Close your eyes and imagine for a moment that you're in Tatooine. Yes, the room inside the vehicle is a bit cramped, but hey, you're in the Star Wars saga so you'll take what you get. You squint into the vast expanse as Luke asks you if you see anything. But before you can celebrate, Tusken Raiders attack and your crew are hopelessly overpowered. Remember, this is Luke before he knew what the "Force" was.

The season 2 finale of The Mandalorian was an emotional roller coaster for a lot of fans (including me), but there was one big reveal that'll most likely have fans debating until the hit show returns for another season in 2021 on Disney Plus. Though Lucasfilm, via Industrial Light & Magic, is known for its cutting-edge digital mastery, one Star Wars fan thought the shocking cameo of you-know-who could use a touch-up using deepfake software. Deepfakes are fake videos that convincingly show people appearing to be doing or saying things they never did. In the season 2 finale, Luke Skywalker (Mark Hamill) shows up to save the day with his lightsaber in hand, after getting Baby Yoda/Grogu's Force message. The digital re-creation of Hamill's 1983 film face is impressive.

A significant shortcoming of current state-of-the-art (SOTA) named-entity recognition (NER) systems is their lack of generalization to unseen domains, which poses a major problem since obtaining labeled data for NER in a new domain is expensive and time-consuming. We propose ZERO, a model that performs zero-shot and few-shot learning in NER to generalize to unseen domains by incorporating pre-existing knowledge in the form of semantic word embeddings. ZERO first obtains contextualized word representations of input sentences using the model LUKE, reduces their dimensionality, and compares them directly with the embeddings of the external knowledge, allowing ZERO to be trained to recognize unseen output entities. We find that ZERO performs well on unseen NER domains with an average macro F1 score of 0.23, outperforms LUKE in few-shot learning, and even achieves competitive scores on an in-domain comparison. The performance across source-target domain pairs is shown to be inversely correlated with the pairs' KL divergence.

Experiences with AI and machine learning at CVS Health and St. Luke's Health System in Boise, Idaho, are having practical benefits to the two organizations. CVS Health is learning how to scale AI applications using machine learning, especially through the house of machine learning operations (MLOps) tools, according to Nels Lindahl, director of Clinical Decision Systems, speaking in a virtual session at the recent Ai4 Conference held virtually recently. And St. Luke's Health Center put a COVID-19 prediction program, a supply chain purchase engine and a demand-based staffing application into initial production using AI and machine learning, said Dr. Justin Smith, senior director of advanced analytics at St. Luke's, also at a recent Ai4 virtual conference session. "We are at an MLOps tipping point, where ML has a growing production footprint, with adoption picking up pace and awareness and understanding at an all-time high," stated Lindahl. "ML tech can now deliver; people are seeing real use cases in the wild and having them grow; it's real."

Baylor St. Luke's Is First in Houston To Adopt Artificial Intelligence for Stroke Care As one of the leaders in stroke care in Houston and the surrounding areas, Baylor St. Luke's Medical Center continues on its promise to leverage the most advanced innovations to provide the best care to its patients. Baylor St. Luke's invested in artificial intelligence technology to service the stroke care team in diagnosing stroke and providing efficient and reliable treatment. Viz.ai technology allows for rapid detection and notification of suspected large vessel occlusion (LVO) strokes. Chethan P Venkatasubba Rao, Medical Director of the Neuroscience ICU at Baylor St. Luke's With Stroke, Timing Is Everything During a stroke, timing is the most important factor for minimizing brain damage. Knowing the signs of a stroke will allow for F.A.S.T. action in the event of an emergency.

MINNEAPOLIS--(BUSINESS WIRE)-- U.S. Bank (USBK) has hired technology leader Dr. Tanushree Luke to lead Artificial Intelligence (AI) efforts at the company. In this role, she will drive the continued development of the AI practice within the U.S. Bank Innovation group and AI strategies across the enterprise. This press release features multimedia. U.S. Bank has hired technology leader Dr. Tanushree Luke to lead Artificial Intelligence (AI) efforts at the company. Dr. Luke's career has spanned multiple industries and sectors.