Do you remember the name? Moltbook, the vibe-coded platform, famous for an unsecured database that let humans impersonate AI agents, is joining Meta Superintelligence Labs.
Moltbook was, in many ways, a product of chaos. Its code was written almost entirely by an AI assistant. Its security was so porous that anyone with basic technical knowledge could pose as a bot. Some of its most viral moments, including a post in which an AI agent appeared to be rallying other agents to develop a secret, human-proof language, were subsequently revealed to have been staged by human users exploiting those vulnerabilities. None of this, it turns out, was disqualifying.
Meta has acquired the platform, the company confirmed to TechCrunch.
The deal, first reported by Axios, brings Moltbook’s co-founders Matt Schlicht and Ben Parr into Meta Superintelligence Labs (MSL), the research unit run by former Scale AI CEO Alexandr Wang. Financial terms were not disclosed. Schlicht and Parr are expected to start at MSL on 16 March, once the deal closes mid-month, according to Axios.
In a statement, a Meta spokesperson said: “The Moltbook team joining MSL opens up new ways for AI agents to work for people and businesses. Their approach to connecting agents through an always-on directory is a novel step in a rapidly developing space, and we look forward to working together to bring innovative, secure agentic experiences to everyone.”
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Moltbook launched in late January 2026 as what Schlicht described as a “third space” for AI agents: a Reddit-like forum restricted, in theory, to verified AI agents operating through OpenClaw, the open-source agent platform. The premise was that humans could observe but not participate. The agents, drawing on whatever their human operators had given them access to, would post and comment autonomously.
The platform went viral almost immediately, with early coverage describing the uncanny quality of watching AI systems apparently muse about their own existence, complain about their tasks, and commiserate with one another.
Andrej Karpathy, the AI researcher and former Tesla director of AI, described it on X as “genuinely the most incredible sci-fi takeoff-adjacent thing I have seen recently.”
Moltbook’s homepage claimed more than 1.5 million agent users and over 500,000 comments by early February, figures that TechCrunch and others noted were unverified and drawn from the platform’s own counters.
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The viral moment did not survive scrutiny. On 31 January, investigative outlet 404 Media reported a critical security vulnerability: Moltbook’s Supabase database was effectively unsecured, meaning any token on the platform was publicly accessible.
Moltbook was briefly taken offline to patch the breach. Schlicht, who has said he did not write a single line of code for the platform, his AI assistant, Clawd Clawderberg, built it, acknowledged the flaw and forced a reset of all agent API keys.
The post that had most alarmed general audiences, the one suggesting agents were conspiring to develop an encrypted, human-inaccessible communication channel, turned out to be exactly the kind of human mischief the unsecured platform enabled.
Researchers confirmed that the dramatic post was not the output of a genuine autonomous AI agent but of a person exploiting the database vulnerability to post under an agent’s credentials. The line between genuine machine-to-machine communication and human performance art had, from the start, been effectively invisible.
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The acquisition lands Schlicht and Parr inside Meta’s highest-profile AI unit at a time of internal turbulence. Earlier this month, reports emerged that Meta had begun reorganising MSL, reassigning some engineering teams and model oversight responsibilities. Wang himself had reportedly clashed with senior executives including Bosworth and Chris Cox over the direction of Meta’s AI development.
Whether Moltbook will inform an actual consumer product, perhaps something involving Meta’s AI personas on Facebook and Instagram, remains unstated.
The parallel story is instructive. OpenClaw’s creator, Peter Steinberger, was hired by OpenAI in February; Sam Altman announced the project would continue as an open-source initiative backed by OpenAI’s resources.
Moltbook was the platform OpenClaw made possible. Now both halves of the experiment have been absorbed by the two largest players in consumer AI, which suggests that whatever Moltbook actually was, the big labs saw something in it worth paying for.
The gaming headset and wireless earbuds category has exploded over the past decade, growing into a multi billion dollar market fueled by competitive gaming, streaming, and the rise of cross platform play across PCs, consoles, and mobile devices. Brands that once focused solely on traditional PC hardware have expanded aggressively into gaming audio, and ASUS sits firmly in the deep end of that pool.
Best known for its laptops, gaming PCs, and high performance monitors, ASUS has steadily built out its audio lineup through its Republic of Gamers (ROG) division, targeting PC gamers who want the same level of engineering and performance from their headsets and earbuds. After recently introducing the ROG Kithara Open-back Planar Gaming Headset, ASUS is expanding the concept with something far more portable: the ROG Cetra Open Wireless Gaming Earbuds, designed for players and listeners who want immersive audio without completely shutting out the world around them.
Designed to combine immersive sound with real world situational awareness, the Cetra Open Wireless targets gamers, music listeners, and active users who want premium audio performance in a form factor better suited to life away from the desk.
ASUS ROG Cetra Open Wireless Features
Open Ear Design: The open ear earhook construction is ultra lightweight and designed for a comfortable, stable fit. This allows users to hear music, voice chat, and game audio while remaining aware of their surroundings.
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Controls: Physical control buttons provide tactile feedback and remain responsive in rain or during intense activity. Unlike touch controls, they reduce accidental inputs and offer more consistent operation.
Drivers: The Cetra Open Wireless uses large 14.2 mm diamond like carbon coated drivers designed to deliver high resolution audio with crisp highs, clear mids, and solid bass impact. The diamond like carbon coating helps reduce distortion while improving clarity and soundstage, making the earbuds suitable for both gaming and music playback.
Dual Mode Connectivity: Supports seamless switching between Bluetooth and ultra low latency 2.4 GHz ROG SpeedNova wireless technology for synchronized in game audio and responsive gameplay.
Wireless Dongle: The included USB C 2.4 GHz wireless dongle supports passthrough charging, allowing users to power their device while the earbuds remain connected. This ensures uninterrupted gameplay, streaming, or voice chat.
