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Jesus, Cleopatra 'selfies' generated by AI go viral: 'Hilarious'

#artificialintelligence

Let there be (ring) light. A British film editor is going viral for using artificial intelligence to imagine famous historical figures such as Jesus, Cleopatra, Queen Elizabeth I and Henry VIII taking selfies. "The results are hilarious, and everyone I've shared my work with can't believe how real the pictures really look," Duncan Thomsen, 53, told SWNS. He said he uses the AI software Midjourney through the Discord app, which responds to user-set prompts and commands to generate pictures by referencing billions of images online. Thomsen has recreated scenes from the Battle of Waterloo, the court of Cleopatra, and the Last Supper.


GitHub - oracle-samples/automlx: This repository contains demo notebooks (sample code) for the AutoMLx (automated machine learning and explainability) package from Oracle Labs.

#artificialintelligence

This repository contains demo notebooks (sample code) for the AutoMLx (automated machine learning and explainability) package from Oracle Labs. The notebooks are intended to show how to initialize, train and explain an AutoML model in a few lines of code. The notebooks also cover many of the advanced features available in the AutoMLx package. Pre-executed copies of each of the demo notebooks are available as html files, which can be viewed without installing anything. The demo notebooks in this repository serve as supplementary documentation for the AutoMLx package.



How Generative AI Will Change Sales

#artificialintelligence

Last month, Microsoft fired a powerful salvo by launching Viva Sales, an application with embedded generative AI technology designed to help salespeople and sales managers draft tailored customer emails, get insights about customers and prospects, and generate recommendations and reminders. A few weeks later, Salesforce (the company) followed by launching Einstein GPT. Sales, with its unstructured, highly variable, people-driven approach, has been a laggard behind functions such as finance, logistics, and marketing when it comes to utilizing digital technologies. But now, sales is primed to quickly become a leading adopter of generative AI -- the form of artificial intelligence used by OpenAI (the company behind ChatGPT) and its competitors. AI-powered systems are on the way to becoming every salesperson's (and every sales manager's) indispensable digital assistant.


Study: ChatGPT has potential to help cirrhosis, liver cancer patients

#artificialintelligence

A new study by Cedars-Sinai investigators describes how ChatGPT, an artificial intelligence (AI) chatbot, may help improve health outcomes for patients with cirrhosis and liver cancer by providing easy-to-understand information about basic knowledge, lifestyle and treatments for these conditions. The findings, published in the peer-reviewed journal Clinical and Molecular Hepatology, highlights the AI system's potential to play a role in clinical practice. "Patients with cirrhosis and/or liver cancer and their caregivers often have unmet needs and insufficient knowledge about managing and preventing complications of their disease," said Brennan Spiegel, MD, MSHS, director of Health Services Research at Cedars-Sinai and co-corresponding author of the study. "We found ChatGPT--while it has limitations--can help empower patients and improve health literacy for different populations." Patients diagnosed with liver cancer and cirrhosis, an end-stage liver disease that is also a major risk factor for the most common form of liver cancer, often require extensive treatment that can be complex and challenging to manage.


Click away the bias: New system to make AI training easier and more accurate

#artificialintelligence

In the past few years, "AI" has become a major buzzword in technology. The prospect of a computer being able to do tasks which only a human could perform is a captivating thought. AIs can be created using multiple different methods, but one of the most popular ones right now involves the use of deep neural networks (DNNs). These structures try to mimic the neural connections and function of the brain and are generally trained on a dataset before they are deployed in the real world. By training them on a dataset beforehand, DNNs can be'taught' to identify features in an image.


Italy bans OpenAI's ChatGPT over privacy fears

#artificialintelligence

The Italian Data Protection Authority said Friday that ChatGPT was violating the European Union's strict General Data Protection Regulation (GDPR) in multiple ways, ranging from the fact that it sometimes spews out incorrect information about people, to OpenAI's failure to tell people what it's doing with their personal data. Until it can satisfy the privacy regulator that it has brought its practices into compliance with the GDPR, OpenAI now has to stop processing the personal data of people in Italy, which means the authority wants it to stop serving users there. It has 20 days to comply with the ban, or face fines that could theoretically go up to €20 million ($22 million) or 4% of global revenue, whichever is higher. OpenAI's revenues are not publicly disclosed. According to OpenAI documents seen by Fortune, the company was projected to have less than $30 million in revenues in 2022 but was forecasting revenues would grow rapidly to exceed $1 billion by 2024.


A knowledge-inherited learning for intelligent metasurface design and assembly

#artificialintelligence

The interaction of machine learning and optics/photonics is transforming the way we design new photonic structures, unearth latent physical laws, and develop intelligent photonic devices. Despite certain achievements, a major impediment persistently exists; datasets and networks are only disposable. Thus, for each new state or task, all datasets and networks have to be discarded, and it is imperative to reconstruct new datasets and networks, leading to an enormous waste of resources. In machine learning-based metamaterial designs, much effort has been inaugurated to enlarge the training dataset or construct specific networks. Either way, each metamaterial is physically separated, and the data utilization efficiency is very low.


Ozzy Osbourne to headline first show this fall since announcing retirement

FOX News

Fox News medical contributor Dr. Marc Siegel discusses the procedure to reportedly remove and realign pins in Osbourne's neck and back. Ozzy Osbourne is among headliners announced this week for the first Power Trip Festival in Indio, California, this fall. The hard rock festival, which will also be headlined by legends Guns N' Roses, Metallica and AC/DC, marks the "Black Sabbath" frontman's return to performing after canceling all his 2023 tour dates and announcing he would be retiring from touring due to ongoing health issues. "I am honestly humbled by the way you've all patiently held onto your tickets for all this time, but in all good conscience, I have now come to the realization that I'm not physically capable of doing my upcoming European/UK tour dates, as I know I couldn't deal with the travel required," he posted on his social media accounts in February. He said his "singing voice is fine," but he remains physically weak after three operations, stem cell treatments, physical therapy and hybrid assistive limb treatment, which uses a robotic exoskeleton to help improve movement.


Exploring The Possibilities of ML Explainability with Talking Language AI #5

#artificialintelligence

Model interpretability is an important consideration in the development of any machine learning algorithm. As technology advances, so too does our ability to use artificial intelligence (AI) to process natural language. With the increasing use of large language models, the need for explainability and understanding of how the model works has become paramount. The Talking Language AI #5 project highlights the need for language model UI that allows us to understand and interact with AI models. By utilizing graphical representations of the model's inner workings, it becomes possible to gain insight into the decisions the model is making. This enables us to better understand the model's rationale and make informed decisions about the performance of the model.