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Speaker 1: Heard around the world on the I Heart Radio app,

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Speaker 1: Apple Podcast or wherever you get your podcast. It's Cannabis

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Speaker 1: Talk one on one with Blue and Joe Grande. Hello,

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Speaker 1: welcome to Cannabis Talk one on one, the world's number

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Speaker 1: one source for everything cannabis. My name is Blue. Along

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Speaker 1: Sideham is Mr Joe Grande. Thank you guys all for

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Speaker 1: listening to the podcast Cannabis Talk one oh one, all

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Speaker 1: around this beautiful world of argy. Guys, it's so good.

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Speaker 1: Make sure you check out the website Cannabis Talk one

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Speaker 1: on one dot com is we are the world's number

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Speaker 1: one source for everything cannabis. We've got so many great

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Speaker 1: articles and blogs on our website and make sure you

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Speaker 1: call us up anytime. Check out the i G pages

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Speaker 1: at Cannabis Talk one on one. Blue was at one,

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Speaker 1: Christopher writes and I am at Joe Grande fifty two.

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Speaker 1: And if you're looking for a trusted cannabis SA at

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Speaker 1: a fair price, you know where you need to go, folks,

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Speaker 1: Rocket seeds dot com or on Instagram at rocket Underscore

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Speaker 1: Seeds and big shout out to Rocket Seeds for going

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Speaker 1: out there for Trees Festival and have much of time

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Speaker 1: with us out there on the show today. Three smart guys,

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Speaker 1: blue smart guys when I smart guys or three not one,

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Speaker 1: not too but three very smart gentleman not tall Pertensky.

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Speaker 1: Did I get that right? Yeah? That's pretty good. Actually, wow, okay,

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Speaker 1: I feel impressed right now. By I'm impressed. How do

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Speaker 1: you say that? If it was your mother was yelling

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Speaker 1: at you, how do you get yells? My mom actually

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Speaker 1: just calls me. How does the name like this get

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Speaker 1: because me it was jose They didn't say your middle name, Joseph. Yeah,

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Speaker 1: you're right, Joseph Fray. Yeah, it was either Joseph Lope

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Speaker 1: or Joseph Fray exactly. So my point is, how does

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Speaker 1: it name like that get yelled at? And what culture

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Speaker 1: is it? Uh? The name is actually Mayan Mayan. Yeah,

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Speaker 1: my mom's a born in Mexico. Okay, so it's hardcore Mexican,

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Speaker 1: a little bit tack out on. She never says my

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Speaker 1: last Well. This guy, you guys, is the founder in

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Speaker 1: the CEO of Sordine Robotics, Inc. Next to him is Andrew.

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Speaker 1: Well is a nice normal name that nobody needs to

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Speaker 1: talk about, which is nice and cool. The chief of

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Speaker 1: staff of Sorting Robotics Inc. Sorry Andrew, your parents weren't

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Speaker 1: as cool as natal as you know what I mean,

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Speaker 1: they weren't in Mexico like that. And Ben are you guys?

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Speaker 1: I don't know if it's a joke on me or

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Speaker 1: what's gonna how do you say your last Reggy's another

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Speaker 1: mouthful of sales. That's a great one. Just to lead

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Speaker 1: into the conversation. Remember and this company Blue and everybody listening.

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Speaker 1: If you're heavery end of the cannabis production game or

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Speaker 1: even planning big things for your cannabis brands, you guys,

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Speaker 1: you're gonna want to sit down and listen to this

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Speaker 1: company because our next guest, these three gentlemen you just heard,

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Speaker 1: have something up there sleeve that I really am impressed

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Speaker 1: with and I want to know more about. Natal is

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Speaker 1: the founder and CEO Sorting Robotics, Inc. A premier tech

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Speaker 1: company building the future hardware and software for the cannabis

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Speaker 1: industry now. Sorting and Robotics specializes in the robotics computer vision,

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Speaker 1: an artificial intelligence that provides cannabis brands and processors valuable

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Speaker 1: solutions to their everyday problem. Whether you're a cannabis brand

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Speaker 1: or grower or co packer let sorting robotics and help

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Speaker 1: you increase your production efficiencies and reduced labor costs. And

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Speaker 1: we're gonna hear all about how you can do that.

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Speaker 1: Ladies and gentlemen, please give a warm welcome to all

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Speaker 1: these gentlemen right here, Ben and you and at all

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Speaker 1: the guys this company you have. How do you convinced

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Speaker 1: nat all like I'm gonna get into this robotic game

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Speaker 1: in the cannabis game. Were you doing robotics and something else?

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Speaker 1: Like how do you specialize it for cannabis? Uh, let's

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Speaker 1: see what we were doing robotics in e commerce industry before.

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Speaker 1: Uh kind of targeting a very small market in uh

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Speaker 1: in like the trading card space. And then we wanted

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Speaker 1: to find a larger market after going through a something

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Speaker 1: called accelerator program called White Combinator, And in that program

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Speaker 1: we kind of we're looking for a bigger market to

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Speaker 1: tackle and we all smoked weed and we all like

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Speaker 1: we're in California and we're just like yeah. And then

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Speaker 1: we we knew some people that were in the cannabis space,

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Speaker 1: and um, when we were asking them along with a

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Speaker 1: bunch of other people, like what what should we build

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Speaker 1: and like, dude, you should just build anything. Everything is

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Speaker 1: done by hand, and everything's like coming out of the

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Speaker 1: like the legacy market, and people are just trying to

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Speaker 1: like pack joints by hand and do all these things hand,

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Speaker 1: just to just build anything. We're like, Okay, this seems

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Speaker 1: like a cool idea. And so it's kind of we

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Speaker 1: transition in a little like kind of the cliff notes

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Speaker 1: of what that was, Like, what was the Yeah, what's

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Speaker 1: the what's the first project that you ended up building?

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Speaker 1: The first thing we ended up building was. Before we

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Speaker 1: go into that, let's go into your history, my background.

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Speaker 1: What's your background? So my background, Um, I used to

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Speaker 1: work at NASA, the Jet Propulsion Laboratory in Pasadino. Yeah,

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Speaker 1: so I worked there the TAN up there in the

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Speaker 1: mountains right exactly exactly where it's at. Yeah, spot, I've

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Speaker 1: been up there. It's fired. Did you go to the

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Speaker 1: open houses? Never? I just know where it's located, and

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Speaker 1: I was never fortunate enough to pass the gate. I've

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Speaker 1: only went to the gate. Then let you in. No,

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Speaker 1: Joe Grinded didn't get past a Lopez, Yeah exactly, really

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Speaker 1: a Lopez that he didn't pass surveillance. Uh. Yeah, so

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Speaker 1: I was there for almost four years working on a

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Speaker 1: device that's currently on the surface of Mars producing oxygen. Fantastic. Yeah,

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Speaker 1: so I was, what's your degrees from dog? What you're

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Speaker 1: backing like that? How do you work at NASA and

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Speaker 1: have something that's on Mars right now? Then thank you

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Speaker 1: for coming to the nava's talking to you right now.

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Speaker 1: Uh so, Yeah, I have a master's degree in aerospace

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Speaker 1: engineering and an undergrad and mechanical and aerospace engineering and somewhere.

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Speaker 1: Master's degree was Georgia Tech, and then undergrad was u C.

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Speaker 1: Davis in California. Nice. And then how do you get

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Speaker 1: a job at NASHA? Do you find that on indeed?

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Speaker 1: Like do you get recruited? Like who gets hired? And

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Speaker 1: how do you get hired at show up and fill

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Speaker 1: out an application? Joe? Is it that sample? I don't know. Well,

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Speaker 1: you want the good story, like the real story, So

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Speaker 1: I'll give you the good one first yea. So basically

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Speaker 1: I was so chill. They're like, yo, I need you,

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Speaker 1: and then they told my advisor, we need the best

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Speaker 1: person in your team and then they picked me. Yeah,

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Speaker 1: that was a good story. So the real story was like, yeah,

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Speaker 1: I just applied yeah. Yeah, like, uh yeah, Georgia Tech's

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Speaker 1: the funnel school for GPL, and so um, if you

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Speaker 1: go to JPL about and the mechanical engineering department, like

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Speaker 1: five percent of that engineering department is from Georgia Tech.

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Speaker 1: So it's like a grooming school. And UM I was

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Speaker 1: in uh like one of the fanciest um research labs.

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Speaker 1: It was like one of the largest labs in the

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Speaker 1: country for aerospace systems design and um they always go

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Speaker 1: there and they interview like the top candidates of the lab.

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Speaker 1: And at that point, I already started a company, like

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Speaker 1: a desktop three D printing company, so they kind of

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Speaker 1: like people that have a very i'd breath and not

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Speaker 1: very specific and UM yeah I just had shown that

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Speaker 1: Uh yeah I built you. Yeah, yeah, you can move

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Speaker 1: into the cannabis industry turned around makes something to create

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Speaker 1: oxygen on the moon. Yeah, I mean that's I think

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Speaker 1: that's what they had in mind. Yeah, it's fantastic and

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Speaker 1: it worked. No, it did work. Actually, they just released

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Speaker 1: a journal article UM JPL did last week about UM

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Speaker 1: the michig success for MAXI, which is the dump your name. No,

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Speaker 1: there's actually no engineers on that journal article. It's all

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Speaker 1: the scientists, But do they give it up to do

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Speaker 1: you guys all talk on like a group chat like

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Speaker 1: it's still going good or it's blown up. We got

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Speaker 1: an email chain, yeah yeah, yeah, Actually most of the

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Speaker 1: team doesn't even work at GPL anymore. They all worked

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Speaker 1: at like, like a few of them are at um

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Speaker 1: Planet Sciences and a few of them went to Blue Origin.

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Speaker 1: And yeah, usually people say at JPL, and it depends

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Speaker 1: if they like the culture or not. But um, yeah,

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Speaker 1: and then what the so so so you guys were

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Speaker 1: smoking some cannabis one day and said, damn, let's create something.

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Speaker 1: And what was it? Boom? So the first thing that

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Speaker 1: we did in the cannabis industry was a biomass sortation system. Sortation, okay, sortation.

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Speaker 1: So you guys ever see on Reddit that, um those

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Speaker 1: like tomato sorters where they're like falling off a conveyor

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Speaker 1: and in super high speed they're shooting out the bad

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Speaker 1: ones and keeping the good ones. So we did that

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Speaker 1: but for weed, so it keeps the nags shoots stams

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Speaker 1: does Yeah. Yeah, basically we'd get biomass and it would everybody. So, yeah,

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Speaker 1: what do you make that? Though obviously you made the

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Speaker 1: prototype first yea on paper, Uh not really. So it's

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Speaker 1: a pretty complicated computer vision algorithm. So what we did initially,

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Speaker 1: like the very first thing that we did is like

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Speaker 1: we didn't know really like anything about the production of

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Speaker 1: weed at that time. Like we were just like stoner

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Speaker 1: Ston We were like smoke weed and yeah, they're like, yeah,

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Speaker 1: we know what it's like. Um. So then we went

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Speaker 1: to a facility this is back in, went to facility,

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Speaker 1: took a bunch of pictures of weed and built on database,

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Speaker 1: and then trained a neural network on that weed to

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Speaker 1: recognize like what weed looks like compared to what a

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Speaker 1: stem looks like and compared what a flower looks like. Yeah,

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Speaker 1: that's from your guys' own weed. That's how you train

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Speaker 1: the computer to look. Initially, we trained it on like

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Speaker 1: a pound of weed, and then once we got like

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Speaker 1: a prototype working and we started running through more of it,

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Speaker 1: and then we're like, oh, we can get this hemp stuff.

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Speaker 1: And it's back in twenty nineteen. We're still learning, right

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Speaker 1: and um. And so then we started training it on

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Speaker 1: hemp and then we deployed it to a facility in Humble,

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Speaker 1: and we started going through like tens of pounds a day,

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Speaker 1: just like sorting through and training the network, and eventually

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Speaker 1: we got it so good we could tell the difference

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Speaker 1: between phenotypes, so like the difference between strains, Like it

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Speaker 1: would be like, oh, like this one's like tighten o G.

