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Autodesk AI: AutoCAD Smart Blocks and Markup Import & Assist

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说明

Join us to learn about AutoCAD software's AI features that make your drafting more efficient than ever: Smart Blocks, Markup Import, and Markup Assist. We'll start by covering Markup Import and Markup Assist, the workflow that uses AI to interpret and apply feedback from marked-up PDFs directly into your AutoCAD drawings. You'll learn how Markup Import and Markup Assist can enhance collaboration, drastically reduce the time it takes to incorporate feedback, and reduce errors in your design workflow. Then we'll review Smart Blocks, a suite of AI tools designed to streamline your drafting and drawing cleanup processes. We'll cover Block Placement, Block Replacement, Block Search and Convert, and Object Detection—all of which use AI to help you find, create, and use your blocks. We'll end the session with an opportunity to share ideas on how else AutoCAD might use AI to increase productivity, enhance collaboration, and improve your drafting and documentation workflows.

主要学习内容

  • Learn about using Smart Blocks to improve drafting efficiency.
  • Learn how to integrate Smart Blocks features into your workflows to reduce the time and effort needed to cleanup drawings.
  • Learn how to use Markup, Import, and Assist to drastically reduce the time it takes to incorporate feedback into an AutoCAD drawing.

讲师

  • Anum Mithani
    Anum's career began in the engineering and construction industries. She is a graduate of the University of Waterloo, holding a Bachelor's in Civil Engineering. Her professional experience includes four years as a building science consultant, where she focused on projects involving low-energy new construction and restoration of heritage buildings. Anum completed an MBA and a Masters in Engineering in Design Innovation from Northwestern University. During this time, she interned with the AutoCAD Desktop Product Management team at Autodesk, and upon graduating she returned to the team full-time. In her current role as a Product Manager for AutoCAD for Desktop, Anum contributes to the customer experience of the Smart Blocks Search and Convert and Object Detection workflows in AutoCAD. She is also working on strategies and features for insights in AutoCAD.
  • Anand Rajagopal
    Anand is the Head of AI Development for AutoCAD at Autodesk, where he has spent the last decade exploring the intersection of AI and Architecture, Engineering, and Construction (AEC). With a passion for harnessing the potential of data and AI, Anand has dedicated his career to improving the connectivity of data across the entire construction lifecycle. He has developed innovative products that cater to both superintendents in the field and drafters in the office. Anand holds two patents for his research focused on enhancing job site safety through data utilization.
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      Transcript

      ANUM MITHANI: Good afternoon and welcome to today's product demo. We really appreciate all of you choosing to tune in to today's presentation. We've got a pretty exciting topic to cover here. We're going to explore Autodesk AI features within AutoCAD, namely Smart Blocks and Markup Import and Assist.

      But before we get into the demo, we'd like to introduce ourselves. I'm Anum Mithani, Product Manager on the AutoCAD Desktop Team. I work on the desktop workflow experience for some of our ML features, as well as our AutoCAD insights strategy. And with me today I have.

      ANAND RAJAGOPAL: Hi. My name is Anand. I'm an Engineering Manager within AutoCAD. I lead the AutoCAD AI and ML development teams. Happy to be here.

      So we're really coming to you today with just one goal. Our goal is to really introduce you to what the Autodesk AI features within AutoCAD look like and how can you leverage them to better increase your own productivity. Let's dive, right [AUDIO OUT]

      We've all seen the AI kind of buzz around us. We felt it. It's been there now almost two years. And it's gone beyond just ChatGPT. That's still what's spoken about the most, but it's making its circles within the AEC realm. You see it every day talking about the productivity enhancements in our industries.

      And we want to really tell you what we're doing within AutoCAD. But before we get there, we want to just maybe take a minute to level set. What is AI? Next slide, please.

      So despite the current attention, I isn't really a new term. It was coined in the 1950s. It's really a broad area of computer science research.

      It focuses on tasks that need humans and computers to interact on tasks which require usually human-level intelligence, but it's not restricted to that. Within this broad umbrella of AI, machine learning, or ML is a subset of techniques. It's just a set of algorithms that rely on today's advanced processing capabilities to sift through large data volumes and discover patterns.

