US Fed Holds Interest Rate Steady, Gives Clarity to Crypto Market

TheNewsCryptoОпубліковано о 2026-01-29Востаннє оновлено о 2026-01-29

Анотація

The US Federal Reserve has decided to maintain the current interest rate range of 3.5% to 3.75%, a move that was widely anticipated by the crypto market. This marks the first time rates have remained unchanged since July 2025. The decision provides clarity but limits the potential for investors to allocate more funds to riskier assets like cryptocurrencies. Following the announcement, the global crypto market capitalization declined by 1.12% to $2.99 trillion, with major tokens like BTC and ETH also experiencing losses. Fed Chair Jerome Powell emphasized the improved economic outlook but noted ongoing tensions between inflation and employment. Looking ahead, there is no immediate sign of a rate cut, and Powell is scheduled to step down in May 2026, with a potential replacement likely to be announced by former President Trump. The crypto market is advised to proceed with caution and conduct thorough risk assessments.

The US Fed, or the US Federal Reserve, has decided to keep the interest rate as it is. The crypto market was earlier speculating what the decision could be, even though the majority of the sphere was confident about no rate cut. The decision comes after the US President Donald Trump and Jerome Powell got into a conflict, reportedly threatening the independence of the central agency.

No Rate Cut by the US Fed

The US Federal Reserve has concluded its January meeting, confirming that there will be no rate cut this time. The rate will remain in the range of 3.5% and 3.75% while officials continue to monitor the nation’s economic activities. The Fed has said that the economic activity of the US has been growing at a solid pace, according to a BBC report.

Jerome Powell, Chair of the central agency, has said that the outlook for economic activity has improved, but there is still some tension between inflation and employment. Only two Fed officials had voted in favor of a rate cut – Stephen Miran and Christopher Waller. The board eventually focused on the recent economic data to keep the rate unchanged.

What’s at Stake for the Crypto Market?

A rate cut would have fundamentally allowed investors to allocate more funds to a risky alternative, the crypto market in this case. An unchanged rate for the first time since July 2025 has offered one clarity – interest rate will remain in the same range of 3.50% and 3.75%.

Bitget, an exchange platform, shared the news and received several responses. Some of them said that there would not be an altseason, to which Bitget replied with HODL. Others hinted that they would wait to see how the situation unfolds, to which the platform asked to carry on.

Meanwhile, the global crypto market has lost almost 1.12% of its market cap, which is now $2.99 trillion. Top tokens like BTC and ETH have lost 1.12% and 1.60% of their respective values over the last 24 hours.

What’s Next?

There is no sign of the next rate cut at the moment; however, Trump is likely to announce a replacement for Powell. Jerome is scheduled to step down in May 2026, which would pave the way for the next Chair to take over. Trump and Powell were earlier in a conflict, which brought out the possibility that Powell was being targeted for not cutting rates soon enough. He defended himself by emphasizing the importance of the Fed’s independence.

For the crypto market, this could be a time to be cautious, to do research, and conduct risk assessment before investments. The US Federal Reserve has decided to hold the rate steady, not strengthening the borrowing capacity of investors any further.

Highlighted Crypto News Today:

Sony Backs Startale Again as Soneium Mainnet Nears

Пов'язані питання

QWhat decision did the US Federal Reserve make regarding interest rates in its January meeting?

AThe US Federal Reserve decided to keep the interest rate unchanged, maintaining it in the range of 3.5% to 3.75%.

QHow did the crypto market react to the Fed's decision to hold rates steady?

AThe global crypto market lost almost 1.12% of its market cap, with top tokens like BTC and ETH declining by 1.12% and 1.60% respectively over the last 24 hours.

QWhat was the significance of a potential rate cut for cryptocurrency investors?

AA rate cut would have allowed investors to allocate more funds to risky alternatives like the crypto market by strengthening borrowing capacity.

QWhat is the current scheduled timeline for Jerome Powell's departure as Fed Chair?

AJerome Powell is scheduled to step down as Chair of the US Federal Reserve in May 2026.

QHow many Fed officials voted in favor of a rate cut during this meeting?

AOnly two Fed officials voted in favor of a rate cut - Stephen Miran and Christopher Waller.

Пов'язані матеріали

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.

bitcoinist50 хв тому

Upbit Rebalances 864B SHIB In Internal Wallet Move

bitcoinist50 хв тому

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.

marsbit50 хв тому

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

marsbit50 хв тому

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.

marsbit55 хв тому

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

marsbit55 хв тому

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.

marsbit1 год тому

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

marsbit1 год тому

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.

marsbit2 год тому

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

marsbit2 год тому

Торгівля

Спот