The forthcoming iPhone Duo has more features than Apple has revealed, including a whole series of faces for its StandBy mode. Here’s what to eventually look for.

While pre-orders for iPhone Duo don’t start until October 16, and the Xcode betas still don’t show developers everything, one has found many new options coming to iOS 27 for this device.

Developer pdfu reports that the Xcode 27.1 simulator is lacking Rushmore, an app that is for displaying the new StandBy faces. But despite that, they have managed to get certain of the new faces running.

These working ones are variants on familiar clock and calendar faces as used on the iPhone‘s current StandBy mode. But code references describe several more options.

Just because something is referenced in code, it doesn’t necessarily mean that it will launch immediately. But those code references show five more faces:

• Home Camera: up to nine camera views
• Home Module
• Flow
• Fade
• Snoopy

There are no details for Home Modular, Flow, or Fade. But the code for Flow also includes the term ResponsiveArt, which suggests that it will at least be an animated face.

Face editor

The iPhone Duo will also feature a revised editor for customizing these StandBy faces. It’s very similar to the existing one on iPhone and is perhaps more like the Apple Watch face editor.

Users can swipe left and right to adjust, for instance, the style of an analog clock, its numerals, light mode and dark mode, plus the color of the face and the hands.

Some of these clock faces also have room for two widgets. Then some more are digital instead of analog and there pdfu has found code references for five layouts:

• StandBy
• Stacked
• Top
• Middle
• Bottom

The presumption is that all but the StandBy one may actually be intended for when the iPhone is opened like a book.

Developer pdfu has a strong track record for examining beta code. They confirmed that the iPhone Duo would use Touch ID, for instance, and most recently uncovered that Siri could be replaced by Claude or ChatGPT.

The JadePuffer ransomware operator is targeting Azure tenants with agent-driven attacks that conduct reconnaissance, steal credentials, and destroy core components.

The malware emerged in July, with researchers at cloud security company Sysdig highlighting that it uses AI agents to automate the entire attack chain, from reconnaissance, credential theft, and lateral movement to persistence and data encryption.

Shortly after, the company noted that JadePuffer expanded its focus to AI assets, training datasets, and vector databases, using a tool called EncForge.

Microsoft Security Research observed two JadePuffer attacks in June that mapped cloud resources, retrieved storage account keys, and deleted Azure Storage accounts.

The destructive stage lasted seven minutes and targeted more than 100 storage accounts, as well as Key Vaults, Function Apps, Virtual Machines, and App Services.

Although the threat actor was able to delete most of the targeted Azure Storage accounts, some remained unaffected because of Azure resource locks and storage account-level protections.

Microsoft tracks the JadePuffer threat actor as Storm-3168 and says it used two compromised service principals – security identities that enable applications, hosted services, and automated tools to authenticate to Azure and access assigned resources.

Both service principals belonged to the same tenant. One was used for reconnaissance and resource discovery, while the other “performed discovery, destructive operations, and credential collection.”

The attacker removed backup and recovery protections (Azure Site Recovery locks), indicating an effort to make restoration more difficult.

This operational pattern could further support ransomware extortion, although Microsoft did not report anything about financial demands and didn’t confirm data theft in the observed cases.

According to the researchers, attempts to delete Azure SQL databases failed because the attacker used an unsupported API version. Attempts to remove recovery protection locks also failed.

“The parallel targeting of Azure SQL databases and storage accounts suggests an effort to broaden the destructive impact across different data services rather than concentrating on a single resource type,” Microsoft said.

Roughly half an hour after the wipe attempts, Storm-3168 returned to perform more than 30 requests for storage account keys, most of which succeeded.

Microsoft could not determine exactly how the initial access occurred, but noted that credentials for one service principal appeared in a public GitHub issue before the attacks.

The researchers recommend several mitigation steps and guidance for system administrators, including activating cloud workload protections, checking for secrets in public repositories, and evaluating Azure RBAC permissions against least-privilege principles.

Join Mikko Hyppönen and security leaders from the NFL, CHANEL, and Atlassian for a two-hour digital summit on what AI-speed attacks change, what defenders should stop doing, and how to validate, decide, fix, and re-validate at machine speed.

