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What is LiteRT?

LiteRT, which was formerly called TensorFlow Lite, is a sophisticated runtime created by Google that delivers enhanced performance for artificial intelligence on various devices. This innovative platform allows developers to effortlessly deploy machine learning models across numerous devices and microcontrollers. It supports models from leading frameworks such as TensorFlow, PyTorch, and JAX, converting them into the FlatBuffers format (.tflite) to ensure optimal inference efficiency. Among its key features are low latency, enhanced privacy through local data processing, compact model and binary sizes, and effective power management strategies. Additionally, LiteRT offers SDKs in a variety of programming languages, including Java/Kotlin, Swift, Objective-C, C++, and Python, facilitating easier integration into diverse applications. To boost performance on compatible devices, the runtime employs hardware acceleration through delegates like GPU and iOS Core ML. The anticipated LiteRT Next, currently in its alpha phase, is set to introduce a new suite of APIs aimed at simplifying on-device hardware acceleration, pushing the limits of mobile AI even further. With these forthcoming enhancements, developers can look forward to improved integration and significant performance gains in their applications, thereby revolutionizing how AI is implemented on mobile platforms.

What is Google AI Edge?

Google AI Edge offers a comprehensive suite of tools and frameworks designed to streamline the incorporation of artificial intelligence into mobile, web, and embedded applications. By enabling on-device processing, it reduces latency, allows for offline usage, and ensures that data remains secure and localized. Its compatibility across different platforms guarantees that a single AI model can function seamlessly on various embedded systems. Moreover, it supports multiple frameworks, accommodating models created with JAX, Keras, PyTorch, and TensorFlow. Key features include low-code APIs via MediaPipe for common AI tasks, facilitating the quick integration of generative AI, alongside capabilities for processing vision, text, and audio. Users can track the progress of their models through conversion and quantification processes, allowing them to overlay results to pinpoint performance issues. The platform fosters exploration, debugging, and model comparison in a visual format, which aids in easily identifying critical performance hotspots. Additionally, it provides users with both comparative and numerical performance metrics, further refining the debugging process and optimizing models. This robust array of features not only empowers developers but also enhances their ability to effectively harness the potential of AI in their projects. Ultimately, Google AI Edge stands out as a crucial asset for anyone looking to implement AI technologies in a variety of applications.

Media

Media

Integrations Supported

PyTorch
TensorFlow
C++
Google AI Edge Gallery
JAX
Java
Kotlin
Objective-C
Python
Swift

Integrations Supported

PyTorch
TensorFlow
Gemma 3n
Google AI Edge Eloquent
Google Cloud Platform
Greenovative
Keras
This Is GEO

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Free
Free Version

Supported Platforms

Android
iPhone
iPad
Linux

Supported Platforms

SaaS
Android
iPhone
iPad

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

ai.google.dev/edge/litert

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

ai.google.dev/edge

Categories and Features

Categories and Features

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