Computer vision is one of the most disruptive technologies of the recent decade. Whether you’re thinking about consumer technologies such as autonomous vehicles and Face ID, or something that works more behind the scenes like AI-powered geospatial intelligence and medical imaging, computer vision brings new opportunities across industries.
Breakthroughs rarely come easy, and that is the case with practical applications of computer vision as well. Today, developing a computer vision model requires a tremendous amount of labeled images and enormous computational power.
These two requirements usually take a massive investment upfront to develop computer vision systems, thus drastically stretching the time to market. Teams that are in a hurry or working with limited resources need to look for creative solutions.
Superb AI and Valohai have partnered to provide an end-to-end solution that tackles these two challenges. Our focus is to make an infrastructure solution that makes computer vision possible with a timeframe and team structure that is more akin to classical ML.
The two platforms cover the data preparation and the model operationalization aspects, respectively, combined as a continuous pipeline. As production models are never one-offs but rather evolving products, any changes such as new data inputs or code modifications will automatically trigger the pipeline from data preparation to model development to model deployment.
Superb AI has introduced a revolutionary way for ML teams to drastically decrease the time it takes to deliver high-quality training datasets. Instead of relying on human labelers for a majority of the data preparation workflow, teams can now implement a much more time- and cost-efficient pipeline with the Superb AI Suite.
A typical data preparation pipeline might contain the following steps:
The labeled dataset from Superb AI gets ingested into a machine learning pipeline. Valohai makes it possible to build pipelines with any number of steps run in parallel or sequence. Each step can contain any language or framework and run on specific hardware suited for the purpose – all without any engineering overhead.
A typical machine learning pipeline might contain the following steps:
Practical computer vision applications are still waiting to be unleashed due to the demanding nature of developing them. The demand for human and machine resources grows the project’s complexity and stretches timelines and budgets that can be out of reach for many organizations. However, as shown above, intelligent platform choices make computer vision much more attainable. With Superb AI’s automatic labeling technology and Valohai’s managed training infrastructure, you can drastically reduce the need for the labelers to get the data right and for the engineers to build and maintain a working infrastructure. If you are looking for a complete solution for developing computer vision applications, let’s schedule a demo and see whether our solution is right for you.
Superb AI is an enterprise-level training data platform that is reinventing the way ML teams manage and deliver training data within organizations. Launched in 2018, the Superb AI Suite provides a unique blend of automation, collaboration and plug-and-play modularity, helping teams drastically reduce the time it takes to prepare high quality training datasets. For more information, please reach out to our team.
Valohai is the only MLOps platform that automates everything from data extraction to model deployment. Valohai is all about taking away the not-so-fun parts of machine learning. Managing cloud instances and writing glue code is neither valuable nor fun. Our platform does that for you. We’re trusted by companies such as Twitter, JFrog, Konux and Preligens. For more information, please reach out to us.
Both Superb AI and Valohai are part of the AI Infrastructure Alliance and dedicated to building the foundation of Artificial Intelligence applications of today and tomorrow.