Latest / Through the Line: Packaging and Processing / PACK EXPO Recap—AI Puts Data to Work and GLP-1s Ripple Through Packaging: End of the Line

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PACK EXPO Recap—AI Puts Data to Work and GLP-1s Ripple Through Packaging: End of the Line · Through the Line: Packaging and Processing

• 0:00
  SPEAKER_03: Hi, I'm Sean Riley and welcome to the End of the Line video podcast.
• 0:06
  SPEAKER_03: I will be handling hosting duties this week as we try to as we're all trying to recover from a long pack expo week.
• 0:13
  SPEAKER_03: I, as always, am joined by Liz Cunio from Healthcare Packaging, Matt Reynolds from Packaging World, Derek Teal from Pro Food World, and we have an extra today, thankfully, with Casey Flanagan, wearer of many hats at PMG.
• 0:28
  SPEAKER_03: And we're gonna just go through we've taken off the monkey suits, no more ties, no more fancy dress.
• 0:33
  SPEAKER_03: We're not walking around.
• 0:34
  SPEAKER_03: We're actually sitting for a minute, and we're just gonna go over some things that we saw during the show, some things that might be relevant that we didn't get to cover in the videos that everybody put together during the week.
• 0:44
  SPEAKER_03: So I'm gonna start off with Casey, who I think has some connectivity to talk about that hopefully will weave us all together so we don't have to wing it.
• 0:54
  SPEAKER_03: Exactly.
• 0:55
  SPEAKER_02: Yeah, so I think this is a good starting point because I would be very surprised if you guys also didn't see something along these lines on the show floor.
• 1:02
  SPEAKER_02: So one of the big themes that I saw this year was connectivity and not just collecting data, that's kind of old news, but finding new and creative ways to use that data once you connect it.
• 1:13
  SPEAKER_02: I saw that in the booths.
• 1:14
  SPEAKER_02: One of those times that I saw in the booth booth was with Red Zone.
• 1:17
  SPEAKER_02: They had their champion AI system, which was basically an AI tool embedded into existing manufacturing workflows.
• 1:25
  SPEAKER_02: On the front end of it, an operator or just anybody that needs some information can chat with it, like any old LLM, but it's all connected to their manufacturing data.
• 1:35
  SPEAKER_02: It's just a kind of an in-house expert built right in.
• 1:38
  SPEAKER_02: And so it the way they were describing is it, and the big distinction with it was that insights from it aren't just for management to review after the fact, it's for anybody on the plant floor to get some real-time insights.
• 1:49
  SPEAKER_02: So thought that was pretty cool.
• 1:51
  SPEAKER_02: And on a similar note, there was stock IQ in their like a logistics kind of company.
• 1:57
  SPEAKER_02: And they had this Edison agencai AI, which was really cool.
• 2:00
  SPEAKER_02: And agentic AI being something that is really actually taking tasks off of the hands of people.
• 2:07
  SPEAKER_02: If there's any basic tasks that you that's really repeatable, it was able to kind of do stuff like that, like basic communication with vendors or reviewing inventory, things like that.
• 2:16
  SPEAKER_02: So just connected to their systems and able to boost productivity and add that efficiency in there.
• 2:21
  SPEAKER_02: And then lastly, not to go on too much of a spiel on this, but I attended an educational session that covered this area as well.
• 2:29
  SPEAKER_02: And it was with Reading Bakery Systems, and they had a session on AI and continuous mixing.
• 2:35
  SPEAKER_02: And basically, it was that AI is currently being used in it, it's in its early stages, and the focus right now is for automation.
• 2:44
  SPEAKER_02: It's for collecting production data and automatically adjusting parameters based on kind of programmed rules.
• 2:50
  SPEAKER_02: But the future look of it, the what this really has potential for as we keep going, is for AI to learn the relationship between those different inputs and to figure out an adjustment that the operator might not see.
