H2O Hydrogen Torch
The no-code deep learning platform (AutoDL) that automates image, text, video, and audio models, with Kaggle Grandmaster defaults and one-click packaging for MLOps.
- H2O Hydrogen Torch is no-code deep learning (AutoDL) for image, text, video, and audio, launched February 2022 and an AI Tech Award winner.
- It supports image classification, detection, and segmentation; text classification, token classification, span prediction, and sequence-to-sequence; video; and speech-to-text.
- Kaggle Grandmaster defaults, transfer learning, and multi-GPU training, with one-click packaging for H2O MLOps.
- Hydrogen Torch does not do time-series forecasting; use Driverless AI or tabH2O for that.
Every unstructured problem type a team actually meets.
Deep learning is a branch of machine learning. Hydrogen Torch is H2O AI's AutoDL: it automates the parts that used to need a research team.
- ImageClassification, regression, object detection, semantic and instance segmentation, and 3D, with transfer learning from strong backbones.
- TextClassification, regression, token classification, span prediction, and sequence-to-sequence, the NLP behind document routing and extraction.
- VideoClassification and regression over video clips, on the same no-code training loop as every other modality.
- AudioClassification, regression, and speech-to-text, so call recordings become structured, searchable data you can model.
- Grandmaster defaultsHyperparameters and augmentations chosen by the people who win Kaggle. Start from a strong baseline, not from scratch.
- One-click to MLOpsPackage the trained model for H2O MLOps deployment and monitoring without ever leaving the tool.
Dataset in, deployable model out.
- 01ImportImages, text, video, or audio with labels. Or label them first in H2O Label Genie.
- 02Choose the problem typePick the task. Hydrogen Torch sets Kaggle Grandmaster defaults that you can override in the UI.
- 03Train and compareMulti-GPU training with live metrics. Run variants, and compare experiments side by side.
- 04Package for MLOpsOne click to a deployable artifact with drift and accuracy monitoring already attached.
A training engine for the data that does not fit in a table.
Hydrogen Torch sits beside Driverless AI and H2O-3 in the predictive lane, serving through MLOps. Highlighted is Hydrogen Torch.
What ships today
Vision and language models the Super Agent can call.
Models trained in Hydrogen Torch deploy through MLOps, which makes them tools the H2O AI Super Agent can invoke: classify the image, extract the span, transcribe the call, then act on the result.
You operate it, or H2O AI operates it for you.
Same platform either way: the same capabilities, the same governance, and the same audit trail. The choice stays open, so you can switch between them as the business changes, without rebuilding what runs on top.
H2O AI Cloud for Government
The H2O AI Cloud for Government has achieved FedRAMP High Certification, delivering the highest standard of cloud security so federal agencies can harness predictive and generative AI without compromising data sovereignty or compliance.
Questions people ask before they call us.
Image classification, regression, object detection, semantic and instance segmentation, and 3D. Text classification, regression, token classification, span prediction, and sequence-to-sequence. Video classification and regression. Audio classification, regression, and speech-to-text.
Bring a thousand labeled images or a stack of call recordings.
We will train, compare, and package a model with you, then deploy it to MLOps in the same session.