INTRODUCTION
Artificial intelligence is positioned at the core of the next-gen software technologies in the market. Companies such as Amazon, Google, IBM and Microsoft have actively implemented AI as a crucial part of their technology. But this comes at a cost: the vast number of computer resources required to perform these tasks. The hardware must be constantly renewed and consumes huge amounts of electricity for cooling. And with the exponentially increasing amount of data to exploit, the trend is only growing.
The cloud market is valued at USD 291 billion in 2019 and is expected to reach USD 1.25 trillion by 2025, at a CAGR of 27.50% during the forecast period. Machine learning is projected to be the segment with highest growth, reaching USD 188.4 billion by 2025, at a CAGR of 48.60%.
DAIN COMPONENTS
Understanding and leveraging the possibilities of an artificial brain with unlimited scalability is a complex task. This white paper splits the explanation of DAIN’s potential into three different interlinked components, examined separately and in detail:
DAIN Ecosystem:
DAIN is created, built, and grown by and for its users. Like theinternet, DAIN users will define what DAIN will become in the future. Users can participate in this ecosystem by playing different roles.
DAIN Solutions:
The business toolbox designed to offer out-of-the-box value to
DAIN users.
It aims to streamline the democratization of AI and enable new business models.
DAIN Platform:
The core underlying infrastructure that enables the ecosystem and the creation of solutions. Its mission is to establish a secure marketplace for computing resources, data and AI models.
DAIN ECOSYSTEM
DAIN is conceptually designed to interact with two kind of users, end users and institutions (private companies or any other kind of institution, such as universities or research centers).
End Users
fuel the computational resources market, sharing the free computing capacity of their devices to cover institutions’ requests for service, receiving a reward (tokens) as payment.
Institutions
make requests for service to the network, consuming its computational resources. Depending on the type of service request, they can be divided into:
Producers:
They create new AI models trained in DAIN using their own data and/or data provided by the network members, paying tokens in exchange for the usage of the required computing resources or data.These solutions can be created only for their own consumption, or they can be exposed in the marketplace at any time to generate new revenue streams.
Consumers:
They directly access the AI marketplace to reuse existing solutions created by Producers.
DAIN SOLUTIONS
As described, DAIN Solutions provide ready-for-use business solutions. This section details the initial set of solutions that will be provided on top of the DAIN platform
- Empathy – Engagement platform
- Knowledger – AI Marketplace
- Soul – Autonomous agents
- Psyche – A Zero-Code Artificial Intelligent Journey Platform
- Intuition – Laboratory
DAIN ECONOMY
DAIN implements different techniques to promote the stability of the utility token and the overall system:
- DAIN token value is referenced by the computing power constituting the network.
- The token has reduced volatility, as the value (not the price) is linked with real and measurable indicators.
- There are clear token value growth drivers.
- Wealth distribution
DAIN Token Value
A DAIN token is directly linked to the computing power of the network. To quantify the network’s computing power, a reference index is defined: DIPS (DAIN Index Performance Standard). Every service request handled by the network can be characterized by a DIPS number, which represents the estimated computing power required to solve it. A DAIN token (DAINT) is defined as the computing capacity allowing the execution of a service request of 1 DIPS, in every active Minimum Resource Cell in the network. 1 DAINT = 1 DIPS x #MRCs To prevent artificial network growth, each MRC requires a DAINT reserve to be considered active and allowed to provide services.
While the price of a specific task is driven by supply and demand, there is a pricing mechanism that links it to the token value, reducing volatility.
Service Fees
Services provided within DAIN have a fee (dsf, DAIN service fee*) paid by the requestor. The purpose of this fee is to reward DAINT holders. The fee is determined as a % of the service price, and the corresponding DAINTs are
“burned” (i.e. no longer circulating in the network). As the total number of DAINTs in the network decreases, the value of the DAINT increases, directly rewarding DAINT holders.
Wealth Distribution
In order to guarantee the network’s survival, it is necessary to ensure that all the participating actors earn a fair reward, avoiding wealth centralization by actors with more capacity or voting power.
This mechanism incentivizes new users to share their computational resources through DAIN, regardless of how big or small the device’s computing capacity is.
The DAIN protocols implement rules designed to ensure that all device types can have equal access to collaborative associations of nodes with heterogeneous characteristics, subsequently ensuring a proportional distribution of the rewards.
Roadmap
We are just beginning, but everything is already mapped out and planned. Learn about our next steps.
2018 Q3
DAIN network conceptualized
2018 Q4
DAIN technical design complete
2019 Q1
Agreement with Universidad Pontificia de Comillas to fund a research project on DAIN
2019 Q2
DainWare funded
White Paper published
Funds raised from 8 angel investors
Advisor Board
2019 Q3
Agreement with SecondWindow to provide development workforce
We are here
2019 Q4
IEO 1.0
Token Private Sale
Telefónica & Eleven Paths LoI sign off
2020 Q1
IEO 2.0 with additional exchanges for extended reach
Research Article Publication
PoC Industrial Use Case
2020 Q2
ICO
2020 Q4
Testnet launch
Concept Demo Release
2021
DainServices set-up
go-to-market service provider and integrator
The DAIN Team
The DAIN team is made up of professionals with extensive experience in startups, entrepreneurship and large multinationals. We also are proud to have the support of collaborators from multiple sectors and the academic world.
José Ramón García Luque
Co-founder & CEO
Cognitive & AI Architect at Sabadell Bank
Luis Garcia San Luis
Co-founder
CIO at Deutsche Bank SAE
Carlos Díaz Conde
Business Development & Strategic Alliances
Jesús García San Luis
CTO
CTO & Founder 8g Analytics
Technology Advisor LossLessLinen
Luis Garcia Lorente
COO
Promptwave founder
(ICEX Innovation award)
Strategic Partner Advisor & Judge @Startup Europe Awards
Andrés Contreras Guillen
Head of Solutions & Services
Research Team
José Luis Gahete Díaz
Professor at Universidad Pontificia Comillas de Madrid ICAI-ICADE
David Contreras Bárcena
Director of the Department of Telematics and Computing at Universidad Pontificia Comillas de Madrid ICAI-ICADE
David Alfaya
Professor in the Department of Applied Mathematics of the ICAI School of Engineering
Alejandro García San Luis
Professor at Universidad Pontificia Comillas de Madrid ICAI-ICADE
Israel Alonso Martínez
Professor at Universidad Pontificia Comillas de Madrid ICAI-ICADE
Advisory Team
Francesc Fajula De Quintana
Director Open Innovation at Banco Sabadell
Roberto Nuñez Del Rio
Founder at Why? Training and HubIT Digital
Marcos De Pedro
CEO at myClouddoor
Covadonga Fernández
Director at Blockchain Observatory
José Salamanca
COO at UST Global España & LATAM
Jorge Alonso
General Director at Second Window
Ricardo Usaola
Regional Vice President - Iberia MuleSoft Sales at Salesforce
Valentin Galan
Channel and Alliance Regional Partner Director at Mulesoft, a Salesforce Company
Juan Boquera
Operations Manager at The Cocktail
Juan Antonio Sánchez Cañibano
Head of Digital Services Sales Specialists
Jorge Aponte
Influencer Blockchain & Crypto | Global Busines Developer
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