Category: Uncategorized

  • Nakamoto Moves to Stabilize Stock Price

    Nakamoto Moves to Stabilize Stock Price

    Nakamoto Sells Bitcoin to Cover Costs Amidst Financial Struggles

    Nakamoto sold 284 Bitcoin on the last day of March to cover operational expenses, according to the company’s first-quarter financial results. This detail highlights the current situation of one of the country’s Bitcoin treasury companies.

    Mounting Losses and Shifting Strategy

    The Bitcoin accumulation strategy that once propelled Nakamoto’s stock above $25 per share has been replaced by selling Bitcoin to manage operating costs. The company reported a net loss of $238 million for the first quarter. Over $102 million of this loss stemmed from a 20% decline in the value of its Bitcoin holdings during the quarter. Despite a 500% increase in revenue quarter-over-quarter, the losses overshadowed these gains.

    Nakamoto currently holds 5,058 Bitcoin, making it the 20th largest corporate Bitcoin holder globally, just behind ProCap Financial. Michael Saylor’s strategy leads the list, holding over 843,000 Bitcoin.

    Reverse Stock Split to Maintain Nasdaq Listing

    The company is now focused on maintaining its listing on the Nasdaq. Last December, Nasdaq issued a warning to Nakamoto after its stock price fell below $1 for 30 consecutive trading days. The deadline to rectify this is June 8. The company’s chosen solution is a 1-for-40 reverse stock split, scheduled to take effect on Friday. Shareholders approved the move at a special meeting earlier this month.

    The reverse stock split will consolidate every 40 shares into one, reducing the total share count from 696 million to 17.4 million. The stock closed at 16 cents on Wednesday, down 7.5% for the day and more than 99% below its price a year ago. A reverse split does not affect a company’s overall market value; it is a structural adjustment designed to increase the price per share above the listing threshold.

    Broader Sector Downturn

    Nakamoto’s challenges are not isolated. Reports suggest that crypto treasury companies have generally experienced a downturn since 2025, with many trading below the value of their assets. Some companies have begun selling their Bitcoin holdings to address debt. For example, Genius Group liquidated its entire 84 Bitcoin reserve in February.

  • Bitcoin Holds Ground Amidst Bearish Sentiment

    Bitcoin Holds Ground Amidst Bearish Sentiment

    Bitcoin Shows Resilience Amidst Bearish Pressure

    Bitcoin continues to demonstrate resilience despite facing mounting bearish pressure below the critical $78,800 resistance zone. Although short-term volatility and repeated rejections have slowed bullish momentum, the overall market structure still indicates an active uptrend, with buyers continuing to defend key support levels and positioning for a potential rebound.

    Bitcoin Finds New Support Around $77,000

    In a recent market assessment, Ultimae highlights that while Bitcoin briefly dipped below the $78,700 support level, the $77,000 zone is currently functioning as the primary defensive floor. This transition suggests that the market is successfully absorbing recent selling pressure, with $77,000 acting as a key technical pivot for bulls to stabilize the price.

    Currently, market participants are closely monitoring the Exponential Moving Average (EMA) as a decisive technical indicator. The asset’s ability to hold above this moving average suggests that short-term momentum is attempting to base, providing a foundation for the next potential move. Should price action result in a clear breach of this immediate support, $75,700 is the next area of interest where liquidity may be gathered. Further downside pressure from that point would bring the $73,500 support into focus, a level that has historically served as a critical zone for institutional interest.

    Despite the recent pullback, Ultimae maintains a distinctly bullish perspective, asserting that Bitcoin’s broader uptrend remains firmly intact. The analyst views the current price decline as a healthy consolidation phase rather than a shift in the longer-term structural trend. To invalidate this upward structure, the price would need to break decisively through the support line of the red box highlighted on the chart. Until that boundary is breached, the current market environment is viewed as constructive. While a minor drift toward $73,500 remains a possibility, the expectation is for a recovery bounce to materialize soon.

