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RWA

RWA (Real World Assets) refers to the tokenization of tangible assets—such as real estate, private credit, and government bonds—on the blockchain. By bringing traditional financial instruments on-chain, RWA protocols like Ondo and Centrifuge provide DeFi users with stable, real-yield opportunities. In 2026, the RWA sector is a multi-trillion-dollar bridge between TradFi and DeFi, enabling fractional ownership and global liquidity for previously illiquid assets. Follow this tag for insights into on-chain credit markets, regulatory compliance, and asset-backed security innovations.

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Created: 2026/02/02 18:52
Updated: 2026/02/02 18:52
South Korea Producer Price Index Growth (MoM) climbed from previous 0.1% to 0.4% in July

South Korea Producer Price Index Growth (MoM) climbed from previous 0.1% to 0.4% in July

The post South Korea Producer Price Index Growth (MoM) climbed from previous 0.1% to 0.4% in July appeared on BitcoinEthereumNews.com. Information on these pages contains forward-looking statements that involve risks and uncertainties. Markets and instruments profiled on this page are for informational purposes only and should not in any way come across as a recommendation to buy or sell in these assets. You should do your own thorough research before making any investment decisions. FXStreet does not in any way guarantee that this information is free from mistakes, errors, or material misstatements. It also does not guarantee that this information is of a timely nature. Investing in Open Markets involves a great deal of risk, including the loss of all or a portion of your investment, as well as emotional distress. All risks, losses and costs associated with investing, including total loss of principal, are your responsibility. The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of FXStreet nor its advertisers. The author will not be held responsible for information that is found at the end of links posted on this page. If not otherwise explicitly mentioned in the body of the article, at the time of writing, the author has no position in any stock mentioned in this article and no business relationship with any company mentioned. The author has not received compensation for writing this article, other than from FXStreet. FXStreet and the author do not provide personalized recommendations. The author makes no representations as to the accuracy, completeness, or suitability of this information. FXStreet and the author will not be liable for any errors, omissions or any losses, injuries or damages arising from this information and its display or use. Errors and omissions excepted. The author and FXStreet are not registered investment advisors and nothing in this article is intended…

Author: BitcoinEthereumNews

2025/08/22

Together AI Enables Fine-Tuning of OpenAI’s GPT-OSS Models for Domain Specialization

Together AI Enables Fine-Tuning of OpenAI’s GPT-OSS Models for Domain Specialization

The post Together AI Enables Fine-Tuning of OpenAI’s GPT-OSS Models for Domain Specialization appeared on BitcoinEthereumNews.com. Timothy Morano Aug 21, 2025 01:10 Together AI’s fine-tuning platform allows organizations to customize OpenAI’s GPT-OSS models, transforming them into domain experts without the need for complex infrastructure management. The release of OpenAI’s gpt-oss-120B and gpt-oss-20B models marks a significant advancement in the field of artificial intelligence. These models are open-weight and licensed under Apache 2.0, designed specifically for customization, making them a versatile choice for organizations looking to tailor AI capabilities to their specific needs. According to Together AI, these models are now accessible through their platform, enabling users to fine-tune and deploy them efficiently. Advantages of Fine-Tuning GPT-OSS Models Fine-tuning these models unlocks their true potential, allowing for the creation of specialized AI systems that understand unique domains and workflows. The open-weight nature of the models, combined with a permissive license, provides the freedom to adapt and deploy them across various environments. This flexibility ensures that organizations can maintain control over their AI applications, preventing disruptions from external changes. Fine-tuned models offer superior economics by outperforming larger, more costly generalist models in specific tasks. This approach allows organizations to achieve better performance without incurring excessive costs, making it an attractive option for businesses focused on efficiency. Challenges in Fine-Tuning Production Models Despite the benefits, fine-tuning large models like the gpt-oss-120B can pose significant challenges. Managing distributed training infrastructure and addressing technical issues such as out-of-memory errors and resource utilization inefficiencies require expertise and coordination. Together AI’s platform addresses these challenges by simplifying the process, allowing users to focus on their AI development without being bogged down by technical complexities. Together AI’s Comprehensive Platform Together AI offers a fine-tuning platform that transforms the complex task of distributed training into a straightforward process. Users can upload their datasets, configure training parameters, and…

