Digital transformation has a lot of topics but only a few of them get enormous attention and focus. Machine learning has become the most talked topic in a short matter of time and all due to one reason. Artificial intelligence. It is in fact, the main driver behind this and numbers are hitting at over $5 billion by 2020.
Mega businesses like Google and Amazon, are investing a huge amount of money in building projects related to ML development and slowly but surely the future will include more machines than we have estimated.
Machine learning and innovative technology have ups but on the contrary, they have downs as well. A lot of challenges and processes are involved, issues are created in the making and only a few companies successfully overcome them and become better than the competition.
So far, there are three known challenges that companies face when it comes to machine learning. There is, of course, one single way to overcome them.
Beforewe start, let’s find out what is machine learning in the first place.
The ability of computer systems to educate themselves and make decisionswithout being previously programmed to do the required things is called machinelearning.
We are not fully aware of it but machine learning is already present in our lives. For example, Facebook uses ML algorithms to gives us the news feed we want while Netflix uses it to offer us the TV shows and movies we want to watch. Machine learning also prevents fraud because it is used in FinTech, and it is able to detect cancer cells a year before diagnosing cancer.
These companies benefit from machine learning accounts because it saves them billions of dollars and equally, customers love it because they want to receive everything they ask or look for without being questioned.
Different from big companies, small and medium companies are extremely behind and do not offer these privileges and lack of machine learning. According to the MIT Sloan Management Review, only 50 percent own some kind of Al strategy. The point often overlooked is the adopting of it. Here come the challenges mentioned before.
- Lack of Machine Learning development resources – The skills required in the IT business are complex, and to find and hire a relevant specialist can be a challenge indeed. Although there are a lot of people with IT careers around, the talent shortage is present because experts in this field are rare and cannot be easily found. Kaggle delivers frightening information. According to it, only 4, 5 percent of data scientists can be called machine learning engineers. Of course, coaching talents is an option but this will bring additional problems with the funds.
- Machine Learning talents require a lot of money – New York Times reports that Al and ML specialists seek $300,000 to $500,000 annually. The demand of them, which by the way is growing up as we speak is the reason why this is happening. On the other hand, we have the Ukrainian developers, with English proficiency, looking for a far smaller salary.
- It takes a long time to higher qualified ML developers – Believe it or not, the average time to hire a quality Machine Learning developer in the USA and Canada is about two months. It is important to mention that only 20 days are needed to hire a developer from Ukraine.
There you go. The three main reasons why small and mid-sized companies drop the idea of developing Machine Learning solutions. These issues can be easily solved in one way. Find a lower-cost country and hire a specialist development provider from there. International talents are as good as the local talents.
A foreign AI outsourcing company, which has a professional team of software engineers who are able to build ML solutions will offer you a lot of collaboration options and can make your project success.
You have to realize that digital transformation is the most important thing nowadays when it comes to business because it gives a lot of advantages and improves the revenue numbers. By employing ML/Al outsourcing IT Company you will stay ahead of every business and you will be able to destroy the competition for sure.
Eastern Europe has to offer a lot of ML specialists. Start contacting people from Poland, Ukraine, Belarus, and Romania. An outsourcing company is the only thing that prevails in the previously mentioned issues.