The most important thing one has to be aware of is that every remarkable advancement in machine learning that have been made possible so far are interdependent on the emergence of big data. The ability of an AI based algorithm that generates useful solutions from the data will greatly rely on the existence of large amounts of data.
Here, the More data tends to provide more opportunity for an AI algorithm to find associations, as more associations are gathered, the greater would be the accuracy of predictions. In the similar way with humans, the more experience a computer has, the better the results would be.
So to provide a base to this booming “data”, Big data stores its worth while storing and managing the huge data in algorithmic and training implementations.
This trial and error criterion in machine learning necessarily requires an immense amount of processing power. It requires processing power specification specialized and designed particularly to enhance the performance of machine learning algorithms.
The primary challenge in context with AI is and will always be the data. “Data is the vital spark of AI. An AI system has to learn from data in order to be able to fulfill its function.
Unfortunately, many of us struggle to integrate data from multiple sources to create a single source of truth to build the product. AI will not solve these integrating data issues – it will only make them more inescapable.”
Essentially, there must be an affirmed methodology to data structure and data collection (mining) before running the data through a machine learning or deep learning algorithm.
Big Data is most undoubtedly here to stay at this point. Though this data driven technology(Big Data) would never draw away anytime soon, AI will be in high demand for the coming inevitable future.
Implications of big data with AI:
Big Data is entirely introduced with new levels of uncovering hidden opportunities. Developers couldn’t analyze large sets of data in the past, but now the ability to handle much larger data can result in unexpected output value. Huge datasets could be easily used to innovate product development.
More precise and quicker decision-making:
On combining AI insights, the access to new sources and its speed of data analytics technology, will result in an unimaginable level of informed decision-making with respect to accurate and smart analyses.
Efficiency boosting abilities to automate various processes has been benefited with the invention of Bigdata. The cost efficiency of Cloud computing has been decreasing gradually in turn making massive data storage more affordable. By adding scalable automated data, IT infrastructure collection would be the easiest way ever.
AI will become an ongoing, cyclical process with Big Data. Firstly, data is fed into the AI engine, probably making the AI smarter. Next, less requirement of human intervention in the AI to run properly. And finally, as less AI needs people to run, the more close society comes to realization of the full potential of this ongoing Big Data/AI cycle.
“By bridging the connections between these data sets, a considerable solution for every critical problem will be enabled from which distinctive AI-driven insights can be identified.” Analytics will become the most prescriptive and predictive by the advancement of AI in collaboration with Big Data ultimately leading to tremendous growth in product developments.