Speaker 1: Hey everyone, it's Robert and Joe here. Today we've got
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Speaker 1: a new season of the Smart Talks with IBM podcast series.
Speaker 2: This season on Smart Talks with IBM, Malcolm Gladwell is back,
Speaker 2: and this time he's taking the show on the road.
Speaker 2: Malcolm is stepping outside the studio to explore how IBM
Speaker 2: clients are using artificial intelligence to solve real world challenges
Speaker 2: and transform the way they do business.
Speaker 1: From accelerating scientific breakthroughs to reimagining education. It's a fresh
Speaker 1: look at innovation in action, where big ideas meet cutting
Speaker 1: edge solutions.
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Speaker 2: Malcolm Gladwell himself as he guides you through each story.
Speaker 1: New episodes of Smart Talks with IBM drop every month
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Speaker 3: To understand why the cosmetics supergiant Lorel Group is teaming
Speaker 3: up with IBM, you must first take a closer look
Speaker 3: at its products. Take lipstick, for example, it's one of
Speaker 3: those things that seems straightforward. A waxy cylinder that you
Speaker 3: rub on your lips to turn them a different color. Easy, right,
Speaker 3: Well maybe not, as my colleague Lucy Sullivan found out
Speaker 3: when I sent her an assignment to Lorel's North America
Speaker 3: Research and Innovation Center.
Speaker 4: All right, I'm reporting live from the Loreal visitor's parking lot.
Speaker 4: Malcolm told me that he would be sending me to Paris,
Speaker 4: France for this Looreal excursion, but instead I am in Clark,
Speaker 4: New Jersey. Pass a lot of strip malls on the
Speaker 4: way here. But to be fair to Clark, New Jersey
Speaker 4: and Lorel, this is a beautiful compound. It kind of
Speaker 4: looks like a spa.
Speaker 3: Lucy went into the center and was blown away. The
Speaker 3: facility houses about six hundred scientists and experts across skincare, makeup, fragrance,
Speaker 3: hair care, innovative packaging, and tech. It is one of
Speaker 3: the largest formulation lab spaces in the industry. It's the
Speaker 3: size of six basketball courts. The reason Loreel's facility is
Speaker 3: so big and has so many people is that everything
Speaker 3: Loriel does to bring a product to market happens here,
Speaker 3: from molecule discovery and product development to consumer testing. The
Speaker 3: center even has its own mini factory. My conception of
Speaker 3: lipstick that it's just a waxy stick was plain wrong.
Speaker 3: Lipstick is a high performance product born from years of research,
Speaker 3: consumer insights, and precision science. Lipstick isn't simple. It's incredibly complex,
Speaker 3: and one of the main reasons it's so complex is
Speaker 3: just a nature of fashion trends. The kind of lipstick
Speaker 3: consumers want is constantly changing.
Speaker 5: A lot of our consumer insights with Lorial is like,
Speaker 5: where are consumers going in the future.
Speaker 3: This is Nadine Gomez. She is vice president for Low's
Speaker 3: research and innovation development team.
Speaker 5: Our chemists are working on five six years down the line.
Speaker 5: We predicted that consumers wanted more of a softer look
Speaker 5: on their lips as well.
Speaker 4: So how do you predict something like that.
Speaker 5: We see slow signals from fashion houses and social media
Speaker 5: and things like that. We kind of see that trend
Speaker 5: evolving a little bit, and then we know at five
Speaker 5: six years it's going to become big.
Speaker 3: Lucy talked with her about the origins of one of
Speaker 3: their products, Mabe Lene matt Ink liquid lipstick.
Speaker 5: Our competitors have two steps. The first step is a
Speaker 5: base code. It's super opique. You get the color and
Speaker 5: you get the madity, but it's very very drying your lips.
Speaker 5: You cannot wear that, honestly more than ten minutes. It
Speaker 5: feels like your lips are like aching at one point.
Speaker 5: So we had to develop a top cot and you'll
Speaker 5: see many of our competitors did the same thing. It's
Speaker 5: like a bomb. You put it on top, it's super comfortable.
