ABQ Times

Dave Ackley, a professor emeritus at the University of New Mexico, played a significant role in research that contributed to the awarding of the 2024 Nobel Prize in Physics. His former dissertation advisor, Geoffrey Hinton, along with John Hopfield, received the prize for their pioneering work on brain-like algorithms that have significantly advanced artificial intelligence.

Hopfield's model of neural networks, known as the Hopfield Network, laid the groundwork for further developments in AI. In collaboration with Terry Sejnowski, Hinton used this model to create a new neural network called the Boltzmann Machine during his time at Carnegie Mellon University. As Hinton’s first Ph.D. student, Ackley was instrumental in implementing this machine.

Ackley recalls working closely with Hinton on the Boltzmann Machine: “To this day, I recall sitting in Geoff's office soon after I'd gotten the code working... The numbers were falling! The errors were decreasing! The machine was learning!” This breakthrough offered a novel approach to using simple components to solve complex tasks and influenced current AI systems like ChatGPT.

The Boltzmann Machine is named after physicist Ludwig Boltzmann and incorporates statistical concepts from physics. Despite its indirect implementation in modern generative AI, it is acknowledged as foundational work paving the way for such technologies.

Ackley humorously noted about computer science’s historical context: “Computer science didn’t exist when Nobel was inventing dynamite and feeling guilty about it.” He expressed surprise and excitement upon hearing about Hinton's recognition: “I got up around 8 and toddled in to look at my email... ‘is this spam?’”

After completing his Ph.D., Ackley worked at Bell Communications Research before moving into academia at UNM. There he pursued interests in cybersecurity and artificial life inspired by natural systems. Since retiring in 2018, he has focused on developing new computer architectures through his Living Computation Foundation.

Reflecting on his contributions to AI research decades ago and its impact today brought him unexpected joy: “Even though I didn’t have the big ideas –– I just did the implementation and experiments... it was still pretty exciting.”