Amazon Kendra VS Carrot2

I recommend you look deeper at LangChain if you are not already familiar with it. You can also look at the aws-samples Github page; they have some great examples to get you started. For example, you could add Amazon Kendra to the mix. Connect it with one of its many sources, like Atlassian Confluence, and set up Langchain to utilize the Kendra retriever. And now you have a chatbot that can answer questions based... - Source: dev.to / 6 months ago

If you're doing this on AWS they already have a really contained solution for this. I'm sure Azure has a similar solution. I'll assume AWS - if so, AWS Kendra is a good place to start. This will give you performant natural language understanding and enterprise search support. Then you just need to map the rest of your desired functions to core AWS solutions. Source: 12 months ago

> > One of the most important capabilities of Bedrock is how easy it is to customize a model. Customers simply point Bedrock at a few labeled examples in Amazon S3, and the service can fine-tune the model for a particular task without having to annotate large volumes of data (as few as 20 examples is enough) I can't even. Does anyone remember Amazon Kendra [1]? They promised the same there. "Here's an ML powered... - Source: Hacker News / about 1 year ago

Amazon Kendra is now FedRAMP High Compliant. Amazon Kendra is now authorized as FedRAMP High in AWS GovCloud (US-West) Region. Amazon Kendra is a highly accurate intelligent search service powered by machine learning. Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they are looking for, even when it's scattered across multiple... - Source: dev.to / over 1 year ago

It supports using Lambdas for fulfilling specific duties, such as placing orders, as well as integrating into Kendra which is a ML powered search service. You can effectively have a conversation asking for information and it can intelligently look through your business domain and respond with answers in a naturally conversational way. - Source: dev.to / over 1 year ago

I would spend time at https://search.carrot2.org/ with the PubMed setting and work on search terms around psoriasis which will tease out search hits in which reference is made to specific microbiome species; then look at your data and think about what you just learned. I tell that store in another post on this page. Source: about 1 year ago

My favorite game is to google the titles of some of his references, often to find out they were retracted and should have been noted. I chose his #10 and found a rebuttal to key points [1]. I'd suggest going to a plant-based website, one for which advertising does not sell pills or foods, but, instead, supports the non-profit foundation and put "animal" in the search bar [2] or study this clustered search at... - Source: Hacker News / over 1 year ago

[2] is a clustered search of PubMed on chewing gum. I've been fascinated with historic claims, e.g. That chewing gum stimulates blood flow to the brain, and others like that. ps: the link is best opened in a private window if you care about cookies. [1] https://www.frontiersin.org/articles/10.3389/fnins.2022.964351/abstract [2] https://search.carrot2.org/#/search/pubmed/chewing%20gum/treemap. - Source: Hacker News / over 1 year ago

The websearch using a clustering search engine [1] lands a cluster called "Parkinsons PD" which has 20 PubMed hits, some of which are suggestive of causal links between Paraquat and PD. [1] https://search.carrot2.org/#/search/pubmed/Paraquat/folders. - Source: Hacker News / over 1 year ago

I've had a very similar issue myself, looking for specific camber information with diagrams. A librarian showed me Carrot2 and my search game is on a whole new level. Source: over 1 year ago