5 Key Google AI Resources Made For Google Cloud Partners
‘I have seen a lot of technology waves. [Generative AI] is not a hype cycle. The ROI is real,’ Google Cloud’s global partner leader, Kevin Ichhpurani, tells CRN.
Google Launches New AI Solutions And Use Cases
Google CEO Sundar Pichai (pictured) said the company is at an “inflection point” in AI and the need to launch new products is more important than ever before.
“We have an opportunity to make AI even more helpful for people, for businesses, for communities, for everyone,” said Pichai during Google’s I/O 2023 event last month. “We’ve been applying AI to make our products radically more helpful for a while. With generative AI, we’re taking the next step.”
Google has injected generative AI capabilities inside flagship products such as Google Workspace, while also consistently adding new features to its conversational chatbot Bard.
On the enterprise front, Google Cloud recently launched PaLM API, a developer offering to make it easier and safer to experiment with Google’s large langue models. PaLM API can be used for a variety of applications and provides access to models that are optimized for multi-turn use cases— such as content generation and chat, as well as general-purpose models optimized for areas like summarization and classification. PaLM 2 was launched in May and offers stronger models in logic and reasoning.
Another new offering is Duet AI for Google Cloud, which is an AI-powered collaborator to help cloud users of all skill levels solve their everyday work challenges. Duet AI serves as an expert pair programmer and assists cloud users with contextual code completion, offering suggestions tuned to a customer’s code base, and assists with code reviews and inspections.
Finally, Google Cloud recently enabled generative AI support for Vertex AI, which is the company’s machine learning platform for training and deploying ML models and AI applications. The new feature gives teams access to foundation models from Google and others, letting users build and customize atop these models on the same platform they use for homegrown ML models and MLOps.
“What’s unique about Google is we have a multitude of models to solve your specific use case. There is no one-size-fits-all model,” said Ichhpurani. “What’s differentiated is we will have a vast array of models to solve customer-specific use cases like PaLM. So that is a unique differentiator we bring to the table, these special-purpose models for your specific use case.”