Jeff Bezos is trying to leapfrog into the artificial intelligence race with a $100 billion fund to acquire manufacturers and bring more AI superpowers to factory floors.

The Amazon founder has reportedly traveled to the Middle East and elsewhere to meet with potential investors for the massive fund. If he succeeds, it would be one of the largest buyout funds and could change the way products are designed, made and distributed.

Here is what you need to know about the big plans:

What is the fund?

Documents connected to the fund described it as a "manufacturing transformation vehicle" that would buy companies that could use an AI upgrade in sectors including chip manufacturing, defense and aerospace, according to the Wall Street Journal.

The fund is expected to use AI solutions developed by a new Bezos-backed venture, Project Prometheus, for manufacturing.

Since stepping down as chief executive of Amazon in 2021, Bezos has turned his attention to his space company, Blue Origin, and his newspaper, the Washington Post. He remains on Amazon's board as its chairman.

But last year, in one of his first official leadership roles after Amazon, he became co-CEO of the little-known Project Prometheus.

His co-founder and co-CEO, Vik Bajaj, is a professor at Stanford's School of Medicine who previously co-founded Google's life science division, Verily. David Limp, the CEO of Blue Origin, was appointed to Prometheus' board of directors.

Project Prometheus has raised $6.2 billion in funding, including from Bezos. The startup does not have a website, but nonetheless it has poached top AI researchers from OpenAI and DeepMind.

What is Project Prometheus?

Project Prometheus is building an AI system to simulate and predict real-world behavior, according to reports.

Its technology, for example, could simulate how air flows around airplane wings, or predict where a metal part might crack under pressure, the the Journal reported. Without flying an actual plane, companies can use AI to generate scenarios to pressure test the wings so a plane can be brought to market faster.

Chatbots such as ChatGPT are large language models that were trained on vast quantities of text, images and videos from the internet. They identified patterns in online information and learned to mimic how people string words, music and pixels together.

They are good at creating images, text and code, and even solving complex math. Most of those AI capabilities exist in the digital world, and many companies are trying to find more ways to bring AI into physical workspaces, whether it is washing dishes, delivering packages or building products.

Project Prometheus intends to build AI that simulates and understands the physical world.

How is AI coming for physical manufacturing?

"For decades, manufacturing innovation has been constrained by how long it takes to test physical ideas," said Pete Schlampp, CEO of Luminary, an AI startup that enables simulation for engineering based on the laws of physics. "AI is changing that by allowing engineers to predict real-world performance much earlier in the design process."

Engineers spend months designing physical things — airplane wings, chips, drug molecules, robots or car parts — and before building them, they need to test them.

Traditionally, testing and fixing designs can take months or even years. Now, companies are training AI models on the output of thousands of simulations they already have, so they can learn to predict the right outcome in seconds.

"Instead of validating one design at a time, teams can now explore thousands of options digitally before building anything," Schlampp said in an email. "This shift is moving engineering from trial-and-error toward prediction-driven design, which can significantly accelerate innovation in industries like aerospace, automotive, and industrial machinery."

AI is further boosting physical industries by optimizing the stages that come after design, including conveyor-belt manufacturing, quality inspections and factory-floor operations.

Companies such as Nvidia have introduced tools for manufacturers to create "digital twins" that mirror live factories or warehouses, to plan layouts and flag anomalies — both before building and after deployment. Carmaker Mercedes Benz uses digital twins of its factories and assembly lines to reduce downtime, and also to test its driving software in simulations before real-world deployment.

Bezos has led Amazon to automate much of its massive distribution network, which now may have more robots than people by some measures. He also has backed Physical Intelligence, a company that uses AI in robotics.

Software represents roughly $1 trillion of economic activity, while manufacturing accounts for closer to $17 trillion globally, according to Schlampp.

"Efforts like Project Prometheus reflect a growing belief that AI can drive major economic impact in the physical economy, not just in software or back-office automation," Schlampp said.

Boosters believe this is a necessary move to reindustrialize America at a time when China is dominating manufacturing.

Is this going to hit jobs in California?

It's still unclear whether California companies would be potential targets of the fund, though the state has many companies in the sectors in which it is reportedly interested.

A $100-billion war chest to automate manufacturing already is exacerbating fears that AI is coming for everyone's jobs.

"Oligarchs are waging all out war against workers. FIGHT BACK," Sen. Bernie Sanders posted on X. "Jeff Bezos, worth $234 billion, plans to replace 600,000 Amazon workers with robots. Now, he wants to spend $100 billion to fully automate not just his warehouses, but factories in the U.S & other countries."

Optimists say that introducing AI in the manufacturing process lowers the cost and speed of designing physical products, which eventually will expand these industries.

"If companies can bring better aircraft, vehicles, energy systems, and infrastructure to market faster and more efficiently, that can drive new investment and growth across advanced manufacturing sectors," Schlampp said. "That growth can support job creation, even as parts of the workforce will need to reskill as AI becomes more embedded in industrial workflows."

He predicts that AI will not replace engineering, but will change where engineers and technicians spend the majority of their time, shifting their focus from repetitive validation tasks to higher-level system design and innovation.

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