Twitter: gaining insights from Tweets with an API for Google Cloud
Editor’s note: Although Twitter has long been considered a treasure trove of data, the task of analyzing Tweets in order to understand what’s happening in the world, what people are talking about right now, and how this information can support business use cases has historically…
Moving off CentOS? Introducing Rocky Linux Optimized for Google Cloud
As CentOS 7 reaches end of life, many enterprises are considering their options for an enterprise-grade, downstream Linux distribution on which to run their production applications. Rocky Linux has emerged as a strong alternative that, like CentOS, is 100% compatible with Red Hat Enterprise Linux. In April…
Apigee best practices for Contact Center AI
By now, you’ve probably interacted with a customer service chatbot at some point. However, many of those interactions may have left a lot to be desired. Modern consumers generally expect more than a simple bot that answers questions with predefined answers—they expect a virtual agent…
Making AI more accessible for every business
Alphabet CEO Sundar Pichai has compared the potential impact of artificial intelligence (AI) to the impact of electricity—so it may be no surprise that at Google Cloud, they expect to see increased AI and machine learning (ML) momentum across the spectrum of users and use cases. Some…
Building AI in the cloud: An easier way with Google Cloud and NVIDIA
NVIDIA GPU-powered instances on Google Cloud provide an optimal platform for organizations to develop their AI applications on the latest hardware and software stack, then seamlessly deploy those applications at scale in production. Simplifying Workflows to Speedup AI Developments NVIDIA recently announced the One Click…
Invest early, save later: Why shifting security left helps your bottom line
Shifting left on security with Google Cloud infrastructure The concept of “shifting left” has been widely promoted in the software development lifecycle. The concept is that introducing security earlier, or leftwards, in the development process will lead to fewer software-related security defects later, or rightwards,…
Automate annotations for Vertex AI text datasets with Cloud Vision API and BigQuery
One of the main challenges machine learning practitioners face is the availability of annotated training datasets or a lack thereof. In many cases, practitioners may have access to existing datasets that have been manually extracted, which they can use to accelerate their model training. Through…
I/O Adventure Google Cloud architecture
Since 2020, many conferences have moved online – either fully or partially – as organizers, presenters, and attendees all reimagine how we approach our life and our work. Google I/O Adventure is a virtual conference experience that brings some of the best parts of real-world…
How Kitabisa re-structured its fundraising platform to drive “kindness at scale” on Google Cloud
The name Kitabisa means “we can” in Bahasa Indonesia, the official language of Indonesia, and captures their aspirational ethos as Indonesia’s most popular fundraising platform. Since 2013, Kitabisa has been collecting donations in times of crisis and natural disasters to help millions in need. Pursuing…
Measuring climate and land changes with AI
Imagine what could be possible if we had a dataset that could automatically and in near real-time show you how the Earth has changed week over week, month over month, year over year. We would get a birds eye view of recent events like floods, fires, snowstorms from days ago and be…
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- Vertex AI grounding: More reliable models, fewer hallucinations
Recent Posts
- Find key insights with contribution analysis in BigQuery ML
- Secure your data ecosystem: a multi-layered approach with Google Cloud
- Gemini for Google Workspace now supports additional languages
- 5 ways small business owners can use Gemini for Workspace to plan for the holiday season and New Year
- Vertex AI grounding: More reliable models, fewer hallucinations
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