H2O LLM DataStudio: V5.0 Release: Automatically Create your own Evaluation datasets (Custom RAG Evals)

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

A new series of Small Language Models from H2O.ai, released under Apache 2.0 and ready to be fine-tuned for your specific needs to run offline and with a smaller footprint. Why Small Language Models? Like most decisions in AI and tech, the decision of which Language Model to use for your production use cases comes down to trade-offs. ...

Open-Weight AI Models: A Path to Responsible Innovation

The recent Request for Comments (RFC) issued by the National Telecommunications and Information Administration (NTIA) on open-weight AI models has sparked an important conversation about the future of AI. As we consider the potential benefits and risks associated with making AI model weights more accessible and transparent, it is clear ...

Transformando Empresas Latinoamericanas con Inteligencia Artificial: Estrategias y Perspectivas

En la actualidad podemos reconocer que hay una alta emoción en foros y publicaciones acerca del uso de inteligencia artificial (IA) en diferentes ámbitos empresariales, muchas veces se habla de los grandes cambios que conlleva el uso de la IA en procesos de negocios sin embargo estos casos de uso exitosos en su mayoría pertenecen a com...

Unlocking GenAI Magic: GenAI AppStudio Revolutionizes App Development with LLMs! (Part 2)

GenAI AppStudio provides a no code way to take user sketches and generates the code for you. DEMO   Introducing GenAI AppStudio GenAI AppStudio is a no-code platform specifically crafted for non-technical users, to easily transform app ideas into reality with a few simple steps. One of its key features is the ability to sea...

H2O LLM DataStudio: V4.1 Release

H2O LLM DataStudio is a comprehensive no-code application designed to simplify data preparation tasks for Large Language Models (LLMs). This tool comprises three key components: Curate, Prepare, and Augment. Curate - Conversion of documents (PDFs, DOC & audio/video files) into question-answer pairs and summarization pairs Prepare ...

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 ...

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 ...

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 ...

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...

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...

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...

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...

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...

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...

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 ...

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...

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...

Explaining models built in H2O-3 — Part 1

Machine Learning explainability refers to understanding and interpreting the decisions and predictions made by a machine learning model. Explainability is crucial for ensuring the trustworthiness and transparency of machine learning models, particularly in high-stakes situations where the consequences of incorrect predictions can be signi...

H2O.ai at NeurIPS 2022

H2O.ai is proud to participate in the 36th Conference on Neural Information Processing Systems (NeurIPS) 2022, one of the biggest and most prestigious international conferences in artificial intelligence. NeurIPS 2022 will be a Hybrid Conference from Monday, November 28th through Friday, December 9th, with an in-person event at the New Or...

A Brief Overview of AI Governance for Responsible Machine Learning Systems

Our paper “A Brief Overview of AI Governance for Responsible Machine Learning Systems” was recently accepted to the Trustworthy and Socially Responsible Machine Learning (TSRML) workshop at NeurIPS 2022 (New Orleans). In this paper, we discuss the framework and value of AI Governance for organizations of all sizes, across all industries a...

Saving Zebras: “Their stripes are like fingerprints. No two are alike.”

It’s been said that a picture is worth a thousand words. But to Tanya Berger-Wolf, a picture is far more valuable than that. To Berger-Wolf, photos, images and videos are key to protecting biodiversity and entire species around the world. Scientists have known for years that we are in the middle of the sixth mass extinction on our planet...

AI for Good: PetFinder.my Levels Up Furry Matchmaking

Nothing tugs at the heart strings quite like a poster in your neighborhood about a missing cat or dog. For years, technology has enabled lost pets to be reunited with their families in the form of a small microchip that contains an owner’s contact information. Now some organizations are turning to emerging technology to help the millions ...

Three Keys to Ethical Artificial Intelligence in Your Organization

There’s certainly been no shortage of examples of AI gone bad over the past few years–enough to give everyone pause on how (and if) this technology can truly be used for good. If it’s not Facebook selling data of its users , it’s self-driving cars from Uber that can’t recognize pedestrians in time to slow down or stop. So while the uses ...

