There’s a lot of information around machine learning (ML) facts that are consistently circling the internet.
Aside from the buzz behind the topic, machine learning technology comes with a wide range of technological adaptations.
It has become such a hot topic that experts believe there will be a 300% increase in investments in machine learning developments.
For some people, keeping up with technology trends can be somewhat challenging.
In this article, you’ll learn about some of the most important machine learning facts and statistics.
Machine Learning Facts in 2023
- Over 90% of the most important companies worldwide are currently investing in machine learning
- Around 97% of mobile users prefer to use a machine-learning voice assistant
- 74% of data scientists utilize machine learning tools
- Businesses have seen a 54% uptick in productivity thanks to machine learning
- Machine learning companies have raised around $3.1 billion
Machine Learning Stats
With the rapid development of machine learning technology, companies and consumers are shifting their attention toward what it has to offer.
Machine learning isn’t a brand-new technology, as we’ve been using the tech for quite a few years.
However, it’s starting to evolve at an extremely rapid pace, with seemingly new developments on a weekly basis.
Taking a look at relevant machine learning statistics will provide a better understanding of what we can expect from the technology moving forward.
1. Stock Market Predictions
When you consider the vast capabilities of machine learning, it’s understandable that the technology could be applied to stock trading.
It’s known that machine learning provides an accuracy of 62% when it comes to predicting highs and lows in the stock market.
You may not use it to pull the trigger on buy and sell calls, but machine learning can help you make better investment decisions.
As the technology continues to develop, this number will likely rise, which will help those who don’t have extensive education navigate the stock market.
62% is already a decent number, but machine learning shouldn’t be looked at as an all-in-one solution.
Combining your due diligence and the predictive information machine learning can offer will make you more prepared to handle each trade.
This is also helpful when the market is especially volatile and unpredictable.
2. Deep Learning ML can Detect Breast Cancer
Google has its own machine learning program called Deep Learning ML.
Although it can be applied to many different use cases, it comes with an interesting statistic that’s quite impressive.
Deep Learning ML is able to detect breast cancer with an accuracy of 89%.
This is groundbreaking, to say the least, but it shows just how intuitive and adaptable machine learning tech has become.
Machine learning as a whole offers many different medical applications that could change the landscape of detection and recovery for patients.
3. Companies See an Increase in Sales
Businesses that have been applying machine learning technology have seen a 50% increase in sales.
This number is more than enough to get other companies on board and comes with more than one upside.
These same companies have also seen reductions in call time of up to 70% and around 40% to 60% in cost reductions.
From a business perspective, it’s only smart to implement machine learning into your sales and marketing processes.
Machine learning only scratches the surface in this space, as artificial intelligence and immersive experiences also play a part.
We’re in a revolutionary era with how technology can make our lives easier and equally fruitful.
4. Machine Learning Finding its Way into the Sales Process
On a global scale, roughly 30% of all companies have integrated machine learning into their sales process.
With the benefit of time and cost efficiency, using machine learning to increase sales is a no-brainer.
It’s also becoming easier to use machine learning, as the learning curve isn’t as extensive as it used to be.
Nowadays, individuals, small businesses, and large corporations can all use machine learning to their advantage.
Adoption of machine learning technology on a corporate level is rising at an extremely quick pace.
The technology is also getting an immense amount of media support due to its advances in recent years.
At this point, it’s only a matter of time before machine learning tech is a normal part of everyday business operations.
5. Improvements in Productivity
Businesses that have integrated machine learning tech into their workflows have significantly improved overall productivity.
They’ve seen a 54% increase in productivity, to be exact, and this is across every level of these organizations.
Machine learning can be applied to numerous business processes, many of which can work with or without human input.
Whether you’re looking for a fully automated or collaborative approach, machine learning has many benefits.
You’ll find that, in due time, machine learning tech will be the option of choice for many different aspects of a business.
It offers time efficiency and helps reduce costs, errors, and downtime.
This is something that simply can’t be ignored, and the benefits of machine learning tech will only continue to expand.
6. Minimizing Errors in Google Translate
For quick and easy translations, many people look to Google Translate for help.
Unfortunately, it’s not 100% accurate, and many people end up dealing with some confusion due to the output errors.
With the help of a machine learning-powered translation algorithm, Google has been able to reduce errors by 60%.
This is a good look for the company’s translation technology.
Due to the nature of machine learning tech, errors will continue to be minimized until it’s essentially a non-issue.
Regardless of the known errors, people will continue to rely on Google Translate’s services.
People will also encounter less confusion between languages moving forward, showcasing another reason why machine learning is being widely adopted.
