In the field of dream research, the study of dream content typically relies on the analysis of verbal reports provided by dreamers upon awakening from their sleep. This task is classically performed through manual scoring provided by trained annotators, at a great time expense. While a consistent body of work suggests that natural language processing (NLP) tools can support the automatic analysis of dream reports, proposed methods lacked the ability to reason over a report's full context and required extensive data pre-processing. Furthermore, in most cases, these methods were not validated against standard manual scoring approaches. In this work, we address these limitations by adopting large language models (LLMs) to study and replicate the manual annotation of dream reports, using a mixture of off-the-shelf and bespoke approaches, with a focus on references to reports' emotions. Our results show that the off-the-shelf method achieves a low performance probably in light of inherent linguistic differences between reports collected in different (groups of) individuals. On the other hand, the proposed bespoke text classification method achieves a high performance, which is robust against potential biases. Overall, these observations indicate that our approach could find application in the analysis of large dream datasets and may favour reproducibility and comparability of results across studies.

Rep. August Pfluger joins'Fox & Friends First' and calls out Biden's handling of border crisis The feds have turned to cutting-edge cameras developed by a virtual reality wunderkind to help them monitor the southern border -- by creating an invisible border wall. The high-tech watch poles known as Autonomous Surveillance Towers are powered by solar energy and use artificial intelligence to detect movement along a two-mile radius, sending the information in real-time to agents patrolling the area. And they're now being installed at different points along the nearly 2,000 miles of the US-Mexico border. "The ASTs are in remote locations that are difficult to reach," Border Patrol agent Joel Freeland recently told The Post. "They operate 24-hours a day and are environmentally friendly because they rely entirely on solar power." The ASTs were developed by Palmer Luckey, the 28-year-old founder and designer of Oculus VR and Oculus Rift.

The Supreme Court's Artificial Intelligence Committee on Tuesday launched its Artificial Intelligence portal SUPACE(Supreme Court Portal for Assistance in Court's Efficiency). The event was attended by CJI Bobde, CJI designate Justice NV Ramana and Justice Nageswara Rao, who is also the Chairman of the Supreme Court's AI Committee, and High Court Judges. While launching the Court's Artificial Intelligence Portal, the CJI called the system a'perfect blend of human intelligence and machine learning' and'a hybrid system', which works together with human intelligence. He stated that the system being launched is unique as there is interaction between the human being and machine which creates remarkable results. During the event, CJI addressed the objections and criticisms that Artificial Intelligence faces, as for most people it means automated decision making.

If you read through the human history, especially the last 2,000 years, you will notice that famines, diseases and wars were the three most formidable challenges that we had to face (or as I call it -- the trifecta of human sufferings). Our response to the trifecta was mostly to seek safety and pray for our survival. History also tells us that when faced with external threats and no possible solutions in sight, we turned inwards and sought solace in numbers to overcome some serious challenges to our species' survival. Gradually, these cycles of sufferings led to emergence and prevalence of the unifying behavior of collaboration amongst humans. Tremendous efforts and resources, collaborated at extraordinary scale, were thrown at solving the trifecta of problems with some amount of success.

Speculations are rife that the EU might soon be bringing in a new set of rules and regulations aimed at artificial intelligence developers. FREMONT, CA: After rolling out comprehensive data privacy regulations, the EU is now considering norms to regulate the development of Artificial Intelligence (AI) solutions. The technology of artificial intelligence has been a revelation and is one of the most-used among all the advanced technologies. Although beneficial, there have been apprehensions regarding the potential misuse of the technology, owing to its over-reaching capabilities. These apprehensions might have been the factors driving the EU towards getting a new AI policy on the cards.

Today, there's a common notion that artificial intelligence (AI) is going to put us all out of jobs. But recently, I read an article (subscription required) where AI expert Robert Atkinson remarked that worries around AI and job loss are overblown. He said, "It's time to take a deep breath and stop panicking about artificial intelligence and what it portends for jobs. No, AI won't destroy more jobs than it creates. No, the pace of technological change is not accelerating. And no, we certainly don't need to tax AI to slow it down."

If you were born in the 80s or 90s, then there's a good chance the words'machine learning' conjure images of Arnold Schwarzenegger as The Terminator. It sounds like a far future concept that may be synonymous with AI and'the rise of the machines'. But as it happens, the rise has actually already begun. Machine learning is no science fiction concept but rather a concrete tool that you likely encounter on a daily basis already – even on the Android device that's currently sitting in your pocket. In this post, I'll attempt to demystify machine learning a little and demonstrate a few ways in which it is already a big part of your life.

Passengers embark on the U.S. side of the last hand-pulled ferry at Los Ebanos, Texas on the Mexico-U.S. border in 2008. LOS EBANOS, Texas -- All along the winding Rio Grande, the people who live in this bustling, fertile region where the U.S. border meets the Gulf of Mexico never quite understood how Donald Trump's great wall could ever be much more than campaign rhetoric. Erecting a concrete barrier across the entire 1,954-mile frontier with Mexico, they know, collides head-on with multiple realities: the geology of the river valley, fierce local resistance and the immense cost. An electronically fortified "virtual wall" with surveillance technology that includes night-and-day video cameras, tethered observation balloons and high-flying drones makes a lot more sense to people here. If a 30- to 40-foot concrete wall is a panacea for illegal immigration, as Trump insisted during the campaign, the locals are not convinced.

Think about the future of automation and AI. The future of automation is here and now. Only, it isn't an edge of the seat sci-fi thriller that you might imagine. Automation is no longer an option in the 21st century enterprise. Across industries, it is already driving efficiency, productivity, agility, adaptability and optimisation.

The world is not moving towards a dystopian future just as yet, but one can't deny the effect innovations in the robotics field will have on human life, especially when it comes to a waning workforce as a result of increased use of automation technologies. Experts have already started sounding the warning bells. As per a report published by advisory analyst firm HfS Research in July, the true impact of the emergence of intelligent automation will be felt on the global industry of 15 million IT services and BPO workers, which will see about 1.4 million job losses--a net decrease of 9%--by 2021. In India, the services industry workforce is expected to shrink by 4.8 lakh by 2021, a decline of 14%--HfS Research estimates that the IT services and BPO industry employs about 3.5 million people in the country. Last year, technology research firm Gartner predicted that one in three jobs will be converted to software, robots and smart machines by 2025.