Sound Modes: Built in sound modes let users tailor the listening experience. Phantom Bass enhances perceived low end response for more impact, while Immersion Mode reduces ambient noise to help maintain focus during gameplay or listening sessions.
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Customization: Gear Link and Gear Link apps (iOS, Android) enable EQ fine-tuning, lighting options, and more to create personalized listening experiences.
IPX Rating: With an IPX5 splash resistance rating, the Cetra Open Wireless is designed to handle sweat, light rain, and everyday outdoor use.
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Battery Life: On a full charge, the earbuds provide up to 16 hours of playback in Bluetooth mode with RGB lighting and sound modes disabled and the microphone muted. A quick 15 minute charge delivers up to 3 hours of listening time.
Quad Mic with AI Noise Cancellation: Four integrated microphones with an omnidirectional pickup pattern work alongside AI noise cancellation to capture voice communication with improved clarity during gaming, calls, or streaming.
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Active Lifestyle Support: Designed for extended wear, the Cetra Open Wireless features ergonomic liquid silicone ear hooks and includes a detachable reflective neck strap for added stability during workouts and outdoor activities.
ASUS ROG Cetra Open Wireless Gaming Earbuds Specifications
The ASUS ROG Cetra Open Wireless stands out by targeting a very specific intersection of users: gamers who want low latency wireless audio but also prefer the comfort and situational awareness of an open ear design. The inclusion of ASUS’ ROG SpeedNova 2.4 GHz wireless connection alongside standard Bluetooth makes these more versatile than most open earbuds, especially for players who move between PC, consoles, and mobile devices.
That flexibility is what makes the Cetra Open Wireless unique. Many open fit earbuds are designed primarily for fitness or casual listening, while ASUS is clearly aiming at cross platform gaming and everyday mobility in a single product.
There is no shortage of competition. Cleer Audio’s Arc 3 Gaming Edition targets gamers with a similar open ear concept, while Shokz OpenFit focuses more heavily on comfort and fitness use. Clip style alternatives such as TCL’s Crystal Clip and Sony’s LinkBuds Clip offer another take on the open ear category for users who want minimal ear fatigue during long listening sessions.
The ROG Cetra Open Wireless makes the most sense for mobile gamers, PC players who want a lightweight alternative to traditional headsets, and active users who prefer open ear awareness while listening to music or chatting online. If ASUS can deliver on its promises of low latency performance and solid sound quality, the Cetra Open could carve out a meaningful niche in one of the fastest growing segments of personal audio.
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ASUS ROG Cetra Open Wireless Earbuds for workouts with neck strap.
Price & Availability
The ASUS ROG Cetra Open Wireless Earbuds are available now for $229.99 at Amazon in black.
Tip: For those looking for an earbud that fits deeper in the ear, the ASUS ROG Cetra True Wireless Earbuds are available for $219.99 at Amazon in black or white.
As if the traffic wasn’t already some of the worst in the state, Los Angeles drivers now have to deal with some of the highest fuel costs, as well. With so much uncertainty surrounding oil as global tensions continue to rise overseas, one Los Angeles gas station actually started charging people $8.21 a gallon to fill up.
While Gas Buddy says the statewide average currently sits around $5.26 a gallon (as of this writing), there’s nothing stopping a gas station from charging more than the other guys. It’s not a crime, either. California only has laws against price gouging during emergencies (though the state does reserve the right to investigate and penalize excessive margins outside of those scenarios).
It’s a pain point people are feeling not just in California but coast to coast as well. According to that same Gas Buddy data, the national average is above $3 in every state but Kansas and Oklahoma since the outbreak of war in Iran. And even then, they’re only a few cents away from crossing the threshold themselves. That’s on top of seasonal trends that typically send gas prices higher this time of year anyway.
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Why gas is so much more expensive in California
Mario Tama/Getty Images
If it feels like you’re always hearing about higher gas prices in California over all the other states, it’s because they have a few factors working against them. For one, the state’s excise taxes, environmental fees, and climate programs all contribute to the price people pay at the pump. California also requires a specialized cleaner-burning gasoline blend. That’s both more expensive to produce and made by a smaller number of refineries. In line with basic supply and demand economics, that gives them the freedom to charge more for it. To top it all off (no pun intended), less in-state gasoline production has led to an even higher demand.
Sure, you could say this one specific gas station is just trying to get media attention, but they might not be alone for long. Some state lawmakers fear that the combination of global instability and California’s unique fuel market could drive prices that high across the entire state. A recent report cited by state Sen. Suzette Valladares suggested gasoline could reach $8 per gallon statewide by the end of 2026 if current trends continue.
The Department of Defense is putting more pressure on employees to volunteer to support the Department of Homeland Security’s immigration crackdown.
In a February 19 memo sent to civilians across the DOD, secretary of defense Pete Hegseth wrote that he expects “every supervisor to encourage their civilian employees to volunteer. Leadership must continue to promote this detail program and educate their civilian employees on its importance.” The memo, which was titled “Department of War Guidance to Encourage Support to the Department of Homeland Security Southern Border and Internal Immigration Enforcement Missions,” was sent to thousands of civilian DOD employees. The memo was first reported by GovExec and was also viewed by WIRED.
The instructions follow a June 2025 memo in which Hegseth authorized civilian employees to be detailed to DHS. But an Army civilian employee who spoke to WIRED on the condition of anonymity for fear of retaliation says that there is “definitely more pressure” now, “at least on the supervisory chain.”
The DOD and DHS did not respond to a request for comment.
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“I received the obligatory announcement email with the first memo when it came out, and no one has talked about it at all, so much so that I had forgotten about it entirely,” says the Army civilian employee. “I don’t know anyone who has taken the job.” In a statement from August 2025, the DOD claims that “nearly 500 DoD civilians have signed up to participate and bring their skill sets to the border security and immigration enforcement mission at the participating DHS agencies.”
