Phoenix.Global. Find the solution to certain issues dealing with data integrity, security, anti-cheating, and transparency using Federated Learning.
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What’s Federated Learning & How it's Implemented on Phoenix Global?
1. How Is Federated Learning
Implemented on Phoenix
Global?
phoenix.global
To improve GPS navigation, MIT researchers are
tagging road features on digital maps through
Machine learning.
The challenge is to use sensitive and massive data
stored in a distributed manner for application
purposes. Federated Learning (FL), a new type of
ML, allows companies to share data in a
"closed-loop system."
https://news.mit.edu/2020/artificial-intelligence-digital-maps-0123
2. phoenix.global
Federated Learning is a step up from the
standard centralized and traditional
decentralized machine learning techniques. It
teaches a shared machine-learning algorithm to
different decoupled devices that maintain local
data without sharing this data among the
devices.
Federated Learning
(or Collaborative Learning)
Through Federated Learning, systems can
maintain data privacy, lessen power consumption,
decrease waiting time, and create more
intelligent algorithms. The Google keyboard
GBoard uses the Federated Learning technique.
https://ai.googleblog.com/2017/04/f
ederated-learning-collaborative.ht
ml
3. phoenix.global
Phoenix Global
Phoenix Global is the blockchain that hosts
next-generation consumer-focused DApps. The
Phoenix Chain is sidechain-agnostic and bridges
with Binance Smart Chain (BSC), Ethereum, Solana,
NEO, and Tron. Phoenix Global augments Big
Data-based Artificial Intelligence (AI) via Federated
Learning.
https://phoenix.global/
Phoenix Global platform focus:
Federated Learning
A merger between APEX network and Red Pulse
Phoenix gave birth to Phoenix Global. During the
Q2 development in 2020, Phoenix Global expressed
the desire to work extensively on Federated
Learning (FL) use cases and ecosystems.
https://apexteam.medium.com/apex-network-and-red-pulse-phoenix-to-merg
e-and-develop-horizon-defi-platform-171df28b5f5c
https://phoenixglobal.medium.com/phoenix-global-q2-development-update-854
ff96c8412
4. phoenix.global
This desire stems from these facts:
FL is a blockchain use case bound to scale to
collaborate with existing AI capabilities and
use cases.
FL can create incremental value as more
people participate in the blockchain network.
China has a high appetite for AI consumer ap
plications.
How does the Phoenix Global
platform implement Federated
Learning?
Integration with existing AI systems
FL could integrate with existing machine learning
algorithms, such as APEX IQ, to expand FL use
cases.
https://phoenixglobal.medium.com/announ
cing-the-new-phoenix-global-node-ecosys
tem-49d310182650
5. phoenix.global
By integrating with the enterprise-ready Oracle,
FL applications can maximize the value of the
blockchain and solve specific issues dealing with
data integrity, security, anti-cheating, and
transparency.
Integration with Phoenix
Oracle
Ecosystem, Network, and
Alliance Expansion
Phoenix Global aims to forge more alliance
partnerships like the technology giant
Green Cloud has partnered with Phoenix Global
to probe FL use cases. Phoenix Global is also in
partnership with ARPA.
https://www.accenture.com/us-en/insights/strategy/green-b
ehind-cloud
https://arpachain.io/
6. phoenix.global
Conclusion
For the futuristic development of AI-based consumer
applications, Phoenix Global integrates Federated
Learning with blockchain technology. PHB is currently
seeking new partners and communities to partner
with and reopening Korean and Chinese local com-
munities.
Phoenix Global is creating a community dedicated to a
common goal - giving both technologies the best possi-
ble outcome. PHB’s interest in Federated Learning por-
trays its dedication to making this vision a reality.
Team Expansion
Phoenix Global is already hiring engineers and de-
velopers to expand its FL team. Transparency and
verification of the data on blockchain will help
hurdle blockages, no matter their specific indus-
tries.