The ways that AI will improve our smartphone experience in 2020

2020 is thought to be a big year for mobile technology transformation with Artificial Intelligence taking centre stage. It will enhance both the hardware and software within mobile phones, offering implications for both marketers and consumers. On average, we use our phones for more than 2.5hours per day and make about 35,000 decisions to which it usually helps us. Without realising, it AI in your smartphone is already helping you make more precise choices. 

Artificial inelegance is a notion which helps computers ‘learn by example’ from large data sets. The use of AI allows computers to gather information and rules in ways which humans would. Learning the information means the machine would be able to generate an outcome in the way a human would without being programmed with a set of rules to follow for every possible outcome. AI, in a way, helps computers to generalise the prediction of what might happen next based on patterns they have seen in the past surrounding similar circumstances. 

According to research gathered by Counterpoint, one in three smartphones will natively embed machine learning and artificial intelligence capabilities in 2020. This is a far cry from 2017 when machine learning and AI were not able to make headway into the mobile device industry due to the limited processing power on smartphone CPUs. AI applications require vast amounts of data processing even for the smallest of tasks and having them on cloud systems makes accessing them time-consuming and challenging, which is why devices with onboard AI-capabilities were a must. 

Fast forward to today, and AI is the backbone in several groundbreaking applications in industries such as video gaming and automotive. The emergence of Edge-AI technology helps to move many of the backend profiling AI capabilities to the phone. Tech giants like Samsung, Huawei and Apple have manufactured smartphones with powerful AI chips that can perform up to 5 trillion operations per second. With the use of AI, smartphones can provide a range of different befits like improving photo quality. 

At the end of 2019, Apple acquired UK based photography start-up Spectral Edge who developed a form of machine learning that can improve pictures in real-time. The technology works by combining images captured via a standard camera with data from an infrared shot. Together they significantly enhance the depth of colour in an image. In an online world fueled by social media and selfies, this is precisely the type of technology consumers would invest in. 

But what does AI in a smartphone mean, and how can it improve our smartphone experience?

AI battles your security threats for you

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AI-based cybersecurity solutions are designed, unlike humans, to work around the clock to protect us from attacks. It has the ability to respond in milliseconds to cyberattacks that would take humans minutes, hours, days or even months to identify. The use of AI can aid existing cybersecurity solutions, broadening their capabilities and pave the way for new ones. As networks get more extensive and increasingly sophisticated, they become less controllable by humans which is why AI implementation is crucial.  

Some credit card companies have adopted the use of AI to help financial institutions prevent billions of monetary losses in fraud. AI in cybersecurity is hugely beneficial due to the way it improves how security experts analyse, understand and study cybercrime. It can enhance the cybersecurity technologies that organisations use to combat crime, keeping us safe, especially when using mobile banking apps.

AI-assisted night shooting and other camera functions

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In some handsets such as the Huawei P20 Pro, AI is used to help capture images at night. It night shooting mode emulates the effect of prolonged exposure. The smartphone’s camera takes a series of shots at different exposure levels and then uses AI capabilities to merge them to get the best result in low-light conditions. 

Advanced AI object recognition is also used to take more aesthetically peasing pictures as it can blur out backgrounds in images with the use of only one camera sensor. AI is used here to map out and recognise the border of someone’s face and even judge where their hair ends and where the background begins in an image. This way, the smart software can decide what areas of the picture to blur and sharpen for better images. 

AI assistance- Google Assist, Siri & Alexa

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Voice-driven assistance such as Amazons Alexa, Google Assistant and Apples Siri are some the most convincing applications of AI in smartphones, even if they don’t mention them. This intelligent software can use voice recognition and speech synthesis, but down to their core, they use AI which feeds off data. Out of the three, Siri is the purest of digital assistance in terms of AI. It does not rely on data in the same way. 

Overall AI is transforming the way we use our smartphones and can change our smartphone experiences in many different ways. Of course, one of the most obvious ways is through our cameras. Being able to capture upload ready pictures without needing to edit them makes all the difference for faced paced social media. However, there some drawbacks to having AI capabilities on our smartphone from Smartphone Checker. For example, AI technology can cost a lot of money and time to build and storage for this type of software can be expensive. 

Its no surprise that we are unable to live without our smartphones and because of this reason the introduction of more powerful software means humans will become increasingly reliant and dependent on it which may overtime make us lose our mental abilities. Many also question is AI technology is ethically and morally correct. For some, the notion of computers and human-like robots recreating intelligence which is a natural immoral? 

Written By: Yasmita Kumar

She has been writing about various topics over many years now. Yasmita enjoys writing about technology and its impact on our everyday life. Other then this she also covers Health and Fashion and previously worked for the NHS.