      It's really an implementation-- one kind of implementation for what AI is today. And it's kind of really synonymously used with AI. AI, ML you kind of see that and you can kind of really interpret them the same way. I want to take a second to call on a specific subset of even machine learning algorithms, the generative AI algorithms.

      I mean, these are the ones which are really hard. People are talking about it everywhere. These are basically a specific set of algorithms which can create new content. ChatGPT for text, Midjourney and the likes for images. This isn't something we are talking about today, but if you have more questions, you can come meet us at the booths.

      It's something we can definitely talk to you more about. But this is also honestly as technical as I want to get today, because our goal isn't to teach you more about what is AI, but really what can we give you within the products leveraging AI. So can we go on to the next slide, please?

      What AI can do for you. So in Autodesk, we look at AI in three different ways. Build. First one is automation. This is to reduce the repetitive, tedious work and increase your own time for the kind of work that you matters most to you.

      The next one is augmenting. Can we augment your everyday workflows with AI to make them better partner with you to keep you in control, but again, free up your time to do the things that matter most? And finally, analyze.

      This is to navigate the large mountains of information that comes today to help you make better decisions. And what you're going to do in the subsequent presentation is talk about how all of these workflows manifest themselves within AutoCAD today. With that, I'm going to pass it on to Anum to walk us through some examples.

      ANUM MITHANI: Thank you. So now that we've got a solid foundation on what is AI, let's see how Autodesk AI can help customer workflows. We'll be using an example to highlight the key Autodesk AI features within AutoCAD.

      And here is our lovely lighting designer, Riley. She's teaming up with an architect on an exciting new project. Today, we'll be following along on her journey and get a sneak peek into her workflow as she reviews a background drawing, designs her lighting plan, adds and replaces lighting elements, and gets feedback from her manager. And guess what? She's doing it all with a little bit help from Autodesk AI. So let's dive right in.

      Riley just got a new drawing from the architect. It's a detailed floor plan of a two-story house. The drawing shows walls, doors, furniture, and even some light fixtures that the architect has already specified.

      Since Riley imported this drawing from a different program, all of the objects within the drawing are exploded, meaning that there are no blocks in the drawing. It's a little bit of a puzzle now, but Riley's ready to figure it out. It's time for some much needed drawing cleanup.

      Riley's reviewing the architect's drawing and notices that some light fixtures are already included. She spots a wall light and sees another one right next to it. Riley decides to convert all of the wall lights into blocks for easier management. Normally, she would have to painstakingly select the geometry, create the block, and then manually search through the entire drawing to find all similar geometries, deleting and replacing them one by one.

      It's a tedious process, and often, objects will get missed. But then, Riley remembers the Smart Block Search and Convert feature within AutoCAD. This handy tool can automatically find all matching geometries. She selects the wall light geometry for conversion and types in the BCONVERT command, and sees all of the exact matches that are in the drawing.

      When reviewing the found instances, Riley can easily remove or add back any of the found instances into her selection. Ready to proceed, she presses enter to convert, and the Convert to Block Palette opens up. This palette displays a total number of instances found on the left. As well, there is a checkbox filter that will automatically remove any found instances that are already blocks.

      But because Riley already knows everything in the drawing is exploded, she doesn't need to use this filter. Riley can choose to convert to an existing block from her library, or to create a new one. Since this wall light is unique to the architect, she decides to create a new block and names it arc wallet.

      AutoCAD will automatically select the geometry center as its base point. But Riley wants a base point to be where the fixture meets the wall. She clicks on Select Base Point and picks the base point directly within the Canvas. Finally, she can also define the layer that the new block instances should be inserted onto. She selects her predefined lighting layer, ensuring that all the blocks are on the correct layer.

      With everything set, she completes the conversion with ease, transforming the scattered wall lights into organized blocks, making her drawing much more manageable. We can see that all of the found instances in the drawing are now the new block.

      Feeling accomplished with those wall lights, Riley notices that the architect has also included some pendant lights in the drawing. Once again, to save time from scouring through the drawing manually, she uses the Search and Convert feature. She selects one pendant light, types in BCONVERT and AutoCAD quickly finds and highlights all of the instances of the same geometry. With the instances selected, she proceeds to convert them.

      Riley knows that her firm commonly uses pendant lights and has a block stored in their block library. So she opts to convert the instances into an existing block. AutoCAD suggests similar blocks for her to choose from, thanks to machine learning algorithms that use geometry and naming to find similar blocks that already exist within your library.

