Merging Artificial Intelligence and Big Data

Artificial intelligence (AI) is everywhere, smartphone companies are using it to create virtual assistants like Alexa and Siri, financial institutions use it to provide investment advice and retailers are using it to predict potential purchases in the future.

Clients will soon see AI bots on helpdesks in banks, it will have all the knowledge it could ever need to answer any query in a manner unlike any human assistant.

AI is the biggest buzzword in tech now, but what happens when it is merged with big data? Researchers are looking for ways to take big data to the next level by combining it with AI. Big data is extremely powerful and by uniting it with AI, it reaches a level of maturity that promises a bigger, industry-wide disruption.

Whatever the application, combining AI and big data will herald an age of new possibilities and astounding new breakthroughs and innovations in technology.

The most dramatic advances in AI are coming from a data-intensive technique known as machine learning. This technique requires lots of data to create, test and train the AI. Therefore, as AI is becoming more important to the economy, so too is data.

According to The Economist, the world’s most valuable resource is no longer oil, but data. It is not only the ability to obtain data about customers, but the ability to program AI to analyse the data. This has become important tools businesses use to compete against each other, and against potential entrants.

New entrants to the market lack access to good data and will face enormous hurdles. This has led some regulators to question the extent to which control over data creates barriers to entry. The hurdles faced by entrants may have implications beyond competition and innovation.

The application of AI on big data is the biggest breakthrough in the modern era, it redefines how businesses create value with the help of data. Big data has produced unprecedented breakthroughs in machine learning, that wasn't possible before.

With access to large volumes of datasets, businesses are now able to derive meaningful information and come up with valuable results. Companies can now process massive data volumes which was not possible before, they previously had to purchase expensive hardware and software.

The availability of massive datasets has corresponded with remarkable breakthroughs in machine learning, mainly due to the emergence of better, more sophisticated AI algorithms.

Google is also exploring big data-powered AI learning, its AI company called DeepMind has already developed an AI that can teach itself to “walk, run, jump and climb without any prior guidance”. DeepMind was never taught how to walk or run, it managed to learn it itself through trial and error.

The benefits of these breakthroughs in AI are astonishing and could be the foundation for further innovations in years to come. Looking at the rate of AI-learning, we can understand why a lot of people around the world are concerned with self-learning AI and the access it enjoys to big data. Whatever the case, the prospects are exciting.