Shulou(Shulou.com)11/24 Report--

CTOnews.com, June 6 (Xinhua) in Monday's WWDC 2023 keynote speech, Apple not only unveiled much-anticipated new products such as the Mac Pro and Vision Pro, but also showed off its latest advances in machine learning. However, CTOnews.com noted that unlike competitors such as Microsoft and Google that promote generative artificial intelligence, Apple did not mention the word "artificial intelligence" in its speech, but used more terms such as "machine learning" and "ML".

For example, in a demonstration of iOS 17, Craig Federighi, Senior Vice President of Software Engineering, introduced improvements in automatic error correction and speech recognition:

Automatic error correction is driven by machine learning on the device, and we have been improving these models over the years. The keyboard now uses a transformer language model, which is the most advanced word prediction technology, making automatic error correction more accurate than ever. And, with the power of the Apple Silicon chip, iPhone can run the model every time you press a key.

It is worth noting that Apple mentioned a term "transformer" in the field of artificial intelligence in its keynote speech. The company specifically talked about a "transformer language model", which means that its artificial intelligence model uses the transformer architecture, the underlying technology used in many recent generative artificial intelligence, such as DALL-E image generators and ChatGPT chatbots. The transformer model (a concept first proposed in 2017) is a neural network architecture for natural language processing (NLP) that uses a self-attention mechanism to give priority to different words or elements in the sequence. It can process input in parallel, thus significantly improving efficiency, and has made breakthroughs in NLP tasks, such as translation, summary and question and answer.

According to Apple, the new transformer model in iOS 17 enables automatic error correction at the sentence level. When you press the spacebar, it can complete a word or an entire sentence. It will also learn according to your writing style to guide its suggestions. Apple also said that speech recognition "uses a transformer-based speech recognition model, using neural engines to make speech recognition more accurate."

In its keynote speech, Apple also mentioned "machine learning" several times, such as describing the new iPad lock screen feature ("when you choose an Live Photo, we use an advanced machine learning model to synthesize extra frames"). IPadOS PDF function ("with the new machine learning model, iPadOS can recognize fields in PDF, allowing you to quickly fill in information such as names, addresses and emails obtained from your contacts using the auto-fill feature." ); AirPods adaptive audio function ("We use machine learning to understand how your listening preferences change over time by personalizing the volume"); and the Apple Watch widget feature Smart Stack ("Smart Stack uses machine learning to show you relevant information when you need it").

Apple has also launched a new app called Journal, which uses device-side machine learning to provide personalized advice and give users diary inspiration. These suggestions are intelligently generated based on users' recent activities, including photos, people, locations, physical training, etc., to help users start recording more easily.

Finally, when demonstrating the Vision Pro head display, the company revealed that the dynamic image on the user's eye is a special 3D avatar created by scanning your face-thanks to machine learning, of course.

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