      Once again, she can choose the right layer for the block. She clicks on the lighting layer to keep everything organized and goes ahead to convert. Riley's now saved a significant amount of time and effort by using the Search and Convert feature. The ability to quickly convert repetitive geometry into blocks minimizes redundancy in the design and provides wider options for organizing drawings and having more performant drawings.

      With the wall lights and pendant lights efficiently converted into blocks, Riley's drawing is now much more streamlined and manageable. She can focus on the finer details of the design, knowing that the tedious part of the process has been handled with ease.

      ANAND RAJAGOPAL: Thank you, Anum, for giving us an overview. I'm just going to do a quick recap of what we just saw there. With Search and Convert, we saw Riley efficiently identify and convert unblocked lighting elements. It helped us search the drawing to select all matching geometry, convert the geometry into an existing block, or new blocks, in just one easy step.

      BCONVERT, that's the command, let's Riley scale her work but still keeps her in control. It allowed her to define custom base points, select appropriate layers, ensuring that the converted geometries fit seamlessly into her design. We're going to follow along with Riley and see what's her next move. Back to you, Anum.

      ANUM MITHANI: Awesome. So with the wall lights and pendant lights efficiently converted into blocks, Riley decides to continue with her drawing cleanup and tackle the rest of the drawing. Remember, all of the objects came in exploded. She wants to block everything else in the drawing quickly to realize blocks performance gains.

      Normally this process would take hours, but Riley would have to go through and identify each object like a piece of furniture, manually selecting each piece of geometry that makes up that object. This can be super time consuming and tedious if the object is small, detailed, or not easily selectable using a selection window. Then she has to convert it into a block and manually find all of the similar objects to delete and replace them with the new block.

      Repeating this over, and over, and over for each type of object would be exhausting. But Riley is savvy and knows that Smart Blocks Detection uses machine learning to scan her drawing and identify objects that can be converted into blocks automatically.

      She heads to the ribbon and clicks on the Detect Button to launch the detection process. The palette opens and she can see it's working to scan the drawing for potential blocks. The best part? It's working in the background, so Riley can close the palette to regain full screen access and continue working on other important tasks.

      A notification soon lets her know that the detection results are ready. From the notification, Riley sees that 17 sets of objects have been found, covering a total of 48 instances. She clicks to review, which takes her to Detection Review mode. At the top, the device-- the visor displays the 17 sets that were found and she can use arrows to flip between the results.

      Each set represents a group of similar detected objects that can be converted into instances of a single block. The visor has other helpful tools. The Convert button. When Riley is ready to convert the set into a block, she can simply click on this button.

      Next is the Report an Error button. If there's an issue with the detected set, Riley can report an error. By reporting errors, she contributes to improving the overall performance and accuracy of the machine learning service.

      The Primary Instance button. This button allows Riley to select a new primary instance. Within each set, the primary instance, outlined by a blue border, serves as a block definition when converting a new block.

      Alternatively, if she chooses to convert into an existing block, the primary instance is used to define the insertion scale and rotation for the block. And finally, Remove Instances. Riley can use this tool to remove any instances within the detected set that should not be converted with the rest.

      Riley then spots a detected set that contains store objects. She wants to convert all of the interior doors, but not the exterior ones into a block. By using the handy Remove Instances tool, she can carefully remove the exterior doors from the selection set, ensuring that only interior doors are included.

      When she clicks to Convert, the Convert to Block palette will open up, showcasing all the helpful capabilities she saw with Search and Convert. She decides to convert the door into an existing block in her library and chooses a half-closed door from the machine learning based suggested blocks.

      Riley selects the appropriate lighting layer, ensuring everything is organized correctly. When she presses Convert, AutoCAD gives her the option to accept the placement of the existing block, or to adjust it as needed. She moves the block into the correct position. Then, she scales it to fit and accepts the changes.

      Now, we can see that all of the interior doors have been changed into the new block, thanks to Riley's smart use of the tools at her disposal. The drawing has become more organized and performant by the minute. Riley continues through the detection results, swiftly creating new blocks en masse. Each set she reviews brings her closer to a more organized and performant drawing.

      However, the next set she encounters has an error. No problem. Riley clicks on the Report Error button. She knows that while detection is best at identifying architectural objects on floor plans, it's not always perfect in this release. By reporting errors, she's helping to continuously improve detection results over time.

