Tech briefing: generative design Supply Management

Sohi now works with companies in manufacturing and design, connecting those innovating in the design sphere with tools that could help them do. Autodesk is well known for its computer aided design and digital prototyping software, putting it at forefront of design technology. There is no doubt that the world of manufacturing and design has been transformed over the past decade, with the technological advances of industry 4.0 changing the way in which products are conceptualised, produced and delivered to consumers. The above site study has been generated by Spacemaker using user inputs for building size (height, width, minimum building margin), specified layout formations and number of stories. The user can select any of these studies as the basis for a design moving forward and use Spacemakers analysis capabilities to further optimise the site.

An array of these structures are generated leaving the user with tools to select their favourite iteration. Not only will this help streamline the design process, but Sohi believes that it is fast becoming necessary to re-think manufacturing to reflect the growing need to produce more with less. “My role at Autodesk for the last five years has been primarily focused on developing partnerships with companies who are doing really interesting manufacturing and design challenges and helping them deliver on those challenges,” he explains.

Open software for AM

In recent years, generative AI has emerged as a revolutionary technology in the eLearning industry due to its ability to enhance the learning experience for students. As an instructional designer, incorporating generative AI into your content creation can offer numerous benefits such as personalized learning, streamlined course planning, and improved engagement. Because these data sets are scraped wholesale from the web, they inevitably include all kinds of offensive, degrading and discriminatory content. In order to ensure that this content does not influence the outputs of generative AI tools and damage their commercial potential, these data sets must be filtered and moderated.

The cost of developing generative design software will depend on the technology stack used for the software. In the aerospace industry, generative design is used to create lighter and more efficient aircraft parts. Airbus, for example, used generative design to create a partition wall for the A320 aircraft that was 45% lighter than previous ones. The new variant also improved noise reduction and thermal insulation, providing a more comfortable experience for passengers. AI is an interdisciplinary field that encompasses elements of computer science, mathematics, psychology, and engineering.

design resources

Nor do we think that the future of robotics in construction is in building robots to do jobs that we, or they, shouldn’t be doing in the first place. You need to assess the entire process and engage actively with technology to see where – or whether – it will add value. You also have to be open to the very real possibility that its use may fundamentally alter that process for the better.As an industry, we have to get better at creating and sharing data, information and learning. We have the computing and processing infrastructure to do amazing things with data in the built environment sector, but we have to create it, share it – and use it. In Part 1 of this two-part blog, we explored how generative design allows engineers to produce increasingly excellent work, meeting—or surpassing—expectations in less time.

When this can be communicated with data, processes and instructions that a machine can understand, it can come up with many different solutions that vastly exceed the parameters of traditional design optimisation. AI-powered design tools can automate repetitive and time-consuming tasks, such as resizing images, generating color palettes, or creating layout templates. genrative ai These tools allow designers to focus more on the creative aspects of their work and save significant time. While AI offers immense potential, it is crucial to consider the ethical implications of its use in graphic design. Designers must be mindful of biases embedded within AI algorithms and ensure that designs promote inclusivity, diversity, and fairness.

A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

Autodesk Generative Design is a cloud-based tool that works by using advanced algorithms to create designs based on input parameters and constraints. It integrates with other Autodesk tools, such as Fusion 360 and AutoCAD, to support the entire design process. Generative design can help reduce material waste by optimizing designs to use less material while still meeting the required performance criteria.

Because AI tools are not smart enough to filter out this content automatically, the majority of content moderation is done by humans, often from the global majority, working under exploitative and extractive conditions. In May, content moderators in Africa who provide services for Meta, Open AI and others voted to establish the first African Content Moderators Union, to challenge low pay and exploitative working conditions in the industry. Part of our endeavour is to bring together all sorts of discrete technologies and products, whose aim is to solve discrete problems.

Fusion 360 Generative Design Extension features

At the end of 2022, OpenAI realised the most profound example of “product-market-fit” in tech history; when Chat GPT gained 100m users in just four weeks. While generative design can produce highly optimized projects, it may lack the human creativity and intuition that can lead to truly innovative ideas. This means that human input and creativity are still important for creating unique and groundbreaking designs. Generative design algorithms can be very complex, and understanding how they work can be difficult. This can make it challenging for designers to use the tools properly and may require specialized training. Once you have developed your software, it’s important to test it thoroughly to ensure that it is functioning correctly and generating optimized designs.

By feeding AI algorithms with specific design parameters, designers can generate a multitude of design options. This process encourages exploration and experimentation, pushing the boundaries of what is possible. Generative design allows designers to discover innovative solutions that may have otherwise remained unexplored. Designers can leverage AI tools that provide intelligent suggestions and recommendations during the design process. These tools analyze data, user behaviour, and design patterns to offer insights and improve the overall quality of designs. By combining the creativity of designers with the analytical capabilities of AI, the result is a powerful collaboration that leads to innovative and impactful designs.

Reach Net Zero faster by reducing weigth, boosting thermal efficiency, and increasing product lifespan – minimising your power usage and helping you become more sustainable. The introduction of new technologies is usually followed by a belated exploitation of their potential. The new opportunities are often constrained by an inherent lack of technical knowledge.

AI algorithms could generate procedurally generated worlds, characters, and quests, offering players unique and personalised gaming experiences. This approach reduces the reliance on scripted scenarios and challenges, making games more dynamic and replayable. Transparency, consent, and data protection should be key guiding principles in the development and deployment of the future of generative AI within the metaverse. Iain Brown PhD, Head of Data Science for SAS, Northern Europe, explores recent developments in AI and delves into the potential promises, pitfalls, and concerns around bias surrounding the future of generative AI.

• These activities not only engage learners but also facilitate their understanding of the content.
• The company wanted the trainer to be comfortable, durable, lightweight and supportive.
• As with many other innovations, its success depends not on the technology itself, but on the way we implement it.
• By analysing data inputs, such as artistic preferences, previous interactions, and contextual information, the system generates customised art pieces, exhibitions, and recommendations.
• Their advanced 3D printing techniques enable precision-driven, complex designs, while fostering growth and pushing the boundaries of additive manufacturing possibilities.

With its ability to explore thousands of solutions, generative design affects far more than the just the design stage. But, thanks to cloud technologies and advances in simulation, 3D printing and machine learning, the concept of generative design in product development is finding broader applications. And with that, it is now time to think about the future role of the product developer. Designers could already leverage publicly genrative ai available text-to-image generative artificial intelligence tools as an early step in the creative process. With TRI’s new tool, initial design sketches and engineering constraints can be added into this process, cutting down the iterations needed to reconcile design and engineering considerations. Text-based generative AI is already pretty impressive, particularly for research, creating first drafts, and planning.