Google Cloud enables organizations to digitally transform themselves into smarter businesses. It offers cloud computing, data analytics, and the latest artificial intelligence (AI) and machine learning tools.

Using our AI research, we’re improving these solutions for Google Cloud customers around the world.

Our research focuses on deciphering written documents, increasing the value of wind energy, and making it easier to use AlphaFold, our groundbreaking AI system designed to better predict protein structures.

Expanding Product Innovation in Document AI

From cuneiform tablets to the printing press, there have been countless ways to share written knowledge throughout history. Modern documents vary by country, language, and industry, making it difficult to extract and use that information, especially on a large scale.

Google Cloud’s Document AI enables users to make digital, printed, or handwritten information in a document, such as an invoice or tax form, extractable and retrievable.

Before Document AI, industries looking to use AI tools for document understanding required massive amounts of training data to perform well. But this data is often unavailable, incomplete, or lacks proper annotation, hindering widespread AI adoption.

Together with the Google Cloud Document AI team, we built innovative machine learning models that require 50-70% less training data than other models to process documents like utility bills and purchase orders.

We are also working to improve Document AI performance in languages ​​with smaller datasets, so we can help more customers across industries and geographies realize the benefits of Document AI.

Increasing the value of wind energy

As part of our efforts to use AI to achieve net zero emissions by 2030, we’ve partnered with Google Cloud Professional Services to advance the wind energy sector and help create a carbon-free future for all.

Wind farms are a major source of carbon-free electricity, but their output can fluctuate depending on the weather. To balance supply and demand in the grid, operators rely on forecasts of energy generation. If operators can commit to selling a certain amount of electricity based on the next day’s forecast, they can get a better price.

In partnership with Google Cloud, we helped develop a custom AI tool to better predict wind energy production. This tool is trained on weather forecasts and the customer’s historical wind turbine data. An additional model recommends how much energy an operator can commit to delivering to the grid a day in advance.

Global energy and renewables provider ENGIE is now testing this technology in Germany. If the pilot is successful, ENGIE can roll out the technology across Europe. Making wind energy more economically attractive — and improving its reliability — will boost the uptake of renewables. That’s a win-win for everyone.

Making AlphaFold more user-friendly with Vertex AI

Developing a new machine learning model involves many stages, from design to deployment. It also requires a good data infrastructure. To support data scientists and businesses, Google Cloud built Vertex AI, a single platform to access machine learning tools for every step of the development journey.

After releasing our groundbreaking AlphaFold system, which accurately predicts the 3D structure of proteins, we made it available on Vertex AI. Now, scientists working in fields as diverse as drug discovery or the fight against plastic pollution can more easily execute the AlphaFold prediction workflow by tracking experiments, optimizing hardware selection, and managing it all at scale.

In 2022, we also expanded the AlphaFold Protein Structure Database to include nearly all catalogued proteins known to science. We partnered with Google Cloud to host this massive database, offering over 200 million proteins for bulk download. Billions of structures have been downloaded, and the database quickly became an essential resource for the scientific community, fueling a new wave of advances in biology.