Speaker 5: But we also noticed that consumers kind of get tired
Speaker 5: of reapplying a bomb, So we're like, what can we
Speaker 5: do to create this two step into one step?
Speaker 3: Well, Loriel had a challenge, how do you make a
Speaker 3: comfortable liquid Matt lipstick that doesn't require consumers to reapply
Speaker 3: a top layer of bomb. Solving this type of problem
Speaker 3: takes a lot of resources and a lot of expertise,
Speaker 3: and crucially, it takes time. Remember Nadine said that working
Speaker 3: on a breakthrough product such as Matt inc can take
Speaker 3: years before it comes out. But can this process be accelerated,
Speaker 3: taken further, be even more sustainable. That's what IBM and
Speaker 3: Lareel are hoping to find out. My name is Malcolm Gladwell.
Speaker 3: You're listening to the latest episode of Smart Talks with IBM,
Speaker 3: where we offer our listeners a glimpse behind the curtain
Speaker 3: of the world of technology. In our last episode, we
Speaker 3: talked about how an AI assistant created with IBM, Watson
Speaker 3: X helps future teachers practice responsive teaching by simulating classroom
Speaker 3: interactions with students. In this episode, we take you on
Speaker 3: an even more or unexpected journey into the world of cosmetics,
Speaker 3: hair care, skincare, fragrance, makeup and how a custom AI
Speaker 3: model could help Loreel's researchers shape the future of what
Speaker 3: we put on our faces every morning. I want to
Speaker 3: say on lipstick a moment longer to help illustrate what
Speaker 3: goes into Loriel's product development, and let's focus on matt
Speaker 3: Inc lipstick. Loreel wanted to create something that was comfortable
Speaker 3: and could be applied in one step.
Speaker 6: So to go from two step to one step, we
Speaker 6: had to look cross functionally and try to figure out
Speaker 6: what can we bring into the product to make it
Speaker 6: more comfortable and luckily we have many different types of
Speaker 6: products at Lorel.
Speaker 3: That's Alex good, a senior chemist who leads the lip
Speaker 3: products team in North America. She says the trick to
Speaker 3: making matt incwork was finding an elastomer, a substance they
Speaker 3: were already using in foundation.
Speaker 6: We have this elastomer that can give you like more
Speaker 6: comfortable and make it feel like there's like something on
Speaker 6: your lips, like a cushion.
Speaker 3: She handed Lucy two jars. The first jar contained the
Speaker 3: former version of the product that was used in super
Speaker 3: State twenty four. By the way, this is exactly why
Speaker 3: I sent Lucy to the lab in my place the samples.
Speaker 6: And I actually have something for you to try here,
Speaker 6: so you can try this is what was the initial product.
Speaker 4: Okay, so this is like it sort of looks like okay,
Speaker 4: it is. It looks like vacline that has like more
Speaker 4: of a color. It's kind of a beige, looks like
Speaker 4: some skin.
Speaker 6: Okay.
Speaker 4: So this was from the two steps this would go
Speaker 4: on after Oh okay, right.
Speaker 7: Islet Okay, So.
Speaker 6: It feels like very wet. As you can see, it's
Speaker 6: kind of it's gonna absorb into your skin and leave
Speaker 6: and then you're gonna feel the dryness of.
Speaker 7: The product once it's long.
Speaker 8: Okay.
Speaker 6: So we're gonna move from the clay product that you
Speaker 6: have on your hand now to the elastimmer.
Speaker 3: Or you try half hour this jar held the elastomer
Speaker 3: that Lareel had spent years developing in the lab.
Speaker 4: This one is it clear, looks like Aqua four, a
Speaker 4: much player and.
Speaker 6: You can see yeah, physical layer that you're putting on
Speaker 6: your aids.
Speaker 4: Yeah, so that's much thicker. It kind of like clumps together. Yeah,
Speaker 4: it was more of a cloudy it's less shimmery though
Speaker 4: that's intended.
