Accomplished ML professionals share their experiences | Hear engineers, entrepreneurs, and other seasoned members of the global AI community working in AI
Collection of 24 PostsGerry Fernando Patia leads AI infrastructure projects at Robinhood, an online platform for investors. Having emigrated from Indonesia and attended a lesser-known U.S. university, he didn’t find it easy to break into AI. He spoke…
My main responsibility at HTC is developing machine learning features for our virtual reality devices, such as eye tracking. My day-to-day work consists of researching the latest AI technologies and algorithms required to develop new functions and testing those functions on hardware. My team and I work collaboratively, brainstorming to come up with ideas and test them. In the early proposal stage, we put forward plans for target customer groups and adjust our model by considering product specifications.
In the mid-2000s, AI was still just a curiosity to the world at large. At Stanford University, however, one of the most popular classes on campus was Andrew Ng’s CS229 machine learning course. Enrollment was frequently too large to fit in the classroom, yet he wanted even more people to be able to master machine learning.
So, working with a few students, he created an online Machine Learning course that could be taken by anyone with an internet connection and a desire to learn. The rest is history. Coursera launched in 2012 with Machine Learning as its flagship title. It was also the platform’s most popular, with almost 5 million enrollments.
This year, to celebrate the course’s 10 year anniversary, DeepLearning.AI and Stanford Online released a successor — the Machine Learning Specialization. Andrew spoke with us about how the new Specialization improves on the original, who should take it, and how it fits into the modern AI builder’s career arc.
Kulsoom Abdullah pivoted from network security into a data science role after taking Andrew Ng’s original Introduction to Machine Learning course from Stanford in 2013. A self-described learning addict, she has taken more than 10 online courses, most recently the Deep Learning Specialization. Outside of work, she’s a fitness fanatic, and was the first competitive weightlifter to compete professionally for Pakistan — after winning a fight to change the dress code to allow religious head coverings. On top of all that, she’s a travel
Kai Saksela is the CEO of NL Acoustics, a Finnish technology startup that designs and manufactures AI products to analyze sounds. He took the Deep Learning Specialization primarily because he loves learning new skills and has been fascinated by the field for a long time. He also had a hunch that neural networks would help his company solve a core problem: providing customers guidance on what they should do when their equipment starts making strange noises. He spoke with us about how his hunch paid off and why AI plays a central role in his company’s growth.
Title: Senior Deep Learning Engineer, Nvidia Location: Santa Clara, California Education: Bachelor of Technology, Electronics and Communication Engineering, Manipal University; MS, Electrical and Computer Engineering, Carnegie Mellon University Favorite areas: Natural language processing, autoML, and interpretable AI Favorite researchers: Christopher…
Jade Abbott turned a childhood desire for a robotic best friend into a career training computers to understand human language. Having studied AI in school, she got her first job coding conventional software, but she found ways to apply machine learning to her work until that became central to her role. In the meantime, she founded an open source project to train NLP models on African languages. She spoke with us about her fascination with language, the importance of community, and how to incorporate wine into your learning practice.
Public service runs deep in Ronisha Carter’s family. Her mother was a Navy medical technician, and her father worked for the Air Force in information management. The two parents ignited a sense of curiosity and love of learning that led Ronisha and her siblings to explore technology. Her sister was the first in the family to earn a Bachelor’s degree, and her brothers became software developers. Ronisha joined the Air Force and went on to earn a Bachelor’s in computer science and a Master’s in computer engineering before carving a unique path for herself in AI.
As a child, Jasjeet Thind led the other kids at his daycare to engage in shenanigans. He still exercises his leadership skills, but instead he uses them to organize Zillow’s army of engineers as they aim to automate everything about real estate. Thind became fascinated with data as a college student at Cornell University in the 1990s, and his career exploded along with the deep learning revolution. Read more.
Growing up in Mauritania, Adama Diallo was fascinated by the human brain. Now, as an AI developer at the software company Paradigm, he’s using artificial intelligence to map architectural spaces. In this edition of our Working AI series, Adama discusses his projects, advice for learners, and views on social bias in the industry. Read more.
While much of the AI revolution has served consumers, AI has a lot to offer to other aspects of society. I work at Noble.AI mainly because it gives me the opportunity to stay close to science. At Noble.AI, we’re building software that speeds up the work of scientists, researchers, and engineers by 10 to 100 times.
Location: San Francisco, California Age: 33 Education: B.Sc. in Computer Science and Mathematics, 2009, University of Ljubljana, PhD in Computer Science, 2014, Cornell University Years in industry: 5 Favorite movie: Event Horizon (1997) Favorite machine learning researcher: Thorsten…
