CLARITY Act May Not Pass Before April, Says Senate Leader John Thune

TheNewsCryptoPublished on 2026-03-13Last updated on 2026-03-13

Abstract

Senate Majority Leader John Thune stated that the CLARITY Act, a key cryptocurrency market structure bill, is unlikely to be considered before April. The legislation aims to clarify regulatory roles for digital assets in the U.S., specifically defining the responsibilities of agencies like the SEC and CFTC. Lawmakers are currently prioritizing other pressing issues, including the SAVE America Act. Thune expressed hope that the market structure bill would advance later, though not immediately. There are concerns that delays could hinder U.S. competitiveness, as other countries like China may gain ground in crypto innovation. Despite the postponement, there is optimism that the bill could pass in 2026 if negotiations proceed smoothly. The act seeks to reduce regulatory uncertainty and support innovation in the digital asset market.

John Thune, the leader of the U.S Senate majority, said that lawmakers may consider delaying the legislation on the crypto market structure until April. He said that the Senate Banking Committee may consider it later. Since lawmakers are currently busy working on other pressing issues. The proposed legislation, known as the CLARITY Act, aims to help lawmakers clarify rules governing digital assets and cryptocurrencies in the US.
The lawmakers proposed the legislation to clarify the roles that different regulators play in the management of digital assets and the overall financial market.

In post X by Eleanor Terret, indicate that the Senate will focus on the SAVE America Act first before the crypto market structure bill. Thune said, “Market structure is a bill that’s, I’m hoping, going to come out soon.” He added that the legislation will probably move forward “probably not before, I would say, the April time period.”

Lawmakers discussed various policy issues related to stablecoin regulation and financial oversight when they shared these comments. Industry observers closely watch these developments because they could significantly influence future cryptocurrency regulations. The lawmakers had already moved previous versions of these bills through House committees during previous discussions. However, Senate leaders are now indicating that they will tackle other legislative priorities before considering cryptocurrency bills.

Debate Over Crypto Regulation Continues

Donald Trump has indicated that continued delays in the regulation of the crypto market could affect the U.S digital asset market. According to Trump, continued delays could allow other countries, like China. This was to have a better position in the world’s cryptocurrency market. He stated that continued delays in the legislation could allow innovation and development to occur outside the United States.

The regulators are working on clarifying the responsibilities that different bodies, like the SEC and CFTC in the United States, have in regulating digital assets. This is in a bid to reduce the uncertainty that exists in the digital assets market and the investments that occur in the market. There is optimism among lawmakers regarding the legislation despite the proposed adjustments that are expected in the Senate. There is a likelihood that the legislation could be passed later in 2026 if everything goes smoothly in the negotiations.

According to different policy analysts, the legislation could be passed later in 2026 if everything goes smoothly in the negotiations. There are continued calls by different bodies for lawmakers to establish clear regulations that support innovation in the digital assets market.

Highlighted Crypto News:

Crypto Miners Turn to Asset Strategies as Profit Pressures Intensify

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11m ago

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

Odaily星球日报11m ago

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.

bitcoinist1h ago

Upbit Rebalances 864B SHIB In Internal Wallet Move

bitcoinist1h ago

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.

marsbit1h ago

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

marsbit1h ago

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.

marsbit1h ago

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

marsbit1h ago

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.

marsbit1h ago

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

marsbit1h ago

Trading

Spot

CLARITY Act May Not Pass Before April, Says Senate Leader John Thune

Abstract

Debate Over Crypto Regulation Continues

Related Questions

Related Reads

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

Upbit Rebalances 864B SHIB In Internal Wallet Move

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

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

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

Trading