Propelling AI startups with powerful GPU tools, tech, and deep learning expertise.
Thanks to MinerEye’s Interpretive AI™ Technology, we have been invited to join Nvidia inception program. This will allow us to develop our technology even further and continue to be at the forefront of innovation.
The Nvidia Inception Program nurtures dedicated and exceptional startups who are revolutionizing industries with advances in AI and data science. This virtual accelerator program helps startups during critical stages of product development, prototyping, and deployment.
Every startup gets a custom set of ongoing benefits, from hardware grants and marketing support to training with deep learning experts.
NVIDIA is helping MinerEye with:
- Deep Learning Expertise: the Nvidia Inception Program is designed to nurture startups who are revolutionizing industries with advances in artificial Intelligence (AI) and data science. Designed as a virtual incubator program, Inception helps members during critical stages of product development, prototyping, and deployment. As an Inception member, MinerEye will get access to Nvidia’s global ecosystem—a massive network of deep learning experts and thought leaders.
- Hardware Grants: the deep learning community is using GPU-accelerated platforms for training and inference in every industry. Inception members can apply for GPU hardware grants, access the latest software, and get remote access to state-of-the-art technology.
Marketing Lift: MinerEye will receive support for it’s marketing goals. These include blogs, podcasts, event support, videos, and a variety of other opportunities.
- And more!
Why does MinerEye invest in this?
Data scientists in both industry and academia have been using GPUs for machine learning to make groundbreaking improvements across a variety of applications including image classification, video analytics, speech recognition and natural language processing. In particular, Deep Learning – the use of sophisticated, multi-level “deep” neural networks to create systems that can perform feature detection from massive amounts of unlabeled training data – is an area that has been seeing significant investment and research.
Although machine learning has been around for decades, two relatively recent trends have sparked widespread use of machine learning: the availability of massive amounts of training data, and powerful and efficient parallel computing provided by GPU computing. GPUs are used to train these deep neural networks using far larger training sets, in an order of magnitude less time, using far less data center infrastructure. GPUs are also being used to run these trained machine learning models to do classification and prediction in the cloud, supporting far more data volume and throughput with less power and infrastructure.
Early adopters of GPU accelerators for machine learning include many of the largest web and social media companies, along with top tier research institutions in data science and machine learning. With thousands of computational cores and 10-100x application throughput compared to CPUs alone, GPUs have become the processor of choice for processing big data for data scientists.
Learn more about NVidia’s program here.