Crowdsourcing offers many benefits, and this is something that we repeatedly demonstrate in this blog. Indeed, over recent years, the training of artificial intelligence has become a service that is requested ever more. The reason: Artificial intelligence must first have knowledge taught to it. It requires systematic training before it can master tasks independently. Here we pursue a unique path, because we combine artificial intelligence with human intelligence. Our crowd is therefore the key: It generates, monitors and interprets training data that serves as input for the machines.
Let’s take as an example lane-keeping assistants in vehicles: Should you leave a traffic lane, the system warns you by means of a sound or vibration. If no reaction follows, the system automatically countersteers to keep the vehicle in lane. Such systems are trained by, among other things, data generated through crowdsourcing. Photos and videos of various different driving situations serve as the input. The crowd labels these images to indicate road markings and embankments, but also hazards such as building sites or sections without road markings. The system must also be able to work perfectly in rain, snow or when the sun is low in the sky. So it’s a question of quantity as well as quality: A vast amount of perfect input data is required. Only then, and after the software has been optimised, is the vehicle able to assess situations independently and take the appropriate action. Without the crowd, the development of such a system would take longer and be more expensive, and would be bound up with huge personnel costs.
That which initially sounds long-drawn out and protracted is in practice ideal for training machine-based systems. Crowdsourcing, that is to say, outsourcing tasks to a crowd of internet users, delivers high volumes of training data in just a short time. Regardless whether data should be newly created, revised, adapted or checked: Crowdsourcing is the smartest solution. Consider this: Anyone who cuts corners with the data basis will later encounter (expensive) problems as a result of incorrect algorithms, unsatisfied clients and automated systems that do not generate any real added value.
Although you can indeed find training data kits online – sometimes freely available – these are however often unstructured and limited in scope. These may well be suitable for initial tests, but they won’t deliver satisfactory results. But even more importantly: This training data is not tailored to your specific requirements. You would be better advised to use unique data instead: It will spare you annoyance and save costs. Fundamentally, only two options really make sense: Either the data has already been custom generated but still needs to be checked and structured, or: completely new data must be generated according to your own particular criteria. We are your ideal partner for both. For example, in the recent past we have been able to train algorithms that enable autonomous driving and generate input for chatbots.
It should be clear that artificial intelligence can only really be trained using training data tailored to your precise requirements. A prerequisite is that the crowd must know precisely what it must do. Therefore, in partnership with you, we create a briefing. Our experience in the areas of machine learning and artificial intelligence is a real advantage here, meaning that the actual training of the algorithms can start within just a short time. A personal project manager assists you, providing individual support and answering your questions. And upon request, the results can be supplied directly into your system via the API interface.
4. Crowdsourcing: High quality and many benefits
Crowdsourcing can speed up machines’ learning processes, as well as achieve this more efficiently and economically. Because the quality of the data is the most important consideration, this must be the focus of quality management systems. In our company, this occurs on the basis of quality levels that build upon one another: Every guru undergoes training and is verified on the basis of test runs. His or her work is pretested by technical validators before undergoing a final inspection by quality management. This is how we combine human and technical intelligence to create outstanding training data.
Of course, being able to receive lots of training data within a short time is a great advantage. But crowdsourcing also offers additional benefits beyond this, and which are simply not achievable with an in-house solution:
- A quick, economical method of generating or checking masses of data
- 365-day availability
- Custom training data, tailored precisely to your intended purpose
- Personal contact person
- Experienced service provider with years of experience in the market
- Quality control (selection, training, QM)
- Supplied in desired format; API for direct feed-in
Algorithms, artificial intelligence, training data, machine learning – The names are varied, but the underlying challenge is often identical: Automatic systems need to be provided with input – Masses of data require structure. This can only be accomplished in-house with high staff costs and other expenditure. Handing over these tasks to a crowdsourcing service provider makes much more sense: The costs are transparent and scalable, and the processing speed is many times greater than that possible with an internal solution. Plus, the results are systems that are worthy of bearing the word ‘autonomous’ in their names.