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A thread on Dbrain by @dbrainio , the platform that triggers the burgeoning adoption of Artificial Intelligence (AI).

If AI is a gun, Dbrain is the trigger.

1- AI is a field in computer science that enables softwares, machines, computers to act and think the way human does. It can’t achieve this without the help of humans currently. The process by which an AI program learns are in phases.
2- The dataset it learns from are gotten from various source, the datasets are now trained and retrained until a best fit is achieved. It’s inevitable for humans to be excluded from dataset gathering or training at the moment as we are still in the early stages of AI

#tech, #AI
3- From the above analogy, the quality of the labelled dataset would be inefficient because humans (prone to mistakes) play a crucial role in the process. It also creates a lot of friction and insecurity of the data source during the training process.
4- This is what motivated the evolution of a project called Dbrain by @dbrainio . Dbrain is an open blockchain platform that links data owners, crowdworkers (data labellers), data scientists and businesses enabling them to transform raw data into real-world AI solutions.
5- The four major bodies that make up Dbrain’s platform are Data owners, Crowdworkers, Data scientists and businesses.

Data owners are the category of people that provides the data that needs to be labelled, validated and trained.
6- Crowdworkers retrieve the raw data from the “Data owners” and do simple tasks of data labelling and validation, and are paid instantly in DBR token for their work.
7- Data scientists use the resulting datasets from the “Crowd workers” to train Neural Networks and build AI apps.

Businesses use existing AI solutions or specify new ones to serve their particular needs
8- A question that might be going through your mind is how does Dbrain fight against data loss, data insecurity and data breach. Another question would be how are labelled data validated and verified to be correct?
9- There are two protocols that answers the questions above, the protocols are also used to power the entire production cycle in Dbrain, they are SPOCK protocol and the PICARD protocol.
10- SPOCK (Subjective Proof of Crowdwork Protocol): verifies the quality of the labelled data by selecting only the results with a higher level of trust/validation from random validators. The original worker then receives a payment and a higher rating.
11- Validators that approve a bad result are punished with a significant drop in rating.

Since the workers and validators do their best to ensure that their rating is not compromised, a nash equilibrium is established and the system becomes self-sustaining. Legendary!
12- PICARD (Protocol for Indirect Access to Repository Data): protects datasets and AI applications hosted on the Dbrain platform and allows data scientists to train AI models using the datasets without downloading them, only if the data owner permits.
13- PICARD also allows the owners of existing data and models and new developers can agree on revenue sharing from the resulting product.
14- @dbrainio didn’t just randomly picked up the idea, they ferreted across various projects, found the problems and provide an innovative solution to the problems.
In existing systems, developers need to find raw data and upload tasks or validate data themselves.
15- Then developers need access to AI compute infrastructure in order to train models and build AI Apps. Finally, developers need to deploy AI Apps somewhere to make them available to business clients.
16- The Dbrain platform covers all stages of the AI production cycle and offers a
comprehensive solution

Dbrain platform can be used in image recognition, video surveillance, medical data processing, natural language processing and lots more. It cuts across diverse field of AI.
17- If you are an AI fan, then hop into the @dbrainio because it’s would take AI to unprecedented levels.

Thanks for reading. A big shout out to @stskeeps for the heads up on this project.
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