[NitpickLawyer]

Keep in mind that the "news cycle" isn't of much use in this field. For 2025, almost all "mainstream" media was dead wrong in their takes. Remember the Deepseek r1 craze in feb25? Where nvda is dead, oai is dead and so on? Yeah... that went well. Remember all the "no more data" craze? Despite no actual researcher worth their salt saying it or even hinting at it? Remember the "hitting walls" rhetoric?

The media has been "social media'd", with everything being driven by algorithms, everything being about capturing attention at the cost of everything else. Negativity sells. FUD sells.

[viraptor]

Some of those weren't really wrong.

> Remember all the "no more data" craze? Despite no actual researcher worth their salt saying it or even hinting at it?

We ran out of fresh interesting data. A large chunk of training needs to generate its own now. Synthetic data training became a huge thing over the last year.

> Remember the "hitting walls" rhetoric?

Since then the basic training slowed down a lot and improvements are more in the agentic and thinking solutions, with lots more reinforcement training than in the past.

The fact we worked around those problems doesn't mean they weren't real. It's like people say Y2K wasn't a problem... ignoring all the work that went into preventing issues.

[NitpickLawyer]

> We ran out of fresh interesting data.

No, we didn't. Hassabis has been saying this for a while now, and Gemini3 is proof of that. The data is there, there are still plenty of untapped resources.

> Synthetic data training became a huge thing over the last year.

No, people "heard" about it over the last year. Synthetic data training has been a thing in model training for ~2 years already. L3 was post-trained on synthetic-only data, and was released in apr24. Research only was even earlier with the phi family of models. Again, if you're only reading the mainstream media you won't get an accurate picture of these things, as you'd get from actually working in this field, or even following good sources, read the key papers and so on.

> The fact we worked around those problems doesn't mean they weren't real.

The way the media (and some influencers in this space) have framed it over the last year is not accurate. I get that people don't trust CEOs (and for good reasons), but even amodei was saying there is no data problem in early interviews in 25.