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Description
Flowhub IDE serves as a versatile tool for visually constructing full-stack applications. Its flow-based programming environment allows users to develop a wide range of projects, from distributed data processing systems to interactive internet-connected art installations. This platform supports JavaScript and operates seamlessly in both browser and Node.js environments. Additionally, it facilitates flow-based programming tailored for microcontrollers, such as Arduinos, making it an excellent toolkit for creating IoT solutions. Flowhub adheres to the FBP protocol, enabling integration with custom dataflow systems. The design begins on a virtual whiteboard, maintaining a streamlined approach throughout the development process. The intuitive “graph” feature presents your software's flow in a clear and aesthetically pleasing manner. Engineered for touchscreen functionality, Flowhub empowers users to develop applications on their tablets while mobile, although having a keyboard may enhance the experience during component editing. Ultimately, Flowhub fosters creativity and efficiency in software development across various platforms and devices.
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
Integrations
C++
C
GitHub
Google AI Edge Gallery
JAX
Java
JavaScript
Kotlin
Node.js
Objective-C
Integrations
C++
C
GitHub
Google AI Edge Gallery
JAX
Java
JavaScript
Kotlin
Node.js
Objective-C
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
Flowhub
Country
Germany
Website
flowhub.io/ide/
Vendor Details
Company Name
Founded
1998
Country
United States
Website
ai.google.dev/edge/litert
Product Features
IDE
Code Completion
Compiler
Cross Platform Support
Debugger
Drag and Drop UI
Integrations and Plugins
Multi Language Support
Project Management
Text Editor / Code Editor
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)