Businesses in the world are rapidly evolving and there’s a significant need for automation-related applications and software, given the fact that the modern era’s technology has reached a point in which it’s possible to implement autonomous, self-learning features within such software, let’s analyse how machine learning will impact every business sector from 2019 and beyond.
The Blockchain Factor
Since what’s known as “The Crypto Boom” in 2016, there has been a significant rise in blockchain-related features in both fintech and general technological development. This is generally due to the fact that modern blockchain-based features apply machine learning algorithms to a general big data architecture: by combining cookies and overall users’ behaviour, in fact, Python-based tools are reshaping how the blockchain perceives such preferences, leading to an overall optimisation in terms of potential conversions. Although still at a very embryonic stage, these tools are definitely taking places within big companies who are trying to exploit data, such as Google, Apple and Microsoft. We’ll definitely see blockchain and ML-based tools more often in the nearest future.
Big Data For Conversion Rate Optimization
It’s no secret that digital marketing and online portals are taking over the traditional, more “direct” form of doing marketing. In order to understand how big data has impacted the business sphere, we must analyse its professional background: in 2018, in fact, the Data Scientist figure was one of the most required within the technology-related job market, with a net 300% increase compared to its previous year. Understanding how to program a certain page or tool, especially when it applies data to optimisation/customisation processes, is definitely the biggest part of this field and, given its technicality and embryonic nature, (still) we can say it will be a massive focus in the 2019’s development world.
Machine learning and deep learning are usually connected to the question “Is a robot going to take my job in the future?”. Well, Alibaba was able to increase its productivity level by a net 70% by completely automate their whole main warehouse in 2018. This is enough (for what concerns the impact of machine learning within this segment) to state the fact that yes, it is very likely to happen. There are many other businesses in the world who are approaching robotics-related technology in order to boost their productivity level and Intel is probably one of the biggest ones within the matter. It’s also safe to say that such an approach in product development will definitely be one of the main sources of income within the warehousing segment, both from a startup-ish perspective and from a triple-A one, in terms of companies who are producing such tools.
After the US, the European pole for technology development is definitely the UK. There have been many case studies for what concerns machine learning applied to the mobile app development world and, in fact, many are stating how deep learning, especially when applied within the technical due diligence realm, will be an architectural focus in development. Google UK has recently stated how SLAM (Simultaneous Localization And Mapping) will be their major focus in development, as it will give Maps a whole new look in both user experience and precision, automatically generating and updating the surroundings in 3D.
Although still at a very embryonic stage, Machine Learning will be a major focus in the development world as it will bring a whole new wave of professional figures and, most importantly, will speed up all those processes that have been bulky and, generally, quite slow in the past.
Paul Matthews is a Manchester based business and tech writer who writes in order to better inform business owners on how to run a successful business. You can usually find him at the local library or browsing Forbes' latest pieces.