Crypto Prices Soar Across the Global Market, Year-End Enthusiasm?

TheNewsCryptoPubblicato 2025-12-29Pubblicato ultima volta 2025-12-29

Introduzione

Cryptocurrency prices have surged across the global market, with the total market cap briefly surpassing the $3 trillion milestone. Bitcoin (BTC) reclaimed the $90k level, rising 2.74% to $90,023.28, with predictions suggesting it could reach around $103,282 in the next three months. Ethereum (ETH) broke the $3,000 barrier, increasing 2.64% to $3,014.26, and is projected to potentially hit $5,385.25. Other major tokens like BNB, SOL, LINK, and ZEC also saw gains. The meme coin segment followed the bullish trend, with DOGE and SHIB rising 2.21% and 1.11%, respectively. PEPE and MemeCore (M) also recorded increases. Looking ahead, predictions for early 2026 remain optimistic, with BTC potentially reaching a new all-time high of $126,198.07 by year-end and ETH possibly reclaiming its previous peak of $4,953.73. The article emphasizes that crypto investments are volatile and require thorough research and risk assessment.

The year-end seems to be drawing the attention of investors, considering crypto prices are up. BTC and ETH have recovered in the last 24 hours. The global crypto market briefly teased a major milestone. The meme coin segment reflected the bullish sentiments triggered by the likes of Bitcoin and Ethereum tokens.

Crypto Prices Over 24 Hours

The global crypto market cap briefly surpassed the $3 trillion milestone. This was possibly triggered by the rising interest in tokens like BTC and ETH. Bitcoin price went as high as $90,023.28, up by 2.74% in the last 24 hours, to reclaim the $90k milestone. The token is now projected to surge by 16.99% in the next 3 months to reach around $103,282.

ETH price has also breached the much anticipated milestone of $3k by reaching $3,014.26, up by 2.64% over the last 24 hours. Its market cap has surged by 3.13% and the 24-hour trading volume is up by 119.42%. Ether is, notably, predicted to outperform BTC by reaching $5,385.25 in the next 3 months. This would be a jump of 77.02%.

BNB and SOL are the next tokens to have jumped by 2.01% and 2.89%, respectively, in the last 24 hours. LINK and ZEC have soared by 2.75% and 2.79%, applicable in the same order, during the same timeline.

Meme Coin Segment Notes Upswing

The effects are evident across the meme coin segment as well. Prices of major tokens have jumped, like DOGE by 2.21% and SHIB by 1.11% over the past 24 hours. Their respective values are now $0.1268 and $0.000007451. Interestingly, SHIB remains one of the top choices for investments looking for low-cost entry alternatives.

DOGE and SHIB are the most-talked-about meme coins at the moment. They are joined by PEPE, which is up by 1.05% in the last 24 hours. However, the frog-themed meme coin has jumped massively by 4.88% in the last 7 days. MemeCore (M) recently reached the 3rd position on the meme coin chart in terms of market cap. It is now trading at $1.49, up by 0.66% in the last 24 hours.

What to Expect in 2026?

Cryptocurrencies are performing well in the year-end timeline. BTC price prediction and ETH price prediction for the first 3 months of 2026 are bullish. Meme coins are likely to follow the trend. Long term prediction underlines the possibility for tokens to reclaim their ATH.

BTC, for instance, could reach $126,198.07 to pave the way for a new ATH by the end of 2026. Similarly, ETH could reclaim its ATH of $4,953.73, which was last noted on August 25, 2025. That said, it is important to note that crypto investments are subject to volatility. Thorough research and risk assessment are important before crypto investments.

Highlighted Crypto News Today:

Coinbase CEO Brian Armstrong Says Bitcoin Acts as a Check on the US Dollar

TagsBTCCryptoETHMEME Coins

Domande pertinenti

QWhat was the global crypto market cap milestone briefly surpassed according to the article?

AThe global crypto market cap briefly surpassed the $3 trillion milestone.

QWhat are the predicted price targets for Bitcoin and Ethereum in the next 3 months?

ABitcoin is projected to reach around $103,282, and Ethereum is predicted to reach $5,385.25 in the next 3 months.

QWhich two meme coins are mentioned as the most-talked-about and what were their 24-hour price increases?

ADOGE, which was up by 2.21%, and SHIB, which was up by 1.11%, are mentioned as the most-talked-about meme coins.

QWhat does the article say about long-term predictions for Bitcoin and Ethereum by the end of 2026?

AThe article states that Bitcoin could reach $126,198.07 to set a new ATH, and Ethereum could reclaim its ATH of $4,953.73 by the end of 2026.

QAccording to the highlighted news, what did Coinbase CEO Brian Armstrong say about Bitcoin?

ACoinbase CEO Brian Armstrong said that Bitcoin acts as a check on the US Dollar.

Letture associate

Gate Research Institute: The 'Wall Street-ization' Wave of Crypto Financial Products – Competition or Integration?

