Nvidia just paid $20B for a company that missed its revenue target by 75%

Original Article ↗ Hacker News Discussion ↗

Regulators, Monopolies, and Political Corruption

  • Many see the deal as an example of weak or captured market regulators, likening the US government to being “for sale” and comparing Nvidia’s position to other big-tech monopolies.
  • Others push back, arguing corruption and regulatory capture have worsened recently, not remained constant, with debate over whether the degree of corruption matters.
  • Some cite FTC underfunding and staff cuts as concrete evidence regulators are being weakened.
  • There’s mention of DOJ merger guidelines that could allow future administrations to revisit serial anti‑competitive behavior, though several doubt this will actually happen.

What Nvidia Really Bought

  • Multiple comments argue this isn’t a classic acquisition but effectively an expensive “acqui-hire”: Nvidia paying to secure Groq’s key technical leaders and IP without absorbing the whole org.
  • Others note Nvidia structured this as IP licensing plus hiring, potentially to dodge CFIUS/antitrust scrutiny while still neutralizing a competitor.

Impact on Groq and Innovation

  • One side claims Nvidia is stifling independent innovation by removing a differentiated hardware competitor and consolidating AI compute under one giant.
  • Another side counters that:
    • Groq the company still exists, retains its hardware, gets ~$20B, and may expand GroqCloud or build “version 2.0.”
    • The IP license is non‑exclusive, so in theory other companies could still use Groq’s tech.
  • Several doubt the optimistic view, predicting most of the cash will go to investors, with employees and long‑term R&D underfunded, but this is speculative and currently unclear.

Bubble vs Strategic Logic

  • Some think the transaction is pure AI‑bubble behavior: huge multiples on shaky revenue projections and hype over fundamentals.
  • Others see a clear strategic fit:
    • Nvidia shoring up its weak spot in low‑latency inference.
    • Removing a future rival while they’re still “cheap.”
    • Accessing non‑TSMC fabrication and specialized architecture.
  • A few stress that both can be true: real technology plus bubble-level pricing.

Revenue Projections, Valuation, and Misrepresentation

  • Several commenters highlight the article’s confusion between valuation and forecast revenue (e.g., $2B valuation vs $500M revised 2025 revenue).
  • Clarifications:
    • Groq reportedly cut 2025 revenue projections from $2B to $500M.
    • Its valuation later increased to ~$6.9B in a subsequent round.
  • Some float the idea that overly rosy projections could be fraud; others note missed forecasts are common and only fraudulent if knowingly false—something that is currently unclear.

Startups as Big-Tech R&D and Equity Concerns

  • There’s broad agreement that this fits a long‑standing pattern: startups act as external, high‑risk R&D labs for giants (similar to biotech/pharma and prior Cisco/Google playbooks).
  • Multiple comments worry about a growing trend where leadership and IP are bought out, but common employees with equity are left with little in “acqui-hire” style deals.

Geopolitics and China

  • One thread warns that selling advanced chip tech and allowing certain foreign ties risks enabling cheaper Chinese clones via reverse engineering.
  • Others agree this could weaken long‑term US competitiveness, though details here are sparse and mostly alarmist, not deeply substantiated in the discussion.

Article Style and Reliability

  • Some readers liked the technical explanations and visualizations (e.g., money stacks); others found them condescending or irrelevant.
  • The author engaged in the thread, clarified using transcription (not LLM generation), and corrected factual errors, but several still view the piece as biased toward an “AI bubble” narrative and mixing up key financial concepts.