AU Class
AU Class
class - AU

AU London Opening Keynote 2019

Share this class
Search for keywords in videos, presentation slides and handouts:

Description

Join Autodesk’s VP of Cloud Platform Sam Ramji, MACE’s Director of Innovation Matt Gough, and Autodesk’s Director of Robotics Dr. Erin Bradner as they explore the biggest design opportunity we have ever seen—the opportunity that is created as the world’s inevitable demand for more clashes with its limited resources. The opportunity of better.

Key Learnings

Speakers

  • Matt Gough
    As Director of Innovation for Mace, Matt is responsible for steering the company in its ambition to be the catalyst for the next evolution of the construction industry. Focused on the disruption of Mace's traditional business model across markets, Matt is leading the company's digital transformation, and how Mace both creates and operates the built environment it is responsible for. He drives the organisation's innovation strategy and the identification and implementation of step-change improvements, helping to embed a culture of innovation and a firm focus on productivity. Matt supported the top line growth of Mace's construction business from ᆪ600m to ᆪ2bn in 2017, and he played an important role in some of the business' biggest wins during that time. His career started in digital, having studied computing as part of his degree, and he is now aligning Mace's interests with the innovation and technology being driven by the digital sector, as part of the transition to Industry 4.0.
  • Erin Bradner
    Erin Bradner, Ph.D., is a Director and Research Scientist at Autodesk in the office of the CTO. Erin helped found the Generative Design practice at Autodesk and now manages AutodeskÕs Robotics Lab in San Francisco. Erin has led strategic research partnerships with institutes such as the U.S. National Laboratory in Livermore and NASA JPL to advance manufacturing automation. During her tenure at Autodesk Erin has led hundreds of research projects to identify the sweet spot where technology feasibility, viability and desirability meet. Erin has authored research in Human Computer Interaction with collaborators at IBM, Boeing and AT&T. She is a co-author on patents in advanced design, and holds a PhD in Information & Computer Science.
Video Player is loading.
Current Time 0:00
Duration 1:19:42
Loaded: 0.21%
Stream Type LIVE
Remaining Time 1:19:42
 
1x
  • Chapters
  • descriptions off, selected
  • en (Main), selected
Transcript

[MUSIC PLAYING]

ANNOUNCER: Ladies and gentlemen, please welcome to the stage Ian Mitchell.

[MUSIC PLAYING]

IAN MITCHELL: Hey, thank you. Good morning. Good morning, London. Welcome to AU, London. Now this is going to be an entertaining five minutes because we're a little late. I apologize for that. So I'm going to fast track. I'm going to go off script and go as quickly as possible to give you some time back. So if nothing else, this will be kind of highly amusing.

OK. So let me try and remember everything I want to say. First of all, we have so much for you to look forward to. We have mainstage today and tomorrow from key Autodesk execs and customers. We have the breakout sessions, the technical labs, certification classes, exhibitor stand, the Autodesk Future of Making showcase-- so much to inspire you and provoke your thinking, have you think differently about what's possible in the design and make space.

All right. Few points of order very quickly. If you please, wear your badge at all times. You'll need to do that. Bring your photo IDs tomorrow. There on no fire drills planned. If the fire alarm sounds, please evacuate as quickly as possible.

Download the AU app if you haven't already. We need your feedback on the sessions. It helps kind of shape future events. Get involved in the conversation, right? So here's how to get involved using the app as well.

Any questions, ask the events team. Want to do that. I actually forgot to do this yesterday in rehearsal I want to thank the sponsors. So just please, a round of applause for the sponsors have helped bring the event to you.

[APPLAUSE]

It is kind of the main reason I'm here, and I can't believe I forgot to do that. OK. We're going to go quick. Right.

So university, it's hard to get into, right? So if you've seen this before, you've been here before, the now traditional customary mass audience intelligence test, you will need to participate. It's like a mass entrance exam.

How this will work, it's multiple choice. You've got three potential answers. So you've got at least a one in three chance of being right, right? And as long as most of you get it right, then you're all allowed to stay. OK. So that's basically the setup.

OK. We're going to go quick. So I am a game show host. All right. You're on a game show with me. You've got to the final, so no pressure. You're already doing well, right? You got the final. You're trying to win a sports car, all right?

I show you three doors. You come up on stage. I show you three doors. Behind one of the doors is a wonderful sports car. You're trying to win this, right? Behind the other two doors on mountain goats, all right?

So let's reasonably assume you want to win the car and not a mountain goat. I think that's a safe assumption. OK. So I invite you to choose a door. So let's say, for the sake of argument, you choose door number one. All right?

Here's the twist. Before I open the door to show you whether you've won, then I tell you that I'm going to open another door. So I go to door number three, and I open it. And I show you one of the goats. Interesting, right?

So now here's the intelligence test. Here's the question. It's a three point question. How do you improve your odds of winning the car? So do you want to stick with your original choice-- no show of hands yet, we'll get to that-- stick with your original choice? Are you better off swapping to the other door, i.e. door number two? Or does it not make a difference?

OK. So here's the setup. I want you to commit to an answer in your head, right? Forget what everybody else says. You might be the only person to vote for one of those options. Right.

So quick show of hands, and I'll get out of your way. OK. Who thinks they're better off sticking with their original choice? All right. a fair few. Who is absolutely convinced that you're better off sticking with your original choice? A fair few. All right.

Who thinks it does not make a statistical or probability difference? Who thinks it didn't matter whether you switch [INAUDIBLE]. All right. A fair few of them. OK. And who thinks it does matter and you're better off switching to door two? Who's going to switch the door two? A fair few of hands. They're so wrong. OK.

Who's absolutely convinced that switching to door two improve your odds of winning? All right. So there is a right answer. It does make a difference. So forget the events team asking those questions. If you have any questions, talk to the people who had their hands up last. It's statistically better off to switch doors. You want to switch to door number two. Your odds of success rise from one in three to one in two.

Now I know you are looking at me like I'm kind of crazy. It's actually true. It caused a lot of discussion in mathematical statistical communities. Your probability goes from one to three to one and two. You're better off switching.

OK. It's called the Monty Hall Problem if you're interested. Don't argue with me. But I actually don't care at this point. Go and Google Monty Hall, He's a game show host from the Americas in the '70s and '80s, used to run this thing, caused a lot of discussion.

All right. So I have just enough time to say on behalf of Autodesk, of our sponsors, and everyone involved in bring in AU London to you this year, we hope you have a truly stimulating and rewarding couple of days. Thanks for your time. Have a great couple of days.

[APPLAUSE]

[MUSIC PLAYING]

ANNOUNCER: Ladies and gentlemen, please welcome to the stage Sam Ramji.

