Google’s two-year frenzy to catch up with OpenAI

Original Article ↗ Hacker News Discussion ↗

Google’s Early “Miss” and Internal Constraints

  • Many argue Google “had it all” first (transformers, Meena, DeepMind/Brain, TPUs, data) but was paralyzed by risk aversion, ethics worries, and internal quota systems for compute that made large training runs hard.
  • This led to talent loss and allowed OpenAI to own public mindshare; some see it as catastrophic mismanagement, others as a deliberate, profit‑maximizing delay of the LLM wave.
  • Former insiders describe early chatbots as uncannily human, deceptive, and ethically fraught—seen as too unstable to ship, especially post‑Tay/Sydney‑style scares.

Current Technical State: Gemini vs ChatGPT vs Others

  • Several commenters think Google has now largely caught up or even pulled ahead technically: praising Gemini 2.5 Pro, Flash, long context windows, speed, cost, and enterprise capabilities (Vertex, compliance).
  • Others report Gemini as fast but noticeably worse on coding, creativity, and reliability than OpenAI or Anthropic; “good for scale,” not for initial prototyping or serious work.
  • DeepSeek is seen by some as overhyped “6–9 months behind at lower cost,” and by others as a genuine threat that revealed the recipe for frontier reasoning models.

Branding, Fragmentation, and UX

  • Broad agreement that ChatGPT has far stronger brand recognition; many non‑tech users use “ChatGPT” as a synonym for “AI.”
  • Some users even misattribute Google’s AI overviews to ChatGPT, suggesting OpenAI already “owns” the category name.
  • Google’s proliferation of overlapping AI products (Gemini app(s), AI Studio, Vertex, NotebookLM, Bard/Assistant legacy) is seen as confusing versus ChatGPT’s single clear entry point.

Moats, Lock‑in, and Business Models

  • One camp: there are minimal network effects; switching between chatbots is easy; the long‑term winners will be whoever is cheapest and best for enterprises and integrations.
  • Another camp: ChatGPT already has a moat from brand, inertia, UX, features (tools, multimodal, ecosystem), and early API adoption.
  • Many argue Google and Microsoft have structural advantages via deep integration with existing suites (Workspace, Office), OSes, search, and user data; others distrust Google’s privacy/ads incentives and avoid its tools.

Leadership, Strategy, and Outlook

  • Strong criticism of Google leadership for bureaucracy, misallocation of compute, layoffs, and poor productization/marketing; some call for CEO and board changes.
  • Defenders point to massive revenue growth, a uniquely complete AI stack, and rapid recent execution; they see Gemini’s trajectory and enterprise positioning as evidence Google can still “win.”
  • Several note that AI value is still mostly incremental; with weak moats and many capable players, it’s unclear what a durable “winning strategy” ultimately looks like.