#34 - Three Breakthroughs: AI Spot Mass Shooters, Quantum Material Breakthrough, and CAR-T Show Promise With Brain Tumors

Can AI stop a mass shooting?

Huh.

Let's find out.

The solution is not easy to these issues, but, you know, here is a company that is trying to do something about it, which is, again, you set up these cameras, they're portable.

And what they were doing is they were replacing specific atoms with 57 other elements.

But just literally profound Results like, can't find the tumor kind of thing.

Hello everyone, welcome back to this episode of The Tech Optimist 3 Breakthroughs. Some housekeeping to get out of the way. Some of the voices that you'll hear today are Mike Collins, the founder and CEO here at Alumni Ventures, Matt Caspari, a managing partner here at Alumni Ventures, and of course myself, Sam Herrick, your guide, editor, and tech note writer for the show. Let's get into it. In a world captivated by criticism, it's easy to overlook the groundbreaking technologies shaping our future. Let's shine a light on innovators who are propelling us forward. As the most active venture capital firm in the US, we have an exceptional view of tech's real-world impact. Join us as we explore celebrate, and contribute to the stories of those creating tomorrow. Welcome to The Tech Optimist. As a reminder, The Tech Optimist podcast is for informational purposes only. It is not personalized advice, and it is not an offer to buy or sell securities. For additional important details, please see the text description accompanying this episode.

You have one today.

Yeah. Okay.

Okay.

I had a backup just in case.

Anything else going on before we dig into it?

I'm calling in from Paris, so yeah, that's going on.

You're out there for the Olympics? Are you competing?

Yeah, my wife's been out here for work, so yeah, I came out with the kids. So we've got a couple Olympics events and seeing friends. So yeah, pretty, pretty awesome trip.

You know, I tried to. I'm.

I.

They're going to LA, and I'm go to my wife. I go, "Oh, we should go." And she was like, she couldn't have been more negative. She was like, "Oh, the crowds! The you don't get to see shit." This is.

You want to watch it?

You want to watch it? You want to watch it on television?

Yeah, this is the emptiest I've ever seen Paris. So it's very interesting. I think no one's shown up. I think the opening ceremony is not for a few days, but the people in the restaurants are kind of freaking out. Like, they've shut down the whole city. No one's here.

Everybody wanted to rent their apartment probably to like people that—

Yeah, maybe the crowds are about to come, but as of right now, the city's weirdly empty.

File that away.

File that away. I have a feeling LA may be pretty different, but yeah, yeah, yeah.

I, again, I'm not sure how much of it was LA versus going somewhere cooler, or yeah, just generally.

I, I've never liked—

I think she wants this view it like— I agree that like Watching the bicyclists go by. Yeah, you know, kind of thing.

I don't know. Yeah, I've never been. My wife's been to two Olympics.

Yeah, I've never been either, and it's kind of like sounds kind of interesting to me.

Yeah, we're gonna see the U.S. men's play France in soccer. So I've never been to a big soccer game, so that'll be cool.

Well, that'll be fun. Yeah, buy a kit.

Yeah, yeah, yeah, yeah.

All right, let's get into it. All right, welcome to. Alumni Ventures and our Tech Optimist podcast. This is our 3 Breakthroughs show where we get together and talk about interesting innovations, cool companies, scientific breakthroughs that we think can change the world. So welcome to this week's show. I think, Matt, I go first this week, right?

Sounds good. Yes.

All right. So I've got 2. The first one I'm going to talk about is in the context of— and I'm going to give a little preamble—

AI.

Okay. There's been a lot of buzz lately and people writing articles kind of taking the counter-trade, which is, you know, hundreds of billions of dollars going and building into this infrastructure and You know, there's no revenue and—

Yeah, when do we get our ROI?

When is our ROI? So, you know, on the surface, it's a reasonable question. I think, I think all the analysis I've seen has really underestimated the cost savings that customers get, meaning it's one thing if you can If you're a provider and you get revenue, and I'm gonna pick Microsoft, so I can sell cloud services and I can get revenue.

Yep.