[MUSIC PLAYING]

SAM RAMJI: Good morning. Welcome to Autodesk University. It is a privilege to host you here. So what does the future look like? An economist might say that automation is going to take half our jobs. A journalist might point you to a bleak headline about a grim future. A technologist, like me, might point out that, you know, dismal headlines sell more advertising, and only technology can save us. So the truth probably lies somewhere between.

I've spent my entire career in software working on middleware, interoperability, and cloud computing at companies like Microsoft, Apogee, and Google. Mostly, I've worked on software that powers software, bits that to talk to bits. What inspires me about this community is that you use software to make things, bits that move atoms. That's why I chose to join Autodesk and all of you and to help build Forge, a platform that helps you move bits that move atoms.

So I see how your work has a tangible impact on the world. I know that althought technology can be a positive force, there are forces pulling in the other direction. So we worry that a growing population is inevitable, that a world with more automation to deliver more things is inevitable. We fear there'll be less jobs and less resources available on the planet. So as much as we accept the inevitability of more, we still struggle to address the inevitability of less.

What do we know about the future with any certainty? Well, we know there are going to be more people. The population is growing fast, and the middle class is growing quickly, too. Last year, we reached a tipping point.

The Brookings Institute reported last September that for the first time since agriculture-based civilization began 10,000 years ago, the majority of humankind is no longer poor nor vulnerable for from falling into poverty. While there are many definitions of the middle class, many experts agree that over half the world's population is now in the middle class. That is enormously good news.

We also know that with more prosperity comes more demand, more demand for motorways and mobile phones, education and energy, housing and hospitals. So more is inevitable. How can we make all we need and do this with less negative impact, less negative impact on the planet, less negative impact on the people?

So in order to solve this fundamental capacity problem, we have to fundamentally rethink the way we make things, balancing the inevitable need to do more with the reality of doing it with less. That's a massive design challenge.

So addressing a challenge of this enormity and complexity is also the biggest design opportunity we've ever had as a society. Our technology helps you with design challenges every day, automating how things are designed in the digital world and made in the physical world, which is why we believe that along with the inevitability of more and the reality of less is the opportunity of better, the opportunity for a more balanced, more sustainable, and more equitable world. Better for the growing middle class, yes, but also better for those still in poverty.

So design challenges don't get much bigger than the one that faces millions of displaced people around the world every year. Imagine if you had to build a city for 600,000 people in just six months. That was the size of the challenge that Phoebe Goodwin faced.

Phoebe is the site architect for UNHCR, the United Nations High Commission for Refugees. And two years ago, her job was to rebuild this community-- Cox's Bazar in Bangladesh.

Cox's Bazar grew quickly as Rohingya refugees fled persecution in Myanmar. In 2017, they reached this refugee camp and many like it. In the last four months of 2017, Cox's Bazar grew seven-fold into a community with 600,000 people.

Now to put that in perspective, that's about the size of Bristol or Dresden or Léon. So the growing number of displaced people put, as you can well imagine, an accelerating burden on the site's infrastructure. So that's why UNHCR and Phoebe got involved.

Now by the time she arrived, the community had already grown substantially in this rugged terrain. You'll note that the real world is made out of three dimensions, which has an impact in monsoon season. So spontaneous settlements were causing problems with existing services already.

Sanitation, safety-- the refugees need wood in order to cook. They burn the wood for fuel, for safety, for comfort, for heat. Deforestation of the surrounding area made it vulnerable to mudslides, especially in the monsoon season, which was only six months away.

Phoebe needed to plan how to build a more resilient community quickly. So she began to plan the changes the site needed. Where should shelters be moved? Latrines, roads, bridges, where do those need to be placed? Where are the paths located in order to keep people safe?

Planning efforts on site often begin on paper. But Phoebe knew that she needed faster, better insights. After all, a flat piece of paper is not a great place to model a complex three-dimensional topology. It's a challenging, mountainous location, as you can see.

So she turned to software that we donated into the available terrain data. And then she turned to Microdesk, an Autodesk partner. Microdesk trained the UNHCR team how to import the 3D data and use it in Civil 3D. They showed how it could save time and deliver better insights.

So Phoebe could now simulate the monsoon season's impact to discover where flooding and landslides could be expected. She automatically generated flood plain and floodway maps, which were enough to persuade the local governments that they needed heavy machinery to build substantial earthworks.

Phoebe used bits to move atoms. Her digital work had a tangible, physical impact. The UNHCR team was able to remodel critically at-risk areas and move the shelters-- over 100,000 of them-- to higher ground, safer ground.

Of course, the inevitable monsoons came. And so did more people. But there was less negative impact on the site and its occupants. Phoebe was able to build a city for 600,000 people in a matter of months instead of years, a city that provides safe refuge, sanitation, basic infrastructure, and a better quality of life

Phoebe was able to seize the opportunity to make a better plan for the monsoon season. Because she used simulation, she discovered better insights, better shelter locations, and a more resilient community, a better community. So if simulation can help us build a more resilient community for 600,000 people, what can it do for the rest of us, for those of us who work in everyday companies doing everyday jobs and making down-to-earth decisions?

It doesn't get much more down-to-earth than cement. Cement is the key ingredient in concrete. Concrete is used as, you know, everywhere, in buildings and bridges, drains and dams.

Claudius Peters is a German company that makes the heavy equipment to build cement. They've been making cement grinding mills, conveyors, and coolers for over a century. While the company dates back to the industrial age, they are moving quickly into the future.

So they're exploring how can they evolve their industrial machinery? How, by making it more efficient, can they save their customers money? How can they reduce the negative impact of cement production? Because as harmless as concrete seems, it's actually a big emitter of greenhouse gas.

Think about this is concrete we're a country-- if concrete were a country, only China and the United States would emit more CO2. In fact, cement production accounts for 8% of global greenhouse gas emissions.

Here's the opportunity for better. 50% of this negative impact happens during the production process. Any improvements to its production will have a meaningful impact.

So Claudius Peters started by looking at how it could evolve their clinker coolers. These things move 13,000 tons of clinker a day. Clinker, as I've learned, is what you get when you grind limestone and clay and heat it to 1,500 degrees Celsius. That's a lot of hot rock.

Now these pans hold the clinker as it comes out of the furnace and deliver it to the next stage in production. They have to cool that rock from 1,500 degrees-- incredible temperature extreme. And think about the specific heat capacity of rock-- that's a lot of energy. Bring that back down to room temperature over and over and over again. It's hard to be a pan.

Now 60 or more pans are bolted together on a series of conveyor lands that move it through the core. So when you think about one of these factories, that's a lot of pans.

So Claudius Peters engineers had redesigned the pan to remove as much excess material as possible. They were pretty confident, being great engineers, that it was optimized and their design was as efficient as humanly imaginable. They'd use inventor's simulation capabilities to validate that the design would perform as expected. It's one thing to be light. It's another thing to really work.

