Of all the alumni speakers so far, I think I related most with Tommy especially with the path he took during his time at William & Mary. He changed his majors a couple of times (because haven’t we all) and landed on studying economics and mathematics. He works for In-Q-Tel which is an independent nonprofit that helps start-up tech organizations grow and engage with partners like the government. He specifically focuses on the investment side, deciding potential machine learning/AI projects should receive investment and contracts. He is also in a main leadership position with Data Community DC which is a not for profit, volunteer run organization that works at connecting people and expanding individuals’ social networks through get-togethers like workshops or other casual social networking events. An aspect of his discussion that I found really interesting was when he was talking about trends in data science, and he just like during the two other alumni lunches, he talked about natural language processing. When talking about some of the limitations concerning NLP, he discussed the natural bias that comes with any language. Meaning no language is developed within a vacuum, there is a historical context and culture that each language was establish upon and has evolved, so even if the same word in the same language is used in two different sentences the implications and significance could vary. Then he did highlight how there have been recent developments where a single module can work across multiple different languages regardless of the shape of the language, making it possible for languages to be mapped on top of each other.