Author: BitcoinEthereumNews

2025/08/22

2025’s Biggest Letdown? Holders Hunt New Tokens to Recover Heavy Losses

2025’s Biggest Letdown? Holders Hunt New Tokens to Recover Heavy Losses

The post 2025’s Biggest Letdown? Holders Hunt New Tokens to Recover Heavy Losses appeared on BitcoinEthereumNews.com. Crypto News Pi Coin was once hailed as the “people’s crypto,” a project that promised accessibility and massive adoption without the usual technical barriers. Millions downloaded the app, mining coins on their phones with dreams of life-changing wealth. But by 2025, reality hit hard. With little utility, no open mainnet, and plummeting confidence, Pi Coin has become a painful lesson in overhype versus delivery. Now, attention is shifting toward tokens that actually do something. Enter Layer Brett (LBRETT), a meme-powered Layer 2 project built on speed, low fees, and real rewards. With gamified staking, NFT integrations, and a $1 million giveaway, LBRETT is capturing the attention of weary Pi Coin holders. Priced at just $0.0044 the entry level is super low. In this article, we’ll explore why Pi Coin collapsed under its own weight, and why projects like Layer Brett could represent the future of crypto utility. Pi Coin (PI): When hype becomes a heavy backpack Pi Coin was supposed to be the crypto revolution everyone could join from their phones. With 60 million users mining “free” tokens, expectations skyrocketed. But in 2025, the dream has soured. PI’s price has plunged 80% year-to-date, volume shrank from $140 million to just $43 million in August, and frustrated holders are left wondering where the promised open mainnet and ecosystem went. The delays haven’t helped. The open mainnet remains locked, while rumors of insider selling swirl. Pi Coin once promised 100 DApps and a $100 million developer fund, but both feel like ghost stories now. Instead of flourishing, the network looks stuck in quicksand. Still, Pi Coin isn’t totally out. With a $3.16 billion market cap and a surprise 154% rally, there’s a sliver of fight left. Yet compared to its scale of expectation, Pi Coin may just be 2025’s biggest letdown, proof…

Author: BitcoinEthereumNews

2025/08/22

South Korea Accelerates Won Stablecoin Adoption with FSC Bill Announcement

South Korea Accelerates Won Stablecoin Adoption with FSC Bill Announcement

TLDR Korea advances won stablecoin bill with bipartisan and regulatory backing FSC sets October launch for stablecoin rules amid bank-tech interest South Korea unites politics, finance in stablecoin legal framework push Won stablecoin gains traction as FSC and lawmakers align on regulation Tether, Circle court top Korean banks as stablecoin law gains steam South Korea [...] The post South Korea Accelerates Won Stablecoin Adoption with FSC Bill Announcement appeared first on CoinCentral.

