What is Iris.ai?

Project Aiur

What if the Research and Development process was automated so that companies could focus on developing products above all?

Iris AI claims that they have a solution which will be able to help companies solve most of their problems 90% faster. In a simpler sense, this seems to mean exactly what was suggested above. Through using Machine Learning, Iris AI hopes to do exactly what was suggested above through their “Project Aiur.” The principal question is: how?

The Tech

With Aiur, it all begins with a research team inputting one paper that they have chosen as suitable for their needs. From here, Iris uses a process which it calls “fingerprints.” In a nutshell, this process uses keywords from the first paper as well as synonyms and hypernyms from the same paper, which then allows Iris to suggest papers from a database of more than 83 million, which might serve the research team’s needs well. If you’re not already clear on the subject, a good example of a hypernym is that plant is a hypernym of a Narcissus, for example.

Iris lists the overall benefits of the fingerprint process as: bypassing keyword search, bookmarking papers in an easier way and bypassing citations or eliminating the need for creating them yourself, as well as being able to download every paper in one place. In short, Iris hopes to provide the one stop shop, Blockchain and Machine Learning based, improved version of Jstor.

The Blockchain fits into the process because it acts as the decentralized database which holds all of the previously mentioned papers as well as those which will be added in the future. As has also already been mentioned, AI fits into the mix in the case of the predictive “fingerprints” process. All in all, the stage is set for Aiur to possibly disrupt the research space, especially in the case of pay-to-play research databases like Jstor. What still isn’t quite clear is exactly what they are planning for the future.

The Roadmap

In the future, Iris also plans to integrate Crypto tokens with Project Aiur in order to provide an incentive for paper authors to post their works on the Aiur Blockchain. Even when the paper is one that fails to achieve significant results in its area, Aiur will still accept it and reward the author equally.

Overall, it seems as if the project is also reaching even higher than just democratizing the research sourcing process as it also aims to also democratize the peer review process so that significant barriers are removed, related to publishing research.

Looking Forward

What still hasn’t been mentioned yet is that Aiur’s not just targeting research professionals. The diagram that they provide related to who they envision being involved in the platform actually includes 8 parties. Beyond research teams and individual researchers, Aiur also hopes to involve quality assurance professionals, software developers, universities and other research institutions, coders, and AI trainers. While the QA professionals and the developers will be the ones maintaining the efficiency and overall operability of the platform, it is hoped that Research institutions and coders will be motivated to help build it and therefore, help decide where it moves in the future. The final, arguably interesting part of the entire platform is that it is hoped that individual researchers will also be motivated to trust the Aiur Blockchain to prove that their research has been published in a trustworthy way.

In short, with these various goals related to the Research space, it should be logical to wonder: how can this all be tied together into one pitch for Aiur? It seems like the most likely way to do this would be to talk about what Aiur hopes to do for the Research space, overall, beyond its individual goals. With all of the information at hand, it does appear that one possible answer could be: Project Aiur hopes to provide an easy-to-use alternative to the traditional academic research process that cuts out the for profit publishing houses. The only remaining question is: just how easy-to-use will Aiur be? Unfortunately, this can’t be answered until it is tested on the open market. Again, all of this will depend on how the network performs on the open market, and as of now, it is slated to launch at a later date.

In this case, it’s important to remember that, overall, everything hinges on the training data that we will be able to gather for ourselves on Aiur’s real-world performance.