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DeeperML - #siriupgrade
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Mark Gurman@Bloomberg Technology
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Apple is facing delays in the release of its AI-powered Siri upgrade, now reportedly slated for Spring 2026 with the iOS 26.4 update. This news follows the recent WWDC 2025 event, where AI features were showcased across various Apple operating systems, but the highly anticipated Siri overhaul was notably absent. Sources indicate that the delay stems from challenges in integrating older Siri systems with newer platforms, forcing engineers to rebuild the assistant from scratch. Craig Federighi, Apple’s head of software engineering, explained that the previous V1 architecture was insufficient for achieving the desired quality, prompting a shift to a "deeper end-to-end architecture" known as V2.
This delay has also reportedly caused internal tensions within Apple, with the AI and marketing teams allegedly blaming each other for overpromising and failing to meet timelines. While no exact date has been finalized for the iOS 26.4 release, insiders suggest a spring timeframe, aligning with Apple's typical release schedule for ".4" updates. The upgraded Siri is expected to offer smarter responses, improved app control, and on-screen awareness, allowing it to tap into users' personal context and perform actions based on what's displayed on their devices. Separately, Apple researchers have revealed structural failures in large reasoning models (LRMs) through puzzle-based evaluations. A recently released Apple research paper claimed that contemporary AI LLMs and LRMs fail to make sound judgements as the complexity of problems in controlled puzzle environments they were tasked to solve increased, revealing their fundamental limitations and debunking the common belief that these models can think like a human being. This work, conducted using puzzles like the Tower of Hanoi and River Crossing, aimed to assess the true reasoning capabilities of AI models by analyzing their performance on unfamiliar tasks, free from data contamination. Professor Seok Joon Kwon of Sungkyunkwan University believes Apple does not have enough high-performance hardware to test what high-end LRMs and LLMs are truly capable of.
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