As someone who, last time I checked, doesn’t have any glimmer of hope of using Siri AI on iOS in the EU, I found this announcement vaguely insulting and highly disingenuous, but that’s Apple for you when it comes to addressing developers these days…
Nov 3rd 2026 · 2 min read
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#ai #apple #fedora #hardware #linux #macbook #silverblue
With the benefit of hindsight, I can now finally come to terms with why this particular hardware revision is much maligned in general, and revisiting it was an interesting experience because:
I had forgotten how bad the keyboard is
The Touch Bar is worse than useless in general, and causes a number of issues in Linux
It can’t use modern 5GHz Wi-Fi (well, it can, but this setup doesn’t support WPA3, and probably never will)
The battery is somewhat shot
It warms up considerably at the slightest provocation
It does, however, have an absolutely beautiful 2560x1600 panel that reminds me of the Lenovo Chromebook I had to send back (still sad about that), and four USB-C ports so it’s trivial to keep topped up enough to use as a thin client:
MacBook Pro running Fedora Silverblue, with the GNOME About panel and Touch Bar visible
The first step is, as you’d expect, to just plug in a USB drive and boot from it. Fedora’s hardware support is, as usual, stellar (power management, backlight, touchpad, etc., all worked out of the box) and I was immediately productive on it by dint of installing pi, asking it to map Esc to Caps Lock, and get the rest of the hardware to work while I just spun up Firefox, logged onto my Obsidian server and kept writing.
The result is a sort of overpowered Chromebook (it has 16GB RAM and entirely too much storage, and even if it has a relatively paltry two cores and four threads, it’s still an i5), and were it not for the pretty hefty weight when compared to more modern machines, I would call it a very satisfactory conversion.
The entire process took something like eight hours altogether (loosely spread over a couple of days), and I’m pretty sure you can get it down to under 4 hours if you slave away at it as a meat proxy to the AI–I just kept doing other stuff and occasionally rebooted for it to test the fixes.
What pi ended up doing was:
Building akmod packages for both the Touch Bar and audio initialization
Debugging microphone and camera inputs
Tracking down and fixing incorrect NVRAM settings that prevented the Wi-Fi from working in 5GHz
Taking several stabs at getting full suspend/resume to work while ensuring all the weird hardware recovered correctly (this is what took the longest, by far)
As you’d expect, I got it to publish all the notes, steps and packages on GitHub, so this should be easily reproducible if you have an identical machine (which, mind you, you might not–there are several subtle variations of this).
Since I forgot to turn on LUKS disk encryption in the first install and I want to move to Fedora 45 (which is launching this week), I will eventually have to do the whole thing again–this time likely going straight to my Niri desktop setup rather than staying in GNOME. However, given the number of changes expected in Fedora 45, I will let that settle first.
All in all, reasonably smooth sailing, although power management and sleep/resume have been a major pain, since it also had to patch and tweak the Touch Bar and audio drivers to come back on when picking up the machine.
There are a couple of things that still don’t really work, but they’re fairly minor considering this is probably going to live out its days as a couch machine:
External displays (might have to do with the old Intel chipset–some monitors are detected but nothing renders)
There’s an annoying phantom tap thing in the trackpad driver, so for the moment I am back to press to click, which is slightly maddening
I like our new AI overlords, especially considering I can use them to breathe new life into this kind of otherwise useless hardware. I might even look into replacing the battery on this one as well…
Nov 2nd 2026 · 1 min read
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#firmware #music #polyend #synthesizers #tracker
Although I never had the good fortune to test one of Polyend’s products (not for lack of wanting), I can’t help but applaud this–the popularity of the FM-1 and its openness is certainly having an impact, and Polyend is unusually well positioned to make a similar move.
The firmware release covers the original Tracker as well as the Tracker+ and Mini, and the original even gets SD card sample streaming. There are SDKs for Sample Editor effects and, on the newer models, synth engines–which gives people a way to add their own sounds and tools to hardware they already own. A documented recovery procedure should also make experimenting with firmware a little less nerve-racking.
