When it comes to business, I’m sure you know a lot of buzzwords get thrown around.
Two that you’ve probably heard recently are “machine learning” and “automation.”
Are they the same thing? Do they leverage each other? What are they?
This blog post will discuss the above and dive deep into the differences between machine learning and automation – and how these changes may affect your business.
Difference Between Machine Learning and Automation
People often confuse machine learning and automation and mistakenly use the terms interchangeably, but there is a slight difference between the two.
Think of automation as the offloading of processes from your business.
This can be done with software you purchase or build or, on a broader scale, by buying companies that do things your company is interested in pursuing.
Some examples of automation are a simple excel formula that formats client information correctly or, on a larger scale, purchasing a cybersecurity firm with preestablished internal methodologies to add that element to your business.
While Machine Learning is a subset of Automation, Machine learning is about allowing a computer to figure out something without being explicitly programmed.
For example, a machine learning algorithm might be used to identify specific features of an image and label it automatically or create a prediction for how long it would take to receive a package from across the country.
The image below that depicts how these two interact.
As we can see, machine learning can be a part of automation, but there does exist subsections of machine learning that have nothing to do with machine learning.
For example, many data scientists use machine learning as an analytical tool to gain insights from data to leverage these to make smarter business decisions.
This process will be very hands-on, and the insights gained are one-off and not repeatable.
Ultimately, the two technologies have unique use cases, and while they intersect often, both will continue to play a vital role in the technology revolution.
Is Machine Learning Always Automated?
Machine learning is not always automated.
Most machine learning is used to gain insights, not to build repeatable systems.
In saying this, the end goal of many machine learning projects is automated decision-making.
How Does Artificial Intelligence Relate To Automation?
Since machine learning is a subset of artificial intelligence, we know there is a ton of overlap between AI and Automation.
Artificial intelligence is defined as computer systems making decisions for us, whether by humans’ predefined rules or machine learning.
In either of these situations, an automated system can be created to allow users and businesses to leverage these systems as a form of automation.
See the image below for clarification.
How Does AutoML Relate to Machine Learning and Automation?
Training and building accurate machine learning systems is complicated, and it takes expensive professionals to do it correctly.
AutoML is an overarching term that describes a specialized subset of machine learning that focuses on streamlining the development of these algorithms by automating the whole process – from data to an accurate model.
This allows businesses to purchase software instead of taking on the daunting task of setting up their own machine-learning teams.
While in general, machine learning is sometimes a subset of automation, in this instance, automation is a subset of machine learning.
AutoML is an exciting new area of machine learning that gets better and better every single day.
Eventually, will All Of Machine Learning Be Automated?
If you’ve ever seen terminator, you know how scary the idea of machines creating algorithms is.
We’ve already seen this with the invention of GANs, where highly realistic images that don’t resemble anything we’ve seen before can be created.
If you want to see how cool this really is, check out thispersondoesnotexist.com and see how accurate those images look.
While images and NLP have made considerable leaps in autoML, other subsections of machine learning still need to catch up.
In the long term, most machine learning will be automated, but I don’t think we will see that for the next 100 years.
References:
https://en.wikipedia.org/wiki/Generative_adversarial_network
Are AI and Automation a Threat to Jobs?
While I know everyone is scared that AI and Automation will eliminate their jobs, this historically hasn’t been true.
Whenever a job is eliminated by automation (and it does happen), another is created.
Think about the industrial revolution; when Henry Ford initially created the assembly line, everyone was scared that everyone’s jobs would be eliminated.
That didn’t happen; more jobs were created in factories, higher wages could be established, and overall quality of life improved.
This same thing will continue to happen with AI and automation.
As jobs are eliminated, higher-paying jobs will replace them, and the overall quality of life will improve.
References:
https://www.thehenryford.org/collections-and-research/digital-collections/expert-sets/7139/
Will ChatGPT Automate Any Jobs Right Now?
While state-of-the-art NLP (natural language processing) models are scary, they’re a little too new to worry about at the moment.
Currently, these models are too expensive to train and to keep up-to-date, so while they could automate simple things like logical questions and answers, there is still a considerable training gap that needs to be figured out before Google and other search engines are out of a job.
Check out openAI and ChatGPT below:
Other This Or That Articles
We’ve written a couple of other articles that are very similar to this one; check out:
- Full Stack Developer vs. Machine Learning Engineer
- Data Science vs. Bioinformatics
- Data Science vs. Operations Research
- Machine Learning Vs Programming
- Heuristic Algorithm vs. Machine Learning
- Machine Learning vs. Human Learning
- Data Science vs. Economics
