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Introducing the h2oGPTe GitHub Action
by Julian Garratt, Issac Liu | November 19, 2025 Agentic AI, Enterprise h2oGPTe

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Building Resilient Infrastructure with AI: The H2O.ai Flood Intelligence Blueprint, accelerated by NVIDIA
by Betty Candel, Shivam Bansal, Piraveen Sivakumar, Srinivas Neppalli | October 27, 2025 NVIDIA

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Why NVIDIA NIM Accelerates Your AI Development Pipeline: A Deep Dive with H2O.ai
by Thomas Bennett | October 27, 2025 NVIDIA

Introduction Every AI developer faces the same frustrating cycle: you've built a promising model in your development environment, but deploying it to production feels like navigating a maze blindfolded. The gap between "it works on my laptop" and "it's serving thousands of requests per second in production" has tradit...

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Supercharge Your Self-Hosted AI: OpenWebUI + h2oGPTe
by Ishan Shrivastava, Kalana Weerakoon, Betty Candel, Shivam Bansal | September 25, 2025 Enterprise h2oGPTe, h2oGPT

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LLM DataStudio - V6.0 Release
by Nishaanthini Gnanavel, Genevieve Richards, Laksika Tharmalingam, Prathushan Inparaj | September 12, 2024 Data Preparation, Generative AI

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Fine Tuning The H2O Danube2 LLM for The Singlish Language
by Dipam Chakraborty, Kavindu Warnakulasuriya, Jordan Seow | June 03, 2024 H2O Danube, Large Language Models

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H2O Release 3.46
by Wendy Wong, Adam Valenta | April 15, 2024 H2O Release, H2O-3

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Open-Weight AI Models: A Path to Responsible Innovation
by Sri Ambati | April 04, 2024 GenAI App Store, H2O-3, Responsible AI, h2oGPT

H2O.ai response to the recent Request for Comments (RFC) issued by the National Telecommunications and Information Administration (NTIA) on open-weight AI models.

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H2O LLM DataStudio: V4.1 Release
by Nishaanthini Gnanavel, Genevieve Richards, Tarique Hussain | January 16, 2024 Data Preparation, Generative AI

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H2O Release 3.44
by Marek Novotny, Wendy Wong | October 20, 2023 H2O Release, H2O-3

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Boosting LLMs to New Heights with Retrieval Augmented Generation

Businesses today can make leaps and bounds to revolutionize the way things are done with the use of Large Language Models (LLMs). LLMs are widely used by businesses today to automate certain tasks and create internal or customer-facing chatbots that boost efficiency. Challenges with dynamic adaption of LLMs As with any new hyped-up thing that […]

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Entrenando Tu Propio LLM Sin Programación
by Favio Vazquez | October 06, 2023 Generative AI, H2O LLM Studio

This blog was originally published in English here: https://www.analyticsvidhya.com/blog/2023/09/training-your-own-llm-without-coding/ Introducción La Inteligencia Artificial Generativa, un campo fascinante que promete revolucionar cómo interactuamos con la tecnología y generamos contenido, ha causado sensación en el mundo. En este artí...

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H2O LLM DataStudio Part II: Convert Documents to QA Pairs for fine tuning of LLMs
by Genevieve Richards, Tarique Hussain, Shivam Bansal | September 22, 2023 Generative AI, H2O LLM Studio

Convert unstructured datasets to Question-answer pairs required for LLM fine-tuning and other downstream tasks with H2O LLM Data Studio Curate. Every organization needs to own its GPT as simply as it needs to bring its data, algorithms, and models (read more here). A common problem we see in organizations is that they want to be […]

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Building a Fraud Detection Model with H2O AI Cloud

In a previous article [1], we discussed how machine learning could be harnessed to mitigate fraud. This time, we’ll delve into a step-by-step guide on leveraging H2O AI Cloud to construct efficient fraud detection models. We’ll tackle this process in three critical stages: build, operate, and detect. First, we’ll utilize Driverless AI in ...