Speaker 6: Yes, So this is a like a powder this dispersed
Speaker 6: in dimethicone and it creates like a comfort on your
Speaker 6: lips a fields, like there's something.
Speaker 9: There for a barrier to keep the.
Speaker 6: Film form on. And that's like the key ingredient that
Speaker 6: came from Foundation that we transferred into lipstick to give
Speaker 6: us this innovative product ahead of the market. Yeah, this
Speaker 6: is what gives it comfort. So the difference between super
Speaker 6: State twenty four and matt Inc is really the comfort.
Speaker 6: They both last a long time, but this matt Inc
Speaker 6: you don't have to apply the bomb over and over again,
Speaker 6: so you can apply matting once for the day and you're.
Speaker 8: Good for it.
Speaker 3: Alex Good is under selling it here, once for the
Speaker 3: day and you're good. That's a liquid lipstick revolution. Literally,
Speaker 3: millions of loreal consumers around the world have worn matt ink.
Speaker 3: It's a blockbuster. It's also a marvel of science. The
Speaker 3: world's first liquid lipstick was developed in the nineteen thirties,
Speaker 3: and it was actually just a stain for your lips,
Speaker 3: barely counts as lipstick. Then came another wave of liquid
Speaker 3: lipstick when they were able to make it matt That
Speaker 3: was a two step version. It felt heavy on your lips.
Speaker 3: You had to keep reapplying the top coat. It was inconvenient.
Speaker 3: Lorel tackled that challenge in the lab, with chemists like
Speaker 3: Alex and the Dean leaving the charge their breakthrough matt Inc.
Speaker 3: But creating matt Inc took a long time, trial and error,
Speaker 3: the hard work of science experimentation. As Nadine told Lucy,
Speaker 3: the lipstick team had to put the new product to
Speaker 3: extensive tests.
Speaker 5: We do a very robustability system here. You know, we
Speaker 5: have color odor appearance. We monitor this in extreme conditions.
Speaker 5: We simulate a forty five degrees celsius and that can
Speaker 5: be something like a three year shelf life. I'm saying
Speaker 5: we simulate your real life product, like if you leave
Speaker 5: your lip gloss in the car in Arizona's one hundred
Speaker 5: and twelve degrees worth three days. Is it still going
Speaker 5: to perform? Is it gonna smell? Is it gonna look granted?
Speaker 5: Is it gonna change colors?
Speaker 10: We do all that?
Speaker 3: See what I mean? Lipstick is complex. Most people would
Speaker 3: never consider it a piece of technology, but one lip
Speaker 3: product has millions of data points.
Speaker 5: So much science behind. And you can see here how
Speaker 5: many scientists we have. You know, some of them have PhDs,
Speaker 5: some of them have master's degrees chemistry, biology, psychology.
Speaker 3: Also, when I first heard about this collaboration between LORI
Speaker 3: L and IBM, I was surprised. I thought, these are
Speaker 3: two very different companies. What do they really have in common?
Speaker 3: You guys?
Speaker 4: Yeah.
Speaker 3: To find out, I went to the IBM research Center
Speaker 3: outside New York City, which I have to say is
Speaker 3: one of the coolest buildings I've ever been in. A
Speaker 3: semi circular modernist masterpiece with a long curving wall of windows,
Speaker 3: looks like something out of a Stanley Kubrick movie. I
Speaker 3: was there to talk with two experts from research and
Speaker 3: innovation at LOREL Metheu Cassier and Gabriel Bertoli metthew IS
Speaker 3: VP for Digital and Transformation, Gabrielle is a Chief Digital
Speaker 3: Transformation Officer for Formulation. These are the people whose jobs
Speaker 3: are to oversee big changes within the company. And Methu
Speaker 3: told me to try on some lipstick.
Speaker 7: I'm gonna make you try this one.
Speaker 3: Okay, this is super stay vinin Final Inc.
Speaker 7: Yeah, so that's a glosse.
Speaker 3: Never in my life put on lipsey. I've no idea
Speaker 3: what I'm doing.
Speaker 8: You don't have to put it.
