Renowned Trader GCR Sets Ethereum Price Target at $10,000, Here’s How High INTL and SHIB Can Go

bitcoinistPubblicato 2024-11-15Pubblicato ultima volta 2024-11-15

Introduzione

Popular crypto trader Gigantic-Cassocked-Rebirth (GCR) has recently made waves in the market by predicting that the Ethereum price will hit...

Popular crypto trader Gigantic-Cassocked-Rebirth (GCR) has recently made waves in the market by predicting that the Ethereum price will hit $10,000. With ETH on the rise, focus is shifting to other popular tokens such as Shiba Inu (SHIB) and IntelMarkets (INTL) to potentially replicate the same performance as Ethereum.

With SHIB’s strong community and INTL’s recent presale performance, many are speculating just how high these altcoins might climb. Let’s explore the factors driving these predictions and what it could mean for crypto investors watching ETH, SHIB, and INTL closely.

Ethereum Price Set to Soar? GCR’s $10,000 ETH Prediction Has Crypto Buzzing

GCR, who has been quite accurate in his trading predictions, has come out with a $10,000 Ethereum price target. He believes ETH will climb since it was one of the first cryptocurrencies connected with DeFi and more corporations are using blockchain technology. GCR views Ethereum as a prominent crypto market participant because of Ethereum 2.0 improvements and other factors, ensuring its continued success.

GCR has also placed inflationary policies and continued money printing as the reason for expecting the Ethereum price to rise. As inflation deteriorates traditional investments, ETH emerges as a hedge to push the Ethereum price to GCR’s ambitious figure.

Furthermore, GCR has a track record of making accurate predictions regarding various events including political events and even the memecoin fluctuations, adding credibility to his ETH price prediction. With Ethereum price appreciation, investors are inclined to buy ETH in an attempt to benefit from the expected appreciation.

Shiba Inu’s Epic Rally: Can SHIB Break the $0.000028 Barrier?

Over the past week, Shiba Inu (SHIB) has surged over 40%, reaching its highest value in six months at $0.000027. The memecoin is now eyeing $0.000030 as a potential resistance level. If such buying pressure remains, Shiba Inu may break this level and open the door for immediate upside.

Metrics derived from on-chain data reveal evidence of rising activity with the seven-day active addresses for Shiba Inu increasing by 346 % while the newly created addresses have surged 458%. This tremendous increase in the activity of the SHIB network proves that more investors are participating in the Shiba Inu market.

Additionally, SHIB’s open interest has reached $108.44 million. As both open interest and network activity continue to grow, Shiba Inu bulls appear poised for a potential breakout above the $0.000030 level.

Intel Markets Set to Soar: GCR’s Bold Ethereum Target Sparks Excitement in Third Presale Stage

Renowned trader GCR’s $10,000 Ethereum price estimate has rekindled crypto enthusiasm in the crypto market. With its current price at $0.046, IntelMarkets is well-positioned to capitalize on this momentum, with expectations of a significant price increase in the coming days.

Driving this surge is Intel Markets’ unique Intelli-M™ robots, which sets it apart. Unlike conventional trading bots, these self-learning robots analyze real-time data, learning from mistakes to refine their performance with each trade. This adaptive approach, combined with increasing trade frequency, aims to optimize returns for users over time, positioning Intel Markets as a serious player in crypto trading innovation.

Adding to its appeal, IntelMarkets employs an Intell-Array™ that is used to monitor the signals and the data behind them. Instead of trying to interpret signals coming from trading channels of different trading interfaces, Intell-Array™ gathers more than 100 000 data points to provide unambiguous signals allowing the user to make the right decision in a highly volatile market environment.

Moreover, Intel Markets is versatile enough to facilitate dual-exchange functionality and runs on both Ethereum and Solana networks. This versatility allows traders to choose the blockchain that best suits their trading needs, positioning Intel Markets for significant expansion.

Join the Movement:

Buy Presale

Visit Intel Markets (INTL)

Join The Intel Community

 

