Artificial Intelligence And Machine Intelligence- Are They Any Different?

It is no secret how dominant the effect of technology lies in our respective lives today. Every system we witness today has been created with great advancement incorporating both- machine and artificial intelligence. Therefore, your overall experience falls on how in sync is the machine and artificial intelligence working for you.

Technically, the tools which one requires to create a certain intelligent system include

  • Natural computer processing
  • Neutral networks
  • Computer vision
  • Deep learning
  • Machine learning*

*(Machine Learning essentially being a sub-part of Artificial Intelligence)

Today, an entire organization’s streamlined process depends upon how superior their artificial intelligence is. On top of that- making better decisions, enhancing the productivity factor and even uncovering data- methods like these decide whether an industry is suitable enough to maintain its position at a critical competitive edge and work in a smarter manner.

All in all, in this draft we’d be covering a huge contrast between both the terms so that there remains no space for the confusion of any sort. So, here’s how it goes, without any further ado:

Understanding Artificial Intelligence

When we take Artificial Intelligence into consideration, we are naturally implying intelligence that is not organic, but man-made. This man-made intelligence has modified the face of various industries- whether we’re talking about manufacturing, healthcare or even banking- the reason they hold massive popularity is that they foster advanced AI technology.

Artificial Intelligence is indeed the science of creating computers and robots that can behave in ways that both exceed and mirror human capabilities. Apart from that, contributions of AI to Mobile Application Development or applications that are AI-enabled can evaluate and contextualize data to offer information or trigger activities without the need for human intervention.

Take smartphone voice assistants as an example. We’re all familiar with Siri and Google Assistant; AI is the heart of these technologies we use. Along with voice assistants, we’ve got other examples of computer vision for images and language processors to identify the human language. The result of incorporating technological advancements like these yields exponential growth in one’s business.

It may also interest you to know

  • AI is expected to increase by 33.2% yearly between 2020 and 2027
  • The worldwide AI industry is expected to grow rapidly in the next years, reaching a market value of $190.61 billion by 2025
  • To solve data quality challenges, 48% of businesses utilize data analysis, machine learning or AI solutions
  • Marketing and sales divisions place 40% more emphasis on AI technology and machine learning for success than any other department

Understanding Machine Intelligence

AI encompasses Machine Learning or Machine Intelligence as an important aspect of it. Machine Intelligence allows machines to automatically learn and improve based on prior data without the need for any complicated programming undergoing’s.

This isn’t just confined to advanced technologies. But it can spread into various other domains like e-commerce, media, various industries, etc. The market for machine intelligence vision is currently growing and many of the world’s largest technology businesses are investing in these superior techniques. Developers also use these technologies to include machine learning into their mobile applications as well. In addition to that, integrating Machine Learning into Android provides a new method to construct apps- take barcode scanning or image detection as a prominent example.

Just by simply experimenting around with machine learning- programmers push the limits of how much they can enhance a computer system’s cognition. The resulting behavior is the demonstration of the working of Machine Intelligence incorporated in it.

Deep learning- a more advanced technique of machine learning, takes things a step further. Deep learning techniques employ vast neural networks; networks that essentially act logically and interpret data like the human brain to understand complicated patterns and generate predictions independent of human input.

Here are some additional stats based on Machine Learning

  • By simply utilizing the best out of Machine Learning, Netflix saved up to a good $1 billion
  • The accuracy of Google’s very own Machine Learning Program demonstrates 89% of accuracy
  • Machine Learning is also adopted by 20% of C-suite companies

Applications of Artificial Intelligence and Machine Intelligence

Computing machinery and intelligence applications in a good variety of sectors have been booming lately. These technologies improve corporate processes, increase productivity and are frequently utilized for predictive analysis simply because of their AI-empowered solutions. Here are a few examples from a variety of industries

  • Finance

Financial services organizations may use Artificial and Machine Intelligence to do investment analysis, examine the competitive environment and assure compliance in a timely and effective manner.

  • Tech

In the computer business, Artificial Intelligence and Machine Intelligence are used to detect cybersecurity threats, fraud attempts and other cyber dangers.

  • Insurance

These sophisticated technologies enable insurers to semi-automatically detect, analyze and underwrite developing risks, as well as uncover new potential income streams.

  • Healthcare

This natural language processing can be used by hospitals and other healthcare institutions to quickly digitize and organize documents, analyze data and make more informed choices.

  • Entertainment

The majority of entertainment streaming services use Artificial Intelligence and Machine Intelligence-powered algorithms to propose material based on the watching history of consumers.


So, this is how enterprise-level firms use cutting-edge technology such as Artificial Intelligence and Machine Learning in order to look beyond the competition and achieve scalable company success. These factors have become vital to stay put on the business front along with keeping a certain reputation intact.