Advice for Those Getting Started on Their AI Journey

H2O.ai Innovation Day Summer ‘22 included a customer insights panel made up of Prince Paulraj, AVP, Data Insights and Chief Data Officer at AT&T , Chris Throop, Managing Director and Global Head of Data Science at Castleton Commodities International and Sean Otto, Director of Advanced Analytics at AES . One of the questions panelists...

The H2O.ai Wildfire Challenge Winners Blog Series - Team Titans

Note : this is a community blog post by Team Titans – one of the H2O.ai Wildfire Challenge winners. You can check out their app here .BackgroundForest fires have been getting worse in recent years. According to a report by the WWF, the duration of fire seasons across the globe has increased by 19% on average. The fire season has been sta...

Improving Manufacturing Quality with H2O.ai and Snowflake

Manufacturers are rapidly expanding their machine learning use cases by leveraging the deep integration between Snowflake’s Data Cloud and the H2O AI Cloud. Many current manufacturing quality checks require that sensor data and image data be processed and analyzed separately. Standard tooling presents challenges in storing and referencin...

The H2O.ai Wildfire Challenge Winners Blog Series - Team PSR

Note : this is a community blog post by Team PSR – one of the H2O.ai Wildfire Challenge winners.This blog represents an experience we gained by participating in the H2O wildfire challenge. We need to mention that competing in this challenge is like a journey in a knowledge pool. For a person who is willing to get the knowledge of buildin...

The H2O.ai Wildfire Challenge Winners Blog Series - Team HTB

Note : this is a community blog post by Team HTB – one of the H2O.ai Wildfire Challenge winners. You can check out their app here . The Challenge The purpose of the challenge was to develop an AI application to improve the forecast of bushfires and wildfires, with the main aim of reducing the human losses that these phenomena can cause...

The H2O.ai Wildfire Challenge Winners Blog Series - Team Too Hot Encoder

Note : this is a community blog post by Team Too Hot Encoder – one of the H2O.ai Wildfire Challenge winners. You can check out their app here .The ChallengeThe aim of the project is to predict the probability of wildfire occurrence in Turkey for each month in 2020. As a result of these predictions, it is aimed to carry out more intensive...

Bias and Debiasing

An important aspect of practicing machine learning in a responsible manner is understanding how models perform differently for different groups of people, for instance with different races, ages, or genders. Protected groups frequently have fewer instances in a training set, contributing to larger error rates for those groups. Some models...

Comprehensive Guide to Image Classification using H2O Hydrogen Torch

In this article, we will learn how to build state-of-the-art models in computer vision and natural language processing within a couple of minutes using H2O Hydrogen Torch. Introduction to H2O Hydrogen Torch H2O Hydrogen Torch (HT) aims to simplify building and deploying deep learning models for a wide range of tasks in computer vision...

Tackling Illegal, Unreported, and Unregulated (IUU) Fishing with AI

According to a report by the High-Level Panel for a Sustainable Ocean Economy, it is estimated that illegal, unreported, and unregulated (IUU) fishing accounts for 20 percent of the seafood and up to 50 percent in some areas. These activities not only affect the marine ecosystem but, in a way, are linked to climate change on the planet a...

A Quick Introduction to PyTorch: Using Deep Learning for Stock Price Prediction

Torch is a scalable and efficient deep learning framework. It offers flexibility and speed to build large scale applications. It also includes a wide range of libraries for developing speech, image, and video-based applications. The basic building block of Torch is called a tensor. All the operations defined in Torch use a tensor. Ok, l...

Introducing H2O Hydrogen Torch: A No-code Deep Learning Framework

Over and over again we heard from customers, “deep learning is cool, but it’s hard and time consuming.” They kept asking “could someone just make it easier?” In typical “Maker” fashion, you ask, we deliver, H2O Hydrogen Torch . H2O Hydrogen Torch is a new product that enables data scientists and developers to train and deploy state-of-t...