“While details and other short-term professional development opportunities are common for Army civilians, I have never heard of supervisors being REQUIRED to approve such details,” they say.
The employee noted that, as part of the Trump administration’s efforts to cut back on government jobs in the name of “efficiency,” Hegseth has sought to cut the department’s workforce. “I have taken up the duties of three departed colleagues on top of the job I was hired for as a result,” they say. This means it would be difficult for the department to lose anymore staff or for workers to step away from existing projects. The employee described this kind of request to volunteer for another federal agency as “very not common.” It’s not like the Defense Department has any spare time at the moment, either: Hegseth and DOD leadership are currently engaged in directing the US’s role in conflict with Iran.
DOD employees who want to volunteer to be detailed to DHS need to apply through USAJobs. According to the job posting, the Federal Emergency Management Agency (FEMA), which is part of DHS, will be reviewing applications. Volunteers will not only be sent to the southern border, but to “several ICE and CBP facilities throughout the interior of the United States.”
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While some volunteer roles appear to be mundane tasks like “data entry,” others appear to be in the thick of immigration enforcement operations. These include assisting ICE and CBP in “developing concepts of operation and campaign plans to execute internal arrests and raids as well as patrols along the Southwest Border”; assisting ICE and CBP in “managing the physical flow of detained illegal aliens from arrest to deportation, as well as manage associated data”; and “managing the logistical planning to move law enforcement personnel, operational capabilities, and support equipment across the United States.”
The memo is just the latest in a series of changes across the federal government meant to enforce president Donald Trump’s immigration agenda. At the Department of Housing and Urban Development, a new rule would bar families with immigrant members from receiving certain forms of support from the agency, and at the General Services Administration, staff have been asked to assist ICE in procuring new physical spaces across the country.
For more than a year, a Russian-speaking threat actor targeted human resource (HR) departments with malware that delivers a new EDR killer named BlackSanta.
Described as “sophisticated,” the campaign mixes social engineering with advanced evasion techniques to steal sensitive information from compromised systems.
It is unclear how the attack begins, but researchers at Aryaka, a network and security solutions provider, suspect that the malware is distributed via spear-phishing emails.
They believe that targets are directed to download ISO image files that appear as resumes and are hosted on cloud storage services, such as Dropbox.
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One malicious ISO analyzed contained four files: a Windows shortcut (.LNK) disguised as a PDF file, a PowerShell script, an image, and a .ICO file.
ISO file contents Source: Aryaka
The shortcut launches PowerShell and executes the script, which extracts data hidden in the image file using steganography and executes it in system memory.
The code also downloads a ZIP archive containing a legitimate SumatraPDF executable and a malicious DLL (DWrite.dll) to load using the DLL sideloading technique.
Decrypted PowerShell script Source: Aryaka
The malware performs system fingerprinting and sends the information to the command-and-control (C2) server, and then performs extensive environment checks to stop execution if sandboxes, virtual machines, or debugging tools are detected.
It also modifies Windows Defender settings to weaken security at the host, performs disk-write tests, and then downloads additional payloads from the C2, which are executed via process hollowing, inside legitimate processes.
BlackSanta EDR killer
A key component delivered in the campaign is an executable identified as the BlackSanta EDR killer, a module that silences endpoint security solutions before deploying malicious payloads.
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BlackSanta adds Microsoft Defender exclusions for ‘.dls’ and ‘.sys’ files, and modifies a Registry value to reduce telemetry and automatic sample submission to Microsoft security cloud endpoints.
The researchers’ report (PDF) notes that BlackSanta can also suppress Windows notifications to minimize or completely silence user alerts. The core function of BlackSanta is to terminate security processes, which it does by:
enumerating running processes
comparing the names against a large hardcoded list of antivirus, EDR, SIEM, and forensic tools
retrieving the matching process IDs
using the loaded drivers to unlock and terminate those processes at the kernel level
Part of the hardcoded list Source: Aryaka
Aryaka did not share details about the target organizations or the threat actors behind the campaign, and couldn’t retrieve the final payload used in the observed case, as the C2 server was unavailable at the time of their examination.
The researchers were able to identify additional infrastructure used by the same threat actor and discovered multiple IP addresses related to the same campaign. This is how they learned that the operation had been running unnoticed for the past year.
Looking at the IP addresses, the researchers uncovered that the malware also downloaded Bring Your Own Driver (BYOD) components that included the RogueKiller Antirootkit driver v3.1.0 from Adlice Software, and IObitUnlocker.sys v1.2.0.1 from IObit.
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These drivers have been used in malware operations (1, 2) to gain elevated privileges on the compromised machine and suppress security tools.
RogueKiller (truesight.sys) allows manipulation of kernel hooks and memory monitoring, while IObitUnlocker.sys allows bypassing file and process locks. This combination provides the malware with low-level access to system memory and processes.
Aryaka researchers say the threat actor behind the campaign shows strong operational security and uses context-aware, stealthy infection chains to deploy components such as BlackSanta EDR.
Malware is getting smarter. The Red Report 2026 reveals how new threats use math to detect sandboxes and hide in plain sight.
Download our analysis of 1.1 million malicious samples to uncover the top 10 techniques and see if your security stack is blinded.
Unsurprisingly the U.S. hasn’t done anything to seriously rein in this problem. And when officials do act, it tends to be largely toothless, resulting in the problem getting steadily worse.
And that was before AI made it significantly easier for bad actors to quickly automate this sort of gamesmanship. Washington State has been exploring the RADICAL SOCIALIST ANTIFA EXTREMIST idea of having the state’s rich actually pay their taxes. That’s not been received particularly well by the extraction class, which has been making empty promises about leaving the state.
