Along with related tech such as AI (Artificial Intelligence), machine learning is having an ever-growing part to play in business and personal life, and its influence is set to grow further as large-scale data capture increases.

Is Machine Learning A Brand New Technology?

Not especially: while machine learning and related technologies are becoming mainstream and touching almost everyone’s lives in one way or another, its roots can be traced back to the 1950s when computer giant IBM first coined the term.

The early tech pioneers’ aim was to eventually produce computers that could literally ‘think’ for themselves and emulate human behaviour, and it’s fast approaching as machine learning in business and everyday life, AI and general machine intelligence develops.

Is Machine Learning, AI and Machine Intelligence the Same Thing?

No. While the terms may often be used interchangeably, they don’t mean the same and indeed follow a specific hierarchy:

Machine intelligence – the main ‘header’ term to cover all manner of ways in which tech, including computers, works in an intelligent fashion such as being able to learn from tasks its performed before and in a human cognitive sense through being able to see, hear, feel and make decisions.

AI – a significant branch of machine intelligence, it encompasses the way in which tech works overall in an intelligent fashion to behave and react like humans.

Machine learning – a branch of AI specifically covering the way in which computers process data in a particular way and learn from it without requiring further programming.

Computers can learn from the data they’re processing, and perform actions based on previous experiences through creating their own algorithms so taking less effort and time to perform similar tasks in the future.

What is Driving The Growth Of Machine Learning?

In a nutshell – data. With increasingly huge amounts of data being collected and stored constantly through everyday actions such as people using their smartphones, apps and more, it provides more useable information so machine learning in business is becoming a major method in using this information productively.

What Are The Benefits Of Machine Learning?

They are many and varied – machine learning for business and other areas of life will be highly influential in: Visual – machine learning techniques have given tech an amazing accuracy for recognising images with error rates as low as just 3%. To put it in perspective: ask a human to group say 10,000 photos of dogs into their respective breeds and it would take some time, likely several days, even if the person is a canine expert. By contrast a computer equipped with visual recognition tech could complete the same task in a matter of minutes. This remarkable visual ability is already being seen in areas such as passport control at airports with facial scanning, and it’s predicted to save considerable time in medical environments: for example, diagnosing for certain conditions using retinal examination. Focused personalisation – future machine learning in business will enable companies to understand their target market with increasing levels of accuracy. For instance, this means future product offerings can be developed based on detailed, real world customer usage data as opposed to more broad brushed research. Improved internet search – you may think Google and other search engines do a decent job of returning the information you require, but machine learning will help optimise online searches so they return even more relevant results. These will be based on factors such as preferences, previous interactions and past search terms used. Enhanced chatbot tech – chatbots are already playing a significant role in commercial settings to help automate certain marketing and customer service roles. The ability for bots to become ‘self-learning’ from the data they work with and thus more efficient makes this area of machine learning in business even more useful: the chatbots will naturally evolve to provide an enhanced experience for customers and prospects. Transport – aviation already benefits from machine learning and related tech with automated systems taking care of most of the actual flying. The self-driving car will use machine learning to adapt to changing road conditions and learn from new circumstances.

The Advantages of Machine Learning

Overall, machine learning – along with allied tech under the machine intelligence umbrella – offers many advantages in certain key areas:

Identify patterns – machine learning can quickly determine trends and patterns from huge amounts of data. For example, e-commerce names such as Amazon understand the buying and browsing habits and histories of visitors and customers, so tailor appropriate offers and content to individuals.

Full automation – once an activity is set up, the machines simply ‘get on with it’ by performing the task and learning as they go. A good basic example of machine learning is email spam identification software.

Wide uses – machine learning plays a big part in various applications including e-commerce, medical, financial, domestic applications and many more.

Ongoing improvement – as a machine learning activity progresses, it makes better decisions and works even faster as it acquires more knowledge through adjusting algorithms based on data flow. Predicting weather is a good example: as more ‘experience’ is gained through data collection over time, more accurate forecasts can be made faster.

Disadvantages of Machine Learning

Quality data – data needs to be of very good quality and unbiased to be of maximum value.

Errors and misinterpretation of data – setting up effective machine learning functions and interpreting data accurately needs the expert touch, so you should seek the services of IT professionals for your machine intelligence related needs.

Experts know how to interpret what the data is telling you. Get it wrong and you could, for example, send inappropriate advertising to certain prospects.

Machine intelligence and machine learning in business can be powerful allies, but errors and mistakes can cause problems – and these can go undetected for extended periods if you’re not aware of the pitfalls.

Experienced professionals can help you avoid them.

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