Pi Coin Price Rises 79% Amid Mainnet Hopes and Analyst Forecast

Pi Coin price prediction

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Pi Coin price prediction (PI) now costs roughly USD 0.6511 as of April 23, 2025. This represents a 79% increase over the past 24 hours, indicating a minor upward trend in what has been a generally quiet period for the token. Initially introduced as a mobile-mined cryptocurrency designed to make digital currencies accessible to the general public, Pi Coin has garnered increasing interest among retail investors and the broader crypto community. With an estimated 6.94 billion tokens in circulation, its market capitalization comes to about $4.52 billion.

Analysts Bullish on Pi Coin

The Pi Coin market has shown wary optimism over the past week. The coin’s worth on April 17 was $0.6039; it has now risen to $0.6519, representing an increase of around 8% during that period. Although these increases may not seem significant compared to the occasionally explosive swings of the larger cryptocurrency market, they indicate a consistent rise that suggests growing interest in the token. Pi Coin trades somewhat behind its all-time high of $2.98, which was attained on February 26, 2025, despite this encouraging trend. PI is now down by almost 78% from its peak, suggesting that early buyers who paid more still have a significant amount of ground to recover.

Several industry analysts have responded with short-term and medium-term pricing forecasts for the future. By April 25, Pimay is expected to increase by another 64%, according to Watcher, reaching a projected price of $0.7113. Growing trade volume and current technical indicators form the basis of my projection. With an average price of roughly $1.27, CoinCodex presents a more optimistic outlook, suggesting that PI could reach as high as $2.18 at some point in April. From current levels, this would indicate an almost 200% increase. Likewise, Brave New Coin has projected a price of $2.08 by May 21, citing rising activity from so-called “whales”—large coin holders—who appear to be accumulating tokens in preparation for a breakthrough. This would indicate rising hope for the project’s future, as it would show a 228% increase from the existing pricing level.

Pi Coin Market Sentiment

Not all markers, though, point to a positive story. Pi Coin’s Fear & Greed Index score currently stands at 39, placing it in the “Fear” range. This implies that investor attitude is still mostly wary. One often used statistic to evaluate feelings and attitudes influencing the bitcoin market is the Fear & Greed Index. A low score typically indicates hesitation among investors, while a high score suggests enthusiasm or possible overconfidence. Although these indicators should not be used alone to guide investment decisions, they do offer insightful analysis of the broader psychological landscape of the market.

Pi Coin Market Sentiment

Several factors are influencing the price movement and the market’s attitude toward Pi Coin. One of the most important is the expected mainnet release by Pi Network. This highly anticipated event aims to establish the token’s actual value and utility. Most Pi Coin transactions have been limited to test environments or speculative trading on unofficial markets up until now. From distributed apps (dApps) to smart contracts and peer-to-peer payments, the token could begin to find real-world use cases once the mainnet is launched. Such advances can fundamentally affect the demand and value proposition of the token.

Trading Volume & Pi Coin

Apart from the speculation on the mainnet, more general market variables are influencing Pi Coin’s price. Over the past month, Bitcoin, Ethereum, and other major cryptocurrencies have experienced erratic trading sessions. Their patterns can impact lesser-known altcoins, such as Pi Coin price prediction. If Bitcoin continues to stabilise above key thresholds, it may create a more suitable environment for altcoins to thrive. On the other hand, a significant market correction might pull PI and like tokens down with it.

Another crucial statistic to consider is trading volume. Pi Coin has recently observed 24-hour trade volumes ranging from $92 million to $150 million. This rise in activity suggests increased interest and involvement among traders, potentially indicating more momentum behind the coin. Depending on concomitant market mood and order book activity, volume spikes sometimes precede notable price moves, either upward or downward.

Pi Coin on the Rise

Pi Coin is presently in a phase of cautious optimism, at least. Supported by small gains and increased trading activity, its price has demonstrated a consistent upward trend over the last week. Although the token is still well behind its all-time high, forecasts from several analysts indicate that it will. However, a positive breakout could be feasible, particularly if the long-awaited mainnet launch occurs and general market conditions remain steady.

The Fear & Greed Index shows that investor sentiment remains conflicted; therefore, any forward-looking assumptions should be balanced with a prudent approach. Like any investment in a cryptocurrency, market players must be knowledgeable, keep a close eye on developments, and properly manage risk.

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Ali Malik

Ali Malik is an experienced crypto writer specialising in simplifying complex blockchain and cryptocurrency topics for a broad audience. With expertise in ICOs, Web3, DeFi, NFTs, and regulatory updates, he offers valuable insights to help readers make informed decisions. He is proficient in SEO optimisation.

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AI Agents in Web3: Risks and Real-World Asset Security

AI Agents in Web3

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Artificial intelligence (AI) and distributed Web3 technologies are collectively ushering in a revolutionary era for the internet. Redoing rethinking ownership, governance, and trust, decentralised autonomous systems are Autonomous artificial intelligence agents—software entities capable of completing complex tasks independently within blockchain networks—are at the core of this disturbance. Although their promise is enormous, their increasing influence has special hazards, particularly in terms of cybersecurity protection and management of Real-World Assets (RWAs). Understanding these hazards and reducing them becomes essential for Web3’s long-term survival as it develops.

