DApp of the Week #04 — Cerebrum

Wassim Bendella
Aug 6, 2018 · 3 min read

Our new series labelled “DApp of the Week” regularly features the most innovative applications built on top of iExec, to showcase what can be achieved with the tools and librairies we have developed, and how you can already launch decentralized applications running on a decentralized cloud.

The DApp of the Week is Cerebrum, and has been created by Salman Rahim.

A decentralized platform for crowdsourced machine learning

In the last years, established IT giants like Google, IBM, and Nvidia — fueled by the abundance of data, algorithmic advances, and the usage of high-performance hard­ware for parallel processing — have begun bridging the gap between science and busi­ness applications.

The global market for AI-based services, software, and hardware is expected to grow at an astonishing annual rate of 15 to 25% and reach $130 billion by 2025. Most of the investment in AI consists of internal R&D spending by large, cash-rich digital-native companies like Amazon, Baidu, and Google, which raises an imminent danger in today’s society:

The overarching solution to these problems is to create AI that is:

This decentralized artificial intelligence (DAI) offers a unique proposition that no other AI can offer: the democratization of AI.

“Our mission is to build the world’s first decentralized platform for crowdsourced machine learning that enables prediction modeling on encrypted data.” — Cerebrum

Source: Blutgruppe/Corbis

Lots of data + machine learning experts + blockchain

Cerebrum tackles the democratization of AI by harnessing the same components driving the supremacy of existing centralized AI juggernauts: lots of data and AI research talent.

Cerebrum is the world’s first decentralized platform for crowdsourced machine learning. It enables anyone to encrypt their data and host machine learning competitions to utilize the collective intelligence of models created by the world’s largest community of machine learning experts without sacrificing data privacy.

Moreover, Cerebrum will promote machine learning competitions on open datasets to collect the world’s largest library of the most optimal intelligent agents for solving particular goals. Anyone will be able to use these agents with their own encrypted data to create multi-agent systems that solve complex tasks.

Cerebrum implements blockchain technology to generate distributed, decentralized artificial intelligence by creating an open, competitive platform that aligns incentives between those wishing to gain predictive power from their data and scientists seeking to monetize their machine learning skills.

Powered by iExec: MARIA — Artificial Intelligence Research Assitant for Medicine

MARIA is an application that allows physicians and researchers to create machine learning competitions that are facilitated by smart contracts on a private Ethereum blockchain and IPFS for data sharing.

The goal is to show that physicians can use crowdsourced machine learning on medical data to make clinical decisions without sacrificing patients’ data privacy.

MARIA is part of Cerebrum’s Alpha 1.0, and below is a video that guides you from creating an ML competition on the platform to selecting a winner. The evaluation of participants’ models is performed using iExec’s decentralized cloud.

Now, Cerebrum have started a pivot to their stage 2 of development, in order to create the AI platform that will run competing ML models on iExec and create a marketplace for them. This marketplace is scheduled for the end of Q4 2018.


[1] Cerebrum (2018) MARIA — Artificial Intelligence Research Assitant for Medicine

[2] Salman Rahim (2017) Announcing the Simple Mind Alpha

[3] Salman Rahim (2017) Decentralized Platform for Crowdsourced Machine Learning

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Blockchain-based Decentralized Cloud

Wassim Bendella

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Wassim Bendella is a business developer at iExec, a blockchain startup decentralizing the cloud market (previously at Shell and Cointelegraph).


Blockchain-based Decentralized Cloud