Competent service for analysing textual data
What do you like best about the product?
- Ability to read from different data sources such as html pages, docs or pdfs
- A no-code web interface as playground
- Easy to follow SDK for integrating with programming languages to use Watson apis in code
- A no-code web interface as playground
- Easy to follow SDK for integrating with programming languages to use Watson apis in code
What do you dislike about the product?
- Comparatively costly. At an age where open source models can be used to achieve more than decent performance in the tasks for which IBM watson discovery is used, it is not clear why someone will like to shell out some money for this.
- Apart from basic aspects about text data such as sentiments and entities, other use cases might not be clear for a no-code user.
- Apart from basic aspects about text data such as sentiments and entities, other use cases might not be clear for a no-code user.
What problems is the product solving and how is that benefiting you?
Approaches such as RAG (Retrieval Augmented Generation) is used to leverage the benefits of LLM in existing workflows. One such use cases is quickly organize the unstructured text data and query the resultant data to gain insights - for this IBM Watson Discovery can act as the playground to realise what improvements to expect if a LLM is used.
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