If You Missed Palantir or Nvidia. This is Far Bigger.

Finance-focused summary (quantum computing investing thesis)

The speaker argues that the quantum computing sector has entered a strong news cycle over the past ~3 months, driven by major industry and government actions plus early commercialization. However, many investors still haven’t properly understood what changed—especially following a sharp October mania peak and subsequent large drawdowns.

The talk frames quantum as a potentially massive long-term technological shift (compared to AI’s early days and past technology adoption cycles), while emphasizing that returns can be distorted by entry timing and poor exit discipline.

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Key markets / macro points

• Primary driver claimed: Quantum adoption is accelerating because major funders—especially governments and hyperscalers—are moving from research toward deployment.
• Electricity / power constraint: The speaker claims electricity is the biggest constraint in AI buildouts and argues quantum hardware can be “cheaper to run” relative to large GPU clusters used in AI. This is presented as a reason cloud companies have stronger incentives to engage.
• Sector sizing (forecast): A quantum computing market forecast of $850B is cited (with a humorous aside to imply a long runway).

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Major instruments / tickers mentioned

Quantum computing / related equities

• INQ (InfleXion Quantum)
• D-Wave (also referenced via ticker QBTS)
• Rietti / IQ (context suggests Rigetti; speaker also says “Rietti” and “IQ”)
• INFQ (InfleXion)
• XND (Xanadu)
• QBTS (D-Wave)
• IBM
• Google (Alphabet)
• Honeywell (via stake in Quantinuum; “Continuum” mentioned)
• Oracle
• Amazon
• Microsoft
• Nvidia (mentioned as a key AI cloud hardware baseline; not presented as a quantum pick)

Other “strategic” mentions (not necessarily tickers)

• Rare earths
• Nuclear (as related to power strategy)
• Chips (as an analogy to how strategic government funding can shift)

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Key timeline / events cited

• ~Last summer: Prior quantum picks and a framework introduced.
• May (this year): A “full breakdown again” plus updated stocks.
• May (government action): ~$2B invested into nine companies as equity purchases (minority shares), not grants/subsidies.
• October last year: Identified as the top of the mania (prices peaked).
• 11th of August: Oracle announcement described as a multi-year deal.
• “Last few weeks”: Mention of an HRL demo with strong error rates.

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What “changed” (framework items)

The speaker claims the sector improved due to three concrete changes, shifting quantum from “pure research” toward commercial readiness:

1. 1) Revenue became real and growing

   • Example: INQ revenue up 287% year-over-year
   • Also: ~40% ahead of estimates
   • Improved free cash flow, but still net losses

2. 2) Real order backlog

   • Example cited: ~$500M backlog (nearly half a billion)

3. 3) Distribution / ownership / channel shift

   • Government equity ownership (minority stakes)
   • Hyperscalers distributing the product (Oracle/Amazon/Microsoft/IBM), implying earlier access by IT departments
   • “You can now buy it” rather than only research-stage partnerships

Additional engineering / scaling rationale

• Error rates improve with scaling: The speaker cites Google’s Willow approach as showing error rates falling as chip size scales up.
• Manufacturability angle: Mentions HRL running 18 cubits with ~0.02% error rate, using spin cubits, allegedly made with ordinary semiconductor equipment (rather than deep-freeze exotic setups). The point is to change the “science experiment” framing into something more scalable.

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Key numbers and performance references

Prior “about a year ago” pick outcomes

• One stock: $10,000 → $115,000 (+1,050%)
• Second stock: +827%
• Third stock: +180%
• Fourth stock: not bought because it “wouldn’t break $20,” supposedly never exceeding that; it was around $18 at the time.

Sector drawdowns

• The speaker repeatedly claims quantum stocks are still ~45% to 70% below October highs.

Oracle / power comparison

• Quantum machine Helios: draws ~60 kilowatt
• AI supercomputer draw: ~16,000 to 39,000 kilowatts
• Emphasis: “hundreds of times bigger”

INQ (earnings-related references)

• Revenue growth: +287% YoY
• ~40% ahead of estimates
• Mentions $80M revenue in one quarter as “real money”
• Still “burning cash” / still “lost money in reality”

HRL error-rate claim

• 0.02% error rate at 18 cubits

Rigetti-like valuation caution threshold

• The speaker says he only wanted to own one stock (likely Rigetti) if it exceeded about $20 (“~20-ish dollars”).

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Explicit recommendations / portfolio construction approach

The “tiers” approach (adoption-to-risk framework)

The speaker shifts from “pure lottery tickets” toward a three-tier allocation based on risk:

• Tier 1 (lower-risk “pigs and shovels”)

  • IBM (cloud “plumbing” via manufacturing + system roadmap)
  • Google (via Willow chip ecosystem; large cash base)
  • Honeywell (industrial + stake in quantum business via Quantinuum)

• Tier 2 (pure-play quantum companies; revenue/backlog required; careful sizing)

  • INQ / InfleXion (fast growth, but still unprofitable)
  • Rigetti (moving toward margins/breakeven; still risky)
  • Mentions backlog ~500M, more commercial than government-mix heavy

• Tier 3 (most speculative “lottery tickets”; very small positions)

  • INFQ (InfleXion mentioned as candidate for ultra-speculative exposure)
  • Xanadu (XND) (photonics; room-temperature angle; high binary risk)
  • D-Wave (QBTS): not “removed,” but “demoted” because it’s “no longer one of my topics,” though it’s still described as plausibly viable

Risk management / exit discipline (core message)

The main emphasis is not valuation/modeling, but when to sell:

• The speaker repeatedly claims most investors lose money due to lack of an exit plan, not lack of intelligence.
• Recommends learning “Wall Street rules” / a “selling rule book” via a free live training (hosted online).
• Warns that a stock can lose a large fraction quickly (example: ~losing half your money in the sector in ~8 weeks).
• Notes severe drawdowns (e.g., a “down 70%” scenario).

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Disclaimers / disclosures

• “I am not a registered financial adviser. I don’t give financial advice. I share my thoughts, my research.”
• Encourages viewers to read, pull it apart, and decide what to do.

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Presenters / sources mentioned

• Winston (co-host; referenced as having discussed earlier stocks; also runs the “Winston app”)
• The speaker (main narrator; name not provided in subtitles)
• Sources/events discussed:
  • Google CEO (quoted: “Quantum today is where AI was 5 years ago.”)
  • BBC News Tonight reporter (clarification of who said the quote)
  • Oracle (continuum / Helios installation announcement)
  • American government (described as buying equity stakes)
  • HRL (lab referenced for cubit/error-rate demonstration)
  • Morgan Stanley (report referenced: “market could grow a hundred times” in an earlier timeframe)
  • Global Foundries (mentioned in the context of government equity split)