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Notes & Links

📝 Edit Notes

Chapters

1 00:00 Let's talk! 00:37
2 00:37 Sponsor: Tiger Data 01:43
3 02:20 Skype & Friends 03:20
4 05:40 Too late for NVDA? 01:20
5 07:00 Not a recent thing 02:18
6 09:18 Picking winners 03:44
7 13:02 Open models FTW 00:43
8 13:45 Peak parameter? 02:01
9 15:46 Project Prometheus 04:03
10 19:49 What is cool? 06:33
11 26:22 Roomba is the future 03:21
12 29:43 Home automation 02:10
13 31:53 Sponsor: Namespace 01:38
14 33:31 IKEA gets in the game 00:22
15 33:53 Matter-compatible 00:55
16 34:48 Air autonomy 02:07
17 36:55 Animals swarm 02:00
18 38:55 The swarm definition 02:10
19 41:05 E pluribus unum 03:10
20 44:14 The Besieged Fortress 05:08
21 49:23 Not a swarm! 02:01
22 51:24 Mission control 03:43
23 55:06 The case of the queen 04:09
24 59:16 Humans on-the-loop 03:22
25 1:02:38 Jerod sniffs danger 03:12
26 1:05:50 Inflating billions 00:43
27 1:06:33 Sponsor: Augment Code 01:30
28 1:08:03 Sponsor: NordLayer 02:45
29 1:10:49 Aladdin's genie problem 03:34
30 1:14:23 State of the art 01:23
31 1:15:46 The next three years 03:11
32 1:18:58 Adam's three use cases 03:00
33 1:21:57 Also not a swarm 02:04
34 1:24:01 Where the people swarm 06:51
35 1:30:52 Go make stuff 02:57
36 1:33:49 Chris on Alexa 02:49
37 1:36:38 Take the power back 00:45
38 1:37:23 Adam's idea 01:09
39 1:38:32 Bye, friends 01:03
40 1:39:35 Next week on the pod 01:33

Transcript

📝 Edit Transcript

Today we have Chris Benson, Practical AI co-host and longtime friend… Welcome to the show, Chris.

Hey, thanks a lot. It’s great to be on the guest side of the equation here.

Yeah. You’ve been interviewing folks for a long time, and now you, sir, are being interviewed, so to speak.

Does that make you nervous?

Well, you guys taught me everything I know, so yeah, a little bit. It’s kind of like –

We held back a few tricks. We’re going to unleash them on you on this show.

Oh my God, okay… But yeah, you guys were the OG originals. Daniel Whitenack and I learned everything we know from you guys.

Well, you guys are good at what you do, so I’ll take that as a compliment. Yeah.

What’s funny is how far back we go. I think there’s some context to give here… And Jerod, just for an exercise here, I went and searched the name Benson - because Chris’s last name is Benson - in my calendar, just to see if the history was there… And literally, April 3rd at 10:30 AM, Chris Benson on Skype. That’s how far back.

  1. Did I not say the year? My bad.

April 3rd, 2018, Chris Benson, 10:30 AM, Skype. That’s what you were doing.

That was way back when we used Skype, you know?

And that was the original conversation that started the host, co-host, Practical AI… I think it was a data show back then, even. I’m not even sure if it had a name.

It didn’t have a name yet…

The beginnings of Practical AI and this long history of relationship.

It was funny, because I know I had reached out to you guys, and then… So you guys had Go Time, and there was this kind of Changelog family that was already there… And I wasn’t part of it yet. But Daniel and I were – Daniel Whitenack and I were both kind of the data AI people in the Go community at the time. And so I was listening to Changelog, and stuff, and thinking “Boy, maybe these guys need to start an AI-focused podcast, or something… But I’d like to do that.” But I was thinking “I need somebody to do it with.” And I was thinking “I’ve got to reach out to Daniel. He’s the other AI data –” So I reach out to Daniel, and he’s like “Oh, by the way, I just started talking to Jerod and Adam about this.” And I was like “Perfect. I just sent them a message.” So the timing –

Yeah, it all just came together. The timing was perfect.

