> The market is saying something about the comparative value of OpenAI.
Is it?
At what point are the models going to all be "good enough", with the differentiating factor being everything else, other than model ranking?
That day will come. Not everyone needs a Ferrari.
Edit: I misread the parent, I think they're saying the same thing.
Model rankings are irrelevant. No one cares.
The differentiating factor will be access to proprietary training data. Everyone can scrape the public web and use that to train an LLM. The frontier companies are spending a fortune to buy exclusive licenses to private data sources, and even hiring expert humans specifically to create new training data on priority topics.
Including paying poets and other experts by the hour to improve the models https://conversationswithtyler.com/episodes/brendan-foody/
> At what point are the models going to all be "good enough", with the differentiating factor being everything else, other than model ranking?
It's already come for vast swathes of industries.
Most organizations have already been able to operationalize what are essentially GPT4 and GPT5 wrappers for standard enterprise usecases such as network security (eg. Horizon3) and internal knowledge discovery and synthesis (eg. GleanAI back in 2024-25).
Yes, and that is why I used the phrase comparative value. The concept of winning business based on being #1 on the benchmarks is dead.
I agree, and most of my peers do as well. This is why most of us shifted to funding AI Applications startups back in 2023-24. Most of these players are still in stealth or aren't household names, but neither are ServiceNow, Salesforce, Palo Alto Networks, Wiz, or Snowflake.
Foundation Models have reached a relative plateau and much of the recent hype wasn't due to enhanced model performance but smart packaging on top of existing capabilities to solve business outcomes (eg. OpenClaw, Antheopic's business suite, etc).
Most foundation model rounds are essentially growth equity rounds (not venture capital) to finance infra/DC buildouts to scale out delivery or custom ASICs to enhance operating margins.
This isn't a bad thing - it means AI in the colloquial definition has matured to the point that it has become reality.