    Bitcoin Rebounds Strongly After Triple Retest

    Bitcoin has demonstrated resilience by retesting the 4-hour bullish order block (OB) three times, resulting in a healthy rebound of $1,700 that successfully cleared the $77,400 resistance level. According to analyst Qingtianbtc, this recovery to the $78,300 level and the subsequent move toward the 4-hour bearish OB are well within expected market behavior.

    The current upward movement is interpreted as a temporary relief rally rather than a trend reversal. Investors should anticipate that any push into the $78,300 to $78,800 range will serve as a point of exhaustion before the asset resumes its downward trajectory. Meanwhile, the 4-hour bearish OB, spanning from $78,800 to $79,600, currently acts as a zone of significant resistance, as a sustained breakout above this range remains unlikely in the immediate term.

  • Bitcoin Worth Nearly $500B Vulnerable to Quantum Computing: Glassnode

    Bitcoin Worth Nearly $500B Vulnerable to Quantum Computing: Glassnode

    Bitcoin Vulnerable to Quantum Computing Threat

    Nearly one-third of all Bitcoin in circulation, representing over 6 million coins and valued at over $469 billion at the time of writing, is potentially vulnerable to theft if powerful quantum computers become a reality, according to a report published Wednesday by blockchain analytics firm Glassnode.

    The analysis examined the Bitcoin blockchain to identify coins with exposed public cryptographic keys. It found that 6.04 million BTC, or 30.2% of the total supply, is susceptible to quantum risk, while the remaining 13.99 million BTC shows no public-key exposure. This estimate of exposed coins is lower than some previous figures, which have been closer to 7 million BTC.

    The concern stems from the architecture of Bitcoin’s security. Each coin is controlled by a private key, which corresponds to a public key visible on the blockchain under specific circumstances. The potential threat is that a sufficiently advanced quantum computer, using an algorithm known as Shor’s algorithm, could theoretically recover a private key from a known public key.

    In such a scenario, any coin whose public key has already been revealed on-chain would be immediately vulnerable, requiring no transaction to be initiated.

    Categories of Exposure

    Glassnode divides the exposed supply into two categories. Structural exposure accounts for 1.92 million BTC, or 9.6% of the issued supply. These coins are locked in script formats that inherently reveal the public key, including early “pay-to-public-key” outputs associated with Bitcoin’s pseudonymous founder, Satoshi Nakamoto, legacy multisignature structures, and more recent Taproot outputs. Many of these coins may be effectively unrecoverable, such as those in lost wallets or dormant holdings that cannot be moved to safer address formats.

    The larger and more actionable category is what Glassnode terms operational exposure. This category totals 4.12 million BTC, or 20.6% of the issued supply. These coins were not initially vulnerable but became so through address reuse, a practice where a wallet receives multiple transactions at the same address, eventually broadcasting the public key during a spend and leaving any remaining balance exposed.

    Exchange Vulnerabilities

    Exchanges are significantly represented in this category. Within the operationally unsafe category, 1.66 million BTC, or 8.3% of the total supply, is exchange-related, accounting for approximately 40% of all operationally unsafe Bitcoin. The exposure varies significantly across platforms. Among the largest exchanges, Coinbase’s labeled balances appear largely concentrated in non-exposed structures, with only 5% exposed, while Binance and Bitfinex show comparatively high susceptible balances—85% and 100%, respectively.

    Glassnode emphasized that its findings should not be interpreted as a risk ranking or a signal of solvency for any particular firm, stressing that the data reflects custody design choices rather than imminent danger. Sovereign Bitcoin holdings fared considerably better, with the United States, United Kingdom, and El Salvador all showing zero quantum exposure.

    Mitigation Strategies and Future Developments

    The report does not predict when, or if, a quantum computer capable of cracking Bitcoin’s encryption will exist. Instead, it presents its analysis as a baseline, noting that for exchanges and custodians, address hygiene, reserve management, reduced key reuse, and migration planning are practical measures to reduce visible exposure.