So here's where things get exciting. Their chief digital officer, Thomas Nagel, wondered if generative design could help them further optimize the pan. Could generative design make the ultimate pan? I kind of feel like the pan is the hero of this story.

Using the engineering team's best design as the baseline, Thomas set up a lab to explore the opportunity. So after four hours, the team had its first results. Thomas called the alien part because it looked so different from their original design.

In place of the engineers angular design was a shape that flowed in unexpected ways. If the way that it looked was unexpected, so was the impact of this process. This part was almost 40% lighter. So the engineers were suspicious if it would perform because, hey, we're engineers. We have to be skeptical.

They returned to Inventor and ran simulations to test the design's performance. And they were astonished. Not only was the pan lighter, it outperformed their prior design. So their work redesigning the pan digitally had an impact on the physical part. They'd use bits to move atoms.

The solution, however, produced a different challenge. Generative design had produced an organic structure that could only be made using industrial additive manufacturing. So think of this as 3D printing in metal. It's expensive. There's a lot of parts. If you want to optimize the cost, that's not the way.

So the engineering team had to figure out a different manufacturing strategy. Within a week, the team had managed to reverse engineer the parts so the pan could be made using more traditional techniques. Going backwards and forwards in Inventor, adapting the design, and simulating its performance, they discovered a solution that could be welded together from laser cut steel plates.

This new pan would be 25% lighter, faster to make, and less expensive-- about 100 euros cheaper per pan. Because the new design is substantially lighter, they also save on shipping costs.

So think about the laser cut steel welding. They used to use casting. Their old pans were cast in Turkey or India where coal is a dominant fuel source. So because a new pan can be made in more places around the world that are less reliant on coal, you also have lighter parts being manufactured locally, reducing the carbon footprint.

So evolving the performance of this pan is one small portion of the investment the Claudius Peters is making in improving the efficiency of their coolers. They manufacture coolers that are more thermally efficient, saving the equivalent of a million euros per year compared to competitive offerings.

Now think about this less fuel means less greenhouse gas emissions. So the Claudius Peters clinker cooler now offers the equivalent of removing over 12,000 vehicles from the road for a single production line.

So this thing might be just one small piece of the puzzle. But by exploring how it can be designed better, Thomas and his team at Claudius Peters found an opportunity to make it better.

The pan can be made more locally, more easily. It uses less material with less negative impact on the planet. So simulation software helped Claudius Peters gain insights into the performance of the new coolers. But it was generative design that opened up the opportunity for them to make better things in better ways.

So as we saw, simulation's a powerful tool that can produce powerful insights. When you run the simulation, you discover insights into a design's performance. The problem, as Claudius Peters will tell you, is that it's extremely compute intensive. So in fact, every time that you double the resolution of a simulation to increase its accuracy the computing requirements increase by a factor of eight, that's our old friend the square cube law.

So the time required for one computer to simulate one design could actually generate you 100 options on a 100 cloud compute nodes. There's so much computing power in the cloud that you can even flip design and simulation around, not just simulating your existing design, not just simulating to validate a new design, but actually simulating to discover the design.

With generative design, you just need to describe the problem-- the constraints, the goals, the forces at play-- and then our technology helps you discover what's possible. It uses cloud computing to analyze the entire solution space, discovering designs you would never imagine so you can select the ones that you really want.

So for example, what's the optimal design for a space vehicle that might land on one of Jupiter's moons? This is a concept designed for a lunar lander. We revealed this at Autodesk University Las Vegas last November. We brought it here so you can see it. Seriously, it's really cool. Go see it yourself. It's just outside the door.

It's the work of NASA's Jet Propulsion Laboratory, or JPL, who use generative design technology as a new way of designing things. So JPL designers are also really interested in exploring new ways of making things. They have some harsh conditions to deal with-- outer space, high temperatures, low temperatures, the stress of landing.

So like Claudius Peters, JPL can't use additive manufacturing-- not because it's too expensive because, hey, this is a government space program, but because it's too early. It hasn't been qualified for space travel. So the idea of 3D printing this lander is still science fiction. However, JPL can 3D print molds and use the molds for casting. And that's exactly what they did for the lander's chassis.

Now the lander's legs on the other hand are optimized to be milled. It's a better approach for managing the stress of landing. So by adding algorithms in diffusion, they would allow us to constrain the design output for specific methods of manufacturing, such as three-axis and five-axis mill

Autodesk is giving JPL the opportunity to design all those [INAUDIBLE] parts better and to manufacture them in ways appropriate for their needs-- many new ways to design, many new ways to manufacture. Generative design is now practical for JPL, and it's practical for Claudius Peters. And we are committed to making it practical for each of you.

Our last story brings us back from outer space and down to Earth with a bump. So as we make more things for more people on Earth, we risk making things worse, not better-- worse for the planet, worse for the people.

There are 18 million people working in construction in the European Union. They contribute almost 10% of the EU'S GDP. So it's an important industry. It's also a risky one. Over 800 construction workers die each year on the construction site in the EU. In the United States, that number is about 1,000.

At the same time, we build over 11,000 buildings per day worldwide. By 2050 and 10 billion people on the planet, we're going to need to produce over 14,700 buildings per day to serve this larger population to have enough homes, enough hospitals, enough schools to house, heal, and educate our people.

So construction projects generate a constant stream of data that could be real-time analyzed. You could make real-time decisions. So as we construct more buildings, the opportunity for improvement is to analyze this data and improve the quality of the product and reduce the number of accidental deaths. So how can we increase the rate and quality of construction for 10 billion people while also making construction safer?

Traditionally, we think of this as the job of the site manager. And that is a hard job. This job can be very reactive because it lives in the world of atoms. Atoms move very fast. And the risk is high. So how can we understand all that complexity at the speed we need?

The answer resides within the enormous stores of compute power in our grasp. The site managers at Royal BAM Group are applying vast computational capacity to analyze all of this data. By analyzing their history, they can see the future. They can look at that data and predict risks.

So just a few years ago, Royal BAM collected their data, like most companies, on paper. Today, Royal BAM's data collection is 95% digital.

Now getting there wasn't easy. They started the process in 2017, digitizing their existing process. They learned a number of interesting things. Most importantly, they were storing a lot of historical data, but 90% of it was never used for analysis. So the team understood by looking at the past, they might predict the future.

So with the permission of Royal BAM and many of their peers, Autodesk collected millions of data points. This real world data presented an opportunity for construction companies. We built construction IQ using over a decade of construction data to better predict and manage risk.

With these tools Royal BAM applies machine learning and predictive analytics. They spot patterns, and they predict high risk issues that could impact the safety of their workers. In addition, Royal BAM incorporated data from other sources combining with BIM 360 solution. I think this is particularly cool.