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Speaker 1: This one's like strawberry cup. So we could separate it

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Speaker 1: like from biomass. So it's like we were getting trim,

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Speaker 1: like hand trim or something like that. You want to

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Speaker 1: get all the smalls out of it. Instead of you know,

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Speaker 1: going by hand and kind of like shaking it out,

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Speaker 1: you put into the machine and it would just do

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Speaker 1: it automatically, and it was that saves a lot of time,

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Speaker 1: a ton of time. Yeah, I mean we're able to

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Speaker 1: have one person run through like a hundred pounds a day.

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Speaker 1: So these portable machines, like you pull up on it

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Speaker 1: now you're huge. It was about the size of this table.

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Speaker 1: And you guys built it. Yeah, we built it. We

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Speaker 1: built a couple actually, so so what did that cost

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Speaker 1: to build something like that? It was like a million bucks? Nice? Yeah,

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Speaker 1: so you guys, you guys pulled it around the funding. Yeah,

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Speaker 1: so at the end of twenty after we had this

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Speaker 1: thing working, we're like, yeah, you know, we know we're

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Speaker 1: doing this computer vision, this AI. We want to start

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Speaker 1: building more for canvas manufacturers. We raised a few million

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Speaker 1: dollars out of Demo Day, which was that startup Accelerator

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Speaker 1: program and UM and then we started focusing a lot

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Speaker 1: on specifically cannabis manufacturers in and is it? Is it

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Speaker 1: right now? Are you feeling? Is it? Are you guys

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Speaker 1: you have companies using your your pode types or is

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Speaker 1: it full production where we at? So for the hold on,

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Speaker 1: hold hold that thought. We come back. It's Cannabis Talk

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Speaker 1: one on one. Well, right back up to this bright Yes, sir,

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Speaker 1: We'll be right back with Cannabis Talk one oh one.

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Speaker 1: Welcome back to Cannabis Talk one oh one. What time

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Speaker 1: is it? Dime times right? Think higher with diameon Industries.

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Speaker 1: Folks find him in California, Arizona and Oklahoma. Check out

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Speaker 1: the website diame Industries dot com and on Instagram Dime

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Speaker 1: dot industries and shout out to everybody over there at

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Speaker 1: Dime Man. We had a great burning trees festival. The

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Speaker 1: website Sorting Robotics dot com. That's all blue. Asked you

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Speaker 1: a question before we went to break. I couldn't wait

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Speaker 1: to hear your answer because I sit here and hear

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Speaker 1: everything that you say. And I know Blue and I

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Speaker 1: we geek out on people like you, like get into

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Speaker 1: cannabis space, Like I don't like geek, Like I look

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Speaker 1: at you like Snoop Dogg. You know what I'm saying,

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Speaker 1: Like to me, you're the level because you're the celebrity

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Speaker 1: in my book, like in my head dog. You just

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Speaker 1: said what you created is like celebrity status in my book.

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Speaker 1: Like what you said you created that's going to help

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Speaker 1: people like that, that's phenomenal. And A Blue asked you

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Speaker 1: a question before we went to bread. Blue said exactly, Blue,

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Speaker 1: go ahead read business said, like, you know, is it

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Speaker 1: in prototype still or is this is this actually you know,

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Speaker 1: um in full operation in different facilities. So the thing

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Speaker 1: that I mentioned the first one, that one we actually

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Speaker 1: just shelved because it was the first one that in

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Speaker 1: that project. We're like, okay, that's you know, it's an

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Speaker 1: interesting thing. It does, it does a lot of value, right,

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Speaker 1: But what we really want to focus on was cannabis

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Speaker 1: manufacturing because that's where it seems like there's not good

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Speaker 1: solutions and it's very complicated. Uh So what we started

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Speaker 1: focusing on after that was actually on the perial side

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Speaker 1: and specifically perial infusion. So now we have a robot

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Speaker 1: that actually injects pre rolls and then you can inject

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Speaker 1: in live rosin and make a column of ross. The

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Speaker 1: whole slides it up easier, Yeah, way easier. So, like

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Speaker 1: if you have settings all correct and you have some

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Speaker 1: good flour, then you can kind of like automate the

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Speaker 1: production of hashols. Fantastic. Yeah, that's a smart Have you

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Speaker 1: tried that with the burning though, like how well it burns,

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Speaker 1: because obviously you're you know, you're talking about how much

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Speaker 1: you put through the center first, you know, in order

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Speaker 1: to allow to have that certain you know, threshold of burn,

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Speaker 1: because if it burns, if it's too thick, it'll be

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Speaker 1: probably it'll burn, you know, not properly. If it's too thin,

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Speaker 1: it probably won't do anything, you know. So it actually

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Speaker 1: improves the way the joint burns. And that's because you

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Speaker 1: kind of change the thermodynamics of how exactly. So instead

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Speaker 1: of the joint normally burning from the outside in, where

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Speaker 1: it's like kind of burning the paper than the flower,

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Speaker 1: it's really burning from the inside out because now you

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Speaker 1: have this fuel rod from the center of candle. Yeah,

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Speaker 1: so it's a wick. Yeah, it's like a wick, right,

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Speaker 1: so it kind of reduces the chances of getting running

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Speaker 1: and stuff like that. I mean, obviously, if you pack

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Speaker 1: it like shit, it's it's gonna run, right dude. But

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Speaker 1: if you're putting good stuff, yeah, is this working? Yeah?

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Speaker 1: We have like we have almost thirty machines in the

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Speaker 1: United States and Canada. People oh yeah, people using okay, yeah, yeah, yeah,

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Speaker 1: that's swift. That's hot. I like that, And that's why

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Speaker 1: you have the whole team here, bands out there, the director,

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Speaker 1: I mean, come on that team now, well, you know,

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Speaker 1: and to hear what you got into Hero describes it.

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Speaker 1: That's is that the main machiner? Do you guys thinking, like,

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Speaker 1: what kind of commissions do I get that? I'm like

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Speaker 1: Martha Stewart though, whisper in there. I know everybody like

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Speaker 1: this stuff is hot. Hey, he's got a machine right there?

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Speaker 1: Is that the Is that the final thing you guys

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Speaker 1: have right now? You know? That was like the first

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Speaker 1: thing that we did. So we started that one last

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Speaker 1: year and then after we noticed, you know, we're pretty

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Speaker 1: good at this whole robot stuff, Let's make another one

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Speaker 1: and so we did a high throughput, high precision cartridge

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Speaker 1: filling machine. And so there's a bunch of a cartridge

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Speaker 1: only machines and they're kind of all over the place

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Speaker 1: and and so we're kind of we got approached by

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Speaker 1: a group that does big cartridges at scale and they're like, oh,

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Speaker 1: you need to make a better and like why, like

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Speaker 1: there's so many of these other ones. When you actually

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Speaker 1: look at those machines, they're just taken from the medical

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Speaker 1: device industry, like for tight trating chemicals, and they just

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Speaker 1: throw heat around it and they're like that will work

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Speaker 1: for show, but it doesn't. It doesn't work very well,

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Speaker 1: and um, you can't go very fast. They're not very precise.

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Speaker 1: And so then we built a machine that with one

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Speaker 1: person you can fill and cap thirty cartridges in a

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Speaker 1: single day, and you can do it with the zero

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Speaker 1: point two percent precision. So like so that brings your

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Speaker 1: cost down drastically, dramatically, And then if you're in a

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Speaker 1: state where distal it's ten tho dollars a leader, it's

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Speaker 1: a big difference. If you lose four percent, then if

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Speaker 1: you lose zero point two for sure, Yeah, and is

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Speaker 1: everybody using that already too, so this one yeah, so

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Speaker 1: this one's new. We launched at the beginning of this quarter.

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Speaker 1: We got a couple in Canada, a couple of California.

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Speaker 1: You guys here, how yeah, I love the people. Well,

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Speaker 1: he knows, he knows that he's doing this guy's you got?

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Speaker 1: So how much are these machines? What are they hip for? Like?

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Speaker 1: Who buys them? Mostly COO packers, packers and large brands.

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Speaker 1: I just want to tell everybody that's watching. I picked

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Speaker 1: this shirt on before Joe picked is on today. I'm

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Speaker 1: looking at it on screen, I'm like, dude, oh my god,

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Speaker 1: I realize Hold on a second. That's what's funnier. People

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Speaker 1: think we're brothers all the time too, or like you

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Speaker 1: guys related. Oh that's so cute, you guys. I really

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Speaker 1: like what you guys are doing. What is the market saying, like,

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Speaker 1: is it going to be something that you guys are

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Speaker 1: doing so quickly? Is it going to be adopted by governments?

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Speaker 1: I mean I feel like what you're saying, you're coming

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Speaker 1: from NASA, right, So you're coming from a standard. Well,

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Speaker 1: you're making products that are on the fucking moon. Literally,

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Speaker 1: sorry my bad. A little further exactly yours is on Mars,

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Speaker 1: and so therefore you have to think of ship that's

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Speaker 1: that far in advance. So I would imagine that your

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Speaker 1: machines are so far to par beyond whatever part is excited,

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Speaker 1: because let's face it, there's nothing that's regulated right now.

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Speaker 1: What you guys are doing, you guys maybe setting the

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Speaker 1: standard of what should be really out there and legally

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Speaker 1: exposed in the cannabis space, right, I mean, think about it,

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Speaker 1: because it's not regulated yet. It's not like you said,

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Speaker 1: the medical field. Medical fields regulated. Those machines are regulated.

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Speaker 1: You can't just fucking make a machine and think you're

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Speaker 1: gonna do a robotic surgery because you're mr. You know

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Speaker 1: what picked the machine, the Da Vinci machine whatever, you

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Speaker 1: know what I mean, you can't do that unless you're certified.

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Speaker 1: So you guys are gonna be able to set a

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Speaker 1: new standard. I think we're gonna see some big things

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Speaker 1: from this type of company. Well, uh, because I don't

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Speaker 1: know if you have a Yeah, that's what. And so

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Speaker 1: that being said, are you working with governments to try

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Speaker 1: to get well, that's why I was leading to because

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Speaker 1: I think you're setting standard. Are you setting a standard

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Speaker 1: to working with government to try to place that standard

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Speaker 1: in action. I mean, it's definitely on the plan. That's

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Speaker 1: something that we talked about all the time, especially on

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Speaker 1: the more medical device instead of government. You know, the

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Speaker 1: government has to go to medical device to concept. Okay,

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Speaker 1: got you, but you have to go through medical like trial, right,

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Speaker 1: because I think where you guys can actually go, you know,

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Speaker 1: really big is creating a standard that the federal you know, yes,

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Speaker 1: right because once you get that federal plaque, I mean,

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Speaker 1: you know of of production level and I don't know

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Speaker 1: if that you guys are going to go there or

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Speaker 1: just make your fortune in the smaller operators, right, because

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Speaker 1: there's a lot of and I say smaller because you know,

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Speaker 1: let's face it, even our big operators in the cannabis

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Speaker 1: industry or small operators like I know, I mean I

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Speaker 1: look at this and I'm like, yeah, you know, we're

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Speaker 1: we're a small fucking business. And even if they are

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Speaker 1: close to Coke Cola, they're not called cola, you know

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Speaker 1: what I mean, like like at their one facility maybe

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Speaker 1: you know when cold Cole is like yeah, we're you know,

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Speaker 1: we have those all over every country. Yeah, so um,

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Speaker 1: but but I think you know the point is the

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Speaker 1: new product line right now? So what are we calling

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Speaker 1: this monster? So the new product lines called the Omnifiller okay, yeah,

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Speaker 1: and then the infusion machine is called the Jico Infusion Robot,

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Speaker 1: and that the new one is the Omnifiller. Yeah, that's

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Speaker 1: the one that we just dropped this quarter. And you

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Speaker 1: guys have photos and stuff like that. Yeah, I mean, yeah,

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Speaker 1: if you love this is the second time you made

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Speaker 1: it past at me bro just a little bit. What's on?

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Speaker 1: And then this young man next to you, what is it? Andrew? Yes?

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Speaker 1: How you doing? So? What exactly are you doing over

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Speaker 1: there at the company? The chief of staff? Huh yeah,

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Speaker 1: So I work with the Tall. We actually share an office.

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Speaker 1: Um so I handle basically business operations, so everything that

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Speaker 1: the Tall doesn't do, I basically do. Nice. Yeah, so

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Speaker 1: I'm involved in marketing operations, just the degree ales. Yeah yeah.

