Apple is reportedly considering using AI models from Anthropic or OpenAI, rather than its own in-house models, to power a new version of its voice assistant Siri. The company has talked with both of the AI firms and asked them to train versions of their models that it could test on its cloud infrastructure. Apple is in the early stages of considering this move, hasn’t made a final decision, and is still actively developing in-house models for use with Siri. The company currently powers most of its AI features with its own models and has been planning to use that technology for a new version of Siri that would be released in 2026. While Apple allows OpenAI’s ChatGPT to answer some web-based search queries in the voice assistant, Siri itself is powered by Apple. Adopting third-party AI models could allow Apple to offer Siri features that would be competitive with the AI assistants available on Android smartphones. It was reported that Apple aimed to bring an AI-powered upgrade of Siri to market in spring 2026, after facing delays and failing to meet its original goal of fall 2024.
Morgan Stanley research shows Apple Intelligence platform has been downloaded and engaged with by 80% of eligible U.S. iPhone owners in the last six months and has an above average NPS of 53
Consumers’ perception of Apple’s AI platform is more favorable than that of investors, Morgan Stanley said in a research note. Morgan Stanley said it found that the Apple Intelligence platform has been downloaded and engaged with by 80% of eligible U.S. iPhone owners in the last six months, has an above average net promoter score of 53, and is characterized by iPhone users as “easy to use, innovative, and something that improves their user experience.” “While much of the public critique of Apple Intelligence is warranted, and investor sentiment and expectations on Apple’s AI platform couldn’t be lower, our survey of iPhone owners paints a more positive picture,” Morgan Stanley said in the note. Since September, the share of iPhone owners who believe it is extremely or very important to have Apple Intelligence support on their next iPhone rose 15 points to reach 42%. Among iPhone owners who are likely to upgrade their device in the next 12 months, the percentage saying that about the AI platform rose 20 points to reach 54%, according to the note. Morgan Stanley also found that consumers are willing to pay more for Apple Intelligence than they were in September. Those who have used the AI platform are now willing to pay an average of $9.11 per month for it, a figure that’s 11% higher than the $8.17 average seen in September, per the note. While we don’t expect Apple to put Apple Intelligence behind a paywall until the platform is more built out, the potential long-term monetization of an Apple Intelligence subscription could reach tens of billions of dollars annually when considering a 1.4B global iPhone installed base, 32% (and growing) of US iPhone owners have an Apple Intelligence support iPhone, and users are willing to pay up to $9.11/month for Apple Intelligence,” Morgan Stanley said in the note.
Apple Store deploys LLM-based system to offer app review summaries that dynamically adapt, capture the diversity and accurately reflect user’s voice and the most up-to-date feedback
The App Store now offers review summaries in iOS 18.4, providing a high-level overview of user reviews while allowing for detailed exploration. This feature is powered by a multi-step LLM-based system that periodically summarizes user reviews. The aim is to ensure these summaries are inclusive, balanced, and accurately reflect the user’s voice, prioritizing safety, fairness, truthfulness, and helpfulness. This feature is a significant improvement over previous versions. Summarizing crowd-sourced user reviews presents several challenges, each of which we addressed to deliver accurate, high-quality summaries that are useful for users: Timeliness: App reviews change constantly due to new releases, features, and bug fixes. Summaries must dynamically adapt to stay relevant and reflect the most up-to-date user feedback. Diversity: Reviews vary in length, style, and informativeness. Summaries need to capture this diversity to provide both detailed and high-level insights without losing nuance. Accuracy: Not all reviews are specifically focused on an app’s experience and some can include off-topic comments. Summaries need to filter out noise to produce trustworthy summaries.
New York City subway riders to be able to add tap-to-pay OMNY transit card to Apple Wallet, joining SF’s Clipper, Washington DC’s SmarTrip and LA’s TAP card
Apple introduced support for dedicated transit cards in Apple Wallet six years ago, and it has since expanded to include San Francisco’s Clipper card, Washington DC’s SmarTrip card, Los Angeles’ TAP card, and Canada’s PRESTO card. New York City’s OMNY card will soon join the fun of Apple Wallet integration, according to the MTA. The MTA is set to phase out the MetroCard fully within the next year, requiring OMNY to be widely available and easy to use. Major updates involving the OMNY rollout include the launch of a mobile virtual OMNY card for normal commuters and students in Q4 2025 and new integration within the MTA app to manage your OMNY card. If things go according to plan, users will be able to add an OMNY card to Apple or Google Wallet in the coming months, just like in Washington, DC, and San Francisco.
Amazon launches Nova Premier, its most capable AI model yet- has a context length of 1 million tokens, meaning it can analyze around 750,000 words in one go
Amazon released what the company claims is the most capable AI model in its Nova family, Nova Premier, which can process text, images, and videos (but not audio). It is available in Amazon Bedrock, the company’s AI model development platform. Amazon says that Premier excels at “complex tasks” that “require deep understanding of context, multi-step planning, and precise execution across multiple tools and data sources.” Nova Premier, which has a context length of 1 million tokens, meaning it can analyze around 750,000 words in one go, is weaker on certain benchmarks than flagship models from rival AI companies such as Google. In bright spots for Premier, the model does well on tests for knowledge retrieval and visual understanding, SimpleQA and MMMU, according to Amazon’s internal benchmarking. In Bedrock, Premier is priced at $2.50 per 1 million tokens fed into the model and $12.50 per 1 million tokens generated by the model. Importantly, Premier isn’t a “reasoning” model. As opposed to models like OpenAI’s o4-mini and DeepSeek’s R1, it can’t take additional time and computing to carefully consider and fact-check its answers to questions.