Autonomous AI Agents in Web3

Designed to function independently depending on pre-defined goals and real-time data inputs, AI Agents in Web3 operate both on-chain and off-chain. They handle tasks including data processing, protocol maintenance, automated trading, and voting for governance. Combined with distributed apps (dApps) and smart contracts, they expedite decision-making and eliminate intermediaries.

Major blockchain systems, including Ethereum, Polkadot, and Solana, are testing artificial intelligence (AI) agents integrated into distributed finance (DeFi) systems and DAOs (decentralized autonomous organizations). These agents often utilize natural language processing (NLP) and reinforcement learning models to examine and react to ideas related to community governance, user behavior, and market dynamics.

Autonomous AI Agents in Web3But as AI agents acquire autonomy, their opacity rises. Predicting or controlling their decisions becomes challenging without unambiguous audit trails or explainability systems. Failure or abuse of these agents can spread throughout dispersed systems, leading to financial losses, misbehavior, and a more general societal collapse.

Tokenizing Real-World Assets Risks

One of Web3’s most aspirational areas is tokenizing real-world assets. Blockchain-based currencies are distributing digital versions of RWAs, including property titles, goods, carbon credits, and even art. These tokens enable liquidity, broader participation, and real-time trading by reflecting fractional ownership or claims on the underlying actual assets.

By funding loans backed by real-world assets, initiatives such as Centrifuge, Goldfinch, and Maple Finance have made progress in bringing real-world assets (RWAs) to DeFi. With firms like BlackRock and Franklin Templeton exploring blockchain rails for asset management, institutional adoption is gaining momentum.

However, the interface separating the physical and digital domains raises technological, legal, and operational concerns. Decentralized challenges environments challenge determining legal owners, ensuring orders, guaranteeing consistency, and controlling counterparty risk. Errors in algorithms or compromised data can have fatal results when artificial intelligence agents are assigned to engage with RWAs—for risk assessment, pricing, or allocation—in whatever capacity. For instance, an inaccurate asset appraisal by an artificial intelligence oracle could misprice a loan’s collateral, resulting in unwarranted liquidations or the creation of systemic lending risk.

Emerging Threats of AI in Decentralized Systems

Adversarial cues, poisoned data, or corrupted training sets allow autonomous agents interacting directly with smart contracts to be controlled. A malevolent actor might, for instance, include biased data in an artificial intelligence’s training set, therefore affecting its behavior and leading it to act against the protocol’s interests. In permissionless settings where data provenance is difficult to verify, this type of data poisoning poses a significant risk.

Moreover, AI agents themselves could initiate attacks. Arbitrage trading and sniping NFT mints both already employ AI-powered bots. These bots might automate highly flexible attacks, such as phishing campaigns at scale or exploiting unpatched vulnerabilities in smart contracts, when paired with deep learning models.

AI agent impersonation is yet another developing issue. We could model human community members or developers in DAO governance venues or Discord groups using sophisticated language models. Artificial intelligence can alter the outcome of votes, influence public opinion, or lead to anarchy in decentralised societies.

This new scene calls for the adaptation of defensive measures, including formal verification, artificial intelligence for threat detection, zero-knowledge proofs (ZKPs), and multi-factor authentication. Still, the rate of innovation is faster than the deployment of appropriate protection can keep pace with.

Legal and Ethical Challenges of AI Agents in Web3

Utilising AI agents in Web3 raises significant legal concerns. When an artificial intelligence agent conducts a damaging transaction, who is responsible? Given the pseudonymous nature of the code among the players involved, how would you enforce legal decisions? Current legal systems mostly leave these concerns unresolved.

Legal and Ethical Challenges of AI Agents in Web3Global authorities are starting to see the necessity for control, including the European Union with its AI Act and the U.S. SEC’s exploratory posture on DeFi. However, with blockchain systems, artificial intelligence agents can operate across multiple countries and outside the purview of any single authority, thereby complicating enforcement.

Ethically, algorithmic bias, lack of transparency, and AI governance raise increasing concerns. In distributed systems that value group decision-making, allowing autonomous agents to influence crucial decisions without transparency undermines the fundamental principles of Web3 democracy.

Safeguarding Web3 with Accountable AI

Stakeholders must employ a multi-pronged strategy to protect the viability of Web3. AI model transparency needs to improve first. Blockchain-based systems could incorporate initiatives around Explainable AI (XAI) to give consumers and auditors information on how AI agents arrive at their conclusions.

Secondly, we need to develop systems of community supervision. DAOs could establish AI  trustees,” elected human monitors with the authority to halt or supersede AI-driven initiatives. In complex governance situations, these trustees can act as operational and ethical guiderails.

Third, developers of blockchains, artificial intelligence researchers, and cybersecurity analysts must naturally collaborate. Red-team simulations, adversarial testing environments, and bug bounty programs should all be considered investments in protocols that stress both artificial intelligence logic and smart contract security.

Final thoughts

Including AI agents in the Web3 ecosystem provides a glimpse into an era of unprecedented efficiency and automation. However, this development poses significant risks, especially when managing Real-World Assets and operating within inherently fragile distributed networks.

Now we must address weak cybersecurity, regulatory uncertainty, and ethical conundrums to prevent catastrophes, as harnessing the benefits would erode confidence in the enterprise and uphold the paradigm. Through encouraging responsible innovation,decentralised lleverage artificiallintelligence while maintaining its fundamental values of openness, security, and decentralisationn

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