Neuromation - 当机器人电动羊的梦

该Neuromation平台将使用与工作令牌blockchain证明革命性AI模式development.The革命沿着分布式计算是姗姗来迟:深度学习采用超大容量的人工神经网络,因此,需要高度精确的标签。采集图像的大型数据集,文字和声音是容易的,但描述和注释的数据,使其可用历来是具有挑战性的和昂贵的。众包应用到数据集创建的问题,并在几年前标注,采用大量的人类,纠正错误,提高精度。事实证明,速度慢,价格昂贵,介绍人为偏差。此外,有任务,人类根本无法做的很好,比如估计对象之间的距离,场景中的量化照明,准确地翻译文本,等等。

代币基本信息

状态
已成功
货币符号
Neuromation
开始日期
2017-10-15
结束日期
2017-11-15
目标上限
200,000 ETH
代币数
700,000,000
官网 Owner of Neuromation?
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基本信息

平台Ethereum
类型未知
接受币种ETH
流通百分比未知
KYC未知
受限地域未知
网站首页链接
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折扣信息

  • First week - 15%
  • Second week - 10%
  • Third week - 5%
  • Fourth week - 1%

项目介绍

The Neuromation Platform will use distributed computing along with blockchain proof of work tokens to revolutionize AI model development.


The revolution is long overdue: deep learning employs artificial neural networks of extremely large capacitance and, therefore, requires highly accurate labeling. Collecting large datasets of images, text and sound is easy, but describing and annotating data to make it usable has traditionally been challenging and costly. Crowdsourcing was applied to the problem of dataset creation and labeling a few years ago, employing large numbers of humans to correct mistakes and improve accuracy. It proved slow, expensive and introduced human bias. Besides, there were tasks that humans simply could not do well, such as estimating distances between objects, quantifying lighting in a scene, accurately translating text, and so on.

We propose a solution whose accuracy is guaranteed by construction: synthesizing large datasets along with perfectly accurate labels. The benefits of synthetic data are manifold. It is fast to synthesize and render, perfectly accurate, tailored for the task at hand, and can be modified to improve the model and training itself. It is important to note that real data with accurate labels is still required for evaluating models trained on synthetic data, in order to guarantee acceptable performance at inference time. However, the amount of validation data required is orders of magnitude smaller than training data!

团队介绍 查看全部

Maxim Prasolov
Maxim Prasolov
CEO
Fedor Savchenko
Fedor Savchenko
СTO
Sergey Nikolenko
Sergey Nikolenko
Chief Research Officer
Andrew Rabinovich
Andrew Rabinovich
Advisor
David Orban
David Orban
Advisor
Constantine Goltsev
Constantine Goltsev
Investor / Chairman