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Starting from February 2nd, a major upgrade is rolling out—introducing the next generation of automated tech infrastructure (v2.0). This marks a significant step forward in autonomous development capabilities, with substantial improvements coming to self-writing cloud services and the Internet Computer Protocol (ICP) ecosystem. The advancement represents a meaningful evolution in how automated systems can handle complex technical operations, signaling stronger momentum for decentralized cloud computing applications.

Specialized AI models? That's a trap. Here's the reality: the game is consolidating fast. Within three years, a few dominant models will dominate the landscape, crushing niche competitors in their path. The playbook everyone's copying from Vertical SaaS won't work here. AI doesn't follow those rules. Betting on fragmentation isn't just wrong—it's ignoring what's actually happening in the market.

Saying goodbye to ERC20 tokens on the Ethereum mainnet.
What a journey it's been.

Vietnam's state-owned telecom giant Viettel is officially moving forward with its domestic chip manufacturing initiative. The construction of the country's first semiconductor plant has kicked off, with production trials scheduled to commence by the end of 2027.
This marks a significant milestone for Vietnam's technological independence and supply chain resilience. The development of local chip production capacity carries broader implications for the entire Asia-Pacific tech ecosystem, particularly as the region continues to strengthen its infrastructure for emerging technologies.
The timeline

A new competitor has emerged in the Voice AI Agent field. The latest speech AI agent API has performed remarkably well in the Speech Reasoning benchmark, achieving a score of 92.3%, surpassing the performance levels of ChatGPT and Google Gemini. This not only signifies a breakthrough in audio understanding and real-time response capabilities but also opens up new possibilities for developers.
More importantly, developers can now build real-time, multilingual voice AI agents based on the same technology stack. What does this mean? It means that cross-language and cross-region AI application dep

Anyone else worried about their content just vanishing into thin air? In Web3, where we're supposedly building on decentralized infrastructure, this shouldn't be happening. Yet here we are—users posting, sharing, engaging, only to watch everything evaporate without a trace. Is this really the permanence we were promised?

Building intelligent agents that work across multiple blockchain networks is now more accessible than ever. The latest integration with Cosmos enables seamless interaction across chains, while local deployment options let you tap into a global network of millions of agents simultaneously. This opens up new possibilities for developers looking to create truly decentralized and interoperable solutions in the Web3 space.

Lucky enough, I kept an extra wallet address. When deleting, I didn't clear everything completely, and the account still shows a balance of 200k. This is ridiculous—normally, deleting a post should wipe the data clean, but instead, traces are retained. I can't quite understand what the underlying logic is.

Here's the practical takeaway:
Already subscribed to GitHub Copilot? Your AGiXT agent can leverage it for all coding work—including cutting-edge models—without extra "premium AI" charges.
The magic: AGiXT handles coordination. Copilot handles the code.

Next-gen AI coding assistants are reshaping how developers build autonomous agents. The key difference? Speed isn't the only win—it's about shipping with confidence. A purpose-built assistant understands agent architecture, ensuring your code doesn't just compile, but operates reliably in production. Security and stability become first-class concerns, not afterthoughts. Whether you're optimizing execution flows or debugging agent behavior, having an AI partner that grasps the complexities of autonomous systems transforms the entire development cycle. The promise: write smarter, deploy safer, s

The intersection of decentralized identity and autonomous AI represents a significant shift in how agents operate across blockchain networks. With protocols like ERC-7231 enabling unified data access across multiple chains, AI systems gain the ability to make truly independent decisions while maintaining sovereignty over their operational parameters. This architecture removes intermediaries from the decision-making process, allowing AI agents to function as autonomous entities rather than externally-controlled tools. As cross-chain identity infrastructure matures, the potential applications sp

Predictable throughput is a real game-changer for developers building complex applications. When you know exactly what your network can handle, you stop guessing and start building with confidence. That kind of reliability matters—especially when you're working on intricate dapps that need consistent, measurable performance. It's the difference between hoping your solution scales and actually knowing it will.

Bitcoin Network Fees & Transaction Efficiency
On-chain activity drives network fee dynamics:
• Average fee: 2.1197 sat/vB
• Peak fee: 6.9254 sat/vB (Feb 24, 2025)
• Sub-1 sat/vB adoption growing: 26.5M transactions processed, accounting for 17.28% of all Bitcoin transactions
This shift reveals evolving network efficiency. Lower-fee transactions are gaining traction as users seek cost-effective on-chain alternatives. The data shows Bitcoin's capacity adapting to varied demand patterns, with nearly 1 in 6 transactions now utilizing ultra-low fee tier—a notable efficiency indicator for network pa

The 2025 upgrade brings a suite of powerful analytics capabilities designed to give you a clearer picture of on-chain dynamics. You can now track asset movements through block-level heat maps, monitor real-time 24-hour network and protocol metrics, and analyze block capacity utilization on both hourly and daily timeframes. For those interested in mining operations, the new Mining and Hashrate Analytics module provides detailed insights into network security and computational power distribution. These enhancements aim to help traders, researchers, and validators better understand network behavi

Open-source AI is having quite the momentum week. Google just unveiled TranslateGemma, a fresh lineup of translation models that covers an impressive 55 languages, making cross-border communication more accessible. Meanwhile, BlackForest Labs shipped Flux.2 [Klein], an open-source image generation model that's turning heads—it whips up stunning visuals in under a second without compromising on quality. These releases highlight how the open-source AI space keeps pushing boundaries, giving developers more powerful tools to build with.

The bottleneck in Web3 has shifted. Execution? That's no longer where the real challenge sits. What matters now is stateless intelligence.
This perspective challenges how most builders are thinking about agents right now. Agents without memory hit a wall—they can't learn, can't improve, can't genuinely reason over time. But here's where it gets interesting: provenance becomes critical. You need to know where your data came from, what it means, and whether it's trustworthy.
The implication is stark. We're moving from an era of "can we compute it?" to "do we understand what we're computing with?

Building memory as a foundational layer opens up new possibilities for intelligent blockchain systems. The architecture stacks semantic understanding through persistent data structures, enabling agents to reason meaningfully over stored context. This creates workflows that preserve information flow across operations, allowing developers to deploy fully functional decentralized applications without reinventing the underlying intelligence layer each time.
What makes this approach compelling is the separation between where intelligence lives and where it executes. The computational logic can be d

Industry Leadership Split on AI-Driven Cyber Threats
A recent survey reveals a striking disconnect among corporate decision-makers when it comes to assessing cybersecurity risks posed by artificial intelligence. CEOs and chief security officers don't see eye-to-eye on the severity and implications of AI-enabled attacks.
The findings highlight a critical gap: while some executives view AI as a manageable threat requiring incremental security upgrades, others warn of fundamental vulnerabilities in existing defenses. This divergence matters—especially in sectors like blockchain and fintech where

Astar ecosystem has seen numerous governance actions this week. The Foundation Forward discussions are ongoing, along with the concurrent runtime upgrade referendum—these all directly reflect the transparent decision-making mechanism within the ecosystem.
Three key updates demonstrate open dialogue and technical strength throughout the process. From community participation to protocol iteration, every step is pushing the ecosystem forward. See the detailed sharing below 🧵