I think the other side of this is, you know, we're looking at companies that are trading at, you know, 30 times revenue. And if they can, and, Not only Microsoft, but their customers, if they can spend a dollar of AI and save a dollar of labor, you know, if it's a $250,000 a year employee that you don't need to hire, and you have to put a 30 multiple on that. So that's, you know, $6 million, $7 million per employee, of every employee that you don't have to hire because you're using AI. I haven't seen enough of that kind of analysis in—

so yeah, no, agreed. And just the increase in productivity you can get by shifting someone's time to higher output activities. And some of that takes time. A lot of these tools are still pretty new. So yeah, I think there's more to come.

So I wanted to jump— use that as a backdrop to drop into my first point, which is a very specific use of AI that I think solves a real problem. And so, this is a company called ZeroEyes. And what they do is they use a combination of cameras and AIs and learning to identify mass shooting prospects. So, they scan, you go to a public event, like a political rally. You set up these cameras around and you—

Seems obvious, like, that we should have this kind of technology.

Well, this is, this is obviously very timely, and the reason I chose it, which is we had, you know, a really tragic example again of, um, you know, uh, a young male with a, you know, military-grade gun going into a public space and creating death and havoc. And the solution is not easy to these issues, but— You know, here is a company that is trying to do something about it, which is, again, you set up these cameras, they're portable, they, uh, have the ability to detect, uh, you know, these weapons, uh, before and better than people that are, you know, wandering around. And oh, by the way, this example from the Trump rally, there was— The Secret Service was there. There was a, you know, there were people up on rooftops and they missed it and it was too late and all of this kind of stuff. This isn't a, uh, a music festival at a county fair where there may be a couple of local police people wandering around.

So, um, we've talked about drones in the past. I mean, so far, as far as I know, it hasn't come out that There were drones used in that situation, which I think surprised a lot of people. Does this company use drones or do you know where they're located?

Yeah, no, this company uses cameras on basically portable telephone poles.

Okay.

So, you go in and you create a perimeter and you set up these things, you drive them in, they feed them. You know, again, the details of how they feed that into a communications vector, 'cause it's one thing for the AI to identify it, then you need to get it to people that are gonna do something about it in a very timely fashion. Um, I think the main, main point I'm trying to make is here's a company— this was, uh, started by a formal— former Navy SEAL kind of after the Parkland High School shooting. Um, you know, it looks at an incredible number of images. It does it in a way that is super intelligent. And the demo is really impressive and company's taking off, obviously. So again, you know, problems, solutions, that's how we're wired to look at things. Yeah, great tech solutions. But this is a case where, you know, you're talking about the power of, you know, cheaper cameras, drone technology, you mentioned, Matt, AI systems, state-of-the-art communications. You know, you got to stay ahead of this stuff. So I just thought it was a very interesting and obviously very timely example.

Yeah, it's a great one.

I mean, wow. I looked into this company, ZeroEyes. I'm gonna, of course, like my MO, I'm gonna play their sort of, uh, mantra video on their technology and how it works. Um, but first I wanted to add a little bit more context as well to the point that Mike made earlier about, you know, AI and if companies are using them, like, you know, putting more money into AI rather than actual labor and staffing and kind of what those numbers look like. So Deloitte University Press published a report recently called How Much Time and Money Can AI Save Government? Highly recommend a read. The article is really fascinating. Cognitive technologies could free up hundreds of millions of public sector worker hours. Pretty much this article exemplifies how, you know, the government sector might use AI within their everyday operations. So I'm going to read a few segments of it. All kinds of institutions today run on data, and that means endless staff hours spent inputting, processing, and communicating. The work needs to get done, so someone has to spend that time pecking away at a keyboard.

Right.