You guys were so far ahead of the curve. Yeah, well, it was very clear – if you were really plugged into the AI world at that point, it was very clear that this was going. Like, where it was going - things change all the time. But it was very clear by that time that the gas pedal was on, and sky was the limit, and there was some kind of journey ahead. And at that point, Daniel and I wanted – we wanted to be steering that journey for everybody. And you guys were awesome in terms of saying “This would be fantastic, and we’d love to do it.”

And that was back in 2018. And here we are in 2025, late 2025.

Yeah. Things have changed, but have stayed the same as well… Here’s a funny story that you might not know, Chris. I’ve given you credit for this before, but I don’t think I ever told you this, which is - at some point the four of us were on a call, and this is like post-launching Practical AI, but pre-ChatGPT moment. And you were lamenting that we missed NVIDIA, or something. We were talking about the run-up. I think NVIDIA had just had a huge run-up with regards to – first it was gaming, but then also machine learning was kind of starting to take off. And you were like “Man, I can’t believe… Look at NVIDIA. It’s crazy, the hockeystick growth on that stock.” You’re like “But we’re too late now. We’re too late.” And this is like 2019.

Yeah. Well, here’s the funny part, Chris. I thought to myself “Are we, though…?” I was like “Are we…?” And I actually left that call and I went and I bought a little bit of NVIDIA stock thinking, “You know, if Chris thinks we’re too late, this guy’s always ahead of everything. So I think he’s ahead.” So I have to thank you for a stock tip that has paid off nicely.

You’re welcome. You buy contrary to my advice, but that’s probably the –

Right. So I need to talk to you more often and kind of do the opposite thing… Yeah.

So yeah, thanks for that. That was cool. Unfortunately, I didn’t buy enough to like just quit everything else and retire, but I’m happy that you thought we missed it.

I’m glad I was wrong on that. They’ve done amazing things. It’s kind of funny, just in AI in general - you know, AI has been around at some level… Even the modern form of AI has been around for decades. it’s not a recent thing. Because like I got introduced to it by my parents, who were actually technical people, Georgia Tech, and Lockheed, and things like that… And they were doing stuff back in the late ’80s and early ’90s, and stuff. And my dad introduced me to neural networks, which is still the basis of all this stuff, in 1992.

And it was funny, the tie-in here to NVIDIA is – we went through another AI winter. There’s been a series of kind of like where everyone gave up on AI for a little while, and then circled back around… They’re called AI winters. And so the last AI winter kind of happened at the end of the ‘90s, going into the 2000s there for a few years, before the modern era, if you will, picked up. But I think the difference is that the notion of modeling and the software basis of AI was there, and there were a lot of great ideas, and a lot of the stuff we’re doing today originated back then, conceptually. But we didn’t have the hardware. We couldn’t actually do the thing. We didn’t have these GPUs, and now other types of chips that enabled all this to happen.

[00:08:26.28] And so it was really like the hardware side of things had to catch up, so that the software thing… And when people say “Well, why did we have an AI winter?”, and I think to a large degree it wasn’t the lack of amazing brainpower to solve these problems and create the models. It was the fact that you didn’t have the hardware infrastructure to do the things that people were envisioning were possible. And it wasn’t until NVIDIA came along and became really the AI hardware company. I mean, I know they do a lot of software stuff, but… That made the difference. And Google came along eventually with TPUs, and lots of other players jumped in, but both sides had to be there. So… A little journey down memory lane there.

It’s the benefit of being old.

You’ve seen it all, Chris. You have seen it all.