Bitcoinist

Bitcoinist

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

Letture associate

Three Years Later: Looking Back on My 2023 Predictions for ChatGPT

Looking Back After Three Years: Revisiting My 2023 Predictions on ChatGPT In March 2023, shortly after ChatGPT's debut and before GPT-4's release, I made over twenty predictions about AI's future based on limited information and intuition. Now, in May 2026, I revisited those forecasts using an AI-driven analysis with 41 Opus 4.8 agents to cross-reference them with the latest data. The assessment used symbols: ✅ Correct, 🟢 Mostly Correct, 🟡 Partially Correct, ❌ Incorrect. Overall, the directional judgments held up well, with only one major factual error regarding GPT-4's rumored parameter size (incorrectly cited as 100T). However, nuances and degrees of accuracy revealed more. **What Was Largely Correct:** Predictions about mechanisms and directions proved accurate. The rise of RAG (Retrieval-Augmented Generation) as the standard architecture for combating AI hallucination was confirmed, as was the transformative potential of LUI (Language User Interface) in creating a new industry layer atop GUIs. The emergence of "robot networks" (agent-to-agent communication protocols) and China's rapid catch-up in developing capable large models (closing the performance gap with top models to ~2.7%) were also on point. The analysis affirmed that LLMs lack consciousness and that the Turing Test merely measures perceived intelligence. **What Was Off Target:** Errors often involved specific numbers, over-optimistic timelines, or misjudged distributions. The prediction that value would primarily accrue to the application layer was half-right but missed NVIDIA's dominance as the profitable infrastructure layer. Forecasts about AI circumventing copyright issues and fostering a "global common ground" by averaging human viewpoints were incorrect; instead, major copyright settlements occurred and AI personalization is increasing. Estimates for model training costs ("$5-10 billion cap") were significantly off, underestimating frontier costs and overestimating replication costs. The notion that LLMs could never do complex math without tools was disproven by later models winning IMO gold. **Key Patterns from the Review:** 1. **Direction over precision:** Judgments about mechanisms and trends were more reliable than specific numbers or definitive statements. 2. **Timing bias:** There was a tendency to overestimate short-term speed but underestimate long-term magnitude and transformation. 3. **The distribution blind spot:** Aggregate-level correctness often masked uneven impacts (e.g., on young professionals' employment). 4. **The value of qualifiers:** Predictions framed with caution (e.g., "reportedly," "for now," "prototype in 2-3 years") aged better. 5. **Some debates continue:** Issues like the nature of "emergent abilities" or machine consciousness remain unresolved. This three-year review highlights that while seeing the big picture is crucial, humility regarding specifics, timelines, and disparate impacts is essential for future forecasting.

链捕手2 h fa

Three Years Later: Looking Back on My 2023 Predictions for ChatGPT

链捕手2 h fa

AI Bubble Warning: AI Investments Are Negative Returns for Most Tech Giants

The article issues a stark warning about a potential AI investment bubble. It notes that while the AI boom shares similarities with the TMT bubble of the late 1990s, its scale is vastly larger, currently driving 93% of U.S. GDP growth. Major hyperscale cloud providers like Microsoft, Alphabet, Amazon, Meta, and Oracle are planning to invest trillions in AI data centers over the coming years. However, calculations based on analyst projections for 2025-2030 reveal a concerning math problem: expected capital expenditure growth far outpaces projected revenue growth. Even under an extremely optimistic scenario of zero costs, the implied return on investment for most of these tech giants (except Amazon) is deeply negative. This suggests that the current trajectory could lead to one of history's largest shareholder value destruction events. The piece outlines two potential escapes: AI generating vastly more revenue than currently anticipated—a near-impossible task—or a significant cutback in the planned investment splurge. The latter scenario could trigger a domino effect, severely impacting the entire tech supply chain (from Nvidia to TSMC), potentially pushing the U.S. economy into recession, and causing a major stock market downturn. The author suggests upcoming high-profile IPOs by companies like OpenAI and Anthropic might represent a transfer of risk from early investors to public market participants. While the peak of the hype cycle might sustain investment through 2026, the fundamental financial dilemma remains unresolved, setting the stage for a potential market correction in 2027 or 2028, similar to the years following Alan Greenspan's "irrational exuberance" warning.

marsbit3 h fa

AI Bubble Warning: AI Investments Are Negative Returns for Most Tech Giants

marsbit3 h fa

From Tokens to Machine Labor: AI is Shifting from Tool to "Worker"

The article "From Token to Machine Labor: AI is Evolving from Tool to 'Worker'" argues that the business model for AI is shifting beyond simply selling computational resources (tokens, GPU hours) or model access. Instead, a new "machine labor market" is emerging, where the core economic transaction is the purchase of economically useful work directly performed by software. The central thesis is that AI pricing will evolve through four stages: 1) raw tokens, 2) standardized LLM capabilities (e.g., text generation), 3) industry-specific labor markets (e.g., legal review, radiology), and finally 4) a programmable results market where tasks like resolving a support ticket are bid on and priced based on outcome. In this future, buyers will care less about *which* model or GPU completes a task and more about whether the work meets specified standards for accuracy, latency, and cost. This transition reframes the impact of AI on human labor. Rather than simple replacement, it suggests a re-coordination where machines handle standardized, verifiable work, freeing humans for roles involving oversight, context management, responsibility, and final judgment. In some cases, this "last 1%" of human input becomes more valuable as it enables the other 99% to be automated. Furthermore, as AI reduces the cost of work, demand may expand, creating larger markets (e.g., 24/7 customer service) rather than just cheaper versions of existing ones. The article concludes that while infrastructure (GPUs, models, tokens) remains crucial upstream, the market is converging on a simpler, tradeable unit: machine labor that can be defined, measured, priced, and procured based on contractible specifications.

marsbit3 h fa

From Tokens to Machine Labor: AI is Shifting from Tool to "Worker"

marsbit3 h fa

Xiaomi MiMo's 99% Price Cut is Not Marketing! Luo Fuli Posts on X to Refute Critics

