Business Transformation through Deep Learning
Posted By : Priyansha Singh | 28-Jun-2021
Business Transformation through Deep Learning
Deep Learning, a subclass of machine learning and artificial intelligence, is already making its way into an array of industry sectors. The neoteric technology is designed to imitate the way the human brain perceives and processes data, consequently enabling computer systems to solve complex problems.
A few years back, deep learning was touted to be a futuristic concept with an advanced approach that demanded innovation. However, today, it has a huge number of business applications with the potential to transform industries, surfacing as the next big disruption of Artificial Intelligence development services.
As deep learning has essentially become more widespread over the years, its applications are fueling an extensive range of industries, everything from content recommendation to autonomous driving and object classification. It has solved the limitations of the traditional ML algorithms and during its growth phase, it has caught the eye of multiple business operations.
Importance of deep learning
- Sentiment analysis of users
- Digital assistants
- Assists in building humanoid robots
- Reinforcement learning enables machines in legitimate learning processes
- NLP based language recognition and translation and image recognition
- Product malfunction detection enabled by computer vision
- Cognitive learning and computing
In this article, we will discuss the top deep learning applications and how they are pushing through in becoming mainstream.
Chatbots effectively fill the gap between the company and customer interactions. While an organization can not expect a human to be present 24x7 to answer customer queries, chatbots act as a digital personal assistant by resolving problems within seconds. Deep learning algorithms and applications are capable of communicating like humans and generate condition-dependent reactions. Industries such as retail, healthcare, logistics, banking, and more are using chatbots more than ever for their business operations.
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Big names such as Siri, Alexa, and Cortana have already made it through everyone’s lives. These cloud-based virtual assistants implement deep learning algorithms to recognize voice commands and respond to tasks.
According to a survey conducted by a UK-based Juniper Research Firm, the usage of digital voice assistants is expected to reach 8 billion by 2023.
The application of deep learning can be seen in automated translations of image language. For instance, with Google Translate, it has become possible to translate photographic images with text automatically into a real-time language in accordance with the user’s preference.
In today’s digital age, almost every industry vertical is susceptible to criminal activities and anomalies. Deep learning models can be efficient in spotting suspicious behaviors and system vulnerabilities in user’s accounts. Unlike traditional fraud detection frameworks that were enormously limited, deep learning-powered applications can provide companies with more reliable, adaptable, and comprehensive fraud detection systems.
Channels such as YouTube, Netflix, Spotify, iMusic, Amazon Prime, and more became a major hit because of their relevant videos, movies, and song recommendations. Based on users’ online content consuming behavior and browsing history, the systems generate accurate and relatable suggestions. Moreover, deep learning techniques are also assisting in generating subtitles automatically and adding sounds to silent movies.
In the advertising industry, deep learning frameworks are assisting advertisers and publishers to boost campaign performance through optimization and to increase ad visibility. Advertisements usually fall heavy on the pockets but deep learning models can significantly reduce a campaign’s cost per acquisition by 50%. It also helps in creating data-driven predictive ads, targeting them to the right audience, and sorting real-time ad biddings.
Deep learning is heavily used in creating robots that can perform human tasks seamlessly. Robots powered by deep learning use real-time updates to sense surrounding environments and pre-plan their activities accordingly. They can be used to carry goods in restaurants, factories, warehouses, hospitals, inventory management, and more.
In recent years, deep learning services and methods, algorithms, and applications have made significant progress and have undoubtedly become the new de facto standard in a multitude of industries. It is being actively used in manufacturing, healthcare, entertainment, eCommerce, banking & finance, agriculture, food, retail, and many other sectors. With the ability to self-learn via reinforcement learning, the deep learning frameworks assist businesses in prototyping and computing much faster than the normal timeframe.
What do you think about this future-focussed technology? If you need any help with idea validation, deep learning integration, or large-scale AI implementation, connect with our team of experts.
Priyansha is a talented Content Writer with a strong command of her craft. She has honed her skills in SEO content writing, technical writing, and research, making her a versatile writer. She excels in creating high-quality content that is optimized for search engines, ensuring maximum visibility. She is also adept at producing clear and concise technical documentation tailored to various audiences. Her extensive experience across different industries has given her a deep understanding of technical concepts, allowing her to convey complex information in a reader-friendly manner. Her meticulous attention to detail ensures that her content is accurate and free of errors. She has successfully contributed to a wide range of projects, including NitroEX, Precise Lighting, Alneli, Extra Property, Flink, Blue Ribbon Technologies, CJCPA, Script TV, Poly 186, and Do It All Steel. Priyansha's collaborative nature shines through as she works seamlessly with digital marketers and designers, creating engaging and informative content that meets project goals and deadlines.