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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

A new wallet is established by creating a unique set of cryptographic words, known as a mnemonic, which grants you access to your assets on the Cardano blockchain. Your mnemonic is not stored by us, and there is no method to reset it if forgotten. Consequently, if you misplace your mnemonic, we are unable to assist you in regaining access to your funds. The mnemonic is processed exclusively in your browser and remains confined to your device. However, if your computer is compromised by malware or a hacker, they could potentially capture the mnemonic you input on the AdaLite platform and gain access to your assets. AdaLite also offers the option to access your funds through a hardware wallet, currently compatible with Trezor model T, Ledger Nano X, and Ledger Nano S. This feature allows you to use AdaLite in the most secure way possible, without ever exposing your mnemonic. Because the mnemonic and private key do not leave the Ledger, they are safeguarded from potential theft. To safeguard against phishing attempts, it is wise to bookmark the official AdaLite URL and consistently verify it before entering any sensitive information. Additionally, keeping your software updated can further enhance your security against emerging threats.

Description

LiteRT, previously known as TensorFlow Lite, is an advanced runtime developed by Google that provides high-performance capabilities for artificial intelligence on devices. This platform empowers developers to implement machine learning models on multiple devices and microcontrollers with ease. Supporting models from prominent frameworks like TensorFlow, PyTorch, and JAX, LiteRT converts these models into the FlatBuffers format (.tflite) for optimal inference efficiency on devices. Among its notable features are minimal latency, improved privacy by handling data locally, smaller model and binary sizes, and effective power management. The runtime also provides SDKs in various programming languages, including Java/Kotlin, Swift, Objective-C, C++, and Python, making it easier to incorporate into a wide range of applications. To enhance performance on compatible devices, LiteRT utilizes hardware acceleration through delegates such as GPU and iOS Core ML. The upcoming LiteRT Next, which is currently in its alpha phase, promises to deliver a fresh set of APIs aimed at simplifying the process of on-device hardware acceleration, thereby pushing the boundaries of mobile AI capabilities even further. With these advancements, developers can expect more seamless integration and performance improvements in their applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

C++
CNFT.IO
Cardano
Cointelli
Divly
Google AI Edge Gallery
JAX
Java
Koinly
Kotlin
Objective-C
PyTorch
Python
Swift
TensorFlow

Integrations

C++
CNFT.IO
Cardano
Cointelli
Divly
Google AI Edge Gallery
JAX
Java
Koinly
Kotlin
Objective-C
PyTorch
Python
Swift
TensorFlow

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

AdaLite

Website

adalite.io

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

ai.google.dev/edge/litert

Product Features

Product 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)

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