What To Know About Using Artificial Intelligence For Big Data Analysis Posted on : Aug 17 - 2018

Artificial intelligence (AI) is revolutionizing the world of technology. Here's what to know about utilizing artificial intelligence for big data analysis.

For the past many decades of hope and promise, 2018 may finally be the year whenAI will gain meaningful traction and use within the Fortune 1000 companies. A survey conducted by New Vantage Partners represented around 97.2% of the executives who were willing to invest in launching and facilitating AI and Big Data initiatives. Also, it was discovered with this survey that all the AI and Big Data ventures are intertwined. Within organizations, greater availability of data will help in empowering the AI and cognitive decision making.

AI’s Noteworthy Accomplishments

Despite the long-term claims and promises of AI materializing and robots gradually replacing humans, nothing has been able to live up to the glittering expectations. AI hasn’t been able to play a significant role in improving the efficiency of the humans and neither did it launch us into a shining future. However, there are a few AI accomplishments which cannot be ignored:

• IBM’s Watson was able to defeat humans on Jeopardy.

• Facebook is relying on deep learning and indexing to serve the photo library to billions of users through Photo Search.

• Amazon makes use of AI to predict the demand for a certain product and to detect fraud.

• The scientists and biologists of Tufts University programmed such an AI which discovered the regeneration process of flatworms.

The relationship between Big Data and AI

With such tremendous volumes of data available, we can feed it into a machine-learning system which can learn how to reproduce the algorithm. Collecting the data is a convenient process as compared to analyzing it at each and every step. This means that we are actually pacing up the process at the AI front. Companies like Google, Facebook, and Amazon are making astounding accomplishments possible just because of their heaps of data. View More