I’ve been around. I’m old as dirt, so…

This is not stock advice, but from your purview here at the end of 2025 - and you have NVIDIA, you have AMD, you have Google, you have Meta… You have these large players making huge investments. OpenAI, of course… I mean, the list goes on and on and on. Which single entity do you think is best positioned to succeed over the next 10 years? If you had to pick one of the top contenders. Is it Google? They seem like they’ve really turned the corner, but I’m not sure if their capital investment on their own infrastructure is going to be the big win that some people are saying it is. I don’t know. What do you think?

So I’m going to cheat a little bit. I don’t really have a one… For a long time, people would say OpenAI, and before that, they were saying Google. There is a there’s a top group, and they are certainly doing well. And at the risk of getting slightly – in terms of social issues, there’s growing inequality between kind of those group of haves, and kind of a lot of others that are have-nots in that way. But I really think that open models are becoming increasingly important, because the difference… If you go back a few years, and like it wasn’t coming out of OpenAI, there was a big performance difference in what you were able to do. And if you look at the closing of the gap between what’s possible… I mean, there are millions of open models out there, and there are hundreds of them that are in kind of like – they are nipping at the heels of the leading ones. And that gap between the latest, greatest thing from one of these big name companies and what’s possible in the open world has narrowed dramatically. And what that’s really doing is pushing pushing model creation into something of a commodity area. And I think you’ve seen that in terms of what some of these big companies – you know, they’ve built services, and they’re building separate businesses, and they’re going into verticals, and things like that… But that’s because just the model generation is not going to be the profitable thing for years and years going forward.

And so they’re turning from being AI providers explicitly into AI service providers now, that are specific to different types of businesses. And I think they’ll do quite well. I think kind of – I don’t know, I’m afraid, especially after pointing out my horrendous…

Well, you drilled it last time.

Yeah, I was gonna say, after my horrendous NVIDIA prediction, the last thing I’m going to go do is pick a winner here.

[00:12:01.03] [laughs] Okay…

But yeah, I mean, they’re making a lot of money by pivoting within the scope of what they do. And they have the expertise… And Meta – as we’re talking now, Meta is just like purely buying the AI talent. Like, “I don’t care what Google is going to pay you. I’m going to pay you 10 times more, and there’s no way you’re going to go anyplace but us”, and trying to kind of catch up to that Open AI… Which is still, as we speak, probably the gold standard there. But with a few others, such as Google, as you mentioned, and several others that are kind of nipping at the heels there. So it’s interesting times…

So the long-winded answer is Open AI? Is that what you’re saying? [laughter]

We have to go back and analyze what Chris said, and tease out the truth of it.

Oh, I tried to escape that. Adam, that was not fair. I worked really hard for five minutes to kind of squirm my way out of your question there…

So… Very close. When you say OpenAI - very close. You got the word open right. How’s that?

So Chris’s answer is the open models will commoditize the frontier models, so to speak, and these people that are just buying all the GPUs, and just training, training, training. And then, of course, inference as well. But…

I mean, it’s requiring you – we’re seeing this progression where we’re building out frontier models is costing less money. There’s a ton of money in some of them, but the efficiencies that are now built into training from some of the latest research has made it where you can build some amazing stuff with not quite as much as you might have expected a year or two ago in terms of relative performance against the hardware that you need to support that. So it might be – who knows, I mean, where the research is taking…?

Is there such thing as peak parameter? I mean, I think I read that xAI’s next model coming out whenever is going to have a trillion parameters, or something. And it’s like, how large is large too large? Or is there no such thing?

