TAO, NEAR, and Other AI Cryptocurrencies Record Heavy Losses

TheNewsCryptoPublicado em 2026-03-19Última atualização em 2026-03-19

Resumo

TAO and NEAR, along with other major AI cryptocurrencies, have recorded significant losses in the past 24 hours. TAO dropped nearly 10.12% to $247.80, while NEAR declined by 5.53%. Other AI tokens like ICP and RENDER also fell by 4.16% and 7.02%, respectively. Despite these daily losses, some, including TAO and RENDER, still show weekly gains. Both TAO and NEAR are forecasted to decline further in the next three months. The broader market downturn coincides with reports that Iran is considering imposing transit fees on ships passing through the Strait of Hormuz, raising concerns about rising shipping costs and their potential economic impact.

TAO and NEAR have lost significant values in the last 24 hours. Their decline aligns with the general downtrend across the crypto market. However, many more AI cryptocurrencies have also shed their respective values. This comes at a time when Iran is considering imposing transit fees via the Strait of Hormuz – triggering high price concerns.

TAO and NEAR

TAO has lost almost 10.12%, going down to $247.80 when the article is being drafted. Even the hourly loss comes to 1.24% for a significant level. However, the Bittensor token has added 16.28% in gains over the last 7 days. It remains in the top position with a market cap of more than $2.67 billion.

Sailing on the same ship is the NEAR Protocol token, NEAR. It is down by 5.53% over a day and 0.10% over an hour. The AI crypto seems to have held its ground strongly compared to TAO at the moment. It still lags when talking about the weekly gain because the addition is only 2.05%.

Interestingly, TAO and NEAR are forecasted to decline in the next 3 months as well. The former could plunge by 23.08% to around $191.08. The latter could plummet by approximately 11.99% to $1.19 from $1.35.

Other AI Cryptocurrencies

Other top AI cryptocurrencies that are down are ICP and RENDER. They have lost 4.16% and 7.02%, respectively, in a single day. Their values now translate to $2.52 and $1.65, applicable in the same order. ICP stands out among the top 4 AI tokens, as it has recorded a weekly loss of 2.85%. RENDER, like TAO and NEAR, has recorded a gain of 3.09%.

FIL, the Filecoin token, also stands out with an hourly gain of 0.05%. Its weekly gain is decent at 5.34%, and loss over the last 24 hours stands at 3.95%.

Transit Fees by Iran

Iran is reportedly considering the imposition of transit fees for ships that pass through the Strait of Hormuz. If imposed, every passage will have to pay tolls and taxes to Iran, which could add to the total shipping cost.

This seems to be applicable to states that have sanctioned it. An official confirmation or update regarding the matter is awaited. The report, anyway, remains a concern, given that Crude Oil price and Brent have already reached $97.41 and $113.71, respectively.

Highlighted Crypto News Today:

US Court Dismisses Coinbase User’s IRS Summons Challenge

Perguntas relacionadas

QWhat are the percentage losses for TAO and NEAR in the last 24 hours?

ATAO has lost almost 10.12% and NEAR is down by 5.53% in the last 24 hours.

QWhat is the forecasted price decline for TAO and NEAR over the next 3 months?

ATAO is forecasted to plunge by 23.08% to around $191.08, and NEAR could plummet by approximately 11.99% to $1.19.

QWhich other top AI cryptocurrencies, besides TAO and NEAR, have recorded losses?

AOther top AI cryptocurrencies that are down are ICP, which lost 4.16%, and RENDER, which lost 7.02% in a single day.

QWhat global event is mentioned as a potential factor contributing to market concerns?

AIran is reportedly considering imposing transit fees for ships passing through the Strait of Hormuz, which could increase shipping costs and is a market concern.

QWhich AI token mentioned in the article has recorded a weekly loss?

AICP stands out among the top AI tokens as it has recorded a weekly loss of 2.85%.

Leituras Relacionadas

Sequoia Dialogue with Jensen Huang: Computing Model Undergoes a 60-Year Transformation; You Won't Be Replaced by AI, But You Will Be Dimensionality-Reduced by 'Those Who Master AI'

NVIDIA founder and CEO Jensen Huang, in a conversation with Sequoia Capital's Konstantine Buhler, argues that we are witnessing the most significant computing shift in 60 years—from retrieval-based to generative computing. Instead of just storing and retrieving data, future systems will generate highly personalized content (text, images, video) on demand, powered by massive "AI factories." Huang envisions a global "intelligence network" that will envelop the planet, following the historical patterns of energy and communication grids. He outlines a five-layer investment framework: 1) Energy, 2) Chips/Computers, 3) Infrastructure (data centers), 4) AI Models, and 5) Applications. He predicts this ecosystem will reach a scale of $20 trillion annually. Crucially, Huang pushes back against fears of AI-driven job loss. He distinguishes between specific "tasks" (e.g., typing, analyzing images) and overall "jobs" (e.g., CEO, radiologist). While AI automates tasks, it increases efficiency and demand for the higher-value problem-solving aspects of professions, thus creating more jobs and "up-leveling" careers. The real risk, he asserts, is not being replaced by AI, but being outperformed by someone who effectively leverages it. He urges everyone to embrace AI as a tool for augmented capability and innovation.