Shapley Values - A Gentle Introduction

If you can’t explain it to a six-year-old, you don’t understand it yourself. – Albert Einstein One fear caused by machine learning (ML) models is that they are blackboxes that cannot be explained. Some are so complex that no one, not even domain experts, can understand why they make certain decisions. This is of particular concern when s...

Introducing the H2O.ai Wildfire Challenge

We are excited to announce our first AI competition for good – H2O.ai Wildfire Challenge .We’ve structured this challenge to be a global collaborative effort to do good for the world that we share. We want teams to submit their ideas and applications freely, knowing that other teams will learn from what they’ve done to improve their AI ap...

How Much is My Property Worth?

Note : this is a guest blog post by Jaafar Almusaad .How Much is My Property Worth?This is the million-dollar question – both figuratively and literally. Traditionally, qualified property valuers are tasked to answer this question. It’s a lengthy and costly process, but more critically, it’s inconsistent and largely subjective. Mind you, ...

Using AI to unearth the unconscious bias in job descriptions

“Diversity is the collective strength of any successful organization Unconscious Bias in Job DescriptionsUnconscious bias is a term that affects us all in one way or the other. It is defined as the prejudice or unsupported judgments in favor of or against one thing, person, or group as compared to another, in a way that is usually con...

H2O Driverless AI 1.9.1: Continuing to Push the Boundaries for Responsible AI

At H2O.ai, we have been busy. Not only do we have our most significant new software launch coming up (details here ), but we also are thrilled to announce the latest release of our flagship enterprise platform H2O Driverless AI 1.9.1. With that said, let’s jump into what is new: Faster Python scoring pipelines with embedded MOJOs for r...

The Importance of Explainable AI

This blog post was written by Nick Patience, Co-Founder & Research Director, AI Applications & Platforms at 451 Research, a part of S&P Global Market Intelligence From its inception in the mid-twentieth century, AI technology has come a long way. What was once purely the topic of science fiction and academic discussion is now...

Building an AI Aware Organization

Responsible AI is paramount when we think about models that impact humans, either directly or indirectly. All the models that are making decisions about people, be that about creditworthiness, insurance claims, HR functions, and even self-driving cars, have a huge impact on humans. We recently hosted James Orton, Parul Pandey, and Sudala...

The Challenges and Benefits of AutoML

Machine Learning and Artificial Intelligence have revolutionized how organizations are utilizing their data. AutoML or Automatic Machine Learning automates and improves the end-to-end data science process. This includes everything from cleaning the data, engineering features, tuning the model, explaining the model, and deploying it into p...

3 Ways to Ensure Responsible AI Tools are Effective

Since we began our journey making tools for explainable AI (XAI) in late 2016, we’ve learned many lessons, and often the hard way. Through headlines, we’ve seen others grapple with the difficulties of deploying AI systems too. Whether it’s: a healthcare resource allocation system that likely discriminated against millions of black peop...

5 Key Considerations for Machine Learning in Fair Lending

This month, we hosted a virtual panel with industry leaders and explainable AI experts from Discover, BLDS, and H2O.ai to discuss the considerations in using machine learning to expand access to credit fairly and transparently and the challenges of governance and regulatory compliance. The event was moderated by Sri Ambati, Founder and CE...

From GLM to GBM – Part 2

How an Economics Nobel Prize could revolutionize insurance and lending Part 2: The Business Value of a Better ModelIntroductionIn Part 1 , we proposed better revenue and managing regulatory requirements with machine learning (ML). We made the first part of the argument by showing how gradient boosting machines (GBM), a type of ML, can mat...

From GLM to GBM - Part 1

How an Economics Nobel Prize could revolutionize insurance and lending Part 1: A New Solution to an Old ProblemIntroductionInsurance and credit lending are highly regulated industries that have relied heavily on mathematical modeling for decades. In order to provide explainable results for their models, data scientists and statisticians i...

Lessons of COVID-19 and Moving Forward: Key Takeaways

This week, we hosted our second virtual panel focused on how AI can empower healthcare organizations to make better decisions and save lives. Improved forecasting and predictions lead to higher chances in managing and mitigating adverse events, such as the COVID-19 pandemic. I’m proud to acknowledge that H2O.ai is committed to helping cus...

