The University of Portsmouth, as part of Space South Central (SSC), one of the UK’s largest regional space clusters, is leading a new international partnership with Saudi space-tech company SARsatX. Together, they are developing the concept for an Earth observation satellite mission aimed at supporting a range of sectors, including climate science and environmental resilience.

As members of the public increasingly turn to AI chatbots to understand their world, even subtle latent biases in the underlying models could affect public understanding of the present—and past. Daniel Karell and colleagues explored the effects of both unintentional and intentional political biases in LLMs by asking 1,912 research participants to read GPT-4o and Wikipedia summaries of two 20th century historical events: the 1919 Seattle General Strike and the 1968 Third World Liberation Front student protests calling for greater ethnic minority representation in academia, which led the establishment of Ethnic Studies departments. 

With the speed at which technology advances, there is little room for suboptimal performance and out-of-date tech. Precise positioning is a field where advancement is needed, as many conventional applications feature tools that are much larger than the objects being worked upon, making high precision a difficult task. Additionally, those that are highly precise have a limited range of motion. Researchers did not want to compromise, and instead set out to create a highly precise machine with a wide range of motion, and were able to do so by developing a palm-sized, precise positioning robot making use of piezoelectric actuators.

Results were published in Advanced Intelligence Systems in January 2026.

A research team led by Dr. Jeong Min Park of the Nano Materials Research Division at the Korea Institute of Materials Science (KIMS), in collaboration with Dr. Jaemin Wang and Prof. Dierk Raabe of the Max Planck Institute in Germany, has developed an artificial intelligence (AI)-based model capable of assessing the likelihood and characteristics of internal defects during process design. This research achievement is expected to significantly enhance the reliability of metal additive manufacturing parts and greatly expand their applicability for mass production in industrial settings.