Graças a essa versatilidade, o novo modo de voz pode fazer bem mais que apenas conversar. Além de poder ser usado em chats, ele também está integrado ao Work e ao Codex — o que significa que você pode usá-lo para coordenar e acompanhar tarefas, sem usar texto.
ChatGPT Voice is now in the desktop app.
Control your computer and direct multiple agents running in ChatGPT Work or Codex, using just your voice.
It's powered by GPT-Live, so it can speak, listen, and coordinate work in the app at the same time.
Para usar a novidade, é necessário abrir um novo chat ou uma nova tarefa vazia no app e selecionar a opção “Iniciar nova conversa por voz”. As conversas ou tarefas precisam necessariamente ser iniciadas nesse modo — caso contrário, apenas o ditado por voz estará disponível.
O ChatGPT Voice oferece suporte a uma alternância natural entre as falas. Você pode interromper o ChatGPT durante uma resposta, fazer uma pergunta complementar ou mudar de direção. Se o ChatGPT começar a executar uma tarefa, continue falando para verificar o progresso ou orientar o trabalho.
Além disso, a OpenAI destaca que é possível iniciar conversas separadas para conversas mais longas, enviar ao app uma screenshot para apresentar o contexto do que está na tela, bem como usar o recurso pelo Remote do iOS com o iPhone emparelhado ao computador.
O ChatGPT Voice no desktop está sendo disponibilizado gradualmente para os planos Plus, Pro, Business, Edu e Enterprise. Nos dois últimos, há um período inicial de duas semanas com acesso antecipado antes de o recurso ser ativado por padrão.
É possível baixar o novo app do ChatGPT para macOS nessa página.
Apple Intelligence on-device processing remains Apple’s most convincing argument in artificial intelligence. Rivals may lead in public model rankings, chatbot adoption and the speed of releasing experimental features, but Apple is building AI inside devices people already use for their most personal work.
That distinction changes the definition of winning.
Apple does not need every iPhone owner to open a separate chatbot app. It can place intelligence inside Messages, Mail, Photos, Notes, Shortcuts, Siri and third-party apps. Local models can operate on private information without automatically transferring that information to an external server.
The strategy appeared slow while the AI market measured progress through chatbot launches and model size. It looks more competitive as the industry confronts cloud costs, privacy concerns, unreliable connectivity and the difficulty of turning general-purpose AI into useful daily actions.
In his video “Apple Lost the AI Race,” Marques Brownlee captures the contradiction in one concise line:
“Apple lost the AI race. Actually, Apple won the AI race.”
The apparent reversal describes Apple’s current position well. Apple may have lost the first race for public perception. It is increasingly prepared for the longer contest over where AI runs, how it reaches users and who controls the personal data required to make it useful.
Apple Intelligence On-Device Changes the AI Relationship
Most popular generative AI products began as cloud services. A user sends a request to a remote model, the provider processes it in a data center and the answer returns through an app or browser.
That structure supports enormous models but creates dependence on internet access, server capacity and continuing infrastructure expense. It also means personal prompts leave the device, even when the provider uses strong security and privacy policies.
Apple Intelligence on-device begins from the opposite direction. The iPhone, iPad or Mac first attempts to handle the request locally using Apple Foundation Models optimized for Apple silicon.
That local model does not need to know everything available on the internet. It needs to understand the user’s request, work with relevant personal context and complete common tasks efficiently.
The difference is similar to owning a capable computer rather than renting every calculation from a distant server. Cloud systems remain useful for difficult workloads, but they no longer need to participate in every interaction.
For Apple, local processing is also a product advantage. The company controls the chip, operating system, model architecture, memory system and apps. Each layer can be designed around the others rather than assembled from unrelated services.
Image Credit: Apple Inc.
Privacy Becomes a Technical Feature
Technology companies frequently describe privacy as a policy. Apple is trying to make it part of the AI architecture.
When a request runs entirely on an iPhone, the associated data does not need to leave the device. A model can work with messages, appointments, photos or app content without uploading that personal context to a conventional cloud account.
That structure is especially relevant to Siri AI. A truly personal assistant needs access to information that users may never place willingly inside an ordinary chatbot: private conversations, travel plans, health-related details, work documents and relationships between people.
