Latest / The Interline Podcast / AI Video On The Shopfloor And In-Store, Defence Spending On Textiles, And Anti-Social Sentiment
Transcript
- speaker-0: So welcome to the edit from The Interline, the show where we run a quick fire analysis on our pick of the most important fashion and beauty technology stories from the last seven days. I'm Grace, the social editor, and I'm joined by Ben, the editor-in-chief, and together we have around twenty five minutes to give you our analysis on the stories that we think really matter. speaker-1: Hey Grace, how are you doing? You got a different background this week. speaker-0: Yeah, I'm just at my friend's chalet in Abersoc, so a bit different, but luckily still a place to record. speaker-1: Hey, well, you know what? I was away the previous couple of weeks, so I think it's fair that we trade. Let's do it. speaker-0: So the first thing that we're talking about is AI because it's been a very AI heavy week, but I suppose we have to go where the news is. And I think it's fair to say that it's been a bit of a broad spectrum with the AI stories. So it's neither AI good or AI bad, but a bit of a balance. So the first story is one that you actually sent my way, and it's something that the Interline published just a few days ago. So Coast Digital, which owns GSD labor quantification, has launched something it calls real motion, which is essentially a AI powered motion analysis for garment factory operations. So I wanted to know what prompted you to pick this story. I'm gonna hazard a guess this is a bit of a testament to just how far AI is being embedded into the supply chain, but let me know what you think. speaker-1: You're correct. It is a bit of a testament to how AI is being embedded in the supply chain. So labor quantification is not the official term for this. It's the one I've ended up using over ⁓ multiple years of looking into it. So GSD is the accepted and I mean that in a most literal sense. It's accredited by the International Labour Organization. It's the accepted method for what you refer to as like motion study or time study, which is quantifying the amount of time that it takes to do a specific factory operation. So that can be a sew operation, it can be a pick operation, it can be a put operation, all of the things that happen on a sewing line for somebody to attach one piece, one pattern piece to another. It is scientifically derived and data backed. ⁓ it's not the only ⁓ one of these, but it is the most prominent one for apparel, at least. There are comparable things in ⁓ in footwear. Sartre has one called Timeline, I believe. But the long story short is that GSD in general, as a methodology, is a way of mathematically and scientifically determining how long it should take to. Do something in a factory and you stack that up and it's how long it would take you to make a product. It also includes what you refer to as like in-cycle time and out-of-cycle time. So ⁓ things that are what they refer to as value add, things that refer to as not value add. ⁓ and from that you can start to work out kind of standards for and allowances for. People going to the bathroom, ⁓ people taking breaks between work and things like that. So it's the foundation upon which a lot of costing ⁓ and negotiation and relationships between brands and their factory partners should be built. Now, it's not universally used for that standard. A lot of people will talk about ⁓ SAMS, so standard allowable minutes or standard minute values, SMDs, depending on where you are, but what they will actually do to get to those values is like historical averaging based on how factories have performed before and costing based on ⁓ what ought to be living wages and things in ⁓ in particular areas. It's done on kind of historical averaging and guesswork rather than this scientific side of things. The reason that is, is that these kinds of method time and motion analysis are They can be tricky to implement. ⁓ they can be they can be tricky to ⁓ to centralize around, although they are a standard. They're not a standard that everybody is just instinctively embraced. Now, the way those standards are built is literal stopwatching. ⁓ so they they use that in a glyph sense, but it is the each of these operations is assessed by somebody there with a like racing style start stop. ⁓ and the and those people are called the ⁓ practitioners or assessors, I think. Elevating AI. To the status of being a foundation for this kind of thing. So being a foundation for pairing operations that you can see in video to pre-existing defined operations with standard minute values, or even creating new ones, is a massive vote of confidence from a company that is really tightly embedded in the supply chain, in the accuracy. The robustness and the accountability of AI in these processes. Now, th don't get me wrong, there's human review in in all of this, but ⁓ philosophically and practically, this is probably one of the kind of biggest votes of confidence for the fact that you can take AI in a nebulous sense, it's it's a vision model applied on top of ⁓ video footage. You can take that and you can use it to do things that are fundamental to relationships between brands and factory partners, to costing, to everything else, and to a standard that is fully independently accredited by the International Labour Organization. I have not spoken to GSD about this since I saw the news. It only came out a couple of days ago. And it's niche in the sense that some people have glazed over probably ⁓ in that in that description that I've just provided. I think it's a big deal. And I think we're gonna see some things come out of this in the near future. speaker-0: For the next story, we're actually gonna pull on the same thread of AI detecting things from video, but actually in a very different setting, so supermarkets. So this week, Iceland, not the country but actually the value supermarket, which is known for its frozen cheap food here in the UK. So they've announced that it's cut its theft-related losses in stores by 80%. After implementing what the stores