Project Aiur

initiated by Iris.ai

We envision a world where the right scientific knowledge is available at our fingertips. Where all research is validated and reproducible. Where interdisciplinary connections are the norm. Where unbiased scientific information flows freely. Where research already paid for with our tax money is freely accessible to all. Where massive R&D budgets also benefit contributors to core scientific breakthroughs. 

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Project Aiur at a glance

Democratizing
Science
through blockchain-enabled disintermediation.

There are a number of problems in the world of science today hampering global progress. In a highly lucrative oligopolistic industry with terrible incentive misalignments, a radical change is needed.

The only way to change this is with a grassroots movement – of researchers and scientists, librarians, scientific societies, R&D departments, universities, students, and innovators – coming together.

We need to forge an alternative to powerful existing intermediaries, create new incentive structures, build commonly owned tools to validate all research and build a common Validated Repository of human knowledge.

A combination of blockchain and artificial intelligence provides the technology framework, but as with all research, the scientist herself needs to be in the center.

That is what we are proposing with Project Aiur, and we invite you to join us.

Media Coverage

“Money makes the world go round, scientific publishing is no exception to the rule”

“Create a world where cutting-edge information becomes accessible to everyone”

“Democratize access to and extend the reach of scientific knowledge worldwide”

“Further the reach of scientific knowledge around the globe”

“It’s a system ripe for disruption”

“Aiur could democratize access to and extend the reach of scientific knowledge”

Key messages

Goal

€10,000,000

We target the ETH equivalent of €10M with a minimum for completion of 60% and a hard cap of 500%. If the minimum is not reached, all ETH will be returned to the original holders.

Allocation

75%

75% of the amount raised will belong to the community, and will be released subject to development milestones – to anyone who achieves them, subject to community scrutiny. The remaining 25% will be allocated to Iris.ai for the planning and initial execution of the project.

Restrictions

2%

i
No token buyers from China, Iran, Singapore, South Korea or United States. Australia and Canada under evaluation.
No one entity holding more than 2% of the total pool
Investments over a certain threshold require identity checks

Far from an instrument suited to short-term financial speculation, AIUR tokens are designed for natural holders, who believe in the value-added that Aiur will bring either to them directly or to other third-party use-cases.

Value growth: the Knowledge Validation Engine

The core of the Aiur economy is a community-owned artificial intelligence-based engine for Knowledge Validation – semi-automation of Peer Review, if you like.

All payments for services from the Knowledge Validation Engine will be done to the Aiur Financial Institution. At the same time, new token issuance to community members will be strictly restricted to value contributions. The Aiur Financial Institution will manage AIUR demand and supply flow, burning excess tokens accumulated via a sustained influx of capital. These mechanics govern the value growth of the community economy.

REVENUE STREAM 1:

Direct querying of the KVE

Universities, research institutes and R&D departments spend $128Bn a year on “digital enablers”, and a medium sized department can save millions yearly with tools like the KVE. These organizations have their own internal tools and processes, and will connect these directly to the Aiur API. They pay AIUR to query the engine.

REVENUE STREAM 2:

Third-party applications

A variety of future applications will rely on the Aiur KVE. This will tap into markets such as patent writing and prior art searches, hedge fund technology predictions, research funding and venture capital. 3rd party tools charge their clients and then pay AIUR to query the engine.

The AIUR Token

Functional token
With clear ’proof-of-human-work’ characteristics in its design, the AIUR token is functional by nature. It's both the only way to tap into Aiur directly and can be a voucher for significantly discounted prices for products built on top of Aiur, including Iris.ai tools.
Functional token
With clear ’proof-of-human-work’ characteristics in its design, the AIUR token is functional by nature. It’s both the only way to tap into Aiur directly and can be a voucher for significantly discounted prices for products built on top of Aiur, including Iris.ai tools.
No short term investors or hodlers