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A Look at the UniformRobust Method for Histogram Type
by Hannah Tillman, Megan Kurka | July 25, 2023 GBM, H2O-3

Tree-based algorithms, especially Gradient Boosting Machines (GBM’s), are one of the most popular algorithms used. They often out-perform linear models and neural networks for tabular data since they used a boosted approach where each tree built works to fix the error of the previous tree. As the model trains, it is continuously self-corr...

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Testing Large Language Model (LLM) Vulnerabilities Using Adversarial Attacks
by Kim Montgomery, Pramit Choudhary, Michal Malohlava | July 19, 2023 Generative AI, H2O LLM Studio, LLM Limitations, LLM Robustness, LLM Safety, Large Language Models, Responsible AI

Adversarial analysis seeks to explain a machine learning model by understanding locally what changes need to be made to the input to change a model’s outcome. Depending on the context, adversarial results could be used as attacks, in which a change is made to trick a model into reaching a different outcome. Or they could be used as an exp...

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H2O LLM EvalGPT: A Comprehensive Tool for Evaluating Large Language Models
by Srinivas Neppalli, Abhay Singhal, Michal Malohlava | July 19, 2023 Generative AI, Large Language Models, h2oGPT

In an era where Large Language Models (LLMs) are rapidly gaining traction for diverse applications, the need for comprehensive evaluation and comparison of these models has never been more critical. At H2O.ai, our commitment to democratizing AI is deeply ingrained in our ethos, and in this spirit, we are thrilled to introduce our innovati...

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Reducing False Positives in Financial Transactions with AutoML
by Asghar Ghorbani | July 14, 2023 AutoML, Data Science, H2O AI Cloud, H2O Driverless AI, Machine Learning

In an increasingly digital world, combating financial fraud is a high-stakes game. However, the systems we deploy to safeguard ourselves are raising too many false alarms, with over 90% of fraud alerts being false positives. These false positives, not only frustrating for consumers but also costly for financial institutions, can eclipse t...

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Winner's Insight: Navigating the Parkinson's Disease Prediction Challenge with AI
by Parul Pandey | July 03, 2023 AI4Good, Healthcare, Kaggle, Kaggle Grandmasters, Machine Learning

Parkinson’s disease, a condition affecting movement, cognition, and sleep, is escalating rapidly. By 2037, it is projected that around 1.6 million U.S. residents will be confronting this disease, resulting in significant societal and economic challenges. Studies have hinted that disruptions in proteins or peptides could be instrumental in...

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H2O.ai and Snowflake Enable Developers to Train, Deploy, and Score Containerized Software Without Compromising Data Security
by Eric Gudgion | June 27, 2023 H2O Driverless AI, H2O-3, Machine Learning, Snowflake

H2O.ai today announced its participation as a launch partner for Snowflake’s Snowpark Container Services (available in private preview), which provides our joint customers with the flexibility to train, deploy, and score models all within their Snowflake account. This further expands the ease of use for data science teams to create machin...

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H2O Releases 3.40.0.1 and 3.42.0.1
by Marek Novotny, Wendy Wong | June 23, 2023 GBM, GLM, H2O Release, H2O-3, XGBoost

Our new major releases of H2O are packed with new features and fixes! Some of the major highlights of these releases are the new Decision Tree algorithm, the added ability to grid over Infogram, an upgrade to the version of XGBoost and an improvement to its speed, the completion of the maximum likelihood dispersion parameter and its expan...

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H2O LLM DataStudio: Streamlining Data Curation and Data Preparation for LLMs related tasks
by Shivam Bansal, Sanjeepan Sivapiran, Nishaanthini Gnanavel | June 14, 2023 Data, Data Preparation, H2O LLM Studio, Large Language Models, NLP, h2oGPT

A no-code application and toolkit to streamline data preparation tasks related to Large Language Models (LLMs) H2O LLM DataStudio is a no-code application designed to streamline data preparation tasks specifically for Large Language Models (LLMs). It offers a comprehensive range of preprocessing and preparation functions such as text cl...

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Recap of H2O World India 2023: Advancements in AI and Insights from Industry Leaders
by Parul Pandey | May 29, 2023 AI4Good, Community, H2O World

On April 19th, the H2O World made its debut in India, marking yet another milestone in its global journey. The conference gathered an array of notable experts and enthusiasts from deep learning, artificial intelligence, and data science. A broad spectrum of topics was covered, shedding light on the strides made in AI technology and its ...

