The Power of Federated Learning and Internet of Things

1. The Power of Federated Learning & Internet of Things phoenix.global

2. The Phoenix Global (PHB) blockchain is powering Nex-Gen DApps that are built to fit customer experience. PHB decentralized applications (DApps) promise optimized scalability and flexibility via enterprise sidechains and multi-tiered smart contracts. Top-level data encryption, a two-fold consensus mechanism for improved agility & performance, security, and advanced interactions are other perks. phoenix.global

3. Federated Learning - A Quick Overview Federated Learning, often referred to as Distributed Artificial Intelligence/Machine Learning, is an approach that facilitates collaborative learning from large datasets belonging to different owners without compromising the privacy of each individual’s raw data FL is specifically helpful if the required data is not open source or readily available for strategic or legal reasons. In addition, it seeks to tackle impending privacy and data governance issues by adopting a collaborative model training approach without disclosing sensitive data. Self-driving cars, for instance, require large sets of real-world data to accelerate learning. FL can assure data security and fast-paced learning. Machine learning (ML) techniques have enjoyed mass adoption in Industry 4.0 and advanced health systems and with FL algorithms, sensitive data are kept safe. phoenix.global

4. Internet of Things (IoT) - A Quick Outlook Internet of Things (IoT) is rapidly penetrating all sides of life with the snowballing of AI-empowered applications and other intelligent services. It facilitates the connection of billions of network-enabled devices - “things” - and utilizes massive amounts of centralized data points. phoenix.global

5. Federated Learning - A Quick Overview While the positives of IoT remain undeniable, the scalability, security, and privacy concerns surrounding it (IoT) remain valid. However, Federated Learning (FL) has surfaced as a collaborative and distributive artificial intelligence (AI) approach to solve these challenges. With several ongoing conversations in the Blockchain space, large volumes of data collected per time, and the emergence of large consumer enterprises and pilots, it is becoming increasingly evident that Federated Learning will accelerate AI capabilities and use cases. A fast-growing application of FL can be seen in the China-driven phenomenon. In addition, the need for AI-based insights has continued to resurface, especially with the exponential growth in the demand for data-driven artificial intelligence applications. phoenix.global

6. Phoenix Global - an independent market player, in conjunction with Seneca ESG and APEX Technologies, is set to offer consumers early enterprise adoption by integrating FL with Phoenix Oracle and current AI models and systems like the APEX IQ. The integration with enterprise-ready Phoenix Oracle will ensure that Federated Learning applications solve issues around consumer data security, integrity, and transparency while also maximizing the full benefits of the Blockchain. The most recent pilots are in Business-to-Business (B2B) collaborations, where data nodes are smart devices or local nodes, as in edge computing. This sort of use case has continued to gain traction in the tech and Blockchain space, and that’s where PHB comes into the mix again. phoenix.global

7. Final thoughts Federated Learning offers a faultless and efficient ML mechanism to solve the existing concerns around hardware capacity, data privacy, and connectivity of IoT devices. Phoenix Global seeks to champion the Nex-Gen systems of extensive decentralized data with improved governance and transparency of AI and data. phoenix.global

8. BLOCKCHAIN POWERING THE NEXT GENERATION OF CONSUMER APPLICATIONS More Private.More Interactive.More Connected. twitter.com/Phoenix_Chain phoenix.global t.me/APEXcommunity github.com/phoenixglobal phoenixglobal.medium.com www.reddit.com/r/PhoenixGlobal