Author: Coincentral

2025/08/22

Crypto AI Agents: Automating the Future of Web3

Crypto AI Agents: Automating the Future of Web3

Crypto AI Agents: Automating the Future of Web3The swift fusion of artificial intelligence (AI) and blockchain technology has created a groundbreaking new era. Crypto AI Agents. These autonomous, intelligent entities are not just reshaping how transactions are executed but also redefining the very foundation of Web3 ecosystems. By integrating the decision-making capabilities of AI with the transparency and decentralization of blockchain, Crypto AI Agents represent a powerful innovation that promises to automate, optimize, and revolutionize everything from trading and asset management to governance and security.This blog dives deep into Crypto AI Agents, exploring their mechanics, applications, benefits, challenges, and their role in automating the future of Web3. By the end, you’ll have a comprehensive understanding of why Crypto AI Agents are poised to become the backbone of decentralized automation.What Are Crypto AI Agents?A Crypto AI Agent is an autonomous software agent that leverages artificial intelligence to perform actions within blockchain and Web3 environments. Unlike traditional bots, which are rule-based and limited in scope, AI agents can learn, adapt, and make decisions dynamically. When combined with blockchain’s decentralized infrastructure, they enable trustless automation across crypto markets, decentralized finance (DeFi), tokenization platforms, and Web3 applications.In simple terms:✦AI gives agents the intelligence to analyze, predict, and optimize actions.✦Blockchain ensures transparency, security, and immutability.✦Web3 provides the decentralized ecosystem where these agents can operate autonomously.The Evolution of Automation in CryptoPhase 1: Trading BotsEarly automation in crypto revolved around algorithmic trading bots that executed buy/sell orders based on pre-set conditions. These bots couldn’t adapt well, leading to failures during high market volatility.Phase 2: Smart ContractsSmart contracts brought rule-based automation to blockchain but still required human developers to code the logic.Phase 3: AI-Driven AgentsNow, AI agents are emerging as the next phase - autonomous systems that don’t just follow static rules but learn from data, adjust strategies, and interact intelligently with decentralized ecosystems.How Crypto AI Agents Work?Crypto AI Agents typically operate through a three-layered framework:Data Layer✦Collects on-chain and off-chain data (price feeds, transaction histories, sentiment analysis, social media insights, etc.).✦Leverages APIs and oracles to access external data feeds.Intelligence Layer✦Powered by machine learning models (neural networks, reinforcement learning, natural language processing).✦Enables agents to make predictions, optimize yields, or detect fraud.Execution Layer✦Interacts with smart contracts, decentralized applications (dApps), wallets, and exchanges.✦Executes actions such as trading, lending, voting, staking, or governance decisions autonomously.Key Applications of Crypto AI Agents1. Automated Trading and Market MakingWith real-time data analysis, AI agents identify patterns, forecast market directions, and execute trades better than humans. They can also serve as liquidity providers on decentralized exchanges (DEXs).2. DeFi Yield OptimizationCrypto AI Agents can move assets across protocols like Aave, Compound, and Curve to maximize yields automatically while assessing risks in real-time.3. Governance ParticipationIn decentralized autonomous organizations (DAOs), AI agents can analyze proposals, evaluate community sentiment, and even cast votes aligned with predefined strategies.4. Fraud Detection and SecurityWith machine learning, agents can detect abnormal transaction patterns, phishing attempts, and potential hacks, alerting the community or even blocking transactions.5. NFT and Tokenization AutomationFrom dynamic NFT pricing to real-world asset (RWA) tokenization, AI agents can manage issuance, pricing, and fractional ownership automatically.6. Personalized Financial AssistantsCrypto AI Agents can serve as personalized assistants, managing portfolios, executing risk-adjusted strategies, and offering tailored investment advice.Benefits of Crypto AI Agents24/7 AutomationUnlike humans, AI agents can operate non-stop in global crypto markets.Data-Driven DecisionsProcessing huge amounts of on-chain and off-chain data, AI drives quicker decisions with greater accuracy.Reduced Human ErrorAutomated systems minimize errors caused by emotional trading or manual mismanagement.ScalabilityA single agent can manage thousands of assets, protocols, and transactions simultaneously.Transparency and SecuritySince operations are logged on-chain, all actions taken by an AI agent remain auditable.Challenges and Risks1. Bias in AI ModelsIf an AI model is trained on biased or incomplete data, it may produce inaccurate results.2. Smart Contract VulnerabilitiesAgents rely on smart contracts, which may have exploitable bugs or loopholes.3. Regulatory UncertaintyAs AI-driven automation grows, regulators may struggle to define accountability for AI agent actions.4. Over-AutomationComplete reliance on autonomous agents may lead to systemic risks if too many agents act simultaneously in volatile markets.5. Security ThreatsMalicious actors may attempt to manipulate AI inputs or exploit vulnerabilities to control agent behavior.Crypto AI Agents and Web3 SynergyWeb3 is about decentralization, trustlessness, and community-driven ecosystems. AI agents complement these goals by providing:Autonomous Governance - DAOs powered by AI agents can manage themselves with minimal human intervention.Enhanced User Experience - AI agents abstract away complexity, allowing mainstream users to interact with Web3 seamlessly.Cross-Chain Interoperability - AI agents can manage assets across Ethereum, Solana, Polkadot, and other blockchains effortlessly.Together, they lay the foundation for a more self-sustaining and intelligent Web3 ecosystem.Future Outlook of Crypto AI Agents1. Integration with Real-World Assets (RWAs)Agents will manage tokenized assets like real estate, stocks, and commodities, bridging TradFi and DeFi.2. AI-DAO HybridsDecentralized organizations may be fully run by AI agents that oversee treasuries, vote on proposals, and manage operations.3. Agent-to-Agent EconomiesFuture Web3 ecosystems could feature AI agents transacting, negotiating, and contracting with each other without human oversight.4. Enhanced User AdoptionBy simplifying crypto complexity, AI agents could attract mainstream users into Web3 through personalized, automated services.5. Global Financial AutomationFrom micro-payments to billion-dollar treasuries, AI agents will automate every layer of finance, ensuring efficiency and transparency.Real-World Examples and Emerging ProjectsFetch.ai - A platform creating AI agents that interact with digital economies.SingularityNET - Decentralized AI marketplace enabling integration of AI services with blockchain.Ocean Protocol - Focused on data sharing where AI agents can consume and analyze datasets.Autonolas - A project working on autonomous services and governance.These forerunners are paving the way for Crypto AI Agents to reach global adoption.ConclusionCrypto AI Agents stand as a pivotal innovation driving the progression of Web3. By combining the predictive power of artificial intelligence with the decentralized integrity of blockchain, these agents promise to automate, optimize, and democratize digital economies. While challenges such as regulatory hurdles, data biases, and security threats remain, the potential of Crypto AI Agents far outweighs the risks.In the future, we may see entire decentralized ecosystems autonomously run by intelligent agents - creating a world where financial decisions, governance, and asset management are more efficient, secure, and equitable than ever before.The age of Crypto AI Agents is not just coming - it’s already here, and it’s set to automate the future of Web3.Crypto AI Agents: Automating the Future of Web3 was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

