Building a slide deck, pitch, or presentation? Here are the big takeaways:

  • Google Cloud launched AutoML, a new machine learning service that requires limited experience to operate.
  • The service will enable businesses of all sizes a chance to overcome talent and cost barriers and begin using AI in their company.

Artificial intelligence (AI) technology may be more easily accessible through Google Cloud’s new AutoML service, the tech giant said in a blog post Wednesday.

Cloud AutoML helps tech professionals build custom machine learning (ML) models, using techniques like transfer learning and learning2learn, the post said. While Cloud AutoML requires limited ML experience, the service could help businesses, especially SMBs, overcome talent shortages and cost barriers and utilize the emerging technology.

SEE: Quick glossary: Artificial intelligence (Tech Pro Research)

“Our goal was to lower the barrier of entry and make AI available to the largest possible community of developers, researchers and businesses,” Google Cloud AI’s Fei-Fei Li and Jia Li said in the post.

Even for larger businesses that have both the talent and budget to work with AI, they may not have the time to create machine learning models, the post noted.

“We believe Cloud AutoML will make AI experts even more productive, advance new fields in AI and help less-skilled engineers build powerful AI systems they previously only dreamed of,” the post said.

The first part of the service to be released is Cloud AutoML Vision, which focuses on ML models for image recognition. Users can upload images, create the model, then manage it on Google Cloud, the post said.

Google Cloud AI has launched other programs to help spread AI in the past year. In 2017, it launched Google Cloud Machine Learning Engine to help machine learning developers build scalable ML models. The engine, along with AutoML, are just the beginning of Google Cloud AI’s efforts to democratize the technology, the post said.

AutoML has not launched publicly, but interested companies can request access via this form.

Only one-third of tech leaders are currently implementing AI, but Gartner estimates IT spending-including AI-will hit $3.7 trillion by 2018. Programs like AutoML may be able to help more tech professionals get into the field as it continues to grow.