1. Security Paparazzi Application

As easy, quick and optimized it is to share, host and document photographs over the internet, it is as easy to exploit such services which could be a hazard to the personal life of almost anyone. Google I/O 2018 made us all witness a feature where your system shall be able to fetch out a set of images that has the concerned person within the frame. Besides this facial recognition as a secure medium and access feature is already reached an industry standard. This is totally possible because facial recognition has reached efficient and quality standards in the first place. 

If that is the case then why can’t the same technology be used to imply ownership of your own face which is a crucial part of your identity?

Why cant technology grant ownership of your facial identity by not letting it owned by anyone else who misuse it for any purpose whatsoever?

The simple crux lies in the fact that if google’s technology is capable of detecting particular faces and isolate them for easy sharing, the same piece of technology is also capable of isolating and deleting them from the control of someone who is not you.

As much independence, our social profiles provide, from an ethical point of view it is totally a valid point that you are the owner of your facial identity and no one else.

Implications of FaceAPP should let you have a better insight into this idea.

2. Applications With Better Mathematical Tools

Google I/O 2018 was also a demonstration of how smart the lens can get when it comes to taking inputs in real-time. This is related to taking language inputs written on paper and converting it into strings for the comprehension of the systems. While extensive research is being carried out to optimize this feature for almost every possible language, it should also be noted that the computing system is still alien to traditional mathematical language which has been the subject of research since the day mathematics ever existed. Considering the speed and accuracy features computer systems are capable of, it would be a great lift if the same lens feature could identity mathematical statements to its understanding. With enhanced machine learning features it seems exactly the correct point of time to execute such a functionality. At its lowest, it could simply help kids and teachers conduct a faster teaching process at least.

3. Applications With Better Music Tools

If mathematics can be a language of the requirement for a computer system then it must also be known that music is also a very old acclaimed language created by humans that have its origin on paper only. While the lens is able to grasp communicative languages like English which have a far difficult manuscript on paper, staff notations seem far much simpler to comprehend and process as per the current standards. This is heavily going to assist music learning and boost the processes of music schools and institutes who shall have more reliable methods pertaining to security and might help human personnel to be employed in better sectors. 

Meanwhile, we have to totally keep in mind that the smartphone is not just an extension of the iPod that just played songs for you. It has an operating system connected to the internet and other systems which can actually produce a musical note for you as well. So it won’t be far the day when AI shall be made to read music as well.

4. Applications With Better ProActive Food Apps

While all the art of cooking and producing taste shall always be vested in the hands of humans, AI can fill the gap and recognize our preferences amongst an ocean of choices and help us eat better. Lensed with great machine learning features your custom food app can record your habits and unburden you with the responsibility of making a choice and performing daily chores. Whether it is quick scheduling or letting the system know your preferences of taste, food applications shall be able to make much better and precise searches and deliver the best results which otherwise takes a good deal of focus, attention and time. Taking of massive connectivity and smart integrations, it is a total possibility that your fitness inputs fetched from your smartwatch might help nutrition analysts serve your healthier choices. And that is something every proactive fitness freak would crave for.

5. Unlike-Anything- Ever-Seen-Before Fitness Applications

Smart Watches and fitness watches are not just notification devices but are capable of taking valuable input which was never possible before this. This includes your pulse and heartbeats at your healthiest and dormant periods of time. Such data can help analysts mark the best routines and figure out any irregularities that might be a potential cause for future problems. More importantly, it is to be noted that such data was not maintained before and the corresponding empirical conclusions coming as a result of the research will be the first of its kind. The fitness practices coming as a result of that will be smarter and fairly accurate. 

As one of the top mobile application development company we at BrainMobi have a very clear understanding of the kind of technologies that shall emerge and the corresponding verticals it shall be applied too. We can help sketch out the most updated versions of such applications that shall always be a step ahead of the current ones. This will always be beneficial for your business and enterprise.

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Big Data is a term widely used to describe very large data sets which have a size which is so large that it can’t be handled using the common software tools prevalent in the market used to handle data. This data may be generated by social networks, banking, and financial services, e-commerce services, web-related services, internet search indices, scientific and document searches, medical records, web logs etc. Every app that you use generates a large amount of data which big companies use to find trends in the data or even to extract useful information from the data.

Big Data is associated with three Vs defining properties and dimensions:

Volume: This is the factor Big Data is most known for. Since we’re dealing with a lot of data, the volume is very large, almost incomprehensible. Facebook stores roughly 250 billion images. It has more users than China’s population and the number just keeps on increasing. Considering this factor, we can imagine how much data is generated by every single user. Much of that data is very valuable for companies. Let’s say, Facebook decides to add a new option for posting status updates. For doing so, Facebook would have to go through a large volume of data to find whether the users would like the new update or not. Based on this understanding, Facebook would decide whether it should go ahead and bring in the new option or not. And this is just one such example, m-commerce companies use information about the purchases to decide which what time of the year would be good for giving additional discounts which would lead to a lot of sales. The amount of data stored is insanely large, and with every passing second, a number of data increases.

Velocity: 250 billion images is a huge amount of data, isn’t it? But imagine the amount of increase in the data considering that Facebook users upload more than 900 million photos every day. This brings us to velocity. Velocity is the measure of the rate of increase of data. To handle this insanely huge amount of data, we would certainly need more responsive means of handling data.

Variety: Data comes in all shapes and sizes. From photographs to sensor data to tweets and encrypted data packets, data is everywhere, and in a surplus. The data is different from each other. Since there is so much variation in the types of the data, we can’t store data in the old rows and columns representation.

Additionally, we could consider the value to be a factor defining Big Data. It is important to choose which data is valuable and which data isn’t since a lot of resources are spent in handling the data. Data here is haphazard and needs special software to be handled properly.

In the next post, we would dig deeper into the world of Big Data with the tools that we use to handle these gigantic piles of data. Stay tuned until then. Do let us know your thoughts on our post in the comments below.

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