The development of computer vision based machine learning technology is defined by changes in data needs, company structure, and workforce size. Machine learning companies of all sizes are heavily reliant on access to annotated training data of sufficient quality, at the scales that their projects require.
For startups, this could mean needing quick, affordable access to smaller quantities of training data. When companies are growing, data quantity needs to be scaled up in line with developing models. And, for larger companies data supply needs to be sustained, responsive, and secure. Flexibility is a key factor for annotated training data provision, for companies of all sizes.
Outsourcing data annotation needs to professional service providers, like Keymakr, is a way in which many companies can ensure flexible and responsive training data services. Experienced annotation companies can ensure flexibility for clients by leveraging the following core strengths.
Adaptable annotation tools
One area in which outsourcing can help organisations of any size is allowing them to gain access to proprietary annotation platforms and tools. Annotation tools primarily aid AI development flexibility by streamlining management systems and communication. Specific labeling tasks can be uploaded onto these tools when need arises.
This task can then be managed, with work being assigned to annotators based on skill levels or familiarity with the project. Companies can also assess the progress of annotation work via these workflow focused platforms. This facilitates project management and planning processes, and creates flexibility as data needs change.
Smart annotation platforms also improve communication and collaboration between AI innovators and annotation services. Tasks can quickly be added to the tool, or scaled back, as proves necessary.
Flexible annotation workforces
Services, like Keymakr, offer a clear advantage in terms of workforce capability and flexibility. Managed teams of skilled annotators are accustomed to the demands of large annotation projects and are familiar with a wide range of tools and labeling techniques.
Working with professional annotators, led by experienced managers, will invariably result in higher quality annotations, that support the development of computer vision models. Additionally having experienced teams of annotators on a project increases the degree of flexibility and adaptability available to clients.
Capable annotators are much more able to cope with increased workload demands, or switch to different kinds of annotation with different data, if that is what the project demands. Managers are also key to a flexible workforce. Proper oversight of annotation teams means that changes in a task can be communicated quickly, and understood right away.
Responsive quality control processes
Quality is of paramount importance to machine learning projects regardless of how much training data is needed at specific times. Flexible annotation services also need to ensure that mistakes and errors in labeling do not make their way into important datasets. Outsourcing allows ML companies to take advantage of established quality processes.
For Keymakr this means three layers of human quality verification, and then a fourth check carried out by algorithm. Annotation services can also distribute work efficiently so that annotators and verifiers are linked. This allows for seamless verification processes, occurring alongside the bulk of annotation work.
Collaboration delivers flexibility for developers
As computer vision projects grow and change, so does the volume and type of training data that they require. Keymakr’s in-house teams of professional annotors work with proprietary annotation tools to ensure that the provision of quality data is responsive to your changing demands.
Contact a team member to book your personalized demo today.