• 3:03
  SPEAKER_02: So if the maybe an operator thinks, oh, we need to adjust our oil amount or the brand of oil we're buying from or something like that, but the AI might be able to just say, Oh, actually, the mixing is just a little bit too fast.
• 3:15
  SPEAKER_02: If you slow it down, you're gonna get the product you want.
• 3:18
  SPEAKER_02: So pretty cool uses of just the latest technology and data management in AI to really boost productivity on the plant floor.
• 3:25
  SPEAKER_02: I guess with that, did you guys see anything along those lines?
• 3:28
  SPEAKER_00: Or I was just gonna say, go ahead.
• 3:30
  SPEAKER_02: Go you go first, Derek, and then I'll let's not fight.
• 3:34
  SPEAKER_00: What?
• 3:35
  SPEAKER_00: Yeah, I was just gonna say that I'm in agreement with Casey in terms of data being the big takeaway from the show, mostly because, as you guys know, we're shooting videos out there, and data is not photogenic, it's very hard to take a picture of data.
• 3:48
  SPEAKER_00: But yeah, there are other companies that I saw, and it's exactly that.
• 3:52
  SPEAKER_00: It's taking that data and turning it, making it actionable.
• 3:56
  SPEAKER_00: And one of the things that I saw was data related, but it was a little different.
• 4:02
  SPEAKER_00: How do I put this?
• 4:03
  SPEAKER_00: It was spec right, and one of the things that they were doing was we talk about ERP a lot and or EPR, sorry.
• 4:10
  SPEAKER_00: See, I don't deal with it.
• 4:12
  SPEAKER_00: That's why my that's why Matt should have gone to that booth instead of me.
• 4:14
  SPEAKER_03: I say it all the time anyway.
• 4:15
  SPEAKER_03: It's funny you say that because I did a bunch of podcasts and it kept coming up and I kept saying ERP.
• 4:20
  SPEAKER_04: Wait, isn't there ERP enterprise resource planning or something?
• 4:24
  SPEAKER_04: Right.
• 4:24
  SPEAKER_01: Look at that, and the data that comes out of the ERP can be used to report into EPR.
• 4:30
  SPEAKER_01: It becomes two different things alphabet soup, as all of these things do.
• 4:34
  SPEAKER_02: But yes, they really gotta workshop that.
• 4:36
  SPEAKER_00: Yeah, yeah.
• 4:37
  SPEAKER_00: I was I'm grateful to be back out in the hoodies and stuff now because the tie was probably cutting off circulation to my brain, and I was losing one of our co-workers came up to me and was like, So you do own a tie.
• 4:49
  SPEAKER_00: I was like, Yeah, oh no.
• 4:52
  SPEAKER_04: That reminds me of a coworker said to me, You own a hoodie.
• 4:56
  SPEAKER_00: Oh, I wonder who that was.
• 5:00
  SPEAKER_00: Anyway, yeah, so one of the things that they had was is really neat.
• 5:03
  SPEAKER_00: It's something that I had seen years ago in a different industry, something similar, where it's trying to take the components of different aspects from of different materials so that it's it's a one source where you can piece together exactly what you're looking for in terms of a product, like an end product for your package by looking at the different resources or different thicknesses, different types of plastics, and it's all right there.
• 5:27
  SPEAKER_00: So, in the end, if you want to make sure and sure that your packaging is going to be in compliance with California or something like that, you can find that right, it'll help you design that sort of right there, help you find the suppliers and the different pieces to see if you would be in compliance.
• 5:42
  SPEAKER_00: Now, it doesn't, it has stuff like California's information there, but it also still has you double check it.
• 5:49
  SPEAKER_00: As we've talked about, it's very difficult right now if you're going state because it's such a patchwork set of rules.
• 5:55
  SPEAKER_00: Yeah, thank you.
• 5:57
  SPEAKER_00: And this is gonna help you put that together a little bit, help at least give you better insight as to ultimately whether or not you're gonna be compliance.
