Huang Reinforces Nvidia’s Role, Pushing AI Cryptocurrencies upwards

TheNewsCryptoPublished on 2026-03-17Last updated on 2026-03-17

Abstract

Nvidia CEO Jensen Huang's keynote at CES 2026 emphasized the company's pivotal role in the expanding artificial intelligence industry, projecting a $1 trillion chip demand through 2027. This announcement boosted Nvidia's stock by 1.63% and positively influenced AI-related cryptocurrencies. Tokens such as FOMO, LISA, and AIN saw significant gains, rising over 30%, while major AI cryptocurrencies like TAO and NEAR also advanced. The broader crypto market rally, including Bitcoin and Ethereum, further supported the upward trend. Additionally, Nvidia's collaboration with Samsung on the Groq LP30 chip, expected to ship in late 2026, was highlighted.

Nvidia CEO Jensen Huang took the stage and outlined that the company is well-positioned to lead the boom in the AI sector. This led to a surge in NVDA share value and a similar uptick across the segment of AI cryptocurrencies. The projected chip demand through 2027 stands at $1 trillion.

Role of Nvidia, by CEO Jensen Huang

Jensen Huang, at CES 2026, delivered a keynote and underlined that the role of Nvidia could be crucial as the Artificial Intelligence (AI) industry aims to grow further. He has estimated that the chip demand backlog worth approximately $1 trillion could be recorded in the next 2 years.

He acknowledged the growth of agentic AI systems while shedding light on the fact that Nvidia is well-equipped to adapt to the dynamic environment. Nvidia CEO quoted the enterprise-ready version, NemoClaw, as an example.

Notably, the values of NVDA shares also surged following his keynote delivery. The company’s share was last seen trading at $183.19, up by 1.63%. Although a slight correction is expected.

For a quick reference, Samsung and Nvidia are also reportedly working in collaboration for the Groq LP30 chip. Huang informed that the chips were in production and scheduled to be shipped as early as the second half of 2026.

AI Cryptocurrencies Note Upticks

AI cryptocurrencies have recorded significant gains in the last 24 hours. Some of the top gainers, at the moment, are FOMO (+64.57%), LISA (+46.67%), and AIN (+31.47%). TAO and NEAR have retained the top positions in terms of the market cap. They have gained 2.89% and 4.16%, respectively, during the same timeline.

ICP stands out with a correction of 0.30%. Most of the other AI cryptocurrencies show a positive sign of recovery. FET added 12.83%, and VIRTUAL followed closely with a jump of 12.82%. The collective market cap is up by 2.22% at the time of writing this article, when the trading volume is up by 16.83%.

Possible Factor

One factor that could possibly be adding fuel to the ongoing surge for AI cryptocurrencies is the general bull run across the crypto market. This includes the likes of BTC, ETH, and SOL, among many others.

BTC has gained 1.22%, ETH is up by 3.50%, and SOL has surged by 1.06%. The sentiment has likely extended to every crypto category, including AI and meme.

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The Impossible Trilemma Is Basically a Pseudo-Problem

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marsbit2h ago

The Impossible Trilemma Is Basically a Pseudo-Problem

marsbit2h ago

The "Impossible Triad" Is Fundamentally a Pseudo-Problem

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链捕手2h ago

The "Impossible Triad" Is Fundamentally a Pseudo-Problem

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Optical Chips: Collective Capacity Expansion

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Stablecoins Finally Find Real Yield: An In-Depth Look at On-Chain Reinsurance Re | A Conversation with Re Founder Karan Saroya

