Feed: Slashdot
Feed Link: https://slashdot.org/
---

Title: Should US Open-Weight AI Labs 'Distill' Frontier Models Too?

Link: https://news.slashdot.org/story/26/09/13/2334...

Silicon Valley giants and national security experts "are calling for action
against Chinese companies engaged in model distillation," reports CNBC. But
"I would do nothing," says Y Combinator CEO Garry Tan. "We could argue that
there should be an American distillation regime." Distillation is the process
of using the outputs of a more capable AI model to train a smaller or less
capable one, sometimes illicitly... Anthropic has accused Chinese companies
such as Moonshot AI, DeepSeek, and MiniMax of the practice, while OpenAI
believes DeepSeek's V3 and R1 model architectures were distilled from its own
GPT-4 and GPT-4o models. In the midst of this, the U.S.'s National Security
Agency, Cybersecurity and Infrastructure Security Agency, and Federal Bureau
of Investigation released an official cyber security advisory warning on the
topic on Tuesday... But Tan believes regulators should focus less on curbing
distillation and more on creating an equilibrium between open weight models
and frontier models - as long as frontier models retain a price premium that
allows their business model to remain feasible. "This is actually the ideal
case. You want open weight models to give people freedom and access," he
explained. "If I were a regulator, that's what I would go after." Tan
acknowledged that this is a hard balance to strike, calling it "a tightrope."
Nevertheless, he says it's a balance worth pursuing - saying it "could result
in the best possible outcome." Tan later told TechCrunch he'd like to see
America with more open-weight options that aren't Chinese, built by smaller
U.S. open-weight AI labs using those same training techniques on products
from America's frontier AI labs: Anthropic CEO Dario Amodei had previously
publicly called on U.S. regulators to crack down on distillation. It's
notable that the commander of Silicon Valley's prestigious and prolific
startup accelerator doesn't agree. To be clear, Tan isn't advocating for
American AI labs to use stolen credentials to distill. He wants them to be
free to come in the front door. In fact, his argument is twofold. He feels
it's an overreach for AI labs to dictate what their customers can do with the
information their models share with them. He also notes that the proprietary
AI labs didn't ask permission when they vacuumed up as much human knowledge
as they could to train their models. They famously ingested plenty of
copyrighted material without the permission of those intellectual property
holders. "Controlling what users and customers do with API calls to closed
weight models feels constraining, and there's a role government can play here
to normalize the fact that access to intelligence that was trained on broad
public access data should itself also be more a form of a public good than
something locked away behind restrictive terms of service," he told
TechCrunch when asked why American labs should be free to distill, too... To
him, the true AI doomer scenario is for all the immense power of frontier AI
to wind up in the hands of a single powerful, proprietary provider. "The
nightmare scenario, the doomer scenario for AI is that there's just one
company," he said. "It has the best access to capital. It has the best AI
researchers. It runs away with it and suddenly there's one company that's
monolithic. And that would be bad."

Read more of this story at Slashdot.

---
VRSS v2.1.180528