There is a licensing catch: the firmware is source-available, under PolyForm Noncommercial with explicit permission to make commercial music, and some synth and DSP libraries are still proprietary binaries. The effects SDK is MIT-licensed, though, so people can sell their own plugins. I’d have preferred fewer restrictions, but giving owners the code and tools to keep improving their instruments is very welcome.
Oct 31st 2026 · 2 min read
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#3d-printing #ai #hardware #linux #music #notes #weekly
Have I ever mentioned how much I hate daylight savings and the utter stupidity of disrupting my (already poorly attuned) circadian rhythms for a completely arbitrary change that makes mornings only slightly more bearable and evenings a dark pit of mild despair?
Well, I guess I just have. It might have also been the tipping point for my feeling slightly feverish and achy towards the end of the working week, which certainly did not help my overall mood or productivity.
The week did have an auspicious start, since spurred by tinkering with the FM-1 I decided to get some music/audio hacking in. I’ve been toying with the idea of turning my Norns into a Microcosm effects pedal for almost a year now, and not only did things finally start to gel with SuperCollider after deciding to reorganize the code but I also thought it would be nice to throw AI at the problem of getting a usable UX on that and iterating through all the visible options:
Mosaic A interface views and secondary controls, with settings, presets and status screens.
I’ve looked at Anthropic’s S-1 and am torn between it being one of the best works of investor fiction ever written (especially regarding profitability vs compute and training costs) and a potential proof point for industry “transformation”.
If it goes through (and they don’t get their lunch eaten by OpenAI, open weights or anything else that will sink per-token pricing, which will certainly have more interesting implications) they might have something interesting there, but I am not betting my money on anything that is pure AI at this point.
I finally managed to make a small dent into my 3D printing backlog–I had been meaning to design 3D printed cases for the Orange Pi 6+, the LattePanda Sigma and another couple of SBCs I have, but a fortuitous search found serviceable ready-to-print ones, so my office is now looking slightly more tidy, and I have fresh new surfaces for dust to settle on, with two caveats:
The Orange Pi 6+’s fan noise was much more noticeable with the case on
I am temporarily lacking the required M3/14mm screws to button down the Sigma properly
Still, it was nice to go back to popping stuff off build plates, and the cases make for a much neater desk. Plus I realized I had an entire roll of white TPU stored away that has come in pretty handy to print feet for most of the cases.
One of the AI-related things I am actually quite happy about is the blooming reverse engineering/hardware repurposing scene, which I’ve been tracking since I would indeed like to make better use of some of my older hardware.
There are now credible, largely working efforts to do stuff like get Linux running on the Lenovo ThinkSmart View and iPad and iPhone hardware (sadly, triggered by Omarchy, but I guess the outcomes are a net positive), re-targeting or recompiling Nintendo Switch games for the Mac and Windows, and various other retrocomputing initiatives.
Of course only time will tell how good and actually useful any of those things are, but the barrier to entry is now so low that taking over Android photo frames and debloating Smart TVs is almost commonplace, and I’m totally here for it.
Oct 28th 2026 · 1 min read
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#apple #hardware #macbook #macos #touchscreen
Very pretty, undoubtedly top tier, very likely to be completely outside the range of anything I can afford, but just as likely to be extremely frustrating to use as a touch screen for the simple reason that macOS isn’t ready for it (I’ve already seen the kludgey semaphore window control interactions in social videos, and it’s as bad as on the iPad).
Given that I have been using touchscreen laptops for decades and (like I quipped to Miguel de Icaza the other day) pretty much only use the touch screen for hitting “Cancel” on dialog boxes when I’m standing near the laptop (because the ergonomics of raising your arms off the keyboard have always been questionable), I’m not terribly excited by the fact that Apple has finally caught up hardware-wise.
