Google Releases the Power of Generative AI at Google Cloud Next
Google has made a major progress in the territory of artificial intelligence (AI) at the Google Cloud Next event held in Las Vegas. The tech giant has fully incorporated generative AI, signifying its potential to a gathering of 30,000 attendees. Google Cloud is chiefly a cloud infrastructure and platform vendor. It has placed generative AI at the center of its offerings. The company declared the incorporation of the Gemini large language model (LLM) to improve productivity across the platform. Despite the difficulty of applying advanced technology in large organizations, Google purposes to shorten the process and unlock the power of generative AI for its customers.
Google’s pledge to generative AI is obvious in its latest offerings. The company has launched its most capable models including Gemini 1.5 Pro. It is now in public preview for Cloud customers and developers. Gemini 1.5 Pro showcases dramatically enhanced performance and includes a revolution in long context understanding. This means it can run 1 million tokens of information steadily, opening up new possibilities for inventiveness to create, discover, and build using AI.
When combined with Gemini’s multimodal capabilities (which can process audio, video, text, code, and more), long context allows enterprises to do things that just weren’t possible with AI before. For example, a gaming company could provide a video analysis of a player’s performance, along with tips to improve. Or an insurance company could combine video, images, and text inputs to create an incident report, making the claims process easier.
Google is also increasing access to a new version of its open model Gemma. It is designed to help customers with code generation and other types of code assistance. These are now available on Vertex AI. It is Google Cloud’s platform to customize and fully manage a wide range of leading gen AI models. Today more than 1 million developers are now using Google’s generative AI across tools including AI Studio and Vertex AI.
Though, the application of generative AI in large organizations comes with challenges. While Google has tried to make it sound easy, in reality, it’s a huge challenge to apply any advanced technology inside large organizations. Much like other technical jumps over the last 15 years — whether mobile, cloud, containerization, marketing automation, it’s been delivered with lots of promises of possible gains. Yet these progressions each introduce their own level of difficulty, and large companies move more vigilantly than we imagine.
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