The cost of training AI models has risen by an average of 260% annually since 2016, with expenses expected to continue increasing as models advance.
Decentralized AI training spreads the workload across a distributed network, offering businesses the potential for enhanced efficiency and cost savings. But what exactly is decentralized AI training, and what dataset providers are best? Let’s explore below.
What is Decentralized AI Training?
Decentralized AI training refers to the process of training AI models using a distributed network of devices or nodes instead of centralized servers or data centers. The blockchain (a public and unalterable record of transactions) is used to track/validate data, ensuring its accuracy and traceability. It also assists in data processing, ensuring an equal contribution between nodes.
The advantages of decentralized AI training are numerous. While these systems can be more complex, they give data providers better control over their information, enabling them to dictate how it’s used or sold. Because data is encrypted and fragmented across an extensive network, decentralized AI (DeAI) systems are much more challenging to exploit. Moreover, these systems are flexible and can be scaled efficiently as demand increases or wanes.
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Discover the Best Dataset Providers for Decentralized AI Training
Choosing a dataset provider is crucial for any business or individual building an AI model. While centralized platforms exist, decentralized alternatives offer many benefits surrounding privacy, cost, and self-sovereignty. Some of the best DeAI dataset providers include:
1) OORT – A Leading Cloud for Decentralized AI Infrastructure
OORT is an innovative decentralized AI infrastructure ecosystem that offers video, audio, and text datasets through its OORT DataHub segment, in addition to storage and compute services. It lets data providers earn rewards for contributing and provides a convenient way for businesses to access high-quality, verified data representative of real-world scenarios they can use to train AI models.
Source: OORT DataHub
Unlike other dataset platforms, OORT offers a comprehensive suite of infrastructure supporting developers through model training and deployment. It leverages the blockchain to ensure transparency throughout the data collection and labeling process. Its implementation of the Proof-of-Honesty consensus mechanism utilizes human input to maintain data quality.
A notable advantage of OORT DataHub is its focus on AI workloads. The data collection and labeling process is tailored to AI model training, making it particularly valuable for decentralized AI applications. With over 200,000 contributors, OORT’s datasets are diverse and actionable. Moreover, developers/businesses can create custom data-gathering campaigns, which is helpful for tailoring AI models to specific needs.
OORT’s approach to data, focusing on diverse, high-quality datasets with real-world uses, makes the project particularly valuable for developers and researchers creating innovative or complex models for AI applications. Similarly, businesses requiring custom data for AI projects can benefit from OORT’s reach and campaign creation system.
2) Ocean Protocol – Privacy-Focused AI Dataset Marketplace
Ocean Protocol facilitates the secure exchange of datasets used in decentralized AI applications. The project utilizes an innovative system to enable the training of AI models on private data without sacrificing provider privacy. Ocean Protocol also pairs providers and developers via its expansive marketplace, which hosts over 1,300 datasets.
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Source: Ocean Protocol
Ocean Protocol leverages the blockchain to pair providers and developers securely and privately. Data providers retain full ownership and control, while developers can train models without exposing the underlying data, ensuring integrity. Providers can create data NFTs to encrypt and store information, which they can then use to generate licensable datatokens.
The main advantage of Ocean Protocol is its focus on user control and privacy. While some competitors offer providers little control over the data they’ve gathered, Ocean Protocol shifts control to its users. It gives them multiple ways to earn from their data. Additionally, the decentralized marketplace makes it easy to browse and access datasets, which is convenient for quickly finding datasets relevant to a specific purpose.
Due to Ocean Protocol’s focus on users, the platform offers substantial benefits to data owners/providers wishing to monetize their datasets in a secure and transparent way without exposing them. The project prioritizing privacy also makes it valuable in industries dealing with sensitive information and requiring AI models, like healthcare or finance.
3) Sahara AI – Upcoming Platform for Creating and Monetizing AI Datasets
Sahara AI is an upcoming decentralized AI platform that enables people to monetize their datasets while allowing developers to leverage them for AI model training. While the Sahara decentralized AI blockchain is still in its testnet phase, developers can apply for early access to the platform. Sahara aims to foster a collaborative data environment, providing an alternative to traditional systems that benefit one party unequally.
Source: Sahara AI
The main feature setting Sahara AI apart from traditional dataset providers is its focus on self-sovereignty. Data providers gain verifiable ownership and control over how businesses use their datasets. The project’s blockchain integration and focus on users have also created an ecosystem that prioritizes privacy and security for providers and developers alike.
Sahara AI utilizes pay-as-you-go models, granting businesses access to data as their demands require. The project is highly scalable and reliable, making it a strong choice for applications where exact requirements are not yet defined or are subject to change. Its focus on collaborative development helps to ensure fairness when participating in Sahara AI’s ecosystem.
With an equal focus on the users providing resources and the developers leveraging them for applications, Sahara AI is a robust platform well-suited to those seeking a collaborative environment. Although it’s still in early access, Sahara AI raised $43 million and seems poised to become a key player in the AI dataset space.
4) Streamr Network – Marketplace Specializing in Real-Time Datasets
Steamr is a unique decentralized dataset provider. Instead of gathering data by sending out questionnaires or collating existing datasets, Streamr focuses on real-time data sharing and monetization. Real-time data refers to continuously updating information streams, like weather, energy/utility consumption, and stock prices.
Source: Streamr
Steamr leverages the blockchain to create its network of data providers and keep data secure and private. Nodes on the network collaborate and route data from providers (publishers) to consumers (subscribers). The Steamr Network is open source, and the project’s team designed it in a way that facilitates interoperability between other blockchains and applications.
Unlike centralized systems, Steamr enables serverless, real-time data sharing, which offers superior accessibility. Moreover, the project’s use of the blockchain provides it with inherent security and censorship resistance. As Streamr eliminates intermediary services, it can also offer cost savings compared to traditional systems.
Steamr is well-suited to people with access to real-time data and a wish to monetize it. Likewise, it benefits businesses requiring efficient access to continuously updated data streams. More specifically, the project’s focus on real-time data renders it particularly useful for Internet of Things (IoT) applications, while marketplaces can sell data from Steeamr to their clients.
Final Thoughts
Decentralized AI training refers to the process of training AI models via a distributed network called the blockchain. It offers advantages over traditional systems, like enhanced privacy, flexibility, and user control. Businesses can also benefit from cost savings and the ability to quickly scale as needed. However, high-quality dataset providers are required for a company to feel these advantages.
Each data provider we’ve discussed has carved out a well-deserved place in the industry. While it’s advisable to choose the platform that best fulfills your individual requirements, OORT stands out as the most robust and comprehensive. It provides a complete suite of AI infrastructure, catering to data collection activities as well as storage and computing needs, making it more versatile than competitors.