So one of the things that we’ve that we’ve been talking about for a while now is the fact that like – it used to be in the early days of the of the GPT series from OpenAI that you saw distinct capability differences as you went from 3 to 3.5, and to 4, and that kind of stuff. But there’s also been – we’ve seen kind of a plateau. It’s almost like you’re seeing that a lot of the – it’s not just a model thing, but also some of the infrastructure that’s being built around it has made it much more accessible in terms of its productivity, and its usefulness, and there’s less of a friction when we’re trying to use models at this point… So I do think that there is no infinite rise in terms of the number of parameters you have to do. I think that that does level out… And also, if you’re going to have that many parameters, being able to use that productively from an inference standpoint… The world is turning out to be a mini model world, instead of a giant model world, you know… And I’m not sure that a lot of people in the general public, that aren’t people like us that follow this closely, really realize that. I think when they think AI, they’re thinking ChatGPT, because it’s what they know. One model to rule them all, one model to bind us. And I’m not at all – like, that’s not what I think is the world. I think the world is many, many models contribute to solving a problem in various ways. And here we are, in 2025, deeply into the age of agents. So it’s no longer just models, but now agents with models that are acting on your behalf… And I think the reality is it’s a many-agent future that we’re talking about here.

Before we go there, I’ve got to ask you, because we’re talking about companies and predictions and potential here…

Have you tapped into or heard of the next Jeff Bezos thing, Prometheus, and the startup he’s chairing, co-founding etc? Are you are you tapped into that?

I’m not up to date on the details.

That’s like half the press, isn’t it? They announced that…

It’s like yesterday’s news, basically… Today… Today’s news.

I think there’s a perpetual Bezos/Musk pissing contest that goes on. And this seems like the next one. He’s like “You have xAI? I’ve got this thing.”

[00:16:17.28] According to TechCrunch, Jeff Bezos reportedly returns to the trenches as co-CEO of new AI startup Prometheus. Project Prometheus. So he hasn’t done anything from a CEO, aside from shareholder, chairman etc. behind Amazon. He’s been just getting swole, essentially. Getting swole and going to space.

Getting swole. On his yacht. Yeah.

Yeah. As you would, if you were…

Well, he’s been doing this space stuff, he’s been doing Blue Origin…

Well, that’s what I said, getting swole and going to space. That’s what he’s been doing. So this is kind of cool, that I suppose the next big thing could be from him. So maybe the next time we talk, Chris, you can give us your non-prediction prediction. [laughter]

I can slide out of that one, too.

Yeah. Do we go buy Amazon right now? That’s what I want to know, Chris…

So I’m probably the wrong person to talk to about this, not only because of the prediction that we just talked about, but also, I want to point out… Honestly, this may sound really counterproductive as Practical AI co-host on this, but… And I think Daniel’s the same way. We’re less interested in kind of the big, big names coming out with their latest big things, because there’s so much amazing work being done by real people out there…

[laughs] Take that, Bezos…

Yeah… Plastic Jeff Bezos. Like, “Hi, I’m Jeff Bezos.” And Elon Musk, and all these guys. They’re always one-upping each other, and they do some big things, but… I think 99% of the press is going to these people…

…but I think 99% of the real productive work in AI is going to all these invisible masses of amazing people that are doing this stuff every day. And if I could get the mainstream press to kind of like refocus, I’d be like “Look around.” There’s just astounding, amazing things that are happening, but they’re not happening by these famous figures. And these guys - yes, they have tons of money, and they’re super, super-ultra wealthy, beyond imagination, and they can throw their money around and stuff, but… You kind of mentioned, it’s kind of a pissing contest, for instance, between some of them… There’s so much cool stuff out there that’s not the latest Bezos/Elon Musk –

I mean, $6.2 billion behind this thing is quite…

…quite an investment in there that he’s raised for it. $6.2 billion.

What are they doing? What’s their deal?

It’s only speculative at this point. It’s only got a name, Project Prometheus, Jeff Bezos… Co-founder, I believe, is Vik… I would only mess up the last name. B-A-J-A-J is the last name of Vik.

Can you imagine being able to throw $6.2 billion at something that you don’t really know what it is yet?

I don’t know if we know. I think if you were to write a check for $6.2 bil, or you even raised those funds, you’ve got –

The reason he announced it is to get better raises. Yeah.

That’s right. Some version of more money…

Get people interested. So Chris, you probably can’t convince the mainstream media to ignore the 800-pound gorillas, but you can convince us. So here we are, we’re ready… What’s cool? What’s underneath the covers, or what’s the invisible stuff that people are doing, that you and Dan and we should be interested in?

