Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Bitrise Reviews & Ratings
    382 Ratings
    Company Website
  • Google Cloud Speech-to-Text Reviews & Ratings
    401 Ratings
    Company Website
  • Unimus Reviews & Ratings
    30 Ratings
    Company Website
  • DXcharts Reviews & Ratings
    28 Ratings
    Company Website
  • Hostinger Reviews & Ratings
    52,103 Ratings
    Company Website
  • TRACTIAN Reviews & Ratings
    115 Ratings
    Company Website
  • RunPod Reviews & Ratings
    159 Ratings
    Company Website
  • Ganttic Reviews & Ratings
    240 Ratings
    Company Website
  • LM-Kit.NET Reviews & Ratings
    19 Ratings
    Company Website
  • Windsurf Editor Reviews & Ratings
    144 Ratings
    Company Website

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 Flower?

Flower is an open-source federated learning framework designed to simplify the development and application of machine learning models across diverse data sources. By allowing the training of models directly on data housed in individual devices or servers, it enhances privacy and reduces bandwidth usage significantly. The framework supports a wide range of well-known machine learning libraries, including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and it integrates smoothly with various cloud services like AWS, GCP, and Azure. Flower is highly adaptable, featuring customizable strategies and supporting both horizontal and vertical federated learning setups. Its architecture prioritizes scalability, effectively managing experiments that can involve tens of millions of clients. Furthermore, Flower includes privacy-preserving mechanisms, such as differential privacy and secure aggregation, ensuring the protection of sensitive information throughout the learning process. This comprehensive approach not only makes Flower an excellent option for organizations aiming to adopt federated learning but also positions it as a leader in driving innovation in the field of decentralized machine learning solutions. The framework's commitment to flexibility and security underscores its potential to meet the evolving needs of the data-centric world.

Media

Media

Integrations Supported

JAX
PyTorch
Python
TensorFlow
Amazon Web Services (AWS)
Android
Apple iOS
C++
Docker
Google Cloud Platform
Hugging Face
Java
Kotlin
MXNet
Microsoft Azure
Modern Leadership (MLX)
NumPy
Raspberry Pi OS
Swift
scikit-learn

Integrations Supported

JAX
PyTorch
Python
TensorFlow
Amazon Web Services (AWS)
Android
Apple iOS
C++
Docker
Google Cloud Platform
Hugging Face
Java
Kotlin
MXNet
Microsoft Azure
Modern Leadership (MLX)
NumPy
Raspberry Pi OS
Swift
scikit-learn

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
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

Flower

Date Founded

2023

Company Location

Germany

Company Website

flower.ai/

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Popular Alternatives

Popular Alternatives

AWS Neuron Reviews & Ratings

AWS Neuron

Amazon Web Services
Keepsake Reviews & Ratings

Keepsake

Replicate