OpenAI raises $8.3B at $300B valuation

Use of Funds, Burn Rate, and Scale

• Many argue $8.3B barely dents OpenAI’s capex ambitions (multi‑GW datacenters, massive GPU clusters); at current spend (reported ~$9B/year), this round might fund well under a year of operations.
• Comparisons to xAI’s ~$1B/month losses and enormous GPU spend illustrate how easily such sums can be “turned into heat, warm water, and expensive sand.”

Valuation, Revenue, and Growth

• Reported ARR/annualized revenue around $12–13B implies ~23x revenue; some see this as insane without clear margins or profitability path.
• Others say 23x isn’t extreme for >100% YoY growth and big optionality, especially versus Nvidia‑like multiples or search‑ads‑scale markets.
• Debate over whether this is another tech bubble vs a rational bet that at least one AI lab will be a multi‑trillion‑dollar winner.

Business Model, Moat, and Competition

• Skeptics think base models and APIs will be commoditized; switching between providers or to open models is seen as relatively easy.
• Supporters point to ChatGPT’s mainstream mindshare (for many, “AI” == “ChatGPT”) and hundreds of millions of users as a significant moat.
• Consensus that subscriptions alone can’t justify $300B; expected future levers include search‑like advertising, affiliate/commerce referrals, vertical apps (code, productivity, agents), enterprise contracts, and government/military work.

Ads, Search, and Consumer Behavior

• Many expect ChatGPT to siphon high‑value queries from Google and become an ad platform; others note Google’s entrenched ad ecosystem and platform control.
• Worries that LLM answers will embed stealth product placement and behavioral manipulation.

Governance, Ethics, and Structure

• Strong resentment over the shift from non‑profit to effectively profit‑maximizing entity, seen as a betrayal of the original mission.
• Comparisons to past bubbles and even Enron‑style “vibes‑based” valuations appear, though others stress OpenAI’s very real, widely used product.