This article doesn't mention TPUs anywhere. I don't think it's obvious for people outside of google's ecosystem just how extraordinarily good the JAX + TPU ecosystem is. Google several structural advantages over other major players, but the largest one is that they roll their own compute solution which is actually very mature and competitive. TPUs are extremely good at both training and inference[1] especially at scale. Google's ability to tailor their mature hardware to exactly what they need gives them a massive leg up on competition. AI companies fundamentally have to answer the question "what can you do that no one else can?". Google's hardware advantage provides an actual answer to that question which can't be erased the next time someone drops a new model onto huggingface.

[1]https://blog.google/products/google-cloud/ironwood-tpu-age-o...

Google is winning on every front except... marketing (Google has a chatbot?), trust (who knew the founding fathers were so diverse?), safety (where's the 2.5 Pro model card?), market share (fully one in ten internet users on the planet are weekly ChatGPT users), and, well, vibes (who's rooting for big G, exactly?).

But I will admit, Gemini Pro 2.5 is a legit good model. So, hats off for that.

As an Ex-OpenAI employee I agree with this. Most of the top ML talent at OpenAI already have left to either do their own thing or join other startups. A few are still there but I doubt if they'll be around in a year. The main successful product from OpenAI is the ChatGPT app, but there's a limit on how much you can charge people for subscription fees. I think soon people expect this service to be provided for free and ads would become the main option to make money out of chatbots. The whole time that I was at OpenAI until now GOOG has been the only individual stock that I've been holding. Despite the threat to their search business I think they'll bounce back because they have a lot of cards to play. OpenAI is an annoyance for Google, because they are willing to burn money to get users. Google can't as easily burn money, since they already have billions of users, but also they are a public company and have to answer to investors. But I doubt if OpenAI investors would sign up to give more money to be burned in a year. Google just needs to ease off on the red tape and make their innovations available to users as fast as they can. (And don't let me get started with Sam Altman.)

It is sort of funny to me how the sentiment about whoever seems to be leading in ML changes so frequently (in particular here on HN.) A couple months ago it felt like people were sure that Google completely fucked it up for themselves (especially due to the fact that they invented the transformer but didn't productize it themselves at first.)

For a short while, Claude was the best thing since sliced cheese, then Deepseek was the shit, and now seemingly OpenAI really falls out of favor. It kinda feels to me like people cast their judgement too early (perhaps again in this case.) I guess these are the hypecycles...

Google is killing it right now, I agree. But the world might appear completely different in three months.

Several people have suggested that LLMs might end up ad-supported. I'll point out that "ad supported" might be incredibly subtle/insidious when applied to LLMs:

An LLM-based "adsense" could:

   1. Maintain a list of sponsors looking to buy ads
   2. Maintain a profile of users/ad targets 
   3. Monitor all inputs/outputs
   4. Insert "recommendations" (ads) smoothly/imperceptibly in the course of normal conversation

No one would ever need to/be able to know if the output:

"In order to increase hip flexibility, you might consider taking up yoga."

Was generated because it might lead to the question:

"What kind of yoga equipment could I use for that?"

Which could then lead to the output:

"You might want to get a yoga mat and foam blocks. I can describe some of the best moves for hips, or make some recommendations for foam blocks you need to do those moves?"

The above is ham-handed compared to what an LLM could do.