As Large Language Models are revolutionizing natural language prompts, Large Vision Models (LVMs) represent another new, exciting frontier for AI. An estimated 90% of the world’s data is unstructured, much of it in the form of visual content such as images and videos. Insights from analyzing this visual data can open up powerful new use cases that significantly boost productivity and efficiency, but enterprises need sophisticated computer vision technologies to achieve this.

Ensuring proper data governance and security relies on the capabilities offered by the software and platforms constituting your data infrastructure.

Because human-machine interaction using natural language is now possible with large language models (LLMs), more data teams and developers can bring AI to their daily workflows.

BigQuery now supports generative AI use cases using Gemini 1.0 Pro with Vertex AI, providing higher input/output scale and better result quality.

Software testing is an indispensable stage in the software development lifecycle, tasked with verifying application reliability, security, and performance before deployment. This process evaluates software components to ensure they adhere to specified requirements and perform reliably under varied conditions.

Automating data extraction from patient registration forms in healthcare is crucial to enhancing patient care efficiency, accuracy, and overall quality. Over 71% of surveyed clinicians in the USA agreed that the volume of patient data available to them is overwhelming. This abundance of data highlights the importance of streamlining the extraction process. Manual extraction is time-consuming and prone to errors, hindering patient safety.

The class of 2027 saw a massive influx of applications at top universities across the United States. Harvard received close to 57,000 applications for the class of 2027, while MIT received almost 27,000. UC Berkeley and UCLA, meanwhile, received 125,874 and 145,882 respectively. Manual transcript processing is an uphill battle for educational institutions at every level.

Prior to 2022, a lot of the AI news centered on use cases like self-driving cars. Of course, use cases like these didn’t exactly apply to enterprise software. In 2023 ChatGPT showed the abilities of AI to mimic human language, but still, this only scratched the surface of AI applications for the modern enterprise. If you’ve ever asked yourself, “What is AI capable of?” then consider the following examples: How many emails do you get per day?