live in such a tech-first world that the gap between folks that can access technology and those that can't is just widening. And here comes this cool technology that's— it's a matter of years that it's going to be in our hands. And this is not just for folks that are not able— that maybe are paralyzed and not able to access technology. It's also for— others who it just unlocks a different behavior. Yeah. You know, the same way that the iPhone introduced the full screen touchscreen and multi-touch, that was a new behavior. And brain-computer interfaces are going to provide another new behavior that's going to enhance the quality of life for, you know, at the beginning millions, but then eventually billions of people. This is going to be the future of how we interact with tech.

All right, to provide a little bit more context on brain-computer interfaces and, you know, brain chips that the guys are talking about, I found a video that Penn Medicine, uh, released about a month ago called Thought-Controlled Prosthetics: A Brain-Computer Interface Breakthrough. Now this video is really cool, um, like it's from, you know, some of the researchers from Penn Medicine, and it features, um, a few of the people from Precision Neuro, one of the portfolio companies within Alumni Ventures. Um, they actually were on episode 27 of The Tech Optimist if you want to go back and hear their story. Really cool story. But, um, this video along the lines of, you know, just computer brain interfaces, they really sort of talk about how their technology is directly implemented into these patients and like how it works and what this breakthrough means for the, you know, the sector of Uh, innovation technology and medicine and everything. So we're gonna play this video, um, now, you know, after we've heard a little bit from Mike and Naren. And so it, it brings like both ends to a point, right, where there's, um, the breakthroughs about, you know, like some possibilities of what this technology could really do. And then there's this video which actually provides a real-world example of what it's doing. Um, so I think marrying them both together really helps sort of round off this subject. So here's that video, and enjoy.

The way that we translate our thoughts into actions is absolutely mysterious. There's no doubt that the motor cortex is involved. There's also no doubt that it's not able to control your movements on its own. And how those things come together Is it, in some sense, the heart of free will?

My area of expertise with functional neurosurgery allows this unique window where we can now research the intricacies of hand and arm function so that ultimately we could drive computer interfaces that would help patients with paralysis.

No, no, so I'm saying for each, so minimum.

I had a profound experience while I was growing up. A friend of mine was paralyzed from a diving accident, and so I've always been thinking about this idea of restoring function with devices to give patients some independence back. Patients that we're recruiting for this research are undergoing deep brain stimulation for movement disorders. They have Parkinson's disease or tremor. We place a long-term electrode deep into the brain for their movement disorder that they're going to have as their therapy moving forward. And just before we wake them up, we place this electrode on the surface of the brain that's about 2 centimeters by 2 centimeters. And then we're going to start the experiment, okay? And it has 1,024 contacts.

It's hundreds of times Higher resolution than the next most readily available electrodes.

It's precision ready.

And it provides the world's highest resolution electrical picture of her motor cortex as she moves.

So we can see a very, very high-resolution window into the brain, and we've created special gloves that reconstruct the movements of the hand. And so in the OR, what we see is this full 3D reconstruction of their actual movement synchronized with the deep activity in the brain and the cortical surface activity. All are a window into how the behavior is being executed.

All right, so I'm going to ask you to reach out to this 3 times.

Each person is different from every other person, and until we study more people, we just don't know what that range of variation is going to be.

When you think about moving the hand or actually go to move the hand, different frequency bands carry different types of information related to movement. What we get is these really interesting time waveforms. You can see how the activity Activity on the brain surface evolves over time, so it's sort of like a musical orchestra where certain frequencies go away, certain frequencies come up. We see interesting patterns of spirals and waves traveling from one direction to the other. One of my colleagues likened it to watching the weather on television. So really, our job is to listen and know what patterns in the music relate to the behavior.

When we are successful in deploying these kinds of technologies, what it will demonstrate is that we understand the brain and its inner workings, and that's going to have foundational impact on who we think we are.

The technology that we're working on to provide thought-based control of external devices to people who are paralyzed, that has never been possible before. That's only been really dreamed of.

And so I imagine a world where, you know, folks with paralysis will be able to interact with things in their home. I imagine a world where we can take somebody who's an amputee and restore the movement with a prosthetic. But it's incredible that we're now at this cusp of new technologies that are going to facilitate us understanding how the brain works and potentially translating that to our patients.

The human brain, the interface between the human brain and silicon brains, just a super fascinating and rich investment area, right? Yeah. And I know we have several things, and a lot of times the first step is to deal with someone that has some health issue going on, you know, paralysis or brain disorder or tremors or something like that, that is this technology helps address. But for most of these companies, this is just a first step into just narrowing the gap between these biological computers and the communities. And, you know, it's sensors, human brains, computer brains, more sensors. Value equals value creation, right?

Yeah.

And so it just is a— it's a fascinating area. Again, also really cool stuff still going on in the area of CRISPR. I think there's, you know, which is going in, in, you know, technology to really get into the brain and snipping, you know, DNA problems. So that's kind of repairing software, if you will. So this whole, this whole class of area is just so exciting. And again, over the next 5 to 10 years, I think we're going to see, we're going to see just another area of just life-changing forever as some of these things come online. and give us ways to interact with other forms of intelligence and other sensors and other good things.

It's just another vector in the whole physical digital universe that's going to be created, you know, and at the intersection of biology and hardware and AI, you know, it's, yeah, it's quite exciting to see what's going to pan out over the next All right, let's

take a break. We'll be right back. Don't go anywhere.

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Yeah, and I think the final one I want to talk about, which is, you know, going to sound a little odd, but I do think it's an interesting story, which is— and I'm going to touch on this superficially, but people can Google it and Wikipedia it. But basically the story is, is there was an AI bot that was created to talk to another AI bot. And, and out of that came the idea between these 2 AI bots to create a meme and a meme coin that's associated with it.