An assistant becomes more useful as it gains context. It also becomes more invasive when the same context is stored, analyzed or used for model training outside the device.
Apple Intelligence on-device allows Apple to expand personal context while maintaining a stronger boundary around it. The assistant can understand information locally, perform an action and discard temporary processing data without building a permanent advertising or training profile.
This is difficult for competitors whose businesses depend on cloud services, large-scale data collection or engagement inside separate AI products. Apple’s hardware business gives it different incentives.
Private Cloud Compute Extends the Model
Not every AI task can fit within the power and memory limits of an iPhone. Apple uses Private Cloud Compute when a request requires a larger model.
Private Cloud Compute is designed to extend the privacy architecture of Apple devices into the cloud. User information is processed only for the request, is not stored and is not made available to Apple for unrelated purposes.
Independent researchers can inspect software images used by the system, creating an unusual level of outside visibility into the cloud environment. Apple has also expanded the architecture while maintaining control over the software and privacy protections used for processing.
This creates a layered system rather than a simple choice between local and cloud AI.
Apple Intelligence first determines whether the device can handle the request. More complex work can move to Private Cloud Compute. External models may be offered separately when the user chooses to involve them.
The user does not need to understand the technical path behind every answer. The system chooses the smallest and most private environment capable of completing the task.
Apple Silicon Was an AI Investment
Apple’s control of its processors has become one of its largest advantages in the AI era.
The Neural Engine first appeared years before generative AI became a consumer obsession. It supported Face ID, photography, speech recognition and other machine-learning tasks. Apple continued expanding that hardware across the iPhone, iPad and Mac.
Those investments now provide a large installed base of devices designed to run machine-learning workloads locally. Recent Apple chips combine CPU, GPU, Neural Engine and unified memory in one architecture that can move information efficiently between different types of processing.
The same design helps foundation models run without requiring the power consumption or separate memory systems associated with conventional data-center hardware.
Apple also controls the operating systems that schedule those workloads. A model can be optimized for the exact processors, memory limits and energy behavior of supported devices.
Competitors can build excellent models, but they often need to support hardware from several manufacturers with inconsistent capabilities. Apple can decide that an AI feature requires a specific generation of silicon and design the complete experience around it.
Developers Gain a Local Model
The Foundation Models framework extends Apple Intelligence on-device beyond Apple’s own apps. Developers can use the system model through native Swift tools rather than shipping a separate large model or paying for every cloud request.
An app can generate structured content, interpret natural language or use tool calling while keeping supported processing on the device. Apple handles model delivery and system integration.
This can reduce operating costs for developers. A cloud-based AI feature creates an ongoing expense each time a user submits a request. Local inference uses hardware the customer already owns.
It can also improve reliability. Features may remain available without an internet connection and respond without waiting for a remote service.
The framework encourages a quieter form of AI adoption. Apps do not need to add a prominent chatbot tab or redesign themselves around a conversational interface. Intelligence can appear inside existing workflows as a useful capability.
That is where Apple’s strategy may reach scale. Millions of apps can incorporate small AI functions that users experience as normal software behavior rather than as visits to an AI destination.
Image Credit: Apple Inc.
The Installed Base Is Apple’s Distribution Advantage
The AI race is often discussed as a contest between models. Consumer adoption also depends on distribution.
Apple can deliver new intelligence features through operating-system updates across the iPhone, iPad, Mac and Vision Pro. Users do not need to create another account, choose a provider or transfer their personal information into a new service.
Siri already occupies the system interface. Apple Intelligence can work across first-party apps. Developers can connect their own features through Apple frameworks.
The scale is difficult to reproduce. A model provider may have stronger benchmark scores but still need users to download an app and consciously open it. Apple can introduce AI during actions people already perform: replying to a message, locating a photo, organizing a note or completing a shortcut.
This does not guarantee success. Apple must make Siri AI reliable, keep feature availability consistent and prove that local models can deliver enough capability to satisfy users accustomed to powerful cloud assistants.
The distribution advantage only becomes meaningful when the experience works.
Winning Without Building the Loudest Chatbot
Apple has made mistakes during its AI transition. Siri improvements arrived later than promised, regional regulations delayed features and competitors established powerful consumer brands before Apple completed its new system.
Those setbacks explain why the claim that Apple lost the AI race became persuasive.
They do not settle the outcome.
