After 6 months of intensive courses and projects, I finally completed Udacity’s Artificial Intelligence Nanodegree!
My internship at Tapad has officially come to an end last week, after I gave a final presentation of my project (see the intro video below). It’s been a very memorable and rewarding summer. I not only learned about the latest technological development and application of machine learning and big data, but also got to experience the industrial work style and start-up culture.
During my final round interview at Tapad, the VP of Data Science noticed my academic background in neuroscience, and we started to discuss how neuroscience research could contribute to online advertising. Later in the interview, he asked “Have you heard of reinforcement learning (RL)?” And I said no. He explained this reward-guided learning paradigm, which immediately reminded me of my undergraduate research on aversive learning in fruit flies. After the interview, he emailed me the link to RL Courses on YouTube taught by David Silver, the leading scientist of AlphaGo.
After investigating a sample dataset using Python for a month on a local computer, I discovered some interesting patterns and optimized my algorithms to achieve a high measure of goodness. This week, I finally got the opportunity to run my algorithms on a much larger dataset – too large to be stored or processed on a single computer. Finally, it is time to Spark!
In my very first meeting with my mentor at Tapad, after an introduction to DeviceGraph and AdTech 101, we started to discuss the project I would be working on during my internship. The first week was very intense and my mentor understood my struggle in the face of information overload. He showed me his system of organizing information by writing down his incremental knowledge about certain technology as well as his spark of ideas. I adapted his system and developed my own archive to track my learning process and ideas using Google Docs (the picture above). Now, 5 weeks have passed and I have continuously updated the documents as I learn: the more I know, the more I realize I do not know, and the more I want to learn. Learning is an iterative process.
Halfway mark of my summer internship at Tapad! The past 4 weeks have been very exciting and fulfilling. Learning from experienced colleagues and marketing gurus is not only educational from a technical perspective, but also quite inspiring for my personal development. This Friday, we had a team-building improv workshop (I truly recommend everyone and every team to check it out. Really mind blowing!). I was impressed by the “Yes, and…” teamworking spirit and the power of encouragement.
“The winning team found a problem that most of us encountered, proposed a good solution, and developed a working prototype. Also, they had very strong branding!” As the SVP of product made the announcement, the one-week intern hackathon came to an end. Although the product my team developed did not win the final competition, I really enjoyed collaborating with full time employees on my team, brainstorming, and building a product from scratch to solve a real business problem. More importantly, I realize the importance of branding.
This week, Neuron published a review titled Neuroscience-Inspired Artificial Intelligence, authored by Demis Hassabis (the cofounder of DeepMind and creator of AlphaGo) , Dharshan Kumaran (computational neuroscientist) , Christopher Summerfield (cognitive neuroscientist), and Matthew Botvinick (experimental psychologist). The authors called for a wide collaboration and communication between neuroscience community and computer science/engineering, illustrated how AI algorithms nowadays were inspired and validated by neuroscience, and envisioned a future where integrated AI and neuroscience research might yield insights into human cognition and smarter machines. When I was reading this review, I felt a deep excitement: I am so fortunate to witness the interaction of these two fields, not only as an audience, but also as a practitioner.