H2O.ai has announced that its Driverless AI automated machine learning platform and H2O4GPU open source GPU-accelerated machine learning package are now both fully optimised for the latest-generation NVIDIA Volta architecture GPUs — the NVIDIA Tesla V100 — and CUDA 9 software.
Driverless AI lets data scientists, engineers, and domain scientists use an incredibly fast, intuitive computing platform to build highly accurate models and pipelines in a fraction of the time spent.
Customers can now apply automatic feature engineering with machine learning to quickly develop hundreds of machine learning models and pipelines, helping businesses mitigate risks and maximize revenue potential. This helps combat the lack of highly skilled data scientists and artisanal data culture that is hindering AI adoption.
Driverless AI also offers first-of-its-kind model interpretability to explain model accuracy and predictions transparently.
“Driverless AI makes it possible for a small team of data scientists to operate at an industrial scale. We’re able to now tackle a host of different use cases all at once because of the power of automated machine learning and interpretability,” said Ajay Gopal, Chief Data Scientist of Deserve, an analytics-based financial tech company.
“HPC is the new PC for AI developers. NVIDIA and H2O hardware/software co-evolution makes it faster, cheaper and easier to build and deploy machine learning models. H2O4GPU makes good on our mission to build a strong open source AI community with the fastest and most accurate software on the hardware innovations on GPU,” said Sri Ambati, CEO of H2O.ai.
“NVIDIA GPUs combined with Driverless AI and H2O4GPU provide a great solution for enterprises looking to transform their businesses with accelerated machine learning. Our financial, healthcare and insurance customers are able to see real growth from the collaboration by gaining tremendous speed to insights and interpretability,” said Jim McHugh, VP and GM of Deep Learning Systems at NVIDIA.