The first stage rewarded companies that released chatbots quickly and demonstrated increasingly large models. The next stage may reward systems that can integrate AI into ordinary life without demanding constant cloud access, high subscription costs or broad collection of personal information.
Apple Intelligence on-device is built for that stage. It uses hardware already in the user’s hand, protects more personal context locally and gives developers access to intelligence without requiring every interaction to become a server transaction.
Apple does not need to win every benchmark or release the most talkative assistant. It needs AI to become a reliable part of the devices people already trust.
Brownlee’s title works because both statements can be true. Apple lost the visible sprint that defined the early generative AI market. By concentrating on local processing, silicon, privacy and operating-system integration, it may already be positioning itself to win the race that follows.
Simply put, polling rate is the frequency at which data is sent between your mouse and keyboard to your computer. For many years, the standard polling rate of most gaming mice and keyboards was 1,000Hz, and that's still a setting that's available by default.
However, with the rise of competitive shooters, particularly tactical ones such as CS2, VALORANT, and Rainbow Six Siege, the pro scene needed a shift, and we saw the advancement towards 4,000Hz and 8,000Hz for "esports tech".
But does anyone really need an 8,000Hz polling rate when gaming? Do the best FPS players in the world even take advantage of it? I'm going through everything you need to know about how 8K works, the latency you can expect, impact on battery life, and all other things you need to consider when properly getting your setup ready for success.
How does polling rate affect latency?
The Razer Viper V4 Pro is among the best gaming mice, and it supports 8K polling (Image credit: Future)
True to its namesake, an 8K polling rate will report its position to your PC a total of 8,000 times, instead of 4,000 times or a thousand times as with 4,000Hz and 1,000Hz, respectively. An 8,000Hz polling rate responds with far lower latency than either of these two previous standards; specifically, updates are sent between a mouse or a keyboard to your computer's processor every 0.125ms, eliminating a theoretical maximum of 0.875 ms input delay, meaning a smoother cursor or movement.
The difference in response time of 0.125ms (8K), 0.25ms (4K), and 1ms (1K) can be huge when it comes to polling rate, provided you have the right hardware to properly take advantage of this. That's because an 8,000Hz polling rate can be incredibly demanding on the battery life of wireless mice and keyboards, and it's one of the main considerations as to why you may want to drop the response time down in your settings.
The drawbacks of an 8,000Hz polling rate
The Corsair Sabre V2 MG, like many top-end mice, have the option of 8K polling wirelessly, even if it comes at 1K out of the box (Image credit: Future)
In brief, an 8,000Hz polling rate for your mouse and keyboard can be incredibly demanding on your computer. That includes heavy strain on even the best processors, the aforementioned heavily reduced battery life on a mouse and keyboard, and even the potential risk of micro-stuttering. As a lifelong PC gamer and a competitive shooter enthusiast who is hopelessly obsessed with VALORANT, I've seen the battery life debate happen in real-time.
I've tested and reviewed hundreds of mice and keyboards throughout my career, and one of the biggest points of contention when it comes to enabling the polling rate comes down to battery life. As an example, my favorite gaming mouse of all time is the Corsair Sabre V2 MG, an 8K-enabled gaming mouse that's built with a Magnesium Alloy frame. It weighs just 56g and features excellent skates, making it ideal for a precision heavy shooter.
As standard, via the Corsair Web Hub, this gaming mouse will run out of the box at 1,000Hz (1K), with battery life prioritized. With the pointer used as the stock, you can expect around 100 to 120 hours of play between charges. In my experience, I am charging this mouse every two weeks or so, depending on how much I'm working day-to-day, etc. However, in my many months with this mouse, I've noticed that things fall off incredibly hard with 8K enabled; my battery life tends to last only around two to three days (or one or two nights of VALORANT Competitive) before I'm reaching for the USB-C lead.
If we take 18 hours as the average battery life from the Corsair Sabre V2 MG when used in 8K mode, that's a reduction of around 85%, which is staggering. We can see a similar drop off from the most well-used new esports mice currently on the market, with the Razer Viper V4 Pro (an excellent mouse), touting up to 180 hours of playback in 1K but only 45 hours when maxed out at 8K. Similarly, while the Logitech G Pro X2 Superstrike has around a 90-hour playback at 1K, that drops down dramatically to between 20 and 35 hours at 8K. With Logitech's pointer, though, you have to factor in the strength of the haptics here, hence the rough range rather than a more exact figure.