have dubbed as AI crime detection technology. So shrinkage is actually a very real issue for retailers in food and beverage. But it's also a massive issue in fashion, where theft often happens in the fitting rooms, which grocery stores obviously don't have, but it is a big issue in fashion. So based on the success of this, Iceland is now apparently rolling out AI-assisted face detection. As an extra lever to prevent shoplifting from known prior offenders. But really interestingly, another story this week actually comes from Sainsbury's. So another UK supermarket that does actually sell clothes in its store. They've suggested that this kind of face detection technology might actually create some issues. So Sainsbury's have actually paused their use of face watch. Which is a software that's also used in other UK retailers. After there was an incident of a person actually being escorted out of their store in London, after FaceWatch incorrectly identified him as a prior shoplifter. So it's a very mixed bag with this technology. And it's also the flip side of the same class of AI that we've just been talking about with GSD Realmotion. So I wanted to know what's your take with this. speaker-1: So you're correct that it is this is a very UK centric story, by the way. We we are going across the pond for the next one. You're correct that it is the same class of technology in that GSD real motion works based on phone video or other video sources of people performing sewing operations and factory operations. And it then uses an AI vision model to ⁓ to derive the ⁓ operations from that. Face watch and other Sort of detection technologies for in-store use seem to work the same way. They are not architected on top of like new cameras or new sensors or anything like that. As far as I understand it, FaceWatch works based on CCTV feeds that already ⁓ exist and are very prevalent in retail here in the UK. And the other one, which is not named, but that Iceland ⁓ has already used to reduce ⁓ theft-related shrinkage by 80%. Again, same thing. It's layered on top of existing CCTV video feeds, but that one is done at the product and shelf level. So ⁓ the Iceland one that they have is not looking for people, it's looking to track ⁓ products and where they have left shelves and then subsequently not been purchased or not been returned. Now, it sounds like one of those is more reliable than the other. ⁓ it sounds like the object detection is probably slightly more accountable than the than the face detection. They're both pr kind of fundamentally the same thing. Now, what we've just said about GSD being a real vote of confidence in how far you can embed AI in very sensitive operations upstream, this demonstrates there's a lot of variability in here, because these are very, very sensitive deployments downstream. Very sensitive deployments in the sense that they are. Culturally part of the same issue that we're seeing in the US with the flock cameras. Now, those are not used in retail, they're used as ⁓ license plate detectors. ⁓ but there is a huge kind of groundswell of ⁓ anti-flock sentiment in the US, ⁓ which is it stems from people not wanting to be surveilled. And the reasons that people don't want to be surveilled, generally speaking, are they they protect their own personal privacy. But nobody likes being accused of a thing that they didn't do. And nobody likes knowing that the machinery exists to pin something on them that ⁓ that they didn't do. Now, in the early days of generative AI in particular, ⁓ there were a lot of stories about ⁓ lower courts and things in the US using it for traffic violations and things along those lines to basically just automate a bunch of that stuff. ⁓ and ⁓ I think a bunch of folks who were not rightly accused ⁓ ended up falling foul of it. It seems like that's becoming the case here with the face detection side of things as well. Now, the part that worries me a little bit about this is not that sewing operation detection is seemingly better than basic face detection. For all we know, that could just be down to the quality of the CCTV feeds or something else. It's that all of these things can get better. But generally speaking, the trajectory of AI is towards progress and is towards maturity and is towards greater success and use in verifiable domains like this. and right now we get to have a conversation about what happens when face detection in shoplifting scenarios goes wrong. I'm equally concerned about what happens when it goes right in the longer term. This is a case where I understand the retail industry's prerogative to reduce shrinkage, but it walks us straight into a cultural quagmire that I think n people need to be keeping watch on what's happening with Flock in the US to see how that's gonna go. speaker-0: So the next one is actually a quicker story, and there's no AI in it, at least not outwardly, and we are also crossing the Atlantic for this one. So the Pentagon and the Department of War have partnered with Georgia Tech and also other bodies across education, NGOs, and industry to modernize textile manufacturing in the United States to support the defense industry. So the initiative is called FutureTechs, and apparently it's promising up to four hundred and eighty million dollars of domestic investment over the next decade, starting with thirty six million dollars in the first year. So I know you've done a bunch of interviews with people in manufacturing, materials, and also ingredient innovation over the past few months. So what is your perspective on this story? speaker-1: So I have spoken to the ones that come to mind are so Stephen Bates from Rheon Labs, Arn Arens from Unspun. And the the most relevant interview for this actually is one I did towards the tail end of last year with Nick Reid, who's the ⁓ the CEO and the founder of Neeme London, which is a menswear brand. Pretty universally, these people agree that being able to innovate in the way that we create materials and in the way that we produce fashion is a necessity if you're going to reshore these things. ⁓ so I think nobody