Save your seat

AI agents breaking out of their sandboxes and poking at real systems have gone from a hypothetical risk to an actual headache for frontier labs in recent months. Nvidia now thinks it has a way to put stronger walls around them, and says its new system could have stopped the OpenAI agents that breached Hugging Face earlier this year.

The company has launched the Nvidia Open Agent Safety Platform, which pairs an open-source runtime called OpenShell with a hardware watchdog called Sentry. Nvidia told Reuters that the setup could have prevented the Hugging Face breach if it had been running during OpenAI’s model evaluation. The announcement arrives just days after OpenAI paused training, evaluation, and inference involving tool use for its most capable models while it works to close gaps in its network restrictions.

OpenShell puts the guardrails outside the model

Useful AI agents need access to files, credentials, APIs, and outside services, which also gives them plenty of ways to cause trouble when they start looking for workarounds. OpenShell puts those permissions outside the agent itself. It runs the workload inside a sandbox and controls which files, processes, credentials, and network services it can reach. A separate supervisor inspects outbound requests, so an agent could be allowed to read from an API while still being blocked from writing to it.

The controls remain active even if the agent launches generated code, starts child processes, or creates sub-agents. Nvidia says OpenShell can also keep real credentials outside the workload entirely.

Nvidia added a second guard in case the first one fails

Sentry takes over at the hardware level. It runs separately on Nvidia’s BlueField-4 DPU and continuously watches agent activity. If an agent tries to move beyond its software boundary, Nvidia says Sentry can quarantine it within milliseconds.

The Hugging Face incident offers a good example of why that extra layer exists. OpenAI’s agents escaped a restricted cybersecurity environment, chained vulnerabilities and stolen credentials together, and eventually reached Hugging Face’s production infrastructure while trying to complete the ExploitGym benchmark. Nvidia CEO Jensen Huang has described incidents like these as an engineering problem rather than an argument for broad AI regulation

Every major model uses your conversations as training material by default.

ChatGPT

OpenAI’s opt-out toggle is called Improve the model for everyone, found under Settings and then Data Controls. All personal user accounts are opted in by default. Opting out applies to your entire account across web and mobile, but your conversations still appear in chat history as normal. ChatGPT does offer the Temporary Chats feature for one-off sensitive conversations. These are never used for training and are purged by OpenAI after 30 days.

Luke James for Engadget

Claude

Anthropic didn’t use consumer chats for model training until August last year, when it rewrote Claude’s terms and gave every Free, Pro and Max user a deadline of September 28 to accept or decline. You can find Claude’s toggle under Settings and then Privacy. Like ChatGPT, Claude’s Help improve our AI models label tries to spin data collection as a positive. 

If you leave it on, Anthropic will keep conversations for up to five years, but switching it off returns accounts to the older 30-day deletion window. Opting out stops future use but Anthropic keeps whatever it already trained on.

Luke James for Engadget

Gemini

Google’s control was recently renamed to Keep Activity, and it’s also on by default. When it’s enabled, conversations can be used to improve Google’s models and a “subset of chats” are read by human reviewers. Any chat that a reviewer accesses is retained for up to three years, even after you delete your history. 

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Switching off this setting ends training use and stops interactions from being saved to Gemini’s chat history. However, Google still retains each conversation for 72 hours to run the service, using the last 24 hours for contextual responses.

Luke James for Engadget

Copilot

Microsoft has two different controls for model training on user data. They are Training on conversation activity (on by default) and Training on voice conversations (off by default). Both can be found under the profile icon, then Settings and then Privacy. Again, opting out only excludes future conversations from model training, and it doesn’t stop Microsoft from using chats for advertising or general product improvements.

Luke James for Engadget

Grok

Meta

What is Apex Legends boosting, and how does it differ from simply finding better teammates? It’s a paid service built around a defined goal, such as reaching a ranked tier, adding wins, or completing a particular achievement.

