미래에는 기술이 인간의 인지, 신체, 지각 능력을 증폭시켜 우리가 세상을 디자인하고, 만들고, 상호작용하는 방식을 변화시키는 증강 시대가 열립니다.

### 증강 시대: 창의성과 혁신의 새로운 시대
* 🔮   앞으로의  20년은 **크리에이터의 작업 방식에 전례 없는 변화**를 가져올 것이며, **인류 역사상 새로운 시대**가 열릴 것입니다.
* 🖥️   수동적 디자인에서 능동적 디자인으로: 주어진 목표와 제약 조건에 따라 독립적으로 새로운 디자인을 만들어내는  AI를 활용한 디자인 도구의 진화는 **크리에이티브 프로세스에 혁신**을 불러일으키고 있습니다.
* 🤖   컴퓨터는 **직관력과 자체 솔루션을 생성하는 능력**을 발전시키면서 문제 해결과 디자인에서 인간과 컴퓨터가 협업할 수 있는 길을 열어가고 있습니다.
* 🌱   로봇 시스템과  AI를 통해 인간은 서로의 능력을 증강시켜 **이전에는 불가능했던 디자인과 솔루션**을 만들어낼 수 있게 되었습니다.
* 🧠   디지털 신경계의 발전은 **우리가 만드는 모든 것을 연결**하여 실시간 피드백을 제공하고 사용자의 요구를 더 잘 충족하는 제품을 만들 수 있게 해줄 것입니다.
* 🌍   증강 시대는 기술이 우리의 역량을 지속적으로 향상시키면서 **다양성, 연결성, 역동성, 복잡성, 적응성, 아름다움**이 더욱 증대된 세상을 가져올 것입니다.

Translator: Leslie Gauthier
Reviewer: Camille Martínez. How many of you are creatives, designers, engineers, entrepreneurs, artists, or maybe you just have a really big imagination? Show of hands? (Cheers) That's most of you. I have some news for us creatives. Over the course of the next 20 years, more will change around the way we do our work than has happened in the last 2,000. In fact, I think we're at the dawn of a new age in human history. Now, there have been four major historical eras defined by the way we work. The Hunter-Gatherer Age lasted several million years. And then the Agricultural Age lasted several thousand years. The Industrial Age lasted a couple of centuries. And now the Information Age has lasted just a few decades. And now today, we're on the cusp of our next great era as a species.

And even our most advanced tools
do nothing without our explicit direction. In fact, to date, and this
is something that frustrates me, we've always been limited by this need to manually
push our wills into our tools -- like, manual,
literally using our hands, even with computers. But I'm more like Scotty in Star Trek. (Laughter) I want to have a conversation
with a computer. I want to say, Computer,
let's design a car, and the computer shows me a car. And I say, No, more fast-looking,
and less German, and bang, the computer shows me an option. (Laughter) That conversation might be
a little ways off, probably less than many of us think, but right now, we're working on it. Tools are making this leap
from being passive to being generative. Generative design tools
use a computer and algorithms to synthesize geometry to come up with new designs
all by themselves.

All it needs are your goals
and your constraints. I'll give you an example. In the case of this aerial drone chassis, all you would need to do
is tell it something like: it has four propellers, you want it to be
as lightweight as possible, and you need it to be
aerodynamically efficient. Then what the computer does
is it explores the entire solution space: every single possibility that solves
and meets your criteria -- millions of them. It takes big computers to do this. But it comes back to us with designs that we, by ourselves,
never could've imagined. And the computer's coming up
with this stuff all by itself -- no one ever drew anything, and it started completely from scratch. And by the way, it's no accident that the drone body looks just like
the pelvis of a flying squirrel. (Laughter) It's because the algorithms
are designed to work the same way evolution does. What's exciting is we're starting
to see this technology

out in the real world. We've been working with Airbus
for a couple of years on this concept plane for the future. It's a ways out still. But just recently we used
a generative-design AI to come up with this. This is a 3D-printed cabin partition
that's been designed by a computer. It's stronger than the original,
yet half the weight, and it will be flying
in the Airbus A320 later this year. So computers can now generate; they can come up with their own solutions
to our well-defined problems. But they're not intuitive. They still have to start from scratch
every single time, and that's because they never learn. Unlike Maggie. (Laughter) Maggie's actually smarter
than our most advanced design tools. What do I mean by that? If her owner picks up that leash, Maggie knows with a fair
degree of certainty it's time to go for a walk. And how did she learn?

Well, every time the owner picked up
the leash, they went for a walk. And Maggie did three things: she had to pay attention, she had to remember what happened, and she had to retain and create
a pattern in her mind. Interestingly, that's exactly what computer scientists
have been trying to get AIs to do for the last 60 or so years. Back in 1952, they built this computer
that could play Tic-Tac-Toe. Big deal. Then 45 years later, in 1997, Deep Blue beats Kasparov at chess. 2011, Watson beats these two
humans at Jeopardy, which is much harder for a computer
to play than chess is. In fact, rather than working
from predefined recipes, Watson had to use reasoning
to overcome his human opponents. And then a couple of weeks ago, DeepMind's AlphaGo beats
the world's best human at Go, which is the most difficult
game that we have.

