Leuty Parker

Tag: #ai

  • New Direction; SWT vs Medi-tech

    The future of fashion isn’t just about aesthetics anymore… it’s about intelligence!

    From designing and selling fashion inmy BA degree, I constantly found myself moving beyond traditional garment #design and towards something a bit more functional. This shift became even more interesting as I sawthe rapid rise of #athleisure, where the audience increasingly expected their clothes to do more than simply look good. The bigger question: what if sportswear evolved beyond performance apparel into performance technology? Could the next generation of garments actively monitor, support, and even enhance our health?

    This shift isn’t about shock, and turning people into superheroes through futuristic gadgets. It’s about #designing products that subtley work in the background, to help us better understand our bodies, identify potential #health concerns earlier, and enhance our overall wellbeing. This is where smart wearable technology (#SWT) becomes really exciting.

    Brands like @KYMIRA are leading this evolution, blurring the boundaries between fashion, sportswear and healthcare through scientifically driven innovation. Alongside pioneers such as @Tala and @NowYouLive, these companies are demonstrating that the future of fashion isn’t just about what we wear, it’s about what our clothing can do for us. Redefining the relationship between design, performance and health, and I’ll be exploring each of them in more depth in future posts.

    And over the last few years, #med-tech has undergone a remarkable transformation, where #healthcare is no longer focused solely on digitising patient records or replacing outdated systems. Instead, we’re entering a new era of intelligent technologies that combine #AI, #robotics, advanced #sensors and #biological data to support faster diagnoses, personalised treatments and continuous health monitoring. Rather than existing as isolated innovations, these technologies are increasingly becoming connected #ecosystems, integrating hardware, software and real-time physiological data to improve clinical decision-making and long-term patient care.

    For someone interested in SWT, this represents an incredibly exciting direction. The boundaries between fashion, engineering and medicine are beginning to blur. #Clothing is evolving from something we simply wear into something that interacts with us, collecting data, communicating with healthcare professionals and adapting to our individual needs. Smart textiles, embedded #biosensors and AI-powered wearables are opening the door to garments that can monitor heart rate, analyse posture, detect early signs of illness and support rehabilitation, all without disrupting everyday life.

    This is why I believe the future of fashion lies beyond traditional apparel. Designing for sport was only the beginning. The next frontier is creating garments and wearable devices that become part of our healthcare infrastructure, products that are as beautifully designed as they are clinically valuable. It is no longer just about creating clothes that enhance performance; it is about developing intelligent companions that help us live healthier, longer lives.

    My new direction is to explore the emerging world of smart wearable devices and robotic healthcare technologies, not simply as medical innovations, but as the next evolution of design itself. From AI-powered health monitors and smart textiles to robotic rehabilitation systems and adaptive prosthetics, these innovations are redefining what it means to wear technology. They are not designed to make us superhuman; they are designed to make healthcare more proactive, personalised and seamlessly integrated into our everyday lives.

    Because perhaps the most exciting fashion trend of the next decade won’t be defined by colour palettes or silhouettes, it will be defined by intelligence.

  • Memes

    LOL, it’s obvious that I used chat GBT to perfect my past post content. Everyone does it, don’t be in denial…

    Internet memes may seem like simple jokes or viral images, but they actually reveal something much deeper about modern culture. A meme is best understood as a unit of cultural information that spreads through imitation and adaptation online. These digital fragments evolve rapidly as people share, remix, and reinterpret them, turning memes into a living form of communication.

    Across the internet, memes exist within distinct communities—each with its own humour, language, and purpose. Some revolve around everyday frustrations, such as bad driving, while others grow within highly specific fandoms or gaming cultures where insider knowledge strengthens group identity. In more personal communities, memes serve an even deeper role, helping people share experiences, cope with challenges, and find validation among others with similar lives.

    Technology is also reshaping meme culture. Artificial intelligence is beginning to generate its own meme-like content, creating a strange mix of fascination and humour as humans react to the unpredictable outputs of machines. At the same time, memes are increasingly used for political commentary, allowing complex ideas to be shared quickly through simple, recognisable formats.

    Despite the chaos and variety of meme culture, one powerful trend stands out: communities dedicated to positivity. In these spaces, memes are deliberately used to uplift, motivate, and highlight moments of kindness. Ultimately, memes are far more than fleeting internet jokes—they are evolving cultural signals that reveal how people connect, express identity, and make sense of the digital world together.

  • Because AI is so woke right now

    You’ve likely noticed I’ve shared plenty of posts about AI, it’s a key part of my niche, blending fashion with technology alongside content on health maintenance (diabetes and TBI). This post continues that focus, while also keeping readers up to date with developments from a more professional perspective.

    Speculation has increasingly shaped global markets since the 1980s, as investors discovered that hype can generate greater returns than underlying business performance. This dynamic fuelled a series of boom-and-bust cycles — from the dot-com era to cryptocurrencies, NFTs and now AI — with AI investment currently driving much of the recent growth in the S&P 500. Yet, like previous speculative waves, signs suggest the AI surge may also be vulnerable to correction, even as investors begin searching for the next trend to replace it.