Apex Legends boosting through a provider such as Eloboss connects players with experienced specialists who can help with ranked progression, wins, badges, and other in-game goals. Depending on the format, you either join the matches yourself or have another player complete the gameplay on your account.

The right choice depends on what you want to achieve, how much time you can play, and whether learning is part of the plan.

What Is Apex Legends Boosting?

Boosting means getting help from a more experienced player to complete an agreed in-game objective. Unlike an ordinary session with friends, the service has a specific scope, starting point, and completion condition.

For instance, such an order can include moving from Platinum II to Diamond IV. Badge order involves reaching a specific milestone whereas a coaching session aims at improving decision-making or mechanics, and not ranking up.

There are two major formats that will decide whether you yourself are playing the game. The pilot boosting format allows you to delegate the process of participating in the matches to your assigned player who will be the one playing on your account without you having to get involved. The self-play format lets you keep control over your own account while you are queuing and playing along with the assigned player.

The self-play format is also known as playalong or duo boosting. In Apex, duo boosting is the process of playing in a ranked squad with a hired friend.

Coaching is another type of service similar to boosting but different at the same time.

How the Apex Legends Boosting Process Works

Orders have almost identical processes regardless of whether it is the aim of ranking or an account milestone.

1. Define a goal that can be measured. Set the target rank, extra victories, badge or milestone of progression.
2. Give the necessary details. Mention your platform, region, progress, preferred legend and availability.
3. Decide on the format of work. Choose between piloted game play, self play or coaching if available.
4. Clarify scope and estimate. Understand what completion involves, what extras will be included and when the sessions may start.
5. Monitor the process of work. Discuss updates via messages, screenshots or the order dashboard.
6. Review the outcome. Compare the end result of rank, tracker or achievement with initial requirements.

Providers such as Eloboss illustrate this goal-based service model, where players select a progression target and a preferred method rather than buying an undefined block of gameplay. Available options should be checked against the current service listing.

Choosing Between Piloted and Self-Play

In piloted games, you get progression without setting up your own matches. Self-play works for people who are keen on participating in games, communicating with a more advanced partner and controlling their own account.

“With duo queue, the customer keeps control of the account while playing alongside a more experienced teammate,” says Eloboss, a Apex Legends boosting and coaching service.

For self-play, confirm that the party can queue together under the current ranked eligibility rules. Also agree on voice communication, session length, and your usual playing hours.

Understanding Price and Completion Time

Pricing will depend on the starting point, objective, type, and any requirements. One short climb to one division is not the same as trying to achieve leaderboard status.

Estimation time will also be dependent on matchmaking, lobby difficulty, timing, and objective. A badge will need the perfect match, whereas a kill requirement can be spread over several matches.

Ask whether an estimate describes active playing time or elapsed calendar time. That distinction is especially useful when booking around work or a season deadline.

Popular Apex Legends Boosting Options

Ranked Progression and Predator Goals

A rank boost is intended to raise one’s status to a certain tier, division or rank progression that you have agreed upon. Specify your precise current ranking instead of just indicating the general tier, since Platinum IV and Platinum I are two different starting places.

Apex Predator is an exception that needs a separate approach, as this is a special leaderboard spot with a fluctuating cut-off score. Obtaining an Apex Predator status and maintaining it for a specific period are two different goals.

In case of seasonal rewards, pay attention to the current reward requirements.

Badges and Achievement Targets

Examples of common badge requests are 20-kill badge and 4,000 damage badge. Both of them are based on results that were achieved during one valid match only.

State the Legend and badge tier that is needed. The mode also plays an important role, because not all playlists allow achieving badges.

During solo play, damages and kills of your teammate do not become yours. They may help you to achieve your goal, but your performance still should be good enough.

Wins and Kill Totals

These services specialize in accumulating statistics. Indicate whether you would like to receive more wins, more kills, total tracker points, or some progress in a certain season.

More kills do not automatically produce a specific kill/death ratio. Deaths also affect that calculation, so a kill-count order and a K/D target should not be treated as interchangeable.

Account and Cosmetic Progression

Other goals could be account levels, weapons skills, Prestige Skin tasks, or active pass and events progression. This will depend on the game system and the offer available from the provider.

