Turns text, images, voice, files, and live context into conversational help across web and mobile. Its edge is tight access to Google Search, Android, Workspace, and multimodal Gemini models; the tradeoff is ecosystem lock-in and uneven reliability.
Interleaves chain-of-thought reasoning with tool-using actions in one LLM loop: the model plans, queries a source like Wikipedia, then revises from results. Cuts hallucination versus reasoning-only prompting and beats trained agents on interactive tasks.
Manages provider configs for seven coding CLIs (Claude Code, Codex, Gemini CLI, OpenCode and more) from one desktop app, so switching API endpoints no longer means hand-editing JSON, TOML, or .env files. Adds tray quick-switch and cloud sync.
Lets developers call Gemini, Nano Banana, Veo, and other Google AI models from apps through SDKs or REST. It is fastest for teams that want hosted multimodal generation without running model infrastructure.
Builds and deploys machine learning models across research, production, web, mobile, and edge environments. Its ecosystem spans Keras, TFX, LiteRT, TensorFlow.js, datasets, model hubs, and visualization tools.
Deploys trained SavedModels behind gRPC and REST endpoints, with hot-swappable versioning so new weights load without downtime. Built around servables, loaders, sources, and a manager, plus request batching to cut accelerator cost.
Grounds language-based robot planning in learned skill value functions, selecting actions that are both useful and feasible. PaLM-SayCan reports 84% planning and 74% execution success across 101 real-world instructions.
Breaks hard reasoning problems into simpler subproblems, then solves them using earlier answers. With 14 exemplars, code-davinci-002 reaches at least 99% accuracy on SCAN splits, including the length split.
Notebooks and sample apps demonstrating generative-AI workflows on Google Cloud's Vertex AI and Gemini — covering RAG grounding, multimodal demos, function calling, and agent-building examples, with deployment-ready templates for evaluation and production.
Unifies access to OpenAI, Anthropic, Google and other LLM providers behind one TypeScript API — swap models by changing a string. Adds streaming UI hooks for React, Next.js, Svelte and Vue, plus a tool-calling loop for agentic workflows.
Upload your own documents, PDFs, slides, or web pages and ask questions answered only from that material, with inline citations pointing to the exact passage used. Audio Overview turns your sources into a downloadable two-host podcast discussion.
Provides code and pretrained models for WeatherNext 2 and WeatherNext Cyclones — ML-based global, medium-range atmospheric forecasting models from Google DeepMind/Google Research. Includes Colab demos, pretrained weights, and guides for cloud access and inference.