Cloud Computing

Today’s AI models are moving from billions to trillions of parameters, and are capable of complex, multi-modal reasoning. This leap in sophistication demands a new class of purpose-built infrastructure and software to handle the immense computational and memory requirements of these next-generation models. At Google Cloud, we’re committed to empowering developers and organizations to build […]

Many enterprises have built their foundational business operations on robust transactional systems powered by Oracle Database. And with Oracle on Google Cloud, they can deploy and manage Oracle Database instances directly within Google Cloud’s highly scalable and secure infrastructure, benefiting from low-latency network connectivity and integrated services. But in today’s digitized world, data utilization is

The emergence of the agentic web — an internet where autonomous AI agents can independently execute complex, multi-step tasks and transactions that previously required human interaction — promises a fundamental shift for how customers and businesses interact. While agents can help deliver a frictionless customer experience, they can also enable new abuse and fraud vectors. 

Written by: Bhavesh Dhake, Will Silverstone, Matthew Hitchcock, Aaron Fletcher The Criticality of Privileged Access in Today’s Threat Landscape Privileged access stands as the most critical pathway for adversaries seeking to compromise sensitive systems and data. Its protection is not only a best practice, it is a fundamental imperative for organizational resilience. The increasing complexity

As AI technology advances at a rapid pace, I am pleased to announce a new set of investments in our partner ecosystem at today’s Partner Connect at the Google Public Sector Summit. Our new initiatives will deepen our collaboration and empower our partners to capitalize on the incredible momentum in AI. We are focused on

Ryan welcomes Tom Moor, head of engineering at Linear, to discuss AI agents’ mixed results for productivity in the development lifecycle, the importance of context for maximizing agents’ effectiveness, and the role that junior developers need to take in a world increasingly driven by AI.

Building and scaling generative AI models demands enormous resources, but this process can get tedious. Developers wrestle with managing job queues, provisioning clusters, and resolving dependencies just to ensure consistent results. This infrastructure overhead, along with the difficulty of discovering the optimal training recipe and navigating the endless maze of hyperparameter and model architecture choices,