    These findings come as quantum computing advances globally and as the Bitcoin developer community discusses protocol-level responses, including a proposed update known as BIP-360, which would introduce more quantum-resistant transaction formats. Another official proposal suggests freezing coins that are not migrated by a set deadline.

    Estimates for “Q-Day”—when a quantum computer becomes powerful enough to crack the cryptography securing blockchains like Bitcoin and Ethereum—range from 2030 to 2032 and beyond. On Thursday, the United States government announced that it will invest over $2 billion in quantum startups and planned foundries to fuel American industry.

  • Spotify, Universal Partner on AI Remix Tool

    Spotify, Universal Partner on AI Remix Tool

    Taylor Swift Fans Could Soon Remix Her Songs Legally on Spotify

    Spotify users may soon be able to legally generate AI remixes of Taylor Swift’s songs.

    Spotify and Universal Music Group announced licensing agreements on Thursday that will allow Spotify Premium users to create AI-generated covers and remixes using music from participating artists and songwriters.

    “The most valuable innovations in the music business always bring artists and fans closer together,” said Lucian Grainge, Chairman and CEO of Universal Music Group, in a statement. “That principle is at the heart of this pioneering AI-enabled superfan initiative, which is designed to support human artistry, deepen fan relationships, and create additional revenue opportunities for artists and songwriters.”

    Universal Music Group represents artists including Taylor Swift, Chappell Roan, The Weeknd, Sabrina Carpenter, Lana Del Rey, Post Malone, Billie Eilish, and Olivia Rodrigo.

    AI Music Controversy

    The debate over AI-generated music intensified in 2023 after a fake song using AI versions of Drake and The Weeknd’s voices circulated on Spotify and YouTube before Universal Music Group compelled platforms to remove it. More recently, Taylor Swift moved to trademark parts of her voice and image after AI-generated deepfakes and fake endorsements targeting the singer spread online.

    Tech Platforms Experiment with AI Remix Tools

    The announcement also coincides with increasing experimentation with AI remix tools by tech platforms. Earlier this week at Google I/O, YouTube introduced a Shorts Remix feature powered by Gemini that allows users to reimagine other people’s videos by turning them into anime clips, pixel art, or altered scenes with added characters and effects.

    Spotify stated that the new tool will launch as a paid add-on for Spotify Premium subscribers. Fans will be able to generate licensed covers and remixes using generative AI technology, while participating artists and songwriters will receive compensation tied to the AI-generated works created on the platform.

    “Solving hard problems for music is what Spotify does, and fan-made covers and remixes are next,” said Alex Norström, Spotify Co-CEO, in a statement. “What we’re building is grounded in consent, credit, and compensation for the artists and songwriters that take part.”

  • Binance Sees XRP Whale Activity Surge, Contrasting Coinbase Data

    Binance Sees XRP Whale Activity Surge, Contrasting Coinbase Data

    XRP is trading below $1.40, with selling pressure keeping the price within a range that has frustrated investors for weeks. The market is cautious, but an analysis by CryptoQuant, tracking exchange-level flow data, has identified a behavioral divergence between two major crypto venues, adding a structural dimension to the current price action.

    Whale Activity on Binance

    The analysis examines the composition of XRP outflows on Binance, specifically the share of daily withdrawals dominated by transactions exceeding one million XRP, a threshold typically associated with whale-scale activity. This share has climbed to 57.6%, the highest since a 66% spike on March 28. A similar elevated reading appeared in late April, near 60%. These instances of whale withdrawal dominance have all occurred within the $1.33 to $1.42 price zone.

    This repetition creates a pattern that the analysis identifies as structurally significant. XRP’s largest holders are moving coins away from Binance at elevated rates each time the price enters this specific range, not in a single event, but consistently across multiple occasions. Whether this behavior reflects accumulation, repositioning, or preparation for a move is the question the comparison with Coinbase begins to answer.