I will be impressed when they sort out the fragmented UX mess they now have across their product range, though. Let me go and put on some very slow popcorn.
Oct 26th 2026 · 3 min read
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#ai #anthropic #finops #llm #openai #piclaw #pricing
OpenAI launched GPT-6.1 Terra today at $1 per million input tokens, $5 for output and $0.05 for cached input. That is pretty similar to what happened with 6.1-Sol, since it is half of what GPT-5.6 Terra costs now, and the cached input rate is a fifth of what my piclaw pricing table recorded for it back in July.
This is kind of interesting to me for a number of reasons, not the least of which is that I have been tracking these numbers for months both at work and as I use my OpenAI subscription–my agents burn through a fair chunk of tokens, so anything that makes them much cheaper is noteworthy.
In case you’re new here, piclaw keeps a dated pricing reference for its token chart, plus a set of finops snapshots with the provider pages they were taken from. Looking at the git history for a few model lines (USD per million tokens, input/output, then cache reads), the trend is pretty interesting:
Line
Earlier
Now
Claude Opus
4/4.1: $15/$75, $1.50
5.5: $4/$20, $0.20
Claude Sonnet
4.5/4.6: $3/$15, $0.30
5.5: $2/$10, $0.10
OpenAI “Sol”
5.6 (July table): $5/$30, $0.50
6.1: $2/$10, $0.10
OpenAI “Terra”
5.6 (July table): $2.50/$15, $0.25
6.1: $1/$5, $0.05
In short, headline prices are down by anywhere from a third to three quarters depending on which line you pick, which is nice but not the interesting part–the interesting part is the last column, and, if you’re doing any sort of agentic work at scale, how caching prices factor into the equation.
When I audited a week of usage on my main instance in September, it came to 2.17 billion tokens. 94.3% of those were cache reads, which is entirely by design since I have been aggressively optimising piclaw’s context structure (and compaction) to maximise caching to lower costs, but still left a bit of fake money on the table.
Since 90% of my workloads are development/agent loops, fresh input on each turn is typically 1.5% and output a measly 0.1% (i.e. one or more tool calls). Agents just ship the same long context over and over to providers (to a point where I have to wonder why the heck we still use the same payload structure…), and 93.7% of the volume was in requests over 272K tokens, which OpenAI bills at twice the input and cache rates.
What this means, in volume, is that the price that matters for agents is actually cache reads, not raw tokens. If you’re burning money to light up your cigarettes (and have a disgusting smoking habit), you probably don’t care that Claude Fable 5.1 and GPT-6 Astra have the same $10/$50 list price, but over time Fable 5.1 cut cache reads from $1 to $0.25, which made it 70% cheaper than Astra on the same replay ($2,064 versus $6,858).
I don’t use Fable (I don’t have access to it anymore, even at work, and Anthropic doesn’t give me the time of day as an individual open source developer), but running my old benchmark’s token counts against today’s prices is… kind of interesting, and makes me really happy I am not paying per token:
Model
Input/output
Cache read
One week, same workload
GPT-6 Astra
$10/$50
$1.00
$6,858
Claude Fable 5.1
$10/$50
$0.25
$2,064
Claude Opus 5.5
$4/$20
$0.20
~$1,030
GPT-6.1 Sol
$2/$10
$0.10
~$990
Claude Sonnet 5.5
$2/$10
$0.10
~$515
GPT-6.1 Terra
$1/$5
$0.05
~$490
Of course, the above assumes a full replay: identical tokens as over that week, identical cache behaviour, etc. I’m glossing over retries, reasoning effort and whether the model actually gets the job done, so it’s just a data point.
I do find it interesting that Sonnet and Sol come out differently despite identical list prices because of OpenAI’s long-context surcharge, which Anthropic doesn’t charge–but, again, subscriptions mask all of this under their flat rate.
