University of Florida scientists want to assess livestock mobility faster and more accurately, ultimately helping farm animal health and production. To do so, they'll use artificial intelligence (AI) to analyze high-definition video of the animals as they move. Samantha Brooks, a UF/IFAS geneticist and associate professor of equine physiology – along with other UF researchers -- have been awarded a $49,713 grant from the Agricultural Genome to Phenome Initiative (AG2PI) for this research. The team will combine machine learning with gait analyses to speed their assessment of livestock mobility. Brooks cites an example of how this technology can help: In horses, one veterinarian can do a basic lameness exam in about 15 minutes.

Explainable artificial intelligence (XAI) aims to make learning machines less opaque, and offers researchers and practitioners various tools to reveal the decision-making strategies of neural networks. In this work, we investigate how XAI methods can be used for exploring and visualizing the diversity of feature representations learned by Bayesian neural networks (BNNs). Our goal is to provide a global understanding of BNNs by making their decision-making strategies a) visible and tangible through feature visualizations and b) quantitatively measurable with a distance measure learned by contrastive learning. Our work provides new insights into the posterior distribution in terms of human-understandable feature information with regard to the underlying decision-making strategies. Our main findings are the following: 1) global XAI methods can be applied to explain the diversity of decision-making strategies of BNN instances, 2) Monte Carlo dropout exhibits increased diversity in feature representations compared to the multimodal posterior approximation of MultiSWAG, 3) the diversity of learned feature representations highly correlates with the uncertainty estimates, and 4) the inter-mode diversity of the multimodal posterior decreases as the network width increases, while the intra-mode diversity increases. Our findings are consistent with the recent deep neural networks theory, providing additional intuitions about what the theory implies in terms of humanly understandable concepts.

An animal scientist with Wageningen University & Research in the Netherlands has created an artificial-intelligence-based application that can gauge the emotional state of farm animals based on photographs taken with a smartphone. In his paper uploaded to the bioRxiv preprint server, Suresh Neethirajan describes his app and how well it worked when tested. Prior research and anecdotal evidence has shown that farm animals are more productive when they are not living under stressful conditions. This has led to changes in farming practices, such as shielding cows' eyes from the spike that is used to kill them prior to slaughter to prevent stress hormones from entering the meat. More recent research has suggested that it may not be enough to shield farm animals from stressful situations--adapting their environment to promote peacefulness or even playfulness can produce desired results, as well.

An AI-powered computer system has been created which identifies the emotional state of farm animals and if they are happy or not. It is hoped that better understanding how animals are feeling can help improve their living conditions and quality of life. Thousands of images of cows and pigs from six farms around the world were used to train the network, called WUR Wolf, which was accurate 85 per cent of the time. An AI-powered computer system has been created which identifies the emotional state of farm animals and if they are happy or not. Pictured one of the images the system was trialled on which reveals a pig which was classified as'alert and neutral' Deep learning algorithms were used to identify 13 facial actions which included difference in an animal's ears, eyes and behaviour.,

OAKFIELD, NEW YORK – Cows that can withstand hotter temperatures. Cows born without pesky horns. Pigs that never reach puberty. A company wants to alter farm animals by adding and subtracting genetic traits in a lab. It sounds like science fiction, but Recombinetics sees opportunity for its technology in the livestock industry.

On the face of it, the connection between the internet of things (IoT) and animals is not an obvious one. However, a number of trials and larger-scale implementations of IoT use with household pets and on farms are showing that connecting Fido and Daisy to sensors could provide real benefits. This should not be surprising: animals are big business, both in terms of personal ownership and commercial farming. Mintel, a market research company, expects UK pet insurance premiums to grow from £976m in 2015 to £1.6bn by 2021. Anything that makes it easier and more efficient to care for and farm animals is therefore likely to be of interest.

An autumn classic matching the unbeaten Tigers, with star tailback Dick Kazmaier--a gifted passer, runner, and punter who would capture a record number of votes to win the Heisman Trophy--against rival Dartmouth. Princeton prevailed over Big Green in the penalty-plagued game, but not without cost: Nearly a dozen players were injured, and Kazmaier himself sustained a broken nose and a concussion (yet still played a "token part"). It was a "rough game," The New York Times described, somewhat mildly, "that led to some recrimination from both camps." Each said the other played dirty. The game not only made the sports pages, it made the Journal of Abnormal and Social Psychology.

An autumn classic matching the unbeaten Tigers, with star tailback Dick Kazmaier--a gifted passer, runner, and punter who would capture a record number of votes to win the Heisman Trophy--against rival Dartmouth. Princeton prevailed over Big Green in the penalty-plagued game, but not without cost: Nearly a dozen players were injured, and Kazmaier himself sustained a broken nose and a concussion (yet still played a "token part"). It was a "rough game," The New York Times described, somewhat mildly, "that led to some recrimination from both camps." Each said the other played dirty. The game not only made the sports pages, it made the Journal of Abnormal and Social Psychology.