Speaker 7: You can try it virtually.
Speaker 3: Oh this may not be news to people who buy makeup,
Speaker 3: but it was news to me. You can try on
Speaker 3: loreal products virtually. They call it augmented beauty. Oh my goodness.
Speaker 3: That is the strangest thing I've ever said. I look
Speaker 3: quite fetching, that's the way.
Speaker 8: It amazing. And I can just hit you can choose
Speaker 8: your color absolutely.
Speaker 3: So I'm on a little app it's looking at me
Speaker 3: and it's just showing me exactly how I would look
Speaker 3: with different shades of lipstick. So the odd idea of
Speaker 3: going into a store and trying on each one, you
Speaker 3: cannot do that from home, if you're not even at
Speaker 3: the store.
Speaker 7: Yeah, absolutely, that's all purpose. If you want to manage
Speaker 7: a trend that would go for something more like pitch.
Speaker 3: You think I'm a peach person. I don't know that
Speaker 3: looks I have to say that looks kind of natural.
Speaker 3: It just is enhanced. It's given me a boys share
Speaker 3: I would not otherwise have. This is why Loreel says
Speaker 3: it creates beauty products and beauty experiences. Loriel is a
Speaker 3: beauty tech company. Over the last decade, Loriel has seized
Speaker 3: the power of AI and more recently, generative AI technology
Speaker 3: has become a driving force alongside science and creativity. And
Speaker 3: while some of this digital technology is relatively new, Matthew
Speaker 3: helped me see that IBM and Lorel have always had
Speaker 3: a lot in common.
Speaker 7: So the original creator of Loyal, Jentulier, was a chemist
Speaker 7: in nineteen or nine, so one hundred and sixteen years ago,
Speaker 7: and he created this new air color type for the
Speaker 7: market in France, and then little by little, it has
Speaker 7: been always a very scientific company. So if you look
Speaker 7: a little bit at key facts, we invented sun filters
Speaker 7: in the nineteen thirties, there was a very very big
Speaker 7: milestone where we also invented not only product, but a
Speaker 7: reconstructed skin. So if you look at nineteen seventeen nine,
Speaker 7: we've been the created this reconstructed skin that helped us
Speaker 7: to go out of animal testing very fast and by
Speaker 7: the way, before the law even asked it to cosmetic companies.
Speaker 7: And then more recently, because it's a history of innovation,
Speaker 7: we launch on new molecules like one you can find
Speaker 7: in naoche pose Milibi three, which is really helping people
Speaker 7: to find against some you know, spots they could have
Speaker 7: on their skin. It's all about like big mountation, how
Speaker 7: to regulate it.
Speaker 3: Loreel and IBM were both started in the early twentieth century,
Speaker 3: Loreel in nineteen oh nine and IBM in nineteen eleven.
Speaker 3: Both companies have long standing histories of innovation, of using
Speaker 3: trial and error to improve everything they do. The two
Speaker 3: companies have been doing that in parallel for more than
Speaker 3: a century until recently. When does that start when doll
Speaker 3: Lorel and IBM start working together.
Speaker 8: So we started in twenty twenty three at the end
Speaker 8: of the year.
Speaker 11: But you know, really the discussion is really recent, absolutely absolutely,
Speaker 11: it's really recent in reality. You know, I would say
Speaker 11: the first really interaction happened at the beginning of twenty
Speaker 11: twenty four.
Speaker 3: This is Gabriel Bertoli, who I spoke to alongside Matthew.
Speaker 11: What really played a key role here is we wanted
Speaker 11: to bring from a logic perspective to R and D together,
Speaker 11: which normally, you know companies like us, you just go
Speaker 11: to a provider. You know, it's a customer and the
Speaker 11: supplier and new work they delivered to you.
Speaker 8: Here the concept was totally different.
Speaker 3: Mid two said that the collaboration began with simple conversations.
Speaker 7: So if you look at the way IBM entered into
Speaker 7: Loreal Labs, it's started by interviewing people what would help
Speaker 7: you to do your job?