• 6:04
  SPEAKER_00: Now, there is a lot they've incorporated AI so you can ask questions of it and say, I'm looking for this, and it'll help you put everything together, help you which supplier and so forth that you want to look at for that product.
• 6:17
  SPEAKER_00: And again, I am babbling on this because it is outside my wheelhouse, but I thought it was really neat the how, and it was a very in-depth presentation as to how it can help packagers with their product.
• 6:30
  SPEAKER_00: But the other thing that I thought was really neat was when I finally got over to the confectionery side, I finally got to see some saw some really cool machines.
• 6:39
  SPEAKER_00: One of them was you know, when you talk about when you have like sandwich cookies, you have your base cookie, then it has like your filling, then it has something that has to put the top on that cookie as it comes down that line, finish that sandwich.
• 6:52
  SPEAKER_00: And what happens though if you have a say a windmill shape?
• 6:59
  SPEAKER_00: Now it's not just a round or square, and that's not something that puts it on.
• 7:03
  SPEAKER_00: You're not gonna get it wrong.
• 7:04
  SPEAKER_00: So you can have upside-down windmill, and your products ruin we have quality control issues.
• 7:09
  SPEAKER_00: This new machine, it like sees it, sees the packages or sees the cook bottoms as they're coming in, and then articulates it as it grabs, it'll grab and spin and put it on exactly as it needs to be in that company that was Royal Hoydick.
• 7:25
  SPEAKER_00: I'm terrible with names.
• 7:26
  SPEAKER_01: Yeah, it's a Scandinavian company, Royal Hoyjeck.
• 7:29
  SPEAKER_01: Pat did a uh a story on that equipment not too long ago.
• 7:32
  SPEAKER_01: There are some real-world applications of it.
• 7:35
  SPEAKER_01: So interesting company, very innovative.
• 7:38
  SPEAKER_00: Yeah, and the other one I saw that was really neat was again, I talk about sustainability a lot, but it was with regard to keeping pipes heated.
• 7:46
  SPEAKER_00: So as something like chocolate comes through, like you don't want your chocolate sticking to the inside of those pipes.
• 7:51
  SPEAKER_00: So, what do you do?
• 7:52
  SPEAKER_00: Right now, it's a lot of people.
• 7:53
  SPEAKER_01: Speak for yourself.
• 7:57
  SPEAKER_00: It's using they'll use heat jackets that are coming from your boiler, so you're sending water around that because you don't want the water touching your product, so you've got water heating the pipes as the product is going between that, but the costs of doing that heating the water, even the boilers are pretty efficient.
• 8:14
  SPEAKER_00: This company, I'm blinking on the name of it off the top of my head, but it basically was using frequency modulation, I think, to vibrate essentially the pipes as it's as the product is passing through with much less energy involved.
• 8:31
  SPEAKER_00: And they were saying that it was about 10% of the energy that was normally used to heat those pipes, that you can get that same effect with just 10% using this frequency modulation on those pipes.
• 8:44
  SPEAKER_00: And I am blanking on I'm terrible.
• 8:46
  SPEAKER_00: I'm feel so bad that I can't remember that company's name off the top of my head.
• 8:49
  SPEAKER_00: I've been sitting there looking through my card to see if I can find it, but it was really neat to see, and we I definitely will be including that in our innovation reports for 2027.
• 9:00
  SPEAKER_01: Fantastic.
• 9:00
  SPEAKER_00: Very cool.
• 9:01
  SPEAKER_01: Yeah, Matt, you had something to add in one ear, out the other.
• 9:04
  SPEAKER_01: I think.
• 9:05
  SPEAKER_01: I think it I can only fit so much of one.
• 9:07
  SPEAKER_01: It was regards to data.
• 9:08
  SPEAKER_01: First of all, Derek mentioned spec right.
