Greatest Wealth Transfer Is about To Happen For Altcoins, Analyst Warns

bitcoinistPublicado a 2026-03-28Actualizado a 2026-03-28

Resumen

An analyst warns that a major wealth transfer to altcoins may be imminent, despite their underperformance in the last bull run. Altcoins have been consolidating within a large wedge pattern since 2018, including during the 2021-2022 rally. The analyst, Cryptollica, suggests the altcoin market bottomed in 2025 and is poised for a breakout, predicting a potential 500% surge that could propel assets like Ethereum and Solana to new all-time highs. However, the Altcoin Season Index remains neutral at 50, well below the 75 threshold indicating a true altcoin season. With Bitcoin dominance still high at 58.8%, a full altcoin season typically requires a further drop in Bitcoin's market share.

One part of the last bull run that disappointed investors was the fact that altcoins seemed to completely fall behind against Bitcoin. Going by previous bull markets, the expectation was that altcoins would rally once the Bitcoin price topped, leading to the legendary ‘altcoin season.’ While there has been nothing like that since then, many in the space have still not given up hope of an altcoin season, predicting that it is only a matter of time before altcoins rally again.

Altcoins Are Getting Ready To Take Off

Crypto analyst Cryptollica shared a chart showing that altcoins have actually been trading in an interesting trend for a while. According to the post, these cryptocurrencies have been compressing inside a massive wedge, and this did not begin recently.

Cryptollica pointed out that the total altcoin market cap has actually been compressed inside this massive wedge since 2018. This would mean that it has been this way for more than seven years, and that even the explosive altcoin season that was experienced in 2021-2022 also happened inside of this massive wedge.

Using the same trend over the years, the crypto analyst point out that the altcoin market has actually bottomed back in 2025. A similar trend was seen in early 2021, after which followed a legendary altcoin season that saw various altcoins hitting multiple new all-time highs at rapid speed.

If the crypto analyst is correct and the altcoin market is about to break out of this wedge, then it would be very bullish for price. The analyst predicts an over 500% increase, which would mean the likes of Ethereum, Solana, and other altcoins would be hitting new all-time highs.

Altcoin Season Index Stays Neutral

The Altcoin Season Index measures how the top 100 altcoins are performing against Bitcoin. The more of the altcoins are performing better than Bitcoin, the higher the chances that the market is experiencing an altcoin season. This index charts the performance on a scale of 1-100, and in an altcoin season, the index sits above 75.

Presently, the index is sitting at 50, which means that altcoin season is still not here. The Bitcoin dominance has since dropped below 60%, but remains quite high at 58.8%. Hence, it is unlikely that the altcoin season is starting now. This is because an altcoin season usually happens when the Bitcoin dominance drops.

Altcoin market cap still below $3 billion | Source: Crypto Total Market Cap Excluding BTC on TradingView.com

Criptos en tendencia

CitreaCTR

wrapped stUSDTWSTUSDT

Velodrome FinanceVELODROME

BrevisBREV

PancakeSwapCAKE

JUSTJST

Preguntas relacionadas

QAccording to the analyst Cryptollica, what pattern has the total altcoin market cap been trading in since 2018?

AThe total altcoin market cap has been compressing inside a massive wedge pattern since 2018.

QWhat does the current Altcoin Season Index reading of 50 indicate about the market?

AAn Altcoin Season Index reading of 50 indicates that an altcoin season is not currently happening, as the index needs to be above 75 to signal an altcoin season.

QWhat is the predicted percentage increase for the altcoin market if it breaks out of the wedge, according to the analyst?

AThe analyst predicts an over 500% increase for the altcoin market if it breaks out of the wedge.

QWhat is the relationship between Bitcoin dominance and the start of an altcoin season, as mentioned in the article?

AAn altcoin season usually happens when the Bitcoin dominance drops, as it indicates that altcoins are outperforming Bitcoin.

QWhat significant event does the analyst compare the current altcoin bottom to, suggesting a similar outcome could happen?

AThe analyst compares the current altcoin market bottom to the one seen in early 2021, which was followed by a legendary altcoin season where many altcoins rapidly hit new all-time highs.

Lecturas Relacionadas

Upbit Rebalances 864B SHIB In Internal Wallet Move

South Korean cryptocurrency exchange Upbit moved a total of 864 billion SHIB (worth approximately $4 million) between its internal wallet addresses. The activity, involving transfers of 384 billion SHIB outbound and 480 billion SHIB inbound, occurred following a 36% SHIB price rally. On-chain data indicates this was a routine internal wallet rebalancing operation by the exchange, not a sell-off or liquidation event. The article cautions that while large on-chain transfers are highly visible, they require proper context and wallet labeling to interpret correctly. In this case, the movement between known Upbit addresses does not inherently signal a change in market supply or selling pressure for SHIB.

bitcoinistHace 8 min(s)

Upbit Rebalances 864B SHIB In Internal Wallet Move

bitcoinistHace 8 min(s)

