Advances in bioengineering and biomedicine demand a deep understanding of the dynamic behavior of biological systems, ranging from protein pathways to complex cellular processes. Biological networks like gene regulatory networks and protein pathways are key drivers of embryogenesis and physiological processes. Comprehending their diverse behaviors is essential for tackling diseases, including cancer, as well as for engineering novel biological constructs. Despite the availability of extensive mathematical models represented in Systems Biology Markup Language (SBML), researchers face significant challenges in exploring the full spectrum of behaviors and optimizing interventions to efficiently shape those behaviors. Existing tools designed for simulation of biological network models are not tailored to facilitate interventions on network dynamics nor to facilitate automated discovery. Leveraging recent developments in machine learning (ML), this paper introduces SBMLtoODEjax, a lightweight library designed to seamlessly integrate SBML models with ML-supported pipelines, powered by JAX. SBMLtoODEjax facilitates the reuse and customization of SBML-based models, harnessing JAX's capabilities for efficient parallel simulations and optimization, with the aim to accelerate research in biological network analysis.

Twitter CEO Elon Musk provides insight on the consequences of developing artificial intelligence and the potential impact on elections on'Tucker Carlson Tonight.' Academic leaders from around the world penned an open letter calling on artificial intelligence developers to learn more about consciousness as artificial intelligence (AI) systems advance rapidly, giving it a prominent place in our moral landscape, raising ethnical, legal and political concerns. The Association for Mathematical Consciousness Science (AMCS), "a large community of over 150 international researchers who are spearheading mathematical and computational approaches to consciousness," published a letter Wednesday as "a wakeup call for the tech sector, the scientific community and society in general to take seriously the need to accelerate research in the field of consciousness science." The Association for Mathematical Consciousness Science published an open letter calling on "the tech sector, the scientific community and society in general to take seriously the need to accelerate research in the field of consciousness science." Its writers referenced the recent letter written by leaders in tech that called for a pause in AI experiments, noting "we are living through an exciting and uncertain time in the development of artificial intelligence (AI) and other brain-related technologies" and warned that AI is "accelerating at a pace that far exceeds our progress in understanding their capabilities and their'alignment' with human values." Signatories of the letter argue that language models like OpenAI's ChatGPT and Google's Bard are based on the neural networks of animal brains, but in the near future will be constructed to mimic "aspects of higher-level brain architecture and functioning."

UNDERSTANDING WHEN AND why a cell dies is fundamental to the study of human development, disease and aging. For neurodegenerative diseases such as Lou Gehrig's disease, Alzheimer's and Parkinson's, identifying dead and dying neurons is critical to developing and testing new treatments. But identifying dead cells can be tricky and has been a constant problem throughout my career as a neuroscientist. Until now, scientists have had to manually mark which cells look alive and which look dead under the microscope. Dead cells have a characteristic balled-up appearance that is relatively easy to recognize once you know what to look for.

The health of people and communities around the world has been improving over time. For example, the steep decline in child and maternal mortality is a key indicator of positive momentum. However, progress has not been equal across the globe, and there is a great need to focus on societal issues such as reducing health inequity and improving access to care for underserved populations. While researchers work to unlock life-saving discoveries and develop new approaches to pressing health issues, advancements in technology can help accelerate and scale new solutions. That is why we are launching AI for Health, a new $40 million, five-year program to empower researchers and organizations with AI to improve the health of people and communities around the world.