The team pulls in photos from cameras all around the job site. And they use Autodesk Partner and Developer Smartvid.io to integrate this and analyze the imagery for risk. The integration happens through the Forge API, and they've combine that analytics with their BIM 360 solution.

So Smartvid.io connects this imagery to other data and other data streams to help Royal BAM understand the risk to their workforce. So not only does Royal BAM identify the financial inequality risk associated with certain subcontractors, they can now also identify the safety risk associated with missing scaffold guardrails. The team gets much more value from their data in new ways like this.

So today, Royal BAM is analyzing data to predict risk, delays, and cost overruns digitally using BIM 360. The job site managers are more productive. They close out safety and quality issues 20% faster. They have better insights to ensure less rework, making their sites safer, more predictable, more productive, and more profitable. So these sites are less risky for their workers and for their business.

The computational power that we have today offers the capacity to converge the way that we design and make things. Today, the way that something could be made is starting to drive how it should be designed. So we want to give you a clear line of sight from design to make, from part to production.

You want to better understand the different options that you have. How could your designs be made? You want to understand the different material choices. What is the embodied energy, right? What are the costs in each design option?

In addition to the capacity to converge the way that you design and make things, imagine if we could give you the capacity to connect them as well. If you use this computational capacity to connect your design challenges and your production challenges, think of the insights you could discover.

If you could see supply and demand for your raw materials, for your labor, imagine how much more balanced you could make the world-- part counts, recycled materials, staffing. You could bring your industry towards peak efficiency, a circular economy.

Together, if we help construction become more predictable like manufacturing and manufacturing more flexible like construction, we can help you become more efficient and further reduce waste. By converging and connecting what you design and make, this computational capacity makes it possible to imagine and better see what you're really trying to accomplish.

So Royal BAM saw the opportunity to better manage risk and create a safer workplace. Their data insight let them balance the profitable with the predictable and increase human safety. JPL saw an opportunity to better design all kinds of parts and to manufacture them in all types of ways. Claudius Peter saw an opportunity not just for a better way to design things but to find better ways of making them that would have less negative impact by using less material and less energy. Phoebe and UNHCR saw an opportunity to improve the lives of 600,000 displaced people by giving them a better plan for a better community.

What opportunities do you see? You understand the impact of your work on the world. Imagine the impact you will have with limitless computation. Imagine applying this capacity to the problems that you wrestle with. Together, we're exploring the opportunity to make the world more balanced, more sustainable, more equitable. Let's make a better world. Thank you.

[APPLAUSE]

Now we'll hear from Matt Gough. Director of Innovation at Mace. The company has been leading the industry with amazing ideas made real like the rising factory, a fantastic demonstration of thinking big to try and solve some of the world's most pressing problems-- urbanization, sustainability, and labor availability. Please join me in welcoming Matt to the stage.

[MUSIC PLAYING]

MATT GOUGH: Thanks. Good morning, London. It's my pleasure to welcome you to this amazing city this morning and my pleasure as the Innovation Director of London's top contractor to be able to share with you how we're embracing the opportunity for better at Mace. I'm going to talk to you about the acceleration of our digital transformation, the acceleration of building buildings, and importantly our collective role in doing so responsibly and sustainably.

But first, we need to go back a few years. Mace is an international construction and consultancy company founded in 1990 in pursuit of a better way for delivering construction projects for our clients. In 1998, when Egan was encouraging us to rethink construction as a manufacturing process, Mace was already exploring that opportunity for convergence to deliver the London Eye to a program and a budget that the rest of the traditional UK construction industry had told us could not be achieved-- had told our client could not be achieved.

We saw a better way. In 2011, we were completing London's tallest building, the Shard, safely and to a rate of production not achieved before in the city of London. We did so by applying both digital and offsite pre-fabrication techniques to test, prototype, and assemble all of the building's most complex elements, a great case for convergence.

And we continue to innovate in order to deliver enhancements to London's skyline. Any football fans in the room? We've recently completed Tottenham Hotspurs' world-beating new stadium, a mega-projects in which 30,000 unique operatives were inducted over a three-year program.

We're midway through turning the power back on Battersea Power Station, a 1.6 billion pound transformation of one of London's most iconic buildings. There's 19 tower cranes on that site alone at present.

But for today, our innovation case study really hones in at the site of one of Mace's most significant success stories-- the Olympic Park, home of the London 2012 Olympic games. Following the success of London 2012, Mace has continued a role to help transform the part into the fantastic legacy that it is today.

In 2014, we were appointed by our client Qatari Diar Delancey to build No. 8 a twin tower development and podium building that delivers 480 much needed new homes for Londoners-- designed traditionally, procured traditionally, but built using a radical new way of construction, a first for the UK.

Our project team at No. 8 were tasked with changing how we build. There were a number of project risks to be mitigated. Accidents when working at height continue to be the biggest cause of fatalities within our industry.

We had some challenges with the wind, particularly in East London, which stopped cranes and causes program delays. And importantly, when delivering residential the critical path always get stuck with the fit out. You simply can't start laying carpet until you've got the building weather tight and stopped the rain coming in.

So our team found a better way. At the top of those towers, you can see our two rising factories-- 600 ton steel structures that sit at the top of-- that jump as each floor of the building is completed. They're roughly the size of the Tower of London, each of those. That jump, in order to lift them, when activated, is the equivalent of a space rocket taking off-- our very own Mace X.

And inside the factory is a very different environment in which to build. We're about to go in one. This video is shot 100 meters up in the air, although you wouldn't necessarily be able to tell. And it shows a standard sequence for our construction operatives to install a residential floor.

So in the top left, you'll see a clock counting down from 55 hours-- Monday morning to Saturday lunchtime, a working week on site, and how quickly we were finishing a residential floor plate. What you can see is a sequence of bringing in a number of industry standard components, such as pre-cast concrete columns and twin wall.

What is unique is not the product but the sequence and the process in which it is being delivered. This is not a construction site. This is a factory floor. You will note that there's no tower cranes. All lifting is taking place via set of high-powered Gantry cranes that allow us to lift bigger elements-- up to 20 tons-- unrestrained by the wind.

There's some MEP modules which are coming in a minute. They're much larger than we could normally lift. And they provide the entire horizontal MEP services to the floor plate, installed in just 30 minutes. Just about to come in now.

You will also spot that there's not many operatives on the working deck. We've got a real challenge on labor availability within our industry. And at No. 8, we were able to reduce the number of operatives-- the amount of labor required on site-- for the five major packages by 50%.

And in terms of safety, there's no leading edge. The factory entirely removes the requirement for working at height, and there's no chance of dropping anything. Just some of the many benefits achieved.

Once we got going, we built 18 stories of residential in 18 weeks. The two towers were completed 30% faster than any of the traditional construction market had achieved in the UK. It was our safest high-rise project with over 2 million man hours completed without an incident. We were more productive, and importantly, we reduced our impact during the construction process significantly.

