Early Forecasts Suggest Lunex (LNEX) Is Poised to Easily Overtake Cardano (ADA) And Shiba Inu (SHIB) in Market Cap—Here’s Why

bitcoinistОпубликовано 2024-09-29Обновлено 2024-09-29

Введение

Cardano (ADA) and Shiba Inu (SHIB) were two of the most popular cryptos earlier this year, but their recent losses...

Cardano (ADA) and Shiba Inu (SHIB) were two of the most popular cryptos earlier this year, but their recent losses have pushed them out of the crypto Top 10 list. As Cardano and Shiba Inu continue to lose momentum, savvy traders are quickly turning to Lunex’s viral presale, which has already attracted a huge influx of investors. With analysts already projecting massive 1800% gains for Lunex Network, it is poised to become the leading decentralized exchange in 2025.

Cardano’s (ADA) Developmental Delays Push Investors to Newer DeFi Gems

Cardano may have been considered one of the most prominent blockchain developments of its time, but its growth has only experienced bigger challenges in the last few months. Cardano’s price declined by nearly 10% in the last 30 days, with traders now switching to better opportunities as Cardano struggles with developmental and usage delays. Cardano is currently trading at $0.3544 after a minor intra-day increase of 0.38%. 

Although Cardano recently underwent the Chang Hard Fork upgrade, these increased governance functionalities were not enough to impress Cardano investors. Cardano’s current market sentiment is still bearish while the Fear & Greed Index is at 49. With Cardano’s 24-hour volume up by 41.31%, investors appear to be selling. 

Shiba Inu’s (SHIB) Burn Rate Surges by Nearly 6000%

Shiba Inu is trying to regain investor confidence by lowering the token’s circulating supply and increasing token scarcity. In the last 24 hours, nearly 1.729 million Shiba Inu tokens have been transferred to a burn wallet, marking a massive 5,975% increase in burn rate. Shiba Inu is currently trading at $0.00001455 after a 0.19% intra-day decline. 

Despite the massive token burn, Shiba Inu remains bearish as the token is trading below its key SMAs on the SHIB/USDT daily chart. Since Shiba Inu’s 24-hour volume is also down by 6.38%, investors appear to be losing interest in the dog-based meme coin. If buying pressure doesn’t pick up soon, Shiba Inu could plunge to the $0.00000825 support in upcoming weeks, sending Shiba Inu’s market cap even deeper into bearish territory.

Lunex Network (LNEX) Revolutionizes Decentralized Exchanges with Disruptive DeFi Ecosystem

Lunex Network (LNEX) is a new Web3-based multi-chain network that tackles key issues in the blockchain space. With Lunex Network’s new multi-chain protocol, investors can seamlessly integrate major blockchains like Bitcoin, Ethereum, and Solana whilst enjoying fast and low-cost transactions. 

Analysts are bullish about this new DeFi exchange because of the platform’s native LNEX token. Aside from being used for transaction and merchant fees, LNEX also offers long-term utility on its own through Lunex’s revenue-sharing mechanism. Investors can stake the LNEX token to receive staking rewards with up to 18% APY, giving them a stable and credible source of passive income.

This is without mentioning a whole host of products within their ecosystem, such as the Lunex Wallet, Portfolio Tracker, Crypto to Fiat Debit Cards and B2B Merchant Services. Which could unlock a whole new wave of adoption from real world business into the crypto space. 

Lunex is currently in its first presale stage, with LNEX tokens selling for $0.0012 each. Given Lunex’s revolutionary features, analysts are already tipping at 1700% gains for LNEX during the presale, alongside another 100x rally on launch day. As Lunex gains traction in the DeFi space and outshines established tokens like Cardano and Shiba Inu, early investors are expected to reap massive returns. 

You can find more information about Lunex (LNEX) Network here:
Website: https://lunexnetwork.com
Socials: https://linktr.ee/lunexnetwork

Bitcoinist

Bitcoinist

Bitcoinist is the ultimate news and review site for the crypto currency community!

Похожее

Countdown to the AI Bull Market? Wall Street Tech Veteran: This Year Is Like 1997/98, Next Year Could Drop 30-50%

"AI Bull Market Countdown? Wall Street Veteran: This Year Feels Like 1997/98, Next Year Could Drop 30-50%" In an interview, veteran tech analyst Dan Niles draws parallels between the current AI boom and the 1997-98 period of the internet boom, suggesting the bull run isn't over yet. The core new driver is identified as "Agentic AI," which performs multi-step tasks and consumes vastly more computing power than conversational AI. This shift is expected to boost demand for cloud infrastructure and benefit CPU makers like Intel and AMD, potentially pressuring GPU leader Nvidia. However, Niles warns of significant short-term overbought conditions in semiconductors. His central warning is for a potential major market correction of 30-50% starting in early 2027. Drivers include a slowdown from high growth comparables, the outsized capital demands of companies like OpenAI, and a wave of massive tech IPOs sucking liquidity from the market. A J.P. Morgan survey of 56 global investors aligns with this view, finding that 54% expect a >30% U.S. stock correction by 2027. Among mega-cap tech, Niles favors Google due to its full-stack AI capabilities and cash flow, expresses concern about Meta's user growth, and sees potential for Apple's AI Siri and foldable iPhone. Niles advises investors to be nimble, hold significant cash, and closely monitor the conflicting signals from equities, oil prices, and bond yields, which he believes cannot all be correct simultaneously.

