While only about 1% of companies are making the most of their data today, real progress is being made in democratizing the use of AI, and the future of business automation via AI is quite bright, H2O.ai's CEO and founder Sri Ambati said before a pair of H2O World conferences this week. "There's still a long way to go from where we are. It's in the earliest phases of adoption," Ambati told Datanami in an interview earlier this month. "You can see that only 1%, or less than 1%, of the world's companies can truly leverage their data. So that means 99% needs further adoption, simplification, and cultural transformation to use data and AI. It's going to take the next 10 to 20 years."

If you came here looking for an introduction to water, or a synopsis of the 2003 TV series about teenage mermaids you have sadly come to the wrong place. The H2O that we will talk about is H2O.ai, a company which develops products for easy, scalable, machine learning and artificial intelligence. Machine learning and artificial intelligence (or AI for short) are topics which have had a lot of interest over the past 4-5 years. Some of this interest has come from businesses as they begin to utilise the information they collect on a day-to-day basis to streamline/automate processes or gain insight. A lot of companies are now looking to hire data scientists/engineers and in turn this is making a lot more people interested in machine learning and AI.

H2O.ai is based in Mountain View, California and offers a suite of Machine Learning platforms. H2O's core strength is its high-performing ML components, which are tightly integrated. H2O.ai is a Visionary in the Gartner Magic Quadrant for Data Science Platforms in its report released in Jan'2019. Let's take a brief look at the offerings of H2O.ai: H2O is an open-source, distributed in-memory machine learning platform with linear scalability. H2O supports the most widely used statistical & machine learning algorithms and also has an AutoML functionality.

At H2O.ai, it is our goal to democratize AI by bridging the gap between the State-of-the-Art (SOTA) in machine learning and a user-friendly, enterprise-ready platform. We have been working tirelessly to bring the SOTA from Kaggle competitions to our enterprise platform Driverless AI since its very first release. The growing list of Driverless AI features and our growing team of Kaggle Grandmasters and industry expert data scientists can be seen as our effort and commitment to achieve that goal. Today, we are excited to announce the availability of our latest Driverless AI release 1.9 which comes with tons of new features. This article is the first of the 1.9 release blog series.

Navdeep Gill, Senior Data Scientist and Software Engineer at H2O.ai and Patrick Hall, Advisory Consultant at H2O.ai Utilization of artificial intelligence (AI) and machine learning models have become a common practice in many aspects of the economy. Furthermore, more sections of the economy will start to embrace automation and data-driven decision making over the coming years. While these predictive systems can be quite accurate, they have been treated as inscrutable black boxes in the past, that produce only numeric predictions with no accompanying explanations. Unfortunately, recent studies and recent events have drawn attention to mathematical and sociological flaws in prominent weak AI and ML systems, but practitioners usually don't have the right tools to pry open machine learning black-boxes and debug them. This presentation goes over how one can use Driverless AI to increase transparency, accountability, and trustworthiness in machine learning models.

According to PwC, AI's potential global economic impact will reach USD 15.7 trillion by 2030. However, the enterprises who look to deploy AI are often hampered by the lack of time, trust and talent. Especially, with the highly regulated sectors such as healthcare and finance, convincing the customers to imbibe AI methodologies is an uphill task. Of late, the AI community has seen a sporadic shift in AI adoption with the advent of AutoML tools and introduction of customised hardware to cater to the needs of the algorithms. One of the most widely used AutoML tools in the industry is H2O Driverless AI.

MOUNTAIN VIEW, Calif., June 4, 2020 – H2O.ai announced the availability of H2O Driverless AI integration, a leading automatic machine learning (AutoML) platform, with Snowflake, the Cloud Data Platform. This new integration enables Snowflake users to easily build and deploy ML models. Driverless AI automates the time consuming and demanding data science and machine learning workflows such as feature engineering, model tuning and model selection to achieve the highest predictive accuracy within the shortest time. The seamless integration of H2O Driverless AI with the Snowflake Cloud Data Platform is another step towards democratizing AI for all and empowering every company to be an AI company. "H2O.ai and Snowflake are in a unique position to help our customers adapt in the rapidly emergent business landscape and win with artificial intelligence on the cloud," said Sri Ambati, CEO and Founder of H2O.ai.

H2O.ai, the open source leader in artificial intelligence (AI) and machine learning (ML), today announced the availability of H2O Driverless AI integration, a leading automatic machine learning (AutoML) platform, with Snowflake, the Cloud Data Platform. This new integration enables Snowflake users to easily build and deploy ML models. Driverless AI automates the time consuming and demanding data science and machine learning workflows such as feature engineering, model tuning and model selection to achieve the highest predictive accuracy within the shortest time. The seamless integration of H2O Driverless AI with the Snowflake Cloud Data Platform is another step towards democratizing AI for all and empowering every company to be an AI company. "H2O.ai and Snowflake are in a unique position to help our customers adapt in the rapidly emergent business landscape and win with artificial intelligence on the cloud," said Sri Ambati, CEO and Founder of H2O.ai.

Credit Suisse's DTR Program recognizes the top companies who are disrupting traditional IT with new, visionary, and innovative approaches. "At Credit Suisse, technology innovation is key to providing the best user experience and for our customers and partners," said David Patten, CIO of Credit Suisse's IBCM Division at Credit Suisse AG. "The DTR program was created to recognize the companies that are disrupting the status quo in IT with great products and a clear vision in their respective spaces. H2O.ai is a clear leader in the AI and machine learning space, and continues to push the boundaries on what is possible with these technologies, and helps us deliver high-quality services to our clients." "H2O.ai is honored to be selected into the coveted Credit Suisse's DTR program this year. We are democratizing AI and the trusted partner in the AI transformation of world's leading and sophisticated companies like Credit Suisse," said Sri Ambati, CEO and Founder at H2O.ai.

Wall Street Endorses H2O.ai's Vision to Democratize AI H2O.ai, the open source leader in artificial intelligence (AI) and machine learning (ML), announced that Credit Suisse has selected it as a member of its 2019 Disruptive Technology Recognition (DTR) Program. Credit Suisse's DTR Program recognizes the top companies who are disrupting traditional IT with new, visionary, and innovative approaches. "At Credit Suisse, technology innovation is key to providing the best user experience and for our customers and partners," said David Patten, CIO of Credit Suisse's IBCM Division at Credit Suisse AG. "The DTR program was created to recognize the companies that are disrupting the status quo in IT with great products and a clear vision in their respective spaces. H2O.ai is a clear leader in the AI and machine learning space, and continues to push the boundaries on what is possible with these technologies, and helps us deliver high-quality services to our clients."