Deep learning, in Spanish "deep learning" has become an important artificial intelligence practice with increasing penetration in the business world.
Currently, companies of the stature of Google use it, and it is estimated, according to Report Linker study, that its global market at the end of 2020 was 4.4 billion dollars. It is also expected to reach 44.3 billion dollars in 2027. Evidence of how decisive it can be in business success.
What is deep learning in computing?
In the words of Geoffrey hinton, one of the leading researchers in this area, the deep learning is "a new type of artificial intelligence in which you make the machine learn from its own experience ”.
The idea is that computers reproduce the way the human brain learns: by strengthening the connections between its billions of neurons.
In practice, powerful computers, massive data sets, trained artificial neural networks, and algorithms are used to enable machines to learn by themselves and gain the ability to perform complex tasks that are difficult to perform through traditional programming.
When dealing with the matter of what is deep learning, you should not confuse it with machine learning.
Differences between deep learning and machine learning
One of the main differences between these technologies, is that in the approach machine the computer needs to be guided during learning, as its behavior patterns are generated only through practice and repetition. In deep learning, on the other hand, the machine learns by itself. It can be said that the latter goes one step further than machine learning.
The technology known as machine learning started in the fifties and went Arthur L. Samuel, a pioneer in computing, who coined the concept in 1952. Already in the mid-eighties it began to position itself as a really important practice in the field of artificial intelligence.
Specifically, Geoffrey Hinton and other researchers demonstrated that they could program machines to improve shape recognition and word prediction. Already in 2012, after several advances in the area, he developed a network of 650,000 “neurons”, trained with 1.2 million images, which reduced the error rate in object recognition by almost 50%. Deep learning was born.
Since then, the development of deep learning has been accelerating, driven by other cutting-edge technologies such as Big Data.
What applications does deep learning have and how does it help business?
This technology has a wide application, ranging from the configuration of intelligent translators and natural language development for virtual assistants, to advanced image processing, process automation and predictive data analysis.
Among the many specific applications of the technology, you can identify customer preferences, automate personalized marketing, detect fraud, analyze medical images in a short time and with high precision, create identification/IP systems and cybersecurity actions in general.
In the end, these possibilities can drive the digital transformation of your business. In fact, this technology focused on companies achieves the combination of strategy and operations with a focus on innovation and data analytics, which translates into increased productivity and a more optimal value chain.
In Codster, we are experts in artificial intelligence, machine learning and deep learning. We can help your company to implement innovative applications based on these technologies, guaranteeing a high quality product fully aligned with the needs of the business and its customers.