Offsite consolidation led to 40% less vehicle movements during construction. That's less impact on the roads, less impact on local residents, and less pollution. And we managed to reduce the waste on site by 75%.

Our project team No. 8 saw a better way and were able to use it to achieve some industry firsts by changing their mindset. They challenged everything about how they thought the construction of a high-rise should be completed and achieved a phenomenal result.

This man here is Dave Bones. He's in that team. Dave is one of our senior construction managers. He's been in the industry for 40 years.

You're all a bit fearful of the stereotype of Dave. He's one of those industry dinosaurs. He doesn't like change much. So what about technology? Don't fancy doing that.

But here at No. 8, our Dave is embracing innovation with both hands. So one day on site, Dave runs into the project office panicked, flustered, a bit put out. What's the matter, Dave, asked our project director, fearing the worst-- a fire, an accident on site, something serious.

Tony, there's loads of traffic today. The crane's decommissioned I'm 12 minutes late on my fit out delivery. 12 minutes late-- not hours, not days, or weeks, or even months, like the delays we face on some capital projects. But Dave is thinking in minutes. It's a different mindset, a different way of thinking to deliver construction.

Across the globe, our people at Mace are employing that different mindset in order to develop, adopt, and deploy technology across all parts of the project lifecycle. In Ireland, our teams of digitized, connected, and integrated the entire construction workflow from design right through to operation and handover using the BIM 360 platform.

We've made people's work easier and more efficient by democratizing data and integrating all of our onsite processes. That has accelerated people's work. Our site managers and operatives are saving up to eight hours a week, a 32% increase in their productivity.

We're also pioneering the use of BIM 360 plan for our onsite planning and production control. Technology is allowing us to plan in greater detail, increasing from 150 tasks a week using paper to 350 tasks using digital. Greater detail offers greater integrity.

And our percentage of work completed has increased accordingly from 71% to 80% of planned tasks. So we're not just tracking more. But we're completing more work more consistently using technology as the enabler.

More closer to home, just over the river from here in Greenwich, our onsite teams are scanning and validating all completed works, comparing what's been built versus what should have been built. On the piling alone, we've reduced the cost of error by 72% by identifying and resolving errors in real-time.

And globally across our projects, we are more efficient and more productive every day through the use of technology. We're flying drones, using VR, AR, 360 cameras, sensors, automation. We're designing, estimating, and delivering in digital. And we're handing over better quality projects as a result.

And to do that, we're empowering our people with technology. Across our 6,000 staff globally, we are completing a program of training in all aspects of digital from 3D coordination through to 60 operations. Across our supply chain via our Mace Business School, we are training the industry to be better at tech, from MBA level courses for our supply chains rising stars to digital basics on our sites and our offices worldwide. And the result is that we have a more empowered workforce, a happier workforce, that are driving up our productivity and delivering better outcomes for our clients.

Yet while we are achieving great things by applying technology to do those things better, we also recognize the need to do better things. There are many reasons that we need to change as an industry-- rapid urbanization, the environment, poor productivity, labor availability. We all know the list, right?

But our industry is digitizing fast. And that puts us on the cusp of a significant, once-in-a-lifetime transformation of our industry. The entire game is changing.

Our response at Mace is moving from construction to production. We see a near future where we will design, manufacture, assemble, and operate the built environment that we are responsible for in a very different way. We'll be faster, safer, leaner, more predictable on outputs, such as time and cost, and better.

By 2022, 85% of Mace's projects will be manufactured and assembled 50% faster than our 2017 baseline. And our clients are going to be 100% more delighted with the outcomes. This business model is going to be enabled by technology.

We're now well underway with building the ecosystem that will allow us to transform. How we engage our supply chain will be radically different. We're taking a lot of learning from the retail sector, and we'll have full end-to-end visibility of all supply chain activity, from order through to operation. We will control our onsite execution and assembly processes far more efficiently with integrated logistics and material management, plug-and-play assembly, real-time site execution.

And most importantly, the customer and end users will be at the center of our future production system. Client configuration will enable more agility in the design stages. Our platform enables real time transparency across the entire project lifecycle. So the power of project status and performance is in everybody's hands. And digitized buildings and smarter assets mean an ongoing rich relationship between the built environment and its users, giving us the data to continuously improve all aspects of the project lifecycle.

In doing so, we will unlock the power of our organization and the wider industry to guarantee a better outcome for our clients. And by this, I don't mean those traditional construction outputs that we all love measuring so much-- a bit faster, a bit lower cost, a few less defects. That's that nasty but necessary capex thing that a lot of people aren't too worried about. I'm talking about outcomes, the purpose of the buildings that we're all responsible for creating, day in and day out.

OK. Remember Dave? Now, I'll be honest. I have to deal with a few Daves in my day-to-day, too. We all know a Dave. All right. Close your eyes. Picture him. You can probably see him now.

Turns out not everybody is that fussed about business model transformation or technology adoption. But the good people-- Dave included-- definitely care about outcomes-- better education for kids, better productivity for office workers, better health care for patients, better journey times for commuters.

You see all this transformation and change only really works when your people believe in it, drive it, champion it. And that is what is accelerating our thinking at Mace where we're putting our purposeful approach into practice already.

Working for a major Whitehall client on their 10-year estate strategy, we've identified a 10% capital cost reduction and a 20% opex improvement across a 4 billion pound program. We're rethinking design, thinking about the estate as a suite of standard design platforms and putting our focus on product development to help them realize a brave new approach, which is cool. But the real cool, the real outcome, is going to be more available, more suitable and more sustainable accommodation for service men and women way into the future.

Our next iteration of the rising factory is now in production. It doesn't involve a factory. But it does involve faster construction and reduced costs by integrating floor and facades into modules and applying all of the innovation multipliers from the factory.

We're vertically integrating our supply chain. We're working in a better, more collaborative way with our clients, architects, and designers. And the real outcome is going to be more, better homes for Londoners faster.

And we're also deploying technology across our commissioning and facilities management projects to get better operation efficiency for our clients. Working with partners, we were achieving significant savings in energy use and operational expenditure.

Recently, a big banks corporate HQ in London, we reduced the energy usage in the building by 20% a year within the first month of our contract. But the real outcome is better productivity, better well-being, better health for those employees.

And as we move from construction to production, this focus on outcomes for our industry is the most important point for us all to remember. Not to be too existential, but what is our purpose as construction?

We beat ourselves up about the industry-- image of the industry far too often. I mean, it is tough at times-- really tough. We had a month's worth of rain in London last week in six hours. That's a lot of rain. That's a lot of mud.

But despite that, we achieve amazing feats. We build amazing projects. We've looked at some of Mace's earlier. And we make a tangible impact on people's lives every minute of every day, be they working, traveling, sleeping, studying. You just can't say that if you build mobile apps for living. And that's why at Mace we're laser focused on our vision, to be the industry leader in shaping cities and building sustainable communities and the positive outcomes that we generate as a result.