Can Generative Models Finally Be Trained End-to-End? The Core Is a For Loop

This article introduces a novel training paradigm for generative models called Explorative Modeling (XM), which enables true end-to-end training. Traditionally, powerful generative models like autoregressive and diffusion models are not trained end-to-end. They are trained to predict a single small step but require iterative multi-step sampling for inference. This "exposure bias" leads to error accumulation and limits performance. The core challenge XM addresses is "mode blurring." In generative tasks, a single input (e.g., "generate a dog") corresponds to many valid outputs (multiple modes). Standard training objectives like reconstruction loss force the model to average these modes, producing unrealistic, blurry outputs. To avoid this, existing models break generation into many small, almost deterministic steps, sacrificing end-to-end training. XM tackles this by restructuring the training loop itself. Its key insight is to amplify "generative expressivity." For each training input, instead of generating one sample, the model generates K candidate outputs. Only the candidate closest to the real data is used for computing the loss and updating the model via backpropagation. This simple "best-of-K" mechanism is implemented as a short for-loop. By exploring multiple possibilities, the model learns to distribute its guesses across different modes rather than collapsing to their uninformative average. The paper demonstrates that "exploration" acts as a new, powerful scaling axis. Gains from XM increase with model size, data scale, and compute. Experiments show improvements in FID scores for image generation and significant efficiency gains, sometimes outperforming larger models without exploration. When pushed to the limit, XM enables fully single-step, end-to-end generative models. In robotics tasks, an "Explorative Policy" matched the performance of a 100-step Diffusion Policy with a single forward pass, drastically improving inference speed. While the best-of-K concept is not entirely new, the authors' contribution lies in formally understanding it as a direct method to boost generative expressivity without fragmenting the generation process. This work suggests that as models scale, enhancing exploration during training may become crucial for overcoming fundamental performance bottlenecks.

marsbitHace 8 min(s)

Can Generative Models Finally Be Trained End-to-End? The Core Is a For Loop

marsbitHace 8 min(s)

A Maximum of 20 Submissions Per Person? DeepMind Researcher Satirically 'Petitions' Against ICLR's New Rule

The International Conference on Learning Representations (ICLR) 2027 has introduced a new submission rule limiting authors to a maximum of 20 papers per conference. This policy, announced due to a 68% surge in submissions for ICLR 2026 that strained the review system, aims to ensure fair and informative peer review. Google DeepMind researcher Dan Roy responded with a sarcastic petition on X, calling the 20-paper cap "absurd" and claiming it would slow AI progress. His post mockingly argued that AI agents can now produce incremental research and that large language models (LLMs) already handle all reviewing, so output should be maximized. This satire critiques the broader trend of AI's role in academia, referencing a 2025 study that found about 21% of ICLR 2026 reviews were likely fully AI-generated. Roy's underlying point questions whether simply capping submissions addresses the systemic issue of AI potentially flooding conferences with agent-written papers and AI-assisted reviews. The debate highlights tensions between managing submission volume and maintaining research quality as AI tools become pervasive.

marsbitHace 13 min(s)

A Maximum of 20 Submissions Per Person? DeepMind Researcher Satirically 'Petitions' Against ICLR's New Rule

marsbitHace 13 min(s)

Coldcard Vulnerability Leads to $89 Million Theft, Sparking Largest On-Chain Migration Since FTX Collapse

A security vulnerability in Coldcard hardware wallets led to the theft of 1,367.05 BTC (approx. $89 million) from 4,585 addresses, according to Galaxy Research. The flaw, caused by insufficient randomness in seed phrase generation for specific firmware versions, triggered a massive migration of funds as users moved assets to new, secure wallets. This event caused the largest on-chain movement of small Bitcoin transactions since the FTX collapse, distorting key market indicators like active addresses and exchange deposits, and significantly dampening market sentiment. The incident also highlighted challenges in cybersecurity investigations, as researchers reported that safety guardrails on mainstream U.S. AI models hindered the analysis of attack patterns, forcing them to use an open-source Chinese AI model for forensic work. This underscores a dilemma in balancing AI security restrictions with the need for rapid response in tracing stolen crypto assets.

marsbitHace 58 min(s)

Coldcard Vulnerability Leads to $89 Million Theft, Sparking Largest On-Chain Migration Since FTX Collapse

marsbitHace 58 min(s)

Annual Salary of Millions Competing for Electricians, Meta Rushes to Open Its Own Technical School

The AI boom is facing an unexpected bottleneck: a severe shortage of skilled construction workers and electricians. As tech giants like Meta, OpenAI, and Alphabet race to build massive data centers—such as OpenAI's $16 billion "Stargate" project—they are hitting a critical labor wall. The U.S. needs an estimated 130,000 more electricians, 240,000 construction workers, and 150,000 supervisors by 2030 for AI infrastructure alone, but tens of thousands of electrician jobs go unfilled each year. While AI companies offer high premiums, with electricians earning up to $280,000 annually, worker scarcity still causes massive losses—delays on a single project can cost $14.2 million per month. The complexity of building AI data centers, which require immense power (equivalent to powering hundreds of thousands of homes), sophisticated electrical systems, and advanced liquid cooling solutions, demands highly skilled technicians who are in short supply. To combat this, companies are investing heavily in training. Meta has committed $115 million to a free training school offering tuition, housing, and stipends, targeting 5,000 new workers. OpenAI is partnering with unions to secure skilled labor. These efforts are paying off, with a significant rise in Gen Z interest in trade schools over college. However, the power demands are staggering. AI data centers are driving a rapid surge in electricity consumption, projected to account for up to 12% of U.S. power use by 2028 and raising costs for consumers. Furthermore, the construction boom is project-based, leading to a potential future glut of trained workers once building peaks, which could depress wages industry-wide. The race for AI supremacy now depends as much on skilled hands as on advanced chips.

marsbitHace 1 hora(s)

Annual Salary of Millions Competing for Electricians, Meta Rushes to Open Its Own Technical School

marsbitHace 1 hora(s)

Trading

Spot

Artículos destacados

Cómo comprar ONE

¡Bienvenido a HTX.com! Hemos hecho que comprar Harmony (ONE) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar Harmony (ONE) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu Harmony (ONE)Después de comprar tu Harmony (ONE), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear Harmony (ONE)Tradear fácilmente con Harmony (ONE) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

405 Vistas totalesPublicado en 2024.12.12Actualizado en 2026.06.02

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de ONE (ONE).