[00:20:02.03] It’s funny, we just… I’m going to say something that I said the other day, and I’m starting to say it more and more, but I think people easily look around wherever they are in the world and whatever their politics are, and it feels like a difficult moment. And there’s all these things you can point at, and say “We’re going through a really tough time, and it’s tough, and everyone’s trying to figure out…” But I want to offer a counter narrative to that. We’re also at this moment where this stuff has – the AI, and there’s a hardware revolution going on, and there’s a robotics revolution going on, all together, and they’re all connected, and they’re powering each other… And I think we live in the coolest moment in human history right now. We are sitting in it as we speak today.

And so what’s happening right now is with all of these different relevant capabilities, the robot people, and the AI people, and the software people, and the hardware people - it’s all coming together, and you can do amazing stuff today that even a year ago we couldn’t do.

Before now, we’d have kind of several years of little software eras, and we were getting into certain ecosystems with a language or whatever, and they’d kind of run for a few years… But right now it’s changing so fast, and the capability is coming so fast, that aside from the big 800-pound gorilla types and stuff, everybody can get into this stuff. And so I think we’re at a moment right now where it’s really going to start being pervasive in everyone’s life, in a bigger way than it has been. Not just I’m going to open my phone up and talk to ChatGPT kind of way… Because yeah, I mean, that was unimaginable, if you think about it, just a few years ago. It hasn’t been long since that was an unimaginably amazing thing to do. But we don’t even think about that now; we do it all the time, and don’t even think about it now. But physical AI, and the fact that robotics have come so far in the last few years, and that now in addition to NVIDIA there are many other chip makers that are coming on scene to support AI… And some of them are doing more of the dedicated AI chips, and others are more combining different types of chips, so that you have that… And some are great for data centers, big cloud data centers, and others are great for edge devices and tiny little constructs. And I think you’re going to see so much happening in the marketplace right now that are coming from startups. They’re not coming from the 800-pound gorillas. They’ll have their fair share. At 6.2 billion, they’d better.

Yeah. They’d better do something with that.

Yeah. You’re going to see amazing capabilities coming out of fairly small companies. And speaking back again to Daniel Whitenack, my co-host and part of our family in this, he started his own company, which is kind of supporting that. And that’s what I like seeing. He has Prediction Guard, which is kind of supporting open model approach… And I think that in general, that approach of anybody can go – whether you’re using a cloud environment, or a startup like Daniel’s, or something like that, you can go productively pull down models from Hugging Face, which I likened to GitHub for AI… You know, the way GitHub has always been for software. Combine a bunch of different, fairly sophisticated open source software packages and do some amazing things without 6.2 million. You can do it as a college student in the dorm, figuratively speaking. And that’s the thing that really excites me, is that, is the ability to - everyone becomes a maker, if you will. Everyone out there can become – once upon a time, we were kind of like “Hey, we have the internet. Everyone can be a software developer. All the stuff you need to learn is online, there’s all these resources, a lot of it can be done for free, it doesn’t matter where in the world you are…” Well, now everybody can become a maker. Everybody can access these different things and go do something great.

[00:24:19.14] And I think the fact that we all have these Roomba type things, these vacuums in our houses, everybody is now completely used to that. But I think we’re right on the cusp of having lots of little devices like that in our houses and our businesses that are doing all these things… Which eventually will get us into this notion of swarming that we’re going to talk about.

Yeah. I’m ready for the little robots. I don’t want the big, scary robots, but I like the little robots that help you do things. The Neo thing is weird; we don’t have to talk about that, but that was kind of strange.

Was it Neo? It wasn’t Neo. Johnny Mnemonics. You think Johnny Mnemonics?

Yeah, what’s Johnny Mnemonics?

Well, Johnny Mnemonics was like he had – man, I can’t remember this one, but it was same actor, Keanu Reeves, and I believe he had… Oh, he had something in him, and he was carrying data.

