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Introducing the H2O GenAI App Store: A Playground of Generative AI Innovation
As the world becomes increasingly interconnected and reliant on data-driven decisions, the need for powerful and innovative AI solutions has never been more critical. At H2O.ai, we've been at the forefront of AI and machine learning for the last decade, providing you with the tools and platforms to harness the power of data. Today, we're ...
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Apresentamos a H2O GenAI App Store: um Playground de Inovação em Inteligência Artificial Generativa.
This blog was originally published in English here: https://h2o.ai/blog/2023/gen-ai-app-store/ À medida que o mundo se torna cada vez mais interconectado e dependente de decisões orientadas por dados, a necessidade de soluções de IA poderosas e inovadoras nunca foi tão crítica. Na H2O.ai, estivemos na vanguarda da IA e do aprendizado de ...
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Presentamos la H2O GenAI App Store: Un Playground de Innovación en Inteligencia Artificial Generativa.
This blog was originally published in English here: https://h2o.ai/blog/2023/gen-ai-app-store/ A medida que el mundo se vuelve cada vez más interconectado y dependiente de decisiones basadas en datos, la necesidad de soluciones de inteligencia artificial (IA) potentes e innovadoras nunca ha sido tan crítica. En H2O.ai, hemos estado a la ...
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H2O Release 3.44
We are excited to announce the release of H2O-3 3.44.0.1! We have added and improved many items. A few of our highlights are the implementation of AdaBoost, Shapley values support, Python 3.10 and 3.11 support, and added custom metric support for Deep Learning, Uplift Distributed Random Forest (DRF), Stacked Ensemble, and AutoML. Please r...
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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 thi...
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Entrenando Tu Propio LLM Sin Programación
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
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 able to...
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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
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
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
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
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
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
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
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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Generating LLM Powered Apps using H2O LLM AppStudio – Part1: Sketch2App
sketch2app is an application that let users instantly convert sketches to fully functional AI applications. This blog is Part 1 of the LLM AppStudio Blog Series and introduces sketch2app The H2O.ai team is dedicated to democratizing AI and making it accessible to everyone. One of the focus areas of our team is to simplify the adoption of...
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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...
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Recap of H2O World India 2023: Advancements in AI and Insights from Industry Leaders
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
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
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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Insights from AI for Good Hackathon: Using Machine Learning to Tackle Pollution
At H2O.ai, we believe technology can be a force for good, and we’re committed to leveraging its power to create a positive impact in the world. As part of this commitment, we recently organized an AI for Good Hackathon during the H2O World India event, where participants had the opportunity to apply their data science skills to a real-wor...
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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...
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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...
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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 ...
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What's new in the latest release of H2O AI Hybrid Cloud?
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
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
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
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
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)
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”
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
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
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
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
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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What it means—and takes—to be at AI’s edge with Dr. Tim Fountaine
Dr. Tim Fountaine, Senior Partner at McKinsey & Company joins us at H2O World Sydney 2022 to discuss why business leaders should care about AI, what mindset to adopt, and what actions to take to effectively bring AI into your organization. Dr. Fountaine discusses real-world examples and insights from McKinsey’s collaboration with the ...
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10 Consejos para Convertirte en un Científico de Datos Exitoso
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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