OpenAI’s announcement says Terra matches Astra on Agents’ Last Exam (a test of agents using office software, which I’ve always found hilarious given there’s so much more useful stuff to test them on) “at one-tenth the price per token”, and that it finishes tasks over three times faster than both Astra and Sol.
There are also claims that Terra is over three times as token-efficient as Opus 5.5 at maximum effort, which would make it about nine times cheaper per task–likely more because Terra would also be using fewer tokens.
Now, I’m much more focused on actual results, and even if I don’t care anything about synthetic benchmarks like BenchLM, they are less flattering on stuff I care about:
Terminal-Bench 4.0: Terra scores 50.3%, against 70.6% for Sonnet 5.5.
OSWorld 2.1 (offline subset): Terra 74.2%, Opus 5.5 87.2%.
OpenAI itself still points people at Sol or Astra for “in-depth research or complex coding”.
Still, if you consider that the smart approach is to have Luna and Terra carry out pre-defined instructions drafted by Sol or Astra and use extensive standard automation, Terra is starting to look really good for churning through things like ticket triage, running test harnesses and even managing CI.
This is the bit that puzzles me. If Sol and Terra now get you most of the way to… well, anywhere, really, for a fraction of the price, why does Anthropic still sell Fable (and Mythos) at $10/$50?
I have a few theories, ranging from good marketing, lack of competitive pressure at the premium level, and the current shape of the market:
They are not alone. Astra costs exactly what Fable does, so OpenAI also keeps a premium tier. It’s just not the one it advertises, which is an interesting inversion of Anthropic’s marketing spiel.
The mid-range has already converged. Sneakily (well, quietly, at least) Sonnet 5.5 now has the same list price as GPT-6.1 Sol, down to the $0.10 cache reads, and Opus 5.5 is at $4/$20, so the price war is happening one tier down (maybe at the level Claude users actually set most of their agents to).
They nominally still win where it matters for coding agents. My results with Opus have been consistently lousy across the board where it regards code quality (and the models outright lying to me regarding implementation), but market perception seems to be completely opposite to mine.
Most people never see a token price. Claude Max, Codex and Copilot sell allowances, not tokens, and a flat $200 a month both hides most of the difference unless you hit the limits and is psychologically justifiable as being “best of breed” (even if it isn’t).
What I do know is that, on my own workload, the cheapest Anthropic model I’d trust with real work (Sonnet 5.5) now costs about the same as Terra, and Opus 5.5 costs half of what Fable does. So Anthropic is, surprisingly, cutting prices too.
Still, I’ll be running Terra against my usual piclaw tasks over the next few days, mostly to see whether the token-efficiency claims hold up. My guess is that it’ll replace a lot of my bounded, well-tested work and none of my hard debugging, planning or code audits, but we’ll see.
Oct 26th 2026 · 1 min read
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#apple #hardware #ipad #tablets
I miss using my iPad Mini 5, but ever since iOS 27 came out it’s been massively slower and I’ve mostly switched to my M1 iPad Pro (which also makes a few other things simpler, like travel, note taking, using external displays, etc.).
I very dearly want to go back to the Mini since the Pro is too large as a permanent companion device, but the inflated pricing is not helping. and neither is my feeling that Apple has likely nerfed the hardware in ways that matter to me.
As an example, there’s a sidenote in the announcement where Apple promises extended display mode with iPadOS 27.2. But I am going to wait until detailed reviews show how well that actually works, since the Pro can drive my Kuycon P20 at full resolution, and if the new Mini doesn’t do at least as well, then I will likely start hunting for unicorns good Android tablets.
Oct 26th 2026 · 1 min read
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#ai #art #music #science-fiction #video
Here’s a fun rabbit hole I fell into over the weekend, and that should make you wonder if William Gibson is a visitor from a future timeline–because Claudia not only echoes Idoru to a great degree but also might be somewhat of an inflection point. Just not necessarily because of the base content on the site: this pretty amazing French “slop core” video has been making the rounds in socials, and even considering it’s AI-generated, I don’t think you can just ignore it without appreciating the creativity its human director put into it.
