watchOS 9 is available for Apple Watch Series 4 and later when paired with iPhone 8 and later or iPhone SE (2nd generation) and later running iOS 16.

At present, the specific update content of watchOS 9.3 is not clear. In watchOS 9.2, “Route Race” allows users to compete against their previous achievements in outdoor running, outdoor cycling and outdoor wheelchair training; new custom algorithms for kickboxing in the “Fitness Training” app make the measurement indicators more accurate. precise.

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How to upgrade iOS / iPadOS / watchOS / macOS dev / public beta?
Simply download and install the [description file] to detect the development / public beta update in the system update.

Please note that due to the caching problem of Apple’s regional node server configuration, there may be a slight delay in detecting the update in some places, usually within half an hour, not too long.

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The update includes improvements and bug fixes for Apple Watch.

• Interruptions in streaming audio on Spotify
• Snooze alarm notifications continue for AssistiveTouch users after deleting the alarm
• Incomplete syncing of wallet and fitness data on newly paired Apple Watches
• Microphone audio interrupted for some Apple Watch Series 8 and Ultra users

watchOS 9.0.2 can be downloaded for free through the dedicated Apple Watch app on iPhone by going to General > Software Update.

To install the new software, the Apple Watch needs to have at least 50% battery, needs to be on a charger, and needs to be located within the communication range of the iPhone.

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First, the redesigned Compass App features an analog compass that displays a digital view of the current bearing and direction. Users can tap to display a zoomed view of current bearing, elevation, inclination and latitude and longitude for more information.

It should be noted, however, that some features will be limited to the new Apple Watch SE / Series 6 and above – such as using the “waypoints” feature with custom color schemes/symbols The Waypoints feature allows you to mark points of interest in the Compass App.

All Waypoints will be displayed in the Compass Home view so users can retrieve them when needed.

Secondly, Apple Watch Series 6 and newer models will also have access to Backtrack, which uses GPS to record the route the user has taken so they can return to it if they get lost.

Finally, watchOS 9 is available for Apple Watch Series 4 and later, so if you’re interested, you can manually check for updates now.

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The new low-power mode in watchOS 9 is separate from the Apple Watch’s existing power reserve mode, which only displays the clock when enabled.

The low-power mode is just one of the new features that will be available on the new Apple Watch Series 8 and Apple Watch SE, which are available for pre-order starting today and will be available on September 16. other new features on the Apple Watch Series 8 include a temperature sensor focused on women’s health and car accident detection.

As for the new high-end Apple Watch Ultra, Apple said a new battery optimization feature will be introduced later this year that will give the device up to 60 hours of battery life per charge, and it sounds like this feature will be different from the low-powered model.

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For example, Apple Watch’s Assistive Touch feature, AirPods Pro’s conversation enhancement and the door detection feature released in iOS 16 and iPadOS 16 are just a few of the ways Apple is making it easier for people with special needs in the accessibility space. Meanwhile, in the area of health, Apple has been thinking about the health of most people. That’s why Apple introduced the new “Sleep Stages” feature in watchOS 9, which will help people better understand their sleep conditions.

She believes that machine learning is becoming an important tool for Apple’s innovation. During the session, she also mentioned that Apple’s machine learning models are not only dependent on chip performance, but also require high-quality input, including touch, motion, sound, and visual information. Apple does this by integrating sensors into hardware devices in order to provide fast and highly accurate signals.

What information did Apple give at the AI World Conference? What are Apple’s new developments in the field of artificial intelligence? We can use this presentation to get an update on what Apple is up to.

▲ Yue Ge, Vice President and Managing Director, Greater China, Apple Inc.

The following is the full text of the speech “Machine Learning for a Healthier and Accessible Future” by Yue Ge, Vice President and Managing Director of Apple Greater China.

Dear Leaders and Distinguished Guests: Good afternoon, everyone. First of all, thank you very much for inviting me back to the World Congress on Artificial Intelligence, and I’m glad to have the opportunity to speak with you today.

At Apple, we want our products to help people innovate and create, providing the support people need in their daily lives. Machine learning plays a critical role in that: it can better leverage the power of our combination of hardware and software to improve people’s lives in every way. We’ve seen its tremendous capabilities countless times.

Today, I want to dive into two areas where the potential to improve people’s lives is particularly clear: accessibility features and health features. We’ll explore some of the features of Apple that machine learning helps make possible: some of them are designed specifically for people with disabilities and special needs, while others can help people from all walks of life lead healthier lives.

But like any technology, machine learning can’t work alone, so I’ll start with the innovations that have helped make it such a powerful tool.

At Apple, we’ve always focused on the holistic nature of product design. So whether it’s the hardware or the software in our products, we’ve always believed that design and integration should go hand in hand.

And a great example of this integration is Apple Silicon, which has helped enable some powerful new features through strong performance and excellent battery life. The Neural Network Engine is a key part of these innovations. It’s built for machine learning and is very powerful and efficient at running machine learning models.

Of course, our cutting-edge machine learning models don’t just rely on powerful chips; they also require high-quality inputs, including information about touch, motion, sound, and vision. We integrate powerful sensors into our devices. These sensors can provide fast and highly accurate signals to our machine learning models.

