As Apple prepares to unveil iOS 19 at WWDC 2025 on Monday, several rumors have surfaced, including a potential new name for the operating system, an entirely new design inspired by the Vision Pro, and more.
Here’s a roundup of the most notable features rumored to be coming to iOS 19.
New name
Sources told Bloomberg that Apple plans to rename its operating systems to reflect the release year rather than using version numbers. This means that iOS 19 will be renamed iOS 26, similar to how car model years are designated. This name change will also apply to other software updates, such as iPadOS 26, macOS 26, watchOS 26, tvOS 26, and visionOS 26.
Major design overhaul
Anticipated to be the most significant design change since iOS 7, the operating system may feature a complete visual overhaul, one that’s reportedly inspired by Apple’s Vision Pro headset, according to Bloomberg. This could include translucent panels for navigation and circular app icons. The visionOS-inspired design will be made across Apple’s entire ecosystem (including CarPlay) with the goal of creating a more cohesive experience.
Additionally, there are three apps expected to undergo the most changes– the Phone app, Camera, and Safari. For instance, the Phone app is rumored to introduce a new option that allows users to merge their favorite contacts, recent calls, and voicemails into a single view. Meanwhile, both the Camera app and Safari are anticipated to have more visual updates, such as a transparent address bar for Apple’s browser app.
Dedicated gaming app
Apple is also rumored to be releasing a gaming app that will integrate Apple Arcade and the App Store’s game offerings, featuring a central hub for achievements, leaderboards, and App Store content. This comes after the company acquired its first game studio, RAC7, according to DigitalTrends.
Virtual health coach
Apple may also be developing an AI feature to serve as a personal health coach. This new chatbot is expected to suggest lifestyle changes and provide health advice based on user data collected from the Health app. Additionally, the Health app may be revamped to include a food-tracking feature, allowing users to log their carbohydrate and caffeine intake.
Smarter battery management
Apple could improve iPhone battery health with AI-powered battery management. This new feature is reported to analyze device usage and make adjustments to conserve battery life. There may also be a new charging icon on the lock screen that gives an estimated time for when it’s fully charged.
Another rumor suggests that reverse wireless charging is being tested on the iPhone 17 Pro models, allowing users to charge accessories such as AirPods or the Apple Watch directly from their iPhone.
AI translation for Messages
According to 9to5Mac, the Messages app is set to get an Apple Intelligence-powered translation feature that can automatically translate messages as soon as they hit users’ inboxes. 9to5Mac also reports that Apple Intelligence could power a polling feature that lets people in group chats vote and offers AI-generated poll suggestions.
Additionally, Messages may also add the ability to set a background image, following in the footsteps of WhatsApp and Instagram.
Preview app
Apple may bring its Preview app from macOS to iPad and iPhone users, allowing them to annotate and edit PDFs. This will reportedly be a preinstalled app, per Bloomberg.
New Genmoji feature
As Bloomberg reports, Genmoji could gain a small yet exciting feature that allows users to combine existing standard emojis, such as a basketball going into a trash can.
What about Siri?
One notable absence from all the rumors is the impressive Siri capabilities highlighted in Apple’s 2024 presentation, which featured a more context-aware assistant that can gather information and perform actions across different apps. The company stated in March that the new features are delayed.
While we can expect some AI-related announcements, the primary focus is likely to be on design changes. Reports indicate that improvements to existing Apple Intelligence features will also be introduced, along with some new additions.
This story was originally published June 3 and will be updated as more rumors come out.
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![In Harvard study, AI offered more accurate emergency room diagnoses than two human doctors | TechCrunch
A new study examines how large language models perform in a variety of medical contexts, including real emergency room cases — where at least one model seemed to be more accurate than human doctors.
The study was published this week in Science and comes from a research team led by physicians and computer scientists at Harvard Medical School and Beth Israel Deaconess Medical Center. The researchers said they conducted a variety of experiments to measure how OpenAI’s models compared to human physicians.
In one experiment, researchers focused on 76 patients who came into the Beth Israel emergency room, comparing the diagnoses offered by two internal medicine attending physicians to those generated by OpenAI’s o1 and 4o models. These diagnoses were assessed by two other attending physicians, who did not know which ones came from humans and which came from AI.
“At each diagnostic touchpoint, o1 either performed nominally better than or on par with the two attending physicians and 4o,” the study said, adding that the differences “were especially pronounced at the first diagnostic touchpoint (initial ER triage), where there is the least information available about the patient and the most urgency to make the correct decision.”
In Harvard Medical School’s press release about the study, the researchers emphasized that they did not “pre-process the data at all” — the AI models were presented with the same information that was available in the electronic medical records at the time of each diagnosis.
With that information, the o1 model managed to offer “the exact or very close diagnosis” in 67% of triage cases, compared to one physician who had the exact or close diagnosis 55% of the time, and to the other who hit the mark 50% of the time.
“We tested the AI model against virtually every benchmark, and it eclipsed both prior models and our physician baselines,” said Arjun Manrai, who heads an AI lab at Harvard Medical School and is one of the study’s lead authors, in the press release.
