Michael Abramov

The potential of autonomous vehicles is huge. By supporting or replacing human drivers AI models can make roads safer and increase the efficiency of transport and delivery for us all. However, there still remain significant barriers to the widespread use of this technology. Autonomous vehicles will not be adopted until

Accessing precisely labeled training data at scale is a key challenge for computer vision based AI companies. The process of labeling images and video can be extremely time consuming and labour intensive. As a consequence commercial annotation tool providers, like Keylabs, are constantly seeking to speed up annotation tasks. However,

The construction sector is expected to grow by as much as 9% in 2021. This growth is due to the return of normal working practices and demand levels as the COVID-19 pandemic eases. However, forecasters expect strong growth in the industry through the beginning of this decade. Demand for housing,

Aerial technology systems are a vital, and sometimes controversial, part of modern society. Drones are used in every industry, from entertainment to the military. Similarly, satellite imagery plays an important role in many sectors. Aerially captured images and video give a different perspective that can show things that are not

The data annotation process is the engine of any computer vision based AI project. In order to create cutting edge machine learning models with world changing applications, innovators need access to precise training data at scale. In order to provide this level of labeled image and video data companies and

Computer vision AI systems have the capacity to reliably identify objects in digital images. AI developers are using this capability in a range of industries to improve efficiency, customer experience and safety. Object recognition may be of particular value in the retail sector. Retailers are beginning to introduce AI into