In fact, in Go, there are more
possible moves than there are atoms in the universe. So, in order to win, what AlphaGo had to do
was develop intuition. And in fact, at some points,
AlphaGo's programmers didn't understand why AlphaGo was doing what it was doing. And things are moving really fast. I mean, consider --
in the space of a human lifetime, computers have gone from a child's game to what's recognized as the pinnacle
of strategic thought. What's basically happening is computers are going
from being like Spock to being a lot more like Kirk. (Laughter) Right? From pure logic to intuition. Would you cross this bridge? Most of you are saying, Oh, hell no! (Laughter) And you arrived at that decision
in a split second. You just sort of knew
that bridge was unsafe. And that's exactly the kind of intuition that our deep-learning systems
are starting to develop right now.

Very soon, you'll literally be able to show something you've made,
you've designed, to a computer, and it will look at it and say, Sorry, homie, that'll never work.
You have to try again. Or you could ask it if people
are going to like your next song, or your next flavor of ice cream. Or, much more importantly, you could work with a computer
to solve a problem that we've never faced before. For instance, climate change. We're not doing a very
good job on our own, we could certainly use
all the help we can get. That's what I'm talking about, technology amplifying
our cognitive abilities so we can imagine and design things
that were simply out of our reach as plain old un-augmented humans. So what about making
all of this crazy new stuff that we're going to invent and design? I think the era of human augmentation
is as much about the physical world

as it is about the virtual,
intellectual realm. How will technology augment us? In the physical world, robotic systems. OK, there's certainly a fear that robots are going to take
jobs away from humans, and that is true in certain sectors. But I'm much more interested in this idea that humans and robots working together
are going to augment each other, and start to inhabit a new space. This is our applied research lab
in San Francisco, where one of our areas of focus
is advanced robotics, specifically, human-robot collaboration. And this is Bishop, one of our robots. As an experiment, we set it up to help a person working in construction
doing repetitive tasks -- tasks like cutting out holes for outlets
or light switches in drywall. (Laughter) So, Bishop's human partner
can tell what to do in plain English and with simple gestures, kind of like talking to a dog, and then Bishop executes
on those instructions with perfect precision.

We're using the human for what the human is good at: awareness, perception, and decision-making. And we're using the robot for what it's good at: precision and repetitiveness. Here's another cool project that Bishop worked on. The goal of this project, which we called the HIVE, was to prototype the experience of humans, computers, and robots all working together to solve a highly complex design problem. The humans acted as labor. They cruised around the construction site, they manipulated the bamboo -- which, by the way, because it's a non-isomorphic material, is super hard for robots to deal with. But then the robots did this fiber winding, which was almost impossible for a human to do. And then we had an AI that was controlling everything. It was telling the humans what to do, telling the robots what to do, and keeping track of thousands of individual components. What's interesting is, building this pavilion was simply not possible

without human, robot, and AI augmenting each other. OK, I'll share one more project. This one's a little bit crazy. We're working with Amsterdam-based artist Joris Laarman and his team at MX3D to generatively design and robotically print the world's first autonomously manufactured bridge. So, Joris and an AI are designing this thing right now, as we speak, in Amsterdam. And when they're done, we're going to hit Go, and robots will start 3D printing in stainless steel, and then they're going to keep printing, without human intervention, until the bridge is finished. So, as computers are going to augment our ability to imagine and design new stuff, robotic systems are going to help us build and make things that we've never been able to make before. But what about our ability to sense and control these things? What about a nervous system for the things that we make?

Our nervous system, the human nervous system, tells us everything that's going on around us. But the nervous system of the things we make is rudimentary at best. For instance, a car doesn't tell the city's public works department that it just hit a pothole at the corner of Broadway and Morrison. A building doesn't tell its designers whether or not the people inside like being there, and the toy manufacturer doesn't know if a toy is actually being played with -- how and where and whether or not it's any fun. Look, I'm sure that the designers imagined this lifestyle for Barbie when they designed her. (Laughter) But what if it turns out that Barbie's actually really lonely? (Laughter) If the designers had known what was really happening in the real world with their designs -- the road, the building, Barbie -- they could've used that knowledge to create an experience that was better for the user.

What's missing is a nervous system connecting us to all of the things
that we design, make, and use. What if all of you had that kind
of information flowing to you from the things you create
in the real world? With all of the stuff we make, we spend a tremendous amount
of money and energy -- in fact, last year,
about two trillion dollars -- convincing people to buy
the things we've made. But if you had this connection
to the things that you design and create after they're out in the real world, after they've been sold
or launched or whatever, we could actually change that, and go from making people want our stuff, to just making stuff that people
want in the first place. The good news is, we're working
on digital nervous systems that connect us to the things we design. We're working on one project with a couple of guys down in Los Angeles
called the Bandito Brothers and their team.