      She continues on, empowered, knowing that her drawing is as accurate as possible and leveraging tech to complement her expertise. As Riley continues, she feels a sense of accomplishment. The once chaotic and exploded objects have been transformed into well-defined blocks, making the entire layout so much more manageable.

      She takes a moment to appreciate how much time and effort she saved. Instead of manually searching for and converting each object, she's harnessing the power of Smart Block Detection to do all the heavy lifting. This has allowed her to quickly move on and focus on her next important task of designing the lighting plan, where her expertise will truly shine.

      ANAND RAJAGOPAL: Thank you, Anum. Way to go, Riley. We earlier just saw her use the BCONVERT command, and that was to find matching lighting elements. This time, we saw her use the Detect command to automatically scan and identify all unblocked objects that can then be converted into blocks in her exploded drawing.

      Under the hood, Detection uses machine learning to determine if a particular group of geometric elements should be blocked, or are usually blocked. This, again depends on the context of the drawing. So it's something which is always going to learn from how people engage with the particular command and how they use it.

      This was a great way to clean up the drawing. The AI today, as Anum mentioned, is better at certain objects and is always getting better. And it should continuously learn and improve with subsequent releases. With that, I'm going to pass it back to Anum to move on and show us what the lighting plan looks like.

      ANUM MITHANI: Awesome. So as Riley progresses through her lighting design, she has to place blocks from her blocks library into the drawing. Normally, this can take some time. She has to make sure that the scale and rotation for each block makes sense for the floor plan.

      But as she continues on with her work, the Smart Blocks Placement Engine begins to learn from how the existing block instances have been placed in the drawing. This intelligent engine starts to infer the optimal placement and scale for the next instance of the same block. When Riley goes to insert another wall light, the engine provides placement suggestions near similar geometries where that block has been placed before. Impressively, it autorotates the wall light to align with the wall.

      This feature is a gamechanger for Riley. It significantly speeds up the process of placing blocks, ensuring that they're correctly oriented and positioned without the need for constant manual adjustments. With each block placement, the engine becomes more accurate, learning from Riley's design choices and making smarter suggestions. This not only saves time, but also reduces the chance of errors ensuring a more consistent and professional layout.

      ANAND RAJAGOPAL: Thank you, Anum. We just saw the Smart Blocks placement engine learn on the go as Riley continued her work within AutoCAD. It inferred the optimal placement, the scale, the rotation for the new instances. And this was based on how the previous blocks have been placed, or could have been-- it provides some smart suggestions Riley, based on what she's looking to do. It could automatically recommend a rotation or multiple placement of something in the right spot and the right place.

      And like Anum said, this helped to go much faster on the overall lighting plan. It helped to ensure a more consistent layout, consistent design, and help reduce the chance of errors. Riley still makes all the decisions, but she's just got a smart tool in her pocket to help her go faster. With that, let's move on to our last Smart Blocks workflow.

      ANUM MITHANI: Awesome. So Riley's now got a lot of her lighting plan done, but she needs to fine tune. She identifies some hallway lights that need to be replaced with a different type of light symbol. Instead of deleting the blocks she's already placed and inserting the correct light symbol, she knows she can leverage Smart Block's replacement.

      She selects all the instances of the hallway lights that she wants to replace and types in the BREPLACE command. AutoCAD suggests similar blocks for her to choose from. She can also replace the selected blocks with another block she specifies, either from a drawing or from a list of recently inserted or created blocks.

      The beauty of this feature is that the replaced block retains the scale, rotation, and attribute values of the original block. She selects the correct block from the suggested block list, and instantly all of the hallway lights are replaced with the new symbol. This seamless replacement process saves Riley a significant amount of time and effort, ensuring that consistency and precision that she needs in her drawing.

      Her drawing's now much more polished and refined, thanks to the powerful features of Smart Block Search and Convert, Detection, Placement, and Replacement. The ability to quickly replace blocks without losing their properties has made her job so much easier.

      ANAND RAJAGOPAL: Thank you. So we saw the Smart Block Replacement workflow and the BREPLACE workflow-- or the BREPLACE command, sorry. This used to determine good replacement candidates for the given blocks, and this was based on the blocks present in Riley's local library. So it works great with what you already have. It just needs you. It just understands what is a good replacement, either based on prior use, based on how it's defined, or just what it represents.

