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10 Bits: The Data News Hotlist

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This week’s list of top data news highlights covers June 8, 2024 to June 14, 2024 and includes articles on LinkedIn’s new AI tools and a machine learning algorithm used to better understand post-surgical recovery.

1. Upgrading Apple Products

Apple is integrating AI into the next generation of iPhones, iPads, and MacBooks. The new built-in AI features include a chatbot that uses OpenAI’s GPT-4o model to answer questions and “Genmoji,” which will allow users to generate custom emojis from a text prompt.

2. Streamlining Airport Security Screenings

The State of New York has launched a mobile app called M-ID that allows travelers to use digital IDs at security checkpoints at New York City’s LaGuardia and John F. Kennedy (JFK) airports. Passengers can scan a QR code in the app to verify their identity instead of providing a physical ID or boarding pass, streamlining the security verification process and cutting airport lines ahead of the busy summer travel season.

3. Enhancing Water Infrastructure

The City of Atlanta is addressing its aging water infrastructure by using AI to detect breaks in water mains, which carry drinking water to homes and businesses. The city is planning to install AI-enhanced devices on water line valves at the sites of recent breaks that had resulted in a 72-hour emergency.

4. Navigating Job Searches

LinkedIn is introducing new features for premium users that include an AI chatbot, which can help answer questions about specific jobs or broader career questions, and a tool that uses generative AI to write resumes, cover letters, and evaluate job fit. The new features will help people find more relevant job opportunities aligned with their skills rather than blindly applying everywhere, with AI assisting in tailoring resumes and cover letters.

5. Navigating Loss and Grief

An Indiana-based startup called Bereave has created software that allows employers to help employees navigate the practical and emotional challenges of dealing with the loss of a loved one. The platform, which businesses can offer as a benefit to employees, provides a checklist and resources for handling tasks like closing accounts, settling estates, and accessing grief counseling when someone dies.

6. Preventing Phone Theft

Google is testing new anti-theft features in phones in Brazil. The phone uses AI to detect signals of common physical movements associated with theft and locks the device’s screen automatically to prevent thieves from using it. This feature may disincentivize phone thefts.

7. Learning Languages

A Ph.D. student at the Massachusetts Institute of Technology (MIT), has created DenseAV, a system that can learn human language from scratch by watching videos and listening to the corresponding audio. DenseAV uses machine learning to identify connections between words, sounds, and visuals to understand the meaning of language without any initial text input. Learning language from audiovisual data could enable machines to comprehend any language, even those without a written form.

8. Revamping Quantum Hardware

Researchers at the University of Bristol in the United Kingdom have integrated the world’s smallest quantum light detector onto a silicon chip, which will enable high-speed quantum communications and help optical quantum computers operate more efficiently. This detector is smaller than a human hair but can precisely measure quantum noise, which is essential for analyzing quantum light and reconstructing quantum states.

9. Treating Diabetic Complications

Scientists have used Tianhe-2, one of the world’s fastest supercomputers, located in Guangzhou City in China, to identify a chemical that can significantly increase blood clotting rates. By studying the properties of this chemical, scientists may be able to create novel therapeutics for treating diabetes patients, who have an increased risk of blood clots.

10. Predicting Surgical Recovery

Researchers at Washington University in St. Louis have developed a machine learning algorithm that uses data from wearables, smartphones, and clinical records to predict recovery outcomes after lumbar spine surgery. The model analyzes different outcome measures like physical function and pain to provide more comprehensive insights regarding factors impacting surgical recovery. The new predictive analytics tool outperformed standard methods, promising to improve clinical decision-making and help doctors personalize treatments for easier post-surgical recovery.

Image credit: Souvik Banarjee


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