The price of Xiaomi's MiMo-V2.5 series API has been permanently reduced by up to 99%, specifically for the "Input (Cache Hit)" cost, which covers users re-reading historical context in long conversations. MiMo's head, Luo Fuli, published a detailed technical blog to clarify that this drastic price cut stems from genuine engineering breakthroughs, not a marketing stunt or a simple price war. The core of the achievement lies in six key engineering optimizations. First, the model architecture adopts a Hybrid Sliding Window Attention (SWA), reducing the memory footprint (KVCache) to 1/7th of a traditional model. Second, a dual-pool memory management system actually utilizes these savings, allowing a single GPU to handle over 5 times more concurrent users. Third, an upgraded prefix caching mechanism achieves a cache hit rate of 93-95% for repeated reads, meaning most such requests bypass GPU computation entirely. Fourth, a self-developed distributed cache (GCache) utilizes idle SSD space on existing GPU servers, eliminating additional storage costs. Fifth, an intelligent scheduling system (LLM-Router) efficiently routes requests to maximize cache reuse and performance. Sixth, Multi-Token Prediction (MTP) accelerates the model's text generation ("output") side. Together, these systemic optimizations dramatically lower the real computational cost per request, enabling the 99% price reduction for cached inputs while reportedly maintaining positive gross margins. Luo Fuli's disclosure aims to shift the narrative from "price war" to a demonstration of substantive AI engineering progress.

marsbit5 h fa

Xiaomi MiMo's 99% Price Cut is Not Marketing! Luo Fuli Posts on X to Refute Critics

marsbit5 h fa

$26 Billion: An 'All-Chinese Team' Backs the World's Highest-Valued AI Programming Company

Cognition AI, the company behind the AI programmer "Devin," has raised over $1 billion in new funding at a valuation of $26 billion, just eight months after reaching a $10.2 billion valuation. The round was led by Lux Capital, General Catalyst, and 8VC. Founded by three young Chinese entrepreneurs with strong competitive programming backgrounds, Cognition initially gained fame with Devin, marketed as the world's first AI software engineer capable of handling tasks from start to finish. While its early demos were impressive, real-world usage revealed reliability and cost-effectiveness issues, leading to a significant price cut for Devin in 2025. A pivotal moment came when Cognition acquired the assets of AI IDE company Windsurf after a failed acquisition by OpenAI. This move gave Cognition a crucial developer-facing tool, allowing it to pursue a two-pronged strategy: Devin for autonomous task execution and Windsurf for integrated, collaborative coding within an IDE. This shift helped the company move away from the controversial "AI replacement" narrative towards a model of augmenting human engineers, particularly for repetitive or maintenance tasks. This strategic pivot is backed by strong commercial metrics. The company reports a 10x increase in enterprise usage this year, with an annual revenue run-rate of $492 million and a 50% month-over-month growth in enterprise Devin usage over the past six months. Its client list now includes major corporations like Goldman Sachs and Mercedes-Benz, as well as government agencies like NASA and the U.S. Army. Investors are betting on Cognition becoming a foundational piece of next-generation software engineering infrastructure, positioning it at the center of a hybrid future where AI agents and human developers work in tandem.

marsbit5 h fa

$26 Billion: An 'All-Chinese Team' Backs the World's Highest-Valued AI Programming Company

marsbit5 h fa

Trading

Spot
Futures

Articoli Popolari

Come comprare SHIB

Benvenuto in HTX.com! Abbiamo reso l'acquisto di SHIBA INU (SHIB) semplice e conveniente. Segui la nostra guida passo passo per intraprendere il tuo viaggio nel mondo delle criptovalute.Step 1: Crea il tuo Account HTXUsa la tua email o numero di telefono per registrarti il tuo account gratuito su HTX. Vivi un'esperienza facile e sblocca tutte le funzionalità,Crea il mio accountStep 2: Vai in Acquista crypto e seleziona il tuo metodo di pagamentoCarta di credito/debito: utilizza la tua Visa o Mastercard per acquistare immediatamente SHIBA INUSHIB.Bilancio: Usa i fondi dal bilancio del tuo account HTX per fare trading senza problemi.Terze parti: abbiamo aggiunto metodi di pagamento molto utilizzati come Google Pay e Apple Pay per maggiore comodità.P2P: Fai trading direttamente con altri utenti HTX.Over-the-Counter (OTC): Offriamo servizi su misura e tassi di cambio competitivi per i trader.Step 3: Conserva SHIBA INU (SHIB)Dopo aver acquistato SHIBA INU (SHIB), conserva nel tuo account HTX. In alternativa, puoi inviare tramite trasferimento blockchain o scambiare per altre criptovalute.Step 4: Scambia SHIBA INU (SHIB)Scambia facilmente SHIBA INU (SHIB) nel mercato spot di HTX. Accedi al tuo account, seleziona la tua coppia di trading, esegui le tue operazioni e monitora in tempo reale. Offriamo un'esperienza user-friendly sia per chi ha appena iniziato che per i trader più esperti.

497 Totale visualizzazioniPubblicato il 2024.12.11Aggiornato il 2025.03.21

Come comprare SHIB

Discussioni

Benvenuto nella Community HTX. Qui puoi rimanere informato sugli ultimi sviluppi della piattaforma e accedere ad approfondimenti esperti sul mercato. Le opinioni degli utenti sul prezzo di SHIB SHIB sono presentate come di seguito.

活动图片