      It still retains the same scale, the rotation attribute values of the original blocks. This ensured that Riley could update the plan seamlessly, without the need of any further adjustments. Yeah. And I think with that, we've seen a whole host of Smart Blocks workflows, but we've got actually one more AI-based workflow that we want to show you. Back to Anum.

      ANUM MITHANI: OK. So now we know the lighting design is complete, Riley emails a PDF of the drawing to her manager for review. Her manager is pretty old school, so she's printed out her PDF and made handwritten markups, leaving the paper copy on Riley's desk.

      Typically, Riley would have to keep moving her eyes from her desk to her screen, trying to find all of the places where edits need to be made and keeping track of which ones she's already incorporated as she works through the list. But Riley knows about Markup Import and Assist, which can make this process much smoother. She takes a photo of the markup, drawing on her phone and saves it to her computer.

      Then she heads to the Collaborate tab in the ribbon and clicks on Markup Import. Riley selects the photo from her files to import the markup image. Markup Import overlays a markup file on top of the drawing in the Trace workspace. Imported markups are automatically aligned with the existing drawing. Sometimes, the markups don't align perfectly and require manual adjustments. Riley can move, align, rotate, or scale the markup if needed.

      Once the markup is properly aligned, Riley switches to the Drawing workspace. Here, Markup Assist comes into play by identifying text in the imported markup and highlighting it with blue boxes. She begins by editing the lighting notes. By clicking on the blue box around her manager's handwritten addition, Markup Assist converts a handwritten message in a text. Riley can then easily append this addition into her notes.

      Markup Assist can also identify strikethroughs. Riley uses this feature to erase existing text and replace it with the corrected markup, ensuring that her drawing reflects the latest updates from her manager. She can also insert new text directly from the markup by selecting it and inserting it as an MText. This is incredibly useful for adding new notes and annotations.

      Next, we'll see that Markup Assist can also interpret instructional texts. When Riley clicks on the blue box around the Remove Markup, it triggers the Erase command, allowing her to remove specified objects. Once she completes the task, she can fade the markup, indicating that the instruction has been addressed.

      Similarly, when Riley clicks on the Move Markup-- oh, wait. She's still fading markups. Awesome. Similarly, when Riley clicks on the Move Markup, the Move command is triggered, enabling her to select and relocate objects as directed. This automation saves her a significant amount of time and ensures precision in following her manager's instructions. Again, we see here fading the markup once it's been addressed.

      Riley can also insert text as MLeader with Markup Assist. She clicks on the markup, and, if needed, she edits the text. Sometimes, her manager's notes can be a little bit messy. She then selects Insert as MLeader and places it precisely where it's required. She then fades the arrow markup and displays the Mleader arrow behind.

      With these tools at her disposal, Riley quickly incorporates all of her managers mark ups. She's efficiently handled the addition of new text, removal of objects, and relocation of elements, all with the help of Markup Import and Assist. Now she's ready to send the updated drawing back to the architect.

      She reflects on how much time she saved using Markup Import and Assist, along with all of the Smart Blocks features. These tools have not only made her workflow more efficient, but again, has ensured that her drawing is accurate and professional. She feels confident and prepared that if any future revisions or updates come in, she has the right tools to handle them with ease. With these advanced features, she can continue to work smarter and not harder to achieve her design goals more efficiently.

      ANAND RAJAGOPAL: Thank you, Anum. We saw Riley use Markup Import and Assist, two commands to streamline the process of incorporating feedback. Riley used Import to conveniently overlay the photo and the information in that photo on top of a drawing in the Trace workspace.

      Once this data is in Trace, this is when Markup Assist kicks off. It helps-- it smartly helped her make the changes needed. It identified and highlighted the handwritten text on the photograph, used OCR, or optical character recognition, to quickly convert that under the hood into text, which the computer can then work with, or edit.

      The comments are now ready in the clipboard. They can be quickly incorporated into either MLead or MText. Everything is just with one click.

      It can go further. It can understand the intent of some of this feedback and helpfully trigger the right workflows. We saw examples of Remove. We saw examples of Move, or Erase. It can even identify which objects need to move. This whole process augments her current collaboration process and makes every iteration go a little bit faster.

