GITNUX MARKETDATA REPORT 2024

Machine Learning Vs Statistics: Market Report & Data

With sources from: marketsandmarkets.com, statista.com, ibm.com, deepmind.com and many more

Statistic 1

By 2024, the international Machine Learning market is predicted to reach $20.83 billion.

Statistic 2

Machine learning parcels out workloads in data centers, reducing electricity needs by 40%.

Statistic 3

When it comes to customer engagement, AI beats machine learning by reducing customer churn by up to 20%, while ML can only reduce it by around 10%.

Statistic 4

In natural language processing, deep learning models have an error rate of only 5.1% while traditional machine learning models lag behind at 8.5%.

Statistic 5

In 2019, more than 66% of businesses were using machine learning to drive business process efficiency.

Statistic 6

Machine Learning on its own is predicted to grow with a CAGR of 43.8% between 2018 to 2024.

Statistic 7

By 2022, artificial intelligence, including machine learning technology, is expected to create over 58 million new jobs.

Statistic 8

About 77% of devices that we currently use are utilizing machine learning in some way.

Statistic 9

While machine learning algorithms can reach an accuracy rate of 82% in detecting malware and cyber threats, deep learning algorithms can achieve a superior rate of 95%.

Statistic 10

Nearly 60% of business processes can be automated with machine learning.

Statistic 11

Machine Learning showed an accuracy of 81% in predicting heart failure, while traditional statistical methods achieved only 65.8%.

Statistic 12

Machine learning algorithms can reduce traffic congestion by 25% compared with current traffic signal systems.

Statistic 13

The adoption rates of AI-driven chatbots rose by 92% due to machine learning capabilities, as compared to regular rule-based chatbots.

Statistic 14

Machine learning algorithms could predict stock market changes with an accuracy of up to 60%.

Statistic 15

Machine learning algorithms detected prostate cancer with an accuracy of 72% compared to 58% accuracy of traditional methods.

Statistic 16

The estimated value for machine learning as a service is believed to be around $5.4 billion by 2024.

Statistic 17

Customers are 63% more likely to spend more money and time on a website that uses machine learning to provide personalized experiences.

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In this post, we explore a myriad of statistics showcasing the profound impact of machine learning on various industries and applications. From predictions on market growth and job creation to advancements in healthcare and cybersecurity, the data highlights the crucial role of machine learning in driving efficiency and innovation. Let’s delve into the numbers that underscore the transformative power of statistics in the realm of machine learning.

Statistic 1

"By 2024, the international Machine Learning market is predicted to reach $20.83 billion."

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Statistic 2

"Machine learning parcels out workloads in data centers, reducing electricity needs by 40%."

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Statistic 3

"When it comes to customer engagement, AI beats machine learning by reducing customer churn by up to 20%, while ML can only reduce it by around 10%."

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Statistic 4

"In natural language processing, deep learning models have an error rate of only 5.1% while traditional machine learning models lag behind at 8.5%."

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Statistic 5

"In 2019, more than 66% of businesses were using machine learning to drive business process efficiency."

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Statistic 6

"Machine Learning on its own is predicted to grow with a CAGR of 43.8% between 2018 to 2024."

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Statistic 7

"By 2022, artificial intelligence, including machine learning technology, is expected to create over 58 million new jobs."

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Statistic 8

"About 77% of devices that we currently use are utilizing machine learning in some way."

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Statistic 9

"While machine learning algorithms can reach an accuracy rate of 82% in detecting malware and cyber threats, deep learning algorithms can achieve a superior rate of 95%."

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Statistic 10

"Nearly 60% of business processes can be automated with machine learning."

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Statistic 11

"Machine Learning showed an accuracy of 81% in predicting heart failure, while traditional statistical methods achieved only 65.8%."

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Statistic 12

"Machine learning algorithms can reduce traffic congestion by 25% compared with current traffic signal systems."

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Statistic 13

"The adoption rates of AI-driven chatbots rose by 92% due to machine learning capabilities, as compared to regular rule-based chatbots."

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Statistic 14

"Machine learning algorithms could predict stock market changes with an accuracy of up to 60%."

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Statistic 15

"Machine learning algorithms detected prostate cancer with an accuracy of 72% compared to 58% accuracy of traditional methods."

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Statistic 16

"The estimated value for machine learning as a service is believed to be around $5.4 billion by 2024."

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Statistic 17

"Customers are 63% more likely to spend more money and time on a website that uses machine learning to provide personalized experiences."

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Interpretation

The statistics presented consistently highlight the significant impact and potential of machine learning across various industries and applications. From enhancing data center efficiency to improving customer engagement, reducing error rates, predicting diseases, and automating business processes, machine learning continues to demonstrate its value through its ability to drive innovation, efficiency, and accuracy. The projected growth in the machine learning market, along with the creation of new jobs and the widespread adoption of machine learning technologies, further emphasize the crucial role this technology plays in shaping the present and future landscape of industries globally.

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