I’m Aldy Syahdeini. I’m Artificial Intelligence (AI) engineer for BukaLapak I have just started work here 3 months ago, but then asked to speak here, so let’s see I’m just going to share my experience these past three months work at Bukalapak As our theme ‘Kickstart You Carrier’, I’d like to share some pointer for you who’d like to start a carrier in Data Field You see AI is quite a hype nowadays We see it on news and papers, all about AI I hope with this hype, we can be one of the leaders in AI field So, what is AI engineer? First, one thing need to be clarified Why Bukalapak use the term AI Engineer While others use machinery engineer or data scientist I thought ìisnít it too sophisticated to use the term AI engineer? Then it come to me, well itís just a name and name is like a hope or an aspiration Us, by using that term AI engineer; we are going to go there by what weíre doing now So, it’s just a name. it doesn’t really matter Then, what exactly are we doing as AI engineer? Here in Bukalapak, me and the team We basically make a model, or an algorithm based on our data Models that hopefully can help processing in Bukalapak Processes such as Business process, marketing process, logistic process and others Using statistical and deep learning approach Hereís a little story of AI at Bukalapak Recently, September 2017 We are emerging from 1 division called core-Data Started from data engineer, we’re doing bunch of stuffs Then on November 2017 Ohh.. before we have AI guild Bukalapak have guilds for people who wants to learn of something, we can study together there But in November 2017, we start of BLAIR In short for Bukalapak AI Research At first, we start as sharing community Sharing some papers & information about cutting edge technologies in AI Engineering
Then in 2018 we started doing collaboration with universities in Indonesia By collaboration, we mean that we gave data to students whose working on their final assignment We also in touch with the lecturer (from the universities) In case we are facing some problems (with the data) Next step, we going to need personal in Autonomous and Reinforcement Learning And our hope from BLAIR is to publish a paper in the future Are you following so far? Do you get confused with AI, data scientist, data engineer? What’s the difference? Well, in my opinion, as the one who work at Bukalapak AI engineer is the intersect between data engineer and data scientist So, we need to be good in software engineering skill Knowledge in distributed system And ?? learning in data scientist Here at Bukalapak, data scientist focusses on driving business decisions Give some insights, or data analyzing if a problem occur While AI are more into developing intelligence system And data engineers are into building installable infrastructure While AI working as a team, data scientists inserting themselves into other team or subdivision AI also do the research in machine learning, deep learning and personal learning Data scientist also works on machine learning, but the loads of works done more by AI Here I try to put into graphics myself.
Hope you can understand As you can see, data scientist got request from stake holder Then data scientist looks for some insight from data or model then report back to stake older AI also got request from stake holders, plural not singular And we also do a meeting to see if there any problems we can solve (at Bukalapak) Because sometimes the stake holder doesnít have the idea that certain problems can be solved by AI So the AI team need to be more proactive in problem solving As you can see, thereís a different in technologies (between AI and data scientist) Well, the diagram actually incomplete Because I made it based only on my knowledge about data scientist Then we also have different results. AI give a micro service as the result of the problem solving Which then use by the stake holders It also applicable to other stake holders with some editing, adding features resulting in new version of the micro service Then data scientist results usually more into data transformation (in solving a problem) We often asked data scientist first whether they already got a data (on the problem) Here is my own personal experience I was a back-end engineer at Bukalapak I worked as back-end engineer for six moths Then I stop (working) to get my masterís degree And back to Bukalapak on November as AI engineer Then there’s a question of what the different of back-end engineer and AI engineer So I’ll share a little with you, based on my experience Back-end engineers are mostly making good logics/semantics to be used by other engineers A system reviews While AI engineers, we are more into looking for a right algorithm or model for the problem or data AI engineers (work) more in mathematics algorithm Also add in knowledge in distributed programming AI engineers can also utilize published paper, in searching usable approach of solving (similar) problem The time frame also different Back-end engineers usually using scrum, itís about two weeks AI engineers also using scrum, but weíre not expected to published result after two weeks We have more time, it can get to a month or event three months. Now, what skills needed to be an AI engineer? First, a strong coding skill Because weíre making a micro service At least, you experienced