Perspective: The current AI supercycle will last 15 years, but most are still buying stocks in the first FOMO stage

marsbitОпубликовано 2026-05-09Обновлено 2026-05-09

Введение

This article outlines a 15-year AI supercycle, segmented into four investment stages. It argues that while most investors are still focused on the first stage, smart money is already moving to the third. **Stage 1: The Foundation (2023-2025) - Priced In** The semiconductor layer (e.g., NVIDIA, AMD) is complete. While growth continues, the historic entry opportunity is over as risk/reward has compressed. **Stage 2: The Build-Out (2025-2027) - In Progress** This phase involves building the necessary physical infrastructure: power/utilities (CEG), cooling (VRT), networking (ANET), and nuclear SMRs (OKLO, SMR). Significant upside remains, but obvious names have already moved. **Stage 3: The Asymmetric Bet (2026-2028) - Positioning Window** AI moves into the physical world. Key areas include robotics/autonomy (Tesla Optimus), space/defense/drones (Rocket Lab, LUNR), and critical materials. This stage presents the best asymmetric risk/reward and is where positioning should occur now. **Stage 4: The Endgame (2028+) - Software Dominance** The mega-cap cloud platforms (Microsoft, Alphabet, Amazon, Meta), with their massive capital expenditure, will build the AI software layer and AGI infrastructure, aiming to win the entire cycle. **Core Conclusion:** The cycle is confirmed in Stage 2. Stage 3 (robotics, space, defense, nuclear SMRs) is where capital is currently rotating for maximum opportunity, while the majority of investors are expected to be 12 months behind this shift.

Author: Rand Group (@cryptorand)

Compiled by: Deep Tide TechFlow

Deep Tide Intro: Crypto KOL Rand Group breaks down the AI supercycle into four stages, from chips to infrastructure to robots to platform software, marking the core targets and risk-reward ratios for each stage. His judgment is: Stage 1 (Semiconductors) is over, Stage 2 (Power/Cooling/Networks) is being priced, and the true asymmetric opportunity lies in Stage 3 — robotics, space, defense, nuclear energy.

The AI supercycle will last 15 years. This is year three.

Most investors are still buying Stage 1 stocks, but smart money is already rotating into Stage 3.

I've broken the entire cycle into four stages, with the most important tickers labeled for each.

The AI supercycle is the biggest investment theme of this generation. Bigger than mobile internet, bigger than cloud computing. A 15-year structural shift that will reshape every industry in the global economy. Hyperscale cloud providers just committed $725 billion in capex for 2026, nearly double last year's. Microsoft, Google, Amazon, Meta — each over $100 billion individually.

This is not speculation.

🔴 Stage 1: Over (2023-2025)

The foundation layer is complete. AMD was up 78% in 2025, NVDA up 39%, Intel just delivered a blowout Q1, pushing the Philadelphia Semiconductor Index above 10,000 for the first time. Chips still drive every stage, but the historic entry opportunity is gone; the risk-reward has compressed.

Tickers: NVDA, AMD, ARM, INTC, AVGO, MU, GLW

Sectors: Semiconductors, Memory, Photonics/Optics

Status: Foundation complete, still growing, but priced in.

🟡 Stage 2: Buildout Peak (2025-2027)

The stage most investors are just waking up to. CEG acquiring Calpine to become the largest private U.S. power producer at 55 GW. GEV up over 200% in a year. VRT co-designing cooling for NVIDIA's Rubin architecture. GLW up 74% YTD on fiber demand. Nuclear SMR is the biggest dark horse — OKLO, SMR, BWXT are laying direct power lines for data centers.

Still upside, but the most obvious names have moved.

Tickers: CEG, GEV, VRT, VST, TLN, ANET, GLW, MOD, EQIX, OKLO, SMR, BWXT, NNE

Sectors: Power/Grid, Cooling, Networking, Nuclear SMR Buildout Peak

Note: Nuclear SMR is the hidden major opportunity.

🟡 Stage 3: Positioning Window (2026-2028)

The stage where AI leaves the data center and enters the physical world. Most will be late.

Tesla is converting its Fremont factory into an Optimus robot production line — $25 billion capex, targeting mass production in H2 2026. Rocket Lab posted a record $602M revenue, backlog at $1.85B. LUNR up 47% YTD with $943M in contracts. KTOS's Valkyrie drone selected by the Marine Corps.