What about the human limitations of an 8,000Hz polling rate?
(Image credit: Future)
Now that we've covered what an 8,000Hz polling rate is, how it works, how it compares against 1K and 4K, and the technical drawbacks, we now need to go over the human limitations with 8K. As previously mentioned, 1K means a 1ms response time, and that gets cut down to just 0.125ms with 8K, but what does that mean for a human being, and not a machine?
The average human response time is around 250-280ms; that's the time it takes to see something and physically react. I am not a pro player, but I do play video games at a high level, with a response time average of around 175ms, though I've been faster. The best esports players can eclipse this effortlessly: you only need to look as far as VALORANT and CS2 players, such as TenZ (widely considered to be among the best VALORANT players), with an average reaction time of 135ms. 100ms is even possible, even though the average tends to hover around the 150ms mark.
If we take 1K as a baseline for polling rate, that means there's an average of 150 reports between the mouse/keyboard and the processor, as you tap a key or click what you see. Taking 8K, then, sees 1,200 instances. With this information in mind, is there really much of an advantage here, even at this granular level, with the best players in the world and, conversely, the only people who would even notice a proper difference between 1K, 4K, and 8K?
Do pro players use 8,000Hz polling rates?
The best gamers in the world aren't interested in using an 8,000Hz polling rate for their keyboards or mice. (Image credit: Secretlab)
Considering the far lower latency, you would expect that professional esports gamers would all dial their settings to an 8,000Hz polling rate by default when playing demanding games, but that's simply not the case. If we look back at TenZ's mouse and keyboard settings when playing VALORANT, he last used the Pulsar TenZ Signature Edition mouse at 1,600 DPI, 0.24 sensitivity, and (most crucially) a 1,000Hz polling rate as standard; no 4K, and certainly no 8K enforced here.
What about a VALORANT player from the most aggressive team in the game? Then we must look at f0rsakeN from the legendary Paper Rex. He was last using the Pulsar Sustanto-X with an 800 DPI, a 0.71 sensitivity, and a 4,000Hz polling rate. Let's move away from Riot Games' shooter and instead turn our attention to Valve, then. As far as CS2 players go, few are as well-regarded in 2026 as Team Spirit's donk.
The young Russian is widely regarded as the best player in the world. Is he using an 8K polling rate for his mouse and keyboard to do this? No, while he previously used the industry standard Logitech G PRO X Superlight 2, he's now switched to a bespoke, and as of yet unreleased/prototype Zowie X Donk mouse at 800 DPI, 1.25 sensitivity, and a 1,000Hz polling rate. What about Niko? He recently had his own Razer collaboration drop, and currently uses a Razer Deathadder V4 Pro Niko Edition with an 800 DPI, 0.9 sensitivity, and a 2,000Hz polling rate.
Let's briefly look at two games for the sake of argument, and two of their respective top players. Peterbot is widely considered the best Fortnite player in the world, and he uses a Logitech G Pro X Superlight 2 at 800 DPI with a 1,000Hz polling rate. ImperialHal is among the best Apex Legends players, and the CEO (as he's known) currently uses a Finalmouse Starlight Pro with an 800 DPI, a 1.1 sensitivity, and a 1,000Hz polling rate. So, pro players simply are not using an 8,000Hz polling rate when playing, and they're simply better than the other 99.9% of players who play these games.
Is using an 8,000Hz polling rate worth it?
Based on everything I've gone through here, it becomes challenging to wholesale recommend (or actively condemn) 8K. An 8,000Hz polling rate is mechanically and technically better for how it responds between the peripheral and the machine, even if the human who presses that key or clicks the mouse ends up being the limiting factor, or bottleneck. It's the simple, undeniable truth that the saved milliseconds are (really) indistinguishable to basically everyone on the planet.
Then we get into the debate of battery life. Do you want your gaming mouse to last over 100 hours on a single charge, or just 10? That's a tough sell, considering it undercuts the primary reason to cut the cord in the first place. Then there's the massive CPU overload, game engine incompatibility (and developers and publishers are not yet gearing their software for the tech), and the variables of the hardware itself. Hardware makes the difference: TMR and Hall Effect switches and sensors will have far more of an impact than the simple reporting time between the processor and peripheral.