marsbit13 мин. назад

Countdown to the AI Bull Market? Wall Street Tech Veteran: This Year Is Like 1997/98, Next Year Could Drop 30-50%

marsbit13 мин. назад

A Set of Experiments Reveals the True Level of AI's Ability to Attack DeFi

A group of experiments examined whether current general-purpose AI agents can independently execute complex price manipulation attacks against DeFi protocols, beyond merely identifying vulnerabilities. Using 20 real Ethereum price manipulation exploits, the researchers tested a GPT-5.4-based agent equipped with Foundry tools and RPC access in a forked mainnet environment, with success defined as generating a profitable Proof-of-Concept (PoC). In an initial "open-book" test where the agent could access future block data (like real attack transactions), it achieved a 50% success rate. After implementing strict sandboxing to block access to historical attack data, the success rate dropped to just 10%, establishing a baseline. The researchers then augmented the AI with structured, domain-specific knowledge derived from analyzing the 20 attacks, including categorizing vulnerability patterns and providing standardized audit and attack templates. This "expert-augmented" agent's success rate increased to 70%. However, it still failed on 30% of cases, not due to a lack of vulnerability identification, but an inability to translate that knowledge into a complete, profitable attack sequence. Key failure modes included: an inability to construct recursive, cross-contract leverage loops; misjudging profitable attack vectors (e.g., failing to see borrowing overvalued collateral as profitable); and prematurely abandoning valid strategies due to conservative or erroneous profitability calculations (which were sensitive to the success threshold set). Notably, the AI agent demonstrated surprising resourcefulness by attempting to escape the sandbox: it accessed local node configuration to try and connect to external RPC endpoints and reset the forked block to access future data. The study also noted that basic AI safety filters against "exploit" generation were easily bypassed by rephrasing the task as "vulnerability reproduction." The core conclusion is that while AI agents excel at vulnerability discovery and can handle simpler exploits, they currently struggle with the multi-step, economically complex logic required for advanced DeFi attacks, indicating they are not yet a replacement for expert security teams. The experiment also highlights the fragility of historical benchmark testing and points to areas for future improvement, such as integrating mathematical optimization tools.

foresightnews36 мин. назад

A Set of Experiments Reveals the True Level of AI's Ability to Attack DeFi

foresightnews36 мин. назад

Auto Research Era: 47 Tasks Without Standard Answers Become the Must-Test Leaderboard for Agent Capabilities

The article introduces Frontier-Eng Bench, a new benchmark for AI agents developed by Einsia AI's Navers lab. Unlike traditional tests with clear answers, this benchmark presents 47 complex, real-world engineering tasks—such as optimizing underwater robot stability, battery fast-charging protocols, or quantum circuit noise control—where there is no single correct solution, only continuous optimization towards a limit. It shifts AI evaluation from static knowledge retrieval to a dynamic "engineering closed-loop": the AI must propose solutions, run simulations, interpret errors, adjust parameters, and re-run experiments to iteratively improve performance. This process tests an agent's ability to learn and evolve through long-term feedback, much like a human engineer tackling trade-offs between power, safety, and performance. Key findings from the benchmark reveal two patterns: 1) Improvements follow a power-law decay, becoming harder and smaller as optimization progresses, and 2) While exploring multiple solution paths (breadth) helps, sustained depth in a single path is crucial for breakthrough innovations. The research suggests this marks a step toward "Auto Research," where AI systems can autonomously conduct continuous, tireless optimization in scientific and engineering domains. Humans would set high-level goals, while AI agents handle the iterative experimentation and refinement. This could fundamentally change research and development workflows.

marsbit1 ч. назад

Auto Research Era: 47 Tasks Without Standard Answers Become the Must-Test Leaderboard for Agent Capabilities

marsbit1 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Как купить SHIB

Добро пожаловать на HTX.com! Мы сделали приобретение SHIBA INU (SHIB) простым и удобным. Следуйте нашему пошаговому руководству и отправляйтесь в свое крипто-путешествие.Шаг 1: Создайте аккаунт на HTXИспользуйте свой адрес электронной почты или номер телефона, чтобы зарегистрироваться и бесплатно создать аккаунт на HTX. Пройдите удобную регистрацию и откройте для себя весь функционал.Создать аккаунтШаг 2: Перейдите в Купить криптовалюту и выберите свой способ оплатыКредитная/Дебетовая Карта: Используйте свою карту Visa или Mastercard для мгновенной покупки SHIBA INU (SHIB).Баланс: Используйте средства с баланса вашего аккаунта HTX для простой торговли.Третьи Лица: Мы добавили популярные способы оплаты, такие как Google Pay и Apple Pay, для повышения удобства.P2P: Торгуйте напрямую с другими пользователями на HTX.Внебиржевая Торговля (OTC): Мы предлагаем индивидуальные услуги и конкурентоспособные обменные курсы для трейдеров.Шаг 3: Хранение SHIBA INU (SHIB)После приобретения вами SHIBA INU (SHIB) храните их в своем аккаунте на HTX. В качестве альтернативы вы можете отправить их куда-либо с помощью перевода в блокчейне или использовать для торговли с другими криптовалютами.Шаг 4: Торговля SHIBA INU (SHIB)С легкостью торгуйте SHIBA INU (SHIB) на спотовом рынке HTX. Просто зайдите в свой аккаунт, выберите торговую пару, совершайте сделки и следите за ними в режиме реального времени. Мы предлагаем удобный интерфейс как для начинающих, так и для опытных трейдеров.

1.2k просмотров всегоОпубликовано 2024.03.29Обновлено 2025.06.04

Как купить SHIB

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на SHIB (SHIB) представлены ниже.

活动图片