Summary

Main Points

• Manufacturers could create profiles for every product to simplify the reselling process through an app.
• The app would allow users to verify the condition of their items and list them easily.
• AI could potentially identify objects for reselling by analyzing photographs.
• The Internet of Things could play a role in the future by embedding tags in items, although this technology might still be far off.
• The speaker considers a co-working opportunity at a fashion hub in Berlin but decides to focus on their own project first.
• Knitwear is mentioned as the most flexible and least wasteful option for on-demand production.
• New technologies could revolutionize the knitwear industry, like pigment printers that print color onto yarn during the knitting process.
• The technology enables complex color patterns without the need for multiple yarns.
• The German knitwear industry is innovating, and a sponsorship from a machine manufacturer is changing the dynamics at a co-working space in Berlin.

Stories and Examples

• The speaker shares a story of their struggle with traditional knitwear production in Nepal and the inefficiencies of sampling back and forth.
• An innovative approach is shared where pigment printers attached to knitting machines allow for customized color patterns with one yarn color, revolutionizing the potential for on-demand, low-waste knitwear production.
• The speaker is offered an opportunity to work at a co-working space at Bikini Berlin, a fashion hub potentially due to their expertise and interest in knitwear.

References and Citations

• Bikini Berlin, the mentioned location of a fashion hub co-working space.
• The German manufacturer of knitting machines, which sponsored the co-working space.
• Internet of Things, referred to in the context of its potential for item tracking in the future.

Potential Action Items

Follow-Up Questions

• What are the specific advantages of using an app for reselling items compared to current methods?
• How does AI currently contribute to object identification, and what advancements are expected shortly?
• What are the precise benefits of pigment printers in the knitwear industry?
• How does the sponsorship from the German manufacturer benefit the fashion hub in Berlin?
• What are the speaker's personal plans regarding their 'shed' project and their potential collaboration with the fashion hub?

Transcript

Okay, so I'm just gonna... Maybe producers would have a... For every profile, and for every product that you sell, basically, you could have a profile ready, right? In an app.

But then, maybe, if I decide I want to get rid of my Adidas jacket, then I just go in the app, and I find the profile based on some number, and then I basically just have to tick some boxes verifying the condition, and then everything would be ready, right? And, I mean, you would not have to have all this hassle by, I don't know, profiling your jogging pants on your own, but it's basically in the system, and it's, like, legislatively... your force as a producer to have that. Yeah.

So, for context, in order for there to be a system that can match people's objects to demand, there would need to be a way for people to easily list these objects or identify them and list them. So, the suggestion is the manufacturer themselves could put out an inventory, and then people can basically just, like, click through condition, report, whatever, images, and list those things. I think that AI also is the solution there, because there's already apps where you can photograph your refrigerator, and it can identify everything in the fridge and make recipes. So, we're getting to the point where identification is getting better and better and better that you might be able to, at some point, take a photo of a bunch of objects, and the AI could actually identify what they are.

Then there's the whole Internet of Things thing, which is if, like, electric tagging, electronic tagging is cheap enough and it could be present in every item, and maybe it's not an NFC chip and maybe it's something else, that might help. But I do think that's a ways off, because then you'd have to actually tag everything. I think this AI identification is the closest. Yeah.

I mean, it would be so cool. Also, this hub in Berlin, this fashion place, is a co-working space. And they have that place at Bikini Berlin. Bikini Berlin.

Yeah. She basically asked me last night if I wanted to work there. Why? What?

Why? Because they like me. But you have to pay, right? Well, I think she offhandedly was suggesting I work with them.

But I think if I were to use the co-working, yeah, I would have to pay membership fee. You don't want to work with them? Well, not right now. I want to launch my shed first.

But they are shifting their focus to knitwear. And they're actually getting sponsored for having... The whole thing? No, but knitwear, as I've been feeling, I mean, it's obvious, excuse me, but it's obvious that knitwear is the most flexible for on-demand production.

It's the least wasteful because it's one filament. And you can build the technical features of the material into the actual unit without extra coatings and stuff. Because knitwear, to an extent, knitwear allows you to actually dimensionally create things. But then you should consider working with them because that's your interest and you enjoy playing in the programs.

I know. And so it is a big thing for me. It's right back on my radar because knitwear has been a blind spot. From the very beginning, I wanted everything to be knitwear and I tried to make it in Nepal.

But it was such a sad process of sampling back and forth between Nepal. And the idea here is you basically, because it's so algorithmic, it's so mechanical, it's so mathematical, you can... Okay, I have to tell you that it's so cool. So already, a knitting machine, it prints out the whole garment.

So you don't need to do any construction afterward, maybe just a very minimal amount. On top of it, one of the annoying things about knitwear machines is that if you do one-off designs, you have to restring it every time with whatever colors are being asked for that project. Or if it's a different gauge yarn, you have to change the gauge. And those things, they take work.

So on the meta level, or on one level of the dynamic, it's about collating orders and then placing them with certain machines so that that machine is set up with that yarn and it can pull different orders from a bunch of different things and do it all at once. But then there's this other solution, which is so cool. It's a digital printer. It's like a pigment printer attached to the knitting machine.

And so there's one color yarn. And as the design is being made, it calculates where it needs to print the color onto the yarn so that the image can show up exactly in those places. So you can have super complex colorings that would not be possible if you had to actually switch out every yarn or knit multiple yarns at once and pull certain ones forward and backwards. I think it's such an amazing technology.

And apparently it already exists for embroidery machines, which is also super smart because you never need to change the color of the embroidery thread. You basically always have white, and then it can print the colors as in embroiders. So cool. So they got sponsorship from the German manufacturer of these knitting machines, and they're getting a couple...

He said this is Signare. This is Born. They're really cool. I think I learned a lot from them.

Okay. Yeah. Okay. Now what I'm going to show you...

Additional Info

Arguments and Areas for Improvement

• There may be privacy concerns when it comes to the use of AI and the Internet of Things for tracking and selling personal items.
• The cost and complexity of implementing AI and IoT technologies may be prohibitive for small manufacturers or resellers.
• The speaker's hesitance to collaborate immediately with the fashion hub could indicate potential concerns about the practicality or alignment with personal goals.

Related Topics

• app development for product reselling
• artificial intelligence in retail
• digital printing on textiles
• fashion industry co-working spaces
• fashion technology
• internet of things (iot)
• knitting machine innovations
• machine learning
• on-demand knitwear production
• sustainable fashion

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