We're leaving a positive impact on the environment because this is a climate emergency and we have a seriously resource-intensive industry. There's roughly 12 years to sort our carbon emissions out if we want to keep global warming to that acceptable level. So we've signed up to the RE100, and we'll remove carbon from our operations by 2022. We're also well on the way from removing all diesel from our sites. But we can all do more.

We're creating a positive impact on the communities we work in and around. Urbanization and an increase in population density is now happening on everyone's doorsteps. And people's health and well-being is significantly impacted by construction.

So let's do it in a positive way. Create jobs. Create opportunities. Champion change. And importantly for today, as a room of change makers, we need to make a positive impact in improving our own industry. We have a collective responsibility to do so. And that is why and how our people at Mace turn up to work every day, pursuing a better way for our clients, our colleagues, and our communities.

And I'll just leave you on this point, which borrows from the excellent innovator Beth Comstock. Mace was founded in pursuit of a better way. And today, we ask our colleagues to continue that mission. And to do so, they-- and I think, us-- have to believe in a better way.

To have an impact-- which I think we're all capable of-- we need to do two things-- firstly, believe that tomorrow can be better today, and secondly, that we have the power to make that so. And that's what we can do in our industry. That's our opportunity for better. Thank you.

[APPLAUSE]

ANNOUNCER: Ladies and gentlemen, please welcome to the stage Erin Bradner.

[MUSIC PLAYING]

ERIN BRADNER: The rhetoric of innovation paints a picture that it's either about waiting for an idea to drop out of the sky, or it's about building a fun environment to coddle creativity. The reality is that innovation is hard work. It's difficult not because conjuring new ideas is difficult-- that's part of it.

What's difficult is executing on those ideas. Not everyone can execute on innovation at the incredible scale that Mace does. Yet I know you have no shortage of incredible ideas. You simply may not have chosen to dedicate the budget and the people full-time to research and development.

So I want to talk to you today about three approaches to innovation that we take at Autodesk. We collaborate to focus our research. We cultivate conditions where innovation can thrive. And we work with customers who catalyze change in their fields by pushing our tools in new directions.

I work in Autodesk Research. And it's our job to innovate, to solve problems we know you have today and we know you will have in the not too distant future. Autodesk dedicates considerable resources to developing new technologies. Our in-house researchers and domain experts continually invent new technologies.

But working independently on our original ideas is just one way we innovate. Today, I'll tell you a few stories about how we work with others to collaborate, cultivize-- collaborate, cultivate, and catalyze innovation so we can help you make better things in better ways.

Let's start with a story about how we collaborate. It's a story that begins with a question. What do you do if you're an architect and your client loves your unique design and you have an idea for how to build it but no one has ever attempted before?

This 24-meter footbridge is not made from exotic materials. Its appeal is not in its steel tubes and plates. Its appeal is in its complex angles. There are a lot of them, and they all need welding.

Welders build fixtures to hold pieces in place while they work. But to do that here, you would need to build a fixture that is as complex as the bridge itself. You could call in a team of carpenters, or you could call in a team of roboticists.

That's what architect Scott Mitchell did. He called Autodesk's robotics team-- my team. Scott runs the architecture studio at the University of Southern California that designed the bridge. And he wanted to know whether our researchers could help him execute on his idea to use a robot to position all 500 parts in his bridge for a human to weld.

Scott knew that a typical assembly line robot can take days to program just one part. So he knew the maths for his bridge wouldn't work out. If 500 parts in CAD equaled 500 days of programming, then it would take over 16 months just to program his bridge.

Scott was also wrestling with what sequence he should follow when assembling the bridge. He was resolved that his robotic workflow needed to be flexible about sequencing.

Our robotics team was resolved about flexibility, too. They had recently developed a research tool called Mimic. It's an open source plugin that brings robotic control into the familiar environment of Maya. Maya is what customers use today to control the motion of animated characters.

Our team was convinced that the sequencing should be driven by Scott within this flexible environment with the robot programming being automated by the design file itself. So they customized Mimic to automatically generate robot motion code from the 3D model of Scott's bridge. The robot knew where to move because every plate and beam knew its place in the design file. The logic in the 3D model was the same logic that drove the robot programming.

Through this flexible workflow, Scott could sequence and re-sequence the assembly in any way he liked as often as he liked. All that he needed at this point was a really big robot. So Scott secured a residency at Autodesk's Technology Center in Boston, and the team there helped him get set up.

Now as Scott began moving the robot, he found a couple of bolts that weren't modeled in the CAD file. And that restricted the robot's reach. In a traditional robotic workflow, this would have stalled production and caused a day or two of delays. But he just nudged the robot in Mimic and recompile the instructions.

It was no big deal. Producing the robot code to drive the robot took just 15 minutes. What the robot made for Scott was not up for debate. The bridge in the 3D file was the bridge that Scott had permission to build. But how the bridge was sequenced was flexible. Scott could adapt his strategy on the fly.

People are great at creativity and common sense, conjuring ideas and making decisions on the fly about how those ideas should best be made. Industrial robots are great at precise positioning and heavy lifting. By using robots and people for what they're each good at, Scott and Autodesk created the opportunity for both parties to do what they do best even better.

With 3D design data driving his robot, Scott was better equipped to move from design to build. He learned how to better execute against his design intent and build a complex bridge with less technical friction. Plus the learning from this collaboration went both ways. Our researchers learned how to better automate robotic assembly at civil engineering scale. Architects collaborating with technologists is a mutually beneficial approach to innovation.

Let me tell you about another approach to innovation, an approach that's less about collaboration and more about cultivation. This approach is about seeding the conditions for growth and creating an environment where innovative ideas can germinate. Because although your next big idea might arrive in a flash of genius, executing on that initial spark can be a stormy slog. But when we bring innovative people into our organizations and give them a resource-rich working environment, their ideas can quickly take root.

We take this cultivation approach to innovation at Autodesk. And we do this by inviting academic researchers, startups, and customers like you into our technology centers to share our space and our equipment as they explore ideas that will shape a better future for all of us.

We have four centers globally, and we host over 300 residents in those centers every year. One resident is a startup called Overview. Overview was founded by a couple of ex-Tesla engineers, and they're residents in our San Francisco Technology Center.

They're developing a machine-learning vision system that watches machines on a production line and generates real-time alerts when production goes awry. Their approach is pretty simple. An inexpensive camera watches machines for a while as perfect intolerance parts are made.

And then over time, a machine-learning algorithm in the cloud learns what perfect looks like. It learns from watching the correct thing being made time and time again. So if something imperfect happens, the system sees it and flags it.

