ML systems are becoming increasingly powerful, with applications in a wide range of fields. Additionally, ML and NLP systems are being used to improve the quality of information retrieval systems, making it easier for users to find the information they need. This makes it much easier for us to access and understand information from a variety of sources. For example,
- Conversational AI can be used to create chatbots that can hold natural conversations with humans.
- Recommender systems can use NLP to recommend products relevant to a user’s interest.
- Sentiment analysis can be used to identify the emotional tone of text.
The training of many deep learning models requires a vast amount of computational resources, such as GPUs and TPUs. The cost of inference can also be prohibitive for the application of these models in high-performance situations.