SEC Chair Touts Crypto-Led Shift To On-Chain Finance

bitcoinistPubblicato 2025-12-13Pubblicato ultima volta 2025-12-13

Introduzione

SEC Chair Paul Atkins announced a significant shift towards integrating crypto-native infrastructure into US financial markets, emphasizing an on-chain future. The SEC issued a no-action letter allowing the Depository Trust Company (DTC) to proceed with a voluntary tokenization pilot program. This initiative permits eligible participants to tokenize securities entitlements using distributed ledger technology, enabling direct transfers between registered wallets while DTC maintains official records. Atkins highlighted benefits like greater transparency, predictability, and efficiency, while also advocating for an "innovation exemption" to reduce regulatory burdens for market participants transitioning on-chain. The pilot is narrowly scoped and time-limited, serving as a supervised sandbox rather than an immediate broad rollout. The announcement reflects a notable tone shift in regulatory approach towards embracing blockchain technology in traditional finance.

SEC Chair Paul Atkins is leaning into a message that would’ve sounded borderline heretical in Washington not that long ago: the rails are changing, and crypto-native infrastructure is going to be part of it.

“As I told @MariaBartiromo last week, US financial markets are poised to move on-chain,” Atkins wrote on X late Thursday, adding that the SEC is “prioritizing innovation and embracing new technologies to enable this on-chain future, while continuing to protect investors.”

Crypto Will Put The Future Of Finance On-Chain

Atkins didn’t leave it at vibes. Earlier in the day, Atkins pointed to a staff no-action letter out of the SEC’s Division of Trading and Markets tied to the Depository Trust Company’s (DTC) voluntary tokenization effort — a pilot that effectively gives the plumbing of US securities settlement a carve-out to experiment without immediately tripping over parts of the Exchange Act rulebook.

“Today, the Division of Trading and Markets issued a no-action letter to the Depository Trust Company (DTC) regarding DTC’s voluntary securities tokenization pilot program. DTC’s initiative marks an important step towards on-chain capital markets,” Atkins shared via X.

The letter dated Dec. 11 describes a “pilot version” of what it calls DTCC Tokenization Services — a preliminary, time-limited program that lets DTC participants elect to have certain security entitlements recorded using distributed ledger tech instead of relying solely on DTC’s centralized ledger.

In plain English: eligible participants can tokenize positions, hold them in registered wallets on approved blockchains, and transfer those tokenized entitlements directly to another participant’s registered wallet — with DTC’s official records still serving as the system of record for what’s real.

Atkins added: “On-chain markets will bring greater predictability, transparency, and efficiency for investors. DTC’s participants will now be allowed to transfer tokenized securities directly to the registered wallets of other participants, which will be tracked by DTC’s official records.I’m excited to see the benefits of this program to our financial markets and will continue to encourage market participants to innovate as we move towards on-chain settlement.”

Notably, the no-action relief itself is narrowly scoped: it’s centered on how the pilot interacts with Reg SCI, Section 19(b)/Rule 19b-4, and certain clearing-agency standards — and it’s structured to sunset three years after launch of the preliminary version, with DTC required to notify staff when that launch happens. So this isn’t “tokenized stocks for everyone next week.” It’s closer to a supervised sandbox with reporting hooks.

Notably, Atkins is already pitching what comes next. “But this is just the beginning,” he wrote, saying he wants the SEC to consider an “innovation exemption” that would let market participants begin transitioning on-chain “without being burdened by cumbersome regulatory requirements.”

That line is doing a lot of work, and it’s also where the fight (or at least the lobbying) is likely to concentrate. What qualifies as “innovation”? Who gets exempted, and from which obligations? And what’s the gating factor — investor protection, market integrity, operational resilience, or just politics?

Crypto watchers noticed the tone shift immediately. CryptoQuant CEO Ki Young Ju summed it up in one sentence: “SEC Chairman: The future of finance is on-chain.”

For now, the tangible takeaway is the DTC pilot: a regulated core market utility experimenting with tokenized representations under staff comfort. The rest — the “on-chain future” language, and the exemption talk — is the part that could either become a framework or just another ambitious headline that runs into the realities of US market structure.

At press time, the total crypto market cap stood at $3.1 trillion.

Total crypto market cap remains above the 2021 high, 1-week chart | Source: TOTAL on TradingView.com

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In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

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A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

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Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

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