Although, this is an old and dusted topic the points I intend to discuss here are based on my 7 years of experience with mobile app development.<img src="https://media.coffeebeans.io/blogs/Hybrid-Vs-Native-App-1-2048x1152.jpg" alt="cover">Hybrid vs Native Battle
Yes, no doubt that a Native app can apparently give a better user experience. And no doubt that if you have budget constraints going native is a challenge. But there are a few points that we need to consider before making the decision. Especially, when there are so many beautiful hybrid app development platforms now.
<ol>
<li>What is the purpose of the app? If the app is a utility and adds to the existing business you are doing, it is worth considering a hybrid app. If the app itself is the main business, think if you really need a native app? I suggest native only if you have to use a lot of native features like GPS, the user experience needs to be kickass, and if you have the money. Most of the banking apps have gone for hybrid, to give you an example.</li>
<li>Cost of ownership. There is no doubt that the cost of development for native is almost double considering multiple platforms. But think about the total lifecycle cost. Each update to the OS, especially with iOS, needs reworking of your code. There might be deprecations, etc. that you will have to fix even if there are no functionality changes. Overall, the cost of maintenance is high.</li>
<li>Time to Market. Hybrid or Mobile app solution is a great way to reach your audience quicker. It’s not really a bad idea to provide MVP with this approach and go native if you see traction. Plus you reach all and not just Android or iOS users.</li>
<li>Enterprise Apps. If you are a company and want to promote BYOD, the Native approach can get expensive if you try making it work for all brands, versions, and different kinds of mobiles unless you force your employees to use one kind of Phone. 😉</li>
</ol>
There are various great Hybrid app development platforms now. Here are a few which are trending:
a. Ionic
b. Titanium
c. Sencha Touch
d. PhoneGap
<ul>
<li><a href="https://medium.com/tag/mobile-app-development?source=post">Mobile App Development</a></li>
<li><a href="https://medium.com/tag/native-vs-hybrid?source=post">Native Vs Hybrid</a></li>
<li><a href="https://medium.com/tag/startup?source=post">Startup</a></li>
</ul>
Credit: Mitesh Bulsara, Serial Entrepreneur and Coach, CTO, CoffeeBeans

This is an old and dusted topic the points I intend to discuss here are based on my 7 years of experience with mobile app development.

Hybrid vs Native: Old Battle — New Approach

Asha, one of the finest employees in her organization, fell into a financial crisis a year back, for reasons outside her control. She missed some payments on EMI and her credit score suffered. This is making it difficult for her to get a new job and is worsening her financial situation. Which in turn, is making it even more difficult for her to find a job.
This isn’t the truth, at least as yet. But you know that you are not very far from this reality. The reality where algorithms will start judging you and take more decisions for you. And before you know it, you will be in an Algorithmic Prison.
<img src="https://media.coffeebeans.io/blogs/Algorithm-Prison-1-2048x1152.jpg" alt="cover">
We are increasingly seeing the use of Machine learning algorithms in predicting multiple facets of life. Predicting if it is going to rain tomorrow is one thing, predicting whether a loan applicant will default, is an entirely different proposition. The algorithms are deciding if you should get the loan, if you are fit for a job, or if you are eligible for that insurance. Although, for companies, the loss of missing out on opportunities on risky propositions may not be worth it; for individuals, it could be life-changing and have very high negative repercussions.
To make matters worse, through connected systems, if you are denied one service, it is likely you will be deemed unfit for multiple such opportunities.
The Bias
The algorithms study multiple data points and behavioral aspects of the past and give out probabilistic predictions. If the past was biased, it is very likely the predictions will show that too. Thereby, possibly depriving certain regions and castes, and religions of opportunities. While we morally preach equality for all, the algorithms do not have moral values. At least not as of now.
Moreover, the algorithms make predictions while segmenting you into buckets. If on average, people like you from the same region, company, or race have defaulted, it doesn’t mean you are going to default too
The Polarised Views
If you are consuming a kind of content. the engines show similar content to you in anticipation of increasing click-throughs. Thereby, just adding to the confirmation bias of your opinions and creating polarised views. We are already seeing the impact of social media on election campaigns. And then there are companies, who are trying hard to use those analytics and help political parties. Media is the only source of information for you, and that is highly driven by algorithms on what to show you next. The movie Inception… its already here, just not in the form of the movie.
The Justice
Most of the algorithms often keep learning with data and make decisions on their own. This makes the systems highly opaque and difficult for a human to reason why a particular decision was made.
We have a proper judiciary system in place. But if an algorithm is denying you a job or a loan, who is to be blamed for that? If it is discriminating against a race or religion, can you explain how the algorithm made the decision? Well, the justice system has to evolve. For all you know, that will also be driven by algorithms.
Privacy — Huh?
You have thought of this at least once that Alexas, Siris, and Googles of the world are “listening”, to you. We have no clue how the companies are tracking our behavioral data for the purpose of providing the best recommendations and services possible.
Monika, a friend, through her privacy awareness, has enabled the highest security an app has to provide. But, there are services that are part of our lives now. Choosing complete privacy is not possible now. We all have to be socially connected. She has to use Maps frequently and share her location. Privacy — well, yeah!!!
Do the right thing
AI is the new hype and we are seeing new prediction/recommendation engines emerging every day. All the systems are being built for a reason and the reasons may vary from being as simple as generating more profits, to as serious as the security of a Nation. It is changing our world entirely, but the consequences may reach far beyond the original purpose.
We understand most of the data is about people’s behaviors and identity. We value and respect it with humanity, while consciously taking responsibility for the world that we want to live in.
An algorithm or software is not good or bad in itself. It is important how we use it. It is up to us, the engineers and the organizations in this domain, to make ethical choices, take responsibility, and Do the right thing
1)Machine learning
2)AI
3)Data Science

Asha, one of the finest employees in her organization, fell into a financial crisis a year back, for reasons outside her control. She missed some payments on EMI and her credit score suffered. This is making it difficult for her to get a new job and is worsening her financial situation. Which in turn, is making it even more difficult for her to find a job.

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