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Speaker 1: And how long you've been with them? Uh? Eighteen months? Nice?

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Speaker 1: You enjoyed it? Yeah? Yeah. Do you see the big

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Speaker 1: picture of the big vision? Yeah? Yeah, going into it,

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Speaker 1: I mean that's that's what really attracted me. And when

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Speaker 1: I started talking to the guys and uh really seeing

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Speaker 1: the team and how they you know, kind of work together.

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Speaker 1: I was like, oh, yeah, this is this is cool

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Speaker 1: and it's in wheat and my background I say, cannabis

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Speaker 1: around here, yeah Canada, but marijuana. Yeah, And so like

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Speaker 1: I was, I was my backgrounds in the wine industry,

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Speaker 1: so I saw a lot of parallels between the two industries.

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Speaker 1: And so I was like, oh, this is this is cool.

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Speaker 1: And my undergrad degrees in biology, so I kind of

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Speaker 1: get some of the you know, high falutant aerospace concepts

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Speaker 1: that go around the the office. But yeah, it's a

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Speaker 1: big words are just flying around, like what the fund did?

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Speaker 1: He just say? Yeah, I just I just not, yeah,

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Speaker 1: totally get that. Yeah, well what do you call it?

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Speaker 1: Frank uhcticals? Fractals? I was like, I've heard of fractals,

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Speaker 1: but what is a fractal? What anybody here know what

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Speaker 1: a fractal? List other than the guy that just educated

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Speaker 1: me today is a fractal? Yeah, it's all telling what

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Speaker 1: a fractless. It's good for America. It's a continuously repeating

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Speaker 1: mathematical pattern that most of nature um exhibits in behavior

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Speaker 1: like tree leaves and the way trees grow and the

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Speaker 1: way seashells grow, like your our neighbor, right, you know,

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Speaker 1: of course everything is in that any OUTI thing. We

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Speaker 1: were talking to him about that, and then I was

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Speaker 1: just winding fractals. Sounds like practical. The smartest ones know

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Speaker 1: it's crazy. It is really crazy. And then Ben, how

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Speaker 1: did you come around? What are you doing there? So

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Speaker 1: titles director of sales, but I've kind of taken over.

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Speaker 1: So up until this point, before I came on, was

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Speaker 1: the one doing sales, biz dev channel partnerships or chief partnerships.

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Speaker 1: When you're the CEO and you're know a little further

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Speaker 1: than a start up stage, you do all the sorts

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Speaker 1: of things. Uh, to the point now where he needed

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Speaker 1: somebody to come over and take over that so you

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Speaker 1: can focus on the things that needed to be focusing on.

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Speaker 1: So I have been on board. This is actually my

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Speaker 1: official tent day on the job. And they put you

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Speaker 1: on the show, and they put me on the show.

422
00:22:19,680 --> 00:22:22,040
Speaker 1: I've been Uh, I've been in the industry since two

423
00:22:22,080 --> 00:22:25,320
Speaker 1: thousand and sixteen. I actually you mentioned clinical trials. I

424
00:22:25,440 --> 00:22:27,959
Speaker 1: got started working with companies that we're looking to take

425
00:22:28,040 --> 00:22:31,280
Speaker 1: medical devices or medicines to the market in a different industry.

426
00:22:31,320 --> 00:22:33,640
Speaker 1: But then they all were migrating into CBD and then

427
00:22:33,920 --> 00:22:37,119
Speaker 1: into cannabis. So that's how I got introduced. I mean,

428
00:22:37,119 --> 00:22:38,800
Speaker 1: I grew up in northern California. I went to school

429
00:22:38,800 --> 00:22:41,359
Speaker 1: at Berkeley. I've been around it my entire life as

430
00:22:41,400 --> 00:22:45,000
Speaker 1: far as a profession. That's how I got introduced at

431
00:22:45,040 --> 00:22:48,000
Speaker 1: Berkeley once and once in a while, maybe I could

432
00:22:48,320 --> 00:22:55,639
Speaker 1: maybe telegraph telegraph. That's not a good weed though some

433
00:22:55,760 --> 00:22:57,960
Speaker 1: people would think that was the best weed nowadays because

434
00:22:57,960 --> 00:23:01,119
Speaker 1: that new stuff is just blown. Like that's having that

435
00:23:01,240 --> 00:23:03,080
Speaker 1: good little weird that just got you a little high

436
00:23:03,160 --> 00:23:05,600
Speaker 1: now and shaking in a corner like what is that?

437
00:23:06,119 --> 00:23:08,680
Speaker 1: What is that? That's funny? So I grew up in

438
00:23:08,720 --> 00:23:10,199
Speaker 1: the Bay Area. You see a lot. I grew up

439
00:23:10,240 --> 00:23:12,440
Speaker 1: and I grew up outside of sacrament Open the polls,

440
00:23:12,880 --> 00:23:14,320
Speaker 1: and then went to school in the Bay Area. Yeah,

441
00:23:14,320 --> 00:23:16,760
Speaker 1: I've been around the industry quite a long time to

442
00:23:16,880 --> 00:23:19,200
Speaker 1: date myself. I was actually going to school there in

443
00:23:19,280 --> 00:23:24,200
Speaker 1: nine when prop to task and you know, big injection

444
00:23:24,280 --> 00:23:28,280
Speaker 1: of information and culture and all that. During that time,

445
00:23:29,080 --> 00:23:30,960
Speaker 1: I didn't I was gonna be a profession for myself.

446
00:23:31,000 --> 00:23:32,760
Speaker 1: But um, once I got into it, I was never

447
00:23:32,840 --> 00:23:35,200
Speaker 1: looking back. Yeah, Berkeley is one of those schools where

448
00:23:35,200 --> 00:23:37,480
Speaker 1: you could think cannabis was a profession there you know

449
00:23:37,520 --> 00:23:39,520
Speaker 1: what I mean? Are like started because a lot of people,

450
00:23:39,600 --> 00:23:41,320
Speaker 1: just some of my roommates, it was a profession back

451
00:23:41,359 --> 00:23:43,400
Speaker 1: then for all of us. It was at some point

452
00:23:43,880 --> 00:23:46,000
Speaker 1: like if you're you know, if you smoked it, it

453
00:23:46,119 --> 00:23:47,800
Speaker 1: became a profession. Was like what you want to buy

454
00:23:47,800 --> 00:23:50,840
Speaker 1: some Yeah, it's definitely. We're gonna find out where this

455
00:23:50,920 --> 00:23:52,639
Speaker 1: company is going. You guys. You want to see him

456
00:23:52,680 --> 00:23:55,399
Speaker 1: online Swordium Robotics dot com. We come back. We got

457
00:23:55,480 --> 00:23:58,120
Speaker 1: the high five and see what direction and what's next.

458
00:23:58,160 --> 00:24:00,280
Speaker 1: I mean, we're gonna do cannabis on the moon. Are

459
00:24:00,320 --> 00:24:03,959
Speaker 1: on Mars Mars right find out it's Cannabis Talk one

460
00:24:04,000 --> 00:24:06,439
Speaker 1: oh one. We'll be right back with Cannabis Talk one

461
00:24:06,480 --> 00:24:21,920
Speaker 1: oh one. Welcome back to Cannabis Talk one oh one.

462
00:24:22,200 --> 00:24:24,920
Speaker 1: Advanced New Treats, you guys, they have a complete growing

463
00:24:25,000 --> 00:24:28,000
Speaker 1: system for cannabis that optimizes all phases and cycles to

464
00:24:28,040 --> 00:24:30,679
Speaker 1: bring your true crops with their true Janet potential. Discover

465
00:24:30,800 --> 00:24:33,360
Speaker 1: more and Advanced New Treats dot com and big ups

466
00:24:33,359 --> 00:24:34,879
Speaker 1: to Big Mike Man. I just talked to her the day.

467
00:24:34,880 --> 00:24:37,480
Speaker 1: He's like, Joe, how's your ankle? Just a real concerned

468
00:24:37,520 --> 00:24:40,280
Speaker 1: gentleman who who cares about me as a real person

469
00:24:40,400 --> 00:24:42,680
Speaker 1: like our friends we've known him for. I mean, you know,

470
00:24:42,800 --> 00:24:44,280
Speaker 1: I just love the man for asking me that the

471
00:24:44,280 --> 00:24:46,120
Speaker 1: first thing out of his mouth, like I don't really

472
00:24:46,160 --> 00:24:49,239
Speaker 1: appreciate exactly That's what I like, because the first thing

473
00:24:49,240 --> 00:24:51,040
Speaker 1: out of his mouth is how's your ankle? And to

474
00:24:51,119 --> 00:24:53,359
Speaker 1: think about that, I really want to thank Jan Erica,

475
00:24:53,480 --> 00:24:57,280
Speaker 1: Daniel cal Christian A Christian s Danny p Funk, Connor,

476
00:24:57,720 --> 00:25:03,360
Speaker 1: Gabriel Sagar, Jessica Cash, Kim Kimberly, Isaiah Salar, Nadia, Ali Pitt,

477
00:25:03,840 --> 00:25:07,720
Speaker 1: Devin Chris, Frank Kino. Of course our guy, Mr Mark Karnes,

478
00:25:07,800 --> 00:25:10,560
Speaker 1: Jennifer and Elvis for everything that you guys do around here,

479
00:25:10,640 --> 00:25:14,159
Speaker 1: Thank you so much. And sorting robotics dot com and

480
00:25:14,240 --> 00:25:16,520
Speaker 1: it's all Andrew and Bend. You guys are working your

481
00:25:16,560 --> 00:25:19,359
Speaker 1: ass off over there with these amazing products that are huge,

482
00:25:19,480 --> 00:25:22,360
Speaker 1: industrial sized things. At one point when I was looking

483
00:25:22,400 --> 00:25:24,000
Speaker 1: at the company, I was thinking you guys were like

484
00:25:24,119 --> 00:25:28,800
Speaker 1: sorting out products in the back for like making robotics

485
00:25:28,880 --> 00:25:31,240
Speaker 1: to like keep things in order or something like that.

486
00:25:31,359 --> 00:25:33,800
Speaker 1: You guys don't do anything like that, are you guys

487
00:25:33,840 --> 00:25:36,960
Speaker 1: getting into cutting the butt off plants as they're gonna

488
00:25:36,960 --> 00:25:39,600
Speaker 1: be robotics for that. Where are we seeing this company go?

489
00:25:40,200 --> 00:25:41,879
Speaker 1: They just made the new product line. I mean, I

490
00:25:41,960 --> 00:25:44,639
Speaker 1: know they're going. They're already moving somewhere else though. Welcome

491
00:25:44,680 --> 00:25:46,679
Speaker 1: back to the show, Joe. So so the new product

492
00:25:46,720 --> 00:25:49,720
Speaker 1: line that we're talking about, like, right, that that's gonna launch. Okay,

493
00:25:49,800 --> 00:25:52,400
Speaker 1: let's let's re launch launch lunch. It's alright, yeah, it's

494
00:25:52,480 --> 00:25:56,639
Speaker 1: it's launched. It's already launched. It just okay, they just

495
00:25:56,800 --> 00:25:59,639
Speaker 1: launched it. That's the big one. Then the infused one

496
00:26:00,000 --> 00:26:06,639
Speaker 1: and the other because exactly I got a few products

497
00:26:06,640 --> 00:26:09,080
Speaker 1: from you guys, the infuse joint one, right, and then

498
00:26:09,119 --> 00:26:11,880
Speaker 1: the shorter one that's okay, the sorting one that sorts

499
00:26:11,920 --> 00:26:14,000
Speaker 1: out all the cannabis, right, no, no, the sorts south

500
00:26:14,000 --> 00:26:16,800
Speaker 1: of cannabis was the first one, right, they discontinued it.

501
00:26:17,160 --> 00:26:20,080
Speaker 1: It's gone, right, that was their demo. Then they came

502
00:26:20,119 --> 00:26:22,720
Speaker 1: out with one that infused it down the middle, and

503
00:26:22,800 --> 00:26:25,679
Speaker 1: that one still good. That one's that in thirty stores,

504
00:26:25,760 --> 00:26:31,000
Speaker 1: thirty stores, right, thirty manufacturing companies many, I'm sorry, manufacturing companies. Yeah, uh,

505
00:26:31,119 --> 00:26:33,760
Speaker 1: And that's the one that infuses it right, which sounds amazing.

