Hello and welcome to Eye on AI. In this edition….Gemini 3 puts Google at the top of the AI leaderboards…the White House delays an Executive Order banning state level AI regulation…TSMC sues a former exec now at Intel…Google Research develops a new, post-Transformer AI architecture…OpenAI is pushing user engagement despite growing evidence that some users develop harmful dependencies and delusions after prolonged chatbot interactions.
I spent last week at the Fortune Innovation Forum in Kuala Lumpur, Malaysia, where I moderated several panel discussions around AI and its impacts. Among the souvenirs that I came back from KL with was a newfound appreciation for the extent to which businesses outside the U.S. and Europe really want to build on open source AI models and the extent to which they are gravitating to open source models from China.
My colleague Bea Nolan wrote a bit about this phenomenon in this newsletter a few weeks ago, but being on the ground in Southeast Asia really brought the point home: the U.S., despite having the most capable AI models out there, could well lose the AI race. And the reason is, as Chan Yip Pang, the executive director at Vertex Ventures Southeast Asia and India, said on a panel I moderated in KL, that the U.S. AI companies “build for perfection” while the Chinese AI companies “build for diffusion.”
One sometimes hears a U.S. executive, such as Airbnb CEO Brian Chesky, willing to say that they like Chinese open source AI models because they offer good enough performance at a very affordable price. But that attitude remains, for now at least, unusual. Many of the U.S. and European executives I talk to say they prefer the performance advantages of proprietary models from OpenAI, Anthropic, or Google. For some tasks, even an 8% performance advantage (which is the current gap separating top proprietary models from Chinese open source models on key software development benchmarks) can mean the difference between an AI solution that meets the threshold for being deployed at scale and one that doesn’t. These execs also say they have more confidence in the safety and security guardrails built around these proprietary models.
