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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 LLM DataStudio

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
by Asghar Ghorbani July 28, 2023 AutoML H2O AI Cloud H2O Driverless AI Uncategorized [EN]

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 H2O AI Cloud […]

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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-correcting. H2O-3’s GBM is […]

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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 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, our commitment to democratizing AI is deeply ingrained in our ethos, and in this spirit, we are thrilled to introduce our innovative tool, […]

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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 Large language models LLM Limitations LLM Robustness LLM Safety 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 […]

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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 Uncategorized [EN]

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 the cost of the […]

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Winner’s Insight: Navigating the Parkinson’s Disease Prediction Challenge with AI
by Parul Pandey July 3, 2023 AI for Good 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 the disease’s onset and progression. Consequently, delving […]

Read More 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 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 machine learning models and deployment […]

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