Although many different translation tools exist, Google Translate is one of the most efficient and intuitive options out there.
Interesting Machine Learning Facts
Statistics are definitely important when it comes to any industry, but there are numerous machine-learning facts that are bound to catch your interest.
The following facts pertain to different aspects of machine learning technology and its industry as a whole.
7. ML Requires Data
For machine learning to operate with effectiveness, it needs relevant, actionable, and precise data.
The technology puts data through learning algorithms to generate results that the users can utilize.
Machine learning is often confused with artificial intelligence. Although they’re part of the same family, they don’t work in the exact same ways.
Without proper data points, machine learning algorithms wouldn’t be as useful as they are today.
In addition, the capabilities of ML are quite expansive as these algorithms are refined as we learn and explore more of what’s possible.
You’ll also find that not all machine learning algorithms are the same, with some being more accurate or useful than others.
In some cases, certain machine learning technology is catered to a specific use case or industry.
8. Training Machine Learning Algorithms
What’s so amazing about machine learning tech is that it can be trained to improve.
The entire concept around machine learning is that the tech can be trained with the help of data input.
For example, by providing highly detailed and informational data, machine learning algorithms can analyze and refine its output.
This process has an expected learning curve, as the quality of data you provide directly correlates to how ML tech responds.
Nowadays, many ML algorithms are becoming much more intuitive and can provide stellar results with minimal data input.
This doesn’t negate the fact that more detailed data creates better results with the help of machine learning.
Some algorithms require trial and error to get the best results, but the technology can be trained to work in your favor.
9. User Error Can Affect ML Output
When machine learning technology fails to deliver what you need, many people immediately think there’s something wrong with the algorithm.
However, more often than not, this comes down to issues with user error.
Systematic errors can occur when a user provides training data that are incorrect.
The capabilities of machine learning are quite amazing, but it still requires collaboration from the user.
This is definitely true if you want to train a machine learning algorithm properly.
10. ML Tech is Here to Stay
With all of the hype around machine learning and artificial intelligence, many people are worried that this is the end of our way of life.
This is an overreaction to something many people don’t understand, as machine learning tech is better seen as a collaborative tool.
Many aspects of machine learning tech still require our input. Moreover, the technology can help to simplify many monotonous aspects of our everyday lives.
It’s another era in history that scares everyday people simply because they don’t truly understand what ML has to offer.
It’s best to accept that machine learning technology will continue to evolve, and your best bet is to use it to your advantage.
There’s no doubt that ML tech will cause a big shift in different facets of life, but this is in hopes that it’ll benefit our lives in more ways than one.
The Growth of the Machine Learning Industry
When you take a look at the machine learning industry from every angle, it consists of many different working parts.
The technology comes with a wide variety of adaptations and use cases, which has led to its integration in a variety of ways.
The growth of the ML industry is hard to ignore, as it is being talked about on a daily basis.
You may be aware of the technology’s relevance, but you may be surprised by a few of the following statistics.
11. Investments Continue to Increase
Many industry experts believe we could see a 300% increase in investments in machine learning technology.
This number is quickly rising as we speak, but it’ll only take a few years before we see this 300% increase.
This is roughly three times the amount ML and AI tech companies are receiving at this time.
You can only imagine how these investments might be applied to ramp up the development of machine learning tech.
12. Market Value by 2027
With the current relevance of the machine learning industry, many industry experts are estimating what the future has in store.
By 2027, it’s expected that the market value of the ML industry will reach roughly $117 billion.
This staggering number may be hard to fathom, but it’s entirely possible with the way things are going for ML.
The improvements we’re seeing at this time are only scratching the surface of what’s possible with machine learning technology.
The industry’s overall value will inherently rise with the help of fast-paced development.
13. Billions of Dollars Raised
There are thousands of companies that are taking part in the evolution of ML technology. At this time, there has been $3.1 billion raised by machine learning companies.
This statistic includes over 4,400 different organizations that are focusing their efforts on the development of machine learning.
Compared to where this industry will be in a few years, this number is actually relatively small.
The companies that are leading the industry forward will continue to push for more as their needs expand.
What we’re seeing now is the beginning of machine learning’s full potential.
The number of organizations that raise funds for the development of ML tech will also expand in the coming years.
The money they raise will go toward future developments centered around what the technology is truly capable of.
The Bottom Line
Some of these facts and statistics may seem shocking, but the industry is truly still in its infancy.
As the years pass by, it’ll be hard to escape machine learning tech as it finds its way into nearly every industry.
Aside from lifestyle applications, ML tech will revolutionize the way we live, whether we like it or not.
This article highlights machine learning facts that’ll help you prepare for what’s to come down the road.