Decentralized infrastructure for copyright of data used by Gen AI and fair distribution of value.

Why is copyright a main issue for Gen AI?

Contamination

The results they deliver cannot be compliant, contaminating the entire downstream data set in which they are used.

Sustainability

As all the stakeholders in the value-creation chain cannot be identified, it is not possible to distribute the value to enable a sustainable ecosystem.

Legal anticipation

Data Act regulation in EU/World will make compliance challenges for AI provider and users even more difficult than they currently are.

To address these issues, we offer 4 services.

Pooling decentralized ressources​

We propose smart contracts and front-end features to enable crowdsourcing of resources (financial and data) organized into projects, each of which can be governed by its contributors like a DAO.

Aggregate data in a fine-tuned AI

For each of this project we propose to create a fine-tuned AI. A fine-tuned AI is an AI model trained on a specific field of data that can interoperate with other, more general AIs (this is called embedding). So it’s not a question of having a broad knowledge base to cover all subjects, but rather of creating deep, subject-specific knowledge bases. 

Provide licencing for Gen AI results​

So that the end-user of a third-party AI can be sure of the compliance of the results generated, we offer license tokens that enable all the fine-tuned AI and data used to be traced, so that they can be remunerated.

Provide a SDK for Gen AI provider​

In order to enable a growing number of AIs to integrate this architecture and this standard for data tracing and value distribution, we are providing AI providers with an SDK enabling them to integrate it into each of their models.

Would you like to find out more about Lay3rs?

Read all about it in our whitepaper.

First use cases

A platform for creating AI-powered digital twins of historical monuments.

In order to develop and improve our model and technology, we set up strategic partnerships enabling us to develop our first use cases. The first is a platform dedicated to the creation of digital twins of the world’s most beautiful monuments. Currently available in testnet with our PLAY token, it enables people to collectively contribute and participate in the aggregation of heterogeneous data into AI-generated 3D digital twins.

Discover Build3rs!

Why should I care?

Get involved and become an actor into the preservation of monuments, natural sites, flora, fauna, know-how and fictional environments.

How can I get involved?

Join a digital twin project by contributing to its creation or evolution and become its curator. Decide on its developments and be rewarded for your contribution.

They support Build3rs

Digital twin

Digital twin : A set of data relating to a subject to be preserved, aggregated by AI into a 3D scene (an expert model). This is a dynamic set (evolving over time) of heterogeneous content (images, archives, reference 3D models, exports, acoustic map, semantic slicing, etc.) assembled in such a way as to be interpreted and used by other AIs, and to enable the generation of exports.


Export : A selection of data (e.g. a 3D model) optimized for a specific use (AR / VR / Unity / Unreal / Voxel, etc.). These exports can concern the entire subject or a specific part of it (work of art, architectural element, texture, etc.) and can be distributed on our platform and on various asset stores.

  • To equip researchers and architects in their preservation and renovation missions.
  • To visit a monument remotly or beyond the limits of time.
  • To serve as virtual studio sets or special effects for the creation of films, TV programs, advertisements or virtual events.
  • To anchor video games environment or metaverse in a specific context.
  • To create material reproductions (e.g. a 3D printing) of a subject or parts of it.
  • To support new forms of digital and immersive art.
  • To support all services located indoors or outdoors (with or without GPS signal).
  • To be embedded in a third party Gen AI to be use to generate results (text, images, videos, etc.)

And the best use cases have yet to be invented…

Enhanced archive

To keep a rich record of what is valuable and fragile by aggregating a large smart set of data on a specific heritage element.

 

Augmented mediation

To give the public a richer, more diversified, more personalized and more sustainable access to knowledge on a subject.

 

Economic model

To create a virtuous economic model specific to the twin, allowing to finance the preservation of the real heritage.

 

Support creation

To provide operational means for creators to reinterpret reality and history in new creative environments (VR, AR, Virtual Studios, metavers, etc.).

 

Emerging innovation

To propose a bottom-up innovation model to heritage institutions that creates a bridge between creators and them.

New environments of creation (XR) represent huge opportunities to invent new ways of promoting and broadcasting culture BUT production of a digital twin remains a very manual work process, very long, expensive, not very resilient (one capture for one output) and only based on visual perception.