Now visual inspection has been around for decades. This is a whole new breed of visual inspection. There's no pre-programming required, and no hard coded rules for exceptions. A shadow might throw off traditional inspection.

But a machine-learning algorithm can learn what a shadow is. And once it's developed shadow detection insight, it can apply that learning across multiple parts and any conditions.

The machines in our Technology Centers don't know if they've made something wrong. Most machines don't. But by applying machine-learning, the overview system can spot errors when people aren't available or aren't trained to spot them.

Through the Technology Center residency, Autodesk is helping cultivate Overview's ideas. They own the innovation. We don't. But our manufacturing customers stand to benefit if they successfully execute on this budding technology since it likely means less money wasted on defective parts and more machine uptime for manufacturers.

Overview is just one of the residents were hosting in our San Francisco Technology Center. The center is focused on the concept of the reef configurable microfactory. And the Boston Technology Center where Scott built his bridge is focused on digital fabrication and construction automation. And our Birmingham Advanced Manufacturing Center here in the UK specializes in additive, subtractive, and hybrid manufacturing methods.

Although each Technology Center has a different focus, they all operate under an open innovation sharing philosophy. Our residents share what they've learned with each other and with us. Nurturing new technology by hosting residents and by cross-fertilizating ideas is what I mean when I say that Autodesk cultivates innovation.

But this approach is not unique to Autodesk. Some of you are doing this, too. I'll give you a quick example. In February, this year I met this man-- Rolando Mendoza-- at a conference on industrialized construction. Rolando told me that he uses the construction sites that he operates as open air innovation laboratories to prove out new technology.

Rolando is the Director of Virtual Design and Construction for an American construction firm-- Mortensen. And that's his laboratory. It's one of many. His company is building half a dozen projects like this at any given time.

He was at the construction conference looking for the next technology to prove out. He and I were both very intrigued by a startup called Dusty Robotics. They were developing a mobile printer to paint wall layout lines on concrete slabs. This is the concept printer from their website.

Now fast forward three short months, and here the Mortenson folks and the Dusty team at a football stadium that Mortenson is building in Las Vegas. Now I'm talking about the kind of football where there is very little contact between the foot and the ball-- American football.

This new stadium will have a retractable grass field, a self-cleaning transparent roof, and 60,000 square meters of concrete floor. Less than 1% of that floor-- just 150 square meters-- became the open innovation laboratory.

Mortenson cordoned off this space for the founder of Dusty Robotics-- Tessa Lau-- so she and her team could complete the biggest automated layout that they had ever attempted. On a Saturday morning at 7 o'clock, Tessa's printer painted wall layout lines for three luxury suites in the stadium.

As the lines took shape on the floor, we all gathered around to inspect the printout. The CAD drawings that Mortenson had provided had been clearly laid out on the concrete. The field test was a success. The printer knew what to paint because it used the lines that were extracted from Revit. An off-the-shelf survey tool-- a total station-- told the robot where to paint.

Now, the following week, Mortenson's subcontractor laid out that same space. They also used a total station to locate points, and then they snapped chalk lines. Their layout confirmed what the Dusty team suspected. The field printer's layout was right on target. As you can see in this image, the blue chalk lines landed right on the black printed lines.

According to Mortenson Construction's construction manager who was at the test, his framing crews could build off the printed lines. It was a watershed moment for him. He could now see into the near future when he had a device that knew its location on a construction site and would make his subcontractors work more accurate, less error prone.

In fact, the subcontractors showed up at the field test. They came on their day off to observe. And they liked what they saw, which surprised me. Because I thought they would see the device as a threat to their job security. After watching the printer paint lines for an hour, they determined it could potentially speed up layout. It could eliminate the need for math in the field-- simple addition and subtraction.

Reserving less than 1% of their construction sites as proving grounds for new technology is helping Mortenson build projects better. They're documenting what they learned from this test and applying it in another month on a future test on a future site.

By cultivating innovative technology like the field printer, Mortenson is giving their layout teams the upper due opportunity to do their jobs in less time, enabling their wall framers to do their job with more precision and accuracy and less waste, less rework.

So I've told you how Autodesk collaborates to innovate. And I've shown how the Autodesk residences and the Mortenson field tests help cultivate innovation by providing opportunities to prove out new technologies. Next, I'll share an example of how you can catalyze change in your industry, how you can innovate in your field by pushing Autodesk tools in new directions.

Artists push tools in new directions all the time. The artist Joris Laarman catalyzed the invention of large scale metal 3D printing by pushing robotic welding in new directions. The artist Madeline Gannon used computer vision and closed loop control to catalyze the creation of interactive robotics.

My last story this morning is about someone who pushed generative design in new directions to catalyze the creation of something sublime. This story starts with a simple design question. Can you find a structure to rest our bodies using the least amount of material?

It's the question that renowned French designer Philippe Starck asked Autodesk's Generative Design tool. And our tool's response was this-- a chair that is as beautiful as it is comfortable, the first commercially available piece of furniture created by artificial intelligence.

Now that's the story you may have read online. But the story is more nuanced as you can imagine. Yes, Philippe Starck is the visionary creator behind this sublime chair. And Starck mentored the algorithm to suitable results. But just how did our Generative Design Tool produce a chair that is both beautiful and manufacturerable, that's novel and yet true to Starck's aesthetic, and that's suited for mass production?

Let's back up to win Starck first encountered generative design. He had high expectations for a system. He imagined being able to describe what he wanted in words and a fully realized design would take form. And being the conceptual thinker that he is, he described what he saw it as something like nature driven by economy, hazard, and need. Now as good as AI is at interpreting human speech, it will be quite some time before it's able to take economy, hazard, and need and create something as beautiful as this chair.

So Starck's design team, which included a design researcher from Autodesk Research, they circled around those inspiring yet abstract requirements for weeks. They stalled out. They didn't know how to push those ideas into the tool.

The breakthrough came when Starck provided minimal lines for a comfortable chair. These lines captured the essence of a Starck chair. They served as the initial geometric constraints for generative design. And they included a minimal seat surface, minimal back and arm supports, and the points of contact between the floor and the chair.

With the constraints defined, next came the functional goals. The goals for this chair were to use minimal material, support a human, and be manufacturable through injection molding. These specific goals plus the constraints were enough to jumpstart the system's brain, and it began kicking out solutions.

It was then that the Autodesk design researchers started exploring the solutions on Starck's behalf. And he saw that he needed to beef up the leg constraints, those rectangles that you saw, because producing criss-crossing legs would not be possible. You cannot injection mold something with criss-crossing legs.

Now here's an example of a first generation design. Starck's critique of these designs-- the initial generations-- was brutal. He said they were either too robotic or too scary. So the algorithm had solved for the functional requirements but was blind to the emotional aesthetic.