Stablecoin Real Yield Found: A Deep Dive into On-Chain Reinsurance with Re's Karan Saroya As stablecoin supply exceeds $170 billion, the search for sustainable, non-speculative yield intensifies. Re, an on-chain reinsurance platform, provides an answer: connecting stablecoin capital to the trillion-dollar traditional reinsurance market. Re operates as a regulated reinsurer, accepting stablecoin deposits as collateral to back US insurance companies. These insurers pay premiums, generating yield that flows back to on-chain depositors. Currently supporting 35 insurers and underwriting $500 million, Re projects scaling to over $1 billion soon. Key insights from a Bankless podcast with founder Karan Saroya and investor Avichal of Electric Capital: 1. **Uncorrelated, Real-World Yield:** Re offers stablecoin holders access to reinsurance returns (targeting 12-14%+), an asset class entirely separate from crypto or equity markets. 2. **Operational Efficiency via Smart Contracts:** Re replaces traditional, labor-intensive capital fundraising with smart contracts, allowing a ~12-person team to compete with industry giants. 3. **Regulatory Leverage:** For every $1 of collateral, regulations allow backing $5-7 in written premiums. This leverage amplifies returns from the underlying risk-free rate. 4. **DeFi Integration:** Depositors receive receipt tokens, which can be used in protocols like Morpho for "looping," potentially pushing yields to 18-20%+. 5. **The "DeFi Mullet" Model:** A compliant front-end (regulated reinsurer) paired with a decentralized back-end (smart contracts, DeFi capital markets). 6. **RE Governance Token:** Modeled on Lloyd's of London, the token governs the central capital pool's allocation, counterparty acceptance, and parameters. 7. **Real Economic Impact:** Capital funds real-world productivity (factories, clinics, businesses) via insurance, moving beyond crypto's internal loops. The discussion highlights a pivotal moment: DeFi's supply-side infrastructure is now met by real demand for productive yield, potentially kickstarting a flywheel where vast on-chain stablecoin capital seeks these real-world returns.

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Stablecoins Finally Find Real Yield: An In-Depth Look at On-Chain Reinsurance Re | A Conversation with Re Founder Karan Saroya

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1996 or 1999? Walsh's First Test is 'How to View AI'

"1996 or 1999? Wall's First Big Test Is 'How to View AI'" Federal Reserve Chairman Wall's initial challenge is not whether to raise or cut rates, but a more fundamental judgment: what kind of boom is the current AI boom? This will determine the Fed's policy path and define his legacy. Economics is split between two opposing views, according to reporter Nick Timiraos. One sees imminent productivity gains that will increase supply and cool inflation, allowing the Fed to hold steady. The other argues that while productivity benefits are distant, demand shocks are here now, and waiting for data confirmation risks missing the intervention window, forcing sharper rate hikes later. Wall has signaled a leaning toward the first view, echoing 1996-era Alan Greenspan, who embraced strong, productivity-driven growth without fear of inflation. However, Wall faces a different macro environment than Greenspan did, with tariff pressures, expanding fiscal deficits, and diminishing globalization benefits, which could force more significant inflation pressures even if AI benefits materialize. Wall's logic, expressed before taking office, is that AI-driven productivity gains won't show in official data for years. If the Fed waits for confirmation, it might mistakenly tighten policy and choke off the very growth that could suppress inflation. This argues for using forward-looking narratives over lagging data. Chicago Fed President Austan Goolsbee presents a key counter-argument. He distinguishes between expected and unexpected productivity booms. A widely anticipated boom, like the current AI wave, can cause people to spend future wealth gains in advance, overheating the economy before productivity actually rises, thus requiring preemptive rate hikes. He cites rising costs for AI data centers as evidence of such overheating. Fed Governor Christopher Waller offers a rebuttal to Goolsbee, noting the "expected spending" mechanism only works if people can borrow against future income, which many households cannot do due to borrowing constraints. Wall also faces a paradox related to his desire to reduce the Fed's use of "forward guidance" (pre-announcing policy moves). This practice was established in 1999 when Greenspan began signaling hikes to avoid market shocks. If the economy follows a less optimistic path, Wall may be forced to choose between using the guidance he wants to abolish or risking market volatility by staying silent. The ultimate question defining Wall's first major test remains: Is this 1996 or 1999?

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1996 or 1999? Walsh's First Test is 'How to View AI'

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