So why am I not fully discouraging you from using an 8,000Hz polling rate in its entirety? Because it ultimately comes down to personal preference, and to feel. If you're running one of the best gaming PCs or best gaming laptops with a high-end processor, a 4K graphics card, and a high refresh rate monitor, then, battery life aside, it doesn't really hurt to have everything cranked up and forgotten about. Are you likely to really notice it? No, but fractional optimization is still (ever so slightly) better than none in the first place.
I'm not quite cynical enough to claim that an 8,000Hz polling rate is just a marketing gimmick; however, I will say that hardware companies have gleefully exploited the ignorance of the end consumer, the simple reductionist view that a bigger number automatically means better, without looking into the nuances of the conversation. Now that's something you will be fully clued up on when considering your next keyboard or mouse.
Our remote team clocked serious hours walking, working, and sometimes jogging to find the best under-desk treadmills for home offices and small spaces.
Our remote team clocked serious hours walking, working, and sometimes jogging to find the best under-desk treadmills for home offices and small spaces.
A leaf-eared mouse living more than 6,700 meters (22,000 feet) above sea level in the Andes has shattered assumptions about where mammals can survive. Near the summit of an Andean volcano, where the air contains barely half as much oxygen as it does at sea level, scientists found something that should not have been there: [...]
Long before Taco Tuesday became part of the pop-culture vernacular, Tuesdays were synonymous with security — and for anyone in the tech world, they still are. Patch Tuesday, as you most likely know, refers to the day each month when Microsoft releases security updates and patches for its software products — everything from Windows to Office to SQL Server, developer tools to browsers.
The practice, which happens on the second Tuesday of the month, was initiated to streamline the patch distribution process and make it easier for users and IT system administrators to manage updates. Like tacos, Patch Tuesday is here to stay.
In a blog post celebrating the 20th anniversary of Patch Tuesday, the Microsoft Security Response Center wrote: “The concept of Patch Tuesday was conceived and implemented in 2003. Before this unified approach, our security updates were sporadic, posing significant challenges for IT professionals and organizations in deploying critical patches in a timely manner.”
Patch Tuesday will continue to be an “important part of our strategy to keep users secure,” Microsoft said, adding that it’s now an important part of the cybersecurity industry. As a case in point, Adobe, among others, follows a similar patch cadence.
Patch Tuesday coverage has also long been a staple of Computerworld’s commitment to provide critical information to the IT industry. That’s why we’ve gathered together this collection of recent patches, a rolling list we’ll keep updated each month.
In case you missed a recent Patch Tuesday announcement, here are the latest six months of updates.
July’s Patch Tuesday sees an end-of-support collision amidst a massive, record-setting patch wave
Microsoft addressed 722 CVEs this month once the 427 Chromium upstream relays are set aside — roughly three times a normal cycle and one of the largest single months in recent memory. Two vulnerabilities arrive under active exploitation: an elevation of privilege in Active Directory Federation Services (CVE-2026-56155), and an elevation of privilege in SharePoint Server (CVE-2026-56164). A third, a BitLocker security feature bypass (CVE-2026-50661) is publicly disclosed but not yet exploited.
The July 2026 Patch Tuesday earns Patch Now recommendations for Windows, Office, Exchange, and SQL Server. SharePoint has two critical RCEs on top of its exploited zero-day, and Exchange Server returns with a critical on-premises spoofing flaw. Adding to our (dear) administrator’s efforts, SharePoint Server 2016/2019 and SQL Server 2016 all reach end of support today. The Readiness team has provided a handy infographic of the expected risk profile of this month’s Patch Tuesday updates.
Microsoft this month released 206 updates affecting Windows, Office, Exchange Server, and its developer tools — including three Windows vulnerabilities already publicly disclosed. That trio includes an elevation of privilege in the Collaborative Translation Framework (CVE-2026-45586), a denial of service in HTTP.sys (CVE-2026-49160), and a BitLocker security feature bypass (CVE-2026-50507). At the moment, none appear to be under active exploitation, but all three are rated “Exploitation More Likely.”
Even without an exploited zero-day, the June 2026 Patch Tuesday release requires Patch Now recommendations for Windows, Office, and Exchange. The latter is back in the patch picture with a consolidated security update that Microsoft recommends installing “as soon as possible.”
