H2O.ai Blog

Agentic AI at Scale: Unlocking Enterprise Value with Domain-Specific LLMs and Exabyte Data

Agents | Building your first Agent step-by-step with h2oGPTe & LLM Chains

Fine Tuning The H2O Danube2 LLM for The Singlish Language

Announcing H2O Danube 2: The next generation of Small Language Models from H2O.ai

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 […]

A Look at the UniformRobust Method for Histogram Type

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...

Testing Large Language Model (LLM) Vulnerabilities Using Adversarial Attacks

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...

H2O LLM EvalGPT: A Comprehensive Tool for Evaluating Large Language Models

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...

Reducing False Positives in Financial Transactions with AutoML

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...

Winner's Insight: Navigating the Parkinson's Disease Prediction Challenge with AI

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...

H2O.ai and Snowflake Enable Developers to Train, Deploy, and Score Containerized Software Without Compromising Data Security

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...

H2O Releases 3.40.0.1 and 3.42.0.1

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...

Generating LLM Powered Apps using H2O LLM AppStudio – Part1: Sketch2App

H2O LLM DataStudio: Streamlining Data Curation and Data Preparation for LLMs related tasks

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...

Enhancing H2O Model Validation App with h2oGPT Integration

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...

Democratization of LLMs

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...

Building the World's Best Open-Source Large Language Model: H2O.ai's Journey

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...

Effortless Fine-Tuning of Large Language Models with Open-Source H2O LLM Studio

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 ...

How Horse Racing Predictions with H2O.ai Saved a Local Insurance Company $8M a Year

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...

Improving Search Query Accuracy: A Beginner's Guide to Text Regression with H2O Hydrogen Torch

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...