Of

course. Which is, you know, which then used another bot to really start posting at huge volumes on X. And that the value created, you know, so this was the first to my knowledge. And then Marc Andreessen, you know, gave it, and this, you know, folks can look up kind of GOAT meme, right? I think, what's the exact name of it, Nouraine? Yeah, it's called— It's

like Goaty is Mad. Yeah, the token is called GOAT, G-O-A-T. And that was the first, uh, when I saw this, I was like, this is absurd, but are you kidding me?

Yeah.

Yeah. But, but no, go ahead, Mike. I'm curious to hear your, your, your perspective on after seeing this.

Wow. And then, you know, and Marc Andreessen, you know, kind of got involved to kind of, you know, grant them $50 grand to kind of run this experiment. And beyond the kind of meme, goofy, weird dimension of this, and oh, by the way, you know, the market cap of this coin, you know— Hundreds

of

millions. Hundreds of millions, I think now, actually. Right. So,

yeah,

again, I just think weird experiments are worth watching, right? I think there's a— I think that that's kind of thing one. Yeah. Like, this is odd. This is strange. You know, our job is to not dismiss it. You know, sometimes it is just that. This is just weirdness. The other times it's like the idea of AI Having discussions with other AI and coming up with things is interesting. And we are just— Yeah. This is like the first example of this, right? And there is going to be much, much more of this flywheel perpetuating stuff like AI writes code, code gets checked by another AI, gets suggestions by a third AI to re— you know, that these kind of loops can exist, I think is— and this is just like a really, really early weird example of it, but I think it points to where the world is heading. Now, I will give you a much more practical example of how this works in my life now, which is, you know, I use all the AI tools every day extensively, and different AI tools do different things better than others and are beginning to segment into areas of competence.

Yeah.

And so if I want to create a very simple workbot to do a very simple workflow for me, I'll use, I'll, I'll use another AI system to basically draft my initial concepts. And then I'll use them and then I'll take that very rough work and I'll give it to a different kind of AI system to elaborate on that idea.

Yeah. Critique it, share more ideas.

Critique it. And then I'm going to be— then I take that into a reasoning model and I'm saying, take this work and make it better. And then, you know, and I take that work and then I could take that work and, um, write a paper on it using a different tool. Or say I wanted to then take that paper and listen to it on my ride home from work, I'm going to use a different tool to do that. So The idea of AI scaffolding, the idea, you know, this will get me to this, to get me to this, to get me to this, I think is in this family of ideas and innovation going on. And I think today that having a family of AI systems that are kind of customized to do different things well. Yeah. You know, you and I were talking about this AI system kind of dropped by Stanford called Storm, right? Which is, you know, in the simplest terms and, you know, this probably undersells it, but it combines a really good kind of web crawler and an LLM. Right. And like, oh, you know, it hasn't, hasn't really been combined that way before. And that allows it to do certain things better than other AI systems. So, you know, you get Anthropic and Claude's really good at certain things and OpenAI and, you know, and Gemini from Google, you know, they're all— Yeah. There are choices being made in the design of them, it seems, that allow them to have strengths and weaknesses. Yeah. And I, you know, and I sit here and have tried to understand those and then orchestrate what I'm trying to achieve in the world and in my day by using the right tool for the right Job in the same way in the internet era you had to, you know, when do I use a Word document? When do I use PowerPoint or Excel?

Different applications.

When do I use email versus text? I mean, we all use all of these kind of internet-based tools for different things, right? And so it's just we're adding a new set of instruments, if you will, to do things. They just happen to be incredibly powerful. So

it's like having your own advisory board. Every person has their own advisory board for anything, right? Like, I mean, it's the, the, and going back to that crypto example, what really stood out to me was the ability, not generating the idea itself, that's fine. But the fact that it was able to market it, to really hype up the value of its own coin. Yeah. I mean, it's, this is, these are all manual tasks again, right? But it, it like, it makes a marketer's job easier. We're already seeing a lot of LinkedIn posts that you can tell somebody's drafted straight from ChatGPT. But yeah, you know, the productivity of that person has significantly increased as a result of that. So it's just, yeah, we're heading into that future. Where, you know, every person will have this advisory board and they'll spend maybe 10% of the time that they spent on some of these tasks that, you know, 5 years ago took up most of their day. And so this is going to be huge productivity enhancements across, and people are talking about, obviously, yeah, people are going to lose their jobs. The other side of it is everybody can do 10x more.

Yeah.

And the economy will increase in that Yeah. So it's that, that's the tech optimist way of looking at it, right? There's, there's not to diminish the concerns of automation, uh, but the reality is going to be somewhere in between that, in between the two of, you know, extreme efficiency and some short-term job loss. Uh, I think the reality is going to be somewhere in between those.

And I do think it is a fairly democratized tool. For white-collar workers, so you know I do think people have the choice to lean into this. And whatever job you're doing, I I say this to my board: is I think there are going to be two types of CEOs. There's going to be tech amplified, AI amplified CEOs and former. Right. So I think, and I think that applies to every job. So it's like you want to lean into these tools, get really good at them. You will be orders of magnitude more productive and an order of magnitude ahead of your non-AI enhanced competitor. But in that world, it is what we've also seen in our society over the last 10 or 20 years is winner take most. Markets become bigger and global, but it becomes a more segmented society. So I do think that on the net, it's great and it's good, but there's going to be local dislocations that are pretty profound. Again, lean in, people. All right, Naren, it was a good one. Big week. Say that every week, it seems. So yeah, good discussion. We'll do it again. Thank you.

Yep. Thanks, Mike. See

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