Author: Medium

2025/08/22

NVIDIA Enhances Training Throughput with NeMo-RL’s Megatron-Core

NVIDIA Enhances Training Throughput with NeMo-RL’s Megatron-Core

The post NVIDIA Enhances Training Throughput with NeMo-RL’s Megatron-Core appeared on BitcoinEthereumNews.com. Ted Hisokawa Aug 20, 2025 16:26 NVIDIA introduces Megatron-Core support in NeMo-RL v0.3, optimizing training throughput for large models with GPU-optimized techniques and enhanced parallelism. NVIDIA has unveiled the latest iteration of its NeMo-RL framework, version 0.3, which incorporates support for Megatron-Core. This enhancement aims to optimize training throughput for large language models by leveraging GPU-optimized techniques and advanced parallelism strategies, according to NVIDIA’s official blog. Challenges with Previous Backends The initial release of NVIDIA NeMo-RL utilized PyTorch DTensor (FSDP2), offering native integration with the HuggingFace ecosystem and enabling quick experimentation through PyTorch’s native parallelisms. However, as model sizes increased to hundreds of billions of parameters, the DTensor path proved inadequate due to significant recompute overhead and lack of optimized NVIDIA CUDA kernels, leading to inefficient step times. Introducing Megatron-Core The Megatron-Core library addresses these limitations by offering a more efficient solution for training extensive models. It employs a 6D parallelism strategy to enhance communication and computation patterns, supporting various model architectures. This backend enables seamless training of massive language models, enhancing throughput and performance significantly. Getting Started with Megatron-Core Implementing Megatron-based training involves adding specific configurations to the YAML setup. The process is streamlined by NeMo-RL, which handles complex tuning automatically, presenting users with straightforward configuration options. This makes the adoption of Megatron-Core more accessible for developers, allowing them to focus on optimizing their model training processes. Performance Improvements Megatron-based training supports both dense and Mixture of Experts (MoE) models. Performance tests have demonstrated superior training performance with Megatron-Core compared to PyTorch DTensor, as shown in various model configurations like Llama 3.1-8B and 70B. The enhancements are evident in faster step times and improved convergence properties. Additional Features and Future Prospects NeMo-RL v0.3 introduces features such as async rollouts and non-colocated…

Author: BitcoinEthereumNews

2025/08/22

Pi Coin (PI): 2025’s Biggest Letdown? Holders Hunt New Tokens to Recover Heavy Losses

Pi Coin (PI): 2025’s Biggest Letdown? Holders Hunt New Tokens to Recover Heavy Losses

Millions downloaded the app, mining coins on their phones with dreams of life-changing wealth. But by 2025, reality hit hard. […] The post Pi Coin (PI): 2025’s Biggest Letdown? Holders Hunt New Tokens to Recover Heavy Losses appeared first on Coindoo.

Author: Coindoo

2025/08/22

Polymath Builds Global Momentum with New Partnerships across Europe and North America

Polymath Builds Global Momentum with New Partnerships across Europe and North America

Polymath Builds Global Momentum with New Partnerships across Europe and North America

Author: Cryptodaily

2025/08/21

SoftBank Reports 30% Uplink Boost with AI-Driven 5G Model

SoftBank Reports 30% Uplink Boost with AI-Driven 5G Model

TLDRs; SoftBank’s new AI-driven Transformer model improved 5G uplink throughput by 30% in live tests. The architecture achieved 26% lower latency compared to previous CNN-based models. Downlink throughput for moving terminals increased by up to 31% in simulations. SoftBank’s work aligns with global AI-RAN efforts, signaling an industry-wide shift in telecom innovation. SoftBank has unveiled [...] The post SoftBank Reports 30% Uplink Boost with AI-Driven 5G Model appeared first on CoinCentral.

Author: Coincentral

2025/08/21

Can Tokenization Solve Canada’s Junior Mining Foreign Investment Problem?

Can Tokenization Solve Canada’s Junior Mining Foreign Investment Problem?

Canadian junior mining companies are struggling to attract foreign investment due to tighter national security reviews, new provincial consultation requirements, evolving European ESG rules, and concerns about short selling on the TSX Venture. Meanwhile, younger investors are choosing tech and crypto over traditional mining stocks. Tokenized funds—already deployed by BlackRock, UBS, and Franklin Templeton—could solve both problems by making it easier for foreign investors to access Canadian mining through compliant digital infrastructure while offering tech-savvy investors a familiar blockchain-based interface. However, Canada needs to modernize its fragmented digital asset regulations and clarify how tokenized funds are treated under securities law for this solution to work.

Author: Hackernoon

2025/08/21

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