Bottos — A decentralized AI data sharing network.

Written by community member SAP Polymorphism

The Bottos project is the first of its kind in that it aims to address the two major pains that currently impact the AI industry’s progression. The Bottos project will be comprised of two developmental stages. The first stage will focus on building a beta marketplace for AI companies to acquire specified high quality, low cost training data for their AI models to mature. Currently, unless you are a big data titan, such as: Google, Amazon, or Facebook, it is difficult to finance and scour such necessary data. Due to this reason, small and medium enterprises, research institutions, and all other entities in need of AI training data cannot proceed in the completion of their models.
Bottos aims to address the impedance that plagues the global progression of AI advancement. Secondly, the development of an AI model marketplace to facilitate their distribution by AI companies will be completed. Whenever companies develop their AI models, Bottos will be the go to place to mature such models using the data that is: acquired, tagged, and cleaned by the Bottos ecosystem. Additionally, the Bottos ecosystem can again be utilized to distribute said models to potential clientele. Bottos, at the highest level, is poised to bring big data and AI to the world.

Bottos Team Experience and Composition

The composition of the Bottos team is one of the strongest in the current AI blockchain space. As of today, the team stands 20 people strong; 12 of whom are developers, all full-time and hailing from Wanxiang Blockchain Lab, a leading Chinese blockchain R&D lab, each with 10+ years of blockchain experience.

Xin Song is the CEO of Bottos. Song previously worked for multinational fortune 500 companies in the U.S. and Europe, such as Liberty Mutual, Accenture, and also headed the Droege Group in China. Song holds an MBA from Georgetown University, a top US private university, and a BS in management information systems from the Shanghai University of Finance and Economics. Song has 13 years of experience related to high technology investing, corporate strategy, and digital transformation.

Tingting Wang is the chief marketing officer of Bottos. She has a proven track record of success as she was formerly the vice president of NEO (currently at 8.9 billion USD in market cap) who headed their marketing and community management. Wang holds a B.S. in computer science from Huazhong University of Science and Technology, and a B.S. in project management from Wuah University. She also founded a robot exoskeleton R&D company, and has remained relevant in the AI and blockchain space.

Chao Wang, the CTO of Bottos, has 14 years of experience in product development. Wang headed the Wanxiang Blockchain Lab as the R&D director prior to joining Bottos, and was the domain architect for global Telecom leader, Huawei. Wang possesses more than 14 years of R&D experience in telecom, cloud computing, and distributed systems. Wang is also the decision-making committee member of the 5G mobile communication organization of China. Wang holds a M.S. in computer science from the Hefei University of Technology.

Zhen Gao, the chief scientist and AI architect of Bottos, is a leader in the space of machine learning, AI modeling, and autonomous systems. Gao is the editor in chief of two AI and robotics journals, and has published over 100 journal and conference papers relating to the subject. Gao is also a professor in the W Booth School of Engineering Practice and Technology for McMaster University in Ontario, Canada.

The Bottos team in its entirety is well composed based on experience and with a proven track record. Breaking down the team into their components: Wang (CMO) has the combined marketing and community management experience of NEO, Song (CEO) has led in strategy and investing direction for top fortune 500 companies, Wang (CTO) has nearly 1.5 decades of R&D experience in cloud computing, telecom, and distributed systems, and Gao (Chief Scientist/AI Architect) who has spent the majority of the latter half of his life devoted to the topics of AI and autonomous systems.

The Bottos AI Ecosystem Protocol

The volume and complexity of a required dataset to train AI models usually depends on the number of sought after parameters. Facial recognition models can sometimes require up to tens of thousands of iterations of 150 photographs per face, each at different angles. That being said, data acquisition for AI model training is a lengthy process when taking into considering the life journey of each data point, from origin to destination. Firstly, data is produced. Secondly, the data must be tagged for specificity, and cleaned to assure the necessary quality of data. The traditional route to achieve this tagging and cleaning process is to hire a company or group of people, but this has proven to be expensive, inefficient, and there is also the concern of the security of data. Finally, the data is ready for purchase and consumption by AI models. Each stage of a data point’s life journey is addressed by the Bottos system protocol, which will be detailed below.
 The users of Bottos’ AI marketplace are classified into three categories: data providers, data requesters, and data validators. Each of the three play an important role in maintaining the ecosystem of the Bottos blockchain. Data requesters are any entity seeking training data sets for their AI models, namely, AI companies (SMEs, research institutions, etc). Data requesters use BTO to pay for the services of the data providers and data validators. Data providers are users of the ecosystem that will be producing the data to be purchased as an asset by data requesters. Additionally, data providers will also be incentivized to participate in data cleaning and tagging. This entire process of data providers is described as the data mining mechanism of the Bottos protocol. Data validators are the third group of users of the ecosystem who are responsible for ensuring appropriate quality of data. The amount of BTO rewarded for data validators and providers will be based on their credit score, which is a quality of work assurance mechanism imposed by the Bottos system. Upon each successful completion of the verification or providing of data, credit is awarded, and the history of each users credit will be reflected on the immutable Bottos blockchain for quality assurance. The figure below shows how each role will interact with each other in the Bottos ecosystem.