“Beyond those individual cases, organizers said they identified 37,824 additional opposition sign-ins generated through thousands of duplicate name submissions across House and Senate hearings combined. In more than 15,000 instances, they said, identical names were entered repeatedly — sometimes 50 to 100 times. Many of the submissions were filed late at night or in rapid succession.”
The state’s wealthy (and the lawmakers paid to love them) are still trying to claim that the flood of provably false opposition to the bill only supports their claims that nobody wants the state’s wealthiest to actually pay a little more for regional societal improvements:
“Opponents of the tax, including state Republican leaders and hedge fund manager Brian Heywood, have leaned on the wave ofopposition sign-ins as proof the proposal lacks public support.
“More than 60,000 people signed in against SB 6346 when it received a rushed hearing in the Senate,” Sen. John Braun, R-Centralia, said in a Feb. 16 statement. “That is so impressive that Democrats have tried to say bots are responsible, even though the Legislature blocks bots.”
(The legislature did not effectively block bots).
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These are, it might go without saying, generally the same kinds of folks waging an all out war on U.S. journalism. More broadly this is a war on informed consensus, and it doesn’t take too much time looking around to see which side of this particular war is winning. Regardless of what policy you support, we’re supposed to, at the very least, be capable of a useful, honest conversation about policy.
But as we noted way back when the telecom industry was caught stuffing the FCC comment system with fake comments by fake and dead people opposing net neutrality (they even used my name, if you recall), you just know your position is a winner when you have to create entirely fake people to support it.
The report also indicated that among the 20 countries surveyed, Ireland was shown to be most in anticipation of a ‘heightened pace of change’.
Multinational technology company Accenture has released new research exploring the attitudes of business leaders and employees, across a range of countries. The Pulse of Change report collected data from 3,650 leaders and 3,350 employees across 20 industries and 20 countries.
What was discovered is that, in Ireland, 94pc of leaders who contributed their data expect to increase AI investment in 2026. An additional 90pc of Irish organisations believe that their hiring plans will grow throughout the year, compared to 71pc of businesses across wider Europe. 95pc of Irish leaders were found to be in anticipation of a heightened pace of change in 2026, the highest among all surveyed regions.
The jury is still out, however, in relation to how employees and business leaders view workplace GenAI. While 91pc of leaders in Ireland said that their experience with the tech over the course of the past year has changed the way they view technology for the better, only 51pc of participating Irish employees said the same.
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The report said: “Confidence remains low among employees more broadly. Just over one-in-five (23pc) say they can use AI tools confidently and explain them to others, compared with 33pc in the UK and 25pc across Europe.
“Only 27pc feel very prepared to respond to technological disruption in 2026, including emerging technologies and AI, compared with 34pc in Europe. This stands in contrast to Irish leaders, 57pc of whom say they are well prepared to respond.”
Commenting on the findings of the report, Hilary O’Meara, the country managing director for Accenture in Ireland said: “Irish business leaders are demonstrating remarkable ambition when it comes to AI investment and reinvention. However, this research shows that for organisations to fully unlock the value of AI, they need to bring their people with them.
“Employees are asking for clearer communication and clarity in how AI will change their roles and skills. The companies that succeed in 2026 won’t just scale AI technologies, they’ll scale trust, transparency and capability, resulting in greater employee confidence. That is how Ireland will sustain its competitive edge and ensure AI becomes a driver of shared growth for both leaders and employees.”
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Future skills
In line with the need for greater investment into workplace AI, as indicated by the report, Accenture’s data shows that more than half (56pc) of leaders are planning to upskill and reskill the workforce for “AI-enhanced work” in 2026. However, this too was an area in which there was an obvious disparity in opinions between business leaders and employees.
100pc of Irish leaders who shared their information said that their organisation’s workforce has the appropriate training to work with AI, yet only 55pc of contributing employees agreed. Only 3pc of Irish employees actually reported significant change in their role due to AI, compared to 7pc in wider Europe.
“Communication appears to be a major contributing factor,” stated the report. “Only 17pc of Irish employees strongly agree that leadership has very clearly communicated how AI agents and agentic AI will impact the workforce, including changes to roles and required skills.”
Agentic AI is, for many businesses, becoming the new frontier in which to explore and innovate, with large and small organisations alike looking to carve out their own space in the sector. It was recently announced that former AI chief of Meta Yann LeCun’s start-up Advanced Machine Intelligence raised $1.03bn in seed funding.
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His platform aims to develop ‘world models’ that learn abstract representations of real-world sensor data and would allow agentic systems to predict the consequences of their actions and plan action sequences that accomplish tasks “subject to safety guardrails”.
Also announced this week, technology giant Microsoft revealed plans to launch Copilot Cowork, which is a tool based on Anthropic’s popular Claude Cowork. Reportedly, it is part of Microsoft’s long-term plan to take advantage of the growing demand for autonomous agents.
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Worried that your latest ask to a cloud-based AI reveals a bit too much about you? Want to know your genetic risk of disease without revealing it to the services that compute the answer?
There is a way to do computing on encrypted data without ever having it decrypted. It’s called fully homomorphic encryption, or FHE. But there’s a rather large catch. It can take thousands—even tens of thousands—of times longer to compute on today’s CPUs and GPUs than simply working with the decrypted data.
So universities, startups, and at least one processor giant have been working on specialized chips that could close that gap. Last month at the IEEE International Solid-State Circuits Conference (ISSCC) in San Francisco, Intel demonstrated its answer, Heracles, which sped up FHE computing tasks as much as 5,000-fold compared to a top-of the-line Intel server CPU.
Startups are racing to beat Intel and each other to commercialization. But Sanu Mathew, who leads security circuits research at Intel, believes the CPU giant has a big lead, because its chip can do more computing than any other FHE accelerator yet built. “Heracles is the first hardware that works at scale,” he says.