      Thank you. With this, we finished showing you four different workflows. Now Anum is going to walk you through how you can actually access these features today and where they're available. Back to you, Anum.

      ANUM MITHANI: OK. So now that you've seen Riley's workflow, we hope that you guys are ready to enhance your own workflows. Let's dive right in on how to access these powerful features, explore detailed tutorials, and share your feedback to help us improve.

      All of the awesome Autodesk AI features within AutoCAD that we've talked about today are ready for you to use in our latest release, AutoCAD 2025. You can also find a subset of these features in earlier releases, namely AutoCAD 2023 and 2024. Some of these features, Placement and Search and Convert, are also available in AutoCAD LT.

      To get the most of these amazing features, here are some helpful tips. First, you can learn more. You can always visit help.autodesk.com to dive deeper into these features and their applications. You can also access help articles by clicking on the Learn More link within the product to find detailed information about specific features as you encounter them.

      And we also have Autodesk Assistant right within the product to help answer any of your questions. This chat bot will provide you AI-recommended solutions for your inquiries and connect you with an agent, if it's needed.

      Provide feedback. Help us make detection even better. Click on the Provide Feedback in the Detection palette. This will direct you to a survey where you can share your valuable input.

      And finally, report errors. If you encounter any issues, you can report errors in the Detection Review visor. This tool displays a list of potential errors within the current set of detected objects. Reporting these errors contributes to our ongoing improvement of the machine learning service's performance and accuracy.

      It's a collaborative effort to refine the AI, ensuring it becomes even more accurate and helpful in the future. While you may not see that the results are perfect all the time, you have the control and the tools that you need to make it work best for you. By leveraging these resources, you can enhance your experience within AutoCAD and help us improve our AI features. There's also additional classes at AU that you can visit to learn more about these features.

      Thank you for joining us today and exploring how Autodesk AI features can transform your workflow, saving you time and enhancing your design process. We'd also like to share an opportunity to connect with the AutoCAD team and have a say on our next releases. Scan the QR code to learn more about our inside the factory event. Thank you.

      ANAND RAJAGOPAL: Thank you.

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      我们通过 Dynatrace 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Dynatrace 隐私政策
      Khoros
      我们通过 Khoros 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Khoros 隐私政策
      Launch Darkly
      我们通过 Launch Darkly 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Launch Darkly 隐私政策
      New Relic
      我们通过 New Relic 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. New Relic 隐私政策
      Salesforce Live Agent
      我们通过 Salesforce Live Agent 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Salesforce Live Agent 隐私政策
      Wistia
      我们通过 Wistia 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Wistia 隐私政策
      Tealium
      我们通过 Tealium 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Tealium 隐私政策
      Upsellit
      我们通过 Upsellit 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Upsellit 隐私政策
      CJ Affiliates
      我们通过 CJ Affiliates 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. CJ Affiliates 隐私政策
      Commission Factory
      我们通过 Commission Factory 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Commission Factory 隐私政策
      Google Analytics (Strictly Necessary)
      我们通过 Google Analytics (Strictly Necessary) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Strictly Necessary) 隐私政策
      Typepad Stats
      我们通过 Typepad Stats 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Typepad Stats 隐私政策
      Geo Targetly
      我们使用 Geo Targetly 将网站访问者引导至最合适的网页并/或根据他们的位置提供量身定制的内容。 Geo Targetly 使用网站访问者的 IP 地址确定访问者设备的大致位置。 这有助于确保访问者以其(最有可能的)本地语言浏览内容。Geo Targetly 隐私政策
      SpeedCurve
      我们使用 SpeedCurve 来监控和衡量您的网站体验的性能,具体因素为网页加载时间以及后续元素(如图像、脚本和文本)的响应能力。SpeedCurve 隐私政策
      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

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      改善您的体验 – 使我们能够为您展示与您相关的内容