    Divergence on Coinbase

    The Coinbase data presents a contrasting picture. On Coinbase, the above-1-million XRP outflow category has dropped to 14.8%, its lowest level since April 11. Simultaneously, the mid-sized wallet category of 10,000 to 100,000 XRP outflows has risen from 19% to 36% between April 11 and May 19. Coinbase is not seeing whale dominance in its withdrawals but rather a shift toward smaller and mid-sized participants moving coins, a structurally different behavioral profile from Binance.

    The divergence between the two venues creates a specific analytical signal. Binance is experiencing renewed whale withdrawal dominance at 57.6%, while Coinbase is experiencing the opposite, with its largest outflow category at a six-week low and mid-sized activity increasing.

    The $1.33 to $1.42 price zone, where whale withdrawal dominance has been observed on Binance, is now a key level for XRP traders to monitor. Large holders have become active at this range on three separate occasions, and the current 57.6% reading suggests they are active again.

    The CryptoQuant analysis does not definitively declare the signal bullish or bearish. Whale withdrawals can reflect accumulation, self-custody migration, or repositioning. The data confirms that the largest XRP participants are behaving differently from smaller ones, and they are doing it at a price level they have chosen repeatedly before.

    Technical Outlook

    XRP continues to trade within the same compressed range that has defined price action since March, currently holding near $1.36 after another rejection below the $1.45 resistance area. The daily chart shows a market trapped between weakening momentum and persistent support, resembling accumulation rather than trend continuation.

    The repeated defense of the $1.30–$1.33 region is a key detail. Since the February sell-off, every meaningful retrace into this zone has attracted buyers, preventing a deeper breakdown. Bulls have repeatedly failed to reclaim the 200-day moving average near $1.50, leaving XRP range-bound.

    Volume continues to contract compared to the February sell-off, confirming that volatility and directional conviction have faded. The market appears to be entering a low-liquidity equilibrium phase where both buyers and sellers are waiting for a catalyst. Technically, the current structure remains neutral-to-bearish while the price trades below the major moving averages. However, sustained consolidation above $1.30 keeps the broader base intact. A breakout above $1.45 could trigger momentum toward the $1.60 region, while losing $1.30 would likely expose XRP to another test of the February lows.

  • Syndicate Labs Shuts Down, Citing Rollup Ecosystem Decline

    Syndicate Labs Shuts Down, Citing Rollup Ecosystem Decline

    Syndicate Labs, an on-chain development startup backed by Andreessen Horowitz (a16z), announced it is winding down operations after five years of building infrastructure for on-chain developers.

    Rollup Market Shifts Cited

    The company cited significant shifts in the rollup market as the primary reason for the decision. In a statement on X, Syndicate Labs said its main focus had been providing developers with better tools to build and scale on-chain applications. However, according to the company, the rollup market has changed dramatically in recent years. It noted that fewer new rollups are entering the space, while several older projects have slowly disappeared.

    The company stated that the market had moved away from the type of technology it was building, adding that EVM rollups are no longer considered the industry standard. Instead, developers are increasingly choosing to build custom chains from scratch through consulting teams, which has resulted in less reusable infrastructure and reduced network effects across the ecosystem.

    Syndicate Labs said it had spent years trying to support the growth of on-chain applications and wished the outcome had been different. Despite the shutdown of the development company, the group stressed that the broader Syndicate ecosystem will continue to exist separately through the Syndicate Network Collective, a Wyoming-based DUNA that holds governance authority over SYND tokens.

    The company also clarified that the collective operates independently from Syndicate Labs, meaning governance over the SYND token is not immediately impacted. It explained that a successor organization could continue maintaining the DUNA structure, though it also outlined plans for an orderly wind-down if no successor emerges.