Brief Perspective on Key Terms and Ideas in Responsible AI

INTRODUCTIONAs fields like explainable AI and ethical AI have continued to develop in academia and industry, we have seen a litany of new methodologies that can be applied to improve our ability to trust and understand our machine learning and deep learning models. As a result of this, we’ve seen several buzzwords emerge. In this short po...

Three Ways Data and AI is Helping Against COVID19

We are in the midst of a global crisis that epidemiologists have warned us about. As of today, 180 countries and sovereign regions have confirmed cases of patients infected with COVID19 (from here ). Putting aside evidence that indicates the virulence of the disease could be much worse, the fast spread of the virus and the presence of hi...

Igniting the AI in Healthcare Community

Yesterday we held our first Community Discussion on AI in Healthcare. Our CEO and founder, Sri Ambati led the discussion between Niki Athanasiadou, Marios Michailidis, one of our Grandmasters , and myself. We had nearly 1,300 participants registered from over 45 countries, and over half of those joined live others are viewing the replay. ...

COVID-19: Doing Good with Data + AI

During times of severe societal strain, individuals have historically shown an inclination to offer aid and assistance. Often these sacrifices have been at great cost to life or livelihood. In other cases, the efforts have been seemingly more mundane but nevertheless still essential. The efforts of the over 10,000 women code breakers of W...

How H2O.ai is Reinventing Healthcare with AI

H2O.ai is hosting a virtual Meetup on AI and Healthcare: Best Practices for Better Outcomes. Join us on 26th March, for a community discussion to collaborate with us and leading healthcare organizations to share ideas and best practices including predicting hospital staffing needs, ICU transfers, as well as sepsis detection and more. Reg...

Summary of a Responsible Machine Learning Workflow

A paper resulting from a collaboration between H2O.AI and BLDS, LLC was recently published in a special “Machine Learning with Python” issue of the journal, Information (https://www.mdpi.com/2078-2489/11/3/137). In “A Responsible Machine Learning Workflow with Focus on Interpretable Models, Post-hoc Explanation, and Discrimination Testing...

It is a privilege to serve the world in its hour of need – H2O.ai response to the COVID-19 pandemic

During the COVID-19 pandemic, our world, our nations, states, counties, cities and communities face an unprecedented challenge with an urgent need to help our citizens and ultimately our national and global economy. At highest risk are senior citizens, at-risk populations (individuals with immunodeficiency, hypertension, diabetes) and our...

Health Outcomes and the Miracle of Data

In 1846, a physician named Ignatz Semmelweis, located at the Allgemeine Krankenhaus in Vienna, faced a dire healthcare crisis. He observed that the maternity ward in his own hospital (as well as those in other area hospitals) had a maternal mortality rate of over 15%. That is, one out of every six mothers who came to his hospital to give ...

Insights From the New 2020 Gartner Magic Quadrant For Cloud AI Developer Services

We are excited to be named a Visionary in the new Gartner Magic Quadrant for Cloud AI Developer Services (Feb 2020), and have been recognized for both our completeness of vision and ability to execute in the emerging market for cloud-hosted artificial intelligence (AI) services for application developers. This is the second Gartner MQ tha...

AI & ML Platforms: My Fresh Look at H2O.ai Technology

2020: A new year, a new decade, and with that, I’m taking a new and deeper look at the technology H2O.ai offers for building AI and machine learning systems. I’ve been interested in H2O.ai since its early days as a company (it was 0xdata back then) in 2014. My involvement had been only peripheral, but now I’ve begun to work with this comp...

Interview with Patrick Hall | Machine Learning, H2O.ai & Machine Learning Interpretability

Audio Link: In this episode of Chai Time Data Science , Sanyam Bhutani interviews Patrick Hall, Sr. Director of Product at H2O.ai. Patrick has a background in Math and has completed a MS Course in Analytics.In this interview they talk all about Patrick’s journey into ML, ML Interpretability and his journey at H2O.ai, how his work has ev...