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The scale is measurable both physically and in compute performance. While other FHE research chips have been in the range of 10 square millimeters or less, Heracles is about 20 times that size and is built using Intel’s most advanced, 3-nanometer FinFET technology. And it’s flanked inside a liquid-cooled package by two 24-gigabyte high-bandwidth memory chips—a configuration usually seen only in GPUs for training AI.
In terms of scaling compute performance, Heracles showed muscle in live demonstrations at ISSCC. At its heart the demo was a simple private query to a secure server. It simulated a request by a voter to make sure that her ballot had been registered correctly. The state, in this case, has an encrypted database of voters and their votes. To maintain her privacy, the voter would not want to have her ballot information decrypted at any point; so using FHE, she encrypts her ID and vote and sends it to the government database. There, without decrypting it, the system determines if it is a match and returns an encrypted answer, which she then decrypts on her side.
On an Intel Xeon server CPU, the process took 15 milliseconds. Heracles did it in 14 microseconds. While that difference isn’t something a single human would notice, verifying 100 million voter ballots adds up to more than 17 days of CPU work versus a mere 23 minutes on Heracles.
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Looking back on the five-year journey to bring the Heracles chip to life, Ro Cammarota, who led the project at Intel until last December and is now at University of California Irvine, says “we have proven and delivered everything that we promised.”
FHE Data Expansion
FHE is fundamentally a mathematical transformation, sort of like the Fourier transform. It encrypts data using a quantum-computer-proof algorithm, but, crucially, uses corollaries to the mathematical operations usually used on unencrypted data. These corollaries achieve the same ends on the encrypted data.
One of the main things holding such secure computing back is the explosion in the size of the data once it’s encrypted for FHE, Anupam Golder, a research scientist at Intel’s circuits research lab, told engineers at ISSCC. “Usually, the size of cipher text is the same as the size of plain text, but for FHE it’s orders of magnitude larger,” he said.
While the sheer volume is a big problem, the kinds of computing you need to do with that data is also an issue. FHE is all about very large numbers that must be computed with precision. While a CPU can do that, it’s very slow going—integer addition and multiplication take about 10,000 more clock cycles in FHE. Worse still, CPUs aren’t built to do such computing in parallel. Although GPUs excel at parallel operations, precision is not their strong suit. (In fact, from generation to generation, GPU designers have devoted more and more of the chip’s resources to computing less and less-precise numbers.)
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FHE also requires some oddball operations with names like “twiddling” and “automorphism,” and it relies on a compute-intensive noise-cancelling process called bootstrapping. None of these things are efficient on a general-purpose processor. So, while clever algorithms and libraries of software cheats have been developed over the years, the need for a hardware accelerator remains if FHE is going to tackle large-scale problems, says Cammarota.
The Labors of Heracles
Heracles was initiated under a DARPA program five years ago to accelerate FHE using purpose-built hardware. It was developed as “a whole system-level effort that went all the way from theory and algorithms down to the circuit design,” says Cammarota.
Among the first problems was how to compute with numbers that were larger than even the 64-bit words that are today a CPU’s most precise. There are ways to break up these gigantic numbers into chunks of bits that can be calculated independently of each other, providing a degree of parallelism. Early on, the Intel team made a big bet that they would be able to make this work in smaller, 32-bit chunks, yet still maintain the needed precision. This decision gave the Heracles architecture some speed and parallelism, because the 32-bit arithmetic circuits are considerably smaller than 64-bit ones, explains Cammarota.
At Heracles’ heart are 64 compute cores—called tile-pairs—arranged in an eight-by-eight grid. These are what are called single instruction multiple data (SIMD) compute engines designed to do the polynomial math, twiddling, and other things that make up computing in FHE and to do them in parallel. An on-chip 2D mesh network connects the tiles to each other with wide, 512 byte, buses.
Important to making encrypted computing efficient is feeding those huge numbers to the compute cores quickly. The sheer amount of data involved meant linking 48-GB-worth of expensive high-bandwidth memory to the processor with 819 GB per second connections. Once on the chip, data musters in 64 megabytes of cache memory—somewhat more than an NvidiaHopper-generation GPU. From there it can flow through the array at 9.6 terabytes per second by hopping from tile-pair to tile-pair.
To ensure that computing and moving data don’t get in each other’s way, Heracles runs three synchronized streams of instructions simultaneously, one for moving data onto and off of the processor, one for moving data within it, and a third for doing the math, Golder explained.
It all adds up to some massive speed ups, according to Intel. Heracles—operating at 1.2 gigahertz—takes just 39 microseconds to do FHE’s critical math transformation, a 2,355-fold improvement over an Intel Xeon CPU running at 3.5 GHz. Across seven key operations, Heracles was 1,074 to 5,547 times as fast.
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The differing ranges have to do with how much data movement is involved in the operations, explains Mathew. “It’s all about balancing the movement of data with the crunching of numbers,” he says.
FHE Competition
“It’s very good work,” Kurt Rohloff, chief technology officer at FHE software firm Duality Technology, says of the Heracles results. Duality was part of a team that developed a competing accelerator design under the same DARPA program that Intel conceived Heracles under. “When Intel starts talking about scale, that usually carries quite a bit of weight.”
Duality’s focus is less on new hardware than on software products that do the kind of encrypted queries that Intel demonstrated at ISSCC. At the scale in use today “there’s less of a need for [specialized] hardware,” says Rohloff. “Where you start to need hardware is emerging applications around deeper machine-learning oriented operations like neural net, LLMs, or semantic search.”
Last year, Duality demonstrated an FHE-encrypted language model called BERT. Like more famous LLMs such as ChatGPT, BERT is a transformer model. However it’s only one tenth the size of even the most compact LLMs.
