I spent $1,000,000 to make my machine translator. Thoughts and Results

Introduction

I have been working on machine translation since 2012, and this business was not chosen by chance. Many years ago I noticed the big impact of localisation on revenue. In our case, support for only 15 languages instead of one helped us to increase the number of mobile app downloads to 35 million without advertising costs. It was the most effective money and time investment. And this was the main reason why I chose this business.

When I published my first story about the project, several hundred people wrote to me. I tried to answer everyone. Basically, there were questions about how to make money on mobile applications, how to start business, etc. A year later, several people said that their lives had changed a lot for the better. So, the advices helped.

The most important advice will be the next:

Before starting your own big business, try to find a company or people who can help you to get experience in the field you are interested in. Try to agree for smaller salary or even work for free. The main point is to get the experience you need — quickly. You need to face with real business problems, people and tasks. You can’t learn business using books and courses. Ideally, to get experience in several areas at once (development, marketing, management). Small startup companies of 10–15 people are suitable for this.

It is not easy to find a successful company where you will have the opportunity to work closely with an experienced manager, to watch on how to make decisions. Most likely, you will need to change several companies and spend a couple of years. The main idea is to quit your job quickly once you see no perspective there.

Learn from the mistakes of others. It takes a very long time to learn from your own. Therefore, choose your place of work very carefully.

The most important conclusion I have realized in 15 years of business — people is a key. Not an idea, not a market, not a technology, but a team. It doesn’t matter what is the competition on market. A good team will make a project of any complexity. Even if there are some mistakes at the beginning it will be always success at the end.

As a founder of the company you should be public and social. It’s necessary to write posts about your project everywhere, take part in events, make interviews. Try to avoid outsourcing of development to freelancers, and focus to gather your own team of professionals. To recruit such people, a personal example is very important. Experienced people want to work with the same as they are.

Posts about your project will help to find good teammates. You can’t find them using vacancies and recruiters. Well-established processes in management and a team of even 10 experts can do wonders.

The beginning of 2020.

At the beginning of 2020, we have made a great progress in the quality of translation.

Previously, to correct translation errors, the “Suggest correct translation” feature was added to our applications. A year later, we turned it off due to the fact that people started spamming and offering complete nonsense for correction. After analyzing thousands of records, I saw that few things turned out to be useful. A translation cache was also made. It works well on 1 and 2 word phrases and allows you to save about 30% of all requests.

We rented 20 dedicated servers with one GTX 1080 graphics card in each.

With the increase in dataset volume, we increased the number of layers, RNN and other parameters of the neural network. It was necessary to achieve a certain level of the quality of translation, to make users not go to competitors.

And then there was one problem. According to our calculations, with the current neural network parameters, it will take 28 years to train 200 language pairs. Even considering all the servers we had, it take so long. Nvidia GTX 1080 graphics cards were very slow for our tasks, and we haven’t enough money to rent expensive V100.

During the year, we participated in various startup competitions with the hope of winning free credits from sponsors. And one day it happend. A couple of months later, we won the AWS Startup Challenge and received 100,000 free credits that could be spent on training models. Instead of servers with 1 x GTX 1080, we began to take 8 x Nvidia V100, From the 28 years, the training time was reduced to 2 months, during which we overtrained our models with the best quality.

At the same time, I watched what our competitors were doing and analyzed the market. More and more projects in the field of machine translation began to appear, such as real-time translation of conferences, translation of video clips and podcasts. Companies that have been specializing in human translation for a long time have begun to invest in machine translation . The basis was the business impact of localization.

The improvement in quality of machine translation has made it possible to reduce the cost of human translation many times, because in localisation the main expense is the salary of people who speak foreign languages. The better the computer translates, the less time a person needs to correct mistakes behind it. The development of technology has already made it possible in some cases to completely replace human translation with machine translation.

On September 1, 2020, the world’s leading scientific journal “Nature” published a report that machine translation has already reached human quality in English-Czech news.

Despite the huge demand for translations, the use of human translation for this task is still expensive and takes a lot of time. The translation of one word by a human costs in average of 5–8 cents. In case of cheaper price of human translation, the more companies are willing to invest in localization. Using more and more high-quality machine translation and CAT tools, the price of word translation is decreasing every year, and the speed of delivery of localised solutions is growing. In future it will lead to an explosive growth of the translation market. In the picture below, I showed this idea.