In 2021, the European Union asked its member states to create 16 million digital twins of monuments by 2030. How to make this recommendation realistic without impoverishing it ? Lay3rs collaborates with research laboratories (CEA, ULB, Ecole Polytechnique) to develop new solutions to make this process more intelligent and able to fully exploit all existing data.

The use of AI to aggregate existing data and extrapolate missing data radically changes the way digital twins are produced. Where previously it was necessary to make in-situ captures for each new model, it is now possible to aggregate all types of data into a single 3D scene, recycle all existing data and generate the missing data, all for a realistic result. In the Build3rs case, we use computer vision (SLAM) and artificial intelligence (NeRF & Gaussian Splatting) algorithms.

In addition to their use for the renovation or scientific study of a subject, when contributors invest in the creation of a twin, in the acquisition of new data, part of these funds are donated to the institution in charge of preserving the real subject. In time, the portion allocated to them by the DAO from the sale of licenses to exploit the exports will constitute a new channel of regular income for the latter.

What's next?

We are planning the development of several platforms dedicated to specific types of heritage and their specific user communities. Thus, it becomes possible to continuously expand the use cases of the LAY currency, to contribute to the preservation of an increasing variety of heritage subjects and to respond more specifically to technical specificities linked to intrinsic characteristics of subjects.

DREAM3RS

Digital twins of fictional fragmented environments to generate global thematic environments

SUPPORT3RS

Most emblematic sports sites and events giving them a new posterity.​

EXPLOR3RS

Places, Minerals, Flora and Fauna including the most beautiful natural sites and their components to procedurally generate evolving environments. 

CRAFT3RS

Gestures and know-how to create digital beings capable of interacting and modifying their virtual environment.​

LAY token

Utilities

What is LAY?

LAY is an utility ERC-20 token for all services and platforms offered by LAY3RS. While the token will be available to the public Q1 2024, a tesnet called PLAY (Prototype du LAY) is already available on the Build3rs.io platform.

 

Total supply : 1 000 000 000 LAY

Technology : Polygon

By assigning to each set of raw data (ERC-721) and to each export (ERC-1155), it becomes possible to manage complex rights structures and to pay fairly (over the entire value chain) and transparently for the various revenues generated by the distribution of exports.

Other tokens

LAY3RS supporting Partners

Roadmap

Initial partnership with CEA List
July 21
Winner of the Future Investment Plan - France 2030
September 22

Matrice (Social & Technological Institute) presents the project to create an ad-hoc structure to develop Lay3rs services.

Company creation
November 22
Build3rs Alpha Launching
July 23
Build3rs Public Launching
September 23
PLAY (Prototype of LAY) Tesnet Launching
September 23
DAO Features
October 23
Assets Marketplace features
December 23
Automation of export creation from API (to include in SDK)
January 24
Smart contract audit validated
February 24
Data Hunting Features
March 24
Launch of digital twin incubation program
March 24
LAY Token Generation Event
April 24
On-ramp integrated in app
May 24
Second internal use case (Announced soon)
July 24
Implementation of ERC-1137 standard to pay in LAY through subscriptions
July 24
Framework to retrieve data from 3rd parties, and qualify to its Lay3rs datasets
September 24
Integration of smart wallets feature
August 24
Digital twins library Desktop tool
October 24
SDK distribution using API key payable in FIAT
October 24
SDK distribution using API key payable in LAY
December 24
SaaS service payable in LAY that generates exports based on AI trained on datasets
January 25

Team

Yann Toullec

CEO

Benjamin Jornet

CTO

Sébastien Malcotti

CIO

Xavier Aubert

CRO

AJ Dinger

Head of Business Development

Mateusz Baranowski

Lead community manager

Rebecca Cervasio

AI Researcher 

Victoriya Kashtanova

AI Researcher

Sébastien Casaert

Head of Product

Zhong Qiang

Commercial manager

Marisol

Community manager

Mathieu Da Silva

Communication

François-Xavier Petit

Public Partnership Advisor

Emmanuel Ea

Development Advisor

Adrien Basdevant

Web3 Legal Advisor

Location