• 9:10
  SPEAKER_01: They actually convened what's called the Sustainable Packaging Data Council, which is a set of brand owners for the most part, but then also like NGOs and solutions providers.
• 9:21
  SPEAKER_01: I believe Triak is involved, Lorax, I think, is involved.
• 9:24
  SPEAKER_01: I could be wrong on both of those, so I'm just off the top of my head.
• 9:27
  SPEAKER_01: Anyways, so there's all these different rules in Oregon and California and Colorado.
• 9:32
  SPEAKER_01: So it's a method of standardizing or harmonizing your packaging data.
• 9:36
  SPEAKER_01: But that's what Derek saw, they was everywhere.
• 9:39
  SPEAKER_01: There, there's the data that Casey was talking about from the operation side, and we've seen AI systems like Harmony AI was one of them.
• 9:46
  SPEAKER_01: I saw them at PacExpo East first, but they were here again.
• 9:49
  SPEAKER_01: George walked me through it's an AI layer that goes on top of existing software and works with your typical EPR, excuse me, ERP systems.
• 9:59
  SPEAKER_01: Yeah, see, it goes back.
• 10:02
  SPEAKER_01: I had that down and now we've loosened the lines on the ship there.
• 10:06
  SPEAKER_01: So that that's one of them, the operational side.
• 10:08
  SPEAKER_01: The other side is EPR, extended producer responsibility.
• 10:12
  SPEAKER_01: We're seeing companies like Recita was an interesting one.
• 10:15
  SPEAKER_01: They were actually at the APR booth, it was the Association for Plastics Recyclers, but they're essentially creating a software where enterprise data, so ERP, is being the input.
• 10:27
  SPEAKER_01: So we know exactly what how much film from Amcore at what gauge, whether it's mono or multi-layer, all of that.
• 10:34
  SPEAKER_01: So that can all be organized and then reported out in a in a way that goes to Colorado or goes to Oregon.
• 10:41
  SPEAKER_01: So yes, data everywhere and connectivity, being able to take disparate systems, SAP and these types of systems, and knitting them all together in one common layer, and then being able to export them to different places like Colorado, like California, in different formats.
• 10:57
  SPEAKER_01: But there is one hub or one, I don't know, single source of truth for all of the packaging materials that people are using.
• 11:03
  SPEAKER_01: So definitely on the operation side, keeping machines running, humming along.
• 11:08
  SPEAKER_01: I saw weights is a company that you, the biggest sensor company that you've never heard of, has sensors all over every line.
• 11:14
  SPEAKER_01: At they didn't tell me which company, but let's say the world's largest e-tail company for e-commerce and D2C.
• 11:21
  SPEAKER_01: So I narrow it down that it's Amazon there.
• 11:23
  SPEAKER_01: They've got sensors that are on everything.
• 11:25
  SPEAKER_01: And it's not the OEM, the equipment manufacturer that's building these sensors into the equipment.
• 11:29
  SPEAKER_01: This is a third-party layer of sensors so that a brand owner can bring that into their own systems to report out of whether this bearing has been shaking or the temperature and this little section of the conveyance, really more for conveyance, is getting a little warmer.
• 11:44
  SPEAKER_01: So the warmth might indicate that something might be out of spec.
• 11:47
  SPEAKER_01: So all of that data that's everywhere, big data.
• 11:51
  SPEAKER_01: We've always talked about big data.
• 11:52
  SPEAKER_01: Now a guy is taking that big data and is actually able to do something about it, make actionable, make brands and users of this equipment be able to make decisions and act on the data that was previously too big and too scary and too much of a too much noise to actually take a signal out of it.
• 12:10
  SPEAKER_01: So that all overpeaks for if there's enough.
• 12:26
  SPEAKER_03: Yeah.
• 12:27
  SPEAKER_01: I would have to, I don't know the answer to that, but I have to assume it's getting better at making inferences and spotting patterns.
