Neuromorphic devices and machine learning combine to make brain-like devices possible
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 30-Dec-2025 10:11 ET (30-Dec-2025 15:11 GMT/UTC)
Here, researchers from Beijing Institute of Nanoenergy and Nanosystems (Chinese Academy of Sciences) and Yonsei University present the latest progress in neuromorphic computing by integrating various neural networks, including SVM, ANN, CNN, RNN, and RC. Starting from the structure of synapses and neurons, they explore how these networks can be combined with neuromorphic devices to replicate more complex brain-like computations. They also propose future development directions for neuromorphic devices, focusing on advancements in their structures, materials, and applications across diverse fields such as vision, touch, hearing, smell, pain and other senses.
Researchers at the University of Hawaiʻi at Mānoa John A. Burns School of Medicine have uncovered a connection between a mother's weight before pregnancy and autism-like behaviors in her offspring. The study marks a significant advance in understanding how early life factors influence brain development.
Led by Professors Alika K. Maunakea and Monika Ward from JABSOM's Department of Anatomy, Biochemistry & Physiology and the Yanagimachi Institute for Biogenesis Research, the research shows that maternal obesity triggers metabolic shifts that cause lasting epigenetic changes in a mother’s eggs. These changes are passed on to the developing embryo and affect genes involved in brain development, including Homer1, a protein important for regulating synaptic signaling, learning, memory and response to neural activity.</p>
Researchers demonstrate that Synthetic Biological Intelligence (SBI) systems react faster, more effectively to stimuli than state-of-the-art RL (reinforcement learning) algorithms. To access these properties, Cortical Labs - which led the research - built the world’s first biological computer, the CL1. With the establishment of a new approach, Bioengineered Intelligence (BI), researchers will seek to establish that engineered biological systems can surpass natural physiological limits, unlocking capabilities beyond those previously demonstrated
An international team of researchers has demonstrated how artificial intelligence (AI) can now detect contaminated food in fields and factories before it reaches consumers, potentially saving four million deaths annually.
A study showed that when compared with students, ChatGPT 3.5 was less likely to correctly answer questions on therapeutics exams focused on clinical applications and cases.
Cornell University researchers developed machine-learning models that can sift through cell-free RNA and identify key biomarkers for myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS). The approach could lead to the development of diagnostic testing for a debilitating disease that has proved challenging to confirm in patients because its symptoms can be easily confused with those of other illnesses.