Comment by cmiles8 16 hours ago
The real code red here is less that Google just one-upped OpenAI but that they demonstrated there’s no moat to be had here.
Absent a major breakthrough all the major providers are just going to keep leapfrogging each other in the most expensive race to the bottom of all time.
Good for tech, but a horrible business and financial picture for these companies.
As history in tech shows you don’t need everyone copying you to be in big trouble, just one or two well positioned players. Typically that has been a big established player just adding your “special sauce product” as a feature to an existing well established product. Thats exactly what’s playing out now and why OpenAI is starting to panic as thy know how that movie typically ends.
> for these companies
They’re absolutely going to get bailed out and socialize the losses somehow. They might just get a huge government contract instead of an explicit bailout, but they’ll weasel out of this one way or another and these huge circular deals are to ensure that.
>They’re absolutely going to get bailed out and socialize the losses somehow.
I've had that uneasy feeling for a while now. Just look at Jensen and Nvidia -- they're trying to get their hooks into every major critical sector as they're able to (Nokia last month, Synopsys just recently). When chickens come home to roost, my guess is that they'll pull out the "we're too big to fail, so bailout pls" card.
Crazy times. If only we had regulators with more spine.
The shenanigans that set off the GFC were much more nakedly corrupt and didn’t have even a fig leaf of potential usefulness to anybody to justify them. The revolution failed to materialize then. If the AI bust isn’t worse for the median person than 2008, I don’t think people in power have anything to fear.
Even Chinese leadership is somewhat skeptical about AI maximalism [0] with worries about "AI Washing" by enthusiastic cadre trying to climb rungs [1], and evoking Solow's Paradox [2].
There is still significant value in AI/ML Applications from a NatSec perspective, but no one is actually seriously thinking about AGI in the near future. In a lot of cases, AI from a NatSec perspective is around labor augmentation (how do I reduce toil in analysis), pattern recognition (how do I better differentiate bird from FPV drone), or Tiny/Edge ML (how do I distill models such that I can embed them into commodity hardware to scale out production).
It's the same reason why during the Chips War zeitgeist, while the media was harping about sub-7nm, much of the funding was actually targeted towards legacy nodes (14/28nm), chip packaging (largely offshored to China in the 2010s because it was viewed as low margins/low value work), and compound semiconductors (heavily utilized in avionics).
[0] - https://www.zaobao.com.sg/news/china/story20250829-7432514
[1] - https://finance.sina.com.cn/roll/2025-09-30/doc-infsfmit7787...
Absolutely. And they will figure out how to bankrupt any utilities and local governments they can in the process by offloading as much of their costs overhead for power generation and shopping for tax rebates.
Maybe there's no tangible moat still, but did Gemini 3's exceptional performance actually funnel users away from ChatGPT? The typical Hacker News reader might be aware of its good performance on benchmarks, but did this convert a significant number of ChatGPT users to Gemini? It's not obvious to me either way.
Definitely. The fact that they inject it into Google Search means that even fewer people who have never used ChatGPT or just used it as a "smarter" Google search will just directly try the search function. It is terrible for actually detailed information i.e. debugging errors, but for summarizing basic searches that would have taken 2-3 clicks on the results is handled directly after the search. I feel bad for the website hosts who actually want visitors instead of visibility.
Anecdotally yes. Since launch I’ve observed probably 50% of the folks that were “ChatGPT those that” all the time suddenly talking about Gemini non-stop. The more that gets rolled into Google’s platform the more there’s point to using separate tooling from OpenAI. There’s a reason Sam is calling this “code red.”
Absolutely. I don't understand why investors are excited about getting into a negative-margin commodity. It makes zero sense.
I was an OpenAI fan from GPT 3 to 4, but then Claude pulled ahead. Now Gemini is great as well, especially at analyzing long documents or entire codebases. I use a combination of all three (OpenAI, Anthropic & Google) with absolutely zero loyalty.
I think the AGI true believers see it as a winner-takes-all market as soon as someone hits the magical AGI threshold, but I'm not convinced. It sounds like the nuclear lobby's claims that they would make electricity "too cheap to meter."
It's the same reason for investing in every net-loss high-valuation tech startup of the past decade. They're hoping they'll magically turn into Google, Apple, Netflix, or some other wealthy tech company. But they forget that Google owns the ad market, Apple owns the high-end/lifestyle computer market, and Netflix owns tv/movie habit analytics.
Investors in AI just don't realize AI is a commodity. The AI companies' lies aren't helping (we will not reach AGI in our lifetimes). The bubble will burst if investors figure this out before they successfully pivot (and they're trying damn hard to pivot).
Helping to prevent a possible skynet scenario probably makes those checks easier to write.
There's a lot more than money at stake.
> I don't understand why investors are excited about getting into a negative-margin commodity. It makes zero sense.
Long term, yes. But Wall Street does not think long term. Short or medium term, you just need to cash out to the next sucker in line before the bubble pops, and there are fortunes to be made!
Did Google actually train a new model? The cutoff dates for Gemini 3 and 2.5 are the same.
Surely, they would throw current events, news articles, the latest snapshot of WikiPedia, etc...
I can't imagine it making sense to purposefully neglect to keep a model as up-to-date as possible!
So why did Google stock increase massively since about when Gemini 2.5 Pro was released, their first competitive model?
That’s not evidence of anything in and of itself. RIMs stock price was at its highest in 2009 two years after the iPhone came out.
I was curious about this - if my Google results are accurate, it looks like the stock actually peaked in June 2007, the same month that the iphone was released.
It seems that Blackberry's market share of new phone sales peaked at 20% in 2009. So I'm not sure if it's coincidence, but it looks like the market actually did a pretty good job of pricing in the iphone/android risk well before it was strongly reflected in sales.
You are correct. I remember the anecdote as something peaking. I thought it was the stock price. It was actually market share
Because Google already has many healthy revenue streams that will benefit from LLMs and all it has to do in the AI space is remain competitive.
Yep, I thought they might have some secret sauce in terms of training techniques, but that doesn't seem to be the case.
It drives me a bit crazy when people say OpenAI has no moat.
Yes, companies like Google can catch up and overtake them, but a moat is merely making it hard and expensive.
99.999.. perc of companies can't dream of competing with OpenAI.