Opioid and substance misuse is rampant in the United States today, with the phenomenon known as the "opioid crisis". The relationship between substance use and mental health has been extensively studied, with one possible relationship being: substance misuse causes poor mental health. However, the lack of evidence on the relationship has resulted in opioids being largely inaccessible through legal means. This study analyzes the substance use posts on social media with opioids being sold through crypto market listings. We use the Drug Abuse Ontology, state-of-the-art deep learning, and knowledge-aware BERT-based models to generate sentiment and emotion for the social media posts to understand users' perceptions on social media by investigating questions such as: which synthetic opioids people are optimistic, neutral, or negative about? or what kind of drugs induced fear and sorrow? or what kind of drugs people love or are thankful about? or which drugs people think negatively about? or which opioids cause little to no sentimental reaction. We discuss how we crawled crypto market data and its use in extracting posts for fentanyl, fentanyl analogs, and other novel synthetic opioids. We also perform topic analysis associated with the generated sentiments and emotions to understand which topics correlate with people's responses to various drugs. Additionally, we analyze time-aware neural models built on these features while considering historical sentiment and emotional activity of posts related to a drug. The most effective model performs well (statistically significant) with (macroF1=82.12, recall =83.58) to identify substance use disorder.

As industries across the world focus on innovation in all facets of their operations today, we inhabit an era of two progressive technologies leading a revolution. These, undoubtedly, are AI & Blockchain. The onset of artificial intelligence, which mimics human intelligence to complete complex tasks, has now seeped into how we function in our daily lives. With the ever so increased rush towards digitization – more and more applications are relying on the use of AI. In 2009, when Bitcoins were launched, Blockchain moved from being a theoretical concept to a real-world use case.

The crypto market has grown in recent years while getting attention from several new investors and the next-gen Millennials. COVID-19 also increased the popularity of the crypto market worldwide. On the other hand, another growing trend is Artificial Intelligence or AI. It has gained traction in recent years, with several experts hoping that the trend continues to grow in the coming years with global digitalization in progress. Now, as crypto is already based on a technology called Blockchain, several tech-savvy investors and crypto market enthusiasts are looking for the role of artificial intelligence in the cryptocurrency market.

Inflation is causing stress and worry around the globe. Residents of Turkey, Argentina, Venezuela and dozens of other countries have seen prices jump by hundreds of percent in recent years. And this is becoming a larger problem in developed countries as well. According to experts at Goldman Sachs, U.K. inflation could hit as high as 22% in the coming period. The European Union also faces sharp price rises.

If you wonder if there is a relationship between Artificial Intelligence and cryptocurrency, then you must know that the crypto market uses Artificial Intelligence in various ways. Due to the use of AI, the crypto market can operate 24X7, and for that, the traders or investors can keep a watch on the price all the time. It creates a large amount of data for AI to examine in order to estimate future prices using back-data discoveries such as analyzing the market price. As a result, crypto AI can assist in more accurate price predictions. Because it eliminates the danger of human error while calculating, they are also faster predictions.

Most people are unable to tell they are watching a "deepfake" video even when they are informed that the content they are watching has been digitally altered, research suggests. The term "deepfake" refers to a video where artificial intelligence and deep learning – an algorithmic learning method used to train computers – has been used to make a person appear to say something they have not. Notable examples of it include a manipulated video of Richard Nixon's Apollo 11 presidential address and Barack Obama insulting Donald Trump – with some researchers suggesting illicit use of the technology could make it the most dangerous form of crime in the future. In the first experiment, conducted by researchers from the University of Oxford, Brown University, and the Royal Society, one group of participants watched five unaltered videos, while another watched four unaltered videos and one deepfake – with viewers asked to detect which one is false. The researchers used videos of Tom Cruise created by VFX artist Chris Ume, which have seen the American actor performing magic tricks and telling jokes about Mikhail Gorbachev in videos uploaded to TikTok.

As of today, many of our everyday activities are conducted virtually, for instance, attending class, working from home, even buying a car or house can be completed virtually. As we are shifting towards a world where we can do many significant things virtually, It has completely changed the way we think and conduct our everyday lives. Virtual currency has also made its mark in our lives. Debit/Credit cards being the first virtual currency has only paved the path for the future of virtual currency. That's where Cryptocurrency comes in.

In the world of cryptocurrency, everyone is looking to make money. For me, I wanted to see if money could be made through trading.

Researchers have trained a drone to search for asteroids that crash to Earth. The drones autonomously fly in a grid pattern, taking photos of the ground over a large area, and use artificial intelligence to search through the pictures to identify potential meteorites. Every year approximately 500 meteorites fall to the planet's surface, but less than two per cent of these are ever recovered – sometimes because they fall in inaccessible locations, such as the ocean, but in other instances simply because they are not found in time. The drone, developed by the University of California, Davis, has been tested around Walker Lake in Vegada, where a meteorite fell in 2019. "Images can be analyzed using a machine-learning classifier to identify meteorites in the field among many other features," said Robert Citron, a postdoctoral researcher at the university.

Scientists have developed a device modelled on the human brain that can learn by association in the same way as Pavlov's dog. In the famous experiment, Russian physiologist Ivan Pavlov conditioned a dog to associate a bell with food. In order to replicate this way of learning, researchers from Northwestern University in the US and the University of Hong Kong developed so-called "synaptic transistors" capable of simultaneously processing and storing information in the same way as a brain. Instead of a bell and food, the researchers conditioned the circuit to associate light with pressure by pulsing an LED lightbulb and then immediately applying pressure with a finger press. The organic electrochemical material allowed the device to build memories and after five training cycles, the circuit associated light with pressure in such a way that light alone was able to trigger a signal for the pressure.