Key Takeaways from the 2020 Gartner Magic Quadrant for Data Science and Machine Learning

We are named a Visionary in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms (Feb 2020). We have been positioned furthest to the right for completeness of vision among all the vendors evaluated in the quadrant. So let’s walk you through the key strengths of our machine learning platforms. Automatic Machine Learn...

Why you should care about debugging machine learning models

This blog post was originally published here. Authors: Patrick Hall and Andrew Burt For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing p...

New Innovations in Driverless AI

What’s new in Driverless AIWe’re super excited to announce the latest release of H2O Driverless AI . This is a major release with a ton of new features and functionality. Let’s quickly dig into all of that: Make Your Own AI with Recipes for Every Use Case: In the last year, Driverless AI introduced time-series and NLP recipes to meet the...

Toward AutoML for Regulated Industry with H2O Driverless AI

Predictive models in financial services must comply with a complex regime of regulations including the Equal Credit Opportunity Act (ECOA), the Fair Credit Reporting Act (FCRA), and the Federal Reserve’s S.R. 11-7 Guidance on Model Risk Management. Among many other requirements, these and other applicable regulations stipulate predictive ...

Building an Interpretable & Deployable Propensity AI/ML Model in 7 Steps…

To start with, you may have a tabular data set with a combination of: Dates/Timestamps Categorical Values Text strings Numeric Values A business sponsor wants to build a Propensity to Buy model from historical data.How many Steps does it take? Let’s find out. We are going to use H2O’s Driverless AI instance with 1 GPU (optional...

Can Your Machine Learning Model Be Hacked?!

I recently published a longer piece on security vulnerabilities and potential defenses for machine learning models. Here’s a synopsis.IntroductionToday it seems like there are about five major varieties of attacks against machine learning (ML) models and some general concerns and solutions of which to be aware. I’ll address them one-by-o...

H2O World Explainable Machine Learning Discussions Recap

Earlier this year, in the lead up to and during H2O World, I was lucky enough to moderate discussions around applications of explainable machine learning (ML) with industry-leading practitioners and thinkers. This post contains links to these discussions, written answers and pertinent resources for some of the most common questions asked ...

How to explain a model with H2O Driverless AI

The ability to explain and trust the outcome of an AI-driven business decision is now a crucial aspect of the data science journey. There are many tools in the marketplace that claim to provide transparency and interpretability around machine learning models but how does one actually explain a model? H2O Driverless AI provides robust inte...

What is Your AI Thinking? Part 3

In the past two posts we’ve learned a little about interpretable machine learning in general. In this post, we will focus on how to accomplish interpretable machine learning using H2O Driverless AI . To review, the past two posts discussed: Exploratory data analysis (EDA) Accurate and interpretable models Global explanations Local...

What is Your AI Thinking? Part 2

Explaining AI to the Business PersonWelcome to part 2 of our blog series: What is Your AI Thinking? We will explore some of the most promising testing methods for enhancing trust in AI and machine learning models and systems. We will also cover the best practice of model documentation from a business and regulatory standpoint.More Techniq...

What is Your AI Thinking? Part 1

Explaining AI to the Business PersonExplainable AI is in the news, and for good reason. Financial services companies have cited the ability to explain AI-based decisions as one of the critical roadblocks to further adoption of AI for their industry . Moreover, interpretability, fairness, and transparency of data-driven decision support sy...

How This AI Tool Breathes New Life Into Data Science

Ask any data scientist in your workplace. Any Data Science Supervised Learning ML/AI project will go through many steps and iterations before it can be put in production. Starting with the question of “Are we solving for a regression or classification problem?” Data Collection & Curation Are there Outliers? What is the Distribu...

Interpretability: The missing link between machine learning, healthcare, and the FDA?

Recent advances enable practitioners to break open machine learning’s “black box”.From machine learning algorithms guiding analytical tests in drug manufacture, to predictive models recommending courses of treatment, to sophisticated software that can read images better than doctors, machine learning has promised a new world of healthcar...