At its latest product unveiling, Apple notably downplayed Artificial Intelligence, a significant departure from previous events where AI was a central theme. The focus shifted predominantly to hardware improvements across its product lines, including iPhones, AirPods, and Apple Watch. This strategy marks a clear pivot for the tech giant, which has faced scrutiny over its AI development compared to competitors.
The Unexpected Quiet: Apple's AI Narrative Shift
Apple's iPhone 17 Event: A New Direction
Apple's recent highly anticipated launch event showcased a range of new products, from updated AirPods and Apple Watch models to the latest iPhones. However, a striking element was the minimal emphasis placed on Artificial Intelligence. Unlike prior presentations that heavily highlighted 'Apple Intelligence,' this event, lasting only 75 minutes, barely touched upon the topic.
iPhone 17 Unveiling: Hardware Takes Center Stage, AI Recedes
While CEO Tim Cook heralded the iPhone 17 as the "biggest leap ever for iPhone," discussions around Apple Intelligence were largely superficial during the new phone's debut. Apple underscored the advancements in its custom silicon, hardware, and software, emphasizing improvements in gaming, photography, processing speed, and battery longevity. Yet, the advanced, user-facing AI functionalities previously showcased, such as visual intelligence and real-time translation for messaging and calls, had already been introduced at WWDC 2025. These features, moreover, are not unique to Apple, with rivals like Google and Samsung having offered similar capabilities for over a year.
From AI Dominance to Background Enhancement: A Strategic Shift
This year's presentation differed significantly from the iPhone 16 launch, where AI was a prominent talking point, leading to user dissatisfaction when some promised features failed to materialize as expected. Instead, Apple chose to illustrate how AI seamlessly operates behind the scenes, powering various functionalities, rather than promoting it as a direct consumer-facing tool. This approach contrasts with recent events from Google and Samsung, which prominently featured their AI assistants.
The Power Behind the Scenes: Neural Engines and Machine Learning
Executives elaborated on how enhanced neural engines drive Apple Intelligence and how local large language models contribute to superior gaming performance and higher frame rates. They highlighted the integration of neural accelerators within each GPU core, enabling iPhone to handle intensive AI workloads at levels comparable to a MacBook Pro.
AI's Subtle Role in Wearable Technology
Regarding new AirPods, Apple emphasized live translation and heart rate monitoring, diverging from Google's strategy of integrating AI assistants like Gemini. Apple clarified that advanced computational models within the devices, combined with Apple Intelligence on iPhones, facilitate live translation. For heart rate sensors, the company pointed to machine learning algorithms that process over 50 million hours of training data from a study involving more than 250,000 participants, enabling on-device AI for activity and calorie tracking.
Healthcare Innovation Powered by AI
Similarly, the discussion on the new Apple Watch's health features also briefly touched on AI. Executives noted how Apple's machine learning algorithms analyze 30-day blood pressure responses to heartbeats, drawing from studies with over 100,000 participants. Dr. Sumbul Desai, Apple’s VP of Health, expressed optimism about identifying over a million undiagnosed hypertension cases within the first year, pending FDA approval.
The AI Landscape: A High-Stakes Environment
The competition in the AI sector has intensified, driven by substantial investments. Companies like OpenAI and Anthropic have secured massive valuations and funding, reflecting the high costs associated with leading AI research. Meta, for instance, has invested billions in talent acquisition and research. Apple has faced criticism for lagging in the AI race, evidenced by recent departures from its AI research department, including key robotics and foundation model researchers who have moved to competitors like Meta, OpenAI, and Anthropic.