marsbitHá 25m

Sequoia Dialogue with Jensen Huang: Computing Model Undergoes a 60-Year Transformation; You Won't Be Replaced by AI, But You Will Be Dimensionality-Reduced by 'Those Who Master AI'

marsbitHá 25m

"I Don't Need a Better Model Anymore": A Panorama of AI Users Under a Reddit Hot Post

Titled "I Don't Need a Better Model Anymore": AI User Reactions on Reddit Anthropic recently released Claude Fable 5, its first publicly available 'Mythos'-tier model, achieving 80.3% on the SWE-Bench Pro benchmark and significantly outperforming its predecessor and competitors. However, a viral Reddit post titled "Claude Fable made me realize I don't need better models anymore" highlighted a growing user sentiment of "good enough." Top comments expressed "model fatigue," with users stating that earlier models like Opus 4.5/4.8 already sufficed for their workflows. High cost was a key concern, as Fable 5's API is nearly twice the price of Opus 4.8, with users questioning the return on investment and suggesting the field has hit a plateau. The most frequent complaint targeted Fable 5's stringent safety filters. Designed to intercept high-risk requests (e.g., cybersecurity), the system was perceived as overly conservative. Users reported frequent rejections for routine security-related tasks, leading to automatic fallbacks to the older Opus model. Paying users were particularly frustrated, feeling they paid a premium for a less usable product. Dissenting voices came from users with heavy, complex tasks. For workloads like high-energy physics simulations with thousands of code lines, Fable 5's improved long-context understanding and error detection represented a significant, worthwhile leap—described as moving from a "college player to an NBA starter." The debate underscores a divergence between benchmark performance and practical utility. For most users, current models meet their needs, making further advances relevant only for extreme use-cases. The discussion also raised concerns about a potential "Public AI Freeze," where the most powerful models (like the restricted Mythos 5) remain exclusive to enterprises and governments, while public offerings stagnate. The launch presents two report cards: one of technical excellence and another of user skepticism. Fable 5's ultimate reception may depend on Anthropic's ability to refine its safety filters and justify its cost for specialized, high-demand users.

marsbitHá 32m

"I Don't Need a Better Model Anymore": A Panorama of AI Users Under a Reddit Hot Post

marsbitHá 32m

When AI Traffic Surpasses Humans, How Do You Prove You're Human?

With AI-generated web traffic surpassing human activity, websites face a crisis as AI agents bypass ads, avoid clicks, and scrape data without generating revenue. This disrupts the ad-based internet economy, diverting traffic and reducing site visits. In response, sites are blocking AI crawlers and deploying traps like Cloudflare's "honeypot" pages. Traditional CAPTCHAs are now ineffective against advanced AI. The focus has shifted to behavioral biometrics—analyzing unique human patterns such as cursor movement, typing rhythm, and keystroke dynamics. Companies like IBM and BioCatch use this data to distinguish humans from bots, even detecting fraud through behavioral inconsistencies. Two competing approaches aim to verify human identity centrally. Sam Altman’s World (formerly Worldcoin) uses iris scanning to create unique credentials, though it faces privacy concerns and regulatory bans. Alternatively, cryptographic zero-knowledge proofs offer anonymous verification without revealing personal data, championed by Vitalik Buterin to avoid centralized surveillance. However, both systems have flaws. Centralized solutions risk biometric data misuse, while decentralized models may be exploited through identity rental markets in economically unequal regions. Despite challenges, the author favors cryptographic methods for preserving privacy over pervasive behavioral monitoring that permanently captures and controls personal biometric data.

marsbitHá 41m

When AI Traffic Surpasses Humans, How Do You Prove You're Human?

