First of it is important to understand why we should use AI. Given the reason then, become very easy to get the different way of using it.

Why use AI?

AI can provide a lot of benefits to both businesses and individuals. Some of the potential benefits are:

1. Automation: AI can automate many mundane, repetitive tasks, allowing you to focus on more creative or strategic work.
2. Efficiency: By analyzing large amounts of data, AI can help identify patterns and insights that you might not be able to see, which can lead to more efficient decision-making.
3. Language processing: AI translation power is quite astonishing. You can use it to translate or generate text or voice input.
4. Personalization: For businesses, AI can be used to personalize experiences for users, such as recommending products or services based on their preferences.
5. Predictive maintenance: AI can help predict, using the amount of data available by the company, when equipment or machinery might need maintenance or repair, reducing downtime and costs.
6. Fraud detection: AI can help detect fraud by analyzing patterns and anomalies in financial transactions.
7. Autonomous vehicles: AI can be used to enable autonomous vehicles, which could revolutionize transportation and logistics.

How to use it

The best way to use AI depends on your specific use case and the resources available to you.

Third-party tools and APIs can be a good option if you don’t have extensive technical knowledge or large amounts of data, while building your own AI model may be necessary for more complex use cases that require customization.

Ultimately, the best approach is to evaluate your needs and resources and choose the option that makes the most sense for your organization.

What are the well know third-party tools?

I will list some examples of third-party tools that can be used to implement AI:

1. Google Cloud AI Platform: This is a cloud-based platform that provides tools for building, training, and deploying machine learning models.
2. Microsoft Azure Machine Learning: This is a cloud-based platform that provides tools for building, training, and deploying machine learning models. It also includes pre-built models that can be customized for specific use cases.
3. Amazon SageMaker: This is a cloud-based platform that provides tools for building, training, and deploying machine learning models. It includes pre-built models that can be customized for specific use cases.
4. IBM Watson Studio: This is a cloud-based platform that provides tools for building, training, and deploying machine learning models. It includes pre-built models and can also integrate with other IBM Watson services.
5. Hugging Face Transformers: This is a Python library that provides pre-trained models for natural language processing (NLP) tasks, such as text classification, sentiment analysis, and question answering.
6. TensorFlow Hub: This is a repository of pre-trained machine learning models that can be used for a variety of tasks, such as image classification, text embedding, and natural language processing.
7. OpenAI GPT-3: I know you know it, maybe it’s the reason why you are here!

TL;DR

AI could give you different benefits both to you and your business, I could make your work more efficient and give you time to focus on the value instead of the process.

If you want to exploit it you can use third-party tools for implementing AI including cloud-based platforms like Google Cloud AI Platform, Microsoft Azure Machine Learning, and Amazon SageMaker, as well as Python libraries like Hugging Face Transformers and TensorFlow Hub.

These tools provide pre-built models and frameworks for building, training, and deploying machine learning models for various tasks, such as natural language processing and image classification.