On the final day of my visit to Japan, I'm alone and floating in some skyscraper's rooftop hot springs, praying no one joins me. For the last few months, I've been using ChatGPT's Advanced Voice Mode as an AI language tutor, part of a test to judge generative AI's potential as both a learning tool and a travel companion. The excessive talking to both strangers and a chatbot on my phone was illuminating as well as exhausting. I'm ready to shut my yapper for a minute and enjoy the silence. When OpenAI launched ChatGPT late in 2022, it set off a firestorm of generative AI competition and public interest.

Since 1999, the opioid epidemic has killed around 645,000 people in America--a number that would no doubt be even higher were it not for naloxone, an opioid antagonist that can effectively reverse the effects of an overdose. However, time is critical: if naloxone is not administered promptly, the victim's chances of survival diminish rapidly. In a paper published August 14 in Device, a team of researchers describe a device designed to detect the signs of an overdose and automatically deliver a dose of naloxone in as little as 10 seconds. The device–which researchers describe as a "robotic first responder"–is named the "implantable system for opioid safety" (iSOS). It's implanted under the user's skin, in the same way as a heart loop recorder.

WEHEAD connects to ChatGPT and displays a face, expressions and voice. The voice Alexis "Lexi" Bogan had before last summer was exuberant. She loved to belt out Taylor Swift and Zach Bryan ballads in the car. She laughed all the time -- even while corralling misbehaving preschoolers or debating politics with friends over a backyard fire pit. In high school, she was a soprano in the chorus.

We introduce OpenBot-Fleet, a comprehensive open-source cloud robotics system for navigation. OpenBot-Fleet uses smartphones for sensing, local compute and communication, Google Firebase for secure cloud storage and off-board compute, and a robust yet low-cost wheeled robot toact in real-world environments. The robots collect task data and upload it to the cloud where navigation policies can be learned either offline or online and can then be sent back to the robot fleet. In our experiments we distribute 72 robots to a crowd of workers who operate them in homes, and show that OpenBot-Fleet can learn robust navigation policies that generalize to unseen homes with >80% success rate. OpenBot-Fleet represents a significant step forward in cloud robotics, making it possible to deploy large continually learning robot fleets in a cost-effective and scalable manner. All materials can be found at https://www.openbot.org. A video is available at https://youtu.be/wiv2oaDgDi8

In this paper, we advocate in favor of smartphone apps as low-cost, easy-to-deploy solution for raising awareness among the population on the proliferation of Aedes aegypti mosquitoes. Nevertheless, devising such a smartphone app is challenging, for many reasons, including the required maturity level of techniques for identifying mosquitoes based on features that can be captured using smartphone resources. In this paper, we identify a set of (non-exhaustive) requirements that smartphone apps must meet to become an effective tooling in the fight against Ae. aegypti, and advance the state-of-the-art with (i) a residual convolutional neural network for classifying Ae. aegypti mosquitoes from their wingbeat sound, (ii) a methodology for reducing the influence of background noise in the classification process, and (iii) a dataset for benchmarking solutions for detecting Ae. aegypti mosquitoes from wingbeat sound recordings. From the analysis of accuracy and recall, we provide evidence that convolutional neural networks have potential as a cornerstone for tracking mosquito apps for smartphones.

ChatGPT is now a smartphone app, which could be good news for people who like to use the artificial intelligence chatbot and bad news for all the clone apps that have tried to profit off the technology. The free app started to become available on iPhones in the United States on Thursday and will later be coming to Android phones. Unlike the web version, you can also ask it questions using your voice. The company that makes it, OpenAI, said it will remain ad-free but "syncs your history across devices". "We're starting our rollout in the US and will expand to additional countries in the coming weeks," said a blog post announcing the new app, which is described in the App Store as the "official app" by OpenAI.

From ShutEye to SleepScore, several smartphone apps are available if you're trying to better understand how snoring impacts your rest, allowing you to leave the microphone on overnight to record your raucous nasal grunts and rumbling throat reverberations. But while smartphone apps are helpful for tracking the presence of snores, their accuracy remains an issue when applied to real-world bedrooms with extraneous noises and multiple audible people. Preliminary research from the University of Southampton looks into whether your snores have a signature sound that could be used for identification. "How do you actually track snoring or coughing accurately?" asks Jagmohan Chauhan, an assistant professor at the university who worked on the research. Machine learning models, specifically deep neural networks, might provide assistance in verifying who is performing that snore-phonic symphony.

From ShutEye to SleepScore, several smartphone apps are available if you're trying to better understand how snoring impacts your rest, allowing you to leave the microphone on overnight to record your raucous nasal grunts and rumbling throat reverberations. But while smartphone apps are helpful for tracking the presence of snores, their accuracy remains an issue when applied to real-world bedrooms with extraneous noises and multiple audible people. Preliminary research from the University of Southampton looks into whether your snores have a signature sound that could be used for identification. "How do you actually track snoring or coughing accurately?" asks Jagmohan Chauhan, an assistant professor at the university who worked on the research. Machine learning models, specifically deep neural networks, might provide assistance in verifying who is performing that snore-phonic symphony.

A smart ring designed exclusively for women will do what no husband would ever dream of – tell them how to snap out of their mood. The Evie ring will monitor the wearer's menstrual cycles, sleep patterns, and other vital statistics in a bid to help her'learn how to feel her best'. Rather than provide the data in complex graphs and charts, the results will instead be simplified into'actionable insights' for the user to change their lifestyle. The Californian-based firm behind the smart ring, Movano, is aiming for it to become the first wearable to also be approved as a medical device. The Evie ring will monitor the wearer's menstrual cycles, sleep patterns, and other vital statistics in a bid to help her'learn how to feel her best' Alongside monitoring heart rate, respiration rate, and skin temperature, the ring will also track users' ovulation, periods, and menstrual symptoms.

Nikon has pushed an update for its NX MobileAir smartphone app that adds new JPEG capabilities, support for RAW files, new quality of life features, and a deep learning algorithm for image analysis. Nikon NX MobileAir is a smartphone app that uploads images taken with a Nikon digital camera to an FTP server without using a computer. It was originally launched last November and is billed as a particularly useful tool for photojournalists that are covering large events like the Olympics or FIFA World Cup who might need to get their images to publications quickly but don't have access to stable WiFi or ethernet. The company says that as part of this update, functions such as image filtering, which uses image analysis technologies, have been added or modified to improve speed and efficiency of workflows. First, Nikon has added what it bills as "deep learning analysis" into the app. The company says that NX Mobile Air now has an algorithm that uses deep learning to analyze images that have been imported, allowing users to filter images in specific criteria, such as subject types and conditions for quick access to intended images.