Far from an instrument suited to short-term financial speculation, AIUR tokens are designed for natural holders. Value growth occurs over time with core usage of, and 3rd party applications on top of, the community owned Knowledge Validation Engine.
No short term investors or hodlers
Far from an instrument suited to short-term financial speculation, AIUR tokens are designed for natural holders. Value growth occurs over time with core usage of, and 3rd party applications on top of, the community owned Knowledge Validation Engine.
Capped token sale
Our token sale will target raising the ETH equivalent of c. € 10,000,000, with a minimum for completion of 60% and a hard cap of 500%. If the minimum is not reached, all ETH will be returned to the original holders.
Capped token sale
Our token sale will target raising the ETH equivalent of c. € 10,000,000, with a minimum for completion of 60% and a hard cap of 500%. If the minimum is not reached, all ETH will be returned to the original holders.
Community ownership off the bat

75% of the amount raised will belong to the community, and will be released subject to development milestones - to anyone who achieves them, subject to community scrutiny. The remaining 25% will be allocated to Iris.ai for the planning and initial execution of the project.
Community ownership off the bat
75% of the amount raised will belong to the community, and will be released subject to development milestones – to anyone who achieves them, subject to community scrutiny. The remaining 25% will be allocated to Iris.ai for the planning and initial execution of the project.
Removing ourself as the central player

There are two phases in Project Aiur. In ‘Phase 1’ Iris.ai will be holding 50%  1 of the tokens in circulation, and after the transition to ‘Phase 2’ we will renounce all tokens outside of the allowed 2% cap, thus becoming an equal community member.
Removing ourself as the central player
There are two phases in Project Aiur. In ‘Phase 1’ Iris.ai will be holding 50% +1 of the tokens in circulation, and after the transition to ‘Phase 2’ we will renounce all tokens outside of the allowed 2% cap, thus becoming an equal community member.
No founder compensation  
Iris.ai’s founders will not receive any direct monetary compensation, in either fiat, cryptocurrency or AIUR tokens. Iris.ai, the initiating commercial entity, sees this as a unique strategic opportunity to impact the industry and the world, and commercially to have a first mover advantage on 3rd party applications.
No founder compensation
Iris.ai’s founders will not receive any direct monetary compensation, in either fiat, cryptocurrency or AIUR tokens. Iris.ai, the initiating commercial entity, sees this as a unique strategic opportunity to impact the industry and the world, and commercially to have a first mover advantage on 3rd party applications.

Ecosystem

Contributors

Earn tokens from their
community contributions

AI Trainers
Build annotated data sets
Implemented from the
 start
AI Trainers
Build annotated data sets
Implemented from the start
Coders
Build the Aiur Knowledge Validatiton engine
Coders
Build the Aiur Knowledge Validatiton engine
Quality Assurance
Find the glitches in the matrix 
And bugs in Aiur
Quality Assurance
Find the glitches in the matrix
And bugs in Aiur
Researchers
Publish their own and review others' research
Researchers
Publish their own and review others’ research
Home

Aiur

Home
  • Oracle observing the outside world
  • Institution maintaining balance
  • Constitution of rights and obligations
  • ETH and AIUR pool
  • Code repository
  • Research content repository
Home

Users

Pay tokens for access to the
core technology and content

R
R&D and institutes
Build custom internal tools on top of Aiur functionality
Universities and Consortia
Queries the Aiur engine directly for core results
Universities and Consortia
Queries the Aiur engine directly for core results
Software developers
Build valuable 3rd party tools on top of Aiur reaching new markets
Software developers
Build valuable 3rd party tools on top of Aiur reaching new markets
Individual researchers
Use the Aiur engine for validation before traditional publishing
Individual researchers
Use the Aiur engine for validation before traditional publishing

Ecosystem

Contributors

Earn tokens from their community contributions

AI Trainers
Build annotated data sets
Implemented from the
 start
AI Trainers
Build annotated data sets
Implemented from the start
Coders
Build the Aiur Knowledge Validatiton engine
Coders
Build the Aiur Knowledge Validatiton engine
Quality Assurance
Find the glitches in the matrix 
And bugs in Aiur
Quality Assurance
Find the glitches in the matrix
And bugs in Aiur
Researchers
Publish their own and review others' research
Researchers
Publish their own and review others’ research
Home
Home
Home

