Understanding the Differences: AI and Machine Learning

We’re living in the Information Age, which definitely has its perks: We have so many options to connect. These include computers and smartphones, to the now-developing internet of things. While we as a society continue to advance, new concepts and ideas emerge. Today, I want to focus on two of these innovative concepts: artificial intelligence or AI and machine learning.

I find that the names of these two concepts are often used interchangeably; however, they are very different from each other at their core. To begin, let's define them.

Artificial intelligence: intelligence manifested by machines.

Machine learning: the automation of learning by machines without explicit instruction.

Artificial intelligence refers to the overall intelligence of a machine. Machine learning, on the other hand, refers to the learning process which makes the machine intelligent.

The two types of machine learning are supervised and unsupervised. With supervised learning, the data is classified and labeled. With unsupervised learning, the data is not categorized, and the machine does its best job learning without assistance. There are five stages to the machine learning workflow which are: gathering data, pre-processing the data, finding the best model for the data, training and testing the model, and evaluation.

Let's delve deeper into these two important concepts by looking at examples at how they are implemented.

Microsoft Azure’s AI and Machine Learning Features

What’s great about cloud computing is that you can use remote, online servers for various computer resources which are popular due to their convenience and efficiency. Microsoft Azure is the perfect example of a cloud computing service. Microsoft has implemented both AI and machine learning within Azure to give subscribers the tools of the future.

Azure offers some of the following cognitive services which form part of their AI solution:

● Vision
● Speech
● Language
● Search

Let's break down each of these.

Face detection, person identification, emotion recognition—these are some of the features within the Vision service. These allow you to leverage Azure to determine these factors within images and videos which can, for example, shorten the time spent on identifying subjects while editing videos.

The Speech service offers speech to text, text to speech, speaker recognition, and real-time speech translation. Do you do business internationally? The AI within the Speech service will instantly translate the language for you.

The Language service includes a content moderator, language understanding, and text analytics. Let's say your website or service offers a discussion forum or platform where people can comment. The content moderator will filter what it deems to be offensive or explicit.

The Search service allows searches through your apps and services to return results without any ads. One feature of this service—Bing Visual Search—gives you the tools to find similar images and products across the internet.

In addition to Azure’s cognitive services, the platform offers a Machine Learning service that allows users to do things like build and train their own custom ML models for use in other AI projects.

Post-Production and Adobe Premiere Rush CC

If you’ve ever edited a video, you have a sense of how long it takes to edit a video file. There are many factors involved such as video length, audio, color schemes, and more. Now, thanks to machine learning and AI services editing videos takes less time. That's because Adobe's artificial intelligence programs will take over some of the tasks and, as the machine learns those workflows, it becomes able to anticipate and repeat them.

To work with these services, you'll need to have Premiere Rush CC. Rush—a cloud-based video editing service—uses Adobe Sensei, an AI, and machine learning engine. Imagine being able to fix audio issues with the click of one button. That's the power of Premiere Rush CC! The fix makes voiceovers sound great by automatically adjusting the volume of background noise.

The AI and machine learning within Adobe Premiere Rush CC are based on what post-production video editors already do. Sensei follows these editors as they create beautiful finished products. Eventually, Sensei learns how it's done and takes over from there.

AI, Machine Learning, and the Future

It’s not unreasonable to expect that soon, computers will know what you want and what you need. These offerings will become more and more personalized and accurate as machines get smarter through machine learning and can make decisions that implement services through AI. It's only a matter of time until you have an actual conversation with a computer robot.

Conveniences such as Google Duplex—the AI system that currently allows users to make restaurant reservations over the phone while speaking to an AI-voiced Google Assistant service—are a benefit to living in the Information Age. More importantly, however, are the upcoming advances in medicine, science, and education. AI and machine learning will transform these fields exponentially over the next century, and beyond.

Our team at MelroseINC is passionate about moving towards a future when this is all possible and becomes the norm. That's why we offer solutions for your business in the technology, infrastructure, and engineering fields.

Whether it’s Microsoft Azure, Adobe Sensei, Amazon Web Services, or another AI or machine learning-infused service, MelroseINC can help you get started with these platforms. Get in touch with us through our contact form to get started!