Yep, buckle up!
Oct 25th 2026 · 1 min read
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#agents #ai #wellbeing #work
I was watching Gergely Orosz the other day for some reason, and he was going on about the impact of AI on the industry (what I like to call the Cambrian Slop Explosion). He mentioned that one of the major changes–and one of the personally taxing effects of using AI–was constant context switching and how fatiguing it was.
And I completely agree. Nearly two months after returning from vacation and after a particularly nasty overlap of work and personal projects, the thing I missed the most was the quiet. To just sit in a room reading or writing with no pressure to check on my agents (work or otherwise, which also feels like work now), letting ideas come to me unbidden, in a Douglas Adams-esque parody, wafting in the wide open space somewhere between my ears and bumping into each other.
It’s kind of nice, the quiet.
Oct 25th 2026 · 4 min read
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#reviews #teams #ugreen #videoconferencing #webcams
It’s been a while since I wrote about my desk setups or how much I rely on having decent audio and a good camera with face tracking, so my return to work in early September seemed like a good time to do that. I’d meant to post this then, but said work was enough of a pain to delay it until late October… But that’s beside the point right now.
Apple users are used to face tracking and auto-framing by now, but I have been using professional videoconferencing systems for many decades.
In fact, back in the mid-90s, I did quite a bit of work on videoconferencing over ISDN and ATM, including hacking NetMeeting into submission… But it took the pandemic and my OBSBOT camera to finally feel personal tech had caught up with the times.
After another bout of back pain this year and a return to my makeshift standing desk, I decided I’d take a look at the webcam market again to see if I could get another OBSBOT (or at least a true gimbal camera) to sit atop my battered Surface Pro 3, which was (until recently) the centrepiece of said “desk”. It has a perfectly usable Windows Hello camera, but I tend to get restless and something that keeps me in frame is nicer to my callers.
I considered the software route first, but I couldn’t find anything that would work with the internal camera and wouldn’t kill the PC (Teams is enough of a challenge for it these days). Trying one of the (excellent) Logitech Brio 4K cameras I still have made me realise I needed to move the camera itself, too. And I didn’t want anything that would require extra software in Linux or on a Mac later.
There’s enough junk software out there already, after all.
But OBSBOT-style cameras were around €200 a pop when I looked, so getting a new one for a secondary desk was a no-go, and I decided to try something cheaper, gimbal-less, but with enough sensor resolution for decent cropping and zooming.
The UGREEN FineCam Pro stood out to me for two reasons–what seemed a decent price for a nominally 4K-capable sensor and its compactness, since it took up far less volume than most other options.
Disclaimer: I bought this one myself; however, my usual review policy applies, because I consider this a bit of a “low effort” review.
The reason I bought it in April was that the built-in firmware handles gesture-controlled framing and zoom itself–with driverless support for Windows, macOS and Linux, and thus complete software independence (which I think will be useful for anyone in alternative platforms).
The FineCam Pro, sporting the perennial dust layer that pervades my office
And why finally write about this now? Well, because I’m testing a brand new Qualcomm-based laptop that does head tracking completely in software, and thought this was worth noting while comparing setups–more on that in a future post about the laptop.
The camera itself is… OK, I guess. It’s an 8-megapixel sensor capable of 4K at 30fps or 1080p at 60fps, has “phase-detection autofocus” and pretty decent lighting sensitivity, as well as two microphones with noise reduction, positioned for stereo capture if you use it for vertical video, which… I didn’t. Audio from those was reported as being good, though.
The rest is mostly creator frills: the mode dial switches between seven dubiously useful built-in filters, and there is a privacy cover.
The camera comes with a magnetic mount and a small tripod, which is another concession to the “creator” audience, and the magnetic holder fits neatly atop my Surface display and lets me detach and reposition the camera without disturbing the mount (it also made it easy to move the camera off-centre when using a sidecar monitor, which is a very “me” thing to do, but which might be of interest to other people as well).
