Larry Page, one of the co-founders of Google and CEO of the company (as well as parent organization Alphabet Inc.) in two different phases of its history, is now helping to build a startup that uses AI to optimize design for manufactured goods. Called Dynatomics, the stealth mode startup is reportedly being run by Chris Anderson, the former CTO of Kitty Hawk, a defunct eVTOL startup that was also backed by Page.
This development illustrates an overlap between at least a couple of major current investment themes in the advanced manufacturing space. First, there is the entry into next-gen manufacturing by one of the big names from the dot-com boom, a theme also embodied by Eric Schmidt’s surprising assumption of the CEO role at Relativity Space. (Schmidt, of course, was Google’s CEO before Page returned to that role a second time in 2011.)
Second, lately, quite a bit of capital is moving into AI-driven design optimization for the manufacturing sector. In December, 2024, for instance, Backflip, a text-to-STL startup co-founded and run by Markforged founder Greg Mark, announced $30 million in funding from investors including Andreessen Horowitz.
The idea that AI is ready to play a pivotal role in reducing the costs and general difficulties associated with 3D design of manufactured products has been gaining steam in the additive manufacturing (AM) industry for years. It is the fundamental selling point of companies like 1000 Kelvin, which, among other projects, has partnered with Fieldmade to bring automated quality control to the frontlines for military MRO.
The straightforward concept at play for companies like Dynatomics, Backflip, 1000 Kelvin, etc., is that manufacturers can greatly cut the costs and issues associated with physical testing and qualification of new designs by essentially “vetting” those designs ahead of time with AI. For the AM industry, the fact that qualification remains one of the biggest barriers to entry standing in the way of new adoption makes AI-optimized design one of the industry’s most exciting areas of innovation.
Another exciting angle here for the AM industry is that, at least in the West, major questions have started to emerge concerning where the AI boom goes from here, a state-of-affairs that has intensified since Chinese startup’s DeepSeek’s release of its open-source LLM. The fact that such prominent AI bulls as Schmidt and Page are signaling that next-gen manufacturing is their newest target strongly suggests that manufacturing is one of the big use-cases that will drive the next wave of AI adoption.
For the AM industry, the potential there may be especially bright, because of all of the pre-existing cross-pollination between the two worlds, and because AM is the niche within advanced manufacturing where AI could ultimately make the biggest difference. Professionals in the AM industry have been griping about the dangers of too much hype for years now, but at least in this case, a little hype might not be such a bad thing.
Feature image courtesy of Niall Kennedy on Flickr.
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