Blog: 8 factors predicting the future of Machine Learning, Artificial Intelligence, and Big Data
In this modern era, people are focusing more on big data, Machine Learning (ML), and Artificial Intelligence (AI). These domains have evolved and developed rapidly during the past 5 years. Currently, a lot of work with a research study and other application processes are running to manage this field.
The recently held Strata conference highlights some of the points which may concern developers and users working in these domains. Continue reading to find them out.
What and how will 5G improve the growth of ML and what are its applications and services?
O’Reilly’s Chief Data Scientist and Strata organizer, Ben Lorica, talked about 5G and trends of ML and AI. They say that with an increase in the bandwidth, the flexibility of 5G will also increase. The technology will move to edge computing. Moreover, China is a growing competitor in this field of technology and that businesses will grow with 5G investments in this domain.
How will skill-sets change for data scientists?
According to Google Cloud’s chief decision scientist, new technology tools have made it easy for any person with fewer skills to work in this domain. Thus, less technical and more skills of being data scientists are now accommodated into the business for perfect work.
How to merge work while being online and offline?
Currently, China still works on physical stores as in the case of Alibaba eCommerce group and Amazon, while, Bricks and Mortar stores are now moving towards concept online stores. It seems that the idea of offline stores are offensive while the idea of online stores is defensive. There is still much to do but companies are using expertise to manage the data and this is giving them a good advantage.
Data Platforms for new innovations
Presentation by data scientists proves that data platforms are playing key roles in building new products and shaping the business. New trends are bringing innovations where data generating sensors are embedded inside products.
Open Source software and open data need
Previously, open source software was utilized to bring big data, ML and AI products into services. However, companies are now focusing more on the importance of open data for new innovations. The quality of algorithms improves with improvements in data which gets input to them.
Open data is more useful and does demand expensive commercial contracts that are very difficult for newer companies to establish and manage.
How is real-time data important?
ML and AI projects do not rely on real-time data, but with newer systems coming into technology, the demand for real-time data increases. Currently, companies are using systems which work on data decisions and rapidly responds to real-time events.
Some legal and ethical issues
Dr. Sandra Wachter of Oxford University talks about legal issues. She pointed out how to protect personal data and how will GDPR reacts to legal issues. Moreover, decisions are generally made on the basis of that data by algorithms. This can cause some of the ethical issues.
The conference came to an end with the following concerns. How small companies which are not given access to large data-sets will compete in this era of big data and Machine Learning. This is indeed a danger as we talked earlier about online and offline stores. Thus, creating space for large companies to get themselves set.
This demanding fields of big data and ML will change the entire world in the way that Google, Facebook, and Amazon have for over 20 years.