    Bridge Compromise and Token Lockups

    The Syndicate Commons Bridge on Base was compromised in late April after attackers gained access through a leaked private key, which eventually drained 18.5 million SYND tokens worth nearly $330,000. However, Syndicate Labs stated that the shutdown decision was unrelated to the incident.

    The affected customer and all SYND holders on Commons Chain have already been reimbursed using treasury reserves specifically set aside for such events. The company further stated that team members and investors remain subject to token lockups and that no affiliated individual has been able to access allocations for short-term benefit. Syndicate Labs said its vesting structure was designed around long-term incentives.

    Broader Industry Trends

    Syndicate Labs is not the only crypto project to struggle after security incidents and changing market conditions this year. Two DeFi projects moved toward shutdowns after struggling with the fallout from major security and financial problems. In February, Solana-based DeFi aggregator Step Finance, along with SolanaFloor and Remora Markets, ceased operations after a wallet compromise led to roughly $30 million in losses. The teams said fundraising and acquisition talks failed to produce a recovery plan.

    A month later, Balancer Labs proposed restructuring the Balancer protocol after months of financial strain, declining TVL, and a November exploit that accelerated liquidity outflows across the platform.

  • AI Romance Users Conceal Full Usage from Partners: 69%

    AI Romance Users Conceal Full Usage from Partners: 69%

    One in seven young adults in committed relationships regularly use AI romantic companion chatbots, and many are keeping this behavior secret from their partners, according to a new report from researchers at Brigham Young University, the Institute for Family Studies, and the Wheatley Institute.

    Study Findings

    The report, titled “Secret Soulmates,” surveyed 2,431 U.S. adults aged 18 to 30 who were dating, engaged, or married.

    “While general engagement with AI companions was high for both men and women, when looking across all results, some specific cautions appear warranted when it comes to young adult men,” the study stated. “Men were more likely to engage with AI companions, more likely to create sexual content with AI platforms and masturbate during these interactions, and more likely to prefer AI interactions to the interactions with their real-life partners.”

    Nearly 30% of regular users said their partner was unaware of the behavior. Another 11% said their partner was only somewhat aware, while 14% said their partner was mostly, but not fully aware.

    “Taken together, this means that half of regular AI companion users who were in committed relationships had either completely hidden or only partly disclosed their use of AI companion platforms,” the study concluded.

    A separate survey conducted in January by Gallup and the Harvard Business Review found that approximately one in ten adults aged 18 to 28 used AI chatbots as a girlfriend or boyfriend at least once a month.

    According to the study, 68% of frequent users said it was easier to discuss their feelings with their AI companion than with other people, and 60% wished their partners behaved more like the AI.

    Researchers also found that regular AI companion use was associated with lower relationship quality. Frequent users were 46% less likely to report stable relationships and 40% less likely to report high-quality communication with their partners.

    The only category where frequent users reported higher scores was physical intimacy satisfaction. Researchers cautioned that this result may reflect what they described as “fragile satisfaction” tied to conflict avoidance rather than healthier relationships.

    Married respondents reported higher rates of AI companion use than those who were dating, with over 17% of married young adults reporting regular interaction with AI companions. Men reported higher usage rates across most categories, though over 10% of women in committed relationships also reported regularly chatting or roleplaying with AI companions.

    Digisexuality and AI Companions

    Researchers describe the rise of AI romantic companions as part of “digisexuality,” a term used in academic research to describe sexual or romantic relationships experienced primarily through technology.

    Before the public launch of ChatGPT in 2022, the term was often associated with technologies like online pornography, sexting, virtual reality pornography, sex dolls, and robots.

    As AI chatbots became more conversational, the term expanded to include people forming emotional or romantic attachments to large language models and AI companions. Online communities such as Reddit’s r/AIRelationships, r/AIBoyfriends, and r/MyGirlfriendIsAI contain thousands of posts from users who describe chatbots as partners, spouses, or emotional companions.

    Researchers and online communities have also used related terms, including “technosexual,” “AIsexual,” and “wiresexual,” to describe people romantically or sexually involved with AI.

