How Machine Learning can Change our Future?

For several decades, hardly any science, business, or manufacturing have gone without computers. Every day we use thousands of routine computer processes such as web search, speech and text recognition, and spam filtering, without suspecting that most of these capabilities we owe to such computer science sub-field as Machine Learning (ML).

Machine Learning is considered one of the most progressive ways in the domain of the human-like Artificial Intelligence (AI). Engineers can implement ML techniques in many industries: automobiles, medicine, genetics, finances, bioinformatics, marketing, game playing, etc.  Thanks to Machine Learning, we can get accurate results for data analysis in minutes to make better and quicker decisions.

One must have noticed that ad sections on websites and social media show you the goods and information targeted to your tastes. How do they know that a person wants a smartphone like this? The answer is: when you surf through websites, Machine Learning algorithms remember your selected preferences and then recommend the goods that may interest you.

Nowadays, the amounts of accumulated data are so big that ever growing volumes of data make it possible to construct predictive models to automate processes for even not trivial decision making. The goal of the computer scientists of the new age is to teach machines how to find the “right answer” without being directly programmed where to look. The problem is that unlike programmed applications (that have clear instructions for actions to get some required results) Machine Learning algorithms can only build on statistics, input examples and previous experience, using large (if not infinite) set of possible models. Actually Machine Learning algorithms should work the same way as a human brain when searching for an answer.

The Machine Learning is not a brand new idea in IT; however, it now gains increasing popularity among a growing generation of programmers. Developers that deal with Machine Learning can select among variety of ready solutions for building ML models without the need to dive deep into studying algorithms and technologies. Among the best known MLaaS are AmazonML, Microsoft AzureML, BigML, Google Prediction API, and IBM Watson. Machine Learning technologies are actively used in real-world projects now. Good examples of ML application are:

• Spelling correction in web search engines
• Recommendations of similar products
• Recommendations of relevant articles according to a user’s previous search
• Analysis of information from IOT devices
• Credit card fraud detection
• Real-time language translation (like in Skype that can translate in real-time a conversation from one language to another)
• Text and voice recognition, computer vision
• Email junk detection
• Speech recognition in smartphones and tablets (Siri, Cortana, Google Now)

The importance of Machine Learning for future science and engineering is evident. Understanding the clients’ needs and interests, being up-to-date with economic global trends, creating marketing campaigns more precisely are only several ideas about how ML can help future entrepreneurs. Self-driven cars that possibly will make our life safer and eco-friendly also use ML algorithms. Using ML in medicine for more accurate and timely diagnostics, monitoring the effect of taking drugs, inventing new pharmaceuticals in shorter time periods – this is what the near future holds for us with ML.

And what if a computer could predict an enemy movements in advance, so that the government can prepare and increase security? Even now, when Machine Learning is only at the beginning of its development, there are already projects.

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Svitla Systems

Proven software development and testing provider at Svitla Systems

Svitla Systems is a proven software development and testing provider. We deliver unparalleled value to our customers, who rely on our expertise in managed teams and build-to-order software applications.

Founded in 2003, Svitla Systems is headquartered in San Francisco, California, with sales and development offices throughout the US, Mexico and Europe (Ukraine, Montenegro and Germany). If you are looking to scale up your technical team quickly, we are your trusted glocal partner.

Since 2003, we have served a wide range of customers ranging from big corporations and leading young companies in Silicon Valley to large educational institutions on time and budget. The list of our customers includes such well-known companies as Monster.com, BMC Software, Ancestry, Affymetrix, Ingenico, Logitech and Stanford University.

In addition to delivering build-to-order software projects for our customers, we use our proprietary Team Extension and Managed Team models, where our experienced developers and project managers become a natural extension of the client’s team.They are being assigned full-time exclusively to client’s project, making it easy to communicate, contribute and deliver throughout the development process.

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