Machine Learning vs Artificial Intelligence: What's the Difference?

In this age of human-like digital avatars and smart voice assistants to self-driving cars and emotionally intelligent robots, artificial intelligence (AI) and _machine learning_ have long since gone from buzzword to reality. But what’s the difference between AI and machine learning? Which career pays more, what degree(s) do you need, and how do you know which to pursue? The good news is, no matter how you cut it, the future is bright for AI and machine learning jobs.

According to the Bureau of Labor Statistics, _the U.S. job market for computer and information research scientists_ (the category into which AI and machine learning jobs are bucketed) is expected to grow much faster than average, paced at a whopping 19 percent between 2016 and 2026. Research and Markets forecasts growth in the _global machine learning job market_ from $1.41 billion in 2017 to $8.81 billion by 2022, and Gartner predicts that AI will create 2.3 million jobs by 2020.

LinkedIn’s 2018 U.S. Emerging Jobs Report put machine learning jobs at the top of its ranks, and noted that the demand for AI and machine learning skills has extended beyond software and IT services and into education, finance, health care, and manufacturing sectors. According to LinkedIn, machine learning engineers, machine learning specialists, and machine learning researchers were among the top emerging jobs in 2018.

Unsurprisingly, machine learning and artificial salary ranges are also competitive. Payscale reports an average salary of $111,736 for machine learning engineers, and AI software engineers earn an average base pay of $103,035, according to Glassdoor. For those with a master’s degree, BLS reflects a median annual wage of $114,520, with the highest 10 percent of workers earning more than $176,780 per year.

But what exactly is the difference between AI and machine learning?

According to Andrew Moore, former dean of Carnegie Mellon University’s School of Computer Science and now head of Google Cloud AI, “Artificial intelligence is the science and engineering of making computers behave in ways that, until recently, we thought required human intelligence." These behaviors include decision-making, image and speech recognition, problem-solving, and translation, to name a few. Roomba, iRobot’s famous robot vacuum cleaner, is a typical example of AI in action. The Roomba can scan a room’s size, identify any obstacles, and figure out the most efficient cleaning routes by itself. _Newer models_ can even make a map of a house and figure out its floor plan.

Machine learning, on the other hand, is a subset of AI and involves learning from past data to make decisions or predictions. Using learning algorithms, machines are trained to identify patterns in historical data. These machines can then proceed with making decisions or predictions on their own using current or future data.

_(Riddle me this: What’s the Difference Between a Data Analyst and a Data Scientist?)_

Spotify is one of the many companies using machine learning. Based on your previous activity and the songs on your playlists, _Spotify uses machine learning_ to customize your recommendations and predict your musical preferences.

What are the most popular artificial intelligence and machine learning jobs?

The most common types of entry-level AI and machine learning jobs are usually in software engineering, earning _an average base pay of $85,868, plus a cash bonus of $7,745_ according to Glassdoor.

Other entry-level AI and machine learning jobs include:

• Computer vision engineer ($87,001 average base pay; $3,037 average bonus)
• Machine learning engineer ($114,826 average base pay)
• Research and development engineer ($73,672 average base pay; $4914 average bonus)
• Research scientist ($76,911 average base pay; $7,106 average bonus)
• Research engineer ($79,794 average base pay; $6,470 average bonus)
• Robotics software engineer ($89,761 average base pay; $7,732 average bonus)

As you improve your skills and gain years of experience, you can level up to a senior role, a manager role where you’ll get to lead a team, or an architect role where you’ll focus on design and performance.

Because an increasing number of industries are starting to employ AI and machine learning technologies—including aviation and space, engineering and construction, medicine, and retail—focusing on a particular industry and becoming an expert in that industry will give you an edge as you continue your career.

What skills are needed for AI and machine learning jobs?

Most, if not all, machine learning and artificial intelligence jobs require strong analytical and problem-solving skills and solid math skills (including logic, probability, and statistics). You’ll also need to know your theory and fundamentals, especially when it comes to algorithms and data structures.

In terms of programming, you’ll be expected to navigate commonly used languages in AI and machine learning such as C++, Java, Python, and R. Additionally, you’ll be required to have knowledge of software development methodologies and tools.

Which cities and states have the most (and the highest-paying) AI and machine learning jobs?

It’s important to remember that _average annual earnings fluctuate based on where you live_ (and work), and the job market in that area.

As of May 2017, California had the highest number of AI and machine learning jobs (5,750), followed by Virginia (2,670), Maryland (2,660), Texas (2,170), and Washington (1,340).

The highest-paying state for machine learning and AI jobs was New York ($136,540 annual mean wage), followed by Washington ($135,240), New Mexico ($132,210), the District of Columbia ($131,980), and Massachusetts ($131,620).

By city, AI and machine learning jobs in Brevard County, Florida paid the most ($159,380 annual mean wages), followed by San Jose, California ($158,170), Huntsville, Alabama ($144,580), Seattle, Washington ($144,530), and Boulder, Colorado ($139,650).

What are the educational requirements for AI and machine learning jobs?

Most AI and machine learning jobs require a bachelor’s degree in math or computer science, where you’ll learn the fundamentals of algorithms and logic, programming, and software engineering. A growing number of universities include AI and machine learning courses in their curriculum, and some have specialized tracks in these fields. _Carnegie Mellon University_ even offers a bachelor’s degree in artificial intelligence.

Many AI and machine learning companies prefer to hire candidates with a master’s degree in computer science, often with a specialization in AI or machine learning, which can be obtained either on-campus or online (like _Columbia University’s_ _Computer Science Master’s Degree in Machine Learning_ or the Lyle School of Engineering's MSCS-AI at Southern Methodist University).

Another way to specialize in AI or machine learning is through _online courses_ or boot camps like Springboard’s AI/Machine Learning Career Track.

If you’re leaning toward an academic path, you’ll need to get a doctoral degree in AI or machine learning. A doctoral degree may also be required by research institutions or R&D departments of companies.

Which is best for you: AI or machine learning?

Artificial intelligence and machine learning are rapidly shaping what the future will look like. Whichever path you take will be promising, and you’ll emerge a winner in the end.

Questions or feedback? Email editor@noodle.com