For May, Patch Tuesday means 139 updates — but no zero-days
Microsoft this month released 139 updates affecting Windows, Office, .NET, and SQL Server (though there were no updates for Microsoft Exchange Server). Despite the absence of zero-days, the May Patch Tuesday update still requires Patch Now recommendations for Windows and Office.
The combination of three unauthenticated network RCEs (Netlogon, DNS Client, and SSO Plugin for Jira and Confluence), four Word Preview Pane RCEs, the large TCP/IP vulnerability cluster, and the carry-over BitLocker recovery condition (still active on Windows 10 and Windows Server) warrants an accelerated deployment release schedule.
Microsoft’s Patch Tuesday release for April is a whopper
Windows admins are going to be busy this month, dealing with the largest Patch Tuesday cycle in memory. The April release involves 165 updates and roughly 340 unique CVEs from Microsoft — including two zero-days, one of which is already being actively exploited in the wild.
The Readiness team recommends “Patch Now” schedules for nearly every major product family: Windows, Office (with a zero-day), Microsoft Edge (Chromium), SQL Server, and Microsoft Developer Tools (.NET). April also brings Phase 2 of Microsoft’s Kerberos RC4 hardening with full enforcement set for July. There is a lot to cover, so here’s a useful infographic mapping the deployment risk for each platform.
For March, Patch Tuesday delivers fixes for 83 vulnerabilities
Microsoft’s March Patch Tuesday release addresses 83 vulnerabilities across Windows, Office, SQL Server, Azure, and .NET — with two publicly disclosed zero-days affecting SQL Server and .NET (though neither is being actively exploited in the wild.) Six additional vulnerabilities spanning the Windows Kernel, Graphics Component, SMB Server, Accessibility Infrastructure, and Winlogon are flagged as “Exploitation More Likely.”
February’s Patch Tuesday release fixes 59 flaws, including 6 being exploited
The company’s Patch Tuesday release for February addresses 59 CVEs across the company’s product family — roughly half the volume of January’s 159 patches. Six vulnerabilities, affecting Windows Shell, MSHTML, Desktop Window Manager, Remote Desktop, Remote Access, and Microsoft Word, are already being actively exploited. (All five Critical-rated CVEs target Azureservices rather than Windows, however.)
We consulted preparedness experts and WIRED’s team of testers for the essential gear to keep on hand in case of wildfires, earthquakes, and lord knows what else.
We consulted preparedness experts and WIRED’s team of testers for the essential gear to keep on hand in case of wildfires, earthquakes, and lord knows what else.
Call forwarding on iPhone is a simple feature with a specific job: it sends incoming calls from your iPhone number to another phone number. That can be useful when you are traveling, using a temporary phone, separating work and personal calls, covering a business line or making sure important calls reach someone else when you cannot answer.
The feature is built into iOS, but it depends on carrier support. Apple notes that call forwarding can be set up on iPhone if cellular service is through a GSM network. If the service uses a CDMA network, users may need to contact the carrier for setup details. That means the option may not appear for every user, every carrier or every plan.
For most supported iPhones, the path is quick:
Settings > Apps > Phone > Call Forwarding
Turn on Call Forwarding, then enter the phone number where calls should be sent. When call forwarding is active, an icon appears in the status bar so the user can see that incoming calls are being routed elsewhere.
Image Credit: AppleMagazine
Call Forwarding on iPhone Sends Calls Elsewhere
Call forwarding on iPhone does not move messages, FaceTime calls, app notifications or voicemail settings by itself. It only redirects standard cellular phone calls. If someone calls your iPhone number, the carrier routes that call to the number you entered.
That distinction is important. If you forward calls to another phone, text messages still arrive on the original iPhone unless other settings or services are involved. FaceTime calls may still ring on Apple devices signed into the same Apple Account. Messaging apps such as WhatsApp, Signal, Telegram or Messenger are unaffected.
Call forwarding is also different from Silence Unknown Callers, Focus modes or Do Not Disturb. Those features control how calls appear or interrupt you. Call forwarding changes where the call goes.
This makes the feature useful in a few common situations. A business owner can send calls to an office line. A traveler can forward calls to a local number. Someone with a damaged iPhone can temporarily send calls to another device. A freelancer can route calls to a partner during time off. A parent can forward calls to a spouse for a short period.
