In simple terms, AI and machine learning is a set of technologies that empower connected machines and computers to learn, evolve and improve upon their own learning by reiterating and consistently updating the data bank through recursive experiments and human intervention.
As a matter of fact, the technological giants, corporations, and data scientists worldwide are already foreseeing big data to make a huge difference in the overall AI and machine learning landscape. In the annual Big Data Executive Survey conducted by NewVantage Partners this year, 88.5% of top executives surveyed were found saying that AI is going to be the most dominant factor that will have a disruptive impact on their companies. Let’s have a look how is it going to realize in practical terms. [/vc_column_text][vc_single_image image=”2253″ img_size=”large” alignment=”center” style=”vc_box_outline” border_color=”vista_blue”][vc_custom_heading text=”Big Data to Enhance Artificial Intelligence” font_container=”tag:h3|text_align:center” use_theme_fonts=”yes”][vc_column_text]Inherently, machine learning is defined as an advanced application of AI in interconnected machines and peripherals by granting them access to databases and making them learn new things from it on their own in a programmed manner. As the size of big data is continuously growing and new grounds are being broken in analyzing its implications as well, it is becoming more meaningful and contextually relevant for the machines to have a better idea of their functions with the help of big data analysis.
For example, the automation infrastructure of a leather garments plant based in Bangladesh that exports its products to the entire European market will be able to judge market requirements for the coming winter season in much accurate and insightful manner if it is able to access and analyze big data reports about the market, financial and weather conditions of that area throughout the year. [/vc_column_text][vc_custom_heading text=”Big Data to Help Expand AI & Machine Learning Workforce” font_container=”tag:h3|text_align:center” use_theme_fonts=”yes”][vc_column_text]One of the major concerns people are having about AI today is that it will minimize human requirement in all the job sectors as most of the work will be done by robots and AI-based computers in future, while the truth is far from it when observed with the role to be played by big data in the picture. The sentimental and emotional big data analysis will always require human intelligence as the machines lack emotional intelligence and decision-making abilities based on sentiments.
For example, a data scientist analyzing the big data pertaining to a pharmaceutical giant that caters to the needs of South-East Asian market may be able to sense the pharmaceutical prescriptions to be launched in those areas keeping the local inhibitions and reservations in mind, while computer-based big data analysis can never yield such contextually sensitive search results.
Hence, the increasing collaboration between AI, machine learning, and big data will only make way for talented and capable human data scientists to consistently evolve and rise in the market, and by all means, they will be required in a much huge number as the applications of these technologies gain movement. [/vc_column_text][vc_custom_heading text=”AI & Machine Intelligence Solution Providers to Benefit from Big Data” font_container=”tag:h3|text_align:center” use_theme_fonts=”yes”][vc_column_text]Right now, the overall size of global markets for machine learning and artificial intelligence based solutions is highly limited. With increasing proliferation of big data analysis into the artificial intelligence and machine learning procedures, devices and machines will get smarter and able to perform in a better manner. This will lead to consistent improvement, enhancement and advancement in AI solutions which will boost the market adoption of these solutions, giving rise to a high increase in their market demand.
In his analytical piece, James Canton, a well-known Big Data, and AI expert suggests that as in near future even the network nodes, chips, sensors and the software programs that will run IoT networks will be AI enabled via the cloud or at the chip or infrastructure level, it will be impossible for the massive global IoT network of tomorrow that will process, distribute, collect big data to enable us, humans, to run this network without a digital brain or AI based solution that is smart enough to do this.
For example, big data analysis of AI best learning in the schools of rural and smaller towns of Latin American regions ten years hence will help inconsistent modification and revision of AI-based academic solutions, so that more schools and educational institutions will be encouraged to adopt artificial intelligence into their training and teaching methods and the market sector will witness a considerable growth accordingly. [/vc_column_text][vc_custom_heading text=”Big Data to help in Global Diversification of AI &Machine Learning Offerings” font_container=”tag:h3|text_align:center” use_theme_fonts=”yes”][vc_column_text]With the advent of newer technologies and increasing scales of production, the prices of AI and machine learning based solutions will fall considerably. This will result in a massive adoption of these devices in third world nations which have diverse cultural, religious, ethnic, linguistic and political affiliations and inclinations. Therefore, the artificial intelligence and machine learning solutions to be provided in these markets will have to be trained and skilled differently from each other.
Banking upon big data analysis of these factors from region to region, the artificial intelligence and machine learning solutions will be able to be relevantly molded and trained so that the sentiment of different demographics don’t get hurt, and these solutions also prove to be useful to the customers. For example, a women-centric artificial intelligence solution catering to the needs of Iranian women will have to be designed, developed and trained in an entirely different manner than the same being targeted upon the female customers in the Sri Lankan market. [/vc_column_text][vc_custom_heading text=”Big Data backed Market Analysis to Boost AI & Machine Learning Adoption” font_container=”tag:h3|text_align:center” use_theme_fonts=”yes”][vc_column_text]Right now, the market sector of artificial intelligence and machine learning based products is in its nascent stage. As the market will grow, players will come to realize what sorts of product offerings, features and functionality are preferred by customers to have or not have on their devices and solutions. Here again, big data will come as a formidable rescue to the enterprises developing and selling AI and machine learning based solutions.
A market-wide and deep big data analysis focusing upon the sales patterns, feedback, and suggestions gathered from a large section of customers will allow the companies to develop solutions and services that are found to be more suitable according to the requirements of their customers.
For instance, an AI-based solution predicting forecasts in the commodity exchange in India will be required to undergo enormous modifications and improvements to fulfil the requirements of a large section of sellers and buyers, owing to the huge number of commodities varying from each other in terms of demands in local markets, seasons of availability and the control prices[/vc_column_text][/vc_column][/vc_row]