    Despite the growing digisexual subculture, researchers noted the level of secrecy surrounding AI companion use.

    “Whether this is due to embarrassment, concerns about their partner’s reaction, or struggles articulating the use of AI companions to a partner, many men appear content to engage with their secret soulmate in private, with little to no partner disclosure,” the study concluded.

  • DeepSeek Develops Claude Code, Backed by Beijing.

    DeepSeek Develops Claude Code, Backed by Beijing.

    DeepSeek Enters the Agentic Coding Arena

    DeepSeek, the Chinese AI lab spun out of the quantitative investment firm High-Flyer, is assembling a new team to develop “Code Harness,” an agentic coding tool designed to directly challenge Anthropic’s Claude Code and OpenAI’s Codex. The announcement came from DeepSeek engineer Deli Chen, who posted two job listings on X this week seeking a product manager and an R&D engineer. Both positions are based in Beijing.

    The company’s requirement for employees to be based in Beijing, rather than other tech hubs like Hangzhou or Shenzhen, underscores the city’s significance as the symbolic and political center of China’s technological ambitions. Beijing is also where the government’s relationship with the AI industry is most direct and closely monitored by Washington.

    “You can call it DeepSeek Code or something,” Chen wrote in the post, accompanied by laughing emojis.

    The job listings, also posted on High-Flyer’s recruitment platform, are unusually transparent about DeepSeek’s goals. The team’s internal formula is “Model + Harness = Agent.” The product manager role specifically requires experience with Claude Code, Codex, Cursor, GitHub Copilot, Manus, and OpenClaw, indicating DeepSeek’s intention to compete with these established agentic tools. Salary details for both positions were not disclosed.

    Agentic coding tools, which autonomously plan, write, test, and debug software projects, have become a key battleground in the AI industry. DeepSeek aims to capitalize on this trend.

    DeepSeek possesses a notable advantage: its latest model, DeepSeek V4, already functions natively within Claude Code. The V4 lineup, released on April 24, includes V4 Flash, optimized for speed and handling agentic tasks at $0.14 per million input tokens, and V4 Pro, the more capable tier, priced at $0.435 per million tokens during an introductory promotion ending May 31. In comparison, Anthropic’s flagship model, Claude Opus 4.7, costs $15 per million input tokens. This price difference could be significant for teams using continuous, loop-intensive agent pipelines.

    The development of Code Harness is about controlling the entire user experience. By building a harness, DeepSeek would manage the interface developers use, including checkpoints, terminal commands, rollback features, and integrations. This is where user loyalty is established, and where revenue is likely to follow.

    DeepSeek has a history of downplaying its capabilities before delivering significant results. When it released R1 in January 2025, the reasoning model caused a nearly $600 billion drop in Nvidia’s market capitalization, as it matched OpenAI’s o1 at a lower cost. Despite initial skepticism, DeepSeek has continued to innovate.

    No launch date has been announced for Code Harness.

  • Chainlink On-Chain Activity Soars as Exchange Supply Dwindles

    Chainlink On-Chain Activity Soars as Exchange Supply Dwindles

    Chainlink has fallen below the $10 mark as the market experiences a potential further downturn, leaving holders facing a price structure that offers little immediate relief. While the decline is evident, a report by CryptoOnchain has identified a development in the network data from earlier this month that provides context for the current price weakness.

    Network Activity Spike

    Between May 9 and 10, Chainlink’s active address count surged to over 280,000, a figure that requires context. The network’s historical baseline is approximately 3,000 daily active addresses. This spike represents a 93-fold increase from that baseline, compressed into a two-day window, with no precedent in Chainlink’s recent on-chain history. This indicates significant activity on the network, far exceeding routine levels.

    In traditional on-chain analysis, such a spike would typically suggest retail panic, large token movements toward exchanges, and preparation for liquidation. The historical pattern for anomalies of this scale is distribution, where large holders and retail participants simultaneously rush to sell, creating selling pressure. However, this assumption does not hold in this case.

