Trump Presses Congress To Pass Crypto Market Structure Bill ‘ASAP’

bitcoinistОпубліковано о 2026-03-04Востаннє оновлено о 2026-03-04

Анотація

President Donald Trump has publicly urged Congress to pass the CLARITY Act, a comprehensive crypto market structure bill, "ASAP." In a Truth Social post, he accused the banking industry of undermining both the pending legislation and the previously signed GENIUS Act, which deals with stablecoins. Trump warned that failure to pass the bill could cede U.S. leadership in crypto to other countries like China and argued that Americans should benefit from the financial opportunities digital assets provide. He called for cooperation between banks and the crypto industry. Legislative progress on the bill has stalled due to disputes between these groups, with a key Senate committee now targeting a markup session for late March.

President Donald Trump has publicly addressed the legislative impasse surrounding the CLARITY Act, the long-debated crypto market structure bill that has yet to reach his desk for final approval.

The delay, according to ongoing discussions in Washington, stems largely from disagreements between the banking industry and crypto representatives, particularly over provisions tied to stablecoin rewards.

Trump Says Banks Threaten Stablecoin Law

In a post shared Tuesday on Truth Social, Trump sharply criticized the banking sector, accusing it of attempting to weaken both the broader crypto framework and a separate stablecoin measure he signed into law last year — the GENIUS Act.

“The Genius Act is being threatened and undermined by the Banks, and that is unacceptable — We are not going to allow it,” Trump wrote. He argued that passing comprehensive market structure legislation is urgent, adding, “The U.S. needs to get Market Structure done, ASAP. Americans should earn more money on their money.”

The President also claimed that financial institutions, despite reporting record profits, are working against policies designed to expand opportunities within the digital asset sector.

Trump warned that failing to finalize the CLARITY Act could weaken America’s position in the global crypto race. “We are not going to allow them to undermine our powerful Crypto Agenda that will end up going to China, and other Countries if we don’t get The Clarity Act taken care of,” Trump stated.

Calls For Banking-Crypto Cooperation

Trump further urged the banking sector to reach constructive agreements with the crypto industry, arguing that collaboration would serve the best interests of American consumers and businesses alike.

“This Industry cannot be taken from the People of America when it is so close to becoming truly successful,” he wrote, closing his message with a call for attention to the issue.

Legislatively, progress on the CLARITY Act has been uneven. The Senate Agriculture Committee advanced its portion of the bill in January of this year. However, broader movement has stalled.

The Senate Banking Committee had initially scheduled a markup in January, but that session was canceled amid the same disputes between banking representatives and crypto advocates that continue to complicate negotiations. The committee is now reportedly targeting a new markup date in mid-to-late March.

The daily chart shows the total digital asset market cap at $2.3 trillion as of this writing. Source: TOTAL on TradingView.com

Featured image from OpenArt, chart from TradingView.com

Пов'язані питання

QWhat is the name of the crypto market structure bill that President Trump is urging Congress to pass?

AThe CLARITY Act.

QAccording to Trump, which industry is threatening and undermining the GENIUS Act?

AThe banking industry.

QWhat is one of the main reasons for the legislative delay of the CLARITY Act as mentioned in the article?

ADisagreements between the banking industry and crypto representatives, particularly over provisions tied to stablecoin rewards.

QWhat did Trump warn could happen to America's position in the global crypto race if the CLARITY Act is not finalized?

AIt could weaken America's position, and the crypto agenda could go to China and other countries.

QWhich Senate committee had initially scheduled a markup for the bill in January but canceled it?

AThe Senate Banking Committee.

Пов'язані матеріали

Rubin Ultra Makes Major Cuts, Even Nvidia Can't Handle Memory Price Hikes?

NVIDIA's Rubin Ultra, the top-tier variant of the newly announced Rubin AI accelerators, has reportedly seen significant specification downgrades, according to an industry report from SemiAnalysis. Initially designed with four compute dies (4-die), the Rubin Ultra is now said to be reduced to a 2-die design. Key changes highlighted in the report include: * **No increase in peak theoretical compute performance**, remaining at 35 PFLOPs like the standard Rubin. * **Severe reduction in memory capacity** to 192GB using 8-Hi HBM stacks, which is less than the standard Rubin's 288GB using 12-Hi stacks. * **Negligible memory bandwidth improvement** of only 1 TB/s. * **Slightly higher chip-level power consumption**. * The **primary upgrade is a massive increase in scale-up interconnect capacity**, supporting connections for up to 576 GPUs via NVLink, compared to 72 for the standard Rubin. The report suggests the redesign is primarily a cost-optimization move driven by the sharp rise in HBM (High-Bandwidth Memory) prices. By reducing the expensive HBM content and shifting investment towards enhanced system-scale networking, NVIDIA aims to maintain the platform's value for large-scale AI training clusters while managing soaring material costs. The news reportedly triggered a sell-off in South Korean memory stocks, with SK Hynix and Samsung shares falling around 8%, as markets grew concerned that NVIDIA—a major HBM buyer—might be reducing its reliance on high-capacity memory, potentially capping future pricing power for memory makers.

Odaily星球日报11 хв тому

Rubin Ultra Makes Major Cuts, Even Nvidia Can't Handle Memory Price Hikes?

Odaily星球日报11 хв тому

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.

bitcoinist1 год тому

Upbit Rebalances 864B SHIB In Internal Wallet Move

bitcoinist1 год 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.

marsbit1 год тому

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

marsbit1 год 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.

marsbit1 год тому

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

marsbit1 год 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

Торгівля

Спот