      Google Optimize
      我们通过 Google Optimize 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Google Optimize 隐私政策
      ClickTale
      我们通过 ClickTale 更好地了解您可能会在站点的哪些方面遇到困难。我们通过会话记录来帮助了解您与站点的交互方式,包括页面上的各种元素。将隐藏可能会识别个人身份的信息,而不会收集此信息。. ClickTale 隐私政策
      OneSignal
      我们通过 OneSignal 在 OneSignal 提供支持的站点上投放数字广告。根据 OneSignal 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 OneSignal 收集的与您相关的数据相整合。我们利用发送给 OneSignal 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. OneSignal 隐私政策
      Optimizely
      我们通过 Optimizely 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Optimizely 隐私政策
      Amplitude
      我们通过 Amplitude 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Amplitude 隐私政策
      Snowplow
      我们通过 Snowplow 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Snowplow 隐私政策
      UserVoice
      我们通过 UserVoice 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. UserVoice 隐私政策
      Clearbit
      Clearbit 允许实时数据扩充,为客户提供个性化且相关的体验。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。Clearbit 隐私政策
      YouTube
      YouTube 是一个视频共享平台,允许用户在我们的网站上查看和共享嵌入视频。YouTube 提供关于视频性能的观看指标。 YouTube 隐私政策

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      定制您的广告 – 允许我们为您提供针对性的广告