Vaguely, I recall this. It’s been a while.

Yeah. It was like the idea of a mule, but not drugs.

That was back when he was young.

Yes. Yes. I thought you were talking about Johnny Mnemonics.

You jumped right to The Matrix, which makes sense, Adam, because most of my references are The Matrix… But I was actually talking about this new robot in your house that costs 20 grand, and it’s controlled by a human currently…

I saw that, but I still don’t think that’s going to be the thing.

No, I don’t think so. I was gonna say, that’s kind of weird at this phase. It’s a general-purpose – like, it does laundry, it does your dishes, and it’s like a humanoid, full size, similar to what the optimists think they’re building… And yet it’s at this point, because they need data to train these models better, it’s not at all autonomous. It’s controlled by a human with what I imagine is like a sophisticated joystick, probably overseas…

It’s kind of creepy when you think about it.

Your grandma’s in there with a stranger in the form of a robot…

Yeah. Now, Wall Street Journal did a great video about it… Joanna Stern told it to do the dishes or something, and it took like three minutes to load a cup into the dishwasher… Which is a 15-second task. Anyway…

It’s not there yet. I feel like that’s being too big and general-purpose. I feel like more specific, small… Like the Roomba [unintelligible 00:26:22.21]

The Roomba is the future. That was an early thing, but… It’s purpose built for a very specific thing, and there’s a whole bunch of different makes and manufacturers and stuff on the market… And we can go through and debate what’s better and all that kind of stuff, but I think you’re seeing that, times many, many, many things across all sorts of tasks. And they’re cheap. And even Roomba-type, the vacuums are too expensive right now. I think with the cost of robotics coming down and accessibility, then it’s like the – if you think outside this and just walking into a retail store, or getting online to Amazon or whatever, and just buying something that once upon a time might’ve been expensive, and now it’s 30 bucks, you know… And I think that in this day and age that 30-buck purchase, I think that getting a robot that’ll do this and that and the other, and the fact that they have – eventually you have families of robots that can do different things, and you can put it in swarming mode, and just say “Auto my house in swarming mode”, as we’ll get into, and they just like coordinate and do all the stuff, they’re sensing you, they’re moving around you, you’re doing the thing… And that’s real life. Aside from just the vacuum, your lawn and garden care is getting taken care of, your security around your house, your roof and gutter inspections…

[00:27:56.14] …it’s integrated into your smart home stuff… You don’t have to worry anymore about where your packages were left by the delivery driver, because those robots or the swarms that are managing your house are just doing that… And it’s not insanely expensive. People are like “Yeah, yeah, where am I going to get the 6.2 billion from Bezos to buy my swarm for my house?”

And I’m like “No. No, it’s not. You’re going to have the Christmas deal.” We’re coming up on the holiday time, and you’re going to get online and you’ll have all the different packages about “What level of swarming do you want? This one is an 18-accessory swarm package.”

“It’s going to handle your outside, it’s going to do this…” And you’re trying to choose, you’re like “Well, I don’t know. I’m going to spend more for my kids on that… But there’s great aunt Louise, and we only talked to her once every five years, and I send her kind of a token thing… So I’ll send her the four items swarm package, that she can add into whatever she’s already using, because it’s all open stuff.” That’s gonna be normal, and we’re not that far from the opportunity, and it’s not the 800-pound gorillas that are going to bring that. It’s going to be the billions of startups out there. They’re each doing a little piece of it, and they’re swarm components and stuff are able to communicate. That’s the future that we’re going to build.

