As your app’s audience grows, bots and scammers become increasingly interested in your app. When we needed a scalable tool for breaking bots and users apart, we found it way too expensive to cover all the bases with reCaptcha, which we were already using. So here is what we did.
In an ideal world, a perfect developer would find time to read professional articles, attend conferences, and work on pet projects. This is not always the case in the real world: fatigue at work, personal and family issues, going to a doctor — there are a million things to do and reasons to say “not today.”
That’s why our Android team created the “developing together” internal meetup format. We either prepare short presentations on new topics or watch professional videos together. We have time to do things after work, and our conscience isn’t burdened. Furthermore, we can discuss the applicability of what we heard immediately with our colleagues.
What is more critical in a push notification — the text or the picture? How does it depend on the mobile platform? When can sending push messages more frequently get better results? What mistakes can be made while you’re figuring it all out? Learn about it in this piece by the team developing the push notification system for FunCorp entertainment apps.
Since most of our users are from the USA, FunCorp decided to update its icon and splash screen for the Halloween holidays last year. Let’s recall that story. The task seemed trivial, but in the process, we found some more cases and grew our essential checklist from 8 to 13 items (attached).
I’ll explain how the Microbenchmark library works and show examples of how to use it. Perhaps this will help you evaluate performance and solve controversial situations during the code review.
We often see pictures in images: comics, for example, combine several pictures into one. And if you have an entertainment app where people post memes, like in our iFunny, you’re going to run into that all the time. Neural networks are already capable of finding animals, people, or other objects, but what if we need to find but another image in the image? Let’s take a closer look at our algorithm so that you can test it with a notebook in Google Colaboratory and even implement it in your project.
Over the past 4 years, we’ve developed an adaptation process enjoyed even by ultra-experienced newcomers. Today, we’ll share its main stages and a basic checklist. You can easily adjust them to fit engineers of any level that you hire.
Most articles about the algorithms of the multi-armed bandit are too academic. They are filled with formulas and seem to imply that we have an immutable set of handles for pulling and n→∞ attempts. I will try to talk about these algorithms from the point of view of an ordinary developer, taking into account the real conditions in which our iFunny application for recommending memes works.
We share the zombie object detection mechanism we made for the iFunny app, and present tips for those who also want to get rid of this issue. So you turn on your laptop, open Crashlytics, and voila: EXC_BAD_ACCESS objc_release… What now?
Imagine how much memory space a 10k-pixel comic book takes up. And now imagine that you can’t compress it because if you did, it would lose too much quality and become unreadable. Curious how we at FUNCORP deal with this? Then read on!
We’ve been long working on improving the user experience in UGC products with machine learning. Here are our ten key lessons of implementing recommendation systems in business to build a really good product.
The iOS team of iFunny has gone from a completely ad-free model to using a variety of ad networks and formats in their popular entertainment app. In this article, we will discuss some of the less-apparent nuances of working with advertising SDKs that can affect the user experience and performance of your product and share the code that will help you fix them.
Overview of self-supervised methods.
While the demand for neural networks is growing, most state-of-the-art approaches to adapt them to business needs often lag, hindered by insufficient or absent markup. Supervised learning is hardly feasible in this situation, and standard unsupervised methods won’t work for most of your tasks. This is where self-supervised plans come to the rescue. Depending on the task, they require next to no markup or none at all.
A developer’s perspective (MLOps inside)
At iFunny, we are trying to compose the best possible feed of memes and funny videos. To rate our job, people use smile/dislike buttons and comments. Some of them even post memes about our efforts.
Recommendation systems will always stay relevant — users want to see personalized content, the best of the catalog (in the case of our iFunny app — trending memes and jokes). Our team is testing dozens of hypotheses on how a smart feed can improve user experience. This article will tell you how we implemented the second-ranking level of the model above the collaborative one: what difficulties we encountered, and how they affected the metrics.
Founded on years of work experience in testing
There is a tremendous variety of QA Engineer vacancies, ranging from junior to lead tester and even to principal QA Engineer. We’re often asked what qualities a senior-level tester should have compared to junior or middle-level ones. Let’s try to answer this.
