Tailo Ai

Fairfield Dolan MBA Program Launches Artificial Intelligence (AI) Concentration

Fairfield University’s Charles F. Dolan School of Business has launched an AI concentration in its Master of Business Administration program (MBA AI).

Artificial intelligence coupled to pharmacometrics modelling to tailor malaria and tuberculosis treatment in Africa

Africa’s vast genetic diversity poses challenges for optimising drug treatments in the continent, which is exacerbated by the fact that drug discovery and development efforts have historically been performed outside Africa. This has led to suboptimal therapeutic outcomes in African populations and overall scarcity of relevant pharmacogenetic data, including characteristic genotypes as well as drugs prescribed in the continent to treat infectious diseases. Here, we propose a general approach to identify drug-gene pairs with potential pharmacogenetic interest. Our pipeline couples machine learning and artificial intelligence with physiologically-based pharmacokinetic (PBPK) and non-linear mixed effects (NLME) modelling to hypothesize which pharmacogenes could be of potential clinical interest, and which dose adjustments could be made to provide better treatment outcomes for African populations. Drug-gene pairs are first ranked with the latest knowledge embedding techniques, based on public structural and bioactivity data for drugs and genes, followed by a large language model-based refinement. Selected genes are then evaluated for their sensitivity in PBPK analysis, and relevant variants subsequently inspected with NLME for dose optimization. The analysis is focused on genes with potential clinical relevance in Africa. We delve deeper into malaria and tuberculosis therapies, many of which remain uncharacterised from a pharmacogenetic perspective. Authors analyzed malaria and tuberculosis drugs to create a pharmacometric model. They used an AI pipeline that prioritized pharmacogenetic drug-gene pairs with an emphasis on high variant frequency genes in an African population.

Advanced Agrilytics to Launch AI Tool for Agronomic Decisions - AgWeb

Leveraging artificial intelligence and 15 years of data, TerraSIGNAL will extend access to agronomic expertise, using sub-acre data points to provide automated recommendations.

How AI is reshaping the economics of tail spend - Kearney

Inside China, artificial intelligence is a snake eating its own tail

Opinion: AI researchers refer to this as “model collapse,” a phenomenon in which models trained on their own synthetic outputs degrade over successive generations.

Improving next-generation aircraft with supercomputing and AI

Researchers are using Argonne’s new Aurora supercomputer to run large-scale simulations and machine learning models that improve understanding of turbulent airflow and support the design of more efficient next-generation aircraft.