Infinity AI Raises $5 Million to Build Automated Synthetic Training Data

Infinity AI, a startup that generates automated synthetic training data, announced a $5 Million seed round led by Matrix with participation from founders and operators from companies like Snorkel AI, Tesla, and Google. The funds will be used to bring the company’s novel generative tools, which complement Infinity’s existing self-serve API, to market.

AI models are only as good as the data they are trained on, but traditional data collection and annotation processes – fueled by human labor – are notoriously expensive and slow. Enterprise data scientists spend over 80% of their time gathering, organizing, and labeling the training data they use. Bottlenecks in training data are a primary reason that computer vision projects get canceled.

Synthetic data – or data that is generated via simulation rather than collected by a sensor – leapfrogs the data collection and annotation steps. Training on synthetic data has become an established best practice as major tech companies like Tesla, Amazon, and Microsoft all announced products by training on synthetic data. Gartner recently placed synthetic data at the top of its list of strategic predictions for 2022 and beyond, saying that “by 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated.”

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Infinity’s platform allows engineers to upload a single real-world video and turn that into hundreds of similar and perfectly labeled synthetic videos. Infinity uses a combination of physics-based simulations and generative techniques to do this. For example, its self-serve API allows engineers to generate hundreds of videos that meet desired statistical distributions of camera location, lighting conditions, avatar appearances, and more.

Infinity’s generative tools, currently in beta, bring those capabilities to the next level. They include a Stable Diffusion-based inpainting tool that massively augments scenes and another generative tool that adds infinite clothing textures to avatars. Infinity will release these tools publicly in 2023.

Infinity AI currently works with over a dozen customers across fitness and smart facilities, including Tempo Fitness, Voxel Safety, SwRI, as well as a Fortune 50 company. Infinity’s customers have generated over 5M synthetic data frames using the self-serve API in just 6 months.

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The economic downturn has led to increased customer demand at Infinity. Although companies are tightening overall budgets, they still want to continue to get new AI products to market. Synthetic data is a perfect solution since it is orders of magnitude (10-100x) cheaper than working with sensor-collected data.

Infinity AI has an edge over competitors because their products span the entire lifecycle of machine learning (ML) model development. Customers can use Infinity AI’s off-the-shelf training datasets for early exploration, then graduate to the self-serve API for fine-grained control over their data, then progress to using Infinity AI’s data flywheel technology to feed failure cases into the Infinity engine and receive perfectly-labeled infinite variations on that data in return

“Using Infinity AI, we can get new products out the door faster. And, our ML engineers are happier because they get to spend more time on the fun part of model development,” says Harishma Dayanidhi, Co-Founder and VP of Engineering at Voxel, one of Infinity AI’s early customers.

As part of today’s announcement, Infinity AI is launching the Infinity Marketplace, the world’s largest open-source marketplace for synthetic datasets. There are already 1 million free frames that can be used for both research and commercial purposes, and more are added every month. Datasets run the gamut from fitness and robotics, to smart retail, industrial safety, and more.

“We want to make it easy for ML teams to start working with synthetic data,” says Lina Avancini Colucci, one of the founders of Infinity AI. “The ML community has a scarcity mentality with regards to data today. Synthetic data turns this into an abundance mentality. Infinity is democratizing access to training data since this is the biggest roadblock to progress in ML today.”

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