Why the AI Agent Development Kit Is About to Change Everything in Production-Ready AI
An AI Agent Development Kit (ADK) is the pragmatic answer to the gap between experimental LLM integrations and dependable, scalable automation. As teams move ...
Understanding JSON Schema
Agentic applications are autonomous, goal-directed software agents that run at the edge to sense, decide, and act on users’ behalf. In one sentence: agentic ...
Understanding JSON Schema
LiteRT-LM enables privacy-first AI agents by running models locally on-device, reducing data exposure while delivering fast, efficient on-device inference. Key takeaway:LiteRT-LM matters because it ...
Understanding JSON Schema
The ADK ecosystem is a framework for building interoperable, multi-tool AI agents that connects agent runtimes, tool connectors, and model endpoints to automate workflows ...
Understanding JSON Schema
On-device function calling turns models into local orchestrators: small, auditable functions run inside a secure runtime on the device, enabling offline AI tasks, latency-free ...
Understanding JSON Schema
On modern mobile devices, developers increasingly need models that are fast, private, and energy-efficient. 270M parameter models are emerging as a practical sweet spot: ...
Understanding Quantum Computing: A Beginner’s Guide
The Agent Development Kit (ADK) is changing how teams stitch AI into everyday developer workflows. In this analysis I unpack what ADK offers for ...
Advanced JSON Schema Techniques
FunctionGemma is a runtime and API pattern for on-device function calling that enables high-performance, low-latency agentic mobile apps by running decision logic and small ...
Ethics in Artificial Intelligence
The AI agency war is no longer an academic debate — it’s a practical architecture decision that will shape product roadmaps, regulatory exposures, and ...
Future Applications of Quantum Technology
This quick, practical guide gets you from zero to a working on-device function-calling prototype using the Google AI Edge Gallery. Read the TL;DR, follow ...