Machine Learning

Image by Editor   # Introduction  Vertex AI Search, formerly known as Enterprise Search on Google Cloud, represents a significant evolution in how organizations can implement intelligent search capabilities within their applications. This powerful tool combines traditional search functionality with advanced machine learning capabilities to deliver semantic understanding and natural language processing (NLP). For data scientists …

Building Vertex AI Search Applications: A Comprehensive Guide Read More »

Today, we’re releasing a major upgrade to Gemini 3 Deep Think, our specialized reasoning mode, built to push the frontier of intelligence and solve modern challenges across science, research, and engineering. We updated Gemini 3 Deep Think in close partnership with scientists and researchers to tackle tough research challenges — where problems often lack clear …

AI model update designed for science Read More »

I with countless organizations that are surrounded by more data than they know what to do with. Metrics flood in from every direction, from website traffic numbers to ad impressions and conversion rates. Yet somehow, the decisions still feel like guesswork. The problem is not lack of data; it is that data alone does not …

How to Leverage Explainable AI for Better Business Decisions Read More »

Image by Editor   # Introduction  Getting labeled data — that is, data with ground-truth target labels — is a fundamental step for building most supervised machine learning models like random forests, logistic regression, or neural network-based classifiers. Even though one major difficulty in many real-world applications lies in obtaining a sufficient amount of labeled data, …

Why Most People Misuse SMOTE, And How to Do It Right Read More »

New research shows that reorganizing a model’s visual representations can make it more helpful, robust and reliable “Visual” artificial intelligence (AI) is everywhere. We use it to sort our photos, identify unknown flowers and steer our cars. But these powerful systems do not always “see” the world as we do, and they sometimes behave in …

Teaching AI to See the World More Like Humans Do — Google DeepMind Read More »

as the years before: fireworks across the globe. People greeted the new year with new resolutions and new goals. Someone, somewhere, surely said: “2026 is going to be THE year.” Then January happened. As the weeks went on, the end of the month came closer. And for people in ML research, late January has a …

The Machine Learning Lessons I’ve Learned Last Month Read More »

Image by Editor   # The Fragile Pipeline  The gravitational pull of state of the art in modern machine learning is immense. Research teams and engineering departments alike obsess over model architecture, from tweaking hyperparameters to experimenting with novel attention mechanisms, all in the pursuit of chasing the latest benchmarks. But while building a slightly more …

Is Your Machine Learning Pipeline as Efficient as it Could Be? Read More »

Acknowledgements This research was developed by the SIMA 2 team: Maria Abi Raad, John Agapiou, Frederic Besse, Andrew Bolt, Sarah Chakera, Harris Chan, Jeff Clune, Alexandra Cordell, Martin Engelcke, Ryan Faulkner, Maxime Gazeau, Arne Olav Hallingstad, Tim Harley, Ed Hirst, Drew Hudson, Laura Kampis, Sheleem Kashem, Thomas Keck, Matija Kecman, Oscar Knagg, Alexander Lerchner, Bonnie …

A Gemini-Powered AI Agent for 3D Virtual Worlds — Google DeepMind Read More »

are so easy to use that it’s also easy to use them the wrong way, like holding a hammer by the head. The same is true for Pydantic, a high-performance data validation library for Python. In Pydantic v2, the core validation engine is implemented in Rust, making it one of the fastest data validation solutions …

Pydantic Performance: 4 Tips on How to Validate Large Amounts of Data Efficiently Read More »

Image by Author   I used to hate vibe coding. I believed I could write better code, design cleaner systems, and make more thoughtful architectural decisions on my own. For a long time, that was probably true. Over time, things changed. AI agents improved significantly. MCP servers, Claude skills, agent workflows, planning-first execution, and long-horizon …

Tech Stack for Vibe Coding Modern Applications Read More »