Crypto Market Structure Bill Nears Key Moment As CFTC Chair Signals Progress Within Months

bitcoinist2026-02-04 tarihinde yayınlandı2026-02-04 tarihinde güncellendi

Özet

Newly appointed CFTC Chair Michael Selig advocates for the passage of the crypto market structure bill (CLARITY Act), arguing it could establish the U.S. as the global "gold standard" in crypto regulation. He emphasizes that the legislation would provide long-needed clarity by defining a token taxonomy and clarifying regulatory jurisdictions, challenging the current approach of treating most digital assets as securities. Selig believes the bill could reach President Trump's desk within months, aided by executive support. Meanwhile, Senate Democrats are planning a closed-door meeting to discuss the bill, which recently stalled in the Senate Banking Committee due to industry opposition, despite passing in the Agriculture Committee.

As uncertainty grows around the fate of the crypto market structure bill (CLARITY Act), newly appointed Commodity Futures Trading Commission (CFTC) Chair Michael Selig is making a strong case for its passage.

Selig argues that the legislation moving through Congress could position the United States as the global benchmark — or “gold standard” — for crypto regulation, addressing what he described as years of regulatory ambiguity that have held the industry back.

Clear Crypto Rules Could Arrive Within Months

Speaking in an interview with FOX Business, Selig said the US has long suffered from a lack of clear oversight for digital assets, forcing innovation and capital to move offshore.

He explained that the proposed crypto market structure legislation is designed to introduce long‐needed clarity by defining a “token taxonomy” and clearly outlining which regulators have authority over different parts of the crypto market.

For the first time, he added, developers and investors may soon have a framework that clearly defines what qualifies as a security, what does not, and how digital assets should be treated under US law.

Selig also challenged the approach of treating nearly all digital assets as securities, calling it outdated. He argued that many cryptocurrencies function more like commodities and should therefore fall under the CFTC’s jurisdiction rather than being regulated exclusively by the Securities and Exchange Commission (SEC).

Looking ahead, Selig said he believes the market structure bill could reach President Donald Trump’s desk within the next couple of months. He also praised the president’s leadership and vocal support of the crypto sector, suggesting that executive backing could help push the legislation across the finish line.

Senate Democrats Plan Closed‐Door Meeting

Meanwhile, activity is picking up on Capitol Hill. Crypto journalist Eleanor Terrett reported on X (formerly Twitter) that Senate Democrats are planning to reconvene for a closed‐door meeting on crypto market structure.

The meeting, expected to take place this week, would mark the first member‐level Democratic caucus discussion on the issue since the Senate Banking Committee postponed its markup last month.

This comes as the delayed markup occurred last month after pushback from the industry. That opposition included crypto exchange Coinbase withdrawing its support over provisions related to tokenized equities, decentralized finance, and stablecoin rewards and yields.

As a result, the bill stalled in the Senate Banking Committee, increasing the uncertainty surrounding its eventual passing schedule, even though the Senate Agriculture Committee’s version of the bill passed during last week’s vote.

The daily chart shows the total digital asset market cap’s drop to $2.5 trillion on Tuesday. Source: TOTAL on TradingView.com

Featured image from OpenArt, chart from TradingView.com

İlgili Sorular

QWhat is the main argument made by CFTC Chair Michael Selig in favor of the crypto market structure bill?

AMichael Selig argues that the legislation could position the United States as the global benchmark or 'gold standard' for crypto regulation, addressing years of regulatory ambiguity that have held the industry back and forced innovation and capital to move offshore.

QAccording to Selig, what key definitional framework might the proposed legislation provide for the first time?

AFor the first time, developers and investors may soon have a framework that clearly defines what qualifies as a security, what does not, and how digital assets should be treated under US law.

QWhich regulatory approach does Selig criticize as outdated, and what alternative does he propose?

ASelig criticizes the approach of treating nearly all digital assets as securities as outdated. He argues that many cryptocurrencies function more like commodities and should therefore fall under the CFTC’s jurisdiction rather than being regulated exclusively by the SEC.

QWhat recent development is mentioned regarding Senate Democrats and this legislation?

ASenate Democrats are planning to reconvene for a closed-door meeting on crypto market structure, which would be the first member-level Democratic caucus discussion on the issue since the Senate Banking Committee postponed its markup last month.

QWhy did the Senate Banking Committee's markup of the bill get postponed last month?

AThe markup was postponed after pushback from the industry, including crypto exchange Coinbase withdrawing its support over provisions related to tokenized equities, decentralized finance, and stablecoin rewards and yields.

İlgili Okumalar

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbit28 dk önce

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbit28 dk önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbit32 dk önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbit32 dk önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbit32 dk önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbit32 dk önce

İşlemler

Spot
活动图片