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What if an All-Knowing Algorithm Ran Traffic and Transit?


A journalist who reports on cities and autonomous vehicles responds to Linda Nagata's "Ride." I like to think of myself as deeply skeptical of the many internet algorithms telling me what I want and need. I turn off targeted advertising wherever I can. I use AdBlock to hide what's left. Most of my YouTube recommendations are for concerts or sports highlights, but I know I'm just a few clicks away from a wild-eyed influencer telling me to gargle turpentine for a sore throat. But I make an exception for the sweet, all-knowing embrace of the Spotify algorithm, to whom I surrender my ears several times a day.

Would You Let a Self-Driving Ride-Share Car Decide Where You're Going?


This story is part of Future Tense Fiction, a monthly series of short stories from Future Tense and Arizona State University's Center for Science and the Imagination about how technology and science will change our lives. A handsome boy, 17 and soft-spoken, told Jasmine about an Easter egg. "Try it," he urged, sincerity in his voice and in his eyes as he gazed at her across the tall front desk. She smiled all day at the hotel's guests, chatting with them when time permitted, listening to their stories. Her role came easily: bright-eyed island girl, young and pretty, a white flower tucked behind her ear. "Ah, your parents are here," she said as the couple emerged from the elevator alcove into the expansive lobby, its glittering perfection empty now of other guests in the lull of early afternoon. The boy waved at them, then turned again to Jasmine. "Give it a try," he exhorted her in a conspiratorial whisper. She didn't want to disappoint those eyes. So she played along, teasing, "I might." It was just a little game, after all. "And if it works for you, then tell someone else, OK? Keep it going." "And how will I know if it works?" He answered with a blissful smile. His parents joined him at the desk. Jasmine wished them all a safe trip home. Her shift ended at 4. Still wearing her uniform--a blue, body-hugging aloha-print dress--she left alone through the employee entrance, sighing at the shock of transition from air-conditioned comfort to the withering heat and humidity of a late-summer afternoon. Out of sight but audible, surf rumbled against the artificial reef. Closer, mynah birds chattered amid the heavy bloom of a rainbow shower tree. After a few minutes, an electric cart rolled up, nearly full with resort employees on their way home.

Why Java is the Most Preferred for Artificial Intelligence -


AI has brought digital transformation into business operations across various industries. It has become a significant part of our lifestyle. We can offer many use cases where Artificial Intelligence simplifies the process workflow, from autopilots for self-driving cars to using robots to handle warehouse jobs, implementation of chatbots in the customer care portals and more. The Artificial Intelligence technology implications for the purpose of business processes in different sectors are enormous. That is why the purpose and need for hiring skilled java developers to build AI-based apps is skyrocketing in recent years.

A Gentle Introduction to Data Augmentation


The quantity and diversity of data are important factors in the effectiveness of most machine learning models. The amount and diversity of data supplied during training heavily influence the prediction accuracy of these models. Hidden neurons are common in deep learning models that have been trained to perform well on complex tasks. The number of trainable parameters grows in unison with the number of hidden neurons. The amount of data needed is proportional to the number of learnable parameters in the model.

Cellphone and tech clues that your partner is cheating on you

FOX News

An easy way to keep two romantic lives separate is to buy two separate phones. That way, the cheater doesn't get confused and text the wrong person by mistake. A second phone is also a liability, even if expressed as a "work" or "emergency" phone. Another technique is to purchase a separate SIM card. Some phones allow you to have two SIM cards but that can be a hassle. A much easier way is to get a Google Voice number that rings on the current phone. In this photo illustration, Apple's iPhone 12 seen placed on a MacBook Pro.

Building artificial intelligence: staffing is the most challenging part


Every company worth its weight is set on achieving practical and scalable artificial intelligence and machine learning. However, it's all much easier said than done -- to which AI leaders within some of the most information-intensive enterprises can attest. For more perspective on the challenges of building an AI-driven organization, we caught up with Jing Huang, senior director of engineering and machine learning at Momentive (formerly SurveyMonkey). Q: AI and machine learning initiatives have been underway for several years now. What lessons have enterprises been learning in terms of most productive adoption and deployment?

Samsung to hire over 1,000 engineers from top colleges


These young engineers will work on various domains like artificial intelligence, machine learning, IoT, deep learning, networks, image processing, …

Global Temperature Analysis


The problem we will tackle is predicting the average global land and ocean temperature using over 200 years of past weather data. We are going to act as if we don't have access to any weather forecasts. What we do have access to is a century's worth of historical global temperatures averages including; global maximum temperatures, global minimum temperatures, and global land and ocean temperatures. Before you begin utilising profound learning models to tackle the temperature-forecast issue, we should attempt a straightforward, common-sense approach. It will fill in as a second look for good measure, and it will set up a pattern that you'll need to beat to show the handiness of further developed AI models.