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Science is in trouble Information overload Built-in bias - PowerPoint PPT Presentation

Science is in trouble Information overload Built-in bias Reproducibility issues Access issues Incentives Iris.ai is helping Information overload Built-in bias Reproducibility issues Access issues Incentives Iris.ai 4.0 works with the


  1. Science is in trouble Information overload Built-in bias Reproducibility issues Access issues Incentives

  2. Iris.ai is helping Information overload Built-in bias Reproducibility issues Access issues Incentives

  3. Iris.ai 4.0 works with the researcher Result Focus Explore Start Bypass human made Define a problem Narrow down to exact Draw conclusions taxonomies to get a fresh statement to solve in reading list without based on highly perspective and broad overview 300 words. reading a single paper. relevant papers. of the problem. IRIS.AI 4.0

  4. We’re doing well! - Top 10 Innovative AI company - Raised $2M - Paying blue chip corporate and top nordic university clients - 10,000+ registered users - Proven technology through peer reviewed papers 2017 Top 10 2016 Most Innovative Company London in Artificial Intelligence Startup Battlefield Contestant

  5. Buuuuut… Information overload Built-in bias Reproducibility issues Access issues Incentives

  6. Introducing Project Aiur and blockchain Aiur is entirely community owned Validated repository Knowledge Validation Engine New incentive model Through creating the AIUR token Semi-automating quality review Open, validated and accessible

  7. Why blockchain and a token? Two sided marketplace without set prices Pseudonymity Communal property New economic model can be designed from scratch All members own it (DAO) Equal opportunity, equal scrutiny,

  8. The incentive model Earn tokens Spend tokens • AI Training • Iris.ai premium tools • Coding • Directly to the Aiur engine • Quality Assurance • In 3rd party services • Publishing • Building 3rd party services • Peer reviewing

  9. The Knowledge Validation engine “Semi-automated peer review” hypothesis extraction paper argument mining hypothesis ‘truth tree’ report each assumption validated trust level of each hypothesis Time line: 4 years

  10. The Validated Repository - Failed results - Parallell publishing - Open access - Peer reviewed - Ongoing review - Integration, collaboration

  11. Governance Iris.ai is the initiator, not owner Community decisions 75% of funds to community 1% ownership cap Iris.ai burns down within 18mo Token sale (ICO) in late May All members has voting power

  12. So… people make money on tokens? The token is functional but there is value potential 3rd party tools Repository Technology The Aiur KVE will be a powerful tool A unique, growing, living body of Funnels corporate money in to the knowledge ecosystem

  13. But why are you doing it, again? - The Knowledge Validation Engine - Strategic revenues - First mover advantage … and most important IMPACT.

  14. Founding team from Singularity University Anita Schjøll Brede Victor Botev Maria Ritola Jacobo Elosua CEO CTO CMO CFO Has built several high- Has done AI research Has created global Has secured billion tech startups & built products communities dollar deals SingularityU GSP15 Chalmers, MSc Computer Science SingularityU GSP15 SingularityU GSP15 Chalmers, MSc Entrepreneurship Sofia, MSc Artificial Intelligence HSE, MA Economics ICADE, MA int’l business HiOA, BA Theatre ESCP-EAP Paris administration, BA law, BA Stanford & UC Berkeley Skrill economics cPac UN SingularityU Denmark Faculty Chalmers Bank of Finland UBS Investment Bank 4 high-tech startups Demos Helsinki Civio

  15. I’m gonna have to Science the shit out of this! The Martian

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