Speaker 8: What is your business need?
Speaker 7: So it was, by the way, two months ago, a
Speaker 7: long series of interviews and from all the people around
Speaker 7: the world we have in research in Brazil, in India,
Speaker 7: in China, Japan, US, France of course, So we really
Speaker 7: want to make sure that at the end of the day,
Speaker 7: this new model, this new tool that we will give
Speaker 7: to people is really people centrick in the way that
Speaker 7: it selves their daily need.
Speaker 3: More the point, Lourel has leveraged technology for decades and
Speaker 3: accumulated amounted of scientific knowledge, everything from consumer aspirations and
Speaker 3: market trends to the results of all the experiments conducted
Speaker 3: during product development. To which formulations melt in a hot car.
Speaker 3: It's hard to get your head around. Loreal isn't just
Speaker 3: a cosmetics company. It's a beauty data powerhouse.
Speaker 11: If we have sixteen thousand terabat of data coming from
Speaker 11: consumer insights, coming from market research coming from sales, well
Speaker 11: with the new technology, maybe by aligning those two and
Speaker 11: using best in class technology you can solve that problem.
Speaker 3: So you say you have sixteen terabytes of data, put
Speaker 3: that in perspective. How much data is that?
Speaker 8: Give me?
Speaker 11: This is one hundred year of Looreal data based on
Speaker 11: the last forty years of data in the systems. So
Speaker 11: this is really I mean, we're talking about one hundred
Speaker 11: year of data that only Lorial have.
Speaker 8: Take the example of the ellipsis.
Speaker 11: I mean, you know, if ellipsex can be between twenty
Speaker 11: and thirty arrow material, each raw material will have I
Speaker 11: would say ten or fifteen way of doing things.
Speaker 3: Gabrielle is talking about how things used to be done.
Speaker 3: Researchers at Lorel needed roughly twenty five ingredients for a
Speaker 3: new lipstick formulation, but they have to choose from a
Speaker 3: pool of hundreds, if not thousands, of raw materials, and
Speaker 3: even after they settle on the ones they want. They
Speaker 3: have to figure out how much of each ingredient they
Speaker 3: need and in what form, what molecular weight, what combination.
Speaker 3: It's not just a math problem. It's a problem that
Speaker 3: requires balancing multiple perspectives safety, performance, quality, compliance standards, sustainability
Speaker 3: and more. It can take years. But what if you
Speaker 3: could simulate hundreds of cars parked in a sweltering heat.
Speaker 3: What if you could do all those files and errors
Speaker 3: virtually over and over and over again. What if instead
Speaker 3: of mixing materials together by hand, you could ask AI
Speaker 3: to predict what combinations might work best and then try
Speaker 3: those out first.
Speaker 8: This is ten on the power of twenty five.
Speaker 11: This is one hundred billion of years for a human
Speaker 11: to do a change in the formula or the possibility
Speaker 11: they have. You can only do this by using technology,
Speaker 11: power of technology and data that you have.
Speaker 3: This, Matthew says, is where IBM can come in to
Speaker 3: help take things further. Using artificial intelligence. IBM can help
Speaker 3: Lorio create a custom AI model that helps to crunch
Speaker 3: those numbers, to be a companion to the researchers, to
Speaker 3: give them superpowers.
Speaker 7: We don't want to replace the intuition of The sentis
Speaker 7: we just want to make sure that this intuition is
Speaker 7: really augmented by some inclination poor that, as Gabrielle said,
Speaker 7: then does those ten at the poor of twenty five
Speaker 7: solution and seem probably try this one, this one, this one,
Speaker 7: it looks like a better solution and Thentimately that's really
Speaker 7: the decision of the chemist to make it happen.
Speaker 3: Well. To make a predictive AI model that can give
Speaker 3: Lorel researchers those superpowers, you'd need that mountain of data,
Speaker 3: years worth of laboratory testing and all Loreal's data digitized
Speaker 3: and AI ready. You'd need to train artificial intelligence on
Speaker 3: everything the company has already done in order for it
Speaker 3: to predict what it could do.