• 12:33
  SPEAKER_01: And even let's say you the the AI that we use every day, if it's if something's misspelled in our personal, it's able to spot that and still read through it, right?
• 12:43
  SPEAKER_01: So let's say two digits get transposed in a report such that something's impossible, like a thousand degrees.
• 12:49
  SPEAKER_01: It's really not going to be a thousand degrees in this corner.
• 12:52
  SPEAKER_01: So I have to assume that there's some that there's some limits.
• 12:55
  SPEAKER_01: There's a ceiling and there's a floor where they'll it'll accept the data.
• 12:59
  SPEAKER_01: Otherwise, it might reject that data and say this is unrealistic.
• 13:02
  SPEAKER_01: This the for something to be a thousand degrees is probably a hundred degrees.
• 13:06
  SPEAKER_01: There's an extra digit or something was transposed.
• 13:09
  SPEAKER_01: But I don't know, that's just a guess.
• 13:12
  SPEAKER_00: I would say that it's not necessarily to the point where it can make a decision per se, but Matt said earlier that yeah, it helps give the producers a chance to look at it.
• 13:21
  SPEAKER_00: It's good enough to say there's probably something that you want to look at here, but ultimately it's still the human's responsibility to find that or to look at it and make sure that okay, yeah, this is something that does need to be taken, something does need to be done about this.
• 13:33
  SPEAKER_00: And just to add that the company was P of N Group and it was their Tesla tube.
• 13:38
  SPEAKER_00: So, anyway.
• 13:39
  unknown: Okay, cool.
• 13:40
  SPEAKER_03: Fair enough.
• 13:41
  SPEAKER_03: Yeah, so we've left Liz in silence.
• 13:44
  SPEAKER_03: I don't want to cut you off, Casey.
• 13:45
  SPEAKER_03: I will come back to you, but I feel bad that we've left poor Liz.
• 13:49
  SPEAKER_03: Liz, does any of this jibe with anything you've saw?
• 13:52
  SPEAKER_03: Because you did a lot of healthcare packaging pavilion, a lot of the West Hall.
• 13:55
  SPEAKER_03: Yeah, any of it jibing with what you saw?
• 13:58
  SPEAKER_03: Did you see some other things that were cool?
• 14:00
  SPEAKER_03: What was your encounters at Pac Expo?
• 14:02
  SPEAKER_04: Yeah, so being on the healthcare pavilion and some of the package or printing area, I saw less AI probably than you guys.
• 14:10
  SPEAKER_04: Did see some interesting inspection detection machinery that incorporates AI just to do a better job and to really look for things maybe outside the traditional box of defects, as if you will.
• 14:21
  SPEAKER_04: So that's interesting to see different ways AI is being used besides just like data analytics or faster, better programming.
• 14:28
  SPEAKER_04: So interesting to see things get more precise when we talk about inspection.
• 14:32
  SPEAKER_04: So that was fun.
• 14:33
  SPEAKER_04: I got to see a lot of like actual tangible things this time, which I always love.
• 14:37
  SPEAKER_04: Different ice pack options for cold chain shipping, mailers.
• 14:41
  SPEAKER_04: We've talked a lot of companies really like that GLP one focus still is really not going anywhere or not going away, I should say.
• 14:48
  SPEAKER_04: So much boom in that that really affects different mailers, different cold chain solutions for that segment, and really just like more volume in that area in general, more growth.
• 14:59
  SPEAKER_04: Got to see some cool pill bottles for OTC, new tamper evidence, new single-handed opening.
• 15:06
  SPEAKER_04: So it's always fun to see and touch these things at these shows, right?
• 15:09
  SPEAKER_04: And I know you mentioned Derek, like AI is hard to take a photo of, but that's totally true.
• 15:14
  SPEAKER_04: So I'm lucky to be able to take photos of real things in different packages.
• 15:18
  SPEAKER_04: That's always been a highlight for me is to see it in action versus just behind a computer screen.
