Although Hammond says he barely remembers his life before computers and coding, there was indeed a time when his world was much more analog. Hammond grew up on the East Coast and spent his high school years in Salt Lake City, where his mother was a social worker and his father was a professor of archaeology at the University of Utah. Over the course of 50 years, Philip C. Hammond excavated several sites in the Middle East and made dozens of trips to Jordan, earning him the nickname Lion of Petra. Kris joined these expeditions for three summers, working as his father’s surveyor and draftsman.

“Now, once a week, I ask ChatGPT for a biography of my father, as an experiment,” Hammond says, bemused. “Sometimes, it gives me a beautifully inaccurate bio that makes him sound like Indiana Jones. Other times, it says he is a tech entrepreneur and that I have followed in his footsteps.”

While those biographical tidbits are more AI-generated falsehoods, Hammond and his father have both traced intelligence from different worlds — one etched in stone and another in silicon. Wanting a deeper understanding of the meaning of intelligence and thought, Hammond studied philosophy as an undergraduate at Yale University and planned to go law school after graduation. But his trail diverged when a fellow member of a local sci-fi club suggested that Hammond, who had taken one computer science class, try working as a programmer.

“After nine months as a programmer, I decided that’s what I wanted to do for a living,” Hammond says.

That sci-fi club guy was Chris Riesbeck, who is also now a professor of computer science at McCormick. Hammond earned his doctorate in computer science from Yale in 1986. But he didn’t abandon philosophy entirely. Instead, he applied those abstract frameworks — consciousness, knowledge, creativity, logic and the nature of reason — to the pursuit of intelligent systems.

“The structure of thought always fascinated me,” Hammond says. “Looking at it from the perspective of how humans think and how machines ‘think’ — and how we can ‘think’ together — became a driver for me.”

But the word “think” is tenuous in this context, he says. There’s a fundamental and important distinction between true human cognition and what current AI can do — namely, sophisticated mimicry. AI isn’t trying to critically assess data to devise correct answers, says Hammond. Instead, it’s a probabilistic engine, sifting through language likelihoods to finish a sentence — like the predictive text you might see on your phone while composing a message. It is seeking the most likely conclusion to any given string of words.

“These are responsive systems,” he says. “They aren’t reasoning. They just hold words together. That’s why they have problems answering questions about recent events.”

The National Science Foundation (NSF) said on Wednesday that it is looking to open a National Artificial Intelligence Research Resource Operations Center (NAIRR-OC) to arm the nation’s researchers and educators with critical AI tools and resources. 

In a solicitation, NSF said that it is aiming to build on its National AI Research Resource (NAIRR) pilot by building sustained operational capabilities for NAIRR and broadening access to AI resources for the research community, which largely lacks the tools and resources “to investigate fundamental AI questions and train students.” 

NAIRR was launched in January 2024 and serves as a shared national infrastructure to support the AI research community and power responsible AI use.  

“The NAIRR Operating Center solicitation marks a key step in the transition from the NAIRR Pilot to building a sustainable and scalable NAIRR program,” said Katie Antypas, director of the NSF Office of Advanced Cyberinfrastructure.  

“We look forward to continued collaboration with private sector and agency partners, whose contributions have been critical in demonstrating the innovation and scientific impact that comes when critical AI resources are made accessible to research and education communities across the country,” continued Antypas. 

Specifically, NSF’s solicitation asks for proposals to create a community-based center to oversee “the development of the overarching framework, operations strategy and management structure needed to support the NAIRR’s scaling and growth.” 

That includes integrating advanced computing and data resources, a centralized web portal with access to tools, and collaborating with partner organizations, while conducting outreach and engagement with the national AI research community. 

NSF said that the NAIRR-OC will directly carry out priorities in the Trump administration’s AI Action Plan, released in July, which said that the federal government should “build the foundations for a lean and sustainable NAIRR operations capability that can connect an increasing number of researchers and educators across the country to critical AI resources.”   

Since NAIRR’s launch, it has connected 400 research teams with computing platforms, datasets, software, and models, and is partnering with 28 industry members and supported by 14 federal agencies, according to NSF. 

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