Approximately 100,000 units of varying content come through our iFunny app daily, and every single one of them needs to be checked. We have already dealt with forbidden imagery by creating a classifier that automatically bans it. Next up — old memes, reuploads, and straight-up doubles that users try to sneak past the moderation.
To get rid of those, we have introduced a duplicate detection system. It had already gone through several iterations, but at some point, we realized it was impossible to put version-to-version improvements in proper perspective. And so we ventured into the Net, searching for books and articles that would allow us to examine currently existing approaches to duplicate detection and — most importantly — to their quality assessment. You can see what we’ve found below.
FUNCORP’s services and advertising infrastructure have recently undergone significant changes. In addition to the Prebid Mobile, we now also support and develop the Prebid Server to work with our apps.
We chose Prebid because we’ve been using its Software Development Kit for a long time and have enough experience and competence in working with it. This expertise allows us to improve and develop the service without compromising its stability. As a result, Prebid has become one of the critical services within our infrastructure.
It is pretty standard that as a project grows, so does the complexity of its build. Too many different technologies, third-party components, libraries, lints, server-side rendering, and project-specific nuances — as a result of all this, the configuration of a build may involve more than a thousand strings.
This article explains how you can automatically divide a dataset of images into clusters classified by qualitative contextual feature, thanks to embeddings from the much talked about neural network called CLIP created by Elon Musk’s company. I will give you an example using the content from our iFunny app.
There are different ways to remove a user’s personal information at the user’s request to make a product compliant with the CCPA or GDPR. The most basic method is to handle every request received by mail manually. The important thing is to make sure the process is as straightforward as it can be and clear to the user. So a little automation is not such a bad idea.
In 2020, for the first time since World War II, the world was faced with an epic, uncontrollable crisis. The overwhelming majority of the world’s commercial industries, including the tech industry, have had to deal with the negative impact of the pandemic.
In this piece, we’ll use a plain example to illustrate the existing types of DDoS attacks, and how businesses try to fend them off.
DDoS is a type of internet attack capable of disrupting anything from a phone booth to the Pentagon for those unfamiliar with the subject. A total of 5,351,930 DDoS attacks were recorded in Q1 2021 alone. The average attack duration was 50 minutes, representing a 31% increase.
At FUNCORP, we are contributing much to creating a safe and caring working environment.
It's not only about team building, serving food in the office, and other fancy things a social package company provides. It's also about nurturing an atmosphere of open communication, process transparency, feedback culture, and trust between co-workers.
iFunny users upload about 1,000,000 pieces of content to the app every day, including not only memes but also racism, violence, pornography, and other inappropriate material.
Previously, we checked all this manually, but now we are developing automatic moderation based on convolutional neural networks. We have already trained the system to divide content into three classes: it recognizes what can be included in user feeds, what needs to be removed, and what is hidden from the shared feed. To make the algorithms more accurate, we decided to add a specification for removing content that did not have such markup before.
Testing ad integrations is quite a tedious process. Since we work with third-party SDKs that can hardly be controlled, it can be challenging to automate the testing process. Nevertheless, to reduce testing time, we have developed and implemented a debug panel, which we will discuss in this article.
Year after year, March 8th is celebrated as International Women’s Day all over the world. It marks the social, economic, cultural, and political achievements of women while highlighting the problems they face in day-to-day life and the professional environment. The day also marks a call to action for accelerating gender parity.
FunCorp is fully committed and continuing its focus on providing ad transparency. In November 2020, we responded to an article published by Pixalate. As we previously noted in our blog post, we strongly disagree with the assertions and conclusions stated in Pixalate's article. After conducting our internal investigation, findings from our third-party experts, and soliciting feedback from our ad partners and clients, we have found essential inconsistencies and discrepancies between the article's allegations and how iFunny functions. These findings further confirm that iFunny did not and could not generate the purported fraudulent ad traffic.
How we process a colossal amount of content
The various social media channels and content sharing platforms all over the internet have paved the way for a whole new era of self-expression. Today, anyone can make videos, live stream, express themselves on social media platforms, or create content. In fact, according to a study from Comscore, when users create and share content on social media channels, they get 28% higher engagement compared to standard company posts.