    Contrasting Exchange Flows

    The CryptoOnchain report cross-references the network surge with exchange flow data, revealing a different picture. Despite the extreme active address anomaly, Binance’s LINK reserve has been declining steadily for the past 14 days, falling from 86.3 million to 85.8 million tokens. The 7-day average netflow remains heavily negative, with outflows consistently outpacing inflows throughout the entire period.

    Market participants were actively withdrawing LINK from Binance during the period of intense network activity. If the spike in active addresses represented panic selling, the exchange flow data would show coins moving onto exchanges rather than away from them. The data, however, shows coins leaving exchanges.

    Structural Interpretation

    This divergence between network intensity and exchange behavior suggests a structural interpretation rather than a sentiment-driven one. Tokens migrating toward self-custody or being locked in smart contracts, potentially related to CCIP adoption and the expanding use of Chainlink’s cross-chain infrastructure, would produce this pattern: explosive on-chain movement alongside declining exchange reserves and persistently negative netflow.

    The implication is a reduction in the liquid float available for immediate sale. This reduction, occurring alongside genuine network utility growth, creates supply tightness that historically precedes structural price appreciation.

    Price Analysis

    Chainlink continues to trade under pressure after losing the $10 level. The daily chart shows the market trapped within a broader bearish structure, despite signs of stabilization. LINK is currently trading near $9.60 after rejecting sharply from the recent local high around $10.70, where sellers prevented a breakout above the descending resistance zone that has capped price action since January.

    The chart shows LINK consolidating between roughly $8.80 and $10.00 for several weeks, forming a tightening range just above the 200-day moving average. That level near $9.20 is becoming increasingly important because it has acted as dynamic support throughout May. Bulls have repeatedly defended the area, preventing a deeper retracement back toward the February lows near $7.50.

    The 200-day exponential moving average continues trending downward above the current price, reinforcing the idea that the broader macro trend remains fragile despite the recent recovery attempt. Volume has also cooled notably compared to the capitulation phase seen in February, suggesting that the latest decline reflects exhaustion and consolidation rather than panic-driven selling. For bulls, reclaiming the $10.00–$10.70 region remains essential to shift momentum decisively back in favor of buyers.

  • Nvidia Earnings Top Estimates, Stock Falls; BofA Recommends Buying

    Nvidia Earnings Top Estimates, Stock Falls; BofA Recommends Buying

    Nvidia just reported its most profitable quarter ever, yet its stock price declined. This pattern has emerged, with the chipmaker’s shares falling after three of its last four earnings calls, despite consistently strong financial results.

    Bank of America remains optimistic, however. Lead analyst Vivek Arya and his team reiterated their “buy” rating yesterday, designating Nvidia as a top pick and increasing their price target from $320 to $350. This suggests a potential 56.6% increase from the current price of $223.47.

    The investment note’s headline read: “Beat/raise speaks volumes, ignore noise, buy top pick.”

    Decoding the Jargon

    For those unfamiliar with Wall Street terminology, a “beat” signifies that a company’s earnings exceeded analysts’ predictions. A “raise” indicates that the company’s guidance, or forecast for the following quarter, also surpassed expectations. When both occur simultaneously, it typically signals very positive news. Bank of America advises investors to disregard the stock’s recent correction, which they consider “noise.”

    Record-Breaking Quarter

    Nvidia’s first-quarter revenue reached a record $81.6 billion, an 85% increase year-over-year and a 20% rise from the previous quarter. Analysts had anticipated approximately $79.1 billion. Nvidia exceeded this by 3.1%, or roughly $2.5 billion, in a single quarter. To put it in perspective, the prior quarter’s revenue was already a record at $68.1 billion. Nvidia added $13.5 billion on top of that within three months.

    The primary driver behind this growth is data centers, the large-scale server facilities that power AI models, cloud computing, and much of the internet.