in making API (Application Program Interface), then you can advance into AI engineering Familiar with algebra and probability, good statistic Itís the prerequisite for machine learning and deep learning courses If you join the online course, you see there’re frequency sheets Here’s example repository, you can see, there information of what needed for joining certain course Here’s also information of where to join the course, so can just use the information We also need academic reading (skills), you need to able to read a paper And you also need to be experienced in the project itself Now, among all the applicants of engineer position, what make you stand out? In my experience, you need to have knowledge and experience in deep learning Here’s a little problem For fresh graduate applying for deep learning project But the at the interview, they don’t quite understand About the architecture, data transformation, they just follow the tutorial Then say: Ok I know this But when facing an over-fitting model, they don’t what to do with it Or what to do with vanishing gradient We don’t want that, don’t be that person You need to explore by yourself, not just following the tutorial For distributed computing, we use (Apache) Sparks at Bukalapak Well at least, you have experience in distributed computing It’ll be even better, if you had done assignment on deep learning So, it’s clear that you’re experience on the subject More so if you have published a paper (on the subject), you’ll get in right away. Then, how do I get to learn those knowledges? So, there are two methods, online course and higher education Online course, for me it’s the future of learning method It’s what everybody need to be doing (of learning stuffs) Because you don’t need anything (much), you can just sit in front of your laptop then learn the study by yourself My suggestion, you take the Andrew Ng: Machine Learning and Geoffrey Hinton: Deep learning; it’s quite good Coursera and udacity, youíve already know all that But itís quite challenging, this online course. Why? But itís quite challenging, this online course. Why? If you among the people who finished the course, thatís great. I read somewhere thereíre only 4% of people who joined the course who actually finished it. You can also join Data Camp In fact, one of the start-up company in Indonesia They take their data scientists from Data Camp Data Camp only take one to two weeks, so itís very good So, after learning from these online courses, what’s next? You look for a mentor, a person that have good understanding of the field For you to ask whatís next to learn or give you some exercise in problem solving You can also check on medium (medium.com) of the good courses you can take, you can just follow it. About, higher education. Because I also take higher education, my opinion would be bias. The necessity of it, is the frequently asked question among the under graduates. In my opinion, higher education give us the environment of people who focus on the field You’d be given one to two years to focus on learning the field While if you doing online course, you can be distracted by anything. For undergrads, I’m suggesting to take internship So, the higher education environment will give you more focus in developing your interest Other method, you can learn directly from the researcher, which is very good actually Because they have the full understanding of the actual problems Then you can learn about the research methodologists which is also needed in AI Engineer fields Also, my suggestion, when doing online course, donít just watched Youíll get confused dealing with problems if you just watched If you join github, they usually included jupyter notebook within their repository You can just do the notebook or re-watch the video when you get confused Then usually, a homepage works from the online courses You do the home-works, all of it, then again you can always re-watch the video when you get confused It will give you real experience on the actual work In Bukalapak, we have Machine Learning and AI Engineering internship if you interested
How to update your knowledge? For me, the answer is Twitter I just followed some great accounts Or maybe Instagram, but I prefer Twitter Just, checkout the Twitter account on your spare time, because they usually very updated While itís not usual, unless you already know what youíre looking for, you can open Arxiv You can also subscribe on newsletter (i.e deep learning weekly) So, you can get information about new published papers, methodology, and other stuffs weekly For me, the best AI team is the one that come from various backgrounds Because AI field is very broad Don’t be discouraged if you come from other backgrounds, AI actually needed it We canít be just from CS background with CS point of view, itís not really good Here are the team in Bukalapak We have NLP, Vision, Recommendation, engineering (optimization) We’ll also need Autonomous System in the future Now, let’s get back on our objectives, the three steps So here they are You now know what AI Engineer do and the difference with other careers in data field You know the skillset needed in AI Engineer How to get it and update the knowledges How to get it and update the knowledges Or join the internship with Bukalapak I guess thatís all. Thank you.