Setting the record straight on iFunny
FunCorp, the leading global developer of entertainment tech products and apps, has been working in the entertainment technology field for over 16 years. FunCorp was started from a foundation of honesty in doing business and it prides itself on compliance with not only all existing laws, but the industry’s best practices. These values are ingrained our company. Since 2011, we have been one of the leaders of the mobile entertainment industry, with products spanning half the globe. We have always been mindful of our responsibility and we have always acted according to the principle "to make the world a better place.”
Leading up to TikTok’s potential sale in the U.S., unnoticed by many, there was a flash of news that ByteDance refused to disclose its recommendation algorithm and sell it as part of the American company. On the one hand, it’s a small thing, as most of the algorithms were developed in the last 70–80 years. The company that will buy TikTok will get a huge audience. On the other hand, tech companies and their recommendation systems are of great value. Let’s find out why.
How do we use it at FunCorp, and why it’s one of our most important tools
Going by the most recent reports, the number of users for smartphones will hit a whopping 3.8 billion by the year 2021. This sweeping increase in smartphone users has also led to a rising demand for better mobile apps. These modern apps also use tremendous amounts of data, and thus, a robust management tool for analyzing and managing this data has become a necessity. And this is where the use of Big Data technology for building apps comes into the picture.
The results after six months into the pandemic
Although the COVID-19 pandemic has led to economic, health, and social devastation, it has also created an unprecedented opportunity: to run the world's biggest-ever workplace experiment.
What was once seen as fiction in scientific movies has become a reality and has gained popularity across various sectors. Your smartphones, mobile applications, vehicles, and many other daily consumer items use AI to build essential parts of their business or product around machine learning (ML). Even more so, becoming more integrated into many aspects of social media AI is far from replacing human touch in social media. It is increasing both the quantity and quality of online interactions between businesses and their customers.
US digital ad spending has been growing at a double-digit rate for years even since the last recession. But the pandemic has changed all that. In April 2020 in the height of COVID-19, we took a look at how the pandemic if at all has had any impact on ad spending. Digital media consumption boomed as soon as lockdowns and stay-at-home orders hit various parts of the world from February through April. In mid-April, we shared information with VentureBeat regarding the fall of the advertising market by 20-30% YoY and 40-50% of the planned one. These numbers were indirectly confirmed, for example, by Twitter reports for the second quarter.
CIO of FunCorp, a mobile entertainment app development company, oversees the growth of UGC platforms with AI/ML content feed aggregation.
With the vast competition of digital products and the high speed of launching new ones, it is necessary to quickly and cheaply test the viability of product ideas. In this article, I will share my experience of creating an MVP on my own, i.e., in fact, by one iOS developer, about how I was looking for a balance while creating MVP, about tools, difficulties, and their solution. If you are planning to implement the first projects in mobile development or add a new branch of functionality to an existing product, this article is for you.
2020 was supposed to be an exceptional year for digital media. In the mass media, there appears to be more news about various companies downsizing. Although the situation is very unpleasant, it’s very predictable while only needing a small event trigger it. In recent years, there came considerably more venture money than projects, and many companies have used it without investing the money they received into the company’s fundamental values. Part of this can be attributed to not having a reliable business model and, in return, only providing enough to survive merely.
The spread of the Coronavirus (COVID-19) is sending shock waves across the globe as we all try to adapt to a new reality. And with these challenging times, businesses are scrambling to figure out what the future means. One essential item is what will 2020 look like for mobile apps, and what will be the impact of the pandemic on their marketing budgets? With so many unknown factors arising from this unprecedented global event, it’s too soon to answer this accurately. However, when it comes to mobile app usage, there are clear signs of increasing audience activity due to quarantine. Although this is a positive for some businesses, things aren’t that simple.
The Coronavirus (COVID-19) created huge impacts from people’s daily lives to the modern day workplace. On March 16, 2020, FunCorp switched to remote work. We decided to take this step, weigh the risks and what difficulties we faced in the first week.
The Coronavirus (COVID-19) has significantly changed life as we know it. Globally, we have seen it change in how we interact with others. Almost overnight, schools were closed, companies told employees to work remotely and people are being told not to go outside.