Some designs use the screen estate so ineffectively that only the title and a big, boring, generic graphic is shown on a phone. Users have to scroll all the way down to see the content and find what they need. Better designs show the menu, navigation points, and meaningful, aesthetic graphics. Other designs, such as Gemini 3.6, were quite sophisticated but not optimized for traffic and would not load on a 3G connection. However, a simple static website should load instantly on a mobile connection.

That said, even a simple web page has many requirements, so expecting a turnkey, ready-made design if the user is not guiding the process is not realistic. Thus, I believe the best choice nowadays is a model with good design skills that understands and adheres to an iterative design process, offering a good initial design as a starting point but also prompting the user to provide guidance and feedback. As the design process runs through many cycles, the initial cost should be modest. But more importantly, the model should understand its own design, be able to explain its choices so it can converse with the user using concrete elements in a accurate language to guide the process. IMO, this is still missing from even the frontier models today.

Chinese labs must follow similar trajectories plus their specific efficiency improvements. That also explains the jump from DeepSeek 4 performance in April and July releases. They both use the same pre-trained model as well.

Thus, efficiency and pragmatic enterprise application is the next focus. And for that, the old guards are not necessarily the best. Google needs new blood for this venture, preferably from China with their practical engineering view. Every big AI lab is on the verge. Steering the right way will help avoid a catastrophe and come out stronger than ever. A weak captain could sand the ship and drag down who knows what with them.

Better though, take samples and test against food standards from countries where they actually produce and eat fish sauce. If the sauce is still good (could be due to the high salt content, not sure though), just let Ngo bottle it and sell the good stuff, internationally!

Others have talked about many aspects of the life annd integration process in Germany. But one thing I’m missing from your post is what did you do to your German colleagues and friends? How did you treat them?

It’s certainly interesting to know but I think it’s also an important aspect we often forget.

[1] https://aiproem.substack.com/p/must-read-deepseek-liang-wenf...

He also admits that it’s still a long way to it and along the way you have to recoup some money, too. But that is not their main motive, because focus too much on this short term goal will lower their probability of AGI success and it’s trivial to what AGI can bring. Liang stressed on restraining and emphasized that it’s part of their culture.

Thus, they continue invest in AI because they believe in breakthrough and not just being better.

Without a critical mass of adoption, mesh applications are largely useless.