    Data center revenue alone reached $75.2 billion, up 92% year-over-year. This figure is almost evenly split between major cloud providers like Amazon and Microsoft, and a rapidly expanding group of AI companies, factories, and industrial clients.

    Adjusted earnings per share were $1.87, surpassing the $1.73 analysts had predicted. The gross margin, representing the revenue remaining after production costs, remained at 75%. Free cash flow for the quarter, reflecting the actual cash generated by the company after all expenses, reached $48.6 billion. During the earnings call, Jensen Huang commented, “Agentic AI has arrived, doing productive work, generating real value and scaling rapidly.”

    Agentic AI is currently a major topic of discussion on Wall Street.

    Market Growth and Nvidia’s Position

    The core argument centers on the size and growth rate of the market Nvidia is targeting.

    Bank of America previously estimated the total AI market at $1.7 trillion. They now project it to quadruple, exceeding $3 trillion by 2030. Within this market, they anticipate Nvidia will hold approximately 78% of the AI accelerator market, which comprises chips specifically designed for AI workloads. This essentially gives Nvidia a near-monopoly in what Bank of America considers the fastest-growing technology market they have ever tracked.

    The bank also recently upgraded its assessment of a newer opportunity. Nvidia is entering the agentic CPU chip market, which involves processors designed for AI agents, software capable of autonomously performing complex tasks without human intervention. Bank of America increased its estimate for this market from $125 billion to $200 billion, and states that Nvidia has already secured $20 billion in demand for the second half of this fiscal year.

    The demand is not speculative. Customer purchase commitments totaled $145 billion this quarter, up from $95 billion just three months prior. AWS alone has committed to deploying approximately 1 million Nvidia GPUs through 2027. These are contractual agreements, not projections.

    Risks and Considerations

    Bank of America identifies six formal risks. Two are particularly relevant for those holding or considering Nvidia stock.

    The first is the stock’s own substantial presence in the market. Nvidia now accounts for 8.3% of the S&P 500 index, the benchmark that tracks the 500 largest public companies in America. Approximately 78% of active fund managers already own the stock. With such a high level of ownership, there are fewer potential new buyers to drive the price higher.

    The second risk involves custom chips. Major hyperscale cloud companies like Google, which recently launched its eighth-generation AI chips specifically designed to reduce reliance on Nvidia, are investing heavily in in-house alternatives. Bank of America counters that Nvidia is still expected to maintain over 70% of the accelerator market long-term, arguing that full-platform support and AI factory infrastructure are difficult for custom chips to replicate.

    There is also a recurring criticism that Nvidia’s investments in companies like OpenAI and Anthropic, as a vendor selling them chips, constitute circular spending.

    Financial Projections

    Bank of America raised its earnings-per-share estimates by 9% for fiscal year 2027 (to $9.09) and 15% for fiscal year 2028 (to $13.27). In other words, Nvidia earned $4.55 per share last fiscal year. Bank of America expects that to roughly double to $9.09 this year, then reach $13.27 the following year. Earnings per share growing at 43% annually is rare for any company, especially one already valued at $5.5 trillion.

    At its current price, Nvidia trades at 19.7 times its estimated 2027 earnings. A metric that adjusts the P/E for growth rate, where lower is better, sits at 0.5x against a Mag-7 average of 3.9x.

    Free cash flow is projected to increase from $96.7 billion last fiscal year to $186.8 billion in 2027 and $282 billion in 2028. The company also increased its quarterly dividend 25-fold, from $0.01 to $0.25 per share, and announced an additional $80 billion share buyback authorization, bringing the total repurchase capacity to roughly $120 billion.

    The $350 price target is based on 26x estimated 2027 earnings, within Nvidia’s historical range of 25x to 56x. The next significant event is CEO Jensen Huang’s keynote at Computex on June 1, where Bank of America anticipates he will detail Nvidia’s agentic AI roadmap and CPU strategy.