Companies ranging from high tech startups to global multinationals see artificial intelligence as a key competitive advantage in an increasingly competitive and technical market. But, the AI industry moves so quickly that it's often hard to follow the latest research breakthroughs and achievements, and even harder to apply scientific results to achieve business outcomes. To help you develop a robust AI strategy for your business in 2020, I've summarized the latest trends across different research areas, including natural language processing, conversational AI, computer vision, and reinforcement learning. I've also included external education you can follow to further your expertise. In 2018, pre-trained language models pushed the limits of natural language understanding and generation. These also dominated NLP progress last year.

First, let's look at what these fancy technology terms actually mean. According to Arthur Samuel, a machine learning pioneer, Machine Learning is a field of study that gives computers the ability to learn without being explicitly programmed. AI, on the other hand, is not just one technology, it is a broad field constituting many disciplines from robotics to machine learning. The ultimate goal of AI, most of us affirm, is to build machines capable of performing tasks and cognitive functions that are otherwise only within the scope of human intelligence. In order to get there, machines must be able to learn these capabilities automatically instead of having each of them explicitly programmed end-to-end.