But who or what that someone is, is what is in question here. So I'm gonna read the first segment of their introduction. The promise of reducing or even eliminating all that drudge work is one reason why many managers are enthusiastic about new applications based on artificial intelligence. Finally, staff resources could be freed up to do real work with people having time to focus on creative projects and deal directly with clients and customers. So again, we have this argument where AI is used as a tool. It's not used as a replacement for jobs or labor hours. AI is with companies like this designed to take the positions within these systems that just need a brain, right? When that actual brain from a human. Is more creative and design orientated and more social, right? And so then that social smart human can be put to other work that is more important and more enthusiastic towards the company's mission. So this is what Mike was saying at the first part, whereas when we talk about Zero Eyes in this company, a human brain doesn't have enough time to process like that is a threat. This person is holding a threat within a vulnerable community or a vulnerable building. Let's get response going, right? So then it's this— ZeroEyes is this automatic system that's placed within already existing security cameras in, or like Mike was saying, in those portable ones, those portable telephone poles that you can put around large-scale events and all that fun stuff. So ZeroEyes then is doing that brain work That a human may have trouble doing when that human could be used otherwise. And hopefully, you know, this other brain, this AI brain that is sorting through hundreds of thousands of images from the security cameras, can identify the threat. So without further ado, I'll stop yapping. Um, here is a video from ZeroWise, and then we're gonna hop into a quick break, and then we'll hop right back in. All right, enjoy.

ZeroEyes is a team of former Navy SEALs and military special operations veterans teamed up with elite technologists with a mission to save lives. We use your existing video cameras coupled with our artificial intelligence gun detection to prevent threats rather than react to them. There is no better purpose right now and no more difficult problem to solve than mass shootings.

We go over the existing security cameras at a building, so on the interior and exterior, at entrances, exits, choke points, bottlenecks inside the hallways. So when a shooter walks up and they take out a weapon, ZeroEye system will pick that weapon up. And our military-trained operation experts verify every detection before sending out alerts to local staff, security, And the local 911 center to get the alert to first responders.

It takes about 3 seconds from the time a gun enters the frame of a camera to the time an alert is sent.

So now they know what the shooter looks like, what type of weapon they have.

We have an armed subject in the Southwest Hall.

How many there are, and what was their last known location.

First responders on scene. have access to this information before shots are fired. That will allow them to go directly to the shooter and prevent more violence from occurring.

Drop your weapon now!

Drop the gun!

Drop the gun!

So we can really decrease response times and save lives.

Turn around!

So we're going to stop threats at first sight, not first shot.

Mass shootings are devastating. Current alternatives are reactive. We need a proactive solution that mitigates gun violence, provides actionable intelligence, reduces response time, ultimately saving lives, while at the same time respecting our privacy and rights. ZeroEyes is that solution. Save time. Save lives.

Here in Grand Island, we are north of Buffalo and south of Niagara Falls, and one of the major events that happened was the shooting at the Tops in Buffalo, New York. It was a mass shooting, and it brought home the idea that there are probably more strategies that we can employ, you know, in our district to keep our students and We have a really awesome team from all over Western New York going to come see how the software works.

The whole concept came from turning that traditionally reactive camera into a proactive gun detection system.

We're going to have a live demonstration. The attendees not only will learn about the product, but also get a chance to see how effective it is in communicating to the key people that a district would identify to get this information.

Someone in this office calling our direct point of contact, relaying this information.

So you're able to have this desktop dashboard up as well as receiving the SMS notifications, as well as receiving the notifications on your mobile app.

Navy Pier is a, you know, a big open parkland really where we have a lot of different entertainment. It's a free area for people to come visit, which is hard to secure. So adding this feature I think just helps us with another layer of security.

You'll be able to see Kevin as he walks the cameras, in front of the cameras, and then our dispatch center is with us remotely. They will be dispatching the alerts.

Once the algorithm gets the detection, you're gonna see the single-frame image come in with a red bounding box around the weapon where the analyst is gonna make the determination of yes, this is a gun, or no, it's something else.

Greatest value that ZeroEyes offers is the human intelligence side with the former military personnel and using their experience with weapon identification.

Truly, their sole purpose is to make sure every detection the AI makes is an accurate detection.

It is super impressive. to see how fast the information flows and how quick we can react to keep kids safe.

We're stopping the threat at the first sight of a gun, not after the first shot's been fired.

We did test this for a good 9 months, and to be honest with you, they've been 100% on right now.

