What is Findsight AI?
Findsight AI is a search engine specifically designed to explore and compare core ideas from thousands of non-fiction works. This platform caters to the needs of individuals seeking to understand different perspectives on a particular topic from multiple sources. Its unique function is its ability to perform syntopical reading, enabling users to discover and compare claims from various authors and works.
How does Findsight AI work?
Findsight AI operates by enabling users to explore non-fiction content based on claims, which are the key points made by different sources. Users enter their search criteria and can apply various filters to refine the results. Available filters include BASIC filters like MENTION and REFERENCES, and AI-powered filters such as STATE and ANSWER. Claims identified by these filters can then be compared and explored further to create a more personalized learning journey.
What are the main features of Findsight AI?
The main features of Findsight AI include various search filters including MENTION, REFERENCES, DISCUSS, STATE, and ANSWER. It offers syntopical reading, which lets users discover and compare claims from different sources. Users can refine their search results based on literal text or named entities using the MENTION and REFERENCES filters respectively, target specific tags linked to a source through the DISCUSS filter, or use the advanced AI-powered STATE and ANSWER filters to search for related claims useful for citations or that answer a specific question.
How does the MENTION filter work in Findsight AI?
The MENTION filter in Findsight AI works similarly to a typical Google search, finding sources based on literal text input by the user. While it serves as a good starting point, it may lack precision and broadens the range of results. For example, searching for 'running' could yield results not only in relation to the sport but also about running a business or state-run systems.
Can you explain how the REFERENCES filter works in Findsight AI?
In Findsight AI, the REFERENCES filter refines search results by suggesting named entities or concepts referenced across sources that can be used to further refine results. Users can type a term and select suggestions that appear. Some suggestions link to Wikipedia, while others are named entities. For instance, typing 'running' could produce 'Skill running' as a named entity or 'Run (baseball)' as a linked entity with a Wikipedia icon.
What does the DISCUSS filter do in Findsight AI?
The DISCUSS filter in Findsight AI targets specific tags linked to a source. It functions similarly to the REFERENCES filter but focuses solely on specified topics associated with a given source. These topics appear right beneath each result's title as an expandable list, and may provide more refined and specific search results.
What is the difference between basic and AI-powered filters in Findsight AI?
In Findsight AI, basic filters - MENTION, REFERENCES, and DISCUSS - identify sources based on literal text, named entities or suggestions, and specific tags linked to a source respectively. On the other hand, AI-powered filters - STATE and ANSWER - allow users to enter their custom claims or questions. The STATE filter identifies related claims, while the ANSWER filter locates claims that address the input question with relevant context and data.
How do the STATE and ANSWER filters function in Findsight AI?
In Findsight AI, the STATE filter lets users enter a custom claim to find related claims, useful for citations. The ANSWER filter, on the other hand, identifies claims that directly address a question entered by the user and provides accompanying context and data to help answer it.
What limits are there on using AI filters in Findsight AI?
Findsight AI permits up to 50 searches using AI filters per day. The number of searches can be increased by removing an AI filter.
Can you explain syntopical reading in the context of Findsight AI?
Syntopical reading is a methodology for understanding and comparing insights from multiple works. In the context of Findsight AI, it refers to exploring non-fiction content based on key points or claims made by various sources. By applying filters and examining these claims, users can see how different authors tackle issues, thus gaining a more comprehensive understanding of the topic from diverse perspectives.
What's the difference between the MENTION and REFERENCES filters in Findsight AI?
In Findsight AI, the MENTION filter identifies sources based on literal text input. It can yield broad results as it picks up any text that matches the search terms. The REFERENCES filter refines this approach by suggesting named entities or concepts referenced across sources, allowing for more accurate and refined results based on context and implied meanings in the search term.
How does Findsight AI help to compare claims from multiple sources?
Findsight AI helps to compare claims from multiple sources through its syntopical reading system. It identifies the key points (claims) made by various sources and presents them for comparison. This allows users to understand how authors tackle issues differently and gain a comprehensive understanding of a subject.
Can Findsight AI direct me to the original non-fiction sources?
Yes, Findsight AI does provide links to the original books or articles from where the claims or key points have been referenced. This allows users to delve deeper into specific topics by checking and comparing the original non-fiction sources.
Is it possible to enter custom claims in Findsight AI?
Yes, it is possible to enter custom claims in Findsight AI. The STATE filter facilitates this functionality. It permits users to input their custom claims and find related ones, which are also useful for citations.
How can I refine search results in Findsight AI?
You can refine your search results in Findsight AI by utilizing different filters. Basic filters like MENTION, REFERENCES, and DISCUSS can identify sources based on literal text, named entities, and tags linked with a source respectively. Additionally, AI-powered STATE and ANSWER filters allow entry of custom claims and questions for a more personalized and specific search experience.
What does Findsight AI mean by 'named entities'?
In Findsight AI, 'named entities' refer to specific concepts, items or ideas that are referenced across diverse sources. They are used to fine-tune search results in the REFERENCES filter, categorizing them for more effective differentiation. They could be anything from a concept like 'Skill running' to a specific term like 'Run (baseball)' linked to a Wikipedia page.
What kind of search phrases can I use in Findsight AI, are there special characters or operators?
Within Findsight AI, search inputs can accept prefixes (marked with asterisks) and alternatives using the 'OR' operator. For instance, if you type 'dus* OR wash*', it would fetch results containing words starting with 'dus' and 'wash', like 'dusting' and 'washrooms'. This allows for a wider gamut of search results.
Can I check how authors approach an issue differently using Findsight AI?
Yes, you can check how authors approach an issue differently using Findsight AI. By exploring non-fiction content based on claims or key points made by various authors and comparing these claims, you can understand the various perspectives and approaches used by different writers on the same issue.
How can I create and navigate through my own learning journey using Findsight AI?
Creating and navigating your own learning journey in Findsight AI is facilitated by a nuanced exploration of non-fiction content based on claimsโthe key points made by sources. By discovering and comparing these claims, and navigating to related claims, you can create your own learning journey according to your interests. You can start with a 'Random' claim to explore a new subject.
What does Findsight AI mean by filters like 'state' or 'answer'?
In the context of Findsight AI, the 'STATE' filter allows users to input a custom claim and find related ones, useful for gathering citations. The 'ANSWER' filter identifies claims that address a user's specific question, providing context and data to help answer it, enhancing the search experience by focusing on questions and answers.