Cindicator<\/a>\u2019s basic ideas was intrigued by the formula or \u201ccollective wisdom + AI = hybrid intelligence.\u201d What\u2019s the functions that the AI will perform at the prediction market, and how will it interact with user predictions?<\/strong><\/p>\nYuri Lobyntsev:<\/strong> First of all, our AI has nothing to do with prediction markets. There are numerous differences between our approach and a classic prediction market, and it\u2019s important. Analysts risk their money by making predictions at a prediction market, and those markets are created by customers who pay for that. In our case, there are no bets, and there are no risks.
\nOur analysts make their predictions without any risks, and score points for accuracy of those predictions. The AI studies divergence and accuracy of every analyst\u2019s prediction, and dynamically changes the trust weight factor for them. Thus it solves the problem of forming a single accurate prediction on the basis of many predictions by all analysts, and it uses the accumulated stats on all those analysts.<\/p>\nFL: Are the people needed only to teach the AI, or their interaction will run deeper?<\/strong><\/p>\nY. L.:<\/strong> People will be needed, of course. People and their constantly changing expectations are a part of the market that is compulsively related to its behavior. That\u2019s the basis of our technology and research.<\/p>\nMikhail Brusov:<\/strong> We value both accurate long-term predictions and mistakes as well. Ninety per cent of mispredictions are systematic, and we disclose and research that system to have a set of valuable data used for some analytic products. Ninety per cent of traders work in the red. Just like in any other vertical structure, most estimations are wrong, but it doesn\u2019t make the entire dataset less valuable for our machine learning models.<\/p>\nFL: Who is developing the hybrid intelligence?<\/strong><\/p>\nY. L.<\/strong>: It\u2019s the work of our big team of seasoned mathematicians, coders, data scientists, traders and strategists.<\/p>\nFL: Has this approach ever been tested before?<\/strong><\/p>\nY. L.:<\/strong> Frankly, we haven\u2019t seen anything like that in two years that we\u2019ve spent working on the project. We know that there are a few teams in the world who independently use partially similar approaches. However, we know of no one who used the decentralized mind of financial analysts and machine learning together.<\/p>\n![\"Cindicator:](\"http:\/\/forklog.media\/wp-content\/uploads\/2017\/08\/YUrij-Lobyntsev-300x200.jpg\")
Yuri Lobyntsev<\/p><\/div>\n
FL: Aside from financial markets, where could this approach also apply?<\/strong><\/p>\nM. B.:<\/strong> Hybrid intelligence and its sub-products could be used in any industry requiring one to make difficult decisions under uncertain conditions. Value of this approach may vary for different verticals. I see science, business analysis, social studies, politics and sports as the most promising areas for us.<\/p>\nY. L.:<\/strong> Hybrid intelligence could replace venture investment funds in the future, and Cindicator\u2019s ecosystem could become a new venture investment industry. Some of our analysts could become oracles or delegates for venture areas on Cindicator and assume such functions as project sourcing, due diligance, assessment of cost and attraction of some projects. It also includes factor analysis, risk assessment, analysis of demand, value propositions testing, search for competitors, market research, business development and so on.<\/p>\nHybrid intelligence\u2019s edge over a venture fund team is that our oracles, just like sensors, are distributed across the globe and run analysis 24\/7 in each region with direct physical access to the project teams and regional markets.<\/p>\n
FL: What are the advantages for Cindicator users compared to those of Augur or Gnosis? What\u2019s your opinion on those projects?<\/strong><\/p>\nM. B.:<\/strong> First of all, Cindicator is not a prediction market. We use completely different models, both in technology, business and logical connections between the elements that make up our ecosystem. We offer our oracles to invest their intellectual assets in our ecosystem by doing intellectual job to make different predictions. Our users don\u2019t bet any money, and don\u2019t risk anything at all. Our platform would allow them to monetize their intellectual assets and enhance their analytic abilities by perfecting their forecasting skills and expanding their knowledge base. Some of our superforecasters have been eventually hired by investment funds and major companies. We have validated their skills and tenure at our platform. They\u2019ve been accumulating their experience for 18 month now.<\/p>\n![\"Cindicator:](\"http:\/\/forklog.media\/wp-content\/uploads\/2017\/08\/nedost-300x199.jpg\")
Mikhail Brusov<\/p><\/div>\n
FL: What would it take to make the platform completely decentralized?<\/strong><\/p>\nM. B.:<\/strong> Presently, our team includes centralized traders and analysts that closely cooperate with our data scientists and mathematicians to develop different analytic approaches to retrieving data and testing trade strategies. One of our most important long-term goals is to abandon centralization at this part and using decentralized data scientists, traders and analysts that would complement the hybrid intelligence with their intellectual contributions.<\/p>\nFL: What inspired you to start developing the project?<\/strong><\/p>\nM. B.:<\/strong> Cindicator is a classic black swan that was born out of seemingly random events in my life. That was reading Azimov\u2019s Foundation on a fantastic hybrid science of psychohistory that uses math and history to predict the galaxy\u2019s future. Secondly, there was a meeting with a venture investor in New York who recommended me to read a recently published work on superforecasters titled Superforecasting: the Art and Science of Social Predictions. My proclivity for technological entrepreneurship also had some role in that: I\u2019ve been doing that for eight years now.<\/p>\nY. L.:<\/strong> Cindicator originates from the research of collective wisdom. The idea itself and the research work are evolving together with the project. I\u2019m confident that we\u2019ll see the results of this joint work in a year or two. I\u2019ve always been interested in mind. I\u2019ve spent most of my life studying intellectual and cognitive systems, collective wisdom, and consciousness as a whole. Cindicator is a project where all our ideas come to life. Our lives are the inspiration.<\/p>\nFL: What do you personally consider the most innovative element of the project?<\/strong><\/p>\nM. B.:<\/strong> There are two most important things for me:<\/p>\n\n- Studying the system behind human errors while solving different problems. Ninety per cent of all errors are systematic, so, by knowing the laws of human errors one may avoid them and therefore accelerate technological advancement.<\/li>\n
- Merging different kinds of intelligence in a single living ecosystem that uses the most modern machine capacities to solve different problems and make scientific breakthroughs.<\/li>\n<\/ul>\n
Y. L.:<\/strong> We\u2019re creating a single globally distributed intellectual ecosystem capable of processing highly complex tasks at an evolutionary level that is absolutely new to the human consciousness.<\/p>\n","protected":false},"excerpt":{"rendered":"Cindicator could pass as a yet another prediction market, however, on closer look it becomes clear it\u2019s not one.<\/p>\n","protected":false},"author":1,"featured_media":4246,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"select":"","news_style_id":"","cryptorium_level":"","_short_excerpt_text":"","creation_source":"human_written","_metatest_mainpost_news_update":false,"footnotes":""},"categories":[198],"tags":[438,683,684],"class_list":["post-4244","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-opinion","tag-artificial-intelligence","tag-cindicator","tag-hybrid-intelligence"],"aioseo_notices":[],"amp_enabled":true,"views":"306","promo_type":"","layout_type":"","short_excerpt":"","is_update":"","_links":{"self":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/4244","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/comments?post=4244"}],"version-history":[{"count":2,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/4244\/revisions"}],"predecessor-version":[{"id":4250,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/4244\/revisions\/4250"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/media\/4246"}],"wp:attachment":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/media?parent=4244"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/categories?post=4244"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/tags?post=4244"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
![\"Cindicator:](\"http:\/\/forklog.media\/wp-content\/uploads\/2017\/08\/Cindicator-1.jpg\")
<\/p>\n