8 ways to cut costs and drive profits using data and AI
Google are increasingly seeing one question arise in virtually every customer conversation: How can the organization save costs and drive new revenue streams? Everyone would love a crystal ball, but what you may not realize is that you already have one. It’s in your data….
How to use advance feature engineering to preprocess data in BigQuery ML
Preprocessing and transforming raw data into features is a critical but time consuming step in the ML process. This is especially true when a data scientist or data engineer has to move data across different platforms to do MLOps. In this blogpost, Google describe how we…
Speech AI Year in Review
Almost anywhere you looked, AI-based speech technologies continued to blossom in 2022, from increased interest measured in Google Trends, to surprising medical advances that suggest speech patterns can help detect some illnesses, to the variety of digital services and devices that users control with their voices. …
Vertex AI Vision: Easily build and deploy computer vision applications at scale
If organizations can easily analyze unstructured data streams, like live video and images, they can more effectively leverage information from the physical world to create intelligent business applications. Retailers can improve shelf management by instantly spotting what products are out of stock, manufacturers can reduce…
How our commitment to open source unlocks AI and ML innovation
Google believe anyone should be able to quickly and easily turn their artificial intelligence (AI) idea into reality. Open source software (OSS) has become increasingly important to this goal, heavily influencing the pace of innovation in AI and machine learning (ML) ecosystems. Over the last…
Streamline your models to production with the Vertex AI Model Registry
Machine learning (ML) is iterative in nature — model improvement is a necessity to drive the best business outcomes. Yet, with the proliferation of model artifacts, it can be difficult to ensure that only the best models make it into production. Data science teams may…
Implementing observability for always-on Ecommerce experience
In today’s Digital age, the emphasis continues to be on automation and improving business processes, employee productivity and customer experiences to meet the ever changing business and consumer expectations. According to Gartner, organizations will require more IT and business process automation as they are forced to accelerate digital…
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…
Introducing new AI to help people thrive in hybrid work
Google have been using machine learning in Google Workspace for some years to help make people’s work day more productive and impactful. Today, they’re announcing new features in Google Workspace that tap into their industry-leading AI to help people thrive and get more done in a hybrid work world….
Meet Google’s unified data and AI offering
Without AI, you’re not getting the most out of your data.Without data, you risk stale, out-of-date, suboptimal models. But most companies are still struggling with how to keep these highly interdependent technologies in sync and operationalize AI to take meaningful action from data. Google have…
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Recent Posts
- Unlock multimodal search at scale: Combine text & image power with Vertex AI
- 4 ways Gemini for Workspace can help sellers and marketers spend more time doing what they do best
- Find sensitive data faster (but safely) with Google Distributed Cloud’s gen AI search solution
- Updated smart feature settings give users increased choice and control
- Build and refine your audio generation end-to-end with Gemini 1.5 Pro
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