Developing an AI-based application is big money at the moment. But that’s only if you train it properly. And that means starting with properly labeled data. But, when you have to mark an image pixel-by-pixel, the task becomes overwhelming pretty quickly.
Image annotation software helps, but can only get you so far. At some stage, you’ll have the tedious task of either applying or checking labels. You can deal with this more cost-effectively by partnering with image annotation companies.
But should you take this step? Are you working with a large dataset or complex information? If so, it’s a good move. In this post, we’ll examine the top reasons to invest in image annotation services.
High-Quality Data for Better AI Models
Working with professionals means that your annotations are high-quality and accurate. These firms employ trained annotators who understand how to label complex datasets. They also usually use multi-tier quality control processes.
The benefits of getting this right means that your model will perform better. You’ll also make fewer errors.
Scalability for Large Datasets
You may have to use thousands or hundreds of thousands of images to properly train your AI. Scaling up your in-house team takes time. Even if you can recruit the right professionals, the cost of doing so is high.
Image annotation services have spare capacity, making it easy to upscale. Their teams also have the resources necessary to process massive datasets quickly, such as:
- A wide pool of trained annotators
- Advanced tools
- Streamlined workflows
You can leave your team to focus on core activities.
Access to Advanced Tools and Technology
You can annotate data in many ways. You can use semantic segmentation or bounding boxes, for example. When you need to use these specialized techniques, you need the right tools. These can be expensive to invest in, especially if it’s just for one project.
Cost-Effectiveness
Outsourcing is a time-honored way to save money. Building an annotation team from scratch is difficult and can be expensive. Your team needs specialist skills, so the costs can outweigh the benefits.
Hiring an outside team means only paying for what you need. You don’t have to build in redundancies for sick or annual leave, for example. You also don’t have to train the team.
Expertise in Domain-Specific Annotations
Some industries, such as healthcare and agriculture, need specialized annotations. For example, if you’re developing an app to read X-rays, your annotators must be able to identify common issues like tumors. An agricultural app needs people who can recognize crops from satellite imagery.
Working with a company means gaining access to skilled annotators. They can then, quite easily, upskill them to meet your specific needs.
Faster Turnaround Times
If you’ve got a great idea for an AI-based application, you can bet someone else is thinking up something similar. The accolades usually go to the team who gets to market first.
Annotation services can draw on a pool of annotators, meaning they can upscale their teams easily. In addition to their large teams, they also have streamlined workflows and software.
Focus on Core Competencies
Are you trying your best to label the data? Maybe you’re running on a shoestring budget, so you and your developers are working on the project. It’s a noble idea, but it means that the job drags on. It also means that you can’t spend time on core activities like:
- Product development
- Marketing
- Research
An ancillary benefit is that your team feels more satisfied. They get to leave behind the boring processes and concentrate on work that’s more fulfilling. You can spend more time winning over your customers and investors.
Ensuring Data Security and Compliance
A lot of datasets contain sensitive information like names and addresses. If you’re not careful, this data can leak out in the application. Which means you need to anonymize the information before you train your AI.
This extra step means things take longer. Working with a professional team can reduce potential compliance risks, especially if they understand data privacy regulations. They can also anonymize the data to make things easier for you.
Consistent and Reliable Results
Why not just hire freelancers to augment your team? There are, after all, millions of people offering these services. It might look like a good idea, it’s problematic. If you’re working with a diverse team of annotators, it’s harder to get consistent results. For example, one person might label a picture “cat” while another “kitty.”
An annotation service works with a set team of professionals. You simply need to set your expectations clearly. They’ll then run tests like inter-annotator agreement checks and multi-layer reviews.
Gaining a Diverse Team
Are you working with clients outside your general geographic area? If you have a multicultural target audience, you need to consider how they see things. What one annotator considers modest dressing, for which example, might differ according to culture.
Working with a professional team means gaining access to diverse annotators. It’s especially helpful if you can work with a company based in the same country as your target audience.
Future-Proofing AI Initiatives
AI projects will evolve over time, which means you need to update the annotations periodically. If you work with the right company over the long term, this becomes simple.
They might even build regular reviews into a contract, automating this tedious task. You’ll then be able to work with the same team who helped you to succeed in the first place.
Professional teams will often be able to see where your needs might change. They can give you valuable insights to future-proof your application.
Conclusion
Investing in image annotation services is money well spent. You benefit by getting the expertise you need in a cost-effective manner. You’ll also get high-quality results while saving time and money.
This lets your team focus on other core competencies. You head out and get the world excited about your new application.
