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We are in an era where technology helps us to get a fair share of the profit in our businesses and every other thing.
And when developing mobile apps, you need to be very specific about:The goal of a mobile applicationIt targets the audienceThe time needed to develop the app, finallyThe platform on which the app is developedOnce you are clear with the answers to all of these questions, developing the app becomes easier.
It helps to move in the right direction.
Incorporating hat your competitors are missing (app features) can help you gain an edge over others.Creating a Design and Development ModelPrototypes are new sketches that help define the flow of mobile app improvement with respect to app production and design.Having a plan at your end will make it easier to follow the procedure to get more.
Whether it’s design or development, a pre-planning approach is always the best approach to completing tasks in a structured manner.It is only at this stage that the design and development of mobile applications (agile or waterfall, depending on the need) is suggested.
When hiring a programmer, remember to get experienced resources on board.Test your app again and againMaking mistakes is human and programmers are no different.
The way I usually describe Artificial Intelligence evolution - at least in the next ten to twenty years - is to say that it will be applied in a very narrow domain and, for the most part, what we do not see as workers - we will live our lives, we going to do our job - is that we won't know that AI is there.
The whole idea of robots as AI - our robots, getting us out of work, eliminating human needs - is part of the fantasy associated with them.
I think what we need to understand is how AI, in a very the narrow environment can help alleviate many stress factors and workloads and the tremendous burden that technology has placed on us as humans.Frankly, technology has become very boring and the time-consuming thing for many people and also a very frustrating thing.
What I see is very narrow usage, very limited in terms of AI implementation, but yes, it is very valuable.IRobot is a great example because what you do there is a device that not only can follow a set of rules on how to clean a house but can also learn so that he can understand when you move furniture and plan routes accordingly.
I think we will increasingly work with, be exposed to and collaborate with, devices on many scales on a very small scale - your thermostat, your vacuum cleaner - up to a very large scale.
For example, with autonomous vehicles, one of the biggest conversations today is not how we make them without drivers - we are very close there, what they call level four, on the data storage side - but how to make it more personal; personalized for what you feel on that day.
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