P-Rep Candidate
Team Information

Common Computer HQ: 서울특별시 강남구 강남대로 382, 17층 1769호 (역삼동, 메리츠 빌딩)

AI Network is a blockchain network that makes a paradigm shift from dedicating a massive amount of computing resources on mining to building a federation of distributed computing resources that solve real-world AI problems using AI Network Architecture’ as well as saves an enormous amount of electrical powers.

Self-Intro Video

Proposal Points and Objectives

Common Computer is a blockchain company building AI Network. We believe our experiences in Machine Learning techniques and distributed computing can contribute to ICON community and brings ICON network to the next intelligence.

Block Production: Our technical expertise in managing distributed cloud enables us to manage block production with fault tolerance. 

- AI Block Analysis: Not only we verify transactions, but we also have the capacity to process and analyze a large number of transactions from the blockchain, and provide useful information that can benefit both block producers and developers.

- Governance Decisions: Common Computer will listen to the voice of the ICON community, and participate in the relevant decision process to make sure the ICON blockchain is healthy both technologically and culturally.

- AI marketplace: Common Computer can provide additional features on top of ICON smart contract. Dapp developers will be able to use various AI components reliably and cost-efficiently.


Motivation of the proposal

The ICON Project aims to build a decentralized network that allows independent blockchains with different governances to transact with one another without intermediaries. We want to participate in this vision from the early stage, to create special AI worlds on top of ICON network.



  • Block Production Common Computer will follow initial hardware spec suggested by ICON. If the network requires a more heavy load, we are always ready to scale our settings to ensure reliable block production.

  • AI Block Analysis ICON currently provides icon block explorer (https://tracker.icon.foundation/) which contains basic information of the current block status. As the number of transactions can get larger, it gets harder to understand what is going on in the network. Using machine learning, AI Network can add additional value to make transaction data useful in the following areas:

    • Anomaly Detection: If any new behavior is different from historical behavior, AI can detect and notify users about such an event. Anomaly detection can help network to discover severe security or financial risks as early as possible.

    • Account Categorization: Smart contracts can have a different purpose and it's not possible for a human to understand the purpose of individual transactions. Using machine learning categorization, we can provide a general overview of transaction types which may include exchange, casino, games, financials, and huge transfers.

    • DOS attack detection: One of the critical weakness for DPOS is we have limited network pointers. AI may detect precursors of DOS attack and warns ICON community to cope with.

    • Fraud detection: Using historical fraud pattern, we may able to prevent future fraud and protect people from sending money to the suspicious account.

  • Governance Decisions

    • Common Computer will provide technical perspective for the future decision and additional analysis data to help to make a reasonable decision

    • We will encourage involvement from developers and open source communities.

    • We may provide necessary technical advice or education to make sure new knowledge and findings are shared within the ICON community. 

  • AI marketplace

    • The smart contract can provide limited functionality and expensive by nature. AI Network can provide state-of-the-art AI solutions on top of the blockchain.

    • Developers can improve and utilize AI solutions available in the marketplace.

    • Developers can integrate AI solutions into their Dapps.


4. Roadmap

  • 2019 Q1 P-Rep Application 

  • 2019 Q1 AI Network Beta released.

  • 2019 Q2 P-rep node setup

  • 2019 Q3 Accumulate transactions and organize them in a structured database.

  • 2019 Q4 Start producing basic AI Block analysis

  • 2020 Q1 Launch Sophisticated block analysis

  • 2020 Q2 Design AI market place

  • 2020 Q3 Implement AI market place

  • 2020 Q4 Expand AI market place and create a developer community



5. Team Resources and Contact

⋅ Common Computer Inc.: https://comcom.ai

⋅ AI Network Website: https://ainetwork.ai

⋅ AI Network Facebook

⋅ AI Network Dapp aFan Website: https://afan.ai



Common Computer

Expected Network Information

Singapore, Singapore cloud

Server type: C5.9xlargeCPU Model: Intel® Xeon® Platinum 8124 CPU @ 3.00GHZvCPU(core): 36RAM: 72GDisk: 500G NVMe SSD (EBS bandwidth 4.5 Gbps)Network: 10 Gbps

Team Members

Minhyun Kim Team Member

Minhyun is CEO of Common Computer graduated from KAIST and worked at Google with the record of youngest full-time software engineer ever in Seoul. After 3 years of experience in Google, he spent 2 years outside of Google to learn more about how value is being transferred in our society, the culture of startups, and social welfare in Soongsil University as a graduate student. Then he joined Google again and contributed to Google search engine and machine learning projects, while at the same time contributed to ML developer communities. Now with a mission to create AI system to measure and distribute value at the speed of information via blockchain, Minhyun founded the company to develop AI Network that creates an ecosystem for engineers, researchers & companies and users where they can experience best-in-class technology to maximize each of their values.

John Kim Team Member

John is COO of Common Computer responsible for operating company, build organization, and business development. Before joining AI Network, John has spent 7.5 years working at Google mostly on business organization. In last 3 years of Google, his role was to lead global top tech accounts for Google, such as Samsung, as Global Account Executive consulting brand marketing, product launch strategy, and data strategy using ad tech and cloud platform working with various Google functions as a project manager. John has BA from Korea University and completed Marketing Academy, a bespoke marketing program at Wharton School designed by its MBA faculty, sponsored by Google.

Seonghwa Yun Team Member

Seonghwa is software and blockchain engineer of Common Computer, formerly worked at Naver local search team. Main project that he participated was to enhance search result quality based on AI. He’s interested in understanding and analyzing people’s motivation for certain behavior with various methodology, a common point between his area of interest and mission of AI Network. After graduating KAIST majoring CS, he studied Electricity and Electronic Engineering at KAIST and received a master’s degree.

Lia Yoo Team Member

Lia is a software and blockchain engineer at Common Computer. As a member of the Dev Team, Lia is responsible for reviewing the whitepaper and the design of Deep Computer, as well as building the platform. Lia was selected to participate in a Google’s program for women in Computer Science (CS), and later interned as a Software Engineer on the Google Now team, where she learned the inner workings of Google Search and Knowledge Graph, and developed features to recommend and inform the users of new information based on the users’ previous search data and interests. Lia is most excited when she’s learning about or figuring out solutions to complex real-world problems that are relating to multiple fields of study. Naturally, she developed deep passion for blockchain technology that combines CS, Game Theory, economics and much more, and has been studying the burgeoning technology vigorously. Lia has a BS/CS from Washington University in St. Louis.

Daesung Kim Team Member

Daesung is a Product Manager at Common Computer. He was Senior UX designer at NAVER LABS. He led product planning and design for AWAY (an In-Vehicle Infotainment platform) and navigation module of NAVER Maps. He designed and patented WSD feature in Papago (a machine translator service). Prior to NAVER LABS, he worked at Samsung Electronics, and proposed and designed interaction of Quick connect (a IoT Hub feature shipped in Galaxy S5), and Animated Photo (a cinemagraph feature shipped in Galaxy S4). He designed concepts of Top stories (a smart assistant project), and home launcher.