  • AI in healthcare

    Ai could transform healthcare because care delivery has lagged behind medical progress. Despite advanced diagnostics and treatments, the system remains inefficient, fragmented, and burdened by outdated workflows. Digitisation, especially electronic health records, often worsened clinician and patient experiences instead of improving them.

    Historically, healthcare adopted technology in narrow, task-specific ways rather than redesigning care. Early AI efforts failed due to simplistic models, paper-based data, and a focus on high-risk tasks like diagnosis. Today, low-risk AI applications (like documentation, scheduling, and billing) reduce administrative burden, improve clinician–patient interaction, and build trust.

    AI’s real impact is in early disease detection. Using routine data like ECGs (Electrocardiogram… sounds like an octopus breed), AI can identify serious conditions more accurately than clinicians, enabling automated screening and preventive care. Adoption must be even, so involving doctors in AI design is crucial, and over-reliance could deskill practitioners.

    System-level factors also matter: dominant EHR (Electronic Health Records) providers control patient data, giving them influence over AI innovation. Regulators must balance oversight with the fast pace of AI development to ensure safety without stifling progress.

    The future for clinicians is optimistic! AI won’t replace doctors, just free them from routine tasks, allowing them to focus on judgment, ethics, and patient care.

    AI has the potential to make healthcare safer, more efficient, and patient-centered. By handling routine tasks and enabling early detection, it frees clinicians to focus on judgment, ethics, and human connection. Thoughtful integration is key to realizing its promise, and even though my interest is commercial and design, not medicine, these insights on AI in healthcare can inspire and inform how we approach design challenges.

  • ….. More in depth; AI in design

    One thing that has constantly intrigued me, throughout studying fashion design in my BA then going on to be a fashion developer in London and Hong Kong, and even analysing trends in my MSc in business, was what is woke in a population. That concerns the “what?”… but my pest career focussed more on the “how”?.

    Looking at the current “what,” this post focuses on a topic that particularly interests me: what is trending globally right now—AI. A strong example of this intersection between technology, fashion, and design is L’Oréal’s partnership with IBM. By integrating AI into beauty innovation, the collaboration enables more personalised, inclusive, and sustainable products, showing how technology can quietly enhance design and creative expression rather than overshadow it.

    IBM and L’Oréal are exploring how AI can transform innovation. Using IBM Watson X, they’re developing AI assistants that simulate complex scenarios—originally for education, like classroom interactions—but for L’Oréal, the focus is on cosmetics. Custom AI models can help researchers design products faster, more creatively, and more sustainably.

    Take lipstick as an example. Traditionally, it’s made in two stages: a highly opaque base delivers colour and a matte finish but feels dry and uncomfortable, followed by a second layer to improve wearability. The difference between products like Super Stay 24 and Mad Ink lies not in longevity—they both last—but in comfort. Mad Ink avoids the need for constant reapplication thanks to careful formulation.

    L’Oréal has always been a science-driven company. Early liquid lipsticks in the 1930s were little more than stains; later formulas were heavier and less convenient. Over decades, L’Oréal’s chemists refined these products through trial and error, testing everything from colour and texture to durability under extreme conditions. Every lipstick is essentially a piece of technology, backed by millions of data points.

    The collaboration with IBM, launched in early 2024, brings together two century-old innovators with strong scientific cultures. IBM works directly inside L’Oréal labs to understand researchers’ needs, creating custom AI models tailored to the company’s unique data. Unlike general-purpose AI, these models are smaller, faster, and more energy-efficient, allowing L’Oréal to leverage decades of research in a usable, targeted, and transparent way.

    The potential impact is huge. AI can accelerate product development, expand creative possibilities, and make innovation more sustainable. By narrowing the gap between imagination and reality, it enables breakthroughs that were previously difficult or impossible. This approach isn’t limited to cosmetics—similar AI-driven strategies could help clothing companies fast-track design and fabric development, processing vast datasets and testing countless scenarios to support designers’ judgment.

    L’Oréal also monitors early signals from fashion and social media to anticipate emerging trends, ensuring products meet both current demand and future tastes. Combining this with AI, the company is redefining what’s possible in beauty, showing how data, science, and technology can converge to drive innovation.

    From decades of research to cutting-edge AI, L’Oréal is not just a cosmetics company—it’s a beauty data powerhouse, using technology to turn ideas into reality faster, smarter, and more sustainably than ever.

  • Intelligence

    There’s an ongoing debate about AI intelligence: some believe it will outsmart humans, while others argue it merely mimics us. I don’t hold a fixed view—I just know AI is incredibly useful, especially tools like ChatGPT, even if we don’t fully understand how they work.

    Because AI sits at the forefront of business research, it’s often compared with human and animal intelligence. One example is the “Animal/AI Olympics,” which tests problem-solving across species and AI agents using maze-like tasks in simple 3D environments. Similar tests are used with animals—and even in human neuropsychological assessments.