• 15:23
  SPEAKER_04: So yeah, lots of cool innovations going through all of my 60-something videos right now, still processing them.
• 15:32
  SPEAKER_04: 300 photos, making sense of them all.
• 15:34
  SPEAKER_04: But yeah, it's cool.
• 15:37
  SPEAKER_03: Fantastic.
• 15:38
  SPEAKER_03: Yeah, I still am amazed that I keep hearing I'm familiar with the boon and GLP ones, obviously, but like how much it has touched and influenced our packaging and processing lives.
• 15:48
  SPEAKER_03: It keeps coming up in reports.
• 15:49
  SPEAKER_03: And it was a big thing in PMMI's say to the industry report about how it's driving changes with actual package sizes and packaging because people are eating differently because of them.
• 16:00
  SPEAKER_03: And it's just weird.
• 16:01
  SPEAKER_03: I guess it makes sense that everything sort of trickles down the packaging, but it the dominant aspect that it's having, and for you to but you came across it with the cold chain and stuff like that.
• 16:10
  SPEAKER_03: It is interesting that it has such a major impact.
• 16:13
  SPEAKER_04: A lot of these really big pharma companies are building new plants.
• 16:16
  SPEAKER_04: I keep seeing these releases.
• 16:17
  SPEAKER_04: Wow, new plant here, new plant there on every level.
• 16:20
  SPEAKER_04: A new plant means more equipment purchasing, right?
• 16:23
  SPEAKER_04: So there's that side of it, more employees, different auto injector pens.
• 16:27
  SPEAKER_04: I saw labeling solutions for auto injector pens, plunger rod insertion.
• 16:31
  SPEAKER_04: You see those mechanics, and then you get down to the end, the cold chain and the shippers and all that.
• 16:37
  SPEAKER_04: So it's like there's opportunities in throughout the whole thing from the processing to the packaging, manufacturing.
• 16:44
  SPEAKER_04: And then, like you mentioned, even food, it trickles down even past that, which is really crazy.
• 16:48
  SPEAKER_04: I know we've talked about this before with the rise in protein, really protein-focused food, and what that might look like for packaging in smaller portions and such.
• 16:56
  SPEAKER_04: Yeah, it's interesting to see that's still shaking up the industry a little bit.
• 17:00
  SPEAKER_03: Yeah, it really is.
• 17:01
  SPEAKER_03: I wouldn't think of it as being as have as much of a footprint as it's had.
• 17:06
  SPEAKER_01: Yeah.
• 17:06
  SPEAKER_01: It's yeah, like what Liz was saying, it's the externalities after Liz is talking specifically about getting the drug safely and to a consumer, maintaining the cold chain and not going out of temperature windows.
• 17:18
  SPEAKER_01: That's that's huge in and of itself.
• 17:19
  SPEAKER_01: But then the consumer takes the drug and their behavior changes, and the change in behavior ripples across packaging because they have to have more SKUs that are smaller sizes, like smaller snack packs.
• 17:29
  SPEAKER_01: And then we talked about the protein.
• 17:31
  SPEAKER_01: So it's a ripple effect that it's on it's it happens in the packaging supply chain before it hits a consumer, and then it hits the packaging supply chain again after a consumer takes it and consumer behavior changes.
• 17:41
  SPEAKER_04: Yeah, and not to bring up even more about one last comment is the if you talk about the distribution of these drugs, there is a brand new pharmacies popping up all over the place.
• 17:51
  SPEAKER_04: Here, furs and hymns, you guys have seen those commercials.
• 17:54
  SPEAKER_04: Roe.
• 17:55
  SPEAKER_03: I was gonna say row.
• 17:56
  SPEAKER_04: Yeah, like all these now ones that are like online, they're like direct-to-consumer pharmacies that we've never heard of until now.
