Routes represent an integral part of triggering emotions in drivers. Navigation systems allow users to choose a navigation strategy, such as the fastest or shortest route. However, they do not consider the driver's emotional well-being. We present HappyRouting, a novel navigation-based empathic car interface guiding drivers through real-world traffic while evoking positive emotions. We propose design considerations, derive a technical architecture, and implement a routing optimization framework. Our contribution is a machine learning-based generated emotion map layer, predicting emotions along routes based on static and dynamic contextual data. We evaluated HappyRouting in a real-world driving study (N=13), finding that happy routes increase subjectively perceived valence by 11% (p=.007). Although happy routes take 1.25 times longer on average, participants perceived the happy route as shorter, presenting an emotion-enhanced alternative to today's fastest routing mechanisms. We discuss how emotion-based routing can be integrated into navigation apps, promoting emotional well-being for mobility use.

Grimes' TikTok is a strange and beautiful place -- you truly never know what you're going to get from her. The avant-pop musician has made a name for herself, not only for making some of the most ethereal, groundbreaking contemporary music out there, but also for being a huge advocate for artificial intelligence. In fact, AI is how she and now-boyfriend, tech billionaire Elon Musk, began their romance. The two flirted over the AI thought experiment Roko's basilisk; Musk went to tweet "Rococo's Basilisk" only to see that Grimes had already beat him to it. The rest, famously, is a highly publicized (and scrutinized) relationship, a baby, and history.

Artificial Intelligence and Machine Learning is now considered to be one of the biggest innovations . AI and ML used to be a fanciful concept from science fiction, but now it's becoming a daily reality. The growth of less expensive and more powerful processing, The nearly limitless quantity of available data and affordable data storage has propelled the growth of Machine Learning. Now, before we get into the applications, Let's start with the basic intro to Machine Learning. Machine learning is a branch of AI focused on building applications that improve automatically through experience and by the use of data.

Google has been working hard to make Maps a useful tool for navigating the world and it's continuing to roll out new features. Today, the company is unveiling a set of updates that should make the app more helpful in more scenarios. For one thing, it's bringing its AR navigation tool Live View to some indoor locations like select malls, airports and transit stations. As a recap, Live View is an AR feature that let you see exactly where your destination is by pointing your camera at your surroundings and overlaying directions on the scene. To make that work indoors though, Google had to "develop an entirely new technology" that it's calling "global localization."

From CSR to ESG, most businesses today have good intentions to stand up to their environmental and social responsibilities. Nevertheless, in order for them to reduce its environmental impact, they need to first estimate the effect of their activities in quantitative means. Producing such estimates could be challenging, especially for large businesses involved in multiple chains of production and distribution. This can be resolved by the use of IOT ( Internet of Things) and smart sensors. IOT allows automation of accurate and reliable data collection, which could then be fed into data analytic algorithms that outputs analysis of the different sources externalities or pollutions. Businesses could gain insights from these analysis and take actions.

MACHINE-LEARNING SYSTEMS USE DATA TO UNDERSTAND PATTERNS and make predictions. When the system is predicting which photos are of cats, you may not care how certain it is about its results. But if it's predicting the fastest route to the hospital, the amount of uncertainty becomes critically important. "Imagine the system tells you'Route A takes 9 minutes' and'Route B takes 10 minutes.' Route A sounds better," says Tamara Broderick, an associate professor in the Department of Electrical Engineering and Computer Science. "But now it turns out that Route A takes 9 minutes plus-or-minus 5, and Route B takes 10 minutes plus-or-minus 1. If you need a life-saving procedure in 12 minutes, suddenly your decision making really changes."

Predictive Purchases: Let's say your user went on to the mobile app sometime back to conduct a few purchases. There you have the purchase history that you can look into at any given time. You should know what kind of items the user has been browsing for a while. It could be bow ties, shoes etc. once you have the list handy, you can predict what the customer visiting your shop regularly is going to buy. You can show them more such stuff, and even ensure they go through the funnel to complete the purchase.

Predictive Purchases: Let's say your user went on to the mobile app sometime back to conduct a few purchases. There you have the purchase history that you can look into at any given time. You should know what kind of items the user has been browsing for a while. It could be bow ties, shoes etc. once you have the list handy, you can predict what the customer visiting your shop regularly is going to buy. You can show them more such stuff, and even ensure they go through the funnel to complete the purchase.