Want to improve your machine learning training data? Contact Us

Test your machine learning IQ

How much do you really know about machine learning?
Answer 10 quick questions to find out now.

1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
  • Answer: e. None of the above, they all rely on machine learning

    Of all the possible responses, it’s tempting to decide that maybe GPS systems don’t really use machine learning, but the reality is that many do! Machine learning helps your GPS system do predictive analysis and proactively suggest you avoid locations along your route that are typically congested during your time of travel. Systems also use machine learning to recommend a nearby gas station when you’ve been travelling a distance that’s resulted in the need to re-fuel.

    Reference: 9 Applications of Machine Learning from Day-to-Day Life

Image

What is machine learning?

Machine learning is the process of teaching machines how to learn by providing them with guidance that helps them develop logic on their own and giving them access to datasets you want them to explore. The result is some form of artificial intelligence, or AI.

“Despite its name, there is nothing “artificial” about this technology – it is made by humans, intended to behave like humans and affects humans. So if we want it to play a positive role in tomorrow’s world, it must be guided by human concerns.”


Fei-Fei Li on “human-centered AI”, New York Times

Image

How does machine learning work?

Machines, most often computers, are given rules to follow known as algorithms. They are also given an initial set of data to explore when they first begin learning. That data is called training data.

Computers start to recognize patterns and make decisions based on algorithms and training data. Depending on the type of machine learning being used, they are also given targets to hit or they receive rewards when they make the right decision or take a positive step towards their end goal.

As they build this understanding or “learn”, they work through a series of steps to transform new inputs into outputs which may consist of brand-new datasets, labeled data, decisions, or even actions.

The idea is that they learn enough to operate without any human intervention. In this way they start to develop and demonstrate what we call artificial intelligence. Machine learning is one of the main ways artificial intelligence is created.

Other examples of artificial intelligence include robotics, speech recognition, and natural language generation, all of which also require some element of machine learning.

There are many different reasons to implement machine learning and ways to go about it. There are also a variety of machine learning algorithms and types and sources of training data.

Image

Why is machine learning growing so quickly?

In recent years, there have been 3 things that have contributed to the widespread interest in machine learning.

  1. Growth in all types of data
  2. Declining cost of storage
  3. Massive improvements in computing power

As with anything, there is evidence of other contributing factors and business drivers, but these three advances have clearly been dominant in terms of paving the way for accelerated use of machine learning and new and innovative applications of artificial intelligence.

2018 Machine Learning

Facts & Figures

Market Growth
Spending in AI and ML
International Data Corporation (IDC) forecasts that spending on AI and ML will grow from $12B in 2017 to $57.6B by 2021.
Source: IDC
Market Growth
# of Projects
Deloitte Global predicts the number of machine learning pilots and implementations will double in 2018 compared to 2017, and double again by 2020.
Source: Deloitte
Market Growth
# of Patents
Machine learning patents grew at a 34% Compound Annual Growth Rate (CAGR) between 2013 and 2017, the third-fastest growing category of all patents granted.
Source: IFI Claims
Key Enablers
Endless amounts of data
90% of the data that exists in the world was generated in the past 2 years.
Source: Forbes

Experts predict a 4,300% increase in annual data production by 2020.
Source: Accenture

From online retail transactions to videos to social media to internet searches, the volume is hard to fathom.

Every MINUTE of every day in 2018:

  • Amazon ships 1,111 packages
  • 400 hours of video are uploaded to YouTube
  • Google conducts 3,877,140 searches
  • 2,083,333 snaps are sent on Snapchat

Source: Domo

Key Enablers
Exponential growth in computing power
The most powerful supercomputer is 200x as powerful as it was 10 years ago

2007

46 trillion, 200 billion calc