Developers can now add live Google Maps data to Gemini-powered AI app outputs

Google is adding a new feature for third-party developers building atop its Gemini AI models that rivals like OpenAI’s ChatGPT, Anthropic’s Claude, and the growing array of Chinese open source options are unlikely to get anytime soon: grounding with Google Maps. This addition allows developers to connect Google’s Gemini AI models’ reasoning capabilities with live …

Training Software Engineering Agents and Verifiers with SWE-Gym

We present SWE-Gym, the first environment for training real-world software engineering (SWE) agents. SWE-Gym contains 2,438 real-world Python task instances, each comprising a codebase with an executable runtime environment, unit tests, and a task specified in natural language. We use SWE-Gym to train language model based SWE agents, achieving up to 19% absolute gains in …

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Iterative fine-tuning on Amazon Bedrock for strategic model improvement

Organizations often face challenges when implementing single-shot fine-tuning approaches for their generative AI models. The single-shot fine-tuning method involves selecting training data, configuring hyperparameters, and hoping the results meet expectations without the ability to make incremental adjustments. Single-shot fine-tuning frequently leads to suboptimal results and requires starting the entire process from scratch when improvements are …

Announcing prompt management in the Vertex AI SDK

As generative AI applications grow in sophistication, development workflows become more fragmented. Although AI can be a force multiplier, teams may design prompts in one environment, manage versions in spreadsheets or text files, and then manually integrate them into their code. This leads to inefficiencies, versioning chaos, and collaboration bottlenecks.  Vertex AI Studio is designed …