Dongqi Han

Aug 29, 2024 | microsoft.com | Dongsheng Li |Dongqi Han |Yansen Wang |Alyssa Hughes

As AI research and technology development continue to advance, there is also a need to account for the energy and infrastructure resources required to manage large datasets and execute difficult computations. When we look to nature for models of efficiency, the human brain stands out, resourcefully handling complex tasks. Inspired by this, researchers at Microsoft are seeking to understand the brain’s efficient processes and replicate them in AI.

Jun 30, 2024 | mdpi.com | Xin Tian |Shijie Chen |Yuling Wang |Dongqi Han

1. IntroductionPET plays an invaluable role in the realm of medical imaging, serving as a nuclear imaging technology with profound significance in both clinical applications and research [1]. It provides essential information on the body’s metabolic processes, and it is essential for the diagnosis of cancer and the evaluation of ailments, including heart disease and neurological disorders [2,3,4,5].

Jun 19, 2024 | microsoft.com | Dongqi Han |Alyssa Hughes

In the intertwined worlds of psychology, cognitive neuroscience, and artificial intelligence, scientists continue to pursue the elusive goal of decoding and mimicking human and animal behavior. One of the most intriguing aspects of this research is the interplay between two types of behaviors: habitual and goal directed.

May 24, 2024 | nature.com | Kenji Doya |Dongsheng Li |Dongqi Han

AbstractBehaving efficiently and flexibly is crucial for biological and artificial embodied agents. Behavior is generally classified into two types: habitual (fast but inflexible), and goal-directed (flexible but slow). While these two types of behaviors are typically considered to be managed by two distinct systems in the brain, recent studies have revealed a more sophisticated interplay between them.