506
00:26:33,800 --> 00:26:36,280
Speaker 1: And then now there's a new device that does the

507
00:26:37,000 --> 00:26:42,520
Speaker 1: oils oils the oils one third right now and saves

508
00:26:42,560 --> 00:26:46,399
Speaker 1: three more. But it's you know, so amazing. It's like

509
00:26:46,880 --> 00:26:49,720
Speaker 1: ten times more precise. Usually vape cart fillers like to

510
00:26:49,800 --> 00:26:52,440
Speaker 1: quote like plus or minus five percent. We'll say plus

511
00:26:52,480 --> 00:26:55,760
Speaker 1: or minus is zero point five percent. Wo better, a

512
00:26:55,800 --> 00:27:00,720
Speaker 1: lot better, cleaner, super cleaner, way more like that. One's

513
00:27:00,760 --> 00:27:06,440
Speaker 1: called the Philly And because like when you started the show,

514
00:27:06,800 --> 00:27:10,320
Speaker 1: you said, well I remember that. But as you started

515
00:27:10,359 --> 00:27:12,240
Speaker 1: the show, when you talked to a friend of yours,

516
00:27:12,280 --> 00:27:16,240
Speaker 1: you said, get into anything. Your minds can go anywhere

517
00:27:16,400 --> 00:27:19,280
Speaker 1: in this game. Like that's what I'm saying, because you

518
00:27:19,400 --> 00:27:21,440
Speaker 1: can make up ship that that can make up something

519
00:27:21,480 --> 00:27:23,600
Speaker 1: that you don't even know could help this industry. Yeah,

520
00:27:23,640 --> 00:27:25,600
Speaker 1: we build stuff that doesn't exist. That's what I mean.

521
00:27:25,720 --> 00:27:27,680
Speaker 1: So what is that? Like, what's the next thing that

522
00:27:27,800 --> 00:27:29,879
Speaker 1: your mind's going, Well, we're kind of working on I

523
00:27:29,960 --> 00:27:33,879
Speaker 1: want to leak. I mean the big thing is concentrate production. Right.

524
00:27:34,240 --> 00:27:38,440
Speaker 1: Concentrate production is like still done by hand, and the

525
00:27:38,560 --> 00:27:41,040
Speaker 1: major concentrate like what you're talking about when you get dabs,

526
00:27:41,080 --> 00:27:43,480
Speaker 1: how do you think doesn't. Yeah, no, I get it. Yeah,

527
00:27:43,600 --> 00:27:45,240
Speaker 1: I know how, I know how it's made. I just

528
00:27:45,640 --> 00:27:49,560
Speaker 1: one at a time and they're just meanful. Yeah, so

529
00:27:49,840 --> 00:27:52,040
Speaker 1: what are you gonna do? What's your plan? Build a

530
00:27:52,080 --> 00:27:54,920
Speaker 1: dope pass or about that? Does it? Yeah? Yeah, that's it,

531
00:27:55,600 --> 00:27:59,600
Speaker 1: that's it. Yeah. Well they're already a dope ass robot

532
00:27:59,640 --> 00:28:02,600
Speaker 1: in in like you know, a different you know, extraction

533
00:28:02,680 --> 00:28:04,639
Speaker 1: world that you could just kind of piggyback off of.

534
00:28:05,720 --> 00:28:07,760
Speaker 1: I mean we've really done it. No, like just no

535
00:28:07,840 --> 00:28:10,920
Speaker 1: one's it's it's extremely difficult. We actually tried to do

536
00:28:11,040 --> 00:28:14,400
Speaker 1: it back in and then when we were going down

537
00:28:14,480 --> 00:28:16,440
Speaker 1: that path for a few months, we're just like, oh yeah,

538
00:28:16,480 --> 00:28:19,840
Speaker 1: this is fucking hard and so and and that was

539
00:28:19,880 --> 00:28:21,359
Speaker 1: the time when we had just raised money, so we

540
00:28:21,400 --> 00:28:23,800
Speaker 1: have to be very cognizant about like runaway and stuff

541
00:28:23,800 --> 00:28:25,440
Speaker 1: like that, and like how much this project was actually

542
00:28:25,440 --> 00:28:28,000
Speaker 1: gonna cost to do, and so they don't want to

543
00:28:28,080 --> 00:28:30,360
Speaker 1: just dump it. Then you're in a bad place. Yeah,

544
00:28:30,480 --> 00:28:32,119
Speaker 1: So we kind of started and did like an initial

545
00:28:32,200 --> 00:28:34,679
Speaker 1: discovery and we were kind of doing the Jico robot

546
00:28:34,720 --> 00:28:37,280
Speaker 1: at the same time, and so we're like, okay, like,

547
00:28:37,400 --> 00:28:39,440
Speaker 1: which one of these is more feasible for us to

548
00:28:39,520 --> 00:28:41,320
Speaker 1: develop and like, what do we have more access to?

549
00:28:41,440 --> 00:28:43,040
Speaker 1: Do we have more access to concentrate? Do we have

550
00:28:43,080 --> 00:28:44,720
Speaker 1: more access to pre roles? Like a lot of like

551
00:28:44,800 --> 00:28:48,480
Speaker 1: you know programmatic stuff, right, yeah, And so it's going

552
00:28:48,520 --> 00:28:51,720
Speaker 1: to hit exactly. And so then now we're coming back

553
00:28:51,760 --> 00:28:54,080
Speaker 1: to like concentrates and I think that's gonna be a

554
00:28:54,160 --> 00:28:56,080
Speaker 1: big thing. And uh we already have like a few,

555
00:28:56,680 --> 00:28:58,479
Speaker 1: uh some of our current customers that are like, yo,

556
00:28:58,840 --> 00:29:01,520
Speaker 1: I will pay you to do today We're like, all right, well,

557
00:29:01,600 --> 00:29:03,640
Speaker 1: like we gotta just do it ta get it down.

558
00:29:04,120 --> 00:29:07,280
Speaker 1: So so that the new one, the fillers, I do

559
00:29:07,360 --> 00:29:08,640
Speaker 1: want to see him. I wish I would have seen

560
00:29:08,680 --> 00:29:10,200
Speaker 1: them more BREA because it would give me a bigger

561
00:29:10,640 --> 00:29:13,040
Speaker 1: like just understanding of how many producers at a time.

562
00:29:13,080 --> 00:29:16,880
Speaker 1: It's a hundred that's a small amount. Actually it's a

563
00:29:16,960 --> 00:29:20,400
Speaker 1: hundred in a minute, a hundred minute. It feels a

564
00:29:20,480 --> 00:29:23,640
Speaker 1: hundred every while, So they'll put that perspective. It takes

565
00:29:24,040 --> 00:29:27,160
Speaker 1: uh one person an hour to do a hundred by hand.

566
00:29:27,280 --> 00:29:30,440
Speaker 1: You're crushing it. Yeah, yeah. And then does it box

567
00:29:30,560 --> 00:29:32,880
Speaker 1: them too? It doesn't box them. That's another thing. So

568
00:29:33,000 --> 00:29:34,960
Speaker 1: like when that's the next stage. Yeah, it's another like

569
00:29:35,200 --> 00:29:38,480
Speaker 1: there's that would be the ultimate like ko right, yeah,

570
00:29:38,520 --> 00:29:40,520
Speaker 1: because then you own it the whole way through. Right,

571
00:29:40,680 --> 00:29:42,320
Speaker 1: You're like, okay, well, I can give you the cards,

572
00:29:42,320 --> 00:29:44,480
Speaker 1: I give you the oil, I can fill it, I

573
00:29:44,520 --> 00:29:48,120
Speaker 1: can cap them, I can put into boxes. Now we

574
00:29:48,200 --> 00:29:52,040
Speaker 1: open up up a back section here to start producing it,

575
00:29:52,360 --> 00:29:54,520
Speaker 1: and then throw a couple of robots. Yeah yeah, the

576
00:29:54,640 --> 00:30:00,840
Speaker 1: robots stop, and then and then we quickly the scale

577
00:30:00,880 --> 00:30:03,920
Speaker 1: into a massive facility. Yeah yeah, I like that. You

578
00:30:03,960 --> 00:30:07,840
Speaker 1: don't need as many people need like five, right, and

579
00:30:08,000 --> 00:30:10,440
Speaker 1: and some warehouse space because you're gonna have a lot

580
00:30:10,480 --> 00:30:13,760
Speaker 1: of production and probably saving costs. But is that going

581
00:30:13,800 --> 00:30:16,240
Speaker 1: to be cheaper than you know? Uh well, I guess

582
00:30:16,280 --> 00:30:19,240
Speaker 1: then where do you get the material? So where would

583
00:30:19,240 --> 00:30:22,760
Speaker 1: you buy the material for that, the material to build

584
00:30:23,320 --> 00:30:27,920
Speaker 1: to fill the box the box, like the actual box,

585
00:30:28,200 --> 00:30:31,080
Speaker 1: the actual boxes themselves. I don't know, Andrew, this is

586
00:30:31,120 --> 00:30:33,920
Speaker 1: your thing. Where do we buy the packaging? There's the

587
00:30:34,000 --> 00:30:36,680
Speaker 1: packaging is probably the easiest part of you buy in China,

588
00:30:36,760 --> 00:30:38,960
Speaker 1: then you have it here in the robot folds it

589
00:30:39,040 --> 00:30:41,160
Speaker 1: together and China. No, I mean we can buy it

590
00:30:41,480 --> 00:30:43,720
Speaker 1: source it here in Orange County actually, there's a company

591
00:30:43,920 --> 00:30:47,000
Speaker 1: um that does packaging. They have a facility that they

592
00:30:47,080 --> 00:30:49,880
Speaker 1: make folded cartons here. Yeah. No, but I'm saying we

593
00:30:50,120 --> 00:30:51,920
Speaker 1: want to be able to package it, right that the

594
00:30:52,360 --> 00:30:56,040
Speaker 1: you know, from from start to finish with your machinery.

595
00:30:56,360 --> 00:30:59,200
Speaker 1: Yeah right, that makes you unique. Right now, all of

596
00:30:59,200 --> 00:31:00,959
Speaker 1: a sudden, you're just saying, here it is, and you're

597
00:31:01,000 --> 00:31:04,000
Speaker 1: packaging for everybody, and you've gotta you know, you know

598
00:31:04,320 --> 00:31:07,440
Speaker 1: income you know, revenue machine. Oh yeah, yeah, I mean

599
00:31:07,520 --> 00:31:11,160
Speaker 1: that's what you know. Natal's uh, you know, ideated through

600
00:31:11,360 --> 00:31:14,040
Speaker 1: is building out every piece of that step in a

601
00:31:14,160 --> 00:31:16,479
Speaker 1: production process. Is that the goal you plan on doing

602
00:31:16,520 --> 00:31:18,480
Speaker 1: something like that? Or yeah? I mean the goal is

603
00:31:18,520 --> 00:31:20,680
Speaker 1: to do that both in like the vape card, the

604
00:31:20,920 --> 00:31:24,560
Speaker 1: pre roles, the concentrates, and then continue on. I mean

605
00:31:24,680 --> 00:31:27,520
Speaker 1: even like there's possibility is to do like automation robotics

606
00:31:27,680 --> 00:31:30,280
Speaker 1: in delivery as well. Right right now, what do they

607
00:31:30,320 --> 00:31:32,840
Speaker 1: do in delivery? This pick and pack? But Amazon doesn't

608
00:31:32,880 --> 00:31:35,760
Speaker 1: do that, right, Amazon's got robots doing everything. You know,

609
00:31:35,840 --> 00:31:37,840
Speaker 1: maybe Ease is big enough to do it. Probably not,

610
00:31:38,160 --> 00:31:41,360
Speaker 1: but in a few years they will be. Eventually, the

611
00:31:41,520 --> 00:31:44,080
Speaker 1: industry is going to be mature enough that it can

612
00:31:44,120 --> 00:31:47,640
Speaker 1: adopt these like kind of classical methodologies of doing business,

613
00:31:48,200 --> 00:31:51,400
Speaker 1: and it's so highly regulated that a lot of these

