Suggests that when Meta AI started throwing around those multi-million-dollar paychecks they got 12 from OpenAI, 5 from DeepMind, 2 from Thinking Machines Lab and none from Anthropic.
(There's a small print disclaimer about accuracy at the bottom: "This report was generated automatically by Keenable SELECT at a user's request, from publicly available web sources linked herein. Keenable does not review, verify, or endorse its contents and makes no representation as to accuracy, completeness, or timeliness; AI-based extraction may contain errors.")
Hey, I'm on the team working on this. In terms of accuracy the best way to gauge the usefulness of these reports is to search for some you are deeply familiar with and then estimate.
In general I find these reports have some gaps but for most topics they provide a reasonable picture of what is going on. I personally prefer them over deep research reports coming out of chatgpt etc. as they are just walls of text that I skip to go to the result table.
Hey! I’m on the team working on this. The semantic web comparison is pretty close to how we think about this.
One key difference is that we’re using LLMs to create structured data on the fly based on the query. That means we don't need to relying on webmasters to explicitly annotate pages with metadata which in my view was one of the main reasons why the semantic web did not work out.
Suggests that when Meta AI started throwing around those multi-million-dollar paychecks they got 12 from OpenAI, 5 from DeepMind, 2 from Thinking Machines Lab and none from Anthropic.
(There's a small print disclaimer about accuracy at the bottom: "This report was generated automatically by Keenable SELECT at a user's request, from publicly available web sources linked herein. Keenable does not review, verify, or endorse its contents and makes no representation as to accuracy, completeness, or timeliness; AI-based extraction may contain errors.")
In general I find these reports have some gaps but for most topics they provide a reasonable picture of what is going on. I personally prefer them over deep research reports coming out of chatgpt etc. as they are just walls of text that I skip to go to the result table.
For example as somebody interested in coffee this is pretty comprehensive based on my previous research work: https://select.keenable.ai/r/dual-boiler-prosumer-espresso-m...
Otherwise looks really cool!
One key difference is that we’re using LLMs to create structured data on the fly based on the query. That means we don't need to relying on webmasters to explicitly annotate pages with metadata which in my view was one of the main reasons why the semantic web did not work out.