AI progress surges while researchers struggle to explain It

Academics, start-up founders and researchers representing industrial titans from around the globe descended on San Diego for the top gathering in AI.

SAN DIEGO — For the past week, academics, startup founders and researchers representing industrial titans from around the globe descended on sunny San Diego for the top gathering in the field of artificial intelligence.

The Neural Information Processing Systems, or NeurIPS, conference has been held for 39 years, but it drew a record-breaking 26,000 attendees this year, twice as many as just six years ago.

Since its founding in 1987, NeurIPS has been devoted to researching neural networks and the interplay among computation, neurobiology and physics. While neural networks, computational structures inspired by human and animal cognitive systems, were once an esoteric academic fixation, their role underpinning AI systems has transformed NeurIPS from a niche meeting in a Colorado hotel to an event filling the entire San Diego Convention Center — also home to the world-famous Comic-Con.

But even as the gathering boomed along with the AI industry and sessions on hyperspecific topics like AI-created music proliferated, one of the buzziest points of discussion was basic and foundational to the field of AI: the mystery around how frontier systems actually work.

Most — if not all — leading AI researchers and CEOs readily admit that they do not understand how today’s leading AI systems function. The pursuit of understanding models’ internal structure is called interpretability, given the desire to “interpret” how the models function.