The positioning window is open now.

Tickers: TSLA, RKLB, LUNR, KTOS, AVAV, PATH, ISRG, MP, FCX, ALB, ASTS

Sectors: Robotics/Autonomy, Space/Defense/Drones, Rare Earths

Judgment: The asymmetric risk-reward is here.

🟢 Stage 4: Endgame (2028+)

The endgame. Microsoft capex $190B, Alphabet $190B, Amazon $200B, Meta $145B. Google Cloud backlog exceeds $460B. They are building AI software dominance and AGI infrastructure. Quantum computing is early, but IONQ and D-Wave are laying the groundwork.

The platforms controlling the software layer win the entire supercycle.

Tickers: MSFT, GOOGL, AMZN, META, ORCL, IONQ

Sectors: AI Software Dominance, AGI Infrastructure, Decade-long thesis

Strategy: Buy the dips.

Key Conclusions

  • Stage 2 is confirmed (hyperscale $725B capex)
  • Stage 3 is where smart money is positioning — robotics, space, defense, nuclear
  • SMR is the core trade from 2026 to 2028
  • Most will rotate into these names 12 months late

A 15-year supercycle. Not a single trade. Stage 1 is over, Stage 2 is being priced, Stage 3 is where you should be.

Связанные с этим вопросы

QAccording to the article, what is the author's view on the duration and current stage of the AI supercycle?

AThe author believes the AI supercycle will last 15 years and is currently in its third year. The first stage (2023-2025) is already over, the second stage (2025-2027) is in progress, and the third stage (2026-2028) is where the most asymmetric opportunities lie.

QWhat sectors or 'stages' does the author identify as having the best asymmetric risk/reward opportunity right now?

AThe author identifies the third stage as having the best asymmetric risk/reward opportunity. This stage includes robotics/autonomous systems, space/defense/drones, and rare earths, with specific mentions of companies like Tesla, Rocket Lab, and Intuitive Machines.

QWhich specific sector within the 'construction boom' (second stage) is highlighted as a major hidden opportunity?

AWithin the second stage (the construction boom), the author highlights nuclear energy, specifically Small Modular Reactors (SMRs), as the major hidden opportunity. Companies mentioned include Oklo, NuScale Power (SMR), and BWX Technologies.

QWhat key metric is cited as evidence confirming the transition to the second stage of the AI supercycle?

AThe author cites the $725 billion in committed capital expenditure for 2026 by hyperscale cloud providers (Microsoft, Google, Amazon, Meta) as the key metric confirming the transition to the second stage. This amount is nearly double that of the previous year.

QWhat does the author suggest is the strategy for investing in the 'Endgame' (fourth stage) companies?

AFor the 'Endgame' or fourth stage companies (like Microsoft, Alphabet, Amazon, Meta), which control the AI software platform, the author's suggested strategy is to 'buy the dips,' indicating a long-term, patient accumulation approach.

Похожее

Why Pricing Social Interactions is Doomed to Fail?

Titled "Why Putting a Price on Social Interaction Is Doomed to Fail," this article critiques attempts to monetize social networks directly through SocialFi models, arguing their inevitable failure stems from a fundamental misunderstanding of media dynamics. Using Marshall McLuhan's theory of "hot" and "cold" media, the author posits that social networks are inherently "cold" media. Their value isn't contained in individual posts but is co-created through user participation, interpretation, and fragmented, ongoing interaction (e.g., replies, shares). This ambiguity and need for user involvement are core to their function. The article asserts that SocialFi projects like Friend.tech failed because introducing real-time, tradable financial pricing (a definitive "hot" signal) into this "cold" environment doesn't add a layer—it replaces the medium's essence. The unambiguous price signal overshadows and nullifies the nuanced, participatory social signal. Users become traders, not participants, and when speculative profits vanish, the underlying social ecosystem—never genuinely cultivated—collapses entirely. This principle extends beyond crypto. The author argues platforms like Twitter have gradually "heated up" through metrics (likes, retweets counts, algorithmically defined value), shifting users from participants to performers and eroding organic engagement. The solution isn't to abandon capital but to manage its entry point. Successful models like Substack, Patreon, or Bandcamp allow capital to "condense" at specific, isolated nodes (e.g., subscriptions, one-time payments) without permeating and "heating" every social interaction. They preserve the core "cold," participatory medium while enabling monetization at designated boundaries. The NFT boom and bust serves as a stark parallel: the ancient "cold" medium of collecting (valued for story, community, gradual accumulation) was rapidly destroyed by platforms that introduced real-time floor prices, rarity scores, and trading dashboards, transforming collectors into speculators and vaporizing cultural value when prices fell. The core lesson: "Liquidity equals heat." Injecting high liquidity and definitive pricing into a "cold" participatory medium doesn't optimize it; it fundamentally alters and destroys its value-creating mechanism. The future lies not in pricing every social gesture but in finding precise, non-invasive points for capital to condense without overheating the entire ecosystem.