The article titled "Gate Research Institute: Are Crypto Financial Products Sparking a 'Wall Street' Wave—Competition or Convergence?" explores the evolving relationship between the crypto ecosystem and traditional finance (TradFi). The piece begins by reflecting on Bitcoin's original 2009 vision of decentralization, disintermediation, and moving away from banks. It then contrasts this with the 2024 landscape, where key crypto assets like Bitcoin are increasingly held through Wall Street products like ETFs issued by giants like BlackRock. The article questions whether this signifies that TradFi is systematically taking over the rights to issue, price, custody, and distribute crypto financial assets. The core argument is that this is not a zero-sum takeover but rather a bidirectional convergence where each side addresses the other's weaknesses. Crypto offers 24/7 global markets, programmable settlement, and open access but lacks compliant channels, institutional-grade custody, deep fiat liquidity, and mainstream distribution. TradFi possesses these but is constrained by legacy systems, limited operating hours, and slow settlement. Two primary convergence paths are highlighted: * **Path A (CEX to TradFi):** Exemplified by Gate, which has progressed from offering tokenized stocks and CFDs to providing direct, real stock trading (US, Hong Kong, South Korea) within its platform, using USDT. * **Path B (TradFi to Crypto):** Exemplified by Robinhood, which has integrated crypto trading, acquired exchanges like Bitstamp, and is moving traditional assets like stocks onto the blockchain via tokenization and its own Layer 2. Both paths are ultimately competing to become the next-generation, unified financial account—a "super account" where users can seamlessly trade cryptocurrencies, stocks, ETFs, RWA (Real World Assets), and tokenized treasury products in one interface. The growth of RWA and tokenized treasuries (e.g., BlackRock's BUIDL) is presented as the asset-layer fusion, providing stable, yield-bearing assets on-chain and acting as a bridge between the two worlds. In conclusion, the "Wall Street-ization" of crypto is framed as a mutual transformation. Decentralized ideals persist in the protocol layer, while at the application layer, a more efficient, global, and accessible unified capital market is emerging from this convergence. The future competition lies not between crypto exchanges and stockbrokers, but between platforms vying to offer the most comprehensive asset coverage, liquidity, and user experience within a single account.

marsbit4 min fa

Gate Research Institute: The 'Wall Street-ization' Wave of Crypto Financial Products – Competition or Integration?

marsbit4 min fa

Claude's Major New Feature: Screen Recording + Voice, Distilling Your Skills into AI Tasks in One Click

Claude has introduced a major new feature called "Record a Skill," available for Pro, Max, and Team users. This function, found in the Claude desktop app's CoWork menu, allows users to create reusable AI skills simply by recording their screen and providing voice narration while performing a task. Claude then automatically analyzes the recording and generates a functional Skill. A hands-on test confirmed the feature works seamlessly. Users start recording via the Skills manager, perform their workflow while verbally explaining the steps and logic, and avoid including sensitive information. After recording, Claude processes the content and creates the Skill, which can be saved and later invoked with a slash command (/). This eliminates the need for manual adjustments or writing complex instruction files. The innovation goes beyond mere efficiency. Previously, creating a Skill required writing a detailed SKILL.md file in Markdown—a significant barrier for non-technical users. "Record a Skill" bypasses this by directly capturing both actions and the implicit reasoning shared in the narration. This lowers the barrier to knowledge transfer and automation, addressing a core challenge in corporate knowledge management: the difficulty of getting experts to write and maintain documentation. However, the feature also highlights a shift in the nature of work. A case study from March 2026 showed a freelancer whose five-year client relationship was effectively replaced by a hand-coded Claude Skill automating their content workflow. With the even lower barrier of screen recording, the ability to distill personal expertise into automatable skills accelerates this trend. The "moat" for work is moving from simply knowing how to do a task to mastering tasks that are difficult or impossible to automate.

marsbit8 min fa

Claude's Major New Feature: Screen Recording + Voice, Distilling Your Skills into AI Tasks in One Click

marsbit8 min fa

Feeding AI "Noise" Can Also Boost Scores, This Work Enables Positive Transfer with Noise

Feeding "Noise" to AI Can Improve Performance: A Method Enables Positive Transfer from Noise This work, Semi-Supervised Noise Adaptation (SSNA), introduces a Noise Adaptation Framework (NAF) that challenges traditional transfer learning. Instead of requiring a labeled source domain of real data (e.g., images, text), NAF uses randomly generated Gaussian noise as the source. For a target task with C classes, it constructs C noise clusters by sampling from Gaussian distributions. Although this synthetic noise contains no semantic meaning, NAF trains it to form a discriminative class structure in a shared representation space—clustering same-class noise and separating different classes. The key is aligning this learned structure from the noise domain to the real, sparsely labeled target domain. A small number of target labels are still essential to establish the correspondence between noise clusters and actual classes. The training objective combines: 1) supervised loss on the few labeled target samples, 2) classification loss for the noise to build its structure, and 3) a distribution alignment loss (using Negative Domain Similarity) to minimize the gap between the noise and target domains in the shared space. Experiments show significant gains in few-label settings. With just 4 labels per class, NAF with a ResNet-18 backbone improves accuracy over a standard supervised baseline (ERM) by +12.35% on CIFAR-10, +7.61% on CIFAR-100, +4.38% on DTD-47, and +2.74% on Caltech-101. It also benefits fine-grained datasets and scales to ImageNet-1K (with 100 labels/class) and text classification (AG News). NAF can be integrated into existing semi-supervised methods like FixMatch for further gains. Ablation studies confirm the transferred benefit comes from the discriminative structure of the noise, not randomness itself. Collapsing all noise into a single point causes negative transfer, while increasing separation between noise cluster centers improves performance. The amount of noise per class is less critical once a basic structure forms. In conclusion, this work demonstrates that for positive transfer, the semantic content of source data may not be necessary. What can be effectively transferred is the *organizational structure* of categories within a representation space. This offers a promising alternative for scenarios where real source data is unavailable due to privacy, copyright, or procurement constraints.

marsbit10 min fa

Feeding AI "Noise" Can Also Boost Scores, This Work Enables Positive Transfer with Noise

marsbit10 min fa

Trading

Spot
活动图片