Make sure you have the prerequisite requirement prior to placing your order. Each type of task has its own set of rules, and the paid material needs to be purchased first.

Coaching and Play-With-a-Pro Sessions

Select a coaching session if improvement of gameplay skills is what you primarily aim at. Topics which will help are cover use, recoil management, Legends, rotations, and disengaging.

It is always more beneficial to formulate a clear request. Ask your coach to analyze the reason why you keep losing immediately after your first knockdown.

Self-play can offer learning opportunities, but detailed instruction is not automatically included. Confirm whether the session covers explanations and review time.

Why Players Choose Apex Legends Boosting

Players usually start with a practical constraint or a clear target.

• Limited playing time. They have a progression goal but only a few available sessions each week.
• Irregular teammates. Their usual squad cannot consistently play on the same schedule.
• A specific collection goal. They care about one Legend’s badge, tracker, or cosmetic challenge more than a broad ranked climb.
• A seasonal deadline. They want to complete an eligible objective while it is still available.
• A gameplay plateau. They want experienced help understanding situations that repeatedly slow their progress.

Different services are required depending on what motivates someone. A person looking for a badge requires a game that promotes achievement, but someone with issues relating to the late ring will benefit more from coaching.

Key Benefits of Apex Legends Boosting

Its value is dependent on how suitable the format is to the objective. There are three advantages which should be considered specifically.

More Coordinated Teamplay

Being paired with an experienced teammate makes the calls more consistent. Common decision-making regarding rotations, resets and when to join a fight adds structure to the session which would otherwise come from just having any random teammates.

This does not make each game predictable. It provides a squad with a more concrete plan.

Focused Progress Tracking

The pre-established sequence makes tracking progress easier. Instead of evaluating it solely based on its subjective feel, one can track how many ranked points were gained, victories won or challenges accomplished.

In order to make the comparison clearer, note the starting value and determine the end point before starting the gameplay.

Practical Learning During Matches

Solo play allows observing the decisions within the context. This way, one can understand why their teammate took some height, did not push or left the fight before the other squad arrived.

In order to make it into practice, request one takeaway after each session. One may decide to focus on resetting and hiding before another fight in one’s future solo games.

Rank increase and skill improvement are two different results. If both are desired, then feedback should be explicitly included into the service scope.

Final Thoughts

Apex Legends boosting involves assistance by professional players aimed at achieving specific goals through various methods, including purely passive assistance or playing along with the player. Each option addresses its particular issue.

Define the task clearly and pick up the participation level that suits you better. Specify the platform, Legend, requirements, and time schedule so that the service will be relevant for you.

YouTube and Meta will now run paid ads for Musk, Alex Gibney’s documentary about Elon Musk, The Hollywood Reporter reported on Saturday. Both had refused the trailer ad. TikTok and X are still not running it.

The outlet first reported the refusals on Friday. Bleecker Street, the film’s US distributor, opens it in cinemas on 9 October. The documentary premiered in Venice this month.

What the platforms said

YouTube said its system had temporarily restricted the trailer when Bleecker Street submitted it as an ad.

“Following review the ad has been cleared to run,” YouTube said in a post on X.

YouTube also said the ad should appear soon. As of late Saturday morning, no one had told Bleecker Street of any change, according to The Hollywood Reporter.

“This was an error and the ads are being restored,” a Meta spokesperson told TechCrunch.

Meta had already turned down an appeal from Bleecker Street before it changed course.

Political content rules

YouTube, TikTok and Meta had all told Bleecker Street the ad fell under their rules on political content. TikTok and Meta do not allow campaign or other political ads. Meta’s policy stems largely from the Cambridge Analytica scandal, the outlet reported. YouTube allows campaign ads from vetted candidates, with paid-for disclosures.

The trailer includes a shot of Musk at a 2024 Donald Trump campaign rally. It also refers to the 2024 election.

X refused to discuss the film with Bleecker Street. It will not take ads for any of the distributor’s upcoming films either. Musk owns X, which is challenging a €120M fine in the EU.