marsbit5 мин. назад

Why Pricing Social Interactions is Doomed to Fail?

marsbit5 мин. назад

Jensen Huang's CMU Speech: In the AI Era, Don't Just Watch, Build

Jensen Huang, CEO of NVIDIA and a first-generation immigrant, delivered the commencement address to Carnegie Mellon University's class of 2026. He shared his personal journey from a humble background to founding NVIDIA, emphasizing resilience, learning from failure, and the responsibility that comes with leadership. Huang framed the present moment as the dawn of the AI revolution, a shift he believes is more profound than previous computing waves. He described AI as fundamentally resetting computing—moving from human-written software to machines that understand, reason, and use tools. This will create a new industry for generating intelligence and transform every sector. While acknowledging AI's potential to automate tasks and displace some jobs, Huang distinguished between the *tasks* of a job and its core *purpose*. He argued AI will augment human capability, not replace humans. The real risk, he stated, is not AI itself, but people being left behind by those who effectively use AI. He presented AI as a generational opportunity for massive infrastructure investment—in chip factories, data centers, energy grids, and advanced manufacturing—that could re-industrialize nations like the U.S. and bridge the digital divide by making computing and intelligent tools accessible to all. Huang called for a balanced approach: advancing AI safely and responsibly, establishing prudent policies, ensuring broad access, and encouraging universal participation. He urged the graduates not to fear the future but to engage with optimism and ambition, reminding them of CMU's motto, "My heart is in the work." His core message was clear: this is their moment to actively build and shape the AI-powered future, not merely observe it.

marsbit1 ч. назад

Jensen Huang's CMU Speech: In the AI Era, Don't Just Watch, Build

marsbit1 ч. назад

The Era Has Arrived Where Human Writers Must Prove They Are Not Machines

The article describes an era where AI-generated content is flooding the market, forcing human authors to prove they are not machines. It begins with the example of dozens of AI-written, error-ridden biographies of Henry Kissinger appearing on Amazon within hours of his death, a pattern repeated for other deceased celebrities and even living experts who find fraudulent books under their names. This spam content has exploded, with monthly new book releases on platforms like Amazon reaching 300,000 by late 2025. The issue spans genres, from suspiciously high proportions of AI-written teen romance and self-help books to dangerous, AI-generated foraging guides containing lethal advice. The platforms' automated review systems, designed to catch plagiarism and banned words, are ill-equipped to detect AI-generated text that avoids these pitfalls while being nonsensical or fraudulent. The problem has infiltrated traditional publishing. A major publisher, Hachette, had to recall a bestselling horror novel after AI detection tools suggested 78% of its content was machine-generated. An acclaimed European philosophy book was later revealed to be entirely written by AI under a fake author persona. In response, authors are fighting back. At the 2026 London Book Fair, 10,000 writers published a blank book titled "Don't Steal This Book" containing only their signatures—using emptiness as a protest weapon in an age of AI overproduction. Initiatives like the "Human Author Certification" program have emerged, ironically placing the burden on humans to prove their work is not machine-made. The article warns of a vicious cycle: AI-generated low-quality books pollute the data used to train future AI models, leading to "model collapse" and an ever-worsening flood of digital waste, eroding trust in publishing and devaluing human creativity.

marsbit1 ч. назад

The Era Has Arrived Where Human Writers Must Prove They Are Not Machines

marsbit1 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

2025 год — год институциональных инвесторов, в будущем он будет доминировать в приложениях реального времени.

1.8k просмотров всегоОпубликовано 2025.12.16Обновлено 2025.12.16

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на AI (AI) представлены ниже.

活动图片