Decart raises $300M for its AI optimization software, world models

Artificial intelligence developer Decart.ai Inc. today announced that it has raised $300 million in funding at a nearly $4 billion valuation.

Radical Ventures led the round with participation from Nvidia Corp., Adobe Ventures, Toyota Ventures and other institutional backers. They were joined by several prominent angel investors including OpenAI Group PBC co-founder Andrej Karpathy.

Decart announced the raise alongside an update to DOS, one of its three software products. The platform helps AI developers speed up training and inference workloads. Decart says that it’s generating “significant revenue” from DOS licensing agreements with cloud providers and AI labs.

Typically, developers have to optimize a neural network for every single chip on which they plan to run it. The process can take months. Decart says that DOS compresses the workflow into a few weeks, which reduces the cost of optimizing a model for multiple chips. That cost reduction, in turn, makes it easier for companies to move their AI workloads across chips when requirements change.

DOS 2.0, the new version of the platform that debuted today, enables AI agents to process over 1,600 tokens per second. That’s eight times the industry average. Additionally, Decart says that the software enables world models to process up to 100 frames of high-definition video per second. 

DOS underpins the company’s two other products: a pair of world models called Lucy and Oasis.

Lucy takes a video stream as input and modifies the objects that the footage depicts in real-time. A department store, for example, could use it to power a smart mirror that lets shoppers virtually try on different clothes. An interior design firm, meanwhile, could record a video of a room and have Lucy generate different furniture combinations.

Video models often have output quality limitations. One reason is that quality issues cascade across frames: a relatively minor mistake at the start of the video can lead to a significant decrease in visual fidelity later on. According to Decart, Lucy can catch such issues early and fix them automatically. The company equipped Lucy with that ability by showing the model its “own imperfect outputs” during training.

According to Decart, another use case that the AI supports is generating training data for robots. An online retailer working to automate its warehouses could generate videos that show a robotic arm picking up different packages. Lucy can automatically generate a large number of parcel variations.

Robot developers with more advanced requirements can combine the algorithm with Oasis, Decart’s second world model. The latter AI is designed to generate three-dimensional environments such as simulated logistics warehouses.

Descartes will use its newly raised funding to enhance its product lineup. The company plans to release new versions of Lucy and Oasis in the coming weeks.  

Image: Decart