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TechCrunch - Elicit Building Tool to Automate Scientific Literature Review
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Elicit is built by Ought, an AI safety nonprofit, making this tool relevant to AI safety researchers who may use it to review alignment literature; it also illustrates how AI capabilities are being applied to accelerate scientific workflows.
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Importance: 35/100news articlenews
Summary
TechCrunch covers Elicit, an AI-powered research assistant developed by Ought that automates scientific literature review by extracting key findings from papers, synthesizing evidence, and helping researchers navigate large bodies of academic work. The tool aims to accelerate empirical research workflows by reducing the manual burden of reviewing thousands of studies.
Key Points
- •Elicit uses large language models to search, summarize, and extract structured data from scientific papers without requiring exact keyword matches.
- •The tool is designed to help researchers conduct systematic reviews faster, potentially compressing months of literature synthesis into hours.
- •Elicit was developed by Ought, an AI safety-focused nonprofit focused on augmenting human reasoning and research capabilities.
- •The product targets a practical bottleneck in scientific research: the overwhelming volume of published literature that researchers must manually process.
- •Elicit's development reflects a broader trend of applying AI capabilities to accelerate scientific progress, with implications for AI safety research itself.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Elicit (AI Research Tool) | Organization | 63.0 |
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Elicit is building a tool to automate scientific literature review | TechCrunch
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Elicit is building a tool to automate scientific literature review
Kyle Wiggers
6:00 AM PDT · September 25, 2023
For researchers, reading scientific papers can be immensely time-consuming. According to one survey, scientists spend seven hours each week searching for information. Another survey suggests that systematic reviews of literature — scholarly syntheses of the evidence on a particular topic — take an average of 41 weeks for a five-person research team.
But it doesn’t have to be this way.
At least, that’s the message from Andreas Stuhlmüller, the co-founder of an AI startup, Elicit , that’s designed a “research assistant” for scientists and R&D labs. With backers including Fifty Years, Basis Set, Illusion and angel investors Jeff Dean (Google’s chief scientist) and Thomas Ebeling (the former Novartis CEO), Elicit is building an AI-powered tool to abstract away the more tedious aspects of literature review.
“Elicit is a research assistant that automates scientific research with language models,” Stuhlmüller told TechCrunch in an email interview. “Specifically, it automates literature review by finding relevant papers, extracting key information about the studies and organizing the information into concepts.”
Elicit is a for-profit venture spun out from Ought, a nonprofit research foundation launched in 2017 by Stuhlmüller, a former researcher at Stanford’s computation and cognition lab. Elicit’s other co-founder, Jungwon Byun, joined the startup in 2019 after leading growth at online lending firm Upstart.
Using a variety of models both first- and third-party, Elicit searches and discovers concepts across papers, allowing users to ask questions like “What are all of the effects of creatine?” or “What are all of the datasets that have been used to study logical reasoning?” and get a list of answers from the academic literature.
“By automating the systematic review process, we can immediately deliver cost and time savings to the academic and industry research organizations producing these reviews,” Stuhlmüller said. “By lowering the cost enough, we unlock
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