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Enhancing H2O Model Validation App with h2oGPT Integration
by Parul Pandey | May 17, 2023 Deep Learning, H2O Model Validation, h2oGPT

As machine learning practitioners, we’re always on the lookout for innovative ways to streamline and enhance our processes. What if we could integrate the power of language models into our workflows, especially in the critical phase of model validation? Imagine running validation procedures, interpreting results, or even troubleshooting i...

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Building a Manufacturing Product Defect Classification Model and Application using H2O Hydrogen Torch, H2O MLOps, and H2O Wave
by Shivam Bansal, Genevieve Richards, Nishaanthini Gnanavel | May 15, 2023 H2O Hydrogen Torch, H2O Wave, MLOps, Manufacturing

Primary Authors: Nishaanthini Gnanavel and Genevieve Richards Effective product quality control is of utmost importance in the manufacturing industry. The presence of defective components can have adverse effects on various aspects, including escalating production costs, compromising product quality, diminishing product longevity, and l...

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Democratization of LLMs
by Sri Ambati | May 08, 2023 H2O LLM Studio, Large Language Models, h2oGPT

Every organization needs to own its GPT as simply as we need to own our data, algorithms and models. H2O LLM Studio democratizes LLMs for everyone allowing customers, communities and individuals to fine-tune large open source LLMs like h2oGPT and others on their own private data and on their servers. Every nation, state and city needs it...

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Building the World's Best Open-Source Large Language Model: H2O.ai's Journey
by Arno Candel | May 03, 2023 Large Language Models, h2oGPT

At H2O.ai, we pride ourselves on developing world-class Machine Learning, Deep Learning, and AI platforms. We released H2O, the most widely used open-source distributed and scalable machine learning platform, before XGBoost, TensorFlow and PyTorch existed. H2O.ai is home to over 25 Kaggle grandmasters, including the current #1. In 2017, w...

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Effortless Fine-Tuning of Large Language Models with Open-Source H2O LLM Studio
by Parul Pandey | May 01, 2023 H2O LLM Studio, Large Language Models

While the pace at which Large Language Models (LLMs) have been driving breakthroughs is remarkable, these pre-trained models may not always be tailored to specific domains. Fine-tuning — the process of adapting a pre-trained language model to a specific task or domain—plays a critical role in NLP applications. However, fine-tuning can be ...

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What's new in the latest release of H2O AI Hybrid Cloud?
by Michelle Tanco | April 25, 2023 H2O AI App Store, Hybrid Cloud, Product Updates

Check out the complete release notes here! v23.01.0 | Apr 14, 2023 Upgraded ComponentsCore Components AI App Storev0.22.0 The AI App Store is a platform for accessing and operationalizing AI/ML applications and services that are built using H2O Wave . The 23.01.0 Hybrid Cloud release introduces multiple UI enhancements to make the us...

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Navigating the challenges of time series forecasting
by Jon Farland | April 12, 2023 Time Series

Jon Farland is a Senior Data Scientist and Director of Solutions Engineering for North America at H2O.ai. For the last decade, Jon has worked at the intersection of research, technology and energy sectors with a focus on developing large scale and real-time hierarchical forecasting systems. The machine learning models that drive these for...

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How Commonwealth Bank is transforming operations with Document AI
by Liz Pratusevich | April 11, 2023 H2O Document AI, H2O World

Sonal Surana , General Manager at Commonwealth Bank of Australia shares recent innovative ideas at H2O World Sydney. It’s been a rollercoaster of a ride this first year of our partnership with H2O.ai, and the momentum continues to get even more exciting. We’ve heard from Matt about our AI ambition and how front and center it is for CBA s...

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Introduction to H2O Document AI
by Mark Landry | April 05, 2023 H2O Document AI, H2O World

Mark Landry, H2O.ai Director of Data Science and Product, and Kaggle Grandmasters showcases H2O Document AI during the Technical Track Sessions at H2O World Sydney 2022. Mark Landry: I’m Mark Landry, with some different titles than you see on the screen here. I’ve got a bunch at H2O, so I’ve been at H2O for about seven and a half years...

