Initiated by ChatGPT, the AIGC (Artificial Intelligence Generated Content) wave of excitement extends beyond the realm of text, code, and illustration picture generation. Just as the introduction of steam engines boosted industrial output, so too will the advent of the AIGC.
In 2018, PIX Moving began a journey of research and development in industrial design AIGC in Silicon Valley, USA. Soon after, the industrial software giant Autodesk invited PIX Moving to its Autodesk Technology Innovation Center for incubation in 2019 because of algorithmic innovations in Generative design.
PIX Moving’s first Ultra Skateboard Chassis and self-driving cars were both developed in collaboration with Autodesk and the local communities of San Francisco, Boston, and Toronto using Generative AI.
PIX Moving in Autodesk, SF
A self-riding concept car of the Ultra Skateboard follows shortly thereafter. It debuted at a show in Montreal, Canada, and later made an appearance at the Movin’On 2019 Summit by invitation.
“Using generative design to change the way cars are designed and made now is the riskiest challenge. But this process will bring new knowledge and opportunities to manufacturing. It could also be the glory and dream of PIX Moving’s decision, three years ago, to join the Autodesk Technology Innovation Center.”
Yu Chuan, the founder, and CEO of PIX Moving told Silicon Valley Labs in the United States.
AI-generated text and art, on the other hand, are “based on rich data and resources,” making them challenging for industrial fields to compare and reach.
Accordingly, PIX proposes a strategy for meeting the manufacturing needs of industrial scenarios by employing large-scale models to generate approximate designs through the learning of massive amounts of vehicle data and then employing algorithms to optimize these designs into accurate engineering documents.
PIX Moving’s AIGC build-AAM (Automotive Algorithm Modeling)™was released to the public in 2020, and it offers engineers and designers a brand new AI-driven workflow across all aspects of their work, from design to digital processes, collaboration, and engineering management.
AAM™ (Autonomous Algorithm Modeling) platform
AAM™ is a generative design platform that integrates algorithmic design, simulation, and manufacturing to increase the efficiency of parts design by 60% and the efficiency of lightweight design by up to 20% when compared to the efficiency of sophisticated engineers.
On the other hand, the AAM™ platform is accessible via the web, which makes it ideal for collaborative online design and engineering version management involving multiple users.
“What really excites me is that throughout the entire manufacturing process, from styling sketches to first-model manufacturing, PIX’s AAM™ platform can make multiplied improvements in efficiency over traditional manufacturing processes in the automotive, mechanical, and even aerospace industries.”
Stephen, Director of PIX AAM™
It only takes a few minutes for AAM™ to generate dozens of options for engineers to choose from, according to Stephen Chen, director of PIX AAM™. Whenever there is a need for adjustment, a new boundary condition can be set. If the change can be made in a few minutes like this, it will be a major subversion in modern industrialization.
Dr. Cui from the PIX Innovation R&D Center explains that “AAM™ automatically generates 3D models with quantitative geometric constraints, dynamical constraints, kinematic constraints, process constraints, structural optimization, etc. They are all game-changing for enhancing the productivity of product development.”
Dr. Cui, head of PIX Innovation and R&D Center
Data-driven and methodical approaches to vehicle design are possible in AAM™. Vehicle design and manufacturing processes, such as geometric constraints, manufacturing constraints, structural optimization, and so on, are abstracted into rules and data and stored in algorithm engines
By adjusting system parameters, the CAD model, manufacturing and process files, and costs of the vehicle can be generated instantly. Therefore, engineers and designers can instantly assess the design’s merits in terms of accuracy, cost, timeliness, etc., leading to enhanced precision and productivity in the manufacturing of customized products.
Here is a flow chart of how AAM™ works from design to production:
With the “User-Assembly” Loop opened by AAM™, the efficiency of conventional car design processes was multiplied by a factor of 10, while the efficiency of the manual design was multiplied by a factor of 50 to 100, and both were improved in terms of precision and reliability.
Skateboard Chassis, Moving Space, and the PIX Moving NEV (Personal Mobile Space) are all products that have been developed by PIX Moving and are based on AAM™.
PIX Autonomous driving skateboard chassis
PIX Moving Space at Gitex, Dubai
Moving office space interiors designed on AAM™ platform
PIX NEV
Fulongma Group Co.,ltd., a PIX strategic partner, has also created autonomous sweeping robots for use with the AAM™ platform.
Citibot: Fulongma&PIX self-driving sweeping robot
Parts designed on AAM™ platform
The versatility of AAM™ platforms extends beyond vehicle engineering to include aerospace, marine, and bridge design.
Autodesk recognized PIX Moving as its “Innovator of the Year” for the company’s groundbreaking work in artificial intelligence (AI) algorithm design and cutting-edge manufacturing techniques.
PIX Moving winning “Innovator of the Year” granted by Autodesk
During the CAADRIA 2022 International Conference, PIX Moving presented two papers on the topic of “Industrial Software Core Algorithms.”
The premier international academic conference on industrial software, themed “Post Carbon,” took place in Sydney, Australia, from April 9–16, 2022. At the event, PIX Moving presented PIX Industrial Software for developing AI algorithms and digital production.
Innovative limits on hardware products are set by the hardware and software used in production. Tools are PIX’s true super product, says CEO and co-founder Yu Chuan.
Yu Chuan, PIX Moving Founder&CEO
Typical text and images in today’s AIGC products are examples of non-quantitative approximate content. To accurately and quantitatively control the generated content, PIX AAM™ could benefit greatly from a generative algorithm with realistic constraints (kinetics, statics, kinematics, process constraints).
Generative AI: A Creative New World is a report by Sequoia Capital that predicts the disruption of industries that rely on human creativity, such as writing, product design, programming, advertising, and marketing.
There is also a forecast that “the economic value of the AIGC sector will reach trillions of dollars by the end of the forecast period.”
Open AI, Jasper, Copy.ai, WriteSonic, Peppertype, and many more are just a few examples of AIGC businesses in the fields of text creation, image generation, video creation, and code development, while Autodesk and PIX Moving are leading the charge to promote AIGC in industrial manufacturing.
According to Sequoia Capital’s report: The Rise of Deep Learning and Its Applications, PIX AAM™ enables the quantitative output of engineering documents to meet the needs of industrial manufacturing.
The marginal cost of creative and knowledge labor will be reduced to zero as generative AI greatly increases productivity and generates substantial economic value.