• 18:03
  SPEAKER_04: I don't know if they're all new, but one of the people I was talking with, uh a cold chain company, was like we've had these little mom pa pharmacies that had 12 employees now have 560 employees because of GLP1.
• 18:17
  SPEAKER_04: That's all they distribute, or because they're only servicing these online pharmacies.
• 18:21
  SPEAKER_04: So it's not just through doctors' offices, it's us consumers going online, and there's a whole new segment and a whole new distribution path for these drugs.
• 18:29
  SPEAKER_04: So that requires more and more shipping packages and containers.
• 18:34
  SPEAKER_03: Very cool.
• 18:35
  SPEAKER_03: Now I cut Casey off and I know we're gonna have to circle back, but what was it that you wanted to comment on, Casey?
• 18:40
  SPEAKER_03: I wanted to make sure we didn't forget about Liz.
• 18:43
  SPEAKER_02: Yeah, no worries.
• 18:44
  SPEAKER_02: Yeah, it was just a quick thing on talking about AI and the reliability of it, and especially if it doesn't have good data going into it.
• 18:51
  SPEAKER_02: I was just it got me thinking about agentic AI as I was saying.
• 18:54
  SPEAKER_02: And I think stock IQ is it they had a really cool solution.
• 18:58
  SPEAKER_02: This is not to knock stock IQ, but it just thinking about the concept of using an agentic AI to take off things like talking to a vendor, just there's just something scary about that to me.
• 19:10
  SPEAKER_02: But so it's just I think overall, just human review is just so important with AI.
• 19:15
  SPEAKER_02: So that's all I really wanted to say.
• 19:17
  SPEAKER_03: Yeah, no, I say all the time on here, and I would have made the comment, and I'll make it again that I'm surprised how trusting industry has become.
• 19:24
  SPEAKER_03: And I think we were slower to get it on the plant floor, but you guys have just given examples where it is on the plant floor, and I'm very surprised how trusting we are to involve it in the day-to-day production or day-to-day reveal.
• 19:36
  SPEAKER_03: Like when you were saying that it was measuring oil levels and stuff like that, to get it that close, but I guess there's somebody overseeing.
• 19:43
  SPEAKER_03: I'm hoping there's somebody overseeing it to make sure that it our overlords aren't taking everything over.
• 19:50
  SPEAKER_00: Yeah, Casey and I did talk about that in our podcast from PacExpo about how, yeah, it's a really bad idea to let AI run wild in your plant.
• 20:00
  SPEAKER_00: It's not a good idea.
• 20:01
  SPEAKER_00: Yeah, this is as good as a tool as it is in many respects, it's still definitely not something.
• 20:08
  SPEAKER_00: It's still just that, it's a tool, it's not the brains, it's just a tool.
• 20:11
  SPEAKER_00: Totally.
• 20:13
  SPEAKER_01: I saw an interesting cartoon the other day where it had a uh like a stagecoach and wagon, which is only a hundred years ago.
• 20:22
  SPEAKER_01: That was our technology, and they had two kind of pioneers in the stagecoach and wagon hooked up to the Starship Enterprise as like the instead of a horse, and it said, giddy up.
• 20:32
  SPEAKER_01: That's pretty much this the state that we are in right now.
• 20:35
  SPEAKER_01: We are allowing something much more powerful than we've ever known, control a lot of things.
• 20:39
  SPEAKER_01: So I thought that was apt to a lot of the AI discussion around Pac Expo.
• 20:43
  SPEAKER_03: I would say, yeah.
• 20:45
  SPEAKER_03: And I think that's a good way to uh put a button on our discussion for today to wrap up what we've saw.
• 20:50
  SPEAKER_03: I'm sure it'll leak into some upcoming end of the lines where some pack expo stuff that we forgot about will get covered.
• 20:56
  SPEAKER_03: But thanks again for everybody for being on here, and thanks again for everybody for listening.
• 21:01
  SPEAKER_03: Thanks, everyone.