Top 10 advantages of AI in mobile app development:
Artificial Intelligence (AI) technology is the new normal. As everything is powered by AI in the current time, it has altered our way of living. The widespread adoption of AI across businesses and corporations is helping them in streamlining their processes, increasing productivity, boosting efficiency, and reducing costs. Here are the top 10 benefits of AI in mobile app development.
- Speech recognition technology: Unlike us, computers’ language is so simple it has only 1s and 0s. Ours is so complicated we use puns, sarcasm, movie references. With Natural Language Generation, data can be assessed, analyzed and communicated with precision. Emails spam box or voicemail transcripts on our phone, Google Translate, all are examples of NLP technology in action and with Siri and google assistant everyone is aware about Speech recognition.
- Improved security with Biometrics: Biometric authentication and verification are in use virtually everywhere in the world. You’ve probably used it at the office to clock in your day or even used fingerprint recognition to unlock your smartphone. Many security applications include Facial recognition or fingerprint recognition. For example, in access control, the system uses face recognition as one of its components. That is, given the photo (or video recording) of a person, recognize who this person is. In other words, the system needs to classify the faces into one of many categories (Siva, Rama, Krishnan and so on) or decide that it is an unknown face. Here the goal is to verify whether the person in question is who he claims to be or not. To deal with different lighting conditions, facial expressions, whether a person is wearing glasses, hairstyle, etc., it is desirable to have a system which learns which features are relevant for identifying a person. Every human body is naturally distinct from all the others. Even identical twins have different biometric identifiers, such as unique fingerprints. This only adds to the robustness of a biometric security system. Only authorized users can get past the security check.
- Automated reply functions with chat bots: Chat bots which helps businesses to give automatic replies to users queries through WhatsApp, SMS & Websites without deploying any employees at backend and Its future of friction less and instant business communication
- Emotion recognition: Artificial Intelligence plays a crucial role in reading human emotions from the face. Emotion recognition technology uses advanced image processing to allow the capture of human feelings with voice intonation and speech signals. This technology is exceedingly popular among various startups. More importantly, Emotion recognition is now being implemented to prevent suicide risks in the psychological and health sectors.
- Image Recognition: This is a great addition for mobile app development and depends on the detection of any object through a digital or video image. This technology identifies license plates, analyzes clients, and diagnoses diseases. Even there are Apps like what the font that scan the text and provide you with fonts that are similar to it, which makes it hassle-free for designers who have to go through umpteen number of text samples.
- Quick Interaction and Competitive Business Solutions: Since the introduction of machine learning in Artificial Intelligence, businesses are already transforming the methods of engaging their users. With AI’s personalized information, companies, developers, and patrons can consider the possibility of having intelligent interactions within mobile applications. This highly versatile technology is responsible for learning the choices and trends of users and later processes the information for the delivery of precise solutions.
- Enhanced search: The biggest way search engines use AI is to rank web pages, videos, and other content in search results. Most readers will be familiar with the concept of web page ranking. That is the process of submitting a query to a search engine, which then finds web pages relevant to the query and which returns them in their order of relevance. To achieve this goal, a search engine needs to ‘know’ which pages are relevant and which pages match the query. Such knowledge can be gained from several sources: history, the link structure of web pages, their content, the frequency with which users will follow the suggested links in a query, or from examples of queries in combination with manually ranked webpages. A rather related application is collaborative filtering. Internet bookstores such as Amazon, or video rental sites such as Netflix use this information extensively to entice users to purchase additional goods. Voice and visual search are increasingly going beyond text-based input, with voice and visual search rapidly becoming the preferred way to search on mobile and opening up more avenues for using AI-powered search. Gartner predicts that 70% of customer interactions will start with speech through smart speakers and assistants by 2023.
- Learning Behavioral Patterns: Most AI-enabled apps can learn from a user’s behavioral patterns and use that data to make the next session more intuitive and seamless. For example, if you are watching a Korean drama on Netflix and order Ramyeon in Zomato a couple of times, the machine learns that you crave for Ramyeons while watching K-Dramas. So, it learns that Korean dramas are a trigger and you respond by ordering them. Thus, you get ads related to Ramyeon restaurants in your feed, while watching a K- Drama on Netflix.
- Machine learning: Machine Learning is just one of the many applications of AI. The key principle of Machine Learning is that machines receive data and teach themselves based on it. These days, ML tools are the most highly demanded AI-powered tools for businesses. Machine Learning systems are capable of applying knowledge acquired via training from enormous sets of data in order to excel at facial and speech recognition, object recognition, translation, chatbots, etc. While a hand-coded program requires specific instructions to complete a task, ML learns to recognize patterns on its own to predict the next step.
- Natural language technology: Unlike us, computers’ language is so simple and has only 1s and 0s. Ours is so complicated we use puns, sarcasm, movie references. With Natural Language Generation, data can be assessed, analyzed and communicated with precision. Emails spam box or voicemail transcripts on our phone, Google Translate, all are examples of NLP technology in action and with Siri and google assistant everyone is aware about Speech recognition.
As you can see, AI is capable of greatly facilitating the workflow of different organizations. That’s why adoption of this technology is moving at a breathtaking pace. Seasoned companies along with fresh-baked startups are integrating Machine Learning and Deep Learning algorithms into their applications to offer advanced features to end users. If you want your business to succeed and stay ahead of the curve, you will have to consider BSEtec- A company that offers AI- powered solutions by leveraging innovative methods and technologies to help businesses and organizations make smarter decisions, cut down on cost, and increase profits.
Originally published at https://bsetecindia.blogspot.com.