Apple’s Artificial Intelligence and Machine Learning are more advanced than many believe

Apple has been working of Artificial Intelligence and Machine Learning for decades, but longtime Apple analyst Tim Bajarin believes that Apple is more cautious about publicly touting its own AI prowess in light of the recent controversies surrounding Microsoft’s Bing AI and Google’s Bard ChatGPT competitor.

Apple M2 Pro Neural Engine
Apple M2 Pro Neural Engine

Tim Bajarin for Forbes:

From a historical standpoint, Apple began showing off early AI models when they introduced their futuristic Knowledge Navigator in 1987 And by 1990, Apple started a significant speech recognition project under Kaifu Lee who today is one the top researchers and experts in AI.

Of course, Apple’s Siri employs modern-day AI and advanced machine learning to deliver answers to spoken questions or requests and is at the heart of Apple Maps.

Apple historically does not take the lead in new technologies, especially if they are not consumer proven…

Apple not jumping into the ChatGPT fray now is reasonable, given the current arrows aimed at Microsoft and Google’s AI ChatGPT solutions.

Although Bing’s ChatGPT and Google’s Bard are excellent products with great potential, it was clear that researchers and savvy media would poke holes in its capabilities and make those failures the headlines.

Given Apple has been researching and applying AI to many of its products since 1986, it is probable they already have its own version of ChatGPT, among other significant breakthroughs in the pipeline.

However, when and how to debut these around an Apple-specific public strategy is being worked on diligently now.

MacDailyNews Take: Apple has made significant strides in the fields of Artificial Intelligence and Machine learning over the years and its efforts are accelerating. Some of Apple’s notable achievements include:

• Core ML: Apple’s Core ML is a framework that allows developers to integrate machine learning models into their iOS apps. Core ML supports a variety of popular machine learning tools and techniques, such as neural networks and decision trees.

• Face ID: Apple’s facial recognition technology, Face ID, uses AI and machine learning to recognize a user’s face and authenticate their identity. Face ID is used on the iPhone and iPad, and is considered one of the most secure forms of biometric authentication.

• Siri: Apple’s voice-activated personal assistant, Siri, is one of the company’s most well-known AI applications. Siri uses natural language processing (NLP) and machine learning to understand and respond to spoken requests from users.

• Apple Neural Engine: Apple’s custom-designed Neural Engine is a chip that is used in some of the company’s devices, including the iPhone and iPad. The Neural Engine is designed specifically for machine learning tasks, and is used to power features like Face ID and Siri.

• Machine Learning Research: Apple also conducts research in the field of machine learning, with a particular focus on developing techniques that can be used to improve user privacy. For example, Apple has developed a technique called “differential privacy,” which allows data to be analyzed without revealing individual users’ personal information.

Overall, Apple has made significant contributions to the field of artificial intelligence, and continues to invest in AI research and development.

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[Thanks to MacDailyNews Reader “Fred Mertz” for the heads up.]


    1. What you mentioned (Yoji) is one of the most garish Apple deficiencies. It’s inexplicable. I’ve ranted here a few times that I go to Google to confirm a word’s spelling–when Apple cannot–and 99.9% of the time an answer is given. They are NEVER complicated words that Apple cannot, but Goog does provide an answer.

      I remember way back in early oughts reading an article about simple tasks that translate to material time saved when using an Apple machine, vs a pc (mouse precision & typing actions). True at the time…but today (in addition to spelling disfunction), I’m often befuddled at the iOS cursor. Was it about 5 yrs ago it was changed? Since that time, I’m reminded of the above article and it’s a flip-flop. The cursory often seems like it’s stubborn and hardly responsive and rarely precise.

      Say nothing of Siri…which I gave up two+ yrs ago and I’m better off for it. Siri’s productivity is much like the spelling and cursor examples. She really is an idiot. No one at Apple experiences the curious ineffectiveness?

  1. “ Apple historically does not take the lead in new technologies, especially if they are not consumer proven.”
    You mean other than inventing the personal computer, the Lisa/Macintosh ……?

  2. Forget machine learning, how about just „learning”? I’m willing to treat Siri like a little kid and teach it to do very specific tasks that are repetetive that would be very helpful to semi-automate. But I can’t even do that! Forget ever asking for something obvious like, „hey Siri, read my shopping list note”, we don’t even have a Notes app for the watch yet!

  3. It is true that they are more cautious in their statements, but it does not indicate that they are more intelligent than Bing AI and Google. The use of AI on Apple products makes me think they are being too arrogant.

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