Techcrunch event
San Francisco, CA
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October 13-15, 2026
To be clear, the study didn’t claim that AI is ready to make real life-or-death decisions in the emergency room. Instead, it said the findings show an “urgent need for prospective trials to evaluate these technologies in real-world patient care settings.”
The researchers also noted that they only studied how models performed when provided with text-based information, and that “existing studies suggest that current foundation models are more limited in reasoning over nontext inputs.”
Adam Rodman, a Beth Israel doctor who’s also one of the study’s lead authors, warned the Guardian that there’s “no formal framework right now for accountability” around AI diagnoses, and that patients still “want humans to guide them through life or death decisions [and] to guide them through challenging treatment decisions.”
In a post about the study, Kristen Panthagani, an emergency physician, said this is an “an interesting AI study that has led to some very overhyped headlines,” especially since it was comparing AI diagnoses to those from internal medicine physicians, not ER physicians.
“If we’re going to compare AI tools to physicians’ clinical ability, we should start by comparing to physicians who actually practice that specialty,” Panthagani said. “I would not be surprised if a LLM could beat a dermatologist at an neurosurgery board exam, [but] that’s not a particularly helpful thing to know.”
She also argued, “As an ER doctor seeing a patient for a first time, my primary goal is not to guess your ultimate diagnosis. My primary goal is to determine if you have a condition that could kill you.”
This post and headline have been updated to reflect the fact that the diagnoses in the study came from internal medicine attending physicians, and to include commentary from Kristen Panthagani.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Harvard #study #offered #accurate #emergency #room #diagnoses #human #doctors #TechCrunchbeth israel,harvard medical school,OpenAI](https://i2.wp.com/techcrunch.com/wp-content/uploads/2024/01/GettyImages-104509077.jpg?resize=1200%2C800&ssl=1 "In Harvard study, AI offered more accurate emergency room diagnoses than two human doctors | TechCrunch
A new study examines how large language models perform in a variety of medical contexts, including real emergency room cases — where at least one model seemed to be more accurate than human doctors.
The study was published this week in Science and comes from a research team led by physicians and computer scientists at Harvard Medical School and Beth Israel Deaconess Medical Center. The researchers said they conducted a variety of experiments to measure how OpenAI’s models compared to human physicians.
In one experiment, researchers focused on 76 patients who came into the Beth Israel emergency room, comparing the diagnoses offered by two internal medicine attending physicians to those generated by OpenAI’s o1 and 4o models. These diagnoses were assessed by two other attending physicians, who did not know which ones came from humans and which came from AI.
“At each diagnostic touchpoint, o1 either performed nominally better than or on par with the two attending physicians and 4o,” the study said, adding that the differences “were especially pronounced at the first diagnostic touchpoint (initial ER triage), where there is the least information available about the patient and the most urgency to make the correct decision.”
In Harvard Medical School’s press release about the study, the researchers emphasized that they did not “pre-process the data at all” — the AI models were presented with the same information that was available in the electronic medical records at the time of each diagnosis.
With that information, the o1 model managed to offer “the exact or very close diagnosis” in 67% of triage cases, compared to one physician who had the exact or close diagnosis 55% of the time, and to the other who hit the mark 50% of the time.
“We tested the AI model against virtually every benchmark, and it eclipsed both prior models and our physician baselines,” said Arjun Manrai, who heads an AI lab at Harvard Medical School and is one of the study’s lead authors, in the press release.
Techcrunch event
San Francisco, CA
|
October 13-15, 2026
To be clear, the study didn’t claim that AI is ready to make real life-or-death decisions in the emergency room. Instead, it said the findings show an “urgent need for prospective trials to evaluate these technologies in real-world patient care settings.”
The researchers also noted that they only studied how models performed when provided with text-based information, and that “existing studies suggest that current foundation models are more limited in reasoning over nontext inputs.”
Adam Rodman, a Beth Israel doctor who’s also one of the study’s lead authors, warned the Guardian that there’s “no formal framework right now for accountability” around AI diagnoses, and that patients still “want humans to guide them through life or death decisions [and] to guide them through challenging treatment decisions.”
In a post about the study, Kristen Panthagani, an emergency physician, said this is an “an interesting AI study that has led to some very overhyped headlines,” especially since it was comparing AI diagnoses to those from internal medicine physicians, not ER physicians.
“If we’re going to compare AI tools to physicians’ clinical ability, we should start by comparing to physicians who actually practice that specialty,” Panthagani said. “I would not be surprised if a LLM could beat a dermatologist at an neurosurgery board exam, [but] that’s not a particularly helpful thing to know.”
She also argued, “As an ER doctor seeing a patient for a first time, my primary goal is not to guess your ultimate diagnosis. My primary goal is to determine if you have a condition that could kill you.”
This post and headline have been updated to reflect the fact that the diagnoses in the study came from internal medicine attending physicians, and to include commentary from Kristen Panthagani.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Harvard #study #offered #accurate #emergency #room #diagnoses #human #doctors #TechCrunchbeth israel,harvard medical school,OpenAI")
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