Using generative AI in Collaborative Design Work to Boost Inspiration and Communication

At this point, it is important to review the difference between generative design and other technologies such as topology optimisation, grid optimisation or the like, which are often listed under one name. Simply put, generative design means humans and computers working together to create objects beyond human imagination. This application comes with a vast array of tools for design, exploration and analysis which will be explored in greater depth in future blog posts. Even after the initial designs have been produced by SiteSolve, architects and developers can provide the human element and customise them to a specific brief or site, respecting the cultural context, aesthetic appeal and the local community. We’ve seen customers that have specific targets for their project, e.g. whether the main target of the scheme is maximising south-facing apartments, maximising net area or efficiency, or a combination of criteria.

This has the potential to minimise the number of components in a product, as well as enhancing component performance. The user creates basic CAD blocks for areas which must be included or excluded in the design, such as boss features. Hypothesising that the bolt structure of the engine block would put too much stress on the engine mount over time, he used generative design to develop a new bolt configuration that would be more structurally sound. He also sees potential in emerging technologies within the additive manufacturing space. “For example, generative design as a technology at Autodesk is only just over a year old now. And understandably, with anything that’s new tech like that, and the geometries that they see it produce, there’s a natural anxiety to assume that this is out of the question for me or there’s no way that I can use it at my company.

Enhance Design Cycle Productivity

Generative design uses artificial intelligence (AI) and machine learning to design parts that can be manufactured to be absolutely optimal for their intended use. For an aircraft or a car, for example, this might be a component that is both lighter and stronger, leading to increased fuel efficiency and lower CO2 emissions. This study is the first known application of Generative Design to a biomedical implantable device. An advanced design technique, used to develop components for aerospace and automotive industries, has been harnessed in the production of bespoke medical devices. Since 2016, GM has launched 14 new vehicle models with a total mass reduction of more than 5,000 pounds., or more than 350 pounds per vehicle. Of those models, more than half of the vehicles shed 300 pounds or more including the all-new 2019 Chevrolet Silverado, which reduced mass by up to 450 pounds.

Topology optimisation returns only one optimised concept for evaluation based on the human-designed model. Lastly, it returns to the user an optimised mesh design result that must be rebuilt in a CAD system that is intended for downstream use. There are different types of AI, including narrow or weak AI, which is designed to perform specific tasks, and strong AI, which has the capability of performing any intellectual task. Some of the most common applications of AI include voice recognition, autonomous vehicles, virtual personal assistants, and image recognition. Crafting effective prompts is crucial for successful communication with generative AI. Well-crafted prompts should be clear, concise, and unambiguous, to ensure that the AI understands the user’s intent accurately.

Faster Design Iteration

The AI system then uses computer-aided design (CAD) software to build the part per the pre-established specifications. Kirsh is part of a conversation between researchers from across The Bartlett – including Robert Aish, Sean Hanna and Abel Maciel – who are collaborating on an inquiry into what they see as the newly-energised promise of generative design. The term “Artificial genrative ai Intelligence” (AI) was coined as long ago as the 1950s, and, while certain disciplines have already put it into practice, recent developments mean it could soon have a significant impact on designers of 3D environments. By striking this balance, we can harness the true potential of future generative AI while building a more equitable and responsible digital landscape for all.

The development time required to create generative design software will impact the cost. More complex and sophisticated software will take longer to develop and test, which will increase the cost. It provides topology optimization and other advanced simulation capabilities that help designers to develop more efficient and productive designs. ANSYS Discovery Live is a simulation software that supports real-time, interactive generative design. It uses physics-based simulations to build and evaluate multiple prototype options in real-time, allowing designers to quickly explore and change their designs. At this point, AI is best seen as a tool that can assist designers, rather than replace them.

New ideas can also be explored by pushing boundaries in a safe, cost-effective, and risk-free way – letting you see if an idea works well before any spades are put into the ground. Artificial intelligence is taking the world by storm, with almost every industry seeing new tools being created seemingly overnight. The aerospace sector is among the most highly regulated industries, with components having significantly smaller tolerances for error due to the extreme applications in which they are typically employed. With a few modifications, commercial-grade AI tools might be capable of creating components for crucial space missions. The hackathon’s goal was to explore the way designers change their approach when working with different tools.

• Mr Iorio says that generative design starts from the basis of design intent (i.e. what a part or design has to achieve) but can then generate many alternatives to come up with the desired outcome.
• Designers can input criteria such as brand guidelines, target audience, or design objectives, and AI algorithms can generate multiple design concepts or compositions to choose from, helping designers explore different possibilities efficiently.
• Executives and engineers from the two companies will participate in a series of onsite engagements to exchange ideas, learnings, and expertise.
• The productivity of the product development department in the design phase can increase immensely, as well as the gain in creativity and innovation if more time can be invested in researching conceptual designs.

With a great professional team and years of experience behind us, we are full of enthusiasm to assist and consult you throughout the entire process of generative design software development and beyond. When carefully planning each step, Magora is ready to predict and prevent a tiny error. Based on these factors, the cost of creating generative design software can range from tens of thousands of dollars to millions of dollars. The cost will depend on the specific needs of the project and the level of sophistication required for the software. It’s important to work with a skilled development team  and carefully evaluate the requirements of the project to accurately estimate the cost of development.

