Here’s how AI and ChatGPT will do more jobs for humans

AI and ML Jobs

There’s a dark air about AI these days, with many people who aren’t familiar with the details believing that AI will replace human jobs and tech professionals will lose their jobs. In practice, however, some people are reluctant to embrace AI, fearing that it will take away or destroy their jobs. Fortunately for all of us, the truth is that artificial intelligence will create so many jobs and pave the way for so many.

As long as the rise of artificial intelligence and AI tools such as ChatGPT threatens to loom, these tools could also create high-paying jobs. Reports show that with the rise of AI, the role of highly-paid and responsive engineers is emerging in every field.

The tech industry has always been known for creating high-paying jobs, usually for people coming from STEM backgrounds. However, the rise of various mods such as ChatGPT and GPT 4 has created a new field of swift engineers.

Bloomberg reports that the prompt engineer is a new role that has emerged thanks to the rise of AI tools. These jobs can pay as high as $335,000.

Here are the jobs that will be very in demand thanks to artificial intelligence:

data sourcing

Data sourcing involves collecting and classifying data from various internal and external sources. These data sources are the starting point for all the data you need. It can be a database, a file, or an API. Data sourcing gives you access to a myriad of data, which is like gold in today’s data-driven world.

Not all documents are the same. Even after successfully training an AI model with different datasets for AI automation, errors and questions may still arise when classifying certain documents. In these situations, data sourcing experts can provide feedback and help improve the performance of AI models.

data detective

If you enjoy CSI and Sherlock, a career as a data sleuth might just be what you’re looking for. You can start by providing a video annotation service that needs to label every object in each frame that a machine learning algorithm uses to recognize clues, evidence, and suspects.

You can then move on to more advanced positions that involve using AI to analyze data and use it to narrow down lists of suspects. The use of artificial intelligence in law enforcement is starting to become commonplace, creating many jobs for creative and forward-thinking individuals.

Data Annotation Specialist

Have you ever wondered why machine learning algorithms are getting smarter? The reason is that they are fed massive amounts of annotated data so that they can perceive everything around them. is.

This involves taking the raw data and annotating everything you want the machine to recognize. Whether you need video annotation or other forms of annotation, there is a growing need for people who can provide these forms of service.

One of the main reasons this job is so in demand is that it requires attention to detail, but it is also very time consuming. Developing machine learning algorithms takes a lot of time and effort, and companies don’t have time to annotate the huge amount of images and videos they need.

This is where data annotation specialists come in. They play an important role in the project. Because if they don’t label their data properly, the whole project will be delayed and have to start over. Mindy Support has the experience and expertise to handle even the largest data annotation projects. Everything can be annotated within the specified timeframe, regardless of the complexity or difficulty of the task.


Machine learning and AI automation can now be integrated into any process or product for better results. You can use AI and ML in manufacturing and retail, or integrate them with cameras to detect vehicles, assess food quality, and more.

With so many integrations into various processes in all sectors, AI automation has paved the way for not only ITOps, but DevOps, AIOps, and MLOps.

These measures require experts who can set up the AI/ML infrastructure and deploy its models, manage and maintain the models and logistics, and improve them to improve efficiency.

Even in a mobile-first world, where about 97% of mobile users are using AI-powered voice assistants, the reach is growing. These assistants rely heavily on ML models, creating opportunities in Dev/AI/ML Ops.

read more:

Source link

Leave a Reply

Your email address will not be published. Required fields are marked *