How to Turn On Call Forwarding
To turn on call forwarding:
Settings > Apps > Phone > Call Forwarding
Turn on Call Forwarding
Tap Forward To
Enter the phone number
Go back to save the setting
Use the full phone number, including area code. If forwarding to an international number, include the correct country code. After setting it up, test the feature from another phone. Do not assume it works until a test call rings at the forwarded number.
To turn call forwarding off:
Settings > Apps > Phone > Call Forwarding >Turn off
After turning it off, test again. A quick call from another phone confirms whether incoming calls are back to normal.
If the Call Forwarding menu spins, fails to load or does not save the number, restart the iPhone and check cellular service. If the problem continues, contact the carrier because the setting depends on the carrier network.
Why the Setting May Be Missing
Some users look for call forwarding and cannot find it. That usually means one of three things: the carrier does not expose the feature in iPhone settings, the plan does not support it, or the network requires carrier codes or account-level setup.
Apple’s guide says CDMA users should contact their carrier for call forwarding information. Some carriers also use special dialing codes for forwarding all calls, forwarding when busy, forwarding when unanswered or forwarding when unreachable. Those codes vary by carrier and country, so guessing is not a good idea.
The best path is to check the carrier’s support page or app. Many carriers let users manage forwarding from the account dashboard, especially for business lines or multi-line plans.
If the option is missing, the iPhone is not necessarily broken. The carrier may simply handle forwarding differently.
What Happens to Voicemail
Call forwarding can affect voicemail behavior depending on the carrier and destination number. If the forwarded phone does not answer, the call may go to the voicemail of the forwarded number instead of the original iPhone voicemail. In some cases, carrier rules may still send it back to the original mailbox, but users should not assume that.
This is another reason to test. Call the iPhone from another number, let it ring, and see where the missed call lands. If the goal is to preserve the original iPhone voicemail, carrier support may be needed.
For work numbers, this can be especially important. A forwarded business call going to a personal voicemail greeting can look unprofessional. A personal call going to a shared office voicemail can create privacy problems. Check before relying on it.
Image Credit: Apple Inc.
Call Forwarding and Dual SIM
iPhone users with Dual SIM or eSIM setups should pay attention to which line is being forwarded. A personal line and business line can have separate carrier settings. Forwarding one does not automatically forward the other.
To check lines:
Settings > Cellular >Select the line you want to manage
Then return to:
Settings > Apps > Phone > Call Forwarding
The available settings may vary by carrier and line. If one line supports call forwarding and the other does not, that is usually a carrier difference, not an iPhone problem.
Dual SIM users should also test both numbers separately. Call the personal number, then call the business number, and confirm each behaves as expected.
When Call Forwarding Is Useful
Call forwarding works best when the goal is temporary coverage. It is useful during travel, device repairs, vacations, business handoffs, office moves, event coverage or times when another person needs to answer calls.
It can also help people who use a landline or desk phone during work hours. Calls can be forwarded from the iPhone to the office line, then turned off at the end of the day. The reverse can also work if the carrier supports it.
For small businesses, call forwarding can help avoid missed calls without adding a full phone system. A company can route calls to whoever is available. For individuals, it can be a quick fix when an iPhone battery is failing, a device is being repaired, or cellular reception is better on another phone.
The feature is less ideal as a permanent business phone solution. If multiple people need to answer calls, if calls need menus, if calls need recordings, or if voicemail needs to stay organized, a dedicated phone service may be better.
Privacy and Cost Considerations
Call forwarding may create charges depending on the carrier, plan and destination number. Forwarding calls to an international number can be expensive. Forwarding to another domestic mobile number is usually simpler, but users should still check the plan.
Privacy also deserves attention. Once calls are forwarded, the person or device receiving them may hear personal, business or sensitive conversations meant for the original number. Do not forward calls to a shared phone unless that is intentional.
Before forwarding a work line to a personal number, check company policy. Some organizations do not allow business calls to be routed to unmanaged personal devices.
Image Credit: Freepik
How to Troubleshoot Call Forwarding
If call forwarding does not work, start with the basics. Confirm the iPhone has cellular service. Restart the device. Check that the forwarding number is entered correctly. Turn call forwarding off, wait a few seconds, then turn it on again.