614
00:31:51,480 --> 00:31:55,440
Speaker 1: kind of traditional robotics companies don't even want to mess

615
00:31:55,520 --> 00:31:57,720
Speaker 1: with it. And so that's where we're comming. You're go

616
00:31:57,800 --> 00:32:00,320
Speaker 1: into m J biscon, I'm MJ, I'm packed. Do you

617
00:32:00,360 --> 00:32:03,480
Speaker 1: want any of these? Both both of them yet pitching

618
00:32:03,520 --> 00:32:06,520
Speaker 1: a m oh good for you, dude, nice dude, nice,

619
00:32:07,440 --> 00:32:09,440
Speaker 1: of course. I think we have one of the biggest

620
00:32:10,200 --> 00:32:13,280
Speaker 1: boo booths there. Yeah. Cool, Yeah, we actually have a huge,

621
00:32:13,400 --> 00:32:17,840
Speaker 1: massive footprint with advanced nutrients. I believe it's gonna be

622
00:32:18,000 --> 00:32:22,760
Speaker 1: rocket seeds, uh, Kelly effects or uh was it a

623
00:32:22,920 --> 00:32:29,280
Speaker 1: spirit right now, Larry Flint, they're not they're not confirmed yet,

624
00:32:29,320 --> 00:32:31,400
Speaker 1: but these are on my list. Yeah, we're actually gonna

625
00:32:31,440 --> 00:32:33,240
Speaker 1: have a big dinner out there with a lot of

626
00:32:33,280 --> 00:32:36,560
Speaker 1: the companies stuff. We were really well, we can discuss that,

627
00:32:36,680 --> 00:32:39,600
Speaker 1: you know, so I think you might make a little

628
00:32:40,400 --> 00:32:50,400
Speaker 1: We can certainly discussed that. But you know, yeah, listen, guys,

629
00:32:50,480 --> 00:32:53,600
Speaker 1: what is it that that you know? You know, ultimately

630
00:32:53,680 --> 00:32:56,800
Speaker 1: you're very intelligent, man um. I actually really look at

631
00:32:56,840 --> 00:32:59,480
Speaker 1: your guys team right now, and I see it. I

632
00:32:59,560 --> 00:33:03,360
Speaker 1: see the you're probably your method of madness of how

633
00:33:03,440 --> 00:33:05,959
Speaker 1: it goes and how these guys are working with you. Um,

634
00:33:06,680 --> 00:33:09,080
Speaker 1: and then you know, where are you guys going in

635
00:33:09,280 --> 00:33:11,080
Speaker 1: and is there's something that we can do to help you?

636
00:33:11,160 --> 00:33:12,880
Speaker 1: What do you guys think about that? So the ethos

637
00:33:12,920 --> 00:33:18,120
Speaker 1: of sorting robotics is specifically to sophisticate the cannabis industry. Right,

638
00:33:18,360 --> 00:33:22,160
Speaker 1: we're moving from cottage to commercial, we're moving to the mainstream.

639
00:33:22,240 --> 00:33:25,000
Speaker 1: Eventually they'll be federal form. But there needs to be

640
00:33:25,120 --> 00:33:29,000
Speaker 1: this like driving force that improves the whole industry. And

641
00:33:29,000 --> 00:33:31,240
Speaker 1: I think technology is a very good way to do that.

642
00:33:31,920 --> 00:33:35,120
Speaker 1: And given that we also have experience in like actually

643
00:33:35,200 --> 00:33:37,840
Speaker 1: running cannabis companies. So I started a copacking company back

644
00:33:37,880 --> 00:33:42,840
Speaker 1: in Oakland, UM with a few like industry operators, and

645
00:33:42,960 --> 00:33:48,280
Speaker 1: like I ran that for years UM and we even

646
00:33:48,280 --> 00:33:49,880
Speaker 1: like started like an in house brand and stuff. So

647
00:33:50,200 --> 00:33:53,360
Speaker 1: there's not many people that really understand what it's like

648
00:33:53,480 --> 00:33:56,240
Speaker 1: to run a cannabis company and then service a cannabis

649
00:33:56,320 --> 00:33:59,560
Speaker 1: company on the tech side. And so with that lens,

650
00:34:00,000 --> 00:34:03,720
Speaker 1: sophisticating the industry is our goal. So when you think about, like, oh,

651
00:34:04,040 --> 00:34:06,360
Speaker 1: what is our goal, it's to do that. How can

652
00:34:06,400 --> 00:34:09,480
Speaker 1: you help us give us people that we can help

653
00:34:09,560 --> 00:34:11,680
Speaker 1: sophisticate because a lot of people in this industry are

654
00:34:12,239 --> 00:34:17,840
Speaker 1: like struggling in different states, some states not um and

655
00:34:17,960 --> 00:34:20,480
Speaker 1: if they just have a little bit of a shift

656
00:34:20,560 --> 00:34:24,839
Speaker 1: in their perspective, they can go from struggling to extremely profitable. Yeah.

657
00:34:24,960 --> 00:34:26,520
Speaker 1: And and it's funny how you say that it's just

658
00:34:26,560 --> 00:34:28,759
Speaker 1: a little shift in your perspective, because it really is

659
00:34:29,360 --> 00:34:32,480
Speaker 1: like a lot of people have a hard time being unrealistic,

660
00:34:33,000 --> 00:34:34,960
Speaker 1: you know. And I explained that to people, and I

661
00:34:35,040 --> 00:34:36,440
Speaker 1: try and tell them all the time, do you have

662
00:34:36,520 --> 00:34:39,440
Speaker 1: to be unrealistic? Because wealthy people are very unrealistic people,

663
00:34:40,080 --> 00:34:42,960
Speaker 1: and very intelligent people are very unrealistic people because they

664
00:34:43,040 --> 00:34:45,440
Speaker 1: did things that people didn't believe they can do, like

665
00:34:45,560 --> 00:34:48,080
Speaker 1: go to college right years, like you you know what

666
00:34:48,160 --> 00:34:49,799
Speaker 1: I mean, Like like no, no, I want to college

667
00:34:49,880 --> 00:34:51,960
Speaker 1: rate extra years? Why because I felt like it, you know.

668
00:34:52,160 --> 00:34:55,680
Speaker 1: And it's like but everybody else that was crazy, that's unrealistic.

669
00:34:55,800 --> 00:34:57,719
Speaker 1: It's not it's not gonna help me, it's not gonna

670
00:34:58,040 --> 00:35:00,600
Speaker 1: but it's like, no, but that person did this person

671
00:35:00,680 --> 00:35:02,640
Speaker 1: went and you know went and you know, thought of

672
00:35:02,800 --> 00:35:05,520
Speaker 1: making a fucking machine that that you know that no

673
00:35:05,640 --> 00:35:08,040
Speaker 1: one that no one had out there that put a

674
00:35:09,160 --> 00:35:11,320
Speaker 1: you know, a strip of wax down the middle of

675
00:35:11,400 --> 00:35:14,279
Speaker 1: your joint. It sounds amazing, like like who knew? That

676
00:35:14,520 --> 00:35:18,000
Speaker 1: is fantastic? You know, it really is. IM That's why

677
00:35:18,000 --> 00:35:20,520
Speaker 1: I want to see. I wanted to see the the filler.

678
00:35:20,560 --> 00:35:22,160
Speaker 1: I've seen a bunch of the pod fillers, you know

679
00:35:22,160 --> 00:35:24,600
Speaker 1: what I mean, and whatever, um you know, and and

680
00:35:24,640 --> 00:35:28,240
Speaker 1: stuff like that, and those I've seen since the industry

681
00:35:28,280 --> 00:35:32,080
Speaker 1: before quite frankly, the you know vape industry. You know, um,

682
00:35:32,560 --> 00:35:36,560
Speaker 1: but you know that that little beach that was cool.

683
00:35:36,680 --> 00:35:38,759
Speaker 1: You know I've already got four of the machines for

684
00:35:38,800 --> 00:35:46,080
Speaker 1: you guys like you, like I can already. He said

685
00:35:46,120 --> 00:35:49,080
Speaker 1: the wrong thing, he said, We'll take your idea, not mine,

686
00:35:49,160 --> 00:35:52,520
Speaker 1: but I'm not gonna take mine. Right, we'd like to

687
00:35:52,600 --> 00:35:54,239
Speaker 1: do the high five with all the guests that we

688
00:35:54,360 --> 00:35:56,200
Speaker 1: come on to show you guys and where your company

689
00:35:56,280 --> 00:35:58,160
Speaker 1: is going and what you're doing is phenomenal. I really

690
00:35:58,239 --> 00:36:00,200
Speaker 1: love how you're bringing the industry to the next level.

691
00:36:00,280 --> 00:36:02,560
Speaker 1: Two Because like I said to me, I wasn't bullshit.

692
00:36:02,760 --> 00:36:04,919
Speaker 1: I know how we look at you. Congratulations. You guys

693
00:36:04,960 --> 00:36:07,480
Speaker 1: are rock stars just because you're setting a level higher.

694
00:36:07,680 --> 00:36:11,960
Speaker 1: Is the company profitable right now? Yeah? Actually those quarter congratulations?

695
00:36:12,040 --> 00:36:13,759
Speaker 1: That's what I like that. That's that I didn't want

696
00:36:13,760 --> 00:36:15,440
Speaker 1: to ask it on air, but yeah, I didn't want

697
00:36:15,480 --> 00:36:18,680
Speaker 1: to ask it. But it's important to know it's not

698
00:36:19,200 --> 00:36:22,080
Speaker 1: especially because they've already dumped one, you know, so that

699
00:36:22,280 --> 00:36:25,560
Speaker 1: wasn't profitable. Right, you built it, and this is gonna work.

700
00:36:25,960 --> 00:36:31,040
Speaker 1: Let's start over money. Um, And that's that's in perspective, right,

701
00:36:31,040 --> 00:36:32,440
Speaker 1: because what's a lot of money to you is not

702
00:36:32,520 --> 00:36:34,480
Speaker 1: a lot of money to somebody else, you know? And

703
00:36:34,600 --> 00:36:36,920
Speaker 1: and or is it what it takes the scale? Right?

704
00:36:36,960 --> 00:36:39,160
Speaker 1: Because when people don't get it again, like I said,

705
00:36:39,200 --> 00:36:42,400
Speaker 1: I can sit here and um, have a conversation with

706
00:36:43,000 --> 00:36:46,839
Speaker 1: you know, the ten people that hurt it, and then

707
00:36:46,960 --> 00:36:49,239
Speaker 1: you know, not one of them said think congratulations. But

708
00:36:49,320 --> 00:36:54,520
Speaker 1: when you mess up, right, Yeah, so you get the

709
00:36:54,560 --> 00:36:57,120
Speaker 1: answer nine times correct and on that tenth one you

710
00:36:57,200 --> 00:36:59,680
Speaker 1: mess it up and everybody starts laughing at you when

711
00:36:59,680 --> 00:37:01,680
Speaker 1: you mess sit up. But they didn't see the nine

712
00:37:01,719 --> 00:37:04,279
Speaker 1: that you did, right, They didn't say congratulations are the

713
00:37:04,360 --> 00:37:08,920
Speaker 1: ones afterwards either? It's just a you motherfucker, So we congratulate.

714
00:37:08,920 --> 00:37:11,960
Speaker 1: Congratulations exactly. This is hot and it's very hot, and

715
00:37:12,000 --> 00:37:13,960
Speaker 1: it's all we're gonna go in this order. You'll answer

716
00:37:14,000 --> 00:37:16,359
Speaker 1: it first, then we'll go with you Andrew, and then

717
00:37:16,400 --> 00:37:18,439
Speaker 1: you've been you'll be the same question in that order.

718
00:37:18,880 --> 00:37:21,200
Speaker 1: It's the high five with these gentlemen. Of course, check

719
00:37:21,239 --> 00:37:24,200
Speaker 1: out the website story and robotics dot com. Question number one,

720
00:37:24,480 --> 00:37:26,520
Speaker 1: how are you guys the first time you spoked cannabis?