For some stupid reason (yes, I know it’s probably the creator audience, but it’s still stupid) the camera defaults to vertical orientation, which I suppose comes hand in hand with its mode dial and effects.
That dial is clearly geared at people doing social media, but gleefully ignores the fact that even on TikTok (which I don’t use but am regularly kept apprised of) nobody seems to use those effects, and, as you’d expect, I didn’t use them either (except once by mistake).
Additionally, the USB-C port seems to have been purposefully positioned at the most inconvenient position possible on the back–the weight of the cable tore off the camera from the magnetic mount and the cable protrudes from the back too much, adding to the imbalance.
It took me a little while to figure out the right distance at which to hold my hand to enable tracking, but after a while that became second nature (I’m used to having to do that with my OBSBOT as well, because for some reason there is no way to set that default even after years of firmware upgrades).
Picture quality in Teams calls was good, with smooth tracking–but of a different flavour than the OBSBOT. The differences in quality and motion are subtle, and in practice I’m mostly the one who notices.
But here’s a pro tip: perform the magical tracking gesture incantations before you enter the call, if you can, otherwise people will feel compelled to wave back, even in very formal official settings…
I don’t regret my purchase, but I do think it would be pretty safe for UGREEN to simply remove the mode dial and move the USB port to the side. I’d much rather have a smaller camera than a selection of filters I never use.
I haven’t tried the plainer FineCam, but its shape is pretty much the form factor I’d want. Put the Pro’s camera hardware and tracking into that enclosure, and I’d be perfectly happy not having to see the dial…
Oct 24th 2026 · 1 min read
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#agents #ios #notes #weekly #wifi
I’ve been more interested in exploring how to simultaneously enjoy Greek yoghurt, orange marmalade and the glorious golden-hour light that pervades my living room than, well, most other things, so this week was a bit of a bust as far as personal projects go.
Part of that is because I have finally swapped the Surface loaner I was using for a brand new machine (more on that later) and am also returning the Lenovo Chromebook I recently reviewed, so I had to spend a little while making sure nothing of relevance was lost.
A sharp-eyed reader (hi!) noticed that I mentioned the Radxa Linkr had some WPA3 issues, and told me an OpenWrt update had some WPA3 interoperability fixes for the Cudy M3000, so I upgraded one of my APs–that didn’t fix the Linkr, but after some soaking in I upgraded the rest with no ill effects.
Roaming around the house still works fine, but there are a couple of reported issues with fast-transition (FT) associations in this build, so I’m keeping an eye on OpenWrt PR #23181 and mt76 issue #1098 in case I come across any issues in the future.
I’ve found an interesting workaround for my “no local agents on my Mac” rule–I’ve been using Open Minis on my iPad for a while now because of its iOS integrations (it can handle Reminders, Calendar, HomeKit, etc.), and I realised that it can run as a fully sandboxed iOS app on my MacBook Pro and sync via iCloud with my iPad and iPhone.
Since I had previously gotten my iPad to sync skills with memento, it took me 5 minutes to get everything working on my Mac, including mapping a couple of “external” folders to it.
Since it’s using the same engine as ios-linuxkit (even if they didn’t take any of my PRs and fixes, which is a bit sad), there’s additional ARM-on-ARM emulation going on, but on a MacBook that barely registers–and having a sandboxed agent that can run its own native Safari WebKit browser completely isolated from my Mac is pretty nice.
I’ve been patiently nudging piclaw to port itself to pi-durable. Most of that has already happened–the new version is self-healing and is gradually removing the redundant abstractions I had built atop the original SDK.
No hurry there.