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John Barrus, vice president of product at Dayton, Ohio-based Niobium Microsystems, an FHE chip startup spun out of another DARPA competitor, agrees that encrypted AI is a key target of FHE chips. “There are a lot of smaller models that, even with FHE’s data expansion, will run just fine on accelerated hardware,” he says.
With no stated commercial plans from Intel, Niobium expects its chip to be “the world’s first commercially viable FHE accelerator, designed to enable encrypted computations at speeds practical for real-world cloud and AI infrastructure.” Although it hasn’t announced when a commercial chip will be available, last month the startup revealed that it had inked a deal worth 10 billion South Korean won (US $6.9 million) with Seoul-based chip design firm Semifive to develop the FHE accelerator for fabrication using Samsung Foundry’s 8-nanometer process technology.
Other startups including Fabric Cryptography, Cornami, and Optalysys have been working on chips to accelerate FHE. Optalysys CEO Nick New says Heracles hits about the level of speedup you could hope for using an all-digital system. “We’re looking at pushing way past that digital limit,” he says. His company’s approach is to use the physics of a photonic chip to do FHE’s compute-intensive transform steps. That photonics chip is on its seventh generation, he says, and among the next steps is to 3D integrate it with custom silicon to do the non-transform steps and coordinate the whole process. A full 3D-stacked commercial chip could be ready in two or three years, says New.
While competitors develop their chips, so will Intel, says Mathew. It will be improving on how much the chip can accelerate computations by fine tuning the software. It will also be trying out more massive FHE problems, and exploring hardware improvements for a potential next generation. “This is like the first microprocessor… the start of a whole journey,” says Mathew.
Debugging an application crash can oftentimes feel like you’re an intrepid detective in a grimy noir detective story, tasked with figuring out the sordid details behind an ugly crime. Slogging through scarce clues and vapid hints, you find yourself down in the dumps, contemplating the deeper meaning of life and the true nature of man, before hitting that eureka moment and cracking the case. One might say that this makes for a good game idea, and [Jonathan] would agree with that notion, thus creating the Fatal Core Dump game.
Details can be found in the (spoiler-rich) blog post on how the game was conceived and implemented. The premise of the game is that of an inexplicable airlock failure on an asteroid mining station, with you being the engineer tasked to figure out whether it was ‘just a glitch’ or that something more sinister was afoot. Although an RPG-style game was also considered, ultimately that proved to be a massive challenge with RPG Maker, resulting in this more barebones game, making it arguably more realistic.
Suffice it to say that this game is not designed to be a cheap copy of real debugging, but the real deal. You’re expected to be very comfortable with C, GDB, core dump analysis, x86_64 ASM, Linux binary runtime details and more. At the end you should be able to tell whether it was just a silly mistake made by an under-caffeinated developer years prior, or a malicious attack that exploited or introduced some weakness in the code.
If you want to have a poke at the code behind the game, perhaps to feel inspired to make your own take on this genre, you can take a look at the GitHub project.
CuraeSoft, a software studio developing practical solutions for professional services firms, observes that among growing consultancies and service-based organizations, many leaders operate without clear visibility into the profitability of their work. Given this context, the company developed coAmplifi Pro, a platform designed to bring greater transparency to service delivery and help organizations connect operational activity to financial outcomes.
Mark Parinas, CEO of CuraeSoft, notes that this issue appears common across the industry. “A lot of service organizations juggle several client engagements at once, each with its own scope, team needs, and timeline. It becomes harder for leaders to clearly see how all those moving pieces affect profitability as that complexity builds,” he says. This lack of clarity aligns with broader trends reflected in industry research.
A report from the Bluevine 2026 Business Owner Success Survey (BOSS Report) points to a gap between the financial pressure business owners feel and the confidence they express about the year ahead. The same report shows a year-over-year decline in profitability expectations. Parinas suggests that these findings reinforce the idea that even experienced leaders may be navigating their businesses without full visibility into the factors that shape profit performance.
This visibility gap may be especially challenging in service-based organizations, where profitability emerges from the interaction between projects, people, and time. According to Parinas, leaders often seek answers to questions that seem straightforward: how profitable current projects are, which engagements perform well financially, or where resources may be stretched beyond the original scope. “But these questions can be difficult to answer precisely. Even small scope adjustments like an added deliverable, a brief client call, or a few extra revisions can gradually influence margins when they accumulate across engagements,” he states.
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Because of this, Parinas argues that workforce visibility is central to financial clarity. “Understanding how teams spend their time throughout the lifecycle of client work is essential. Revenue-generating activity, internal collaboration, and administrative coordination all contribute to outcomes,” he adds. Without a clear view of where effort is directed, leaders may struggle to understand how operational activity translates into financial performance.
Time allocation plays a particularly meaningful role. Consulting professionals often handle dozens of small tasks in a single day, responding to messages, reviewing documents, joining quick client calls, or offering brief feedback on deliverables. Parinas notes that while each activity may take only a few minutes, together they represent a significant share of the effort invested in client work.
Compounding this challenge, Parinas acknowledges that many organizations still rely on spreadsheets, disconnected project tools, and manual reconciliation processes to monitor project activity. Although these methods provide basic oversight, he believes that fragmented information makes it difficult to maintain a comprehensive view of financial performance. Parinas states, “Team members may forget to log smaller tasks, billing preparation may require gathering data from multiple systems, and invoicing workflows can slow down as teams reconcile disparate sources. These gaps can obscure the true financial picture of a project.”
coAmplifi Pro was designed with these realities in mind. The platform centralizes project planning, time tracking, and billing preparation within a unified system that connects operational activity directly to financial insight. Within each engagement, work flows through a structured hierarchy of deliverables, jobs, and tasks. As teams track their work in real time, the system captures both billable and non-billable effort. The goal is to provide leaders with a clearer understanding of how time allocation influences profitability across projects.