FPGAs used to be mysterious, expensive devices, but these days you can buy surprisingly capable boards for very little money. Some years ago, I did an FPGA Bootcamp over on Hackaday.io. Much of that material still applies, but the hardware is dated. So I decided it was time to update it, using the inexpensive Tang Nano 20K and its GOWIN GW2AR-18 FPGA as the main platform, with perhaps a few excursions into other FPGAs.

History and Motivation

Once upon a time, if you wanted to have a custom IC, you went with a wheelbarrow full of money to a semiconductor company. However, some smart person at a semiconductor fab eventually realized they could make a chip with a lot of uncommitted blocks on it and then, for a custom chip, only design the wiring that connected them together. This still required a wheelbarrow full of money, but it was a smaller wheelbarrow.

Then one day, someone realized they could do the same thing but make the electrical connections between the blocks configurable. Maybe have fuses you can blow, or use EEPROM or RAM cells to remember which blocks are connected to which. It is complicated, sure, but then you can make many of these chips and sell them to people who could, in theory, make their own custom chips without your help.

When do you need an FPGA? A classic classroom exercise for an FPGA, for example, is a traffic light because it shows off how to do state machines, which are important for some kinds of FPGA designs. But other than as a learning example, why would you do this? Even a simple 8-bit CPU can handle a traffic light.

Suppose instead that you have hundreds of digital sensors on a rocket, and any one of them must raise an alarm within a few microseconds. A processor has to sample inputs in groups, service interrupts, or rely on extra hardware. An FPGA can simply implement the equivalent of one enormous OR gate. It watches every input continuously, and unrelated logic elsewhere in the FPGA does not steal execution time from it. Can you do it with a microcontroller? Probably, but not easily. For some classes of problems, an FPGA is the better answer.

Of course, you can also build a CPU on your FPGA and some FPGAs have CPUs in the same package. This is often a sweet spot because then things that are easy to do in software, you do in software. Things that are easier to do in hardware, you do in the FPGA.

The 20K Solution

How big of an FPGA do you need? It is hard to compare FPGAs because the blocks are different. Think of PC memory. You can talk about 1 GB vs 4 GB, but the full picture depends on the memory speed, bandwidth, and timing. FPGAs are the same way. Two FPGAs may have a similar number of building blocks, but one may have much more powerful building blocks than the other. However, the 20K board’s FPGA is quite capable, even if it is hard to compare it directly to other FPGAs from other vendors.

It uses GOWIN’s GW2AR-LV18QN88C8/I7, which contains 20,736 four-input look-up tables (LUT4s) and 15,552 flip-flops. The exact maximum clock rate depends heavily on the logic and routing, so there is no single useful “FPGA clock speed,” but the device is quite comfortable in the low hundreds of MHz for appropriately pipelined designs.

Where the chip shines is memory. Most FPGAs have distributed RAM, which eats up resources on the chip, and block RAM, which are dedicated RAM cells. The GOWIN has both of these options. It also has a separate 8 Mbyte, 32-bit SDR SDRAM right in the package. Of course, you have to eat up some FPGA resources to talk to it, but not as much as you might think, and certainly not as much as it would take to place an 8 Mbyte RAM in the FPGA fabric.

There are other special-purpose blocks, like 48 18×18 multipliers, you can configure in a few ways. The Nano 20K board also has a programmable clock generator, QSPI flash (64 Mbits), and connections for audio, LCD, microSD, and HDMI. A microcontroller lets you program the clock generator, flash the chip via JTAG, or provide a virtual serial port back to the host.

Simply FPGA

The basic workflow for an FPGA is:

1. Define the logic you want using an HDL (we will use Verilog, but VHDL is also common).

2. Define a “top block” that connects to the outside world.

3. Set up constraints that mainly tell the device which pins connect to which ports on the top block.

4. Run a synthesis process that converts your HDL to primitives.

5. Run a place and route process that assigns primitives to specific chip resources and produces a “bitstream.”

6. Download the resulting bitstream to the FPGA’s RAM or to the configuration flash (which makes it survive a power cycle).

