AI Safety Institute launched as Korea’s AI Research Hub
Business Announcement
Updates every hour. Last Updated: 6-May-2025 14:09 ET (6-May-2025 18:09 GMT/UTC)
“AI Safety Consortium” established to foster collaborative research among industry, aemia, and research institutes, with the AISI serving as the central hub. And active paticipation in the “International Network of AI Safety Institutes” (starting Nov 21), taking a leading role in advancing global collaboration.
By providing flexibility services to renewable energy systems, consumers can both help in balancing power grids and receive financial benefits. Hosna Khajeh’s doctoral dissertation from the University of Vaasa, Finland, introduces new methods that enable the efficient utilisation of energy users’ flexibility resources in distribution and transmission networks.
The melting of Greenland is accelerating, with an estimated loss of between 964 and 1735 gigatonnes of ice per year by 2100 in a scenario of high greenhouse gas emissions (SSP585), according to three regional climate models. This melting will lead to a rise in sea levels of up to one metre, threatening millions of people in coastal areas. New research conducted by the University of Liège and supported in particular by its NIC5 supercomputer will contribute to future IPCC assessments.
Large language models, a type of AI that analyses text, can predict the results of proposed neuroscience studies more accurately than human experts, finds a new study led by UCL researchers.
The findings, published in Nature Human Behaviour, demonstrate that large language models (LLMs) trained on vast datasets of text can distil patterns from scientific literature, enabling them to forecast scientific outcomes with superhuman accuracy.
The researchers say this highlights their potential as powerful tools for accelerating research, going far beyond just knowledge retrieval.
Scientists are revolutionizing microproteomics by combining droplet-based microfluidics with mass spectrometry. This approach enhances proteomic profiling in small cell populations, especially single cells, by minimizing sample loss and reagent use, accelerating reactions, and increasing throughput, enabling highly sensitive single-cell proteomic analysis with promising future applications.
The team proposed a new index structure called HATree.