marsbitHá 41m

2026 Landscape of Decentralized AI: Why is Blockchain the Inevitable "Antidote" for AI?

**The 2026 Landscape of Decentralized AI: Why Blockchain is the "Cure" AI Cannot Ignore** Decentralized AI addresses fundamental bottlenecks of centralized AI: scarce and expensive computational resources, excessive control concentration, unverifiable model outputs, and increasing difficulty in acquiring training data due to privacy and regulation. Blockchain offers a path to make intelligence open, verifiable, and economically accessible. The technical stack comprises three layers: 1. **Applications & Services**: The main crypto use cases are "Agentic Finance" (converting natural language into on-chain actions) and "Agentic Payments" for machine-to-machine commerce. Projects like Giza, Infinity Labs, Coinvest AI, and x402 (handling 173M+ transactions) are key players. 2. **Middleware**: This coordination layer enables agents to discover, identify, and transact. Notable projects include Gokite AI (specialized L1), Virtuals (an OS for the agent economy), and especially Bittensor—a network of specialized subnets forming competitive AI micro-economies. 3. **Infrastructure**: The capital-intensive layer providing raw resources. It includes decentralized compute (Akash, Render, Aethir), verifiable inference (Venice AI, OpenGradient), distributed training (Prime Intellect, Templar AI), decentralized storage (Filecoin, Walrus), and privacy/verification layers (Nillion, Arcium, Phala Network) using technologies like ZKPs, MPC, and TEEs. The outlook for 2026-2027 indicates AI demand outpacing infrastructure, with AI agents as a primary growth engine. Computation is becoming an asset class, with on-chain markets as its financial layer. Tokenomics is emerging as a structural advantage for coordinating capital, compute, and data in decentralized AI networks. While still early—with adoption uneven and revenue often trailing token incentives—projects like Bittensor, NEAR, and Virtuals demonstrate a shift from speculative narrative to a new model for coordinating intelligence.

marsbitHá 44m

2026 Landscape of Decentralized AI: Why is Blockchain the Inevitable "Antidote" for AI?

marsbitHá 44m

a16z Crypto Partner: Cash Flow is the Moat

Cash Flow as the Moat: A Playbook for Crypto Founders Historically, the most enduring businesses have been built by positioning themselves within the "flow of funds"—facilitating the creation and transfer of value in a network and extracting a portion of it. Cryptocurrency is the first modern technology natively built for this purpose. For startups, failing to architect products and businesses to leverage these principles means missing a major opportunity. Blockchains are inherently network businesses. Each transaction settles on a shared ledger, and every new participant strengthens the underlying network for all. Well-designed network tokens amplify this by aligning users, developers, and validators around growing the network, with value flowing back to contributors in a transparent feedback loop. This model is not new; companies from railroads and Standard Oil to Google, Meta, and AWS have thrived by inserting themselves into critical flows of value (goods, attention, compute). Financial markets make it even clearer: firms like Visa and major market makers generate immense revenue not by predicting markets but by being in the path of transactions. The combination of fund flow and network effects creates one of the most durable business structures. The high margins in traditional finance (payments, custody, lending, FX) represent prime targets. Crypto founders have the opportunity to build the next version—programmable, instant, global, and natively in the flow of funds. The frontier extends beyond finance to areas like computing/GPUs, AI training data, energy, robotics, and space—markets without entrenched intermediaries, ripe for building new, efficient value rails on programmable infrastructure. Founders should ask: Are you in the flow of funds today? Does your revenue scale 10x with the value of activity on your platform? Where in your target market are profit margins highest relative to value created? The opportunity is clear: embed your startup into the new flows of value and let the network effects accumulate.

marsbitHá 46m

a16z Crypto Partner: Cash Flow is the Moat

marsbitHá 46m

Trading

Spot

Futuros

Artigos em Destaque

Como comprar AL

Bem-vindo à HTX.com!Tornámos a compra de Archloot (AL) simples e conveniente.Segue o nosso guia passo a passo para iniciar a tua jornada no mundo das criptos.Passo 1: cria a tua conta HTXUtiliza o teu e-mail ou número de telefone para te inscreveres numa conta gratuita na HTX.Desfruta de um processo de inscrição sem complicações e desbloqueia todas as funcionalidades.Obter a minha contaPasso 2: vai para Comprar Cripto e escolhe o teu método de pagamentoCartão de crédito/débito: usa o teu visa ou mastercard para comprar Archloot (AL) instantaneamente.Saldo: usa os fundos da tua conta HTX para transacionar sem problemas.Terceiros: adicionamos métodos de pagamento populares, como Google Pay e Apple Pay, para aumentar a conveniência.P2P: transaciona diretamente com outros utilizadores na HTX.Mercado de balcão (OTC): oferecemos serviços personalizados e taxas de câmbio competitivas para os traders.Passo 3: armazena teu Archloot (AL)Depois de comprar o teu Archloot (AL), armazena-o na tua conta HTX.Alternativamente, podes enviá-lo para outro lugar através de transferência blockchain ou usá-lo para transacionar outras criptomoedas.Passo 4: transaciona Archloot (AL)Transaciona facilmente Archloot (AL) no mercado à vista da HTX.Acede simplesmente à tua conta, seleciona o teu par de trading, executa as tuas transações e monitoriza em tempo real.Oferecemos uma experiência de fácil utilização tanto para principiantes como para traders experientes.

293 Visualizações TotaisPublicado em {updateTime}Atualizado em 2026.06.02

Discussões

Bem-vindo à Comunidade HTX. Aqui, pode manter-se informado sobre os mais recentes desenvolvimentos da plataforma e obter acesso a análises profissionais de mercado. As opiniões dos utilizadores sobre o preço de AL (AL) são apresentadas abaixo.