believes that taking the offshore sourcing and manufacturing model that is currently in effect in China, Bangladesh, Vietnam and so on, and relocating it to America, to France, to the UK, to Italy, or anywhere else. is the way that this should work because it it inevitably leads to a massive increase in prices. ⁓ we talked about New Balance previously and ⁓ we commended them for s showing that your made in UK or made in USA shoes are significantly more expensive than ⁓ the ones made overseas. Now, the other thing all of those people agree on is that in order for brands to be able to place a lot of domestic orders, either for materials or for manufacturing, The infrastructure for that has to exist. It's like a chicken and egg scenario where domestic factories and domestic mills are not going to spend a fortune of their own money on building out like on-demand, low MOQ, innovative capacity if brands are not going to then place orders for it. Brands are not going to build collections on the assumption that that capacity exists until that capacity actually exists. So you end up in a weird cycle, which is what ⁓ Nick from Neeme talked about. Now, I think everybody also agrees that state level sponsorship and subsidies and other programs are the way to bridge that gap. They are the way to shore up the domestic supply chain for materials and production. Now, $480 million is not a lot of money to do this in a country the size of the US. $36 million in the first year is absolutely not a lot of money, but it is a step in the right direction. And I think the interesting part for a lot of this is you're not going to get. That kind of investment and that kind of subsidy from governments who just want to reshore textile production or who want to reshore manufacturing. I don't think the political will is there. I don't think the industry ambition and kind of achievability is there. Every country, but the US in particular, spending a lot more on defense at the moment, if you can successfully hook those subsidies, investments, and sponsorships from the government into defense contractors and ambitions. And then the upshot of that is that you end up with a domestic industry for textile production or a larger one, or a domestic industry for garment manufacturing, or a larger one. That's what it's going to take, I suspect. And that won't be wildly different to what it took to ⁓ around World War II or other other initiatives when the ⁓ kind of domestic industrial build-out happened. as a function of defense. And then afterwards those same logics around assembly lines and everything else was repurposed for the automotive industry or heavy steel or all those other kinds of things. So yeah, I I think it's it it's sad in a way that that's what it takes, but history tells us that that is what it takes. And ⁓ I suspect that this will be where a lot of the success for upstream innovation ends up coming from from a pure like who's paying for it point of view. speaker-0: So I was hoping for the next story that we could have a fun conversation about Croc's new mascot, Niles, which according to the press release we got sent is ushering in a whole new bold era of storytelling, but actually we found out it is just a man in a crocodile suit. I don't know about you, but this kind of whimsical storytelling for the whole family is something that I really enjoy. But instead, unfortunately, we're gonna talk about two things that in a much less wholesome way have also been marketed across generations, but now they're facing a bit of reckoning for it. So the first one and the first topic is about social media, and basically Meta has had this case brought by 29 US states who are accusing Meta of knowingly allowing Facebook and Instagram to contribute to negative health outcomes for minors. Now, you and I have talked about the social media bans before, one of which is coming into force here in the UK next spring, but this is something very different. It's active large scale litigation. Based on the foundational principle that social media is addictive and harmful. Then we've also seen this week that OpenAI, probably in response to this trial, has announced that they'll be launching a new ChatGPT for teens, which includes built in safety protections, controls, and also structures designed to support learning. So all of this is aimed at people between 13 and 17. So there is obviously so much about all of this that we don't really know, but I wanted to get your take on what you think this means for fashion. speaker-1: This is a long question, but I think my answer's quite short to this one actually. We have previously talked about social media bands, which are not exclusive to the UK and similar things being debated in France, although it's it's struggling there. In Australia is obviously ⁓ at the the forefront of a lot of this. All of this is based on teens and young people being the most at risk population when it comes to the deleterious effects of social media and potentially ongoing parasocially sorts of relationships with ⁓ with AI. I think fashion brands are aware of this. We're not telling them anything new. I think a lot of fashion brands don't really advertise to 13 to 17 year olds. although I also wish we were having a conversation about Niles, because I like I like the dude in the crocodile suit and give me give me more mascots. ⁓ in generally speaking, we should probably have one at the interline at some point. but what all of that is is a lightning rod for a wider conversation about social media's negative impact on people of all ages and all backgrounds, and potentially the same with AI as well. I've recently done an interview with somebody who works in the fintech side of things, ⁓ so the kind of deferred payment stuff. And I had a conversation with him about something that you and I have talked about relatively recently, which is the idea of AI. being persuasive and AI kind of encouraging people towards transactions and those transactions then becoming more seamless as a result of deferred payments by now pay later and so on. you can extrapolate