Results for “google-quantum-ai”

Design, simulate, and run quantum circuits on Google Quantum AI hardware and other providers using Cirq, including noise modeling and characterization experiments.

Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology, including dataset creation, metric selection, failure analysis, and iterative improvement.

Guides usage of the Gemini API on Agent Platform with the Google Gen AI SDK, covering SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API.

Configures dynamic threshold alerting policies for Google Cloud Vertex AI Agent Platform agents, monitoring latency, error rates, and quality metrics using Terraform and PromQL.

Designs and implements a Google Cloud solution for live, bidirectional multimodal streaming workloads with AI agents, covering requirements discovery, architecture design, and deployment planning.

Generates high-quality prompts for AI image, video, and music generation platforms, with optional browser automation to submit them to target sites.

Access Google's most advanced AI models using the Gemini API in Agent Platform (formerly Vertex AI) with SDK installation, authentication, and code examples.

Design, simulate, and run quantum circuits on simulators and real quantum hardware using Google's Cirq framework.

Generates images from text prompts using Google Gemini's image generation model, saving them as PNG files for use in UI, documentation, and design assets.

Design, simulate, and run quantum circuits on simulators and quantum hardware using Google's Cirq framework.

Design, simulate, and run quantum circuits on simulators and quantum hardware using Google's Cirq framework.

Generates images via OpenAI, Google, DashScope, and Replicate APIs, supporting text prompts, reference images, aspect ratios, and quality presets.