Two artificial intelligence researchers who were once considered for leadership roles at Jeff Bezos-backed Project Prometheus have chosen a different path, launching their own company focused on using AI to model physics and complex real-world systems.
The founders, Anima Anandkumar and Benedikt Jenik, unveiled their company, Accelerated Understanding Inc., on Tuesday. They say they have developed an AI system capable of processing an extraordinary amount of information in a single prompt—up to 5 trillion pieces of data in testing.
That figure is roughly 5 million times larger than the amount of information that leading models from companies such as Anthropic and Google can typically process at once.
But unlike ChatGPT-style systems designed primarily to understand and generate language, Accelerated Understanding’s technology is designed to understand physical phenomena unfolding across space and time.
Moving beyond language-based AI
Today’s most prominent AI systems were largely built by training on enormous quantities of text and other digital information. These models learn patterns in language and can predict what words or tokens are likely to come next.
Anandkumar and Jenik are pursuing a fundamentally different approach.
Their system is based on neural operators, a technology designed to learn relationships between complex physical systems rather than simply predicting language.
Anandkumar, a professor at Caltech, described the distinction as a move away from a human-centered definition of intelligence toward a nature-centered approach.
The company has also moved away from the Transformer architecture that underpins many modern generative AI systems, including ChatGPT.
Building an AI “world model”
Accelerated Understanding is entering a growing field of AI research focused on creating world models—systems that can understand the physical world rather than simply processing language, images or other conventional digital information.
Several AI researchers and companies are exploring similar ideas, including organizations associated with prominent researchers such as Yann LeCun and Fei-Fei Li.
Accelerated Understanding’s strategy is to build a general-purpose neural-operator system capable of predicting physical events that may be impossible or difficult for humans to observe directly.
The founders believe such technology could eventually become useful across multiple industries.
From chip design to extreme weather
One of the company’s most promising applications is semiconductor design.
AI is already being used by chip companies to write software, automate engineering tasks and analyze technical information. Accelerated Understanding believes that an AI system with a deeper understanding of physics could go further.
Instead of repeatedly testing different materials, temperatures and configurations in physical laboratories, the system could potentially simulate how those variables affect chip performance before engineers build physical prototypes.
The same underlying technology could potentially be applied to:
- Robotics, by modeling how machines interact with physical environments.
- Weather forecasting, including prediction of extreme weather events.
- Energy exploration, through analysis of geological structures and underground conditions.
- Materials science, by predicting how materials behave under different conditions.
- Industrial engineering, by optimizing complex physical systems.
The founders’ long-term ambition is to develop one flexible AI system capable of addressing different physics-related problems instead of creating a separate mathematical model for every individual application.
A different path from Bezos’ Prometheus
The company’s creation is particularly notable because Anandkumar and Jenik were previously considered for involvement with Project Prometheus, the AI company backed by Bezos.
According to documents reviewed by Reuters, the possibility of working together was discussed during a dinner in the Los Angeles area in late 2024.
Anandkumar had previously worked as a scientist at Amazon and had attended private AI gatherings hosted by Bezos. She also spent five years as a director at Nvidia, while Jenik worked as an AI infrastructure engineer.
The pair had already started developing their own company when they were approached about joining Prometheus.
A proposal reviewed by Reuters reportedly offered Anandkumar a prominent leadership role, including responsibility for the company’s scientific direction and a board position. Jenik would have served as a board observer.
Together, they were offered a 35% stake in Prometheus and a combined annual salary of $1 million, which would have increased to $2 million after three months.
The proposal also outlined more than $2 billion in planned funding through Series B, with Bezos among the prospective investors.
They chose to build independently
Despite the substantial offer, Anandkumar and Jenik decided to continue developing their own company.
Their decision appears to have paid off in terms of momentum.
While Accelerated Understanding has remained relatively quiet about its financing, the founders say they have partnerships with computing providers that have supplied the powerful hardware clusters needed to train and operate their AI system.
They have not publicly identified those partners.
Meanwhile, Bezos and Vik Bajaj continued developing Prometheus, which raised $12 billion in a Series B round in June 2026. Prometheus is focused on AI systems capable of automating the manufacturing of complex physical products.
The two companies are therefore pursuing related but distinct visions: Prometheus is targeting physical manufacturing, while Accelerated Understanding is concentrating on AI capable of modeling the underlying physics behind real-world systems.
The Nvidia connection
Anandkumar’s interest in physics-focused AI has deep roots in her work at Nvidia.
She joined the chipmaker in 2018 and led research into how Nvidia’s graphics-processing units could be used for advanced AI applications.
One early project demonstrated that AI could potentially accelerate weather forecasting while maintaining accuracy comparable to computationally intensive traditional forecasting methods.
The work attracted the attention of Nvidia CEO Jensen Huang, who highlighted Anandkumar’s research on neural operators during Nvidia’s 2021 GTC conference.
According to Anandkumar, Huang strongly encouraged her to pursue the idea further.
His enthusiasm was reportedly captured in a memorable comment after she suggested that AI could eventually outperform traditional physics-based research approaches.
AI’s next frontier may be physics
The emergence of Accelerated Understanding reflects a broader shift in the AI industry.
The first wave of generative AI was largely built around language. The next generation could increasingly focus on understanding how the physical world actually works.
If successful, physics-focused AI could reduce the amount of expensive trial-and-error experimentation required in areas such as chip manufacturing, drug development, robotics, energy and climate modeling.
For businesses, that could translate into faster product development, lower research costs and more efficient engineering.
Accelerated Understanding is initially targeting enterprise customers rather than consumers, suggesting that its founders see immediate commercial opportunities in specialized industrial applications rather than another consumer chatbot.
The larger bet is ambitious: instead of teaching AI to understand humanity through the world’s text, Anandkumar and Jenik want to teach machines to understand nature itself. If their approach works at scale, it could open a new chapter in AI—one where the most valuable models don’t simply generate words or images, but predict and simulate the physical world.