Probably one of the greatest inventions that we've had in recent years, to be honest with you. It's real-time info. And that's huge.

Now that I've seen how the system works, it's very good.

I thought the presentation was great. It was well prepared. I really think that it would be beneficial for any school district throughout the country.

I thought it was very informative, and I think, I think it'd incorporate well actually into our school system.

It sent the alerts to my phone.

I was able to zoom in and see what hallway, where the location was.

And seconds are crucial, and if you're saving seconds or minutes detecting weapons, it's really going to help not only the first responders but the life-saving measures.

This identifies the threat before they enter if the gun is brandished, and that to me changes everything.

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Now back to the show.

Great. All right, what do you got?

Yeah, so I came across an article this past week that was published by the Department of Energy's Lawrence Berkeley National Lab, or short, just call Berkeley Lab. So what they were showcasing was this really innovative approach that researchers have taken to find breakthrough materials for quantum applications.

Mm-hmm.

So quantum materials, just really quickly, these are materials that can have what we find to be very unusual properties because of quantum mechanical effects. So they can potentially do these amazing things such as conduct electricity without any loss, completely change their properties with just a small change in temperature or a magnetic field. And what this article goes through is kind of the way that scientists historically create quantum materials. And the way they do this is they create defects in materials. So they're actually going in and replacing one type of atom in a material with a different The problem is that these defects are very hard to create. So the way that scientists have done this is they create a lot of defects, then they evaluate them one at a time. And if a material doesn't have good properties, which is usually the outcome, they go back and they repeat the whole process.

Yeah.

If it does show an interesting property, then they need to try and figure out what's going on and why. So there's just a Massive number of combinations and possibilities. You can replace these atoms with all kinds of different elements. You can put them in different places. So what that means is it actually can create decades of work to screen and find defects in just one type of material. So where this starts to get interesting is this team flipped the process. They started with theory. And then they finished with experiments. And the high-level idea was to use theoretical computation as a guide to upfront identify what they thought would be a much smaller number of promising defects. And after they'd screen those using computation, then they'd actually fabricate the material. So they went through this, they predicted 750 different defects in a specific material. And what they were doing is they were replacing specific atoms with 57 other elements. So they go through this whole long process, and at the end they found one material that had interesting properties. And this was a defect that had never been shown before. No one had ever seen this. So then they went to the step of actually making the material. They evaluated the defect and actually worked. So this is pretty cool. They're able to fabricate materials, they're able to replace specific atoms. They actually had this quote that I thought was, was kind of interesting in the article. So they knocked out a bunch of sulfur atoms in this material, leaving these tiny little holes. They then applied a mist of cobalt atoms to the surface, and then they used the sharp metal tip of a scanning tunneling microscope to find a hole and nudge a cobalt atom in. They said similar to putting in golf.

Okay.

But pretty, pretty wild. So, and then they make this another analogy. There's a quote in the article is we're essentially playing with atoms like Lego bricks. So pretty wild. I think we're about to see a lot of interesting things happen in material science. We've talked about this a bit in the past, but this ability to just rapidly accelerate and change the whole scientific process using the power of computers and also these super state-of-the-art tools. I think we're in for some interesting things.

No, very exciting time. I mean, this reminds me a little bit of work being done with proteins and protein folds and things that were just hunt and peck and slow and labs. And, you're doing this now with technology and software and super advanced tools and Yeah, and they were using state-of-the-art computing resources that they have at Berkeley Lab.

So a lot of this has to do with just the power of compute where you couldn't have done this a few years ago. These are the benefits of all this AI spend and infrastructure that we were talking about coming online is that unlocks all kinds of—

Yeah, and again, I think it also points, Matt, to this is another great example of scientists doing basic research. And it's like, you know, this, this, oh, this is all waste. You know, why aren't they doing something practical? And, you know, a bunch of nerds in a lab somewhere moving atoms around.

This is—

without that, you don't develop a new battery technology that makes EVs possible.

Yeah.

So this is the future of computing, telecommunications, climate change.

Yeah, exactly.

Exactly. Yeah, massive potential.

Good reminder.

