It is estimated that between 80% and 90% of the world’s data is unstructured1, with text files and documents making up a significant portion. Every day, countless text-based documents, like contracts and insurance claims, are stored for safekeeping. Despite containing a wealth of insights, this vast trove of information often remains untapped, as the process of extracting relevant data from these documents is challenging, tedious and time-consuming.

Making informed decisions on technology adoptions and ensuring the sustained growth and relevance of the organization in the market has never been more exciting than in the current times we live in. The Gartner hype cycle is a valuable tool in this pursuit with all its insights into the timing, adoption, and potential benefits of various technologies.

More than two-thirds of companies are currently using Generative AI (GenAI) models, such as large language models (LLMs), which can understand and generate human-like text, images, video, music, and even code. However, the true power of these models lies in their ability to adapt to an enterprise’s unique context. By leveraging an organization’s proprietary data, GenAI models can produce highly relevant and customized outputs that align with the business’s specific needs and objectives.

We’ve integrated generative AI features deeply into our no-code test automation platform, Rainforest QA. Each of these features is designed to help you avoid the time-consuming and otherwise annoying work of keeping automated test suites up to date — so your software development team can stay focused on shipping, fast. In this video, our CEO, Fred Stevens-Smith, walks through what some of these genAI features look like in action.

How to use Gemini generative AI models through BigQuery to boost productivity in Google productivity tools like Sheets.

In today's rapidly evolving digital landscape, superior software is essential, whether it be the apps on our phones or the intricate systems supporting various business requirements. The process known as Software Testing (ST) has undergone an immense transformation in order to meet this necessity where Artificial intelligence (AI) and machine learning (ML) play a great role in QA solutions.

The BigQuery ML.GENERATE_TEXT function lets you use LLMs from Vertex AI within your SQL queries to analyze text in a BigQuery table.

Recently, Cloudera, alongside OCBC, were named winners in the“Best Big Data and Analytics Infrastructure Implementation” category at The Asian Banker’s Financial Technology Innovation Awards 2024. This recognition underscores the importance of trusted data when building AI and generative AI (GenAI) models and serves as a testament to the impact that reliable data can have in real world use cases.