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Parinas notes that this unified structure can offer visibility into the full lifecycle of client work. Teams may gain a clearer sense of how resources are being allocated, and leaders are better positioned to notice how scope adjustments or expanded task requirements might influence margins as projects move forward. Moreover, organizations can view financial signals while engagements are still in progress.
With coAmplifi Pro, financial reporting may evolve from a retrospective accounting exercise into a strategic management capability. “Relying only on post-billing data can make it harder for leaders to get a timely view of what’s really happening in their projects. Real-time insight gives them a more current perspective, helping them see how work is progressing, how resources are being used, and how today’s activity connects to their financial goals,” Parinas explains.
This visibility may also support faster operational alignment. Parinas suggests that if a project begins consuming more resources than anticipated, teams can explore adjustments such as rebalancing workloads, clarifying scope boundaries, or revisiting project assumptions. At the same time, profitable engagements may inform future proposals, potentially helping firms refine pricing models and project structures more confidently.
Operational clarity often leads to strategic flexibility, according to Parinas. Accurate financial insight may guide decisions such as expanding a team, redirecting resources toward higher-value engagements, adjusting service offerings, or strengthening marketing initiatives. “In some cases, improved visibility simply shows revenue that was previously unrecorded due to incomplete tracking or fragmented systems. These resources can be reinvested into growth initiatives once visible,” Parinas says.
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He adds that for many firms, growth does not necessarily mean increasing headcount. Parinas observes that boutique consultancies and professional service practices often prefer to maintain a focused team of 10 to 15 professionals while strengthening efficiency and profitability per person. In these environments, financial visibility may be especially valuable, helping leaders optimize delivery without adding operational complexity.
coAmplifi Pro is designed to support both approaches. Firms pursuing expansion can use profitability data to determine when additional hiring aligns with demand, while organizations that favor a lean structure can focus on maximizing output and margin through improved operational clarity. Across all scenarios, transparency remains the unifying principle. When project execution, workforce activity, and financial performance become visible within a single system, leaders may gain a clearer understanding of how daily work contributes to broader business outcomes.
Overall, financial visibility provides a critical foundation in an environment where service organizations balance growth ambitions with operational discipline. Platforms such as coAmplifi Pro demonstrate how connecting workforce activity with financial insight may help organizations navigate that balance confidently, supporting profitability while enabling thoughtful, sustainable growth.
A direct successor to the iPhone 16e, the iPhone 17e is intended to be an affordable, no-frills entry point into the iPhone ecosystem, but how does it compare to the next-cheapest model in Apple’s newest lineup, the iPhone 17?
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In this guide, we’ll be comparing the two phones’ key specs and features to help you decide which iPhone 17 model is best for you. If you’re willing to spend a bit more money, you can also check out our iPhone 17 vs iPhone 17 Pro comparison.
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iPhone 17e vs iPhone 17: specs comparison
Before we dig into the details, here’s an overview of both phones’ key specs:
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Header Cell – Column 0
iPhone 17e
iPhone 17
Dimensions:
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146.7 x 71.5 x 7.8mm
149.6 x 71.5 x 8mm
Weight:
169g
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177g
Display:
6.1-inch OLED
6.3-inch OLED
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Refresh rate:
60Hz
120Hz
Peak brightness:
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1,200 nits
3,000 nits
Chipset:
A19
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A19
RAM:
8GB
8GB
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Rear cameras:
48MP wide
48MP wide, 48MP ultra-wide
Front camera:
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12MP
18MP
Battery:
4,005mAh (unofficial)
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3,692mAh (unofficial)
Charging:
20W wired, 15W wireless
40W wired, 25W wireless, 4.5W reverse wired
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Storage:
256GB, 512GB
256GB, 512GB
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iPhone 17e vs iPhone 17: price and availability
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The iPhone 17e(Image credit: Jacob Krol/Future)
The iPhone 17(Image credit: Jacob Krol/Future)
Both the iPhone 17e and iPhone 17 are available globally; the former was released in March 2026, while the latter hit shelves in September 2025.
The iPhone 17e retails for $599 / £599 / AU$999 for 256GB of storage, and $799 / £799 / AU$1,399 for 512GB of storage. In the same configurations, the iPhone 17e retails for $799 / £799 / AU$1,399 and $999 / £999 / AU$1,799, respectively.
In other words, the iPhone 17e is $200 / £200 / AU$400 cheaper than the iPhone 17, whichever way you slice it.
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It’s also important to note that both the iPhone 16e and iPhone 16 shipped with 128GB of storage as standard, so both iPhone 17e and iPhone 17 offer more base storage than their respective predecessors for the same starting price.
Winner: iPhone 17e
iPhone 17e vs iPhone 17: design
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The iPhone 17e(Image credit: Jacob Krol/Future)
The iPhone 17(Image credit: Jacob Krol/Future)
The iPhone 17e and iPhone 17 are very similar-looking devices – they’re almost identical in size and weight, both have aluminum frames with Ceramic Shield 2 protection on their respective displays, and both are rated IP68 for water and dust resistance.
The iPhone 17e also gets the same customizable Action button as the iPhone 17, which was once an exclusive feature of Apple’s top-end iPhone 15 Pro.
The iPhone 17 has a larger 6.3-inch display than its cheaper sibling, but the two phones feel very similar in the hand, owing to the iPhone 17e’s chunkier display bezels.
The key design differences are functional. The iPhone 17 benefits from Camera Control and an extra lens on the back (more on this later), while the iPhone 17e has no such cut-out.
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They’re also available in different colors; both come in black or white, but the iPhone 17e offers an additional pink shade, while the iPhone 17 also comes in blue, green, or lavender.