    I experienced this myself after a brain injury, when a neurologist tested my memory and problem-solving through mazes and drawing tasks. While basic navigation is easy, more complex challenges, like manipulating objects or understanding cause and effect, require common sense. These are difficult for less-evolved animals and still extremely hard for even advanced AI.

    This is well captured by my mother’s old phrase: “very intelligent, but no sense.”

    Intelligence involving higher-level reasoning is often seen as more advanced, yet closer inspection shows that different intelligences have entirely different profiles of skills. One challenge for AI is convincing us it is human-like.

    A useful metaphor is the octopus. Octopuses (or octopi) are highly intelligent: they use tools, plan escapes, and adapt to new situations. Their intelligence doesn’t resemble ours, yet it is remarkably effective. Unlike mammals, they have a distributed nervous system one central brain and one in each arm allowing semi-independent action.

    Octopus intelligence feels almost alien: efficient, decentralised, and fundamentally unlike human cognition. In this sense, AI may be best understood not as a lesser human mind, but as a genuinely different—almost alien—form of intelligence

    AI is difficult to understand not because it evolved on another planet or in some distant galaxy. In a sense, it is an alien—but one that evolved alongside us. We created it deliberately, designing it in the hope that it might give us a glimpse into deeper forms of understanding and intelligence.

  • Black Swan x SWT

    The SWT sector is inherently exposed to Black Swan dynamics because it sits at the intersection of fast-moving tech, shifting consumer behaviour, and fashion cycles.

    Black Swan events (in wearables) can:

    Create instant category leaders.

    Single unexpected breakthroughs; like a new AR display,

    Battery chemistry.

    AI-native eyewear (that can suddenly redefine the market and push one product to the front).

    Make existing products obsolete very quickly …. “Best-in-class” devices can be dethroned instantly when a competitor releases a surprising features. Radically better optics, double the battery life, or a new use-case that shifts what consumers expect.

    And in my area of specialism, they can also accelerate fashion–tech convergence. When a luxury brand releases a wearable that unexpectedly resonates culturally, it can pull the entire market toward lifestyle-led design. This can show how culture can shift faster than any forecast.

  • The Black Swan Effect

    The Black Swan effect refers to rare, unexpected events that have huge impacts, and only seem obvious in hindsight. It’s like the butterfly effect; small or unpredictable triggers lead to dramatic, far-reaching consequences.

    In short, it explains how humans underestimate the likelihood of extreme situations, but rely heavily on past data.

    Important attributes include unpredictability; nothing in the past clearly points defined the future.

    It concludes to really big consequences; PESTLE (as learned in my MSc: Political, Economic, Social, Technological, Legal and Environmental) or cultural. It’s only afterwards when it becomes obvious and should have been expected.

    Black Swanevents can instantly transform entire industries, markets, technologies, and even society itself.

  • L’Oréal x IBM

    L’oreal = cosmetics.

    Many businesses, obviously , include an R&D department, and for cosmetics, this includes scientists, skincare, makeup, haircare and packaging, all glued together with the development department. This is only in the HQ, though, manufacturing takes what has been from the HQ.

    What makes any company in a predictive industry (fashion) , is having to understand what’ll be the trend, tomorrow. This prediction will instigate development, therefore the presumption must be well backed up.

    Where L’Oréal meets IBM is through their exploration in technology.

    L’Oréal products can be seen, without psychically pulling it on, L’Oréal call it “virtual beauty” L’Oréal creates “beauty experiences”, which is why traditional UX can be explored so viscerally.

    With this R&D collection and experimentation gives a HUGE amount of data.

    With this raw materials will be chosen , what combination are decided and how much.

    Safety, performance, quality, compliance and sustainability… and the rest. All this development would take forever!

    But what if… this process could be done digitally. Like L’Oréal’s earlier stages… “virtual beauty”.

    … where IBM comes in… using a custom AI model can help organised and conjoin those results. Where computers collaborate with the human designers, to enhance their work.

    Ages of results found by experts can be analysed and assimilated using AI to predict what’ll be next.

    In essence, the AI dies all the long, dirty work. It takes time results of what has been designed and experimented by the humans.

    After so much testing and results being gathered, the data is “AI ready”. The predictions can tell what the next steps should be.

    Get ready for the future move.

  • The art of AI

    Like many new investors, few actually know how it really works. For AI, all I know is the acronym is “artificial intelligence”.

    There is a HUGE TREND amongst pretty much everyone I know (maybe everyone you know, too).

    The only get the impression (condensed, too detailed for here) is you give it a prompt, and it will give a perfect reaction based on previous linkages from the internet.

    This could be totally wrong, but basing on that judgement;

    We like what we’re good at. We LOVE for the imperfections.

    Like the odd incorrect note in a song, or the imperfections in the sound of their vices. Even the obviously wrong brushstroke in a painting. You can tell it’s done by a being with fallibilities, with emotions, with a conscious.