Popular CNBC host of “Mad Money,” Jim Cramer, has recently drawn notice for his pessimistic comments regarding the future of Bitcoin (BTC). In his most recent post on X, he has reiterated his assertions. Furthermore, he is now endorsing the “Number Go Down” motif, referencing the sharp drops in Bitcoin prices.

Jim Cramer Offers Opinion On The Decline Of Bitcoin
Jim Cramer discussed how Bitcoin fell 20% from its peak of $48,969 after the introduction of the Spot ETF on X on Tuesday, January 23. Furthermore, he indicated that Bitcoin is ready to take a “strong stance,” but there’s more to it than that. The host of “Mad Money” continued by saying that even if Bitcoin recovered, there wouldn’t be enough money coming in to support it.

He wrote, “Now that Bitcoin’s down about 20% from its high i expect a strong stand to be made but it won’t hold because not enough money is coming in. New theme: Number Go Down.” Earlier, on Monday, Cramer had expressed further criticism regarding BTC’s future. The host wrote, “Unlikely that Bitcoin finds its footing.”

However, industry experts expect that such comments from Cramer would eventually propel the Bitcoin price up. Rufas Kumau, Senior Contributor at Forbes, quoted Cramer’s tweet and expressed optimism. Embracing the Inverse Cramer hashtag, Kumau wrote, “You know what it is.. we going back up.”

BTC Price Falls Below $39,000

The oldest cryptocurrency in the world has recently struggled with a bearish trend. In today’s session, the price of Bitcoin went below $39,000, indicating a significant 20% decline in relation to the peak of $48,969 set last week for the ETF. By 4.39% as of the time of publication, the value of Bitcoin was $38,919.42 on Tuesday.

With a market cap of $762.87 billion, the cryptocurrency appeared to have decreased by 4.51%. On the other hand, the trading volume of Bitcoin increased by 82.63% to $31.10 billion. Due to the significant decline, Bitcoin fell from a high of $41,169.30 to a low of $38,839.95 on Tuesday.

While citing past patterns, well-known cryptocurrency expert Ali Martinez predicted that the price of Bitcoin would potentially fall below $33,000. “Looking back at the last two bull cycles, $BTC usually retraced to the 50% Fibonacci level,” he said after hitting the 78.6% Fib.”

The analyst also mentioned that Bitcoin just retested the 78.6% Fibonacci level. Therefore, if the historical pattern continues, he anticipates a pullback to the 50% Fibonacci level. Moreover, he hinted at a 16% decline from the present price by saying it would drive the value of Bitcoin to as low as $32,700.

The Profit-Taking Process in BTC

This scenario could lead to a loss of confidence among investors, resulting in reduced market participation and potentially hindering price recovery. A long-term profit-taking period could also be an indicator of market fatigue or skepticism about Bitcoin’s short-term prospects.

The Price Trend in BTC

If the mentioned trend continues, it could prevent newcomers from entering the market, and existing investors may prefer to stay on the sidelines, waiting for clearer signs of an uptrend. In the last few days, the number of short positions opened against BTC increased from 48% to 51.52%. However, if BTC’s price takes a positive turn, it could worsen the situation for investors.

The US Securities and Exchange Commission (SEC) Chair Gary Gensler warned of the dangers of artificial intelligence (AI) in the financial sector during a virtual fireside chat on January 17th, organized by Public Citizen. Gensler had previously focused on the cryptocurrency industry. Concerning the possible risks of an AI monoculture, Gensler stated that centralized AI systems would jeopardize the stability of the financial system. This occurs in the midst of expanding conversations around regulatory control and AI’s place in the financial sector.

Safeguarding financial stability in the face of the AI monoculture threat

Gary Gensler, often referred to as the “crypto cop on the beat,” emphasized the potential dangers of centralized AI markets, specifically those relying on a limited number of models. Drawing parallels with the dominance of Amazon, Microsoft, and Google in cloud services, Gensler warned that a financial system overly dependent on a small number of AI models could become fragile. He envisioned a scenario where a “monoculture” emerges, with numerous financial actors relying on a single central data or AI model, thus exacerbating systemic risks.

Gensler highlighted the lack of regulatory oversight for AI models in the financial sector, pointing out that the so-called “central nodes” crucial to the industry are currently unregulated. He stressed the need for diversity in both AI models and data sources to ensure a robust and resilient financial system. This echoes his previous sentiments about the crypto industry being a “wild west” and the potential destabilization of financial markets through the use of AI, indicating a consistent concern for maintaining stability in the financial realm.

AI’s evolution – From breakthroughs to regulatory challenges

The AI sector, currently dominated by a handful of major players, including OpenAI, Microsoft, Google, and Anthropic, is witnessing a shift in focus. While large language models have garnered significant attention, there is a growing emphasis on mathematical-based AIs, particularly those addressing high-level geometry problems. Google Deepmind recently announced a major breakthrough in this domain, indicating the continuous evolution of AI capabilities beyond language processing.

As artificial intelligence (AI) gains prominence at the World Economic Forum in Davos, the conversation has widened to cover the technology’s possible drawbacks, such as its propensity to propagate false information. The growing focus on AI’s wider ramifications highlights how urgent it is to close legislative loopholes and guarantee a diverse approach to AI adoption in the financial industry.

Important considerations concerning the regulatory environment of the future are brought up by Gary Gensler’s most recent alert regarding the dangers of AI monoculture in the banking industry. As AI technologies are further adopted by the financial sector, strong oversight and diversified models are increasingly important. Can regulators in AI-driven finance find a middle ground between encouraging innovation and averting the establishment of a precarious monoculture? To effectively traverse the complexity of this technological frontier, the growing discourse surrounding artificial intelligence (AI) and its effects on financial stability necessitates cautious thought and aggressive regulatory actions.