Users

Pay tokens for access to the core technology and content

R
R&D and institutes
Build custom internal tools on top of Aiur functionality
Universities and Consortia
Queries the Aiur engine directly for core results
Universities and Consortia
Queries the Aiur engine directly for core results
Software developers
Build commercial and open source tools on top of Aiur
Software developers
Build commercial and open source tools on top of Aiur
Individual researchers
Use the Aiur engine for validation before traditional publishing
Individual researchers
Use the Aiur engine for validation before traditional publishing

Aiur

  • Oracle observing the outside world
  • Institution maintaining balance
  • Constitution of rights and obligations
  • ETH and AIUR pool
  • Code repository
  • Research content repository

The challenges faced by science

Information overload

Home

Challenge

The amount of scientific knowledge we have as a human species is unprecedented and growing. No human mind can cope with the vast volume of research being generated today. This unmanageable information overload slows down and introduces massive inefficiencies in both academic and corporate research processes, hampering global innovation.

Solution

AI-based tools to assist humans in navigating and connecting the knowledge. Iris.ai’s tools today semi-automate the literature review phase – next we need to do machine hypothesis extraction, hypothesis validation and eventually building new hypotheses. 

Access barriers

Home

Challenge

Traditional publisher business models are coming under increased scrutiny. The sustained, abnormally high relationship between economic returns yielded and business risks assumed by these legacy models has faced harsh criticism from scientific researchers, academic institutions, policy-makers and the general public alike.

Solution

A united global grassroots movement pushing for Open Access research and putting join pressure on the large publishing houses to alter their business models and pricing schemes. The OA movement has made great progress until now – and it’s time to shift gears. 

Poor reproducibility

Home

Challenge

Substandard reproducibility of published research studies adds to pain points suffered by students, researchers and R&D departments across sectors. And when considered in combination with other problems here, reproducibility deficits make it fundamentally hard to build new knowledge on top of old results.

Solution

A combination of 1) a Knowledge Validation Engine: validating every aspect of a research paper up against all other knowledge. This can immediately uncover underlying false assumptions, circular dependencies, conflicting results and other reasons why a paper might not be reproducible before substantial time is spent on it, and 2) increased public scrutiny incentivizing more thorough diligence.

Built-in biases

Home

Challenge

Existing tools focused on scientific search have been built with a common keyword and citation-based architecture that incorporates serious issues with learning-over-time and the identification and address of biases including negligence of under-cited research.

Solution

A long-term process, with users gradually realizing that there are great results de facto not visible through existing search engines. Additionally, Aiur will provide an invaluable control set to test the effectiveness of the citation system and help newly written articles have a more comprehensive and easy to build citation list.

Misaligned incentives

Home

Challenge

Research professionals are currently forced to deliver, publish and review on tight deadlines, with little to no accountability and reward for authors and reviewers, creating perverse incentives towards exaggerating facts and omitting assumptions and constraints.

Solution

Authors will get tokens for embracing increased openness standards, including for publishing of failed results. Aiur will also open up the peer review process, and it will facilitate the generation of specialized datasets.

Timeline

June 2015
May 2017
Dec 2017
Jan 2018
Apr 2018
May 2018
July 2018
September 2018
Jan 2020

June 2015

Iris.ai was born

During our time at Singularity University’s Global Solutions Program at NASA Ames Research Park summer 2015, the Iris.ai/Project Aiur cofounders first met. Sitting down to find a problem to solve – one that would positively impact a billion people within a decade – the discussions started circling the long row of problems surrounding academic research.

Whether it was having been involved in deeply technical startups and first hand experienced the pain of diving head first into finding the right research, experiencing serious illness and needing to identify and understand the latest medical breakthroughs, or simply having research being our everyday job – we could all relate to the same pain points.

Towards the end of the summer, the initial idea of building an “AI Researcher” was born – and execution began.

