H2O.ai announce deep learning engine, H2O Hydrogen Torch

AI cloud leader, H2O.ai has announced the H2O Hydrogen Torch, a deep learning training engine. The engine will make it easy for companies of any size in any industry to make state-of-the-art image, video and natural language processing (NLP) models without coding. 

“Accelerated by COVID-19, video streams, speech, audio podcasts, email and natural language text have become the fastest-growing data for our customers in every industry. Transforming and fine-tuning pre-built deep learning models to deliver high accuracy requires a no-code AI Engine to democratise AI for these use cases,” said Sri Ambati, CEO and founder, H2O.ai. 

“H2O Hydrogen Torch does exactly that by bringing best practices from Grandmasters to tackle problems ranging from improving in-store customer experiences, identifying fashion trends, and discovering vaccines, to saving lives with video-enabled drones fighting fires with AI on the edge. With H2O Hydrogen Torch as a core AI Engine of the H2O AI Cloud, our customers can train models in deep learning and better serve their customers and challenge tech giants,” he added.

Prior to the launch of H2O.ai’s Hydrogen Torch, creating deep learning models has required extensive data science knowledge and time. 

The new deep learning training engine was developed by the world’s best data scientists and the challenging parts of creating world-class deep learning models are handled automatically by the product. 

With its simple, no-code user interface, data scientists and developers can rapidly make models for numerous image, video and NLP processing use cases, including identifying or classifying objects, analyzing sentiment or finding relevant information in a text. 

H2O.ai’s Hydrogen Torch for NLP and image and video processing

H2O.ai’s Hydrogen Torch has been successfully used by Aura.ceo, a unique talent screening platform that offers a data-driven, outside-in perspective on any organisation’s workforce.

Stelios Anagnostopoulos, CTO at Aura.ceo commented: “H2O Hydrogen Torch has been a key enabler in helping us operationalise machine learning for shifting data. We can get from a new dataset to a deployed model and updated tables in our data warehouse in a couple of days instead of weeks.”

The new engine by H2O.ai can be used for both image and video processing and NLP. For images and videos, H2O Hydrogen Torch can be trained for classification, regression, object detection, semantic segmentation and metric learning. 

For text-based or NLP use cases, H2O Hydrogen Torch can be trained for text classification and regression, token classification, span prediction, sequence-to-sequence analysis and metric learning. 

H2O Hydrogen Torch is part of H2O.ai’s broad and rapidly expanding set of H2O AI Cloud products, including the recently announced H2O AI Feature Store and H2O Document AI. 

This announcement comes just a few months after the company closed $100 million in Series E funding led by Australia’s largest bank, customer Commonwealth Bank of Australia (CBA). Now, H2O.ai has raised over $250 million and is valued at $1.7 billion.