Well, I’ll tell you one thing… You’ve definitely put a lot more pressure on the idea of home lab, that’s for sure… Because that’s all home lab. Those are a ton of DNS queries out there, probably a ton of telemetry being tracked… A lot of things you may or may not be concerned – but those are things I think about when I think about adding more and more devices to my home. Gosh, man…

So separate – I have a slight side story, but it contributes to that. So about a year ago now, almost exactly a year ago, we bought and moved into the house that I’m in now. And the guy that we bought it from, he and his wife, he was a fanatical home automation person. And so we moved in, not because of the automation; that was incidental. But it’s helped me move from just like thinking – more of a professional kind of thing, like [unintelligible 00:30:15.04] to thinking about stuff around the house, with all the sensors and the cameras and stuff… And we have all the various types of home automation stuff that you see out there, [unintelligible 00:30:27.28] We have many, many, many dozens of Kasa devices all over the place.

And Kasa is the brand from Lutron. Is that right?

Right. It’s from TP-Link, actually.

But that’s just one. There’s a whole bunch of them. And you have Apple Home, and Google Home…

I was thinking Caseta. Caseta’s from Lutron. Those are the light switches.

Yeah, Lutron does the light switches… But there’s some common protocols that they all work on. And I’m starting to see – because I didn’t have to go start it from scratch, and because I inherited what this guy had already kind of put together, and then had to figure it out and make it work… And suddenly, I’m like “Well, gosh, it would be really easy to add this…” And we’re talking about this robotic future even in our homes; not just a commercial or industrial or whatever thing, but in our homes. And it’s so easy for me to see that now, because I realize I already have a good bit of infrastructure here, and it’s not expensive. It just takes a little bit of effort. And if they can make that easier for people to get into, it’s a done deal. We already have WiFi, and all the other things, and then you start adding things to plug in… It’s like Legos. It’s like home automation Legos in your home.

Break: [00:31:46.22]

Speaking of Legos and home automation, IKEA just announced a whole new set of like 27 smart home things, coming from IKEA.

Talk about bringing it to the masses… That’s the kind of thing that IKEA brings to the masses now, is they make it very simple and straightforward and Lego-esque in order to… And it all runs on Matter, which I think is the open standard for communication between these things.

Matter is in an interesting place… I only buy things that have Matter integrated in. And for listeners and viewers, Matter is a protocol that allows different makes and models of automation to work together over a common protocol, and it’s local based instead of cloud based. But not everything does it yet. So it’s still kind of working – it’s been very slow, it took a long time to kind of come into play, but it seems to be having a second wind right now, because of all this new capability that’s coming about… And so every new thing I buy, whether I’m using Matter yet on that or not, I have to have Matter, so that as I go forward, I can integrate into that. But yeah, everything is – it’s local, it’s Matter, and I’m finding with today’s craziness out there that I’m moving more local and a little bit more out of the cloud, and so Matter is becoming increasingly important, from my standpoint.

Well, from the startup perspective and the swarming perhaps, at least the droning perspective, you’ll be happy to hear, Chris, that we do have a startup coming on soon, Zipline, who are now moving delivery drones into production. They actually have a delivery drone system that is a startup delivering medical needs in Africa, vaccines and stuff like that, and now they’re moving into the States and they’re doing food delivery, small item delivery, small package… So think your Chipotle burrito, that kind of thing.

Yeah, eight pounds or less. It’s super-cool stuff, and they’ve got it to where – they’re actually rolling out into commercialization now. So startups are making moves in this direction. And now there’s our – I’m gonna assume in each city they have a fleet of these delivery drones. Obviously, each drone is operated on its own, I assume eventually autonomously… It actually seems like a simpler problem than autonomous cars, because the airspace is just pretty open. You’ve got problems like wind, and snow, and stuff like that, birds… But it’s gotta be easier than cars.

Yeah, generally. So it’s a different problem. It’s a little bit of both; it kind of depends on how you’re looking at it. With cars - and we were just talking to Waymo again a few weeks ago on Practical AI about this, so this is very top of mind for me. With cars - yeah, there are a lot of challenges, and you have the notion of the child running out, or the ball bouncing out… There’s a lot of stuff that’s right there, but also how you’re navigating is very well defined, in terms of the streets and stuff like that. Air becomes more three-dimensional, and so the challenges are different, but so long as it’s not highly congested, I would agree with you that it is generally easier that you can kind of move from here to there. So long as you have good collision avoidance and some other capabilities for navigation there, then you’re probably doing okay… Though that changes with swarming, because swarming brings in close collaboration.