      Adobe Analytics
      我们通过 Adobe Analytics 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Adobe Analytics 隐私政策
      Google Analytics (Web Analytics)
      我们通过 Google Analytics (Web Analytics) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Web Analytics) 隐私政策
      AdWords
      我们通过 AdWords 在 AdWords 提供支持的站点上投放数字广告。根据 AdWords 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AdWords 收集的与您相关的数据相整合。我们利用发送给 AdWords 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AdWords 隐私政策
      Marketo
      我们通过 Marketo 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。我们可能会将此数据与从其他信息源收集的数据相整合,以根据高级分析处理方法向您提供改进的销售体验或客户服务体验以及更相关的内容。. Marketo 隐私政策
      Doubleclick
      我们通过 Doubleclick 在 Doubleclick 提供支持的站点上投放数字广告。根据 Doubleclick 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Doubleclick 收集的与您相关的数据相整合。我们利用发送给 Doubleclick 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Doubleclick 隐私政策
      HubSpot
      我们通过 HubSpot 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。. HubSpot 隐私政策
      Twitter
      我们通过 Twitter 在 Twitter 提供支持的站点上投放数字广告。根据 Twitter 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Twitter 收集的与您相关的数据相整合。我们利用发送给 Twitter 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Twitter 隐私政策
      Facebook
      我们通过 Facebook 在 Facebook 提供支持的站点上投放数字广告。根据 Facebook 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Facebook 收集的与您相关的数据相整合。我们利用发送给 Facebook 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Facebook 隐私政策
      LinkedIn
      我们通过 LinkedIn 在 LinkedIn 提供支持的站点上投放数字广告。根据 LinkedIn 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 LinkedIn 收集的与您相关的数据相整合。我们利用发送给 LinkedIn 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. LinkedIn 隐私政策
      Yahoo! Japan
      我们通过 Yahoo! Japan 在 Yahoo! Japan 提供支持的站点上投放数字广告。根据 Yahoo! Japan 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Yahoo! Japan 收集的与您相关的数据相整合。我们利用发送给 Yahoo! Japan 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Yahoo! Japan 隐私政策
      Naver
      我们通过 Naver 在 Naver 提供支持的站点上投放数字广告。根据 Naver 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Naver 收集的与您相关的数据相整合。我们利用发送给 Naver 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Naver 隐私政策
      Quantcast
      我们通过 Quantcast 在 Quantcast 提供支持的站点上投放数字广告。根据 Quantcast 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Quantcast 收集的与您相关的数据相整合。我们利用发送给 Quantcast 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Quantcast 隐私政策
      Call Tracking
      我们通过 Call Tracking 为推广活动提供专属的电话号码。从而,使您可以更快地联系我们的支持人员并帮助我们更精确地评估我们的表现。我们可能会通过提供的电话号码收集与您在站点中的活动相关的数据。. Call Tracking 隐私政策
      Wunderkind
      我们通过 Wunderkind 在 Wunderkind 提供支持的站点上投放数字广告。根据 Wunderkind 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Wunderkind 收集的与您相关的数据相整合。我们利用发送给 Wunderkind 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Wunderkind 隐私政策
      ADC Media
      我们通过 ADC Media 在 ADC Media 提供支持的站点上投放数字广告。根据 ADC Media 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 ADC Media 收集的与您相关的数据相整合。我们利用发送给 ADC Media 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. ADC Media 隐私政策
      AgrantSEM
      我们通过 AgrantSEM 在 AgrantSEM 提供支持的站点上投放数字广告。根据 AgrantSEM 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AgrantSEM 收集的与您相关的数据相整合。我们利用发送给 AgrantSEM 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AgrantSEM 隐私政策
      Bidtellect
      我们通过 Bidtellect 在 Bidtellect 提供支持的站点上投放数字广告。根据 Bidtellect 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bidtellect 收集的与您相关的数据相整合。我们利用发送给 Bidtellect 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bidtellect 隐私政策
      Bing
      我们通过 Bing 在 Bing 提供支持的站点上投放数字广告。根据 Bing 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bing 收集的与您相关的数据相整合。我们利用发送给 Bing 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bing 隐私政策
      G2Crowd
      我们通过 G2Crowd 在 G2Crowd 提供支持的站点上投放数字广告。根据 G2Crowd 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 G2Crowd 收集的与您相关的数据相整合。我们利用发送给 G2Crowd 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. G2Crowd 隐私政策
      NMPI Display
      我们通过 NMPI Display 在 NMPI Display 提供支持的站点上投放数字广告。根据 NMPI Display 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 NMPI Display 收集的与您相关的数据相整合。我们利用发送给 NMPI Display 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. NMPI Display 隐私政策
      VK
      我们通过 VK 在 VK 提供支持的站点上投放数字广告。根据 VK 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 VK 收集的与您相关的数据相整合。我们利用发送给 VK 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. VK 隐私政策
      Adobe Target
      我们通过 Adobe Target 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Adobe Target 隐私政策
      Google Analytics (Advertising)
      我们通过 Google Analytics (Advertising) 在 Google Analytics (Advertising) 提供支持的站点上投放数字广告。根据 Google Analytics (Advertising) 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Google Analytics (Advertising) 收集的与您相关的数据相整合。我们利用发送给 Google Analytics (Advertising) 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Google Analytics (Advertising) 隐私政策
      Trendkite
      我们通过 Trendkite 在 Trendkite 提供支持的站点上投放数字广告。根据 Trendkite 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Trendkite 收集的与您相关的数据相整合。我们利用发送给 Trendkite 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Trendkite 隐私政策
      Hotjar
      我们通过 Hotjar 在 Hotjar 提供支持的站点上投放数字广告。根据 Hotjar 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Hotjar 收集的与您相关的数据相整合。我们利用发送给 Hotjar 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Hotjar 隐私政策
      6 Sense
      我们通过 6 Sense 在 6 Sense 提供支持的站点上投放数字广告。根据 6 Sense 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 6 Sense 收集的与您相关的数据相整合。我们利用发送给 6 Sense 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. 6 Sense 隐私政策
      Terminus
      我们通过 Terminus 在 Terminus 提供支持的站点上投放数字广告。根据 Terminus 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Terminus 收集的与您相关的数据相整合。我们利用发送给 Terminus 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Terminus 隐私政策
      StackAdapt
      我们通过 StackAdapt 在 StackAdapt 提供支持的站点上投放数字广告。根据 StackAdapt 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 StackAdapt 收集的与您相关的数据相整合。我们利用发送给 StackAdapt 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. StackAdapt 隐私政策
      The Trade Desk
      我们通过 The Trade Desk 在 The Trade Desk 提供支持的站点上投放数字广告。根据 The Trade Desk 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 The Trade Desk 收集的与您相关的数据相整合。我们利用发送给 The Trade Desk 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. The Trade Desk 隐私政策
      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

      是否确定要简化联机体验?

      我们希望您能够从我们这里获得良好体验。对于上一屏幕中的类别,如果选择“是”,我们将收集并使用您的数据以自定义您的体验并为您构建更好的应用程序。您可以访问我们的“隐私声明”,根据需要更改您的设置。

      个性化您的体验,选择由您来做。

      我们重视隐私权。我们收集的数据可以帮助我们了解您对我们产品的使用情况、您可能感兴趣的信息以及我们可以在哪些方面做出改善以使您与 Autodesk 的沟通更为顺畅。

      我们是否可以收集并使用您的数据,从而为您打造个性化的体验?

      通过管理您在此站点的隐私设置来了解个性化体验的好处,或访问我们的隐私声明详细了解您的可用选项。