We're going to take a short break, but then right after that, we'll be right back.

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Okay, the last one I've got today is, this is something that was in JAMA a little bit ago, but it's CAR-T cell therapy, which has been around a little bit now. And to, again, the very simple explanation of this is this is really using a patient's own immune system To identify a cancer and basically target it and kill it, right? And it— there has been very profound results in certain blood cancers, some childhood cancers.

Yeah.

But what I think is really exciting is the expansion of it into some new types of cancers, including one of the nastiest, most deadly brain tumors, which is glioblastoma.

Yeah.

And actually killed my grandfather.

Oh.

And so, you know, and work being done, a lot of the work is being done at Mass General, not too far from us here in the Boston area.

Yeah, right across the street. Yeah.

Yeah. And, they've developed something. One of the issues is always cancer is just really clever at kind of mutating and changing. And, if you get it one way, it kind of sneaks around you. But, they've created really kind of a bundle of attacking mechanisms. So, it's more than just one protein and identifier. And so, they're kind of hitting it on multiple— Forces and they've designated it CAR-T is kind of the thing they're doing. And, early, again, very early stage.

Very early science. I was going to ask, yeah, what stage?

Stage 1, stage 2, but just literally profound results like can't find the tumor kind of thing.

Amazing.

Has people just, again, very excited about that this technology, which so far has been very effective in a narrow set, is beginning to mature like these things do and the problems get solved and kind of the second generation of these things are now opening up to some very resistant nasty tumors, including, I think there's hope for pancreatic tumors and obviously these very nasty brain tumors.

That's great.

A long way to go yet, but again, encouraging results. Again, you know, I think we're finding with a lot of these cancer things that what we're hoping for is not you take a pill and you're cured, but that there is more tools in the toolbox that just provide a higher quality of life for a longer period of life in a very treat— a series of things that you live with for a long, long time. Which has been the story now of AIDS and things like that, that Manage them for very long periods of time.

Yeah.

Yeah. So, it's really good news. And again, for those that have been touched by cancer, again, I think we're in for a very exciting decade where, you know, one thing is they're just, the number of people that want to get into the trial for this new treatment is just longer than they can handle. Yeah, hugely, hugely demanding. It's expensive, it's labor-intensive, it's, you know, it's still at kind of MVP stage, But very, very promising.

So that's great.

Excellent. Okay.

Okay.

Another good week.

Another—

yeah, that's great.

Another set of interesting things. We'll do it again, Matt.

Sounds good.

Good to see you.

Take care.

Take care. Bye-bye.

Really quick before we wrap up this episode and before the outro plays, I want to provide a little bit more context onto what CAR T cells are and, you know, what they do and sort of how they work better in context to cancer treatment. So the definition of them is they are chimeric antigen receptors, or CARs, are receptor proteins engineered to give T cells the ability to target a specific antigen, combining antigen binding and T cell activating functions into a single receptor. So they're a form of immunotherapy used to treat certain types of cancer. CAR T cells are T cells that have been genetically engineered to produce an artificial T cell receptor called the chimeric antigen receptor on their surface. These modified T cells are designed to recognize and attack specific proteins on the surface of cancer cells. So T cells are collected from the patient's blood. The cells are then genetically modified in a laboratory to express the CARs. And the engineered cells are multiplied into millions. The CAR T cells are then infused back into the patient, and then once they are in the patient's body, the CAR T cells multiply and, guided by their engineered receptor, recognize and kill cancer cells that have the target antigen on their surfaces. So a little bit more context onto what CAR T cells are, how they work, and how they work within the body that has been affected with cancer. But thank you so much for listening to this episode of The Tech Optimist. Thank you so much for joining us, and we will see you on the next episode. Thanks so much. Thanks again for tuning into The Tech Optimist. If you enjoyed this episode, we'd really appreciate it if you'd give us a rating on whichever podcast app you're using, and remember to subscribe to keep up with each episode. The Tech Optimist. Tech Optimist welcomes any questions, comments, or segment suggestions. So please email us at info@techoptimist.vc with any of those, and be sure to visit our website at av.vc. As always, keep building.