721
00:37:26,560 --> 00:37:31,120
Speaker 1: And where'd you get it from? I was seventeen and

722
00:37:31,960 --> 00:37:34,879
Speaker 1: I got it from my friend Glenn. What area where'd

723
00:37:34,880 --> 00:37:37,960
Speaker 1: you grow? Pasadenia? That's okay? Oh, she grew up in

724
00:37:38,040 --> 00:37:41,680
Speaker 1: Pastina as well. Yeah, wuck. NASA, right, Yeah, that's kind

725
00:37:41,719 --> 00:37:44,920
Speaker 1: of cool. Yeah, it was either NASA or SpaceX. Chose NASA.

726
00:37:46,360 --> 00:37:48,480
Speaker 1: SpaceX would have been cool too. Yeah, you gotta work

727
00:37:48,520 --> 00:37:51,359
Speaker 1: real hard there. Yeah yeah, I said, they just hire

728
00:37:51,400 --> 00:37:53,840
Speaker 1: all anyone out of all the all the sporty degenerates.

729
00:37:53,920 --> 00:37:58,759
Speaker 1: What about you? Uh again, I mean I was I

730
00:37:58,840 --> 00:38:03,760
Speaker 1: think twenty and uh yeah it was. I was in Europe,

731
00:38:03,880 --> 00:38:06,520
Speaker 1: you know, for a summer for study abroad. And uh,

732
00:38:07,080 --> 00:38:12,440
Speaker 1: he's like you something new, but don't gay. I was

733
00:38:12,520 --> 00:38:14,440
Speaker 1: like a hardcore runner in high school, Like I was

734
00:38:14,480 --> 00:38:16,320
Speaker 1: the captain of the track and cross country team. I

735
00:38:16,480 --> 00:38:18,920
Speaker 1: was like on it, you know, So I wasn't I

736
00:38:19,080 --> 00:38:22,600
Speaker 1: wasn't like smoking that stuff. I wasn't. No, I was

737
00:38:22,719 --> 00:38:25,080
Speaker 1: so focused, you know. And then I went to and

738
00:38:25,120 --> 00:38:26,920
Speaker 1: then I went to Pepperdine and I went to college

739
00:38:27,000 --> 00:38:29,839
Speaker 1: and uh, you know, I was over in Amsterdam and uh,

740
00:38:30,120 --> 00:38:34,839
Speaker 1: you know, let me hit that. I mean went in Amsterdam.

741
00:38:35,120 --> 00:38:38,920
Speaker 1: What about you, Ben, it's like one six or twelve

742
00:38:39,440 --> 00:38:42,920
Speaker 1: twelve six six? No, actually not. It was later. It

743
00:38:42,960 --> 00:38:49,000
Speaker 1: was eighteen in the Oakland Colosseum Division Bell concert Pink Floyd. Uh,

744
00:38:49,600 --> 00:38:52,000
Speaker 1: some gals sitting next to me in the seats, sit

745
00:38:52,080 --> 00:38:57,480
Speaker 1: here anything something like that. You got the best story, Ben,

746
00:38:57,560 --> 00:38:59,960
Speaker 1: I'm gonna I'm gonna use your story now. Feel for

747
00:39:00,360 --> 00:39:02,600
Speaker 1: that story was really cool because I can imagine it.

748
00:39:02,920 --> 00:39:06,640
Speaker 1: Did you take Did you drive? Uh? I don't know.

749
00:39:07,080 --> 00:39:10,960
Speaker 1: It's fun so I think somebody else drove. Yeah, yeah. Responsible.

750
00:39:11,040 --> 00:39:12,960
Speaker 1: Question number two of the high five, what is your

751
00:39:13,000 --> 00:39:18,000
Speaker 1: favorite way to use or smoke cannabis with my puff? Really?

752
00:39:18,640 --> 00:39:22,200
Speaker 1: The puff? Yeah? Good device? Yeah? Why not have why

753
00:39:22,239 --> 00:39:24,280
Speaker 1: not a puff coo or something like that, a device

754
00:39:24,400 --> 00:39:26,800
Speaker 1: like that because they already have a puff co we

755
00:39:26,880 --> 00:39:29,719
Speaker 1: do stuff that doesn't exist. No, but I'm staying anyone

756
00:39:29,800 --> 00:39:32,200
Speaker 1: that doesn't exist, like a smoking device, would you do that?

757
00:39:32,600 --> 00:39:34,839
Speaker 1: It's like a different way to smoke something. I mean,

758
00:39:34,960 --> 00:39:37,080
Speaker 1: I don't know. I really think puffica is kind of

759
00:39:37,080 --> 00:39:40,160
Speaker 1: the best way to smoke right now. Yeah, at least

760
00:39:40,280 --> 00:39:42,680
Speaker 1: right now. Yeah, there's just coming from a Nasha engineer.

761
00:39:42,920 --> 00:39:46,880
Speaker 1: I mean, hey, they probably did. What about you, Andrew? Um,

762
00:39:47,000 --> 00:39:50,880
Speaker 1: I actually like making little cannabis cocktails at home, so

763
00:39:51,000 --> 00:39:54,960
Speaker 1: instead of you know, I'm a wine guy, but really

764
00:39:55,040 --> 00:39:58,080
Speaker 1: I love my cannabis cocktails. Now you are you microdosing

765
00:39:58,120 --> 00:39:59,560
Speaker 1: that or do you are? Do you just hit him

766
00:39:59,560 --> 00:40:03,920
Speaker 1: home micro doocing? Yeah? I don't microdesca no, um, but no,

767
00:40:04,120 --> 00:40:06,080
Speaker 1: like at night, I'll just have like you know, maybe

768
00:40:06,200 --> 00:40:10,680
Speaker 1: like in it that's microcing. Yeah, yeah, yeah, you know

769
00:40:10,760 --> 00:40:16,719
Speaker 1: it's good. I didn't say how many I have. Hey,

770
00:40:16,760 --> 00:40:18,440
Speaker 1: that's a good one, Andrew, what about you? Ben just

771
00:40:18,560 --> 00:40:21,319
Speaker 1: kidding out there if you're listening, just good old fashion, joint,

772
00:40:22,360 --> 00:40:25,000
Speaker 1: old school. Just just give me a nice one. She

773
00:40:25,080 --> 00:40:26,520
Speaker 1: doesn't need to be doesn't need to put me on

774
00:40:26,560 --> 00:40:30,320
Speaker 1: the moon or marsh some just put me in the

775
00:40:30,360 --> 00:40:32,359
Speaker 1: good mood. But had good old fashion joint. That's nice.

776
00:40:32,400 --> 00:40:34,840
Speaker 1: What about the craziest place question number three of the

777
00:40:34,880 --> 00:40:40,319
Speaker 1: high five that you ever used or smoked cannabis? Craziest place? Damn.

778
00:40:41,360 --> 00:40:43,400
Speaker 1: I usually make sure i'm in like a safe space

779
00:40:43,560 --> 00:40:47,600
Speaker 1: because I'm not a good high person. I'm like pretty useless. Mike,

780
00:40:47,719 --> 00:40:49,680
Speaker 1: you gets cut in. Have you ever smoke at NASA?

781
00:40:51,040 --> 00:40:54,480
Speaker 1: I did not smoke at NASA? Um ever, I was

782
00:40:54,760 --> 00:40:57,439
Speaker 1: sober Stone Colts sober, he said. I repeat, I didn't

783
00:40:57,440 --> 00:40:59,360
Speaker 1: even smoke. Then I didn't even. Yeah, I didn't. I

784
00:40:59,360 --> 00:41:03,040
Speaker 1: didn't smoke. I know anyone that smoked either. Um so,

785
00:41:04,120 --> 00:41:05,960
Speaker 1: but let's see, where is the craziest place I smoked

786
00:41:06,000 --> 00:41:08,600
Speaker 1: at that? Smoking at NASA would be pretty cool. I'm

787
00:41:08,600 --> 00:41:10,400
Speaker 1: just saying if somebody was just say, oh, yeah, I

788
00:41:10,440 --> 00:41:12,399
Speaker 1: smoke once you cross that gate, because you can't cross

789
00:41:12,440 --> 00:41:14,879
Speaker 1: that gate once you cross that gate, and you smoke

790
00:41:14,920 --> 00:41:16,719
Speaker 1: at NASA, that'd be pretty crazy spot. I'm just saying,

791
00:41:17,920 --> 00:41:20,000
Speaker 1: smoking like the high bay where they have the filters

792
00:41:20,040 --> 00:41:21,640
Speaker 1: and everything. You know, if that'd be kind of cool

793
00:41:21,640 --> 00:41:24,200
Speaker 1: if you're smoking NASA, like because I tried to walk

794
00:41:24,239 --> 00:41:26,879
Speaker 1: the smoking NASA buddy, I don't know. I'm just saying

795
00:41:26,880 --> 00:41:29,960
Speaker 1: if they did. If I walked through the NASA campus

796
00:41:30,080 --> 00:41:32,440
Speaker 1: and I smelled weed, I would be like, oh shit,

797
00:41:32,600 --> 00:41:36,759
Speaker 1: it's about to get real. They don't do it, Yeah,

798
00:41:36,800 --> 00:41:38,560
Speaker 1: that'll be messed up. I mean, I don't know. I

799
00:41:38,600 --> 00:41:41,920
Speaker 1: think the craziest place I ever smoked. I mean, like

800
00:41:42,040 --> 00:41:44,399
Speaker 1: E d C. That's good. Yeah, I mean I got

801
00:41:45,040 --> 00:41:50,920
Speaker 1: a good time. Yeah, exactly what about you? Andrew? No,

802
00:41:51,160 --> 00:41:56,080
Speaker 1: I'm like Natal, I like my safe spaces. But yeah,

803
00:41:56,080 --> 00:41:59,000
Speaker 1: I mean I I just I took too many edibles

804
00:41:59,440 --> 00:42:01,160
Speaker 1: when I was in Vegas with my brother in law,

805
00:42:01,239 --> 00:42:04,200
Speaker 1: and uh, let me just say, Casino floor is a

806
00:42:04,400 --> 00:42:09,120
Speaker 1: trippy spot to not even be aware of anything. It

807
00:42:09,239 --> 00:42:13,480
Speaker 1: was those stores can go crazy. That's a crazy places

808
00:42:13,680 --> 00:42:15,200
Speaker 1: on the slot for an hour and I was only

809
00:42:15,239 --> 00:42:18,719
Speaker 1: there for like three minutes. It was bing, bing bing bing.

810
00:42:18,800 --> 00:42:23,439
Speaker 1: What about you? Ben? Crazy? Not as in crazy, good time, crazy, cool,

811
00:42:23,520 --> 00:42:25,680
Speaker 1: craziest as in I thought I was gonna die. Uh.

812
00:42:26,360 --> 00:42:30,200
Speaker 1: One of my first business trips up to humblet and uh,

813
00:42:30,880 --> 00:42:33,480
Speaker 1: I was the new guy that nobody knew besides a

814
00:42:33,560 --> 00:42:36,680
Speaker 1: referraling from a friend. So after get into a location,

815
00:42:36,760 --> 00:42:39,040
Speaker 1: after having a bag on my head, I sort of

816
00:42:39,040 --> 00:42:42,200
Speaker 1: had to prove myself. It wasn't fun. It was crazy though,

817
00:42:44,280 --> 00:42:50,480
Speaker 1: how crazy again? How hard you have yourself? He's the

818
00:42:50,520 --> 00:42:52,640
Speaker 1: only one that read it, he guys, ever seen deliverance? No,

819
00:42:52,640 --> 00:42:57,800
Speaker 1: I'm just kidding. A couple couple of puffs, that was it.

820
00:42:58,080 --> 00:43:01,319
Speaker 1: That's always good of course, number four of the High

821
00:43:01,440 --> 00:43:06,000
Speaker 1: five Swording Robotics Inc. Nice to have you, guys. So

822
00:43:07,800 --> 00:43:12,080
Speaker 1: what is your go to munchy after you get high? Orios? Easy?

