If you want to build a business online, you’ll want to locate it where your customers are. You’ve heard about traditional mediums like blogs, forums, catalogs, social media platforms and maybe you even have an app for your company’s services. The important factors to consider are how much attention your customers pay to the sources and how much time they spend on each platform.
Imagine that you’re building an outstanding mobile application that needs server side support for certain features, like syncing user data or showing posts from other users. Your app is useful and full of animations. However, sometimes it looks laggy while it’s performing server requests; maybe the server is slow, or it often responds with errors. Of course, most users don’t understand the real reason behind lagging – next time when they see a “network error” message, they remove your app, give you a ★☆☆☆☆ rating and write negative review.
Special thanks to @tanzor for his hard work on investigating server performance.
You can solve this kind of problem in two ways: either using optimistic models in your app and avoid showing a “network error” message, or improving your Node.js server performance. The following advice is based on our experience of improving backend servers for some of our mobile apps.
If you are an experienced backend developer, the following tips may be too obvious for you, but you may still find some inspiration!
Why Digital Ocean?
Read Part I where we deployed Parse Server on Heroku and didn’t like the development flow at all; that’s why we selected DigitalOcean as the host service for our Parse servers.
These two services work with different layers of backend infrastructure; Heroku abstracts you away from the ‘bare metal’ giving you configured and ready-to-use dynos, which is convenient at first glance, but can become problematic when your requirements grow or change. On the other hand, DO provides you with a clean Unix box which can be configured in any way you like. The configuration process is harder, it takes more effort, but gives you more flexibility.
Migration to Parse Server brought not only infrastructure related issues but also cloud code compatibility ones. We described challenges we faced during refactoring and prepared the detailed checklist for you.
Special thank you to our iOS Engineer Igor for his significant contributions to this post.
When we started writing on Parse, we expected that at some point, we may change backend provider. We don’t perceive Parse as long-term solution, but rather as a convenient tool to get things done. We have not taken fully to the backends on Parse. Nevertheless, we now have a dozen applications that use Parse.
We build our iOS applications in such a way as that if you suddenly needed to change the backend environment, you wouldn’t significantly modify the app’s code. For this purpose, we hide a networking layer deep inside the app, covering PFObjects with our classes (on ObjC) or protocols (on Swift).
The business logic is mainly implemented in the server-side code (using the Cloud functions and Cloud jobs) rather than coded inside the app.
When Facebook announced Parse shutdown on Jan. 2017 our first intent was to migrate backend code to the Parse Server instead of writing it from scratch using another stack.
Chat bots were one of the hot topics of 2016 and their use is only going to grow in 2017 – not just through big-name AI assistants like Alexa and Siri but also in cut-down, bespoke versions of these bots created by businesses and brands.
Facebook launched its chat bot platform back in April, inviting companies with a Facebook Page to add a bot to it — an automated, AI-powered service appearing through Messenger, using natural language processing to answer customer queries and provide help. Rather than placing orders through the website or over the phone, for example, users could get them through a branded chatbot instead.
Advanced Natural Language Processing Tools for Bot Makers – LUIS, Wit.ai, Api.ai and others (UPDATED)
UPDATE from Dec 22, 2016: Since the original publication of this article there have been some significant market updates which need to be considered. Google bought Api.ai and also released their own home-baked Cloud Natural Language API, Amazon introduced Amazon Lex – conversational API and Wit.ai is updating their Stories and making them even better.
Recent announcements of a bot framework for Skype from Microsoft and a Messaging Platform for Messenger from Facebook have transformed chat through a new platform. More and more developers are coming up with the idea to make their own bot for Slack, Telegram, Skype, Kik, Messenger and, probably, several other platforms that might pop up over the next couple of months.
Thus, we have a rising interest in the under-explored potential of making smart bots with AI capabilities and conversational human-computer interaction as the main paradigm.
In order to build a good conversational interface we need to look beyond a simple search by a substring or regular expressions that we usually use while dealing with strings.
The task of understanding spoken language and free text conversation in plain English is not as straightforward as it might seem at first glance.
Below we look at a possible dialogue structure and demonstrate how to understand the concepts behind advanced natural language processing tools. We also focus on the platforms that we can use for our bots today, including the API – LUIS from Microsoft, Wit.ai from Facebook, Api.ai from
Assistant team Google, Watson from IBM and Alexa Skill Set, and Lex from Amazon.
Ready to build a conversational bot for your business, but confused with the variety of platforms? Let’s talk!
A Dialogue Example
Let’s look at the ways we can ask a system to find ‘asian food near me.’ The variety of search phrases and utterances could look similar to this:
- Asian food near me please
- Food delivery place not far from here
- Thai restaurants in my neighborhood
- Indian restaurant nearby
- Sushi express places please
- Places with asian cuisine
But if we are curious enough, we can also ask Google Keyword Planner for other related ideas and extend our list by about 800 phrases related to the search term “asian food near me”. We use Keyword Planner for such tasks here because it is a great source of aggregated searches that users regularly perform in Google.
You don’t have to travel far in the tech world to find a platform embracing chatbots.
They were a big part of Facebook’s F8 developer conference in April of this year, Google revived the idea with its own Assistant tool when it launched the Pixel phones, and they’re also being rolled out across platforms like Skype and Slack.
Virtual workplace watercooler app Slack is a good barometer for the rise of the chatbot, with its parent company having invested $80 million in startups to help built software that integrates with Slack apps, particularly in the form of these automated bots that can respond to user commands.
Every other year, the computer industry doubles the amount of transistors per silicon chip, thus creating more powerful devices that have a smaller footprint on a board. Current SoC components are powerful enough to have the power of a Cray-2 supercomputer or even an IBM Deep Blue in your pocket. Just look at the performance of Qualcomm’s latest chip, Snapdragon 820, that is powering the new generation of smartphones.
With more power on a device we can use more complex software stacks like Android, instead of sticking with Linux. Such an option is good to consider because of commoditized mobile hardware components, the developer ecosystem, the availability of modern development tools, and the ease of use of network and telephony stacks.
Below we’ll look at these arguments in greater detail.
We are honored to be selected as a Top IoT Developer of 2016 by Clutch.co!
Selection was based on over a dozen quantitative and qualitative factors including: Ability to deliver (references, client’s experience and market presence) and Focus on IoT Development. Even more, Stanfy cited in the Leader Matrix as a “Market Leader.”
We are developers, and as developers, we often need to do some Continuous Integrations. I would, rather, even say that we need to do various automation because CI is not the only thing that we do when we need to automate things.
The automation/continuous integration setup itself is not boring – it’s always side work, which needs to be done, but not as often as the general work we do. But the results that most CI systems are producing are usually unexciting.
The same text, the same few lines of texts, the same number of test runs, the same number of failed tests, maybe there are some other metrics on your project…
What is a Landing page?
I’m pretty sure you’ve heard about them, but have you ever created one for your business? If not, why?
A landing page is a standalone page that visitors land on after clicking on an online marketing call-to-action. Each landing is designed for a specific marketing campaign. The purpose of a successful landing page is to grow your audience and convert visitors to customers, perhaps encouraging them to download the app, or purchase your product.
Almost Every Landing Page Consists Of These Elements:
- Your Unique Selling Proposition (USP)
- The main headline
- A supporting headline
- A reinforcement statement
- A closing argument
- The hero shot (images/video showing context of use)
- The benefits of your offering
- A bullet point list summary of benefits
- Benefits and features in detail
- Social proof (I’ll have what she’s having)
- Trust indicators
- A single conversion goal – your Call-To-Action (CTA) (with or without a form)