Cloud Computing

Closing the gap between impressive model demos and real-world performance is crucial for successfully deploying generative AI for enterprise. Despite the incredible capabilities of generative AI for enterprise, this perceived gap may be a barrier for many developers and enterprises to “productionize” AI. This is where retrieval-augmented generation (RAG) becomes non-negotiable – it strengthens your […]

Cloud applications like Google Workspace provide benefits such as collaboration, availability, security, and cost-efficiency. However, for cloud application developers, there’s a fundamental conflict between achieving high availability and the constant evolution of cloud applications. Changes to the application, such as new code, configuration updates, or infrastructure rearrangements, can introduce bugs and lead to outages. These

Few things are more critical to IT operations than security. Security incidents, coordinated threat actors, and regulatory mandates are coupled with the imperative to effectively manage risk and the vital business task of rolling out generative AI. That’s why in 2025 at Google Cloud Next we are creating an in-depth security experience to show you

Retailers have always moved quickly to connect and match the latest merchandise with customers’ needs. And the same way they carefully design every inch of their stores, the time and thought that goes into their IT infrastructure is now just as important in the era of omnichannel shopping. As retail organizations increasingly adopt AI foundation

Despite the growing global investment in AI, women-founded startups remain underrepresented in the venture capital landscape. Just last year, female-founded companies in Europe received just 1.8% of total VC funding.  To help close this gender gap, we are opening up applications for the Google for Startups Accelerator: Women Founders program for Europe & Israel. This

The exponential growth of machine learning models brings with it ever-increasing datasets. This data deluge creates a significant bottleneck in the Machine Learning Operations (MLOps) lifecycle, as traditional data preprocessing methods struggle to scale. The preprocessing phase, which is critical for transforming raw data into a format suitable for model training, can become a major

Written by: John Wolfram, Josh Murchie, Matt Lin, Daniel Ainsworth, Robert Wallace, Dimiter Andonov, Dhanesh Kizhakkinan, Jacob Thompson Note: This is a developing campaign under active analysis by Mandiant and Ivanti. We will continue to add more indicators, detections, and information to this blog post as needed. On Wednesday, Jan. 8, 2025, Ivanti disclosed two

Online video consumption has skyrocketed. A staggering 1.8 billion people globally subscribed to streaming services in 20231, and 92% of internet users worldwide watched online videos every month in 20242. This growth creates a significant opportunity for advertisers who want to reach their customers with great creative, but ineffective ad placement can disrupt their customers’

Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning (SFT) comes in. When done right, it unlocks incredible precision to tailor Gemini for specialized tasks, domains, and