Speaker 10: Loriial has one hundred years of worse of data, fifty
Speaker 10: years of digitized EGGDA.
Speaker 3: This is Mariam Ashuri, Senior director of Product Management for
Speaker 3: IBM Watson X. Loreal has the data and part of
Speaker 3: IBM's job is to help put that data to work,
Speaker 3: which involves ensuring data quality. Mariam talked about the concept
Speaker 3: of a ready data.
Speaker 10: The sole purpose of this data engineering pipeline is to
Speaker 10: clean the data, and we call them AI ready data
Speaker 10: makes them ready to be consumed by AI, so basically
Speaker 10: looking into biases in the data to fix the distribution,
Speaker 10: looking into guard brains that you're putting into place in
Speaker 10: terms of removing personal information.
Speaker 3: Mariam that explained that a custom model like the one
Speaker 3: IBM is creating with Lorel can be more efficient and
Speaker 3: targeted than the larger general purpose AI models.
Speaker 10: You've heard about large language models. The reason that they
Speaker 10: call them large language model is they are exposed into
Speaker 10: really large amount of data. So the larger the model,
Speaker 10: the more capable the models are, but also the larger
Speaker 10: computed requires that translatestand increase carbon footprint and energy consumption
Speaker 10: that translates, stand increase latency that's your response time, that translates,
Speaker 10: and increase costs. So we started seeing that enterprises started
Speaker 10: grabbing a much smaller model customize it on their proprietary
Speaker 10: data that's the data, their DOMAINO specific data, or the
Speaker 10: data about their users to create something differentiated that is
Speaker 10: applicable to a real world use case but also delivers
Speaker 10: the performance that they needed for a fraction of the costs.
Speaker 10: And that's why there's been a lot of push around
Speaker 10: using custom models versus very large general purpose models.
Speaker 3: So how is a custom model created? Miriam says, you
Speaker 3: start with the base model. Imagine you're buying a car.
Speaker 3: You could get a minivan, or a sedan or a
Speaker 3: sports car, and then you get to customize it. You
Speaker 3: could add a sunroof, leather seats, or a rearview camera.
Speaker 3: Turns out you could do the same thing with your
Speaker 3: AI model. You pick a base and then you customize it.
Speaker 3: You tune it on the data unique to your organization.
Speaker 10: We do believe that one model doesn't fit all use cases.
Speaker 10: You want to truly have access to any model anywhere,
Speaker 10: and by any model anywhere. I really mean any model anywhere,
Speaker 10: open source, proprietary, low call out your machine. Wherever the
Speaker 10: model is. You want to host it yourself, because then
Speaker 10: you would be able to take advantage of the best
Speaker 10: of the technology at any point and pick the right
Speaker 10: model for the target use case.
Speaker 3: So a custom model tuned on Lorel's data would be
Speaker 3: more targeted and efficient than a general purpose model. It
Speaker 3: would understand the researchers world and provide transparency into its workings.
Speaker 3: That's part of the magic. And what could a custom
Speaker 3: AI foundation model do for a company like Lorel.
Speaker 12: Accord with that moder is contain the complexity of the formulation.
Speaker 3: That's game La Moline, an IBM distinguished engineer and one
Speaker 3: of the people working on the AI model.
Speaker 12: And to hype as the formulator to go not only faster,
Speaker 12: but also I would say, be able to include more
Speaker 12: complexity or so in their formulation, more personalization, more certain ability,
Speaker 12: better selected ingredient. So it's really a tool to help
Speaker 12: them and to also help them to unniche the creativity.
Speaker 3: THEAOMI saying that with its custom AI model, Lorel could
Speaker 3: improve every step of its product development pipeline, make the
Speaker 3: process faster and more sustainable. But he's also saying that
Speaker 3: the model could help Lorel create something that's never been
Speaker 3: done before. What could that product be? So I'm mourning
Speaker 3: you with that. All my questions are going to be
Speaker 3: really dumb.
Speaker 9: Okay, now, please by all means.
