Google Releases Enterprise AI Tools and New Chip

On Tuesday, Google disclosed a line of new artificial intelligence technology and collaborations to bring growth for significant businesses.

The Alphabet company created a new public version of its custom-built AI chips. Also, it revealed an enterprise-scale tool for watermarking images and additional tools for its security and office sector.

Moreover, its multiple announcements are a part of its effort to promote its plans with artificial intelligence. This came after Microsoft caught the company with a major AI strategy released last year.

Also, the news from its Google Next conference held in San Francisco reported new customers for its cloud software. The list includes General Motors and Estee Lauder Companies.

Furthermore, it decided to have 20 additional artificial intelligence models to support its enterprise cloud service. As a result, its collection brought the total to 100.

The company reported fresh versions of its foundation artificial intelligence infrastructure that perform better and add features. The new text model is called PaLM, which gives ease to users in processing longer documents. For instance, they could process legal briefs and books faster.

Google’s new chip, TPU v5e, is made to train large models and serve content for them. However, it is not as strong as the yet-launched flagship fifth AI generation chip.

NVIDIA and Google Cloud Broadened Collaboration

On August 29, Google Cloud and NVIDIA reported their new AI infrastructure and software for customers. It aims to build and deploy large models for generative artificial intelligence.

Cloud’s CEO, Thomas Kurian, and NVIDIA’s founder, Jensen Huang, discussed their partnership. They discussed how the collaboration would give end-to-end machine learning services to significant customers.

Also, they aim to make it easy to run AI supercomputers using Google Cloud offerings powered by NVIDIA technologies. Their hardware and software integrations have used the same technologies over the past two years.

Huang mentioned they reached a point where increased computing and generative AI were combined to bring innovation faster.