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AI Weekly: AI helps companies design physical products

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This week in a paper revealed within the journal Nature, researchers at Google detailed how they used AI to design the following technology of tensor processing models (TPU), the corporate’s application-specific built-in circuits optimized for AI workloads. While the work wasn’t novel — Google’s been refining the method for the higher a part of years — it gave the clearest illustration but of AI’s potential in {hardware} design. Previous experiments didn’t yield commercially viable products, solely prototypes. But the Nature paper suggests AI can on the very least increase human designers to speed up the brainstorming course of.

Beyond chips, companies like U.S.- and Belgium-based Oqton are making use of AI to design domains together with additive manufacturing. Oqton’s platform automates CNC, metallic, and polymer 3D printing and hybrid additive and subtractive workflows, like creating castable jewellery wax. It suggests a spread of optimizations and fixes knowledgeable by AI inspection algorithms, in addition to by pre-analyses of half geometry and real-time calibration. For instance, Oqton can mechanically alter geometries to get elements inside required tolerances, simulating warmth remedy results like warpage, shrinkage, and stress reduction on titanium, cobalt, chrome, zirconia, and different supplies.

While it’s nonetheless within the analysis levels, MIT’s Computer Science and Artificial Intelligence Laboratory developed an AI-powered instrument referred to as LaserFactory that may print absolutely purposeful robots and drones. LaserFactory leverages a three-ingredient recipe that lets customers create structural geometry, print traces, and assemble digital elements like sensors, circuits, and actuators. As the researchers behind LaserFactory observe in a paper describing their work, it may in idea be used for jobs like supply or search-and-rescue.

At Renault, engineers are leveraging AI-powered software program created by Siemens Digital Industries Software to automate the design of automated guide transmission (AMT) programs in vehicles. AMT, which behaves like an automated transmission however permits drivers to shift gears electronically utilizing a push-button, can take as much as a yr of trial and error to ideate, develop, and completely validate. But Siemen’s instrument permits Renault engineers to pull, drop, and join icons to graphically create a mannequin of an AMT. The software program predicts the conduct and efficiency of the AMT’s elements and makes any needed refinements early within the improvement cycle.

Even Nutella is tapping AI for physical products, utilizing the expertise to tug from a database of dozens of patterns and colours to create totally different variations of its packaging. In 2017, working with promoting company Ogilvy & Mather Italia, the corporate splashed over 7 million distinctive designs on “Nutella Unica” jars all through Italy, which offered out in a month.

Philosophical shift

People would possibly understand these functions as taking company away from human designers, however the coauthors of a latest Harvard Business School working paper argue that AI really permits designers to beat previous limitations — from scale and scope to studying.

“In the context of AI factories, solutions may even be more user-centered, more creative, and continuously updated through learning iterations that span the entire life cycle of a product. Yet, we found that AI profoundly changes the practice of design,” the coauthors write. “Problem solving tasks, traditionally carried on by designers, are now automated into learning loops that operate without limitations of volume and speed. These loops think in a radically different way than a designer: they address complex problems through very simple tasks, iterated exponentially.”

In a latest weblog put up, person expertise designer Miklos Philips echoed the findings of the Harvard Business Review paper contributors, noting that designers working with AI can create prototypes rapidly and extra cheaply because of the elevated effectivity it affords. AI’s energy will lie within the pace wherein it will possibly analyze huge quantities of information and recommend design changes, he says, so {that a} designer can cherry-pick and approve changes primarily based on information and create the simplest designs to check expediently.

In any case, the ROI of AI-assisted design instruments is probably substantial. According to a 2020 PricewaterhouseCoopers survey, companies in manufacturing count on effectivity features over the following 5 years attributable to digital transformations, together with the adoption of AI and machine studying. Perhaps unsurprisingly, 76% of respondents to a Google Cloud report revealed this week stated they’ve turned to “disruptive technologies” like AI, information analytics, and the cloud, notably to assist navigate challenges introduced on by the pandemic.

Given the enterprise worth, AI-powered design is probably going right here to remain — and to develop. That’s usually good news not just for designers, however for the enterprises and customers that stand to reap the advantages of automation throughout physical product creation.

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