Yeah. So define swarming then, because I think of killer bees when I hear swarming… And I assume with drones you’re talking about a bunch of drones nearby each other then.

You are. And it’s not just a physical distance thing, because what is physical distance is a relative thing, depending on what it is you’re trying to do. But it also – it’s really more about behavior, and so we can dive into that. But before you say that, I think a line of thought we should go down is that as you guys know, I’m really into animals; we were making jokes earlier about a bazillion dogs, and stuff like that. I’m a licensed wildlife rehabber, and I study animals. And in the context of swarming, Mother Nature has perfected not just swarming, but there are many different types of swarming, from different species. And so I have a set of species that I tend to look to for swarming purposes, and say “If I want to swarm with this type of technology or this type of platform, how do we get started on that? How do we get inspiration, or look for some insights on the technology?”

[00:38:01.14] Well, you can look to certain species that are similar to the technology platforms you’re interested in in terms of how they move around and do stuff, and say “Well, how has nature solved it there?” And I definitely do that a lot. It’s not uncommon for me to go into tech meetings and start off with lots of pictures of animals and stuff, and people are like “What’s going on with this?”

Are you thinking like fungus, bees?

I do a lot of bees, bats, birds, starlings… You know, those huge, what are called murmurations of starlings…

Ants are awesome. Ants are awesome. When I’m thinking about robotics on the ground, meaning what we would call a UGV, which is an Unmanned or Uncrewed Ground Vehicle, ants are amazing in what they can do. They’re an awesome thing to look at. But I’ll start with the definition that I use… Given the fact that I work in the military intelligence space, my definition sounds kind of – it uses that jargon, but really don’t get caught up in that. It can be applied to residential, it can be applied to commercial, it can be applied to industrial. So don’t get caught up in this specific wording. So I’m going to read it in front of me. It’s one really long run-on sentence that’s very specific in what it’s trying to imply.

It is “Swarming occurs when numerous, independent, fully autonomous, multi-agentic platforms exhibit highly coordinated locomotive and emergent behaviors with agency and self-governance in any domain, which could be air, ground, sea, undersea, or space, functioning as a single, independent, logical, distributed, decentralized decisioning entity for purposes of C3”, which is command, control, and communications, “with human operators on the loop to implement actions that achieve strategic, tactical, or operational effects in the furtherance of a mission.” So a long, long, long sentence, but it hits a bunch of very precise concepts and integrates them in together.

Yes. I can tell each word was selected there.

Yeah. A mission might be – instead of thinking military, a mission might be getting a package to your house. That might be the mission. And that does have command, control, and communications involved. So it doesn’t have to be the military-esque jargon that we’re talking about. It applies to any of these: commercial, industrial, residential, military, whatever. So…

It’s a lot. And if you want, I can kind of break down high level what some of those mean…

Yeah. I think my broad takeaway – we can talk about the individual words, because I know they’re very specifically chosen, like “independent, logical, distributed, decentralized decisioning entity”, stuff like that… I can tell each word was selected for a reason.

But I think my grand takeaway of a swarm is kind of the E Pluribus Unum. It’s like, okay, all these things are individual and autonomous, but they’re all acting as one. They’re acting with one purpose.

That’s a fantastic insight that you have. And that is the key to it. Swarm is such a buzzword. We always have buzzwords in this AI and software spaces. There’s always the buzzwords of the year. And swarm is certainly a huge buzzword right now… And almost without exception, I will turn around and tell – I can go back to my definition, assuming that you want to accept that as the definition of swarming, and I can defend that fiercely.

I cannot attack it. Can you attack it, Adam?

You