 

May 2017

The Aiur idea was born

Summer 2017 we came to an important realization: Having successfully built a number of AI tools, generating revenue from R&D Departments, we realized while we could build a successful commercial entity, it would not allow us to make the true societal impact we set out to. With the recent advances of the blockchain world, one of the original pain points – paywalled content and entirely skewed incentives – came back up. Through late summer and fall, the discussions intensified.

Dec 2017

The first announcement

At Slush, together with our seed funding announcement, we decided to tell the world what we were working on. The seed funding gave us some financial leeway, and our thinking around the new blockchain project had matured sufficiently that we felt ready to tell the world what we were doing – putting additional pressure on ourselves to iron out the details and getting the show on the road.

 

Jan 2018

Finding the name (and geeking out on Starcraft)

After an internal name nomination and voting round, in which it was discovered that the entire research team (and plenty of the developer team) were long-term Starcraft geeks, the name of the project was found: Project Aiur.

 

Apr 2018

We release more details!

After months of really hard work, we were finally ready to announce the highlights of the project. We launched this website, the summaries of the white paper, a press release and social media channels. We will continue over the next few weeks with video content, more details, AMA’s and other social media events.

May 2018

Full White paper released

In the works since summer 2017, on June 1st our Full Whitepaper was launched to the world! As the full white paper is a thorough piece of work counting a lot of pages, the summaries – including a 2-page plain text summary – can be found at iris.ai/aiur.

July 2018

Token sale starts

In order to fund the Aiur community, we are doing a token sale.

Per early June 2018, we have a private sale ongoing – for more details, contact CEO Anita Schjøll Brede on anita@iris.ai.

We aim at raising the ETH equivalent of EUR 10M, with a minimum threshold of 60% and a cap of 500%. 75% will go to the community escrow, released upon completion of detailed milestones – subject to community scrutiny and open for anyone to participate in delivering. 25% will go to Iris.ai to cover the costs of the initial management of the community.

September 2018

Public sale opens

We are currently targeting September for the public sale. It is of vital importance to us to have a broad community join us, and we will as such commit to a public sale.

Having reached our minimum threshold, the ETH equivalent of €6M, we announce the successful initiation of Project Aiur and get to work on the milestones laid out in the whitepaper together with the community.

Should we have not reached our minimum threshold, received funds are returned to the sender, and we will assess how to move forward with the project without funding.

Jan 2020

Iris.ai releases 50% ownership

After the token sale, Iris.ai will be sitting with 50% of the tokens. At a certain point: either after 18 months; or if the community is ready sooner, then when that occurs; Iris.ai will release most of it tokens to the Institution, remaining only with the cap of 1%, and as such becoming only one of many actors in the community. This event will be stipulated in the smart contracts from the beginning and is non-changeable. At this point, we assume the Institution will find it favorable to the community economy to burn the tokens.

Roadmap

We outline here the route towards stable community and stable development of the Aiur Knowledge Validation Engine. The roadmap includes milestones and a draft target timeline, based on a four-montly release cycle, that will be refined in conjunction with the newly formed community.

Jun ‘18
PD0
Initial setup
Oct ‘18
PD1
Economy stability mechanisms | Keyword Annotation Tool
Feb ‘19
PD2
Consensus protocol | Initial infrastructure + Reward for coders and QA | MVP hypothesi extraction (HE)
Jun ‘19
PD3
Advanced infrastructure | HE improvements + First APIs | Hypothesis annotation tool
Oct ‘19
PD4
HE argument extraction | Alexandria MVP + Reward for researchers
Feb ‘20
PD5
Knowledge Tree Builder (KTB) and Reproducibility Engine (RE) MVPs
Jun ‘20
PD6
KTB improvements | Aldaris MVP
Oct ‘20
PD7
HE and RE black data integration | Project Char – Balancing training sets
Feb ‘21
PD8
Aldaris improvements | Validity Engine MVP
Jun ‘21
PD9
KTB and HE integration | Update of the review platform
Oct ‘21
PD10
Advanced Anti-Fraud service | First version of the KVE
Feb ‘22
PD11
Finalizing Pylon, Aldaris, Alexandria
Jun ‘22
PD12
Advanced KVE

 

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