I had the opportunity to do a live fireside chat with Lee Byron to chat about React Native and GraphQL. I outlined the boring future of React Native 😉
It was pretty surreal as I got to have makeup done by a professional!
I also tested the live video feature of Facebook on the open source booth at f8. I showcased React Native running on Xbox, Windows Phone and Desktop and the F8 app being open sourced.
The first non-trivial feature I’ve done at Facebook is now released 🙂
If you have ever tagged an album, you must know the pain it is to go over all the photos and tag everyone. In order to make this process easier, we can make use of image recognition algorithms to find faces.
When you click enter tagging mode in the photo viewer, all the detected faces are now being displayed. The first face on the left is automatically selected and you are prompted to enter the name of the person. When you press enter, it automatically goes to the next.
In the ideal case, you can just write the first name, press enter, write the second and so on. Then you press the right arrow key to go to the next photo. You don’t have to use your mouse anymore!
This project, strangely, was easy to implement. The difficult part was designing the feature to be user friendly.
First of all, image recognition algorithms can be frightening. The comparison to 1984 is easy to be made. This is a tough issue to deal with and we’ve tried our best to use these algorithms in a way that is not creepy.
A typical algorithm has two distinct parts. Detection is the step to find the faces in the image. Recognition is trying to match the face with the person.
Here, we only use detection. We just show boxes where the algorithm thinks there are faces. We do not try to guess who the person is.
Detecting faces in a picture is an extremely hard problem to solve. The current algorithm works well but is not perfect, and sadly will never be.
The way to deal with it is to make the detected faces a suggestion. The user can at any moment ignore the suggestion and tag anywhere else in the picture. The idea is to make it faster to tag for the most common case, when the algorithm is right. When it is wrong, the user can use the old flow and tag whatever he wants.
From the three months I’ve been at Facebook, I’ve seen a strong emphasis to give people control and let them shares things by themselves. Machine learning is used extensively but never to automatically publish things in behalf of the user.
If the face is already tagged, we don’t want to prompt the user to tag the person again. This is tricky to know if a face has already been tagged.
In an ideal world, the tags would be placed centered in the face. However users don’t always do that. There are a lot of tags in people’s body, feet, hands … Also, since tags trigger a notification and often a mail to the tagged person, users use tags to send an image with someone. The person isn’t even in the photo so no heuristic will help in this case.
We only implement a simple heuristic: if the center of the tag is inside the detected face, we hide the tag. This is going to fail in all the mentioned edge cases but it is not a huge issue in practice. Since we are now going to automatically prompt the user to tag on faces, we are educating them to do so.
Also, most of the tags are done within 24 hours after the image has been uploaded. All the old images with weird cases won’t be seen often.
This project was really interesting as it did not only involve technical skills but also a lot of design. I’ve uploaded several albums since I implemented it and found that it made tagging the entire album more efficient and feel less boring.
This feature also increased the number of tags by few percent, which results in millions of additional tags! Working at Facebook scale is crazy 🙂
I am happy to tell you that I am now a Facebook employee!
Two years ago, like many of you, I applied to Google (thanks tsuna). Obviously I didn’t get in. I did not even made it to the second interview! After analysis, I screwed up everything!
Soon after the interview, I read the excellent book What Would Google Do?. It talks about business models from the new internet companies such as Google, Facebook, CraigsList, Wikipedia … There is one chapter about blogs that was a revelation.
When I applied to Google, the only thing they had on me was a resume with the name of various projects I’ve been working on. I find excessively hard to judge my skills based on my resume. This is where a blog comes in. A blog lets you show off your skills and interests without constraints from a resume.
Most of the articles fall into one of those three categories:
It gives me the opportunity to show what I am interested in and concrete examples of what I am capable of. If you scroll over the many pages of my blog, you will have a much better vision of who I am than a resume.
And one more thing: A blog also makes you visible! I have been contacted by a Facebook employee after he saw my post JSPP – Morph C++ into Javascript on Hacker News! (Yeah I know, that’s crazy!!!). Since I did not want to fail miserably again, I took some more serious preparation (thanks Xavier). Here is a summary of what made me ace the interviews.
I completely failed my Google interview because I had no idea how interviews work. As you can see, half of the interview is not about Computer Science! So you have to prepare for it as-well. Prepare a speech for 2 or 3 projects from your resume that makes you shine for the position you apply for. Make a list of 15-20 questions and you should be good to go.
Train on CS problems. More than half of the recruitment process is about your Computer Science skills. However the process is flawed: it is mostly focused on solving puzzles. You can be a wonderful programmer that excels at making easy-to-use APIs and wonderful self-documented code but that skills will not be tested.
In order to train, the book Cracking the Coding Interview has 150 questions. The quality of individual questions and answers is not top notch, but it will give you a good insight of what will be asked. If you are done with it, you can get more on CareerCup.com.
Your interviewer should want to have a beer with you. This is probably the most helpful advice I have taken from the really good book The Google Resume. Your interviewer is going to be your co-worker right after you get hired, as a consequence, during your interview process, act like if it was a friend instead of it being a faceless institution.All those adventures made me learn one thing. In order to get your dream job, you not only have to be a good programmer, you also have to learn how to sell yourself and have a good preparation for the extremely codified process that interviews are.
If you want to get a job at the Silicon Valley, I urge you to read the three books I referenced and start a blog right now. It is a long term investment that pays off!
This is what I sent to accept the job offer :p
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