AI Data

AI Data -magoosh

We are at the dawn of a technological revolution of greater magnitude than the internet and mobile communication technologies. In 1965, Gordon Moore, co-founder of Intel, theorized that computing power would be able to double every 18 to 24 months. For the next 50 years, his theory proved to be accurate. The High Tech sectors of robotics or biotechnology have made incredible progress.

Today, however, technologies like AI and Big Data are evolving even faster. The respective exponential growths of these two technologies are about to come together, allowing each to grow even faster. Artificial intelligence is no longer simply a film or a book. Elon Musk, Stephen Hawking and even Cédric Villani are some of the personalities to discuss the consequences on a large scale.

First, we are generating more data today than ever before. Every second, humanity produces 6000 tweets, 40,000 Google searches, and 2 million emails. By 2019, global web traffic will surpass 2 zettabytes per year.

This huge amount of data is the first step towards Account-Based Intelligence because the ABI requires granular information about each target company. However, it also raises a new problem. Companies must find how to turn this data into exploitable insights.

Indeed, this task is impossible to accomplish using traditional marketing tools or simple Google searches. The web is too massive and disorganized to achieve it as well. Many companies spend millions of dollars to mix data sources and solution points, which ultimately results in only a very low conversion rate. For good reason, this method usually results in sending the wrong message to the wrong people at the wrong time.

The tools of artificial intelligence for the ABI

Until recently, computers struggled to interpret unstructured data like Facebook content and YouTube videos. However, with recent advances in cognitive computing and processing power, things are changing.

However, this change can benefit businesses for their sales and marketing. Indeed, information on business leaders, the decisions they make, their attitude and demographics are not stored properly in small databases. They are scattered in social media publications, browsing history and geolocation data. Today, new tools allow startup leaders to make sense of this data.

Data Crawlers

The Data Web Crawlers undermine autonomously in search of unstructured data. They examine entities, establish relationships, and create customer profiles. With an estimated 70 percent increase in data per year, it is critical that these programs continually scan the web for the most relevant information.

Startups can use them to deploy the ABI. For example, to find new customers, browsing the web can reveal a niche of customers whose demographics match those of the best current customers.

In 2015, Microsoft acquired Metanaunix for this purpose. By using crawlers, the startup can explore a large amount of non-relational data. It then recovers insights from different sources faster and more accurately than humans.

Natural language processing

The natural language processing can examine the interactions between computers and humans to extract meaning from conversations. By spotting some words or phrases, this technology helps to analyze feelings about the brand. It also predicts which audiences will be more receptive to the company’s message. This is essential in order to communicate the right message to the right people, which is the primary criterion of the ABI.

If the company wants to know what people are saying about its products on social networks, natural language processing can explore social media publications, link them with certain consumer groups, and find out what’s important the most for each group. This system can be used to respond to consumer criticism and positive reviews, to solve problems, and to improve a product.

If you want to try this technology for yourself, be aware that the IV.AI startup allows anyone to try out their natural language processing platform. Type any phase to know the emotion that corresponds to it.

Machine Learning

The Machine Learning allows computers to learn and act without being programmed explicitly. This technology looks for patterns within the data to drive the actions of an Artificial Intelligence program, taking into account the context. The true ABI requires dynamic templates, and the Learning machine automatically adjusts them as new data emerges.

Without even knowing it, new companies are already taking advantage of Machine Learning. Facebook uses this technology to personalize the news feed based on clicks and likes. Other companies use this technology to predict customer loyalty or purchasing behavior, predict product performance, or anticipate risks.

Google Now is probably the most advanced Machine Learning app yet. It learns user habits, mimics their conversation style, and provides them with smart recommendations. For example, if a user needs to go to the airport for a flight that will take place in 30 minutes, Google Now can analyze the traffic delays and schedule an Uber that will take him there on time.

Artificial intelligence is strong, it without a doubt is a great technology. It can find data inaccessible to humans and distill meaning with great precision. Combined with the ABI, it can also guide the company to its next best customers. This technology will be the biggest change of the century in the field of business, and the revolution is just beginning.

The big data and artificial intelligence technologies are both inextricably linked so that a Big Data Intelligence can speak. Artificial intelligence has become ubiquitous in companies in all industries where decision making is transformed by intelligent machines. The need for smarter decisions and big data management are the criteria that drive this trend.

The convergence between Big Data and AI seems inevitable as the automation of smart decision-making becomes the next evolution of Big Data. Rising agility, smarter business processes, and higher productivity are the most likely benefits of this convergence.

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