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AI in Insurance: Resolution Life's AI Journey with Rajesh Malla
by Liz Pratusevich | March 29, 2023 H2O Driverless AI, H2O Hydrogen Torch, H2O World, Insurance

Rajesh Malla , Head of Data Engineering – Data Platforms COE at Resolution Life insurance takes the stage at H2O World Sydney 2022 to discuss AI transformation within the insurance industry. Resolution Life is the largest life insurer in Australasia. Malla discusses the use of H2O Driverless AI to predict claim triage and other insurance ...

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AT&T panel: AI as a Service (AIaaS)
by Liz Pratusevich | March 22, 2023 H2O World

Mark Austin, Vice President of Data Science at AT&T joined us on stage at H2O World Dallas, along with his colleagues Mike Berry, Lead Solution Architect; Prince Paulraj, AVP of Engineering; Alan Gray, Principal-Solutions Architect; and Rob Woods, Lead Solution Architect, CDO to discuss what they’re doing today and where they see the ...

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[Infographic] Healthcare providers: How to avoid AI “Pilot-Itis”
by H2O.ai Team | March 15, 2023 Healthcare

From increased clinician burnout and financial instability to delays in elective and preventative care, the pandemic created a perfect storm of conditions that have strained the healthcare system in lasting ways. This storm continues unabated and is unleashing new challenges and exacerbating old ones. Artificial intelligence (AI) technol...

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Deploy a WAVE app on an AWS EC2 instance
by Michelle Tanco, Greg Fousas | March 10, 2023 H2O Wave, Make with H2O.ai

This article was originally published by Greg Fousas and Michelle Tanco on Medium and reviewed by Martin Turoci (unusualcode) This guide will demonstrate how to deploy a WAVE app on an AWS EC2 instance. WAVE can run on many different OSs (macOS, Linux, Windows) and architectures (Mac, PC). In this document, Ubuntu Linux will be used. T...

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How Horse Racing Predictions with H2O.ai Saved a Local Insurance Company $8M a Year
by Liz Pratusevich | March 08, 2023 H2O World, Insurance, Machine Learning, Snowflake, Use Cases

In this Technical Track session at H2O World Sydney 2022, SimplyAI’s Chief Data Scientist Matthew Foster explains his journey with machine learning and how applying the H2O framework resulted in significant success on and off the race track. Matthew Foster: I’m Matthew Foster, the Chief Data Scientist for SimplyAI. So, I’m going t...

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AI and Humans Combating Extinction Together with Dr. Tanya Berger-Wolf
by Liz Pratusevich | March 01, 2023 Artificial Intelligence, H2O World

Dr. Tanya Berger-Wolf , Co-Founder and Director of AI for conservation nonprofit Wild Me , takes the stage at H2O World Sydney 2022 to discuss AI solutions for wildlife conservation, connecting data, people, and machines. AI can turn a massive collection of images into high-resolution information databases about wildlife, enabling scienti...

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Improving Search Query Accuracy: A Beginner's Guide to Text Regression with H2O Hydrogen Torch
by H2O.ai Team | February 28, 2023 Deep Learning, H2O Hydrogen Torch, Machine Learning

Although search engines are vital to our daily lives, they need help understanding complex user queries. Search engines rely on natural language processing (NLP) to understand the intent behind a user’s query and return relevant results. By formulating a well-formed question, users can provide more precise and specific information about w...

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10 Consejos para Convertirte en un Científico de Datos Exitoso
by Favio Vazquez | January 19, 2023 AutoML, Beginners, Data Science

La ciencia de datos llegó para quedarse. Los científicos de datos utilizan sus habilidades para ayudar a las empresas a tomar mejores decisiones sobre sus productos, servicios, a optimizar procesos, ahorrar y mejorar rentabilidad. Convertirse en un científico de datos de éxito implica muchos aspectos y el estudio continuo, ya que es un...

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Test Page
by H2O.ai Team | June 26, 2025

testing new heights ...

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by H2O.ai Team | June 26, 2025

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by Arno Candel, Ashrith Barthur | June 26, 2025 Blog, H2O AI Cloud, Machine Learning

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