Five AI tools that will replace desk job in future

One might think, the effect of COVID-19 will be temporary. But recent market trends of Artificial Intelligence show that AI beyond 2021 might be the new boss. 

Researchers at McKinsey estimate that 45 per cent of the activities we do at work can be automated with existing technology. Automation of cognitive skills is still challenging as it requires computerized perception and decision making based on unstructured data. However, many AI technologies will be used in the next 10 years for desktop jobs.

 

• AWS
• TensorFlow
• Google Cloud AutoML
• Chatbots
• Azure ML

1. AWS Machine Learning: Amazon is known for adopting artificial intelligence early and deploying it across its operations. AWS machine learning (ML) is a platform for developing and deploying machine learning (ML) models. It’s a fully managed service that makes it easy to train and deploy your models. Released in 2016, it’s one of the most popular ML platforms in the world. Also there are a number of potential drawbacks to using AWS Machine Learning. One issue is that it can be difficult to get started with the service due to the complexity of the interface. Additionally, AWS Machine Learning can be expensive, particularly if you require a lot of storage and compute resources. Finally, the service is still relatively new and is subject to change, which can make it difficult to keep up with the latest features and updates.

 

2. TensorFlow: It is an open-source machine learning platform. It’s used by researchers and developers to create and deploy machine learning models. Released in 2015, it’s one of the most popular ML platforms in the world. TensorFlow has a number of disadvantages, including:

-It can be difficult to learn and use, especially for beginners.

-It can be less efficient than other similar frameworks, such as PyTorch.

-It can be difficult to debug and optimize TensorFlow programs.

-TensorFlow doesn't always support the latest versions of Python.

3. Google Cloud AutoML: Google Cloud AutoML is a platform for training and deploying machine learning models. It’s a fully managed service that makes it easy to train and deploy your models. Released in 2017, it’s one of the most popular ML platforms in the world. Beside all these, there are a few potential drawbacks to using Google Cloud AutoML. First, it is a relatively new tool, so there may still be some bugs that need to be ironed out. Additionally, it is a bit more expensive than some of the other options on the market. Finally, there is always the potential that the machine learning algorithms produced by the tool may not be as accurate as those produced by a human.

 

4. Chatbots: These are AI tools that can help businesses automate customer support and other tasks that would traditionally be done by human employees. In 2021, chatbots are expected to become even more sophisticated and will likely replace many desk jobs. There are a few potential drawbacks to using chatbots as an AI tool. First, chatbots may not be able to handle more complex questions or tasks. Additionally, chatbots may require a lot of training and tweaking to get them working correctly, and they may still make mistakes. Finally, chatbots may not be able to replicate the human element of customer service, which can be important to some people.

 

5. Azure ML: Azure ML is a platform for training and deploying machine learning models. It’s a fully managed service that makes it easy to train and deploy your models. Released in 2016, it’s one of the most popular ML platforms in the world. One potential drawback of Azure ML is that it can be difficult to use for those who are not familiar with cloud-based systems or coding. Additionally, Azure ML can be costly, as it charges by the hour for each training or prediction run. Another disadvantage is that it can be challenging to monitor and optimize models in Azure ML due to the lack of visibility into the inner workings of the platform. Finally, Azure ML is not as widely adopted as some other ML platforms, which can make finding support or integration partners more difficult.

In conclusion, AI tools will replace desk jobs in 2021. This is because they are able to provide the same services as desk jobs, but at a fraction of the cost. This will allow businesses to save money and increase efficiency.