This can lead to more informed and effective design decisions that are made quicker and easier. While SiteSolve has been a great tool for many, we understand generative AI is not for everyone. Looking more generally, I’ve drawn up pros and cons to help you decide on whether to take the AI plunge. By analysing data inputs, such as artistic preferences, previous interactions, and contextual information, the system generates customised art pieces, exhibitions, and recommendations. This level of tailoring ensures that fans feel a sense of ownership and emotional resonance with the art, leading to a more profound and memorable experience.

The new tool has the potential to reduce the number of iterations needed to reconcile design and engineering considerations. For example, by gaining an early insight into how to reduce the drag generated by a new design, aerodynamics can be optimised – a key factor in maximising the driving range potential of battery electric vehicles. These legislations aim to introduce transparency and traceability into fashion supply chains. By definition, when this is completed, the supply chains will generate a massive volume of data – the precise requirement for effective machine learning (ML) and subsequent Generative AI.

Unleashing Creativity with AI: Adobe’s Trailblazing Generative Tools at EMEA Summit 2023

We look forward to testing it further when it’s no longer in beta, so make sure to check back for our findings. It enables you to create unique content specific graphics that are not available on stock image sites and/or would require organizing a photoshoot or advanced design expertise. Key features include content-aware image generation in Photoshop, the ability to generate custom vectors, brushes and textures for illustrations and the option to change the mood, atmosphere and weather in videos. As a trusted partner to individuals and businesses of all sizes, Adobe develops and deploys all AI capabilities with a customer-centric approach and according to its AI Ethics principles, ensuring content and data transparency. Content Credentials provide “nutrition labels” for digital content and are a key pillar of Adobe’s AI principles.

Adobe trains its AI on Adobe Stock images, which is licensed to and isn’t available elsewhere on the internet. This means you will not be bothered by takedown notices from other copyright holders when using images generated with Adobe Firefly. When you enter the prompt and hit generate, Adobe Firefly will generate four images based on the prompt, and you can download all those images. But there are literally 1,000s of others you can get to grips with in your own time. There is also a wide selection to help you at work or find work from writing CV’s to creating great subject lines. Strategy – When creating an AR experience, consider the narrative and navigation.

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It’s very intuitive but also well designed so that users can create professional looking finished projects in a variety of areas. The AI will automatically match perspective, lighting and style to the pre-existing image, meaning you can spend less time faffing with lighting angles and more time being creative. In the image above, we even see that work in reverse – the sun wasn’t in the original shot, but the conditions elsewhere helped the AI to place it correctly.

• Let’s look at the incredible new AI feature, its creative benefits, and potential drawbacks below.
• This feature is currently under construction and isn’t available to try right now.
• Recent research unveiled by Adobe at the summit finds that particularly among the younger generation, expectations of a great experience from businesses only goes up during tough economic times.
• Adobe also noted that only users who are 18 years old and above may access the new feature and that it will only be permitted for non-commercial use while in its beta stage.
• AutoPod’s Multi-Camera Editor simplifies the handling of multiple camera angles and microphones, allowing for seamless transitions between shots.
• We also recognize and respect artists’ ownership and intellectual property rights.

Since its launch in March 2023, Firefly has become one of Adobe’s most successful beta releases with users generating over 100 million assets. It has expanded to support vector recoloring and generative fill, offering professional-quality content that is commercially viable. Firefly’s first model is trained on Adobe Stock images openly licensed content, and other public domain content without copyright restrictions. This allows enterprises to incorporate their own creative collateral, including images, vectors, and brand language, making Firefly a seamlessly integrated part of their workflows. Integrating Firefly across Adobe Experience Cloud applications further enhances marketing organizations’ content supply chain production.

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Given that the technology is still new and being developed, it also has its limitations such as only being able to support prompts from the English language. Adobe also noted that only users who are 18 years old and above may access the new feature and that it will only be permitted for non-commercial use while in its beta stage. At the same time, Adobe announces that users have generated over 150 million images using the new Generative Fill feature, which was released for the beta version of Photoshop about three weeks ago.

Founder of the DevEducation project

In this blog, we look at Adobe’s creative generative AI tool Firefly, its recently added Generative Fill functionality and how all this can be used in a practical setting within education. Have you ever wondered if you could change the type of shirt genrative ai you wear in a picture to something else with basic prompts? Or make you wear a hat in a picture where you’re wearing none by typing a few words? It sounds like magic, but it’s not; it’s called Generative Fill and is available in Adobe Firefly.

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Adobe is also making some of these capabilities available to Firefly beta users on the web (Firefly users, by the way, have now created more than 100 million images on the service). The clearer and more specific your directive, the more accurately the AI can interpret your dreams and wishes. AI uses your prompt to traverse its vast expanse of “knowledge”—Firefly is trained on a dataset of Adobe Stock images, along with openly licensed work and public domain content where copyright has expired. Once I’ve downloaded my AI-generated image I place it in the background of my shot and blur it to create a shallow depth-of-field effect.

It is not yet available for commercial use, and currently supports English-only text prompts. While the conversation regarding AI stealing from artists has been large and controversial, the new advance by Adobe has expanded the possibilities of AI being used as an artistic tool. This feature allows graphic designers, photo editors, and artists alike to make their visions a reality and to better create exactly what they desire. Adobe also claims to be open about the datasets being used to train its AI models.

For Text to Image Generation feature, images of people are not being generated clearly.People are getting distorted. AI needs more training here to understand the prompts better while generating images with people in it. The AI image generator is unique because genrative ai it’s trained on Adobe licensed stock, so potentially, people can use the images for commercial purposes without the risk of copyright infringement. Let’s look at the incredible new AI feature, its creative benefits, and potential drawbacks below.