And one of the things these guys do
is build insane cars that do absolutely insane things. These guys are crazy -- (Laughter) in the best way. And what we're doing with them is taking a traditional race-car chassis and giving it a nervous system. So we instrumented it
with dozens of sensors, put a world-class driver behind the wheel, took it out to the desert
and drove the hell out of it for a week. And the car's nervous system
captured everything that was happening to the car. We captured four billion data points; all of the forces
that it was subjected to. And then we did something crazy. We took all of that data, and plugged it into a generative-design AI
we call Dreamcatcher. So what do get when you give
a design tool a nervous system, and you ask it to build you
the ultimate car chassis? You get this. This is something that a human
could never have designed.

Except a human did design this, but it was a human that was augmented
by a generative-design AI, a digital nervous system, and robots that can actually
fabricate something like this. So if this is the future,
the Augmented Age, and we're going to be augmented
cognitively, physically, and perceptually, what will that look like? What is this wonderland going to be like? I think we're going to see a world where we're moving
from things that are fabricated to things that are farmed. Where we're moving from things
that are constructed to that which is grown. We're going to move from being isolated to being connected. And we'll move away from extraction to embrace aggregation. I also think we'll shift
from craving obedience from our things to valuing autonomy. Thanks to our augmented capabilities, our world is going to change dramatically. We're going to have a world
with more variety, more connectedness, more dynamism, more complexity.

more adaptability and, of course, more beauty. The

The incredible inventions of intuitive AI | Maurice Conti

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크리에이티브를 위한 새로운 시대의 개막

인류가 새로운 시대로 접어들면서 일하는 방식은 인류 역사상 가장 큰 변화를 맞이하고 있습니다.

이제 수동적인 도구에서 컴퓨터 알고리즘을 사용하여 스스로 디자인을 만들어내는 제너레이티브 도구로 변화하고 있습니다.

예를 들어, 제너레이티브 디자인 도구는 사용자의 기준에 맞는 수백만 가지의 가능성을 탐색하고 제시하여 인간만으로는 상상할 수 없었던 디자인을 만들어낼 수 있습니다.

에어버스 A320의 3D 프린팅 객실 파티션에서 볼 수 있듯이 이제 컴퓨터는 제너레이티브 디자인 AI를 사용하여 문제에 대한 자체 솔루션을 생성할 수 있습니다.

컴퓨터와 달리 매기와 같은 개는 경험과 반복을 통해 직관을 학습하고 발전시킬 수 있으며, 이는 지난 60년 동안 AI의 목표였습니다.

논리에서 직관으로 빠르게 발전하는 AI의 모습은 딥마인드의 알파고에서 잘 나타나며, 이제 인간이 순식간에 결정을 내리는 데 사용하는 직관력을 개발하기 시작했습니다.

인간의 능력을 증강하는 기술의 역할

기술은 인간의 인지 능력을 향상시켜 기후 변화와 같은 새로운 도전에 대처할 수 있게 해줄 것입니다.

실제 세계에서는 인간과 로봇의 협업이 강조되고 있으며, 로봇은 반복적인 작업을 정밀하게 수행하고 인간은 인식과 의사결정 능력을 발휘하고 있습니다.

HIVE라는 특정 프로젝트는 복잡한 설계 문제를 해결하기 위해 인간, 로봇, AI가 힘을 합쳐 각자의 강점을 살린 작업을 수행하는 모습을 보여주었습니다.

암스테르담의 요리스 라르만과 그의 팀은 AI를 사용하여 생성적으로 설계하고 로봇을 3D 프린팅하여 최초의 자율 제조 다리를 제작하고 있습니다.

이 프로젝트는 AI 설계와 로봇 건설 간의 협업을 강조하여 사람의 개입이 필요 없음을 보여줍니다.

또한 우리가 창조하는 사물에 대한 신경계의 필요성을 강조하며 디지털 신경계가 우리가 디자인하고 만드는 사물과 우리를 연결하는 미래를 상상합니다.

AI 및 증강을 통한 자동차 설계의 혁신

전통적인 경주용 자동차 섀시에 센서를 장착하고 사막에서 주행하여 40억 개의 데이터 포인트를 수집했습니다.

이 데이터는 드림캐쳐라는 제너레이티브 디자인 AI에 사용되어 인간 디자이너가 혼자서는 결코 만들 수 없었던 자동차 섀시를 만들어냈습니다.

증강 시대의 미래는 제조 대신 농업으로의 전환, 더 큰 연결성, 순종보다 자율성에 중점을 두는 등 세상에 극적인 변화를 가져올 것으로 예상됩니다.