AI-Related Stocks Surge, Cryptocurrencies Mirror the Optimistic Sentiment

TheNewsCryptoPublished on 2026-02-03Last updated on 2026-02-03

Abstract

AI-related stocks surged on Monday, contributing to record highs in major US stock indexes. Companies like SanDisk, AMD, and Micron Technology saw significant gains, with AI accounting for over a quarter of the S&P 500. Alphabet and Amazon also rose ahead of quarterly earnings reports. The optimism extended to AI cryptocurrencies, with the sector's market cap increasing 3.57% to $15.20 billion. Tokens like TAO, NEAR, and ICP posted notable gains. Tron DAO founder Justin Sun expressed bullish sentiment, stating "All in AI." Overall, US indexes performed well, with the Dow rising 1.05%. However, the crypto market faces headwinds from recent Bitcoin liquidations of approximately $2.5 billion, keeping BTC below $80,000.

Stocks of companies in the AI sector surged on Monday, contributing to the highs of the overall US Stock Indexes. AI cryptocurrencies continue to mirror a similar sentiment. Tron DAO Founder Justin Sun published a post to express his support for the AI segment in general.

AI Stocks Soar

Stocks of AI-related companies closed Monday on a high. Alphabet and Amazon added 1.9% and 1.5% to their respective values. However, they were overshadowed by the likes of SanDisk, Advanced Micro Devices, and Micron Technology. Each gained 15.4%, 4%, and 5.5%, applicable in the same order.

AI, according to a report by Reuters, dominated S&P 500 by accounting for more than a quarter of the Index. Notably, Alphabet and Amazon are likely to report their quarterly results sometime this week. It could give an additional glimpse into the near future of AI to investors. Meanwhile, US stocks in the AI segment have re-ignited optimism among investors.

AI Cryptocurrencies Surge

The optimism extends across the sector of AI cryptocurrencies. The collective market cap is up by 3.57% to $15.20 billion. Top AI tokens have recorded significant gains, like TAO (4.55%), NEAR (2.18%), and ICP (2.70%), in the last 24 hours.

Tron DAO Founder Justin Sun has expressed his support for the AI sector by publishing an X post, saying, All in AI. While the context is broad, it likely translates to staying bullish about the sector, including its cryptocurrencies. Needless to say, it is important to do research and risk assessment before crypto investments, or any other kind of investments.

Overall US Stock Indexes

All three US stock indexes performed well on Monday, with Dow noting the highest gains of 1.05%. It is followed by Nasdaq with 0.56% rise and S&P 500 with 0.54% gain. The Russell 2000 index also jumped by almost 1%.

A lot of highs in the AI cryptocurrencies or related stock indexes are attributed to recent developments. This includes the closure of the India-US trade deal and a comeback of Gold & Silver after a couple of consecutive drops.

However, the crypto market, for one, could take time to recover from the recent BTC liquidations of approximately $2.5 billion. The flagship token continues to trade below $80k, down by 10.90% over the last 7 days.

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The Impossible Trilemma Is Basically a Pseudo-Problem

The article argues that the core limitation of blockchain technology is not the scalability trilemma, but its fundamental lack of privacy, which acts as a barrier to institutional capital. It defines blockchain as a slow, expensive, shared computer whose primary value is "permissionlessness" (no administrator) and verifiable trust. While this is ideal for native financial assets like stable币, which now process trillions, two critical flaws remain for mainstream adoption: regulatory legitimacy and a default transparency that leaks all financial activity. The author contends that transparency is not a feature but a tax, quantified through MEV extraction, making the public ledger unusable for serious institutions. However, modern cryptography, specifically zero-knowledge proofs, now offers a solution: "provable privacy." This allows users to prove compliance (e.g., solvency, KYC) without revealing underlying data. This fusion of privacy and auditability resolves the transparency-compliant privacy-compliance dichotomy, enabling a purely upgraded system where transactions are verified but not broadcasted. Closing these flaws is presented as the essential bridge to onboard the next wave of trillions in capital.

marsbit1h ago

The Impossible Trilemma Is Basically a Pseudo-Problem

marsbit1h ago

The "Impossible Triad" Is Fundamentally a Pseudo-Problem

The article argues that blockchain's fundamental limitation is not the scalability trilemma (decentralization, scalability, security), which has been largely solved, but the lack of **privacy** and, until recently, clear **legitimacy**. Blockchain is described as a slow, expensive, globally shared computer whose core value is censorship resistance and verifiability. While ideal for native digital assets like money (e.g., stablecoins), its default transparency acts as a **tax**, exposing all transactions and enabling MEV extraction, which deters serious institutional capital. Simultaneously, its permissionless nature created regulatory ambiguity. The piece contends that **privacy** is the missing critical feature. It rejects the false choice between total transparency and complete anonymity. Modern cryptography (like zero-knowledge proofs) enables **compliant privacy**: users can prove facts (solvency, KYC status, compliance) without revealing the underlying sensitive data (specific holdings, identities). This preserves auditability for regulators and eliminates the leak of financial information. With recent regulatory progress (e.g., the GENIUS Act) addressing legitimacy, adding default, provably compliant privacy becomes a pure upgrade. It transforms blockchain from a costly, public ledger into a confidential settlement layer, finally bridging the gap to mainstream institutional and individual adoption of on-chain finance.

链捕手1h ago

The "Impossible Triad" Is Fundamentally a Pseudo-Problem

链捕手1h ago

Optical Chips: Collective Capacity Expansion

The global optical chip industry is experiencing a massive wave of expansion driven by surging AI data center demand. Major players across the US, Japan, Europe, and China are aggressively investing to ramp up production capacity. In the US, Coherent is expanding its 6-inch Indium Phosphide (InP) semiconductor fab in Texas, supported by CHIPS Act funding and a $2 billion strategic investment from NVIDIA. Lumentum is building a new factory for InP optical devices, and Nokia is scaling its advanced photonic chip packaging and testing capabilities. NVIDIA's investments aim to secure future supply of critical lasers and optical interconnect products for AI infrastructure. Japan's JX Advanced Metals, a leading InP substrate supplier, plans a multi-billion yen investment to increase its capacity 7-10 times, strengthening its grip on the crucial upstream materials market. In Europe, IQE and Tower Semiconductor settled a patent dispute and signed a multi-year InP epitaxial wafer supply agreement, highlighting that next-generation silicon photonics platforms will integrate high-performance InP components. STMicroelectronics and Sivers Semiconductors are also expanding silicon photonics production and partnerships. China is rapidly building out its domestic supply chain. Dongshan Precision's subsidiary, Source Photonics, announced a $12 billion project to expand optical chip and module production. Companies like Sanan Optoelectronics and Yunnan Germanium are scaling up InP chip manufacturing and substrate production, moving towards vertical integration from materials to modules. While debate continues around the exact future architecture—whether CPO (Co-Packaged Optics), NPO, or pluggables will dominate—analysts like Morgan Stanley argue the underlying driver is unchangeable: the explosive growth in bandwidth demand. This will inevitably increase the volume of optical engines, lasers, and related content per GPU, regardless of the final technical path. The competition for "more light" in the AI era has intensified into a global, full-chain capacity race.

marsbit3h ago

Optical Chips: Collective Capacity Expansion

marsbit3h ago

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.

链捕手5h ago

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

链捕手5h ago

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?

marsbit6h ago

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

marsbit6h ago

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