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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
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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?
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MetaverseVagrantvip:
Ha, this is Web3... No matter how good it sounds, it's still all empty promises.
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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.
ATOM-0,8%
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CryptoTarotReadervip:
This cross-chain agent probably won't crash, right? It feels like the previous Cosmos integrations were all just on paper.
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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.
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VitaliksTwinvip:
Isn't this just a database soft delete vulnerability? Deleting a post isn't really deleting it; the backend records are always kept.
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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.
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LiquidationWizardvip:
Another integration tool, this time AGiXT combined with Copilot... the fact that there are no additional fees is quite appealing.
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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
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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
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TokenUnlockervip:
ngl ERC-7231 sounds like black magic, but if we really want to implement autonomous AI agents... could it end up becoming a bottleneck instead?
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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.
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StrawberryIcevip:
The hype is real, but the key is to actually use it, otherwise no matter how reliable it is, it's all for nothing.
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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
BTC-1,57%
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RugpullSurvivorvip:
The proportion of low-cost transactions is increasing, it seems everyone is becoming smarter. Who still wants to be bloodsucked?
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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
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GasBanditvip:
Honestly, block-level heat maps sound advanced, but can they really help me see through the manipulations of the big players? I'm a bit skeptical.
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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.
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ShibaMillionairen'tvip:
Open-source AI really exploded this week. Is the Trans translation model that covers 55 languages? That's a bit exaggerated. Is it actually practical?
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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?
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ConsensusDissentervip:
Ah, here we go again, talking about stateless intelligence, but the agents actually in use are still stuck there.

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Data provenance is indeed an issue, but Web3 folks haven't figured out how to store this stuff yet.

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From "Can it be calculated" to "Does it matter what we're calculating"... sounds good, but I don't know who is actually doing it.

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Memoryless agents are inherently a pseudo-need; changing the name is like discovering a new continent.

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Provenance is important, but the question is, who will bear the cost?

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Another round of hype, I think. The real bottleneck is still the economic model.
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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
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TokenomicsTinfoilHatvip:
ngl This memory layer architecture sounds good, but how many projects can actually be implemented... Most are probably just talk on paper.
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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
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CafeMinorvip:
NGL, this is a typical case of high-level finger-pointing... Web3 is even more dangerous; no one has a standard answer.
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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 🧵
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ImpermanentPhobiavip:
Transparent decision-making? I think it mainly depends on how the voting rights are distributed. Don't let it become a situation where big players call the shots...
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What's really holding back AI's next breakthrough? Two things keep getting overlooked: our over-reliance on massive data centers and the narrow focus on language-only models.
Data centers are becoming a bottleneck—not just for computing power, but for sustainability and accessibility. We're pouring resources into centralized infrastructure when the real innovation might demand distributed solutions.
Then there's the elephant in the room: betting everything on language models. What about multimodal systems? What about models designed for different tasks, different domains? When everyone chases
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AirdropSweaterFanvip:
That's right, the data center setup should have been replaced long ago, it's money-wasting and pollutes the environment.
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Privacy's always been central to crypto's big picture—how to achieve massive scale without sacrificing user confidentiality. Yet it keeps hitting a wall: the proof generation takes forever. Hours of waiting? That's a non-starter. Users can already get privacy through conventional banking without the hassle. When traditional finance moves faster, why bother with blockchain-based solutions? That's the real problem holding privacy-focused tech back from mainstream adoption. The tech needs to solve the speed problem, or it'll stay niche.
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TokenUnlockervip:
To be honest, the generation speed of privacy coins is really lagging. Traditional banks settle instantly, but here we have to wait several hours. Who would use that?
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A Shopify executive took an unconventional approach to solve a practical problem: rather than relying on traditional proprietary software, he engineered his own web-based MRI scanning viewer from scratch using Claude. What might seem like a niche technical achievement actually reveals something bigger about the future of Web3 development—when builders have access to powerful AI tools, they skip the middleman and create solutions tailored to their exact needs. No licensing fees. No vendor lock-in. Just direct problem-solving through code. It's this kind of creative independence and technical re
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4am_degenvip:
ngl this is the true spirit of a builder—being able to breathe freely without being locked in by vendors
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Ethereum execution layer developers held another important meeting. This time, they mainly discussed a few things: first, EIP-7843(slot opcode) was postponed because it involves coordination between the consensus layer and execution layer; second, seven proposed EIPs ultimately did not make it into the Glamsterdam release; additionally, EIP-7954 (contract size increased from 24KB to 32KB) was included in the future consideration scope. Overall, although some proposals are temporarily on hold, Ethereum continues to adjust and refine details on the path of protocol optimization.
ETH-0,55%
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AirdropHarvestervip:
Another batch of EIPs has been delayed. This pace is really... taking it slow.

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Seven didn't make it into Glamsterdam? Feels like it's always like this. When will it finally pass all at once?

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Expanding the contract size to 32KB is actually interesting. At least it shows some effort in optimization.

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Is it really so difficult for the consensus layer and execution layer to coordinate? Why does it always get pushed back?

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Ah, I have to wait again. When will we be able to use these optimizations?

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Refining the details is good, but isn't this cycle a bit too long?
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