a lot of that to Instagram, you can extrapolate a lot of that to ⁓ to TikTok. I I think this is something that is the beginning of a wider anti social media reckoning ⁓ that's gonna spill over into AI. And for fashions purposes, the the the concern is very simple. It's but where do you put yourself? Where do you put your communications? Where do you put your advertising dollars? speaker-0: So our last story is a bit more of a segment, and I think this may be one that we end up bringing or making a weekly fixture. So we do get a lot of investment and acquisition news sent our way. And for this week, you and I have picked the three announcements that we think are most relevant for fashion, even if they're not necessarily fashion stories. So this week Higgsfield was The AI creative platform that's been at the center of a lot of conversation around generative video has raised another $400 million, which values it close to $5.5 billion. Then Bloomberg also reported that Anthropic are in talks to buy Descartes for $6 billion. And I know you've spoken with Descartes before, off the record, about their Lucy models. So I'm keen to hear your thoughts on this. And also finally, we saw that the LA Times reported that Dimension, which actually builds itself as a operating system for TikTok shop, has raised a much more modest $1.6 million. So let's talk about what all of these stories mean for fashion. speaker-1: Yeah, I think we do end up making this a weekly or bi-weekly segment. Let's see. ⁓ and I think I can give you some quick answers to each of them. So I find Higgsfield fascinating. it is by far the biggest and most public kind of AI creative platform. It's primarily expressed as video. and the The part that I find the most interesting about them is so they do have fashion-specific ⁓ pushes in what they're doing. They have a model, I can't remember the name. I wanna say it's called Source, but don't quote me on that. ⁓ they have a ⁓ a model and a workflow that is fashion specific. but the most interesting thing that they've done, I don't know if you saw this, they they've pushed out a couple of purely air-created films starring real actors. There was one called Cully Boys, I think, ⁓ which are Bizarre to watch. ⁓ if you I I would encourage everybody to spend a little bit of time looking through them just to benchmark the state of the art and video generation, but also to see just how big the community has become around a lot of this. So Higgsfield also do their own kind of content production. They have like in house and partner studios and things who create like films and shows. And they'll do short films and they will open source them. Which is again like a fascinating concept of like open sourcing media. ⁓ so they will open source all of the prompts, all of the workflows, everything else that went into it to allow people to experiment and remix ⁓ and and everything else. I I think this is one of those valuations that probably took a bunch of people by surprise because they'd be like, well, it's it's just it's a front end on a lot of different AI video generation models. And let's see Dance 2.5 being the most popular one. How does it earn that valuation? I think it earns that valuation by Basically being the de facto platform for a lot of the community building experimentation that comes with all of this. Now, Descartes, you're right. I did speak to them off the record a little while ago. Their Lucy model is ⁓ the first, I think, or the the first I have seen like real-time video model. So the the the benefit of it is you and I could be having this conversation, and with some slightly perceptible but not massive delay, the The model will ingest the video stream and then generate a new video stream out of it that shows you wearing different clothing. ⁓ and it's it's pretty good. ⁓ you know, it has the same limitations of not being a real simulation that every AI model has. But I think this would be anthropic making a fashion play, essentially, because yes, you can use that real-time video model to do a bunch of other stuff. It's primarily been expressed in Descartes marketing and everything else as a fashion application, as an a new frontier for virtual try-on. So ⁓ I think again, six billion is a lot of money, but ⁓ maybe that's a valuation that's earned. And then the final one, dimension. ⁓ I'll use this to plug an upcoming interview that I've done in our main like Thursday interview show. ⁓ coming in a couple of weeks, ⁓ I've interviewed somebody who works in social strategy and influencer relations and creator relations and things like that. And the main takeaway from that conversation is just how professionalized the creator economy ⁓ and the seller economy around these kinds of things is becoming. I think people tend to think of live shopping and ⁓ cr you know, influencers and creators and things as being a bit scrappy and there being like a lot of unstructured money like sloshing around. ⁓ I think all of this is way more operationalized and professionalized and industrialized than people give it credit for. Now, I've I've not used dimension, I have no no opinion about the product itself, but this category of like financial tools, logistical tools, operational tools, product tools and things for creators and sellers is a category that I see growing pretty quickly. speaker-0: Amazing that's all the stories this week. speaker-1: Great. Thank you. Grace, enjoy the beach. You are not here next week, is that correct? speaker-0: Yep, I'll be on holiday next week, so yeah. speaker-1: Yeah. Perfect. So in your absence, we will be running a ⁓ a mailbag episode. So ⁓ it's a special episode of ⁓ the Inteline podcast rather than this one, where we've fielded some questions from readers and listeners. ⁓ and I brought in some industry friends from Business of Fashion, Voxalo, Clow3D, ⁓ a couple of other ⁓ areas to ⁓ to answer them. It won't come out on Tuesday. I don't know exactly what day it's coming out next week, but ⁓ to fill the void left while you are off surfing, ⁓ we will be tackling some some reader questions next week.