By combining these sensors, state-of-the-art machine learning models, and the powerful Apple Silicon, we’ve designed features that can run entirely on end devices. Each feature can run on hardware we’ve tailored to maximize efficiency and get the best performance without consuming too much power. Since a high-speed network connection is not required, the performance of the functions is more stable and reliable.

Especially important is that privacy is better protected because no data needs to leave the end device. This advantage is especially important for health and accessibility features. Because for these features, a great user experience cannot be achieved without efficiency, reliability and privacy protection.

Let’s start with assistive features that provide accessibility assistance. We believe the best products in the world should meet the needs of everyone. Accessibility is a core value for us and an important part of what we do across all of our products. We are committed to making products that truly work for everyone.

We know that machine learning can help provide independence and accessibility for users with disabilities, including the visually impaired, the hearing impaired, people with physical and motor disabilities, and those with cognitive impairments. Let’s look at a few examples, starting with the Apple Watch, where the Assistive Touch feature on the Apple Watch allows users with upper limb mobility impairments to control the Apple Watch through gestures.

This feature combines machine learning on the device with data from Apple Watch’s built-in sensors to help detect subtle differences in muscle movement and tendon activity in lieu of tapping the display. By including gyroscopes, accelerometers, and optical heart rate sensors, users can manipulate the Apple Watch with hand movements like squeezing or fisting.

Next, let’s talk about AirPods Pro. AirPods Pro combines Apple’s H1 chip with a built-in microphone for a powerful listening experience through machine learning. conversation enhancement on AirPods Pro uses machine learning to detect and amplify sound. If you’re talking to someone in a noisy restaurant, Conversation Enhancement can focus on the voice of the person in front of you so you can hear them more clearly. It’s worth noting that the feature only needs to be on the end device to work.

Finally, let’s take a look at the Door Detection feature recently released in iOS 16 and iPadOS 16. Door Detection combines a LiDAR scanner, camera, and machine learning running on the end device to help visually impaired users determine the location of a door, detect the distance between a person and the door, and determine whether the door is open or closed. It can even read signs and symbols around doors, such as office room numbers, or signs for accessible entrances.

Users can also use door detection in conjunction with people detection to help visually impaired people move more comfortably in public places, recognizing if someone is nearby and thus maintaining social distance. These are just a few examples of the substantial impact machine learning can have on the lives of people with disabilities. Advances that combine all three – chips, sensor technology, and end-device-based machine learning – make our products easier to use and help users better interact with the outside world.

Health is another area we are focusing on that is full of potential to improve people’s lives. Technology can play an important role in making us physically healthier and encouraging people to live in healthier ways.

Our machine learning and sensor technologies can provide useful health information, enabling users to make small changes in their daily behavior and gradually achieve greater overall health. We always make sure these health features stand up to rigorous scientific validation, and protecting user privacy is always our top priority.

For example, this fall we’re introducing watchOS 9, which includes a new “sleep phase” feature. Apple Watch has a heart rate sensor and accelerometer built into it. Using signals from these sensors, Apple Watch can detect whether the user is in rapid eye movement, core sleep, or deep sleep, and provide detailed metrics such as sleep breathing rate and heart rate.

In addition, fall detection calls on the accelerometer and gyroscope in Apple Watch to identify severe falls through machine learning algorithms. By analyzing wrist trajectory and impact acceleration, Apple Watch can send alerts after a user has fallen. Of course, we wanted to go even further and find ways to support and help users before they fell.

To do that, we created Walking Stability. It’s a first-of-its-kind health feature that uses the data generated by iPhone as users walk to see how much risk they have of falling. This important information can help people improve their mobility over time, thereby reducing their risk of falling.

While our exploration in health is just beginning, we’re already seeing the limitless potential of machine learning and sensor technology to provide health insights, encourage healthy lifestyles and more. All of these capabilities are designed to achieve our mission of creating a better life. We are hopeful about the future of machine learning: we are confident that it can inspire more innovation that will improve people’s lives.

It can help us understand the state of our bodies and adopt healthier habits. It can lower the barriers to technology use and bring the outside world within reach. It can also protect our privacy and give us confidence in the technology.

At Apple, we strive to innovate, empower our users, and make technology a force for good in people’s lives. We’re excited to continue on this path, using machine learning to help create a healthier, more accessible future for all. Thank you, everyone!

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The updated “Big Text” dial is similar to the classic two-line text dial, with a new background color. This digitally styled, clean dial displays the time in bold, either full-screen or above an oversized single complication, putting the information you care about most in plain sight. The dial also supports multiple color options.

In early August, Apple’s Apple Watch went live with its first Chinese character dial, called Typograph. Officially designed to celebrate Typography, the dial features three customizable styles: Classic, Modern and Round. You can choose four numbers or twelve numbers and display them in Arabic numerals, Arabic Hindi numerals, Tencheng numerals, etc.

Apple’s watchOS 9 update introduces several new dial options: a “moon phase” dial depicting the relationship between the solar and lunar calendars, which can be used in multiple cultural settings such as Chinese, Islamic, and Hebrew; a unique dynamic artwork called “Happy Hour ” dial, created by Apple Watch and artist Joi Fulton; an elegant “Metropolis” font dial that changes in style as the user rotates the digital crown; and a completely remastered “Astronomy ” dial, which introduces a new star chart function and cloud data function. Several existing dials have also been improved.

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