Most artificial intelligence is generated from machine learning. This is a process that allows a computer to use software and a database of prior instances to learn what to do next. Most of the large cap tech companies are continuing to develop new products that are based on AI. The newest to the crew is Overton which is an Apple AI product.

What is Overton

Apple’s Overton framework is designed to automate AI system training. It’s like school for machines. Overton is designed to automate the training of AI systems. The Overton framework uses abstracts given by the developers. Apple intends to use Overton to limit work by engineers as the Overton system will eliminate many of the developer’s redundancies. The system will operate without needing any programing. The AI will read from several different data payloads through the AI training process. This will provide a framework for Overton to determine what to do. Overton will oversee application functionality. The goal of the machine learning process is to determine what kind of errors are made and how to fix those errors without needing an engineer. You can trade Apple on iFOREX share trading.

Here is how it could work. Generally during normal operations engineers would spend most of their time working on fine-grained quality monitoring. With Overton, Apple intends to limit the amount of work an engineer needs to do, automating many of the chores which focus on the upkeep of a system such as Siri. According to Apple, Overton has been valuable reducing the number of errors that are made by engineers from approximately 1.7 times to 2.9 times against production systems.

What is clear is that big tech continues to focus on AI. Amazon has Alexa, Google has a host of product within Google Home. Apple's machine learning work is considerable with a growing workforce and knowledge base via various acquisitions.

Can Machine Learning Drive AI?

It is not clear whether AI decision-making is ready for the leap. Most successful AI initiatives to date are based on machine learning. Machine learning is based on large number of data sets which can be used to teach a machine about prior experiences. The amount of data that a machine needs to be able to evaluate is growing. This requires integrating multiple data sources, often for hundreds to thousands of machines in larger companies. It requires merging expertise from both operations and information technology. A Machine learning process that is gaining momentum is image classification and face recognition. For this to further gain traction, companies need to provide their AI will unbiased data.

What seems necessary is a process that will reduce the need for large data sets, or a way to streamline the process of machine learning. Frameworks such as Overton, will make their way through other large cap tech companies and provide a potential framework to make AI more efficient.