[woah]

> Perhaps most telling was the sadness expressed by several mathematicians regarding the increasing secrecy in AI research. Mathematics has long prided itself on openness and transparency, with results freely shared and discussed. The closing off of research at major AI labs—and the inability of collaborating mathematicians to discuss their work—represents a significant cultural clash with mathematical traditions. This tension recalls Michael Atiyah's warning against secrecy in research: "Mathematics thrives on openness; secrecy is anathema to its progress" (Atiyah, 1984).

Engineering has always involved large amounts of both math and secrecy, what's different now?

[bo1024]

AI is undergoing a transition from academic research to industry engineering.

(But the engineers want the benefits of academic research -- going to conferences to give talks, credibility, intellectual prestige -- without paying the costs, e.g. actually sharing new knowledge and information.)

[analog31]

It involves math at a research level, but from what I've observed, people in industry with engineering job titles make relatively little use of math. They will frequently tell you with that sheepish smile: "Oh, I'm not really a math person." Students are told with great confidence by older engineers that they'll never use their college math after they graduate.

Not exactly AI by today's standards, but a lot of the math that they need has been rolled into their software tools. And Excel is quite powerful.