Helm.ai Streamlining Self-Driving AI Development with NVIDIA
As a member of the NVIDIA Inception Program, we’re reimagining the development of scalable AI
Our journey towards safe, interpretable, scalable and cost-effective autonomous driving technologies continues to evolve, and Unsupervised Learning is the future for self-driving AI software.
Unsupervised Learning allows us to train neural networks without labeled data. It’s an open area of AI research, with some previous approaches aiming to identify new patterns in data or pre-processing a pool of data.
Through Deep Teaching, our proprietary Unsupervised Learning method, it’s our aim to dramatically reduce time and cost bottlenecks in autonomous vehicle development cycles … chiefly, we’re lessening the burden on human annotators.
Our NVIDIA Partnership
As a member of the NVIDIA Inception Program, Helm.ai is reimagining the development of scalable AI software. In our data center, we use high-performance NVIDIA V100 Tensor Core GPUs to run the unsupervised learning techniques that train our self-driving algorithms. This helps make it possible to process petabytes of data without experiencing costly roadblocks.
We also bring NVIDIA inside the vehicle, running our self-driving software on the NVIDIA DRIVE AGX Xavier AI compute platform to deliver 30 trillion operations per-second for L2+ and L3 autonomous driving. At its core is the Xavier system-on-a-chip, the first-ever production auto-grade SoC, which incorporates six different types of processors.
What Makes Us Unique
Instead of pursuing well-understood capital-intensive approaches, we’ve reimagined the way we can scale AI software development for safety-critical applications, leveraging cutting-edge applied mathematics to train neural networks without human annotation or large-scale fleets.
Because of Deep Teaching, we’re able to offer a full suite of modular AI software throughout the L2/L3 and L4 autonomous driving stacks to OEMs and Tier-1 developers … addressing perception, prediction, fusion, mapping and path planning and control. The result is scalable AI software — achieving driving automation on a far more reasonable timeline and budget.
More accurate and cost-effective AI is mission-critical for the industry as a whole. With more accurate and cost-effective AI training, we’re enabling the industry to safely deploy transportation technologies that will transform the way people and goods move.
Interested in learning more about Helm.ai and our approach to Unsupervised Learning and AI for autonomous driving? Be sure to subscribe to the Helm.ai YouTube channel for more context or visit the Helm.ai website.