The vast majority of published scientific literature and new research is hidden behind paywalls. Worse, what few accessible papers available online are oftentimes written in jargon, i.e., specialist language that can alienate non-expert readers.
Combined, these two issues make it difficult for researchers, scientists, and even entrepreneurs to build on new discoveries and for members of the public to access credible, peer-reviewed literature in the age of misinformation.
The good news is, natural language processing-based startups are working to change the conversation around access to scientific knowledge in impactful ways. One such startup is Consensus, an AI-powered search engine designed to provide users a view into what the research says with the click of a button.
In this episode, host Adam Gamwell is joined by Consensus CEO Eric Olson to talk about the company’s inception, the promise and new waves of natural language processing technology, and how Consensus is making scientific findings accessible and consumable for all.
[04:08] How Eric Olson got into natural language processing
[06:15] How tech can help users know what information to trust online
[08:10] The difference between giving good information and giving engaging information
[10:32] How Consensus attempts to disrupt the global search industry
[13:50] The current state of search
[15:32] How Consensus approaches partnerships
[17:07] On the size of Consensus’ corpus
[19:59] How natural language processing is evolving
[21:19] How Consensus fine-tunes its AI system
[24:53] On using AI generators to write papers
[26:47] How search platforms like Consensus can be built in a way that’s usable for laypeople
[30:32] Why context in AI is important
[33:05] The three things that differentiate Consensus from existing search engines
[39:37] What’s next for NLP-based technologies as a whole
[41:14] What’s next for Consensus
[43:10] On the hypothesis that AI can’t replace subjective, art-based roles
[46:12] Closing statements
Links and Resources:
Check out Consensus
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