Paperspace vs Tensorflow Lite: What are the differences?

Paperspace: The way to access and manage limitless computing power in the cloud. It is a high-performance cloud computing and ML development platform for building, training and deploying machine learning models. Tens of thousands of individuals, startups and enterprises use it to iterate faster and collaborate on intelligent, real-time prediction engines; Tensorflow Lite: Deploy machine learning models on mobile and IoT devices. It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.

Paperspace can be classified as a tool in the "Machine Learning as a Service" category, while Tensorflow Lite is grouped under "Machine Learning Tools".

Some of the features offered by Paperspace are:

• Intelligent alert
• Two-factor authentication
• Share drives

On the other hand, Tensorflow Lite provides the following key features:

• Lightweight solution for mobile and embedded devices
• Enables low-latency inference of on-device machine learning models with a small binary size
• Fast performance