Pivot to B2B market

Every year more than 1 billion people search the Internet for solutions related to translations. The amount of data in different languages is increasing every day, and the share of English as the Internet language has decreased to 25%.

Until 2020, our focus was on mobile translation applications. Recently, the Appstore Search Optimization (SEO) for mobile applications (which helped us to get 40 million downloads and earn the first million $) changed it’s algorithm. The keywords in the Apple App store without purchasing paid installations has become ineffective. The user acquisition with paid traffic has become very expensive.

At the end of 2020, we decided to try the B2B market. We think that any international business needs a translation feature. This can be the translation of documents, a website, multilingual customer support, competitor analysis, and more.

In five years I got thousands of questions “Why Lingvanex is better than Google”. I tried to give different answers, but now I try to answer briefly — data privacy, functionality, price, quality of support service.

If you are a student or a tourist and you need to translate a small post for personal goals, then you can use free services like Google or Microsoft. But if you are a company, then it may not be safe to translate customer emails, invoices, certificates and other internal documents via free online services, because such companies collect your data in order to sell them to advertisers. Also to translate large volumes of text using Google API will be very expensive.

For such cases, we have made it possible to install translator on a corporate network and translate text and files offline. Moreover, everything happens very quickly and with the preservation of formatting. We have all languages that Google has.

The first product we made for B2B market was on-premise translation server. It allows you to translate text, HTML (websites), files into 120 languages with no limits. We have spent enough time to make translations ultra-fast. Now 1 billion characters of text can be translated in 1 day on one Nvidia GTX 1080 video card. Also, unlike the Cloud API (Google, Microsoft, etc.), all your data remains with you, because everything works without the Internet.

It was privacy that became the basis for our first B2B integration with the Vivaldi browser.

The translation server needs Ubuntu OS and comes as a docker image. After the launch, the REST API becomes available, which can be integrated into your project.

The function of translating web pages has been added not only to the desktop, but also to the mobile version of the browser.

Once we finished with Vivaldi browser, we integrated server into the medical library. The client wanted to save costs on HDD and not to store the translated pages in the database. Therefore, translations of web pages occur dynamically as the user surf around the website.

I thought about using the server to create localized versions of websites like Stackoverflow, Quora and then to make money from advertising. Because I see lot’s of websites made this way at Google Search. But didn’t realized this idea yet.

The third project of server integration was a large e-commerce website in the Asian region. Automatic translation of product descriptions into 87 languages was required. Then we sold the server to a lead generation agency, business analytics company, a plugin for translating websites, an electronics plant and others. In general, the server will be useful wherever there is a lot of content and an international audience.

Gradually, our focus shifted to business solutions instead of mobile applications.

For several years, we have often been asked about the feature of speech transcription (converting voice into text). Therefore, speech recognition in 20 languages has been added to the translation server. Thus, the server can translate text, files, HTML and do voice transcription into text.

Now the translation server is our flagship product. A lot of time and effort has been invested in it. The price of the server begins from 2000 euros per year (depending on the number of languages and functions). It’s less than 200 euro / month. A free demo version of the server is available for 1 week.

More information ABOUT TRANSLATION SERVER HERE

Recently we made translation SDK for iOS, Android, Windows and Mac OS. This allows you to connect the offline translation features to any mobile and desktop applications as a static library. To do this, we made separate compact models of languages (up to 100 MB). The same 120 languages are available. It is suitable for private messengers, browsers, legal and medical and other programs where data protection is required.

Also we began to offer Cloud API for translation. The cost starts from $3 per million characters, with the same number of languages and comparable quality as Google. The price depends on the volume. By default, the price is $5 per million characters, which is 4 times cheaper than Google. We can give up to 20 million characters to test for free.

Previously, our desktop applications for Windows and Mac can translate files only online, now we have separate installers that work completely without the Internet.

Finally

There are 18 people in our team, and I am pleased that despite all the difficulties, we have found an effective business model, which we are focusing now.

The rule of 10 000 hours always works. If you are engaged in any activity for a long time, you become a professional and then you begin to succeed. The main thing is to remember about this and not to give up in advance. And it’s better to get a job in a company with a similar project before and just adopt a positive experience. It’s much faster to succeed that way.

More about our projects HERE

Write me to info@lingvanex.com