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Find out how artificial intelligence applied to restoration works

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In recent years, artificial intelligence (HE) It has been one of the most interesting topics of discussion as they grow their capabilities and we get closer to see how technology is implemented.

According McKinsey, there have been twice as articles referring to AI 2017 what in 2016 and fifteen times more than in 2015, a trend that looks set to continue. With all this media noise about, we decided to write a series of articles to explain exactly What is artificial intelligence, how it applies in the world of restoration and benefit As you can Of the same.

Some say that artificial intelligence is like teenage sex: “Everybody talks about it, nobody really knows how to do it, everyone thinks that everyone does, so all claim that they are doing”.

Although AI systems can now learn a game and beat the champions within hours, they are difficult to apply to commercial applications. We in CloudReputation we are AI experts and we're working on put it in the hands of the whole sector of the restoration of the easiest and most attractive way for possible use.

We decided to write a series of articles to explain exactly what the artificial intelligence, how it applies in the world of restoration and how you can you benefit from the same.

What is artificial intelligence?

In the decade of 1950, Parents of field IA Minsky y McCarthy They described artificial intelligence as any work done by a program or a machine, If a human made the same activity, we would say that human beings should apply intelligence to achieve the goal or task. Obviously, This is a pretty broad definition, so sometimes see arguments about whether something is true or not IA.

Artificial intelligence systems generally exhibit at least some of the following behaviors associated with human intelligence: planning, learning, reasoning, Problem resolution, knowledge representation, perception, moving and handling and, to a lesser extent, social intelligence and creativity.

What is machine learning and deep learning?

The key technology is the Machine Learning IA (Machine learning), when a computer system is fed with large amounts of data, which is then used to learn how to perform a specific task, as understanding speech or captioning a photograph.

Surely, you will have also heard of the Deep Learning (deep learning), a branch of Machine Learning that uses a lot of data, often unstructured and photos, audio, text or videos, to teach computers how to do things that were previously only able humans.

The key technology is the Machine Learning IA (Machine learning), when a computer system is fed with large amounts of data, which is then used to learn how to perform a specific task, as understanding speech or captioning a photograph.

A good example is the perception Deep Learning, recognizing what is in a picture, what people say when they talk, help robots to explore the world and interact with it. Deep learning is emerging as a central tool to solve problems of perception in recent years. It is the core technology behind artificial vision and speech recognition. More and more people discover the Deep Learning is a much better tool for solving problems.

The key process are artificial neural networks. These are inspired by the human brain with layers interconnected networks algorithms, called neurons, supplying data from each other and can be trained to perform specific tasks by modifying the importance attributed to the input data as they pass between the layers.

Deep Learning shines wherever there is a lot of data and complex problems to solve and can be applied in many different fields.

Because right now?

One of the fascinating things is how long neural networks have been slow to be a success. The story goes back to the fifties but the Deep Learning, It has really only taken off in the last five years. The reason is the increased availability of data along with the large increase in the computing performance of modern processors.

The story goes back to the fifties but the Deep Learning, It has really only taken off in the last five years. The reason is the increased availability of data along with the large increase in computational performance of modern processors.

For a long time, we did not have huge data sets needed to make the work Deep Learning. These data sets became widely available only with the emergence of Internet, which made possible the collection and labeling of huge data sets.

Especially platforms as Google, Facebook O Instagram They helped a lot to the world sharing information of all kinds. But even when we had large data sets, often did not have enough computing power to make us of them and only in the last five years processors have become powerful enough and fast enough to train large-scale neural networks.

Artificial intelligence 2018: even more exaggerated than reality

Since robots until chatbots Y autonomous cars -of which we have spoken on several occasions in this Middle-, IA is still in its infancy. We are still far from machines that are as intelligent as humans and so far, We have seen only the 5% what AI can do. To put it in an analogy, we are more on the iPod or MP3 era in advanced iPhone X we have today in our hands. Between one and the other they have been more than 12 years.

 To put it in an analogy, we are more on the iPod or MP3 era in advanced iPhone X we have today in our hands. Between one and the other they have been more than 12 years!

At this time, access to IA is mainly confined to the Extremely large corporations with big budgets. There are several reasons why Machine Learning technology today makes so complex predictive IA, slow and costly. To name a few, teams of experts are needed in data science, which they are scarce and expensive, and there is limited access to data.

In CloudReputation we took a year and a half working on the more advanced algorithms IA to handle reputation of your restaurant. One of the main challenges is not only to create advanced technology so that you, restauradores, you may trust, but at the same time we are working on design solutions that make this technology accessible and extremely easy to use.

We have more than 1.000 restaurants in our platform testing our product and we would love to continue to grow with you.

Find out how artificial intelligence applied to restoration works
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About the Author

Armand Ruiz

Product Manager at IBM Watson specializes in Artificial Intelligence and founder of CloudReputation, Spanish startup based in Silicon Valley that offers online reputation for restaurants

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