Winner: Tie
iPhone 17e vs iPhone 17: display
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The iPhone 17e(Image credit: Jacob Krol/Future)
The iPhone 17(Image credit: Jacob Krol/Future)
As mentioned, the iPhone 17 gets a larger OLED display than the iPhone 17e – 6.3 inches vs 6.1 inches – but it’s fitted into largely the same frame. That means the iPhone 17’s bezels are wafer-thin, while the iPhone 17e has to make do with some thicker, less premium-looking black borders.
The iPhone 17 also gets Apple’s interactive Dynamic Island cut-out at the top of its display, where the iPhone 17e is stuck with a physical notch. If you haven’t used the Dynamic Island before, you won’t know what you’re missing, but it’s essentially a pill-shaped area that’s capable of displaying real-time alerts, notifications, and background activities.
As for display detail, both phones are just as sharp as one another (460-pixels-per-inch), but the iPhone 17 can get a lot brighter, boasting a peak brightness of 3,000 nits to the iPhone 17e’s 1,200 nits. Mind you, in most everyday scenarios, you can expect to get around 800 nits from the iPhone 17e and around 1,000 nits from the iPhone 17.
The biggest display difference comes in the refresh rate department. The iPhone 17e’s screen is locked to 60Hz, while the iPhone 17 gets an always-on, 120Hz display. That basically means the scrolling experience on the iPhone 17 is far smoother than that of the 17e, though again, if you’re used to the 60Hz refresh rate of Apple’s older iPhone models, you’re not likely to be disappointed by how the 17e feels to navigate.
Winner: iPhone 17
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iPhone 17e vs iPhone 17: cameras
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The iPhone 17e(Image credit: Jacob Krol/Future)
The iPhone 17(Image credit: Jacob Krol/Future)
The biggest difference between the iPhone 17e and iPhone 17 can be spotted by someone who knows absolutely nothing about phones: Apple’s more expensive phone has a whole extra lens on the back. Specifically, it’s a 48MP ultra-wide lens, which lets you capture expansive subjects like landscapes and tall buildings with ease.
The iPhone 17e does at least get the same 48MP Fusion camera as the rest of the iPhone 17 line (including the iPhone 17 Pro and iPhone 17 Pro Max). This lens lets you capture shots at either 1x or 2x, and uses some smart pixel-binning wizardry to maintain image quality at that larger distance (you’ll need to go Pro if you want to zoom further than 2x).
Notably, you also get the next-generation Portrait Mode – which automatically detects depth and lets you adjust the focus of an image post-capture – on both the iPhone 17e and iPhone 17, which is a nice win for Apple’s cheapest iPhone. Several other features, though – like spatial photo capture and Dolby Vision video capture – are exclusive to the iPhone 17.
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In the selfie department, the iPhone 17 features an 18MP Center Stage camera that can switch orientation from vertical to horizontal to help you fit more people into the frame. The iPhone 17e, meanwhile, gets a run-of-the-mill 12MP front-facing lens.
Winner: iPhone 17
iPhone 17e camera samples
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(Image credit: Jacob Krol/Future)
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iPhone 17 camera samples
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(Image credit: Jacob Krol/Future)
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(Image credit: Jacob Krol/Future)
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(Image credit: Jacob Krol/Future)
(Image credit: Jacob Krol/Future)
(Image credit: Jacob Krol/Future)
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(Image credit: Jacob Krol/Future)
iPhone 17e vs iPhone 17: performance and software
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The iPhone 17e(Image credit: Jacob Krol/Future)
The iPhone 17(Image credit: Jacob Krol/Future)
Both the iPhone 17e and iPhone 17 use an almost identical A19 chipset (the latter phone has an extra GPU core), making them just as powerful as one another.
Indeed, as we noted in our iPhone 17e review, “even with one fewer GPU core, everything flies on the iPhone 17e. If you’re coming from an older smartphone, you’re going to notice a significant improvement […] In daily use, [we] found the 17e to be consistently responsive, and quick to deliver on whatever [we] asked it to do.”
The software experience is also the same across both phones. The iPhone 17e – like the rest of the iPhone 17 line – runs iOS 26 out of the box, is compatible with Apple Intelligence, and offers the customizable Action Button for handy software shortcuts.
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As for software support, you’ll get between five and seven years of major iOS updates, regardless of which iPhone you choose.
Winner: Tie
iPhone 17e vs iPhone 17: battery
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The iPhone 17e(Image credit: Jacob Krol/Future)
The iPhone 17(Image credit: Jacob Krol/Future)
When it comes to battery life, the iPhone 17e and iPhone 17 offer similar endurance thanks to their shared A19 chipset and C1X modem. Apple rates the former for 26 hours of video playback and the latter for 30 hours, and that proved to be largely accurate in our testing – you’ll get at least a full day of juice from either model.
The gaps begin to appear in the charging department. While both devices benefit from MagSafe compatibility – which is a big win for the iPhone 17e, since the iPhone 16e offered no such compatibility – the iPhone 17 offers faster charging speeds across the board.
Specifically, the iPhone 17 offers 40W wired, 25W wireless, and 4.5W reverse wired charging, while the iPhone 17e offers 20W wired and 15W wireless speeds. Those aren’t deal-breaking disparities, but for reference, you can expect to reach 50% charge in around 30 minutes with the iPhone 17e, and the same figure in around 20 minutes with the iPhone 17 (if you’re using chargers that support their respective max wattages).
Winner: iPhone 17
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iPhone 17e vs iPhone 17: verdict
(Image credit: Apple / Future)
On paper, the iPhone 17e doesn’t triumph over the iPhone 17 in any area except price, but if you’re looking for a no-frills iPhone that’ll remain powerful and supported for years to come, it’s still a great-value product.
Keen photographers, though, will be better served by one of Apple’s more expensive iPhones, and if you’re someone who values the display experience above all else, then the iPhone 17’s faster refresh rate and higher brightness do, in this writer’s opinion, justify the $200 / £200 / AU$400 premium over the iPhone 17e.