Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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

Write a Review

Alternatives to Consider

  • Gemini Enterprise Agent Platform Reviews & Ratings
    4.3 out of 5 stars 1,178 Ratings
    Company Website for Gemini Enterprise Agent Platform
  • BAND Reviews & Ratings
    5.0 out of 5 stars 3 Ratings
    Company Website for BAND
  • AdRem NetCrunch Reviews & Ratings
    4.6 out of 5 stars 165 Ratings
    Company Website for AdRem NetCrunch
  • Virtuoso QA Reviews & Ratings
    4.5 out of 5 stars 131 Ratings
    Company Website for Virtuoso QA
  • Kitecyber Reviews & Ratings
    4.9 out of 5 stars 89 Ratings
    Company Website for Kitecyber
  • QA Wolf Reviews & Ratings
    4.8 out of 5 stars 284 Ratings
    Company Website for QA Wolf
  • Creatio Reviews & Ratings
    4.6 out of 5 stars 589 Ratings
    Company Website for Creatio
  • Checksum.ai Reviews & Ratings
    5.0 out of 5 stars 2 Ratings
    Company Website for Checksum.ai
  • Macaw AMS Reviews & Ratings
    4.9 out of 5 stars 8 Ratings
    Company Website for Macaw AMS
  • Flagsmith Reviews & Ratings
    4.8 out of 5 stars 43 Ratings
    Company Website for Flagsmith

What is TF-Agents?

TF-Agents is a comprehensive library specifically designed for reinforcement learning within the TensorFlow ecosystem. It facilitates the development, execution, and assessment of novel RL algorithms by providing reliable and customizable modular components. With TF-Agents, developers can efficiently iterate their code while ensuring proper integration of tests and performance evaluations. The library encompasses a variety of agents, such as DQN, PPO, REINFORCE, SAC, and TD3, each featuring distinct networks and policies tailored for specific tasks. Moreover, it supplies tools for creating custom environments, policies, and networks, which is essential for building complex RL workflows. TF-Agents is optimized for seamless interaction with Python and TensorFlow environments, offering versatility for different development and deployment needs. Additionally, it is fully compatible with TensorFlow 2.x and includes a wealth of tutorials and guides to help users start training agents on well-known environments like CartPole. Ultimately, TF-Agents not only serves as a powerful framework for researchers and developers delving into reinforcement learning but also fosters a supportive community that shares knowledge and resources to enhance learning experiences.

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.

Media

Media

Integrations Supported

Python
TensorFlow

Integrations Supported

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

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

Android
iPhone
iPad
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Tensorflow

Date Founded

2015

Company Location

United States

Company Website

www.tensorflow.org/agents

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

ai.google.dev/edge/litert

Categories and Features

AI Agent Frameworks

Not specified

RLHF

Not specified

Categories and Features

Popular Alternatives

Popular Alternatives

AWS Neuron Reviews & Ratings

AWS Neuron

Amazon Web Services
TensorBoard Reviews & Ratings

TensorBoard

Tensorflow
TensorFlow Reviews & Ratings

TensorFlow

5.0 out of 5 stars
Keras Reviews & Ratings

Keras

5.0 out of 5 stars