Phoenix Global Q2 Development Update

Dear Phoenix Global Community,

These are interesting times for Phoenix Global as we are working on progress on multiple fronts — all in the direction of continuous tech development and optimization while gaining traction for real-world use cases and adoption, in this mid-May update we will briefly cover the following topics:

  • Phoenix Oracle & Initial Release/Use Case
  • Phoenix Staking App
  • Federated Learning
  • New Partner & Enterprise Pilot
  • Exchanges and Marketing

Initial Launch/Use Case

We are glad to announce the first test use case of Phoenix Oracle with Horizon’s data price feeds. We plan to launch the initial module in production-mode along with the Horizon Genesis Mainnet launch, expected in mid-June.

Security/Auditing

The initial module to run along with Horizon Genesis will be audited by Knownsec, and the results will be published prior to Genesis Mainnet launch.

Usage Mechanism

The plan is to have PHB integrated into all Oracle modules and to use it as payment for any and all usage related to data requests and price-feed streams. The current mechanism is to distribute fees to PHB stakers/nodes and the remainder part burned. The exact mechanism, ratios, and calculations are still under discussion and being designed.

We are in the final development phase of the official Phoenix Staking Application (“Staker”) to coincide with our efforts to further decentralize PHB. The Phoenix Staker will be released on the BSC and will follow the staking tiers outlined in the previously released Node Ecosystem Update. Within the next two weeks we expect to release an open testnet of the Phoenix Staker before launching it onto the mainnet.

As time goes on, and through a myriad of conversations, terabytes of data collected, multiple enterprise pilots and hundreds of large consumer enterprises we’ve worked with, it’s becoming more apparent that federated learning (FL) is one blockchain-based use case that 1) will scale fast in combination with existing AI use cases and capabilities 2) create incremental value with network effects the more participants participate in it.

That is why we are determined to invest heavily into developing our FL use cases and ecosystem and to scale adoption. Fast growing usage of federated learning is also can be looked at as a China-driven phenomenon where the appetite for data-driven AI applications continues to grow exponentially albeit with tightening data privacy and consumer consent laws — calling for new decentralized ways to create AI-based insights. It’s apparent that giants such Ant Financial and Tencent Webank are putting in substantial resources, and independent players like Phoenix Global collaborating with strategic partners like APEX Technologies and Seneca ESG are set to capitalize with early enterprise use case adoption.

In particular, here are a few strategic moves that we will take:

Integration with existing AI systems

FL is in essence decentralized AI, and in order to serve functional and vertical use cases, it will need to be integrated with existing systems and models, such as APEX IQ.

(Screenshot of APEX IQ product recommendation AI model used by companies such as Spring Airlines, Alibaba Food Delivery, Bank of China, and Starbucks)

Integration with Phoenix Oracle
Integration with an enterprise-ready oracle is sooner-or-later must have for blockchain-enabled FL — this is crucial in order for the FL applications at hand to maximize the value of the blockchain as well as solve certain issues dealing with data integrity, security, anti-cheating, and transparency. It will also help connect faster and in more reliable ways to various AI platforms.

Ecosystem, Network, and Alliance Expansion
Although at the most minimum there are only two parties required for FL to work, the value is amplified with a larger number of participants and larger datasets. Additionally, the value, differentiation, and business model of a FL “platform” or network, is amplified with more ecosystem participants. The next generation of large data-driven networks will not be centralized players like Facebook, Google, or Amazon, but rather decentralized protocols and platforms with increased transparency and democratization of data & AI.

Team Expansion
Phoenix Global is looking to immediately hire 3–4 additional engineers/developers to be a part of the FL team.

Exploration of Use Cases in IoT

Federated Learning goes hand-in-hand with the explosion of IoT and edge computing. Most current use cases and pilots are in the case of B2B collaboration. In the case where nodes are smart devices or smartphones many times the model is deployed on the device itself, in cases where the devices do not have the computational power (ie. Xiaomi Fit Band), the data is sent to a local node (edge) and the edge-computing mode of federated learning is used. We are seeing a rapid proliferation of this type of use case need, and are looking for technical solutions to support this type of FL. The benefit for Phoenix Global is potentially in having consumers and consumer-devices into the mix, presenting some very interesting opportunities.

New Partner — Green Cloud

Green Cloud

Green Cloud is China’s largest technology provider for the travel industry, with a product suite containing everything from CRM, ERP, payment systems, and ecommerce systems. Green Cloud has a customer ecosystem of over 200 major hotels and airlines. Green Cloud is partnered with Phoenix Global in order to explore federated learning use cases for a select sample of its client group, to help them:

  • Explore privacy-preserving methods to share AI-driven insights across the same customer base across different travel-industry enterprises (between airlines and hotels being one of the most promising test cases)
  • Train and refine customer retention, product recommendation, and targeted marketing AI models across various industry participants.

New Enterprise Pilot — Zhuoyue Education (HK: 3978)

Zhuoyue Education

Zhuoyue Education is a leading Hong Kong-listed online education company. Zhuoyue is looking to leverage federated learning to deploy device-based machine learning apps to improve the customer experience. The first phase of the pilot is set to start in mid June 2021.

Marketing & Exchanges

We are currently open to adding new liquidity to PHB, whether it’d be a CEX or DEX, and are exploring opportunities and having conversations. On the marketing side, we are currently seeking new partners and communities to partner with, and are looking to reopen the Korean and Chinese local communities. We are open to community recommendations of marketing channels, partners, and communities that would be suitable for Phoenix Global.

Blockchain Enablement of the Real Economy. https://phoenix.global/