In my main position, as a data scientist at SIL International, I work on expanding language possibilities with AI. Practically this includes applying recent advances in Natural Language Processing (NLP) to low resource and multilingual contexts. We work on things like spoken language identification, multilingual dialogue systems, machine translation, and translation quality estimation.
Advances in the performance and capability of Artificial Intelligence (AI) algorithms has led to a significant increase in adoption in recent years. In a February 2021 report by IDC, they estimate that world-wide revenues from AI will grow by 16.4% in 2021 to USD $327 billion. Furthermore, AI adoption is becoming increasingly widespread and not just concentrated within a small number of organisations.
As data continues to grow at an exponential rate, our customers are increasingly looking to advance and scale operations through digital transformation and the cloud. These modern digital businesses are also dealing with unprecedented rates of data volume, which is exploding from terabytes to petabytes and even exabytes which could prove difficult to manage.
The phenomenon of web-based, at-your-door-in-minutes, restaurant food-delivery service is widespread and commonplace nowadays, with various apps and platforms, such as Grubhub or DoorDash, providing diners with an at-home eating experience – look up a restaurant, choose what you want to eat, and your food is on its way. The same can be said about grocery shopping.
