KYC passing required No | Whitelist No | Restriction for countries No
|Price||1 Neuromation = 0.001 ETH|
Neuromation search trends in Google
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1. The Neuromation NeuroToken (NTK) White Paper (hereinafter “the White Paper” or “the Document”) is
presented for informational purposes only.
2. Nothing in the Document shall be construed as an offer to sell or buy securities in any jurisdiction, a
solicitation for investment, or investment advice. The Document does not regulate any sale and purchase of the
NeuroToken (NTK; as referred to in the White Paper). The sale and purchase of the NeuroToken (NTK) is
governed by the Terms and Conditions.
3. Several estimates, phrases, and conclusions incorporated in the White Paper constitute forward-looking
statements. Such statements or information concern matters that involve uncertainties and risks, which may
result in material differences from the results anticipated.
4. The White Paper may be updated or altered...
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2. Neuromation Platform
3. Neuromation Platform Pillars
a. Neural Networks & Deep Learning
b. Synthetic Data
c. Distributed Computing
Machine Learning Models
4. Domains of Applications
6. Neuromation Business Model
7. Road Map
8. Token Sale
9. Token Economics
Artificial Intelligence (AI) is seeing another spring and becoming a ubiquitous
part of society. Researchers and engineers have made important steps towards
solving practical problems in machine learning, particularly in such applications
as vision, speech, machine translation, and decision making.
Due to technological advancements coupled with progress in research and
innovation, AI is quickly becoming a part of every company’s operations. This
progress brings its own challenges, such as supply of sufficient talent,
resources, and data. The most pressing problem is the availability of
well-labeled data to support the supervised learning process. Even when
unstructured data is abundant, converting it to a labeled dataset is an extremely
laborious and costly process. There is a need to address the challenges of
practical AI adoption wholesale -- on a platform level. Until this is done, most
businesses will be struggling to adopt AI. Due to the disparity in r...
The AI ecosystem is founded on three pillars:
Datasets – large datasets of structured (or unstructured) data used for deep
learning algorithms to learn a specific task.
Computing power – a standalone server or a farm of interconnected GPUs
designed to provide the necessary framework for training AI models with
existing datasets to achieve the objective.
Machine learning models – a set of algorithms designed to process datasets
in the Neuromation platform environment.
Each of these domains poses a unique set of challenges for both the supply and
demand side of the AI ecosystem.
Neuromation offers a new and effective
approach of connecting supply and demand for each of these domains in a
marketplace, bringing together the competencies of researchers, engineers, and
designers and connecting them with commercial sector companies.
We are building
a critical component of the budding AI ecosystem and plan to
capitalize on the first-mover advantage: The Neuromation platform provides an
exchange and ecosystem where participants can either contribute to or purchase
the components of an AI model.
The Neuromation platform will use distributed computing along with blockchain
proof-of-work tokens to revolutionize AI model development. It will combine all the
components necessary to build deep learning solutions with synthetic data in one
place. Platform service providers, commercial or private, will provide specific
resources for the execution and development of synthetic datasets, distributed
computing services, and machine learning models, addressing the “three pillars”
of AI in the previous slide. Each executed service (dataset generation or model
computation) or data piece sold (dataset or data generator) is associated with a
reward, numerated in our currency, the NeuroToken...
Platform Elements Overview
The Neuromation platform will combine technological and business elements to
efficiently train large-scale deep learning systems on synthetic data.
Platform user experience is divided into the following categories:
Create a data generator
Order dataset from the
Request data labeling
A repository of datasets
for deep learning
A repository of data
Define deep learning
Import the model (e.g.,
clone TensorFlow code)
Order training on
Request a custom
model from the
A repository of deep
Platform Elements Overview
The platform’s backend technology is divided into the following components:
Node analysis (Processing price
floor — minimum amount in
NeuroTokens accepted per
computing unit. Node efficiency
limit based on
Distributed data generation package
Distributed learning package
Node synchronization middleware
Enables efficient matching of
buying and selling orders for
datasets, models, and labeling
Enables liquidity in the system so
that prices across the assets are
conducive to scaling the system
Seed round completed. Work started
Launch of R&D in Retail Lab test synthetic data hypothesis
Proof of hypothesis on synthetic data is finished. Retail synthetic data generator proven. Model development complete (95% of accuracy reached.). Marketing and first sales to retail clients. ICO preparation.
Neuromation ICO. Neuromation platform v1. Launched with 1,000 GPU capacity deployed. Medical devices Lab started.
Active sales and marketing of Neuromation platform. Neuro Tokens are tradable on exchanges. Industrial automation Lab is started.
Neuromation platform v2. Launched with 10,000 GPU capacity deployed.
Neuro Token will migrate to its own blockchain. Neuromation platform v3. Launched with 100,000 GPU capacity deployed.