Additionally, security of data is achieved through the blockchain implementation of the ecosystem, which immediately resolves one of the two major pains of the AI industry (data acquisition and security). Data will be transacted through the blockchain, and only ever accessed by users employed by a data acquisition, cleaning, or tagging job, thus why Bottos’ solution offers a secure approach to exchange data. Bottos does not own any of the data that is transacted through their platform because data requesters deal directly with data providers and validators. Currently, the beta V1.0 of the marketplace, which provide the basic functionalities of data providers and requesters excluding validators, is available through Bottos’ Github at this link: A Mac OS X version is also available, however one must contact the Bottos team through email at so that they may receive the download. V2.0 will bring full functionalities of all three user types, and a more detailed report of the technical aspects of development will be outlined in the month of March.

Partnerships and Their Synergy

Bottos was originally a startup incubated by ARM Innovation Ecosystem Accelerator (ARM). ARM is an incubation and acceleration platform that provides technological development services such as technical consulting, laboratorial services, market and brand promotion, and technical advising. Arm positions itself for the future as the leading AI company and ecosystem. Mutual benefits exist within the partnership between Bottos and ARM. The Bottos ecosystem will require a large user base of data providers, requesters, and validators. In addition to being incubated by ARM’s Accelerator program, Bottos joined ARM’s AI Consulting group, which is comprised of over 100 members from the biggest AI companies, all of which are now working to further foster each other’s growth. It is exactly these types of AI companies that will seek the services that Bottos’ platform will offer.

The ARM AI Consulting group was established to facilitate the assimilation of AI into businesses in all industries, and Bottos fits perfectly into the group, addressing the major pains of the AI industry with its business proposal. Having the data as an asset marketplace being implemented on the blockchain awards security for all data transactions. The data mining and validating mechanism imposed by the Bottos system alleviates the financial and logistical burdens that once made AI model training unfeasible. Finally, working closely with ARM has gained Bottos much exposure in the Chinese market. The Chinese Bottos community is considerably larger than the still developing Western community, boasting over 100,000 people in count.
 Another strategic partnership in place is the alliance with the Draper Dragon Fund (DDF). CEO, Xin Song, has publicly mentioned on a Youtube interview with Crypto Brahma this past week that, DDF has invested into the Bottos project back in December of last year. The DDF is known to be invested into a number of top AI companies — companies of which that can utilize the data acquisition, tagging, and cleaning services found through Bottos’ future AI marketplace. Both the ARM AI Consulting group and DDF contribute valuable networking with numerous other leading AI companies that are no more immune to the pains of data acquisition logistics. Bottos has positioned itself to enjoy a potential clientele base in which no competition for such clientele exist, giving them full share of the market.


Bottos is a two part AI ecosystem in development that aims to service the entire AI industry by solving the two major pain points currently hindering global AI progress. Firstly, Bottos aims to develop an AI data marketplace to bridge the gap between AI developers in need of training data sets and the raw data itself. Data mining describes the process of data production, tagging, and cleaning to bring it to a consumable state for AI models. Secondly, the Bottos system will add AI model distribution to the AI data marketplace. This secondary marketplace will give access to entities in need of AI models who may otherwise not have the resources to implement it themselves.

The Bottos AI marketplace is the first of its kind and there are no direct competitors in the space. All other AI projects follow the model of combining AI with the blockchain. Bottos encompasses not only AI and the blockchain, but also Big Data. Amazon’s Data Marketplace is another similar project in that it offers similar aspects of the data mining mechanism within the Bottos protocol, however they are centralized by design and does not offer the security or immutable data structure benefits as the blockchain does.

Use Cases

The Bottos project is extensive in its use cases, ranging from: AI, IOT, robotics, semantic identification, computer vision, speech recognition, and personal data as intellectual property. The AI model and data as an asset marketplace caters to a wide spectrum of particular training datasets needed to train all walks of AI modeling.