So the Autodesk researcher adapted the constraints to drive the system toward more slender struts and less blocky proportions. Working back and forth with the system, Starck and the researcher continued until Starck was confident in the chair's minimal aesthetic.

Our generative design tool made him confident in how the chair would perform, not just in terms of strength but also manufacturablitity because the algorithm had optimized the walls surface that forms the hollow interior of the chair, and it optimized the chairs overhanging angles. Walls that are too thick cost too much. Walls that are too thin risk collapse. And overhangs risk the chair failing to release during production, which renders a million euro mold worthless.

And so these beautiful curves are there for a reason. They reflect Stark's aesthetic, and they reflect his knowledge of injection molding.

We can apply this insight within Fusion 360 to offer similar performance to our customers in the future. Now Philippe Starck pushed generative design in a direction that we hadn't imagined. Our initial idea for generative design was to optimize for structural performance.

But he pushed the tool toward optimizing for aesthetics and injection molding. By pushing the tool, he helped catalyze our thinking about what generative design could be. He helped us explore new opportunities for how generative design could better make things that are strong, sublimely beautiful, and manufacturable.

Whether your field involves building bridges, laying out walls on construction sites, or making consumer products, it's not a lack of ideas or creativity that stifles innovation. What's difficult is executing on those ideas.

Scott's design studio is quite capable of generating creative ideas, but it's how open Scott was to collaborating with other researchers and robots that's helping him execute on the assembly of this complex bridge. And just as Mortenson opens up 1% of their construction sites to help cultivate the conditions where innovative startups like Dusty Robotics can prove out their ideas, Autodesk opens the doors to our technology centers to cultivate budding projects in a resource-rich environment. And while creativity is no doubt a key ingredient in Philip Starck's recipe for innovation, pushing our generative design tool in new directions is doing more than executing Starck's design ideas. He's catalyzing a new AI-assisted approach to furniture design.

At Autodesk, we work with you, our customers, in many different ways to create new and useful tools. Because despite our innovative ideas and our creativity, it's you, our customers, who shape our ideas into something that adds value, giving you the opportunity to make better things in better ways and do better work. Thank you. Now go open some doors at AU.

[APPLAUSE]

______
icon-svg-close-thick

Cookie preferences

Your privacy is important to us and so is an optimal experience. To help us customize information and build applications, we collect data about your use of this site.

May we collect and use your data?

Learn more about the Third Party Services we use and our Privacy Statement.

Strictly necessary – required for our site to work and to provide services to you

These cookies allow us to record your preferences or login information, respond to your requests or fulfill items in your shopping cart.

Improve your experience – allows us to show you what is relevant to you

These cookies enable us to provide enhanced functionality and personalization. They may be set by us or by third party providers whose services we use to deliver information and experiences tailored to you. If you do not allow these cookies, some or all of these services may not be available for you.

Customize your advertising – permits us to offer targeted advertising to you

These cookies collect data about you based on your activities and interests in order to show you relevant ads and to track effectiveness. By collecting this data, the ads you see will be more tailored to your interests. If you do not allow these cookies, you will experience less targeted advertising.

icon-svg-close-thick

THIRD PARTY SERVICES

Learn more about the Third-Party Services we use in each category, and how we use the data we collect from you online.

icon-svg-hide-thick

icon-svg-show-thick

Strictly necessary – required for our site to work and to provide services to you

Qualtrics
We use Qualtrics to let you give us feedback via surveys or online forms. You may be randomly selected to participate in a survey, or you can actively decide to give us feedback. We collect data to better understand what actions you took before filling out a survey. This helps us troubleshoot issues you may have experienced. Qualtrics Privacy Policy
Akamai mPulse
We use Akamai mPulse to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Akamai mPulse Privacy Policy
Digital River
We use Digital River to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Digital River Privacy Policy
Dynatrace
We use Dynatrace to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Dynatrace Privacy Policy
Khoros
We use Khoros to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Khoros Privacy Policy
Launch Darkly
We use Launch Darkly to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Launch Darkly Privacy Policy
New Relic
We use New Relic to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. New Relic Privacy Policy
Salesforce Live Agent
We use Salesforce Live Agent to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Salesforce Live Agent Privacy Policy
Wistia
We use Wistia to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Wistia Privacy Policy
Tealium
We use Tealium to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Tealium Privacy Policy
Upsellit
We use Upsellit to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Upsellit Privacy Policy
CJ Affiliates
We use CJ Affiliates to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. CJ Affiliates Privacy Policy
Commission Factory
We use Commission Factory to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Commission Factory Privacy Policy
Google Analytics (Strictly Necessary)
We use Google Analytics (Strictly Necessary) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Strictly Necessary) Privacy Policy
Typepad Stats
We use Typepad Stats to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. Typepad Stats Privacy Policy
Geo Targetly
We use Geo Targetly to direct website visitors to the most appropriate web page and/or serve tailored content based on their location. Geo Targetly uses the IP address of a website visitor to determine the approximate location of the visitor’s device. This helps ensure that the visitor views content in their (most likely) local language.Geo Targetly Privacy Policy
SpeedCurve
We use SpeedCurve to monitor and measure the performance of your website experience by measuring web page load times as well as the responsiveness of subsequent elements such as images, scripts, and text.SpeedCurve Privacy Policy
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

icon-svg-hide-thick

icon-svg-show-thick

Improve your experience – allows us to show you what is relevant to you

Google Optimize
We use Google Optimize to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Google Optimize Privacy Policy
ClickTale
We use ClickTale to better understand where you may encounter difficulties with our sites. We use session recording to help us see how you interact with our sites, including any elements on our pages. Your Personally Identifiable Information is masked and is not collected. ClickTale Privacy Policy
OneSignal
We use OneSignal to deploy digital advertising on sites supported by OneSignal. Ads are based on both OneSignal data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that OneSignal has collected from you. We use the data that we provide to OneSignal to better customize your digital advertising experience and present you with more relevant ads. OneSignal Privacy Policy
Optimizely
We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
Amplitude
We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
Snowplow
We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
UserVoice
We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
Clearbit
Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID.Clearbit Privacy Policy
YouTube
YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

icon-svg-hide-thick

icon-svg-show-thick

Customize your advertising – permits us to offer targeted advertising to you

Adobe Analytics
We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
Google Analytics (Web Analytics)
We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

Are you sure you want a less customized experience?

We can access your data only if you select "yes" for the categories on the previous screen. This lets us tailor our marketing so that it's more relevant for you. You can change your settings at any time by visiting our privacy statement

Your experience. Your choice.

We care about your privacy. The data we collect helps us understand how you use our products, what information you might be interested in, and what we can improve to make your engagement with Autodesk more rewarding.

May we collect and use your data to tailor your experience?

Explore the benefits of a customized experience by managing your privacy settings for this site or visit our Privacy Statement to learn more about your options.