823
00:43:12,320 --> 00:43:25,200
Speaker 1: White black? I like to Oh yeah, yeah, we got

824
00:43:25,239 --> 00:43:28,080
Speaker 1: the sin ones at the office. Keep those stopped, keep

825
00:43:28,120 --> 00:43:33,799
Speaker 1: those stock. What about you? M m uh? I think

826
00:43:34,320 --> 00:43:41,040
Speaker 1: like um gummies, like gummy bears, like anything anything horror

827
00:43:42,280 --> 00:43:46,560
Speaker 1: anything anything, every variation, every storage or whatever. I grabbing

828
00:43:46,600 --> 00:43:50,400
Speaker 1: that all right? What about you ben so college? It

829
00:43:50,480 --> 00:43:54,280
Speaker 1: used to be the microwave to case adia, quick and easy,

830
00:43:54,360 --> 00:43:56,839
Speaker 1: but a shitty form of a case adia. So now

831
00:43:57,120 --> 00:43:59,080
Speaker 1: I actually will do it on a griddle or make

832
00:43:59,120 --> 00:44:01,720
Speaker 1: them make a proper case idea. Yeah, that's so funny

833
00:44:01,760 --> 00:44:06,320
Speaker 1: that the old school cheap microwave nacho cheese on the outside.

834
00:44:06,719 --> 00:44:10,239
Speaker 1: Now I put it parmesan on the outside. Now your

835
00:44:10,280 --> 00:44:17,280
Speaker 1: fancy do you do? You bake it on there? The barbrasan.

836
00:44:18,120 --> 00:44:20,799
Speaker 1: So you flip it over, you know, the oil little butter,

837
00:44:20,840 --> 00:44:23,360
Speaker 1: flip it over. Why it's still anytime you fry something right,

838
00:44:23,440 --> 00:44:24,920
Speaker 1: you need a season it right then. So that's when

839
00:44:24,920 --> 00:44:26,480
Speaker 1: you put the parmesan on right, when you flip over

840
00:44:26,520 --> 00:44:29,960
Speaker 1: the first side while it's still cooking. Proap. Oh nice.

841
00:44:30,040 --> 00:44:31,920
Speaker 1: Before we get the question number five, we gotta give

842
00:44:31,960 --> 00:44:35,560
Speaker 1: a big shout out to robo cush Kings of Los

843
00:44:35,640 --> 00:44:38,600
Speaker 1: Angeles in the building. I see them over there, robo

844
00:44:38,719 --> 00:44:41,399
Speaker 1: cush in the building. Okay, you guys, cannabis talk one

845
00:44:41,440 --> 00:44:44,920
Speaker 1: oh one, question number five with the high five natol.

846
00:44:44,960 --> 00:44:48,640
Speaker 1: If you could smoke cannabis with anyone dead or live,

847
00:44:49,280 --> 00:44:54,200
Speaker 1: who would it be and why? Uh? Honestly, I think

848
00:44:54,280 --> 00:44:57,319
Speaker 1: Elon Musk could be kind of interesting because I kind

849
00:44:57,320 --> 00:44:59,439
Speaker 1: of saw him Rogan. I feel like if he wasn't,

850
00:44:59,440 --> 00:45:03,479
Speaker 1: you know, sense third, he'd be funny as fu. Yeah yeah, yeah.

851
00:45:04,280 --> 00:45:05,640
Speaker 1: I like that guy a lot. There's a lot of

852
00:45:05,680 --> 00:45:08,319
Speaker 1: things he does. I think he's pretty uncensored. I mean,

853
00:45:08,480 --> 00:45:10,919
Speaker 1: I think he just he wanted to test the market

854
00:45:11,000 --> 00:45:13,359
Speaker 1: and see how hard is it's stock. He probably made

855
00:45:13,400 --> 00:45:15,800
Speaker 1: a ton of money when that happened. I mean, he

856
00:45:15,920 --> 00:45:20,239
Speaker 1: bought puts. He bought puts. Yeah, sure, right, great, Why

857
00:45:20,239 --> 00:45:21,879
Speaker 1: wouldn't you want to smoke with the guy? Seems cool

858
00:45:21,880 --> 00:45:27,239
Speaker 1: as funk? What about you, Andrew? Mm hmm. Well she's

859
00:45:27,239 --> 00:45:30,560
Speaker 1: still alive, I would say Queen Elizabeth, because if there's

860
00:45:30,640 --> 00:45:34,480
Speaker 1: one person that knows where all the bodies are buried, yea,

861
00:45:35,480 --> 00:45:37,480
Speaker 1: and not only that, she'll know the whole stories of

862
00:45:37,560 --> 00:45:41,400
Speaker 1: what really happened. Why why did your grand Yeah exactly,

863
00:45:41,560 --> 00:45:44,480
Speaker 1: I mean, how many grandkids that are treated like royalty? Say,

864
00:45:44,520 --> 00:45:48,920
Speaker 1: I'm out. I've actually served him wine? No way, no way.

865
00:45:49,320 --> 00:45:51,520
Speaker 1: He's a super cool guy. I bet I love my

866
00:45:51,600 --> 00:45:53,400
Speaker 1: old my old vineyard. He came up for a private

867
00:45:53,440 --> 00:45:56,080
Speaker 1: trip and uh, he came up about five people on

868
00:45:56,160 --> 00:46:00,200
Speaker 1: a on a secret trip and he seems like is

869
00:46:00,520 --> 00:46:02,560
Speaker 1: he would be the realist of actually bust his own

870
00:46:02,600 --> 00:46:05,080
Speaker 1: dishes at the end of it, and he shook my

871
00:46:05,160 --> 00:46:06,879
Speaker 1: hand and said thank you so much for everything. Yeah,

872
00:46:07,120 --> 00:46:11,280
Speaker 1: he was the nicest guy. That's the young prince right there, literally,

873
00:46:11,560 --> 00:46:14,759
Speaker 1: which I like that. I I I'm infatuated with that

874
00:46:14,880 --> 00:46:18,360
Speaker 1: whole culture in history, you know, I mean like queen family.

875
00:46:18,440 --> 00:46:20,440
Speaker 1: Bro he left the family dug So why why wouldn't

876
00:46:20,440 --> 00:46:21,680
Speaker 1: you want to talk to the queen. That's my point.

877
00:46:21,680 --> 00:46:23,839
Speaker 1: You talk to the head of the family. She's the mob.

878
00:46:24,080 --> 00:46:27,640
Speaker 1: She's the head of the mob. Yeah, he's the largest landholder.

879
00:46:28,600 --> 00:46:30,440
Speaker 1: She's the head of the mob. Don't get it twisted.

880
00:46:30,480 --> 00:46:33,440
Speaker 1: She's running. Everybody know, she's the head. Yeah, that's why.

881
00:46:33,680 --> 00:46:38,279
Speaker 1: That's a good one. And the son, I mean, that's

882
00:46:38,280 --> 00:46:40,680
Speaker 1: what I'm saying, like, you know, that's over some minority

883
00:46:40,800 --> 00:46:43,040
Speaker 1: stuff like Okay, my wife's black. I'm but you guys

884
00:46:43,120 --> 00:46:47,880
Speaker 1: miss treating her. I'm not gonna funk with y'all. Is

885
00:46:47,920 --> 00:46:51,840
Speaker 1: that the confirmation or just oh no, that's what I

886
00:46:51,880 --> 00:46:53,920
Speaker 1: know it was. I'm not no, I know there was

887
00:46:53,960 --> 00:46:55,360
Speaker 1: a lot to do with it, But I mean, is

888
00:46:55,400 --> 00:46:59,279
Speaker 1: that is that? Was that? What am I The trip

889
00:46:59,360 --> 00:47:02,920
Speaker 1: that he came was actually secret. So yeah, he's an

890
00:47:02,960 --> 00:47:10,920
Speaker 1: over interview. He just with Megan's Yeah, he went with

891
00:47:11,960 --> 00:47:13,759
Speaker 1: and then not only that, he married Megan and then

892
00:47:13,880 --> 00:47:15,520
Speaker 1: I know they got and it was on Oprah about

893
00:47:15,520 --> 00:47:17,920
Speaker 1: and that's why. Okay, Yeah, so all that I know

894
00:47:18,040 --> 00:47:19,440
Speaker 1: he left the family, I didn't know that was just

895
00:47:19,560 --> 00:47:24,200
Speaker 1: because of Megan. Yeah, yeah, because because his brother, our

896
00:47:24,680 --> 00:47:27,319
Speaker 1: father or of one of them said something racist about her,

897
00:47:27,800 --> 00:47:29,520
Speaker 1: so one of them, and we still don't know who

898
00:47:29,600 --> 00:47:32,200
Speaker 1: it's been under that. Nobody knows still, but that was it.

899
00:47:32,280 --> 00:47:33,879
Speaker 1: It was done, good for it was done. And he left.

900
00:47:33,920 --> 00:47:35,279
Speaker 1: He said, okay, well you can't make that. I like

901
00:47:35,400 --> 00:47:36,960
Speaker 1: that you say that, And she sparked up a whole

902
00:47:36,960 --> 00:47:38,479
Speaker 1: ship in me. That makes you want to know the answer.

903
00:47:38,560 --> 00:47:41,359
Speaker 1: So did you smoke with her? Let me know? She yeah, yeah,

904
00:47:41,680 --> 00:47:43,960
Speaker 1: I'm so curious to you. What about Henna smoke? Yeah,

905
00:47:44,040 --> 00:47:47,600
Speaker 1: that goes ward. I'm gonna join you all right. Oh man, um,

906
00:47:48,480 --> 00:47:50,960
Speaker 1: he's probably a cliche one, but I probably want to

907
00:47:51,000 --> 00:47:55,279
Speaker 1: smoke a joint with Anthony Burden. Ooh, he's traveled a lot.

908
00:47:55,440 --> 00:47:58,280
Speaker 1: He's traveled a lot. You've seen a lot of cultures

909
00:47:58,360 --> 00:48:00,480
Speaker 1: in a lot of places, and it's seen The specials

910
00:48:00,480 --> 00:48:03,640
Speaker 1: are still I watched till this day when I see

911
00:48:03,680 --> 00:48:06,359
Speaker 1: him on. Absolutely, he's a unique man that has done

912
00:48:06,400 --> 00:48:09,040
Speaker 1: some fabulous things, and I think he touches all cultures

913
00:48:09,080 --> 00:48:11,480
Speaker 1: and people and makes you realize that food brings us

914
00:48:11,480 --> 00:48:15,640
Speaker 1: all together, brings us all together. A unique cool dude. Absolutely,

915
00:48:16,160 --> 00:48:17,840
Speaker 1: How many guys in the audience know who that is?

916
00:48:20,680 --> 00:48:22,560
Speaker 1: Just checking as fant to see. Is that only because

917
00:48:22,560 --> 00:48:27,200
Speaker 1: they we've heard it four or five times on the show. Yeah,

918
00:48:27,360 --> 00:48:29,399
Speaker 1: he's a little bit older. Some of the people don't

919
00:48:29,440 --> 00:48:31,080
Speaker 1: know you know what I mean, it's it's it's there's

920
00:48:31,080 --> 00:48:32,880
Speaker 1: the when he died. I think it was such a

921
00:48:32,920 --> 00:48:35,120
Speaker 1: big deal. And he died within the past two years.

922
00:48:35,160 --> 00:48:37,680
Speaker 1: If I'm not going I think, you know, yeah, I

923
00:48:37,719 --> 00:48:39,879
Speaker 1: made it such a big deal, you know, him being

924
00:48:40,000 --> 00:48:43,200
Speaker 1: this iconic guy who has so much history archived with

925
00:48:43,320 --> 00:48:45,840
Speaker 1: all the interviews he's done, so now it becomes iconic.

926
00:48:46,000 --> 00:48:47,560
Speaker 1: So guys, let us know. Is there anything that we

927
00:48:47,680 --> 00:48:50,160
Speaker 1: forgot that you guys wanna, you know, tell the audience

928
00:48:50,320 --> 00:48:52,640
Speaker 1: or just let us all know about you guys before

929
00:48:52,680 --> 00:48:55,279
Speaker 1: we let you guys get on out of here. M hmm.