1. AI — AI development necessitates the acquisition of vast, high quality, training datasets in order to mature and test AI models. AI developers will be able to act as data requesters in the Bottos system, specifying the requirements of data, then finally purchasing the finalized data through the services of data providers and validators. BTO tokens will be used to pay for such services. Moreover, AI companies will be able to issue their own tokens through BTO on the Bottos blockchain, which is a feature that will be available after the Mainnet release which is scheduled for this May — the month in which V3.0 of the marketplace will be launched.

2. IOT — Traceability of data transactions is paramount in the regulation of communication between devices and transaction of such data. All data movement on the Bottos blockchain can be backtracked all the way back to the genesis block, as this is an attribute of the blockchain.

3. Robots — The furthest development of robots thus far has not passed the stage of simple AI algorithm integration with physical shells. For robots to reach a higher cognitive functional state with sensing abilities and flexible physical capabilities, much larger volumes of high quality data is required to train the desired higher functionalities. Eventually, suits with the ability to mobilize paralyzed humans, for example, will be feasible once the necessary datasets become available through the Bottos ecosystem. Finally, to prevent the misuse of AI models and algorithms by malicious entities, the transaction of such software will be secured by preventing access from entities residing outside the blockchain.

4. Semantic Identification — Current challenges in semantic identification involve natural language understanding and natural language generation. These pursuits in semantic identification in AI development require a wide spectrum of unique linguistic circumstances. Bottos’ data mining mechanism will include data to support this type of training dataset requirement.

5. Computer Vision — Computer visual detecting development has reached a bottleneck due to the unavailability of consistent and high quality photographs that aren’t over or underexposed. The Bottos ecosystem offers a solution to this Goldilocks nature of visual data quality requirement. All logistics of data production and processing will be efficiently handled by the Bottos protocol.

6. Speech Recognition — Accuracy of speech recognition sits at about 95% accuracy today. Improving this percentage to 99.9% will be the optimum functionality of AI speech recognition. To achieve this, two major pain points of training data related to speech recognition will be resolved through the utilization of the Bottos ecosystem. The cocktail party problem describes AI’s current inability to differentiate background noise with select noise in an audio data file. Extensive cleaning of data is required, and Bottos’ data validators perfectly fill this need. The second issue lies with extraction of language features. In this case, data requesters can utilize the data requester quality specification functionality to tailor the training dataset to a point of usability, where otherwise would be too expensive to achieve.

7. Personal Data as an Asset — Personal data in any form can be stored, recorded, and secured on the Bottos blockchain and be classified as intellectual property.

Where can one purchase BTO tokens?

Bibox exchange is your best bet in purchasing these tokens. Bibox has good reviews all around, their support team is extremely responsive on Telegram (, deposits/withdrawals are smooth, is open to ALL countries without restrictions, and you can also withdraw up to 2BTC without verifying your account. Coincidentally, Bibox started a referral program for offering commission sharing incentives. If you found this post informative and it brought any value to you, I’d highly appreciate it if you signed up on Bibox through my referral (thanks in advance): is another exchange that has BTO listed. They do have restricted countries (Most US states are restricted), so follow this link to verify if your country is on that list: I’d like to note that gate exchange has been known to have a lot of issues with depositing and withdrawing certain coins lately. I would not recommend them.Be sure head over to their Telegram ( prior to using the exchange in case there are any current issues.

Bottos Website: 
Bottos Telegram: Bottos 
Bottos Facebook: 
Bottos Whitepaper: Bottos 
Introductory Video: Bottos Bitcointalk:;topicseen

Closing Notes

Bottos strives to earn first mover advantage in the AI industry*** as the first AI model, algorithm, and data as an asset marketplace***. In a world that is progressing towards the integration of AI technology into nearly every industry, the ecosystem set up by Bottos will allow for such development to perpetuate at a global level. CEO, Xin Song, fully understands the two major pain points restricting AI technological advancement, namely, the heavily burdensome financial and logistical nature of the data acquisition process, and secure immutable transaction of such sensitive data. The project is ambitious in that no other competition exists in the space, making Bottos pioneers in the space of AI + BIG DATA + BLOCKCHAIN.

V2.0 of the marketplace is scheduled to launch by March of this year, or in about two months. With V2.0 will come the detailed release of the then current state of development progress. V3.0 and the Mainnet will be launched in the month of May. The team is still in discussion of whether to implement Masternodes. They have neither confirmed or denied it, therefore Masternode implementation cannot be ascertained at the moment. The Bottos ecosystem will thrive on the basis of its user base composed of data requesters, providers, and validators. With the current macro situation of AI being an increasingly prevalent matter, the necessities of data acquisition and processing logistics are only growing in size as an impeding issue for AI growth.