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Average Ratings 0 Ratings
Description
Harness the power of your data and create innovative artificial intelligence (AI) solutions using Azure Databricks, where you can establish your Apache Spark™ environment in just minutes, enable autoscaling, and engage in collaborative projects within a dynamic workspace. This platform accommodates multiple programming languages such as Python, Scala, R, Java, and SQL, along with popular data science frameworks and libraries like TensorFlow, PyTorch, and scikit-learn. With Azure Databricks, you can access the most current versions of Apache Spark and effortlessly connect with various open-source libraries. You can quickly launch clusters and develop applications in a fully managed Apache Spark setting, benefiting from Azure's expansive scale and availability. The clusters are automatically established, optimized, and adjusted to guarantee reliability and performance, eliminating the need for constant oversight. Additionally, leveraging autoscaling and auto-termination features can significantly enhance your total cost of ownership (TCO), making it an efficient choice for data analysis and AI development. This powerful combination of tools and resources empowers teams to innovate and accelerate their projects like never before.
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
Axonius
Bobsled
C++
Chalk
Datafold
Drivetrain
Embeddable
Evvox
Google AI Edge Gallery
Horovod
Integrations
Axonius
Bobsled
C++
Chalk
Datafold
Drivetrain
Embeddable
Evvox
Google AI Edge Gallery
Horovod
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
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/services/databricks/
Vendor Details
Company Name
Founded
1998
Country
United States
Website
ai.google.dev/edge/litert
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
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)