Then test from another phone. A test call is the fastest way to know whether the carrier accepted the setting.
If calls still do not forward, check whether the carrier supports call forwarding through iPhone settings. Some carriers require account-level activation, carrier codes or a business calling feature. If the iPhone setting is missing or stuck, carrier support is usually the right next step.
Also check Focus modes and blocked numbers if the issue is not forwarding but missed calls. A call may fail to ring because of Focus, Silence Unknown Callers, a blocked contact, poor signal or voicemail settings rather than call forwarding.
A Simple Feature Worth Testing
Call forwarding on iPhone is easy to use when the carrier supports it. Open iPhone settings, turn on Call Forwarding, enter the destination number and test it. Turn it off when the temporary need is over.
The feature is most useful when it is deliberate and short-term. It can keep calls moving during travel, repairs, work coverage or busy periods, but it should be checked carefully because voicemail, costs and privacy can change once calls are routed to another number.
The iPhone makes the setting simple. The carrier decides how far that simplicity goes.
Cadmium (Cd) contamination is a growing threat to food safety, and rice is one of the most vulnerable crops. Because rice plants can accumulate cadmium from contaminated soils more readily than many other staples, Cd can become a major dietary exposure route for large parts of the world’s population. Yet attempts to lower cadmium often create trade-offs—reducing uptake of essential nutrients or weakening plant performance.
A new study from Okayama University, Japan, and collaborating researchers in China reports a precision-editing strategy designed to avoid those trade-offs. The team focused on the rice metal transporter gene OsNramp5, which is known to move metals such as manganese and cadmium, and used base-editing to search for a beneficial point mutation within the gene rather than disabling it.
Using adenine and cytosine base editors, the researchers generated more than 1,600 genome-edited rice lines and screened them for reduced cadmium accumulation. Their saturation mutagenesis approach targeted OsNramp5 to identify variants that kept normal plant physiology while limiting Cd buildup in grain.
The key breakthrough was the I441T substitution: changing isoleucine to threonine at amino acid position 441. This single change reduced cadmium levels in both shoots and brown rice without altering gene expression, protein abundance, or the subcellular localization of the transporter.
Importantly, the mutation did not come at the cost of micronutrients. Field trials on cadmium-contaminated soil showed a 48% decrease in cadmium concentration in brown rice, from 0.14 mg/kg in wild type to 0.07 mg/kg in the edited plants, while iron, manganese, and zinc levels remained essentially unchanged.
The researchers then explored the mechanism behind the selective effect. Although OsNramp5 transports multiple metals, the I441T mutation shifted its selectivity—enhancing zinc transport preference. Increased zinc accumulation in root cells promoted competitive inhibition against cadmium during root-to-shoot movement.
Instead of completely blocking cadmium uptake, the edited transporter selectively limited cadmium translocation, reducing grain contamination while preserving essential mineral delivery. The team supported these conclusions with physiological assessments, gene and protein analyses, yeast transport assays, and agronomic evaluation.
Overall, the work demonstrates how precision genome editing can address a long-standing breeding challenge: lowering toxic metal accumulation without disrupting nutrient homeostasis. The researchers propose that the OsNramp5I441T allele could accelerate development of safer rice varieties for mildly contaminated regions.
Subject of Research: Not applicable Article Title: Genome-edited rice variety with low-cadmium accumulation in the grain News Publication Date: 18-Jun-2026 Web References: http://dx.doi.org/10.1073/pnas.2610609123 References: DOI: 10.1073/pnas.2610609123 (Proceedings of the National Academy of Sciences) Image Credits: Credit: Professor Jian Feng Ma from Okayama University, Japan
Keywords: cadmium, rice, OsNramp5, base editing, genome editing, metal transporters, food safety, micronutrients, zinc competition, plant breeding
I’m sick of “opt-out” toggles for automatically enabled generative AI features. It’s past time to make “opt in” the default setting for sensitive features.
I’m sick of “opt-out” toggles for automatically enabled generative AI features. It’s past time to make “opt in” the default setting for sensitive features.
No, there weren't "2,700 heatwave deaths due to climate change", says Ben Pile – a figure conjured by Met Office and Imperial College modelling. But nobody must be allowed to remember the warm days of 2026 fondly.
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