AI Tutoring Platform announced that its core learning system has entered the second phase of engineering polishing, covering modules such as task rhythm adaptation, multimodal content adaptation, PoL on-chain verification, and graph-driven path generation, and is committed to building a verifiable, sustainable, and collaborative decentralized intelligent learning infrastructure. The project is not yet online, and all systems are still in the testing phase. The official ecological cooperation pre-access channel is also opened.

July 2025 · From AI Tutoring Labs Inc.

As the global education digitalization process continues to advance and AI content generation technology evolves rapidly, a large number of learning platforms are still stuck in the content distribution and check-in system, and learners’ paths are limited to linear courses, static tasks, and “percentage of completion” driven mechanisms. The key to learning effectiveness – behavioral rhythm, cognitive absorption ability, and understanding process – has never been systematically modeled or verified.

AI Tutoring Platform is changing all this.

As the world’s first decentralized intelligent learning system built on the Proof of Learning (PoL) consensus mechanism, AI Tutoring does not attempt to become another content platform or AI instructor assistant, but is committed to building a complete intelligent learning engine from rhythm control, task scheduling, feedback loop to on-chain verification closed loop.

The project is currently in the second phase of engineering testing. All functions have not yet been launched, but the polishing and internal testing of the following key structural modules have been completed:

 Task scheduling system driven by learning behavior
The platform does not rely on a fixed course rhythm, but automatically adjusts the task length, difficulty and time window by real-time monitoring of learners’ behavioral data (focus fluctuations, repeated operations, pauses in thinking, etc.), so that each section of learning is in a sustainable absorption state, minimizing “passive completion” and “fatigue collapse”.

 Reinforcement feedback mechanism (Reinforcement Loop)
Every operation, an error retry, and an interruption behavior will be regarded as a signal for the system to update the strategy. The platform is testing a set of reinforced strategy feedback networks that can fine-tune the learning path in real time, so that the content is not “recommended to you”, but “dynamically negotiated with your current cognitive state”.

 Multimodal content adaptation engine
Different learners have very different ways of understanding. The platform has designed a content adaptation system based on behavioral preferences, which can automatically switch or merge in multiple forms such as text, illustrations, videos, simulators, etc., to achieve true “learning mode perception”, thereby optimizing absorption efficiency rather than stacking information density.

 Knowledge graph-driven path reconstruction engine
The platform has completed the knowledge structure modeling system, organized all knowledge units in the form of concept dependency graphs, and updated the mastery status of each learner in real time. The system no longer issues tasks by module, but identifies your blind spots and potential areas, and generates structural path recommendations.

 Rhythm-adaptive PoL verification mechanism
In the PoL core module, AI Tutoring emphasizes not only “what has been learned”, but “whether it is truly understood”. The platform uses mechanisms such as behavioral entropy analysis, natural interaction duration, and cognitive delay matching to achieve trusted on-chain verification of the real learning process under non-linear rhythm, effectively blocking mechanical brushing tasks and non-human operation paths, and ensuring the authenticity of incentive distribution.

 Education is not content, but structure
The AI Tutoring team said that they are not in a hurry to launch functions, but hope to enter system testing and ecological joint debugging after the “logical closure and engineering strength” of the functional modules are completed.

“The learning system is not a content factory, it should be a cognitive operating system.”

“We are not building a product, but repairing a set of underlying logic for future education.”

 Cooperation invitation and follow-up arrangements
The project is currently opening the pre-connection window for the following cooperation directions:

Education content platform, course provider and certification agency

Decentralized identity system and on-chain certificate protocol

Web3 education project party and knowledge certificate collaboration party

Wallet system, learning SBT, KYC compliance module provider

RWA learning achievement assetization scenario connection agency

The official will announce the API access details, PoL verification standard document, path adaptation logic structure description in the future, and release the roadmap update at an appropriate time.

Media Contact

Organization: AI Tutoring

Contact Person: James Anderson

Website: https://aitutoring.ink/

Email: Send Email

Country:Singapore

Release id:30631

The post AI Tutoring officially announced the progress of building a basic learning system creating a verifiable decentralized education engine appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section

CryptoTransact launches a real-time crypto payment infrastructure built for global merchants, creators, and platforms. Its stack combines instant on-chain settlement, full compliance automation, and composable SDKs—offering a frictionless alternative to legacy systems.

CryptoTransact today announced the release of its full-stack crypto payment infrastructure designed to meet the real-world needs of merchants, creators, NFT platforms, and game studios. Unlike legacy payment platforms or theoretical blockchain alternatives, CryptoTransact operates as a live-tested system that delivers sub-30-second settlement, predictable transaction costs, and full compliance tooling—all in one unified stack.

While many platforms attempt to mimic traditional finance using tokens, CryptoTransact approaches the problem differently: by subtracting friction, not adding speculation. It integrates deeply at the protocol layer, enabling automated liquidity routing, programmable refunds, and real-time compliance including Know Your Customer (KYC), Anti-Money Laundering (AML), and Travel Rule compatibility.

“Global payments don’t fail because of missing features,” said a core contributor. “They fail because of disconnected systems and unpredictable behavior. We built CryptoTransact to close that gap.”

Designed with a modular architecture, CryptoTransact is built around four interconnected layers: on-chain settlement, liquidity orchestration, compliance enforcement, and developer tooling. Its public SDK suite supports TypeScript, Go, and Python, with open MIT licensing and sandbox access for developers.

At the ecosystem level, CryptoTransact introduces a utility and governance token used to align incentives among merchants, validators, and protocol participants. Instead of relying on hype cycles, the platform anchors its launch strategy in merchant adoption, usage-driven incentives, and system-level transparency.

As digital commerce becomes increasingly global, programmable, and real-time, CryptoTransact positions itself not as a payment gateway—but as the infrastructure layer for the next generation of cross-border value transfer.

Media Contact

Organization: CryptoTransact

Contact Person: Alaric Hawthorne

Website: https://cryptotransact.space/

Email: Send Email

Country:Brunei

Release id:30633

The post CryptoTransact Unveils a Live-Tested Blockchain Payment Infrastructure for Global Digital Commerce appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section

To help more users take part in the network, we’re adding support for Liquid Staking Derivatives (LSD). This means you can stake your LUMINA tokens, earn rewards, and still keep those assets flexible for use across DeFi and other apps. It’s all about giving you more freedom while supporting the network.

At the same time, we’re proud to launch our Green Validator Program — a key step toward building a sustainable blockchain. Validators who use renewable energy or efficient hardware will be recognized and encouraged. As we grow, we want to make sure our infrastructure does too — responsibly, and with the planet in mind.

We’re also integrating with decentralized oracle services, which allow smart contracts on LuminaCoin to access real-world data — like asset prices, weather, and more. This opens the door for developers to build smarter, more responsive applications on our network.

Together, these updates make LuminaCoin more useful, more sustainable, and better connected than ever. Whether you’re a builder, a validator, or a community member — now is the time to get involved.

Stay connected with LuminaCoin:

Website: https://www.luminacoin.pro

Twitter: https://x.com/lumina_p

TG  : https://t.me/luminacomm

Media Contact

Organization: Ember Technologies, Inc

Contact Person: Clay Alexander

Website: https://ember.com

Email: Send Email

Country:Bangladesh

Release id:30634

The post LuminaCoin is entering a new phase of growth and were excited to share whats coming next appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section