Speaker 3: To find out what people at Lorel are dreaming of.
Speaker 3: I spoke with Trisha Iyagari, global general manager at Loriel's
Speaker 3: Mabeline brand, and they asked her about her own dreams
Speaker 3: and how technology and science could help bring those dreams
Speaker 3: into the world. Do you have a secret wish list
Speaker 3: of things you think that this partnership could produce, Like,
Speaker 3: is there a product out there that's been technically too
Speaker 3: difficult that you think could be a worthy target?
Speaker 9: There is one that I think could be really amazing.
Speaker 3: What's that?
Speaker 8: So?
Speaker 9: Shine products in general are harder to create, and we're
Speaker 9: unable to create a shiny, long wearing eyeshadow. So basically
Speaker 9: like a shadow that could stay on your eyelids, that
Speaker 9: won't settle into creases, that won't move all over your face,
Speaker 9: that has a glossy effect. It's like the holy Grail.
Speaker 3: That's the holy grail. H Yeah, you may have seen
Speaker 3: that look in fashion shows, but that look isn't real,
Speaker 3: not for people like me and Lucy.
Speaker 9: Anyway, if you're walking down a runway, you see a
Speaker 9: lot of makeup artists doing techniques where they put some
Speaker 9: shadow on, they layer vasaline over it on, like slather
Speaker 9: vassaline on somebody's eyes to create this very like glossy look.
Speaker 9: But you know, within five minutes after they walk down
Speaker 9: the runway, I'm sure it's all over their face or
Speaker 9: being washed off. So the look is kind of more
Speaker 9: of like a fashion look that we've been unable to create.
Speaker 9: And real, real consumers can't wear it because it would
Speaker 9: get it everywhere.
Speaker 3: Tricia had another thing on her wish list too.
Speaker 9: The other that we would really like is semi prominence makeup.
Speaker 9: So we've talked a lot about really really comfortable thin
Speaker 9: film makeup that you could wear all over your face
Speaker 9: and that you can sleep in, and that it will
Speaker 9: last a couple of days basically, so whether it be
Speaker 9: on your face, on your lashes, on your brows. So
Speaker 9: anything that's like more of a semi permanent meaning lasting
Speaker 9: for three days or more, would be amazing.
Speaker 2: Yeah.
Speaker 3: Yeah, And you say those two things have been the
Speaker 3: whole How long have they been on the wish list
Speaker 3: of Loreel?
Speaker 2: Oh?
Speaker 9: My gosh. I have been trying to develop this shiny
Speaker 9: eyeshadow since I started. What year did I start, Like
Speaker 9: twenty ten? And I'm sure many people had asked before me,
Speaker 9: and we tried so many iterations of it. Nobody's been
Speaker 9: able to achieve it.
Speaker 3: It's clear that Loreel's experts Electricia have a lot of ideas.
Speaker 3: I once said what I called a magic wand project,
Speaker 3: where I called up scientists and technologists in as many
Speaker 3: different fields as possible and asked them what they could
Speaker 3: create if they could just wave a magic wand and
Speaker 3: make it real, and everyone had something they'd want to
Speaker 3: create everyone. That's not the issue. The issue is that
Speaker 3: there are a million different impediments to make the ideas
Speaker 3: on the wish list reel. Lack of resources, lack of time,
Speaker 3: some crucial bit of know how is lacking. There's a
Speaker 3: gap between what we want and what we can actually have.
Speaker 3: And one of the simplest ways to think of the
Speaker 3: promise of AI is that it can narrow that gap,
Speaker 3: not close it, of course, but do enough that people
Speaker 3: with dreams realize there are more things within their grasp
Speaker 3: than they could ever have imagined. Smart Talks with IBM
Speaker 3: is produced by Matt Romano, Amy Gaines, McQuaid, Lucy Sullivan,
Speaker 3: and Jake Harper. Were edited by Lacy Roberts, Engineering by
Speaker 3: Nina Bird Lawrence, mastering by Sarah Bruguerer, music by Gramoscope
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