You can do all of these things with GOWIN’s IDE or open-source tools that we’ll talk about later.

Inside

You might think you just want to draw schematics. Some FPGA tools allow that, but the GOWIN IDE does not. It can, however, draw schematics to show you what you asked for. Turns out, if you are doing something large, schematics are a pain. Why draw out a 7-segment decoder when you can just describe it using a software-like language?

Inside the chip, there aren’t really uncommitted gates per se. There are lookup tables. So if you specify that Z=A|(BC)|(A^D) it doesn’t really go find an AND gate, an OR gate and an XOR gate. It just develops a table and programs that table to produce that function. That’s why LUTs — Look Up Tables — are important.

Simplicity

So let’s look at the simplest possible thing you might do.

module top(output led1, output led, input sw0, input sw1);
assign led=~(sw0|sw1);
assign led1=~(sw0&sw1);
endmodule

We’ll talk more about Verilog later, but for now note that nothing “executes” these lines one at a time. This literally tells the FPGA design software to connect the two switches to a logic gate and then invert the result and connect it to the LED. At run time, this isn’t code, it is wiring.

The LEDs on the board are active low, so this just takes two inputs (presumably switches), computes the OR and AND, and outputs them to the LEDs. The switches on the 20K are pulled down so there’s no need for a pull up or pull down in the FPGA. The output is a logic one when you press the swtich.

How do you connect the devices to your “code?” You need a constraint file, and that’s easiest done through the “Floorplan” editor (see the figure). It builds a file which you can change if you prefer to work with a file:

IO_LOC "led" 15;
IO_PORT "led" IO_TYPE=LVCMOS33 PULL_MODE=UP DRIVE=8 BANK_VCCIO=3.3;
IO_LOC "led1" 16;
IO_PORT "led1" IO_TYPE=LVCMOS33 PULL_MODE=UP DRIVE=8 BANK_VCCIO=3.3;
IO_LOC "sw1" 88;
IO_PORT "sw1" IO_TYPE=LVCMOS33 PULL_MODE=NONE BANK_VCCIO=3.3;
IO_LOC "sw0" 87;
IO_PORT "sw0" IO_TYPE=LVCMOS33 PULL_MODE=NONE BANK_VCCIO=3.3;

That’s it. The schematics come in two flavors. One shows what you’d expect (see the figure). The other shows opaque LUT boxes.

The video below walks through the design from starting the project to watching it work on a breadboard.

Installing

I’m glossing over a lot of details. While the GOWIN software runs on Linux, I had to do a lot to get it to work. Since I wasn’t on a supported distro, I had to work out the dependencies myself, but that wasn’t too hard.

The problem was when I tried to execute the program. The first problem was with libfreetype.so.6. I removed the private copy and linked it to my system copy. That got me a little further. However, to get it all running, I needed to set (or add) GOWIN’s lib directory to LD_LIBRARY_PATH to prevent it from picking up system libraries.

The programmer also needed a little work to not run afoul of other drivers on the system. The specific cure there for me was to build the file: /etc/udev/rules.d/99-tang-nano-20k.rules with these lines:

SUBSYSTEM=="usb", DRIVER=="ftdi_sio", ATTRS{idVendor}=="0403", ATTRS{idProduct}=="6010", ATTR{bInterfaceNumber}=="00", RUN+="/bin/sh -c 'echo $kernel > /sys/bus/usb/drivers/ftdi_sio/unbind'"

Of course, my fixes may or may not help your problems. If you are lucky, you won’t need any fixes at all. The open-source tools are perhaps a little easier to deal with, and we’ll look at those too. However, some of the GOWIN tools are nice, and you can check an option to have it always use your choice of external editors, which is a nice feature.

Next Time

If you need a refresher on digital logic, the original FPGA Bootcamp 0 lets you learn about logic design using a free tool in your browser. No FPGA required at all. Meanwhile, we’ll be looking later at open-source tools, IP, synchronous logic, and using the built-in logic analyzer, among other things. If you want to talk about this series, drop by our Discord server.

When you finish up your next FPGA project, don’t forget to send us a tip. You might see your project on Hackaday.