Cloud Run: the fastest way to get your AI applications to production
It’s no secret that Cloud Run offers one of the most straightforward ways for delivering AI-powered applications to production, letting developers focus on their application logic without having to worry about the underlying infrastructure or how to scale from zero to millions of users. But did you…
Hands on with Gemini models in BigQuery: Decoding sentiment in customer reviews
Sentiment analysis is a powerful tool that uses natural language processing (NLP) to uncover the underlying emotions (positive, negative, neutral) within text such as customer reviews. This analysis can offer valuable insight into how customers perceive your products, services, and brand overall. Furthermore, by utilizing…
New ways to engage with Gemini for Workspace
Google are announcing new, powerful ways to get more done in your personal and professional life with Gemini for Google Workspace. Gemini in the side panel of your favorite Workspace apps is rolling out more broadly and will use the 1.5 Pro model for answering…
Long document summarization with Workflows and Gemini models
With generative AI top of mind for both developers and business stakeholders, it’s important to explore how products like Workflows, Google Cloud’s serverless execution engine, can automate and orchestrate large language model (LLM) use cases. We recently covered how to orchestrate Vertex AI’s PaLM and Gemini APIs…
Creating marketing campaigns using BigQuery and Gemini models
Creating marketing campaigns is often a complex and time-consuming process. Businesses aim to create real-time campaigns that are highly relevant to customer needs and personalized to maximize sales. Doing so requires real-time data analysis, segmentation, and the ability to rapidly create and execute campaigns. Achieving…
Cloud SQL: Rapid prototyping of AI-powered apps with Vertex AI
Developers seeking to leverage the power of machine learning (ML) on their PostgreSQL data often find themselves grappling with complex integrations and steep learning curves. Cloud SQL for PostgreSQL now bridges this gap, allowing you to tap into cutting-edge ML models and vector generation techniques offered by Vertex…
Introducing Shadow API detection for your Google Cloud environments
Enterprises operate a large and growing number of APIs — more than 200 on average — each a potential front door to sensitive data. Even more challenging can be figuring out which of these APIs are not actively managed “shadow APIs”. Born from well-intended development initiatives and…
Chrome Enterprise expands ecosystem to strengthen endpoint security and Zero Trust access
The modern workplace relies on web-based applications and cloud services, making browsers and their sensitive data a primary target for attackers. While the risks are significant, Chrome Enterprise can help organizations simplify and strengthen their endpoint security with secure enterprise browsing. Following our recent Chrome Enterprise Premium launch, today…
AI and the Five Phases of the Threat Intelligence Lifecycle
Artificial intelligence (AI) and large language models (LLMs) can help threat intelligence teams to detect and understand novel threats at scale, reduce burnout-inducing toil, and grow their existing talent by democratizing access to subject matter expertise. However, broad access to foundational Open Source Intelligence (OSINT)…
Game-changing assets: Making concept art with Google Cloud’s generative AI
Developing games is unique in that it requires a large variety of media assets such as 2D images, 3D models, audio, and video to come together in a development environment. However, in small game teams, such as those just getting started or “indie” teams, it’s…
AI can be the catalyst to reignite your digital transformation
Be honest with me: Is your “digital transformation” stuck? Did you start in earnest a few years back, and now you’re sitting on half-finished projects, uneven outcomes, and a distracted staff? It happens. Maintaining momentum for multi-year efforts isn’t easy. Especially efforts that are increasingly…
Introducing new ML model monitoring capabilities in BigQuery
Monitoring machine learning (ML) models in production is now as simple as using a function in BigQuery! Today Google introducing a new set of functions that enable model monitoring directly within BigQuery. Now, you can describe data throughout the model workflow by profiling training or…