Artificial Intelligence (AI) needs just one thing to thrive—data. But raw data is not on its own enough to allow machines to be intelligent. Data needs to be registered, labelled and contextualized for AI models to understand and predict. This is the way the data is given meaning or labeled in the system. It is... Continue Reading
Most of the strategic moves today revolve around data, whether it is marketing, operations, finance, customer experience, or anything else. Before the processing future, companies must understand what has already happened—what we call descriptive analytics. The term often refers to a form of raw data processing that converts it into simplified results and allows decision-makers... Continue Reading
The perception of autonomous cars is achieved by using a combination of highly sophisticated sensors and machine learning algorithms. LiDAR (light detection and ranging) is one of the sensors, playing a major role in helping normal vehicles to detect objects, measure distance, and get them across safely. But LiDAR’s real no-fluff power exists in its... Continue Reading
Electric vehicles (EVs) are not a far-off vision of the future; they’re going mainstream around the world at an unprecedented pace. AI and data annotation are driving auto manufacturing and the electrification boom. As car manufacturers and tech giants continue to push the boundaries of sustainable mobility, AI and data annotation are proving to be... Continue Reading
The race of autonomous vehicles (AV) has remade the face of the global automotive industry. Market studies foresee that the self-driving market will be valued at a few hundred billion dollars by 2030, and as such major contributors like Tesla, Waymo, and Nvidia are putting heavy capital into both Advanced Driver-Assistance Systems (ADAS) and full... Continue Reading