Iris.ai is your AI Science Assistant that semi-automates the discovery and literature review of your research process

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Hi everyone, We’re thrilled to be launching our 4.0 version of our Exploration Tool that comes with critical new updates to the input field, map editing and workflow! The Iris.ai Exploration Tool helps you to find relevant research for your R&D project or thesis work. Based on scientific tests conducted with more than 100 students and researchers from different disciplines, and assessed by independent evaluators, we found that the Iris.ai tool consistently outperforms old-school research tools. Update 1: Start from your own problem statement The Exploration Tool will first ask you to type in a problem statement or paste a URL of a research paper into the search field. The tool will then build an interdisciplinary research map organized around machine generated topics that work as entry points to the topics on the next layer and, finally, to the research articles. With a visualized overview you can navigate around until you find what you need, and directly download the paper - or use the paper to make a new map. When drafting a problem statement, think how you’d describe the problem to a friend who’s not an expert in your field. That’s how the artificial brain of Iris.ai likes to chew the information! A description of 300 words where the most important concepts are explained will deliver a map that covers research papers related to the most relevant angles of the problem. Update 2: Edit the map with the Hierarchy Editor If you weren’t fully satisfied with the topic hierarchy presented by Iris.ai, you can edit the research map with the new Hierarchy Editor. The functionality allows you to merge, remove and reorganize the topics presented in the map. To access the Hierarchy Editor, make sure you have created an account at https://the.iris.ai Update 3: Workflow Our workflow improvements allow a quick navigation to your exploration search history, bookmarked papers and maps, all accessible from your personal dashboard. Like with the Hierarchy Editor, you need to have a registered account to access the dashboard. For those interested in the technology, the brief explanation is that in the process of finding papers, our tool builds a "fingerprint" using machine extracted key concepts and contextual synonyms and hypernyms, and matches the fingerprint against more than +70M Open Access papers. Our research team is currently working on hypothesis extraction from documents to get more insights into the building blocks of research articles. Means that the future tools will have neat new features! With this new version of our AI Science Assistant, we hope we will help you focus on the most critical aspects of the research process rather than formulating keywords to find articles. We look forward to hearing your feedback! Oh, and all this is free for individuals just because it's the right thing to do. :)
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@twitnitnit It sounds great, one of the biggest issues in science is the amount of bad studies that get shared as evidence of a claim. Can the AI determine the strength of the papers? for instance are peer reviewed studies in reputable journals and meta-analyses weighted above the rest? And what do you do to stop people from cherrypicking studies that meet their existing biases?
Really nice tool! Used it for my research about AI 🙃
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@marcel_heinz1 Awesome! Glad to hear it was able to help out. :)
Hey, can't buy tokens on "https://projectaiur.com/token-sale/" since my connection is not private.
@andrey_lukin The link to buy tokens for now just leads to a form to join the whitelist. :) You should be able to join without a private connection, but if you're having any trouble with it don't hesitate to send me a message and I can try to help you out.