930
00:48:55,800 --> 00:48:59,080
Speaker 1: I mean I think we're here to help. Yeah. I

931
00:48:59,200 --> 00:49:02,239
Speaker 1: like that We're here to help and we're doing it

932
00:49:02,320 --> 00:49:05,759
Speaker 1: the right way, which, um, I think this industry is

933
00:49:05,840 --> 00:49:09,560
Speaker 1: kind of touching goes sometimes. Um. But yeah, I think

934
00:49:09,560 --> 00:49:12,840
Speaker 1: we're trying to approach you that sophisticated and as balanced

935
00:49:12,840 --> 00:49:16,000
Speaker 1: as possible. I think you guys are doing that. Man,

936
00:49:16,120 --> 00:49:18,160
Speaker 1: keep up work. I like it, dude, I you know,

937
00:49:18,280 --> 00:49:22,360
Speaker 1: I I really I feel that you guys are on

938
00:49:22,520 --> 00:49:25,080
Speaker 1: something one. I like, I love the dynamic that I

939
00:49:25,120 --> 00:49:27,040
Speaker 1: look and when I look at you guys, I'm like, okay,

940
00:49:27,400 --> 00:49:30,239
Speaker 1: Like it literally makes sense to me, Like I could see, like,

941
00:49:30,520 --> 00:49:35,640
Speaker 1: you know, if if you guys are um, what's a

942
00:49:35,719 --> 00:49:38,600
Speaker 1: great way to say, If you guys are very uh

943
00:49:38,960 --> 00:49:41,400
Speaker 1: committed and you believe in everything you're really doing, and

944
00:49:41,480 --> 00:49:44,160
Speaker 1: you guys can withhold everybody's bullshit because all of us

945
00:49:44,160 --> 00:49:46,680
Speaker 1: have bullshit, you know what I mean, Like this guy's

946
00:49:46,760 --> 00:49:49,080
Speaker 1: math doesn't equal to that and this and this everything

947
00:49:49,120 --> 00:49:51,520
Speaker 1: else whatever it is. If you guys can hang onto that,

948
00:49:51,600 --> 00:49:54,200
Speaker 1: this is gonna be a very special company. Plans to

949
00:49:54,239 --> 00:49:59,920
Speaker 1: go public when it's legal. Yeah, yeah, we'll go pub

950
00:50:00,000 --> 00:50:02,600
Speaker 1: We'll get about by seamans one or the other, you know. Yeah,

951
00:50:03,480 --> 00:50:07,200
Speaker 1: well saying there's next it right, Yeah, yeah, that's the point. Yeah,

952
00:50:07,400 --> 00:50:12,399
Speaker 1: that's goods like that Seamans are da Vinci's right, something

953
00:50:12,480 --> 00:50:14,640
Speaker 1: like that. Crazy, That's what I'm saying, Like I see it,

954
00:50:14,719 --> 00:50:17,400
Speaker 1: like I could watch it route I see what you're

955
00:50:17,400 --> 00:50:20,799
Speaker 1: gonna do. It's dope. Anything else boys. Before we let

956
00:50:20,840 --> 00:50:23,239
Speaker 1: you guys get out here, was say, can I get

957
00:50:23,320 --> 00:50:25,040
Speaker 1: some stock in the company? Can Blue and I get

958
00:50:25,040 --> 00:50:29,080
Speaker 1: a little stock in the company we might about to do.

959
00:50:29,160 --> 00:50:31,000
Speaker 1: So I was gonna say one thing. A lot of

960
00:50:31,080 --> 00:50:34,760
Speaker 1: times certain operators get scared of the idea of automation

961
00:50:34,800 --> 00:50:37,280
Speaker 1: because for them, they're employing their friends, are employing family,

962
00:50:37,360 --> 00:50:39,760
Speaker 1: and they're thinking, Okay, I'm just getting rid of my labor.

963
00:50:40,520 --> 00:50:42,040
Speaker 1: That's not what we're looking to do, and that's not

964
00:50:42,160 --> 00:50:44,719
Speaker 1: the spirit behind the company or automation. What we're trying

965
00:50:44,760 --> 00:50:47,400
Speaker 1: to do is basically take over some of these mundane

966
00:50:47,480 --> 00:50:49,720
Speaker 1: tasks like sitting there and clipping or sorting, which nobody

967
00:50:49,760 --> 00:50:51,120
Speaker 1: wants to do. I don't care how high you are,

968
00:50:51,160 --> 00:50:53,040
Speaker 1: how much you get paid, weed, you don't enjoy doing that.

969
00:50:53,600 --> 00:50:56,000
Speaker 1: But allow that person to go to do something that's

970
00:50:56,200 --> 00:50:58,200
Speaker 1: going to allow them to expand their mind, be more creative,

971
00:50:58,239 --> 00:50:59,800
Speaker 1: Go do something that's gonna bring a bigger r y

972
00:50:59,880 --> 00:51:02,239
Speaker 1: to your company. So just when I had that about

973
00:51:02,239 --> 00:51:05,200
Speaker 1: automation again, sometimes it's the evil word out there, but

974
00:51:05,400 --> 00:51:08,040
Speaker 1: when used appropriately, it can really scale up your operation

975
00:51:08,280 --> 00:51:10,160
Speaker 1: and enhance the people are already working with you. Allow

976
00:51:10,200 --> 00:51:12,120
Speaker 1: them do something a little more meaningful, you know, and

977
00:51:12,239 --> 00:51:15,719
Speaker 1: and honestly, you know, if if you value your core people,

978
00:51:15,760 --> 00:51:17,560
Speaker 1: you would teach them how to use that machine and

979
00:51:17,680 --> 00:51:19,120
Speaker 1: love that they were doing that. I mean, that's just

980
00:51:19,320 --> 00:51:21,440
Speaker 1: it's and they find a different job because it's just

981
00:51:21,520 --> 00:51:22,960
Speaker 1: part of the game. I mean, what you guys are

982
00:51:23,000 --> 00:51:24,799
Speaker 1: doing is just part of the game. It doesn't matter.

983
00:51:24,880 --> 00:51:27,960
Speaker 1: It helps the business, it helps the culture, it helps everything. Yeah,

984
00:51:27,960 --> 00:51:31,279
Speaker 1: we've seen so many people that we've installed machines into

985
00:51:31,480 --> 00:51:34,000
Speaker 1: and they're like, oh, dude, I'm still happy your machines here.

986
00:51:34,040 --> 00:51:36,080
Speaker 1: We'll come back like a few months later and like, yeah, man,

987
00:51:36,160 --> 00:51:37,759
Speaker 1: before we were just like doing this by hand, or

988
00:51:37,800 --> 00:51:39,839
Speaker 1: before we were doing just a different Dude, now I'm

989
00:51:39,920 --> 00:51:41,720
Speaker 1: using this machine. Is so sick. I tell my friends,

990
00:51:41,760 --> 00:51:43,600
Speaker 1: like they'll tell they'll tell us when we're like fixing

991
00:51:43,640 --> 00:51:45,560
Speaker 1: the machine or something like, oh yeah, I told my

992
00:51:45,600 --> 00:51:47,440
Speaker 1: friend that, like I'm using this machine that like sucking

993
00:51:47,480 --> 00:51:52,239
Speaker 1: injects joints. He's like, whoa ue, that's leg and uh.

994
00:51:52,440 --> 00:51:54,160
Speaker 1: And you know, like now these people are becoming like

995
00:51:54,280 --> 00:51:58,160
Speaker 1: more technical, got videos that show it all. Oh yeah, sure, yeah,

996
00:51:58,280 --> 00:52:00,239
Speaker 1: I gotta see all that. You know, my fault for

997
00:52:00,320 --> 00:52:04,560
Speaker 1: not let's come up to our facility and visit it sometimes. Yeah, definitely,

998
00:52:04,600 --> 00:52:06,600
Speaker 1: I'll be there for sure. Yeah, like I have all

999
00:52:06,680 --> 00:52:08,719
Speaker 1: kinds of ideas. I mean, honestly, you know, when I

1000
00:52:08,880 --> 00:52:10,319
Speaker 1: and I was trying to get you guys off the show,

1001
00:52:10,360 --> 00:52:13,360
Speaker 1: but we're gonna start stay and talk no. Yeah, So

1002
00:52:13,719 --> 00:52:17,480
Speaker 1: so you know I could like, well, I see it

1003
00:52:17,520 --> 00:52:19,440
Speaker 1: from a different angle, right, So I know all of

1004
00:52:19,520 --> 00:52:22,160
Speaker 1: your target audience, all of them, like not all them,

1005
00:52:22,160 --> 00:52:24,640
Speaker 1: but fucking all of them, you know, and like or

1006
00:52:24,680 --> 00:52:26,239
Speaker 1: a lot a lot of them, you know, so where

1007
00:52:26,440 --> 00:52:29,240
Speaker 1: it's like they're there there, and and I've been working

1008
00:52:29,320 --> 00:52:32,279
Speaker 1: with them for you know, uh, twenty five years and

1009
00:52:32,400 --> 00:52:34,440
Speaker 1: some of them ten and and and and some of

1010
00:52:34,480 --> 00:52:38,239
Speaker 1: them within the last year. But but you know, I

1011
00:52:38,480 --> 00:52:41,200
Speaker 1: understand it, and I've been in all facets of of

1012
00:52:41,719 --> 00:52:43,719
Speaker 1: of that. You know, I've worked that plant from from

1013
00:52:43,920 --> 00:52:45,799
Speaker 1: from the ground up to you know, and I've had

1014
00:52:45,840 --> 00:52:47,560
Speaker 1: to do all kinds of different things, whether it be

1015
00:52:48,040 --> 00:52:51,840
Speaker 1: you know, uh trimming or growing or uh you know,

1016
00:52:51,920 --> 00:52:53,919
Speaker 1: so I could I could see that and having people

1017
00:52:54,000 --> 00:52:56,279
Speaker 1: that that are intelligent to to build a you know,

1018
00:52:56,400 --> 00:52:59,239
Speaker 1: a project like this, a robotic that can actually uh

1019
00:52:59,360 --> 00:53:01,800
Speaker 1: sustain in the market and come into the market and

1020
00:53:01,840 --> 00:53:05,120
Speaker 1: actually help people grow and and save money and and

1021
00:53:05,600 --> 00:53:08,319
Speaker 1: you know, scale that that's huge that you guys, that's

1022
00:53:08,440 --> 00:53:12,040
Speaker 1: that's something that our industry, uh, you know, really really needs.

1023
00:53:12,400 --> 00:53:15,880
Speaker 1: And I appreciate you guys for it, and you know,

1024
00:53:16,280 --> 00:53:18,919
Speaker 1: I really really appreciate it. Like I'm excited to see

1025
00:53:19,120 --> 00:53:20,840
Speaker 1: you know, and I have some ideas right now for

1026
00:53:20,920 --> 00:53:22,759
Speaker 1: you guys. I just gotta hold my tongue because he said,

1027
00:53:23,360 --> 00:53:28,600
Speaker 1: you know, we'll take your ideas. Okay, now we're talking now,

1028
00:53:28,640 --> 00:53:32,040
Speaker 1: and he tells he's a very smart man. He uses words. Well,

1029
00:53:32,120 --> 00:53:33,719
Speaker 1: he's like, we'll take that idea out of Like now

1030
00:53:33,800 --> 00:53:41,920
Speaker 1: you have this guy. He always went to the high school. Yeah, yeah, yeah, no,

1031
00:53:42,080 --> 00:53:46,200
Speaker 1: these are the guys. Yeah, they're very intelligent group of group,

1032
00:53:46,320 --> 00:53:48,959
Speaker 1: a team and they fit all they check all the marks.

1033
00:53:49,000 --> 00:53:51,880
Speaker 1: So anyways, guys, there anything else, man, I'm cut it

1034
00:53:51,920 --> 00:53:53,960
Speaker 1: out of here. He has done. I think we're good.

1035
00:53:54,160 --> 00:53:55,880
Speaker 1: Where's your website? Man, tell him they can meet you

1036
00:53:56,480 --> 00:53:59,680
Speaker 1: Sorting Robotics dot com. Yep, that's it. Give me a phone,

1037
00:54:00,400 --> 00:54:04,480
Speaker 1: yeah six, Yeah, Well there it is. Guys. It's Cannabis

1038
00:54:04,560 --> 00:54:06,319
Speaker 1: Talk one on one. And remember this, if no one

1039
00:54:06,360 --> 00:54:09,400
Speaker 1: else lives you, we do. Thank you for listening to

1040
00:54:09,480 --> 00:54:12,040
Speaker 1: Cannabis Talk one oh one on the i Heart Radio app,

1041
00:54:12,200 --> 00:54:15,160
Speaker 1: Apple Podcast, or wherever you get your podcasts.