The technology market share is just increasing like an oil spill in the ocean and becoming more and more complex and overwhelming to cope with. To help you learn and understand the ever-changing landscape of technology, we are extending a list of 30 Top LinkedIn Voice in Technology. Allie is the Global Head of Machine Learning Business Development, Startups, and Venture Capital at Amazon Web Service (AWS). Her area of expertise includes AI, Machine Learning, Crypto, Web3 & NFTs. Emmanuel is an undergraduate student of Chemical Engineering, named as the Young Influencer of the year by TIBA.

Huyen, aka Huyen Chip, ranked fifth in the annual Top Voices list released this week by the U.S. professional networking site. It compiles the list by examining all sharing activity on its platform from October 1, 2019 through September 30, 2020, and using a combination of quantitative and qualitative signals including engagement (comments, reactions and shares), follower growth and posting cadence. It said: "Having worked at prominent tech companies including Netflix and NVIDIA, Huyen joined the AI startup Snorkel last December. A Stanford graduate, Huyen turned to LinkedIn to find reviewers for the course she'll start teaching there in January next year, Machine Learning Systems Design." Before coming to the U.S., Chip helped launch Vietnam's second most popular web browser, Coc Coc.

The line between the two terms AI and ML is blurring and they are used interchangeably today. It's hard for one to exist without the other in some cases, though the technical definition of the two is different. Machine Learning is more specific in nature and is a branch or subset of AI. Machine Learning is based on the idea that we can build machines to process data and learn on their own, without our constant supervision. On the other hand, professor John McCarthy defines Artificial Intelligence as the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.