Oct 22nd 2026 · 1 min read
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#apple #foldables #iphone #reviews
I’ve been bemusedly reading and watching several iPhone Duo reviews over the past day or so (besides John’s piece, The Verge has a series of excellent pieces and a thorough video review), and the consensus seems to be that it’s a polished, chunky prototype that hasn’t really figured out what the user experience should be. Being a Mr. Mobile fan and watching his videos on Android foldables for years now, it comes as no surprise. But it also will come as no surprise that two years down the road this thing will have solved most of its teething issues–except the price, of course.
And I do find it amusing that we’ve managed to get to a point where a premium phone actually makes you want to use it less as a phone. I, personally, count that as a good thing.
Oct 21st 2026 · 1 min read
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#hardware #kits #mac #macclock #raspberry-pi #retrocomputing
The Maclock hack I linked to many months ago is now a finished product (with various flavours of kit), which is kind of fun to see. I have managed to procrastinate assembling mine for a stupefying amount of time now, and have some hope that posting this will shame me into finishing it (I actually have two Maclocks, plus my own 3D printed SE/30)…
Oct 18th 2026 · 7 min read
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#agentic #ai #hardware #kvm #networking #reviews
I’ve done quite a few KVM reviews in the past, and there’s a reason for that: All of the homelab and industrial IoT stuff I test needs some sort of physical access for setup, and even if I do have monitors with multiple inputs, USB video capture dongles, etc., it gets really old to have to constantly re-wire stuff, switch between keyboards, etc.
Additionally, most of the newfound range of cheap/compact KVMs that have popped up over the past two years still need an Ethernet connection, and it’s become ridiculously hard to have even semi-permanent test setups–I keep running out of both power and Ethernet ports, and that’s been the reason why I’ve been limping along on Wi-Fi based Pi Zero KVMs as well as one or two KVMs that, sadly, require proprietary apps.
So when I spotted the Radxa Linkr, I just had to try it. And that was even before I knew I could get it to work with an AI agent…
Disclaimer:Radxa supplied me with a Linkr free of charge, and this review follows my usual review policy.
In the box, you get the Radxa Linkr and a set of cables (pictured above in real life, and below in the Quick Start guide).
The supplied Quick Start guide (image: Radxa).
The hardware itself is pretty comprehensive, and packs quite a lot into the small 70 x 22 x 12 mm enclosure:
Rockchip RV1106G3 SoC, with a 1.2GHz Arm Cortex-A7 CPU, a RISC-V co-processor, 1 TOPS NPU and a hardware video encoder.
256MB of integrated DDR3L memory.
16GB eMMC storage or a microSD card slot (I got the variant with internal storage) for firmware and virtual media.
HDMI input up to 2560x1440 at 30Hz, with lower-resolution modes including 1920x1080 at 60Hz and custom EDID support.
Dual-band 2.4GHz/5GHz Wi-Fi 6 using an AIC8800 module, with client and hotspot modes.
A USB-C device port for keyboard and mouse emulation, power (5V/2A) and firmware flashing.
A separate USB-C network port for a direct host connection or 10/100Mbps Ethernet through the supplied USB-C to RJ45 cable.
One FN user button, a system status LED and an HDMI/video status LED.
The device itself is tiny, and the single FN button is used to identify it on the discovery page or (with newer firmware) to toggle the Wi-Fi hotspot with a double press. You can see the USB-C connectors on the back and side through the semi-transparent casing in the photo above.
A nice touch that you will appreciate if you manage many machines is that there are indicator lights that show when someone is remotely connected (the blue power LED will turn green) or there is a video input problem (signalled by a blinking video status LED).
Besides direct USB connectivity to your machine (which I honestly didn’t spend any time on), the Linkr supports both 2.4GHz and 5GHz Wi-Fi. However, it doesn’t seem to support my particular flavour of WPA3 (at least in current firmware versions), so I stuck to 2.4GHz/WPA2 for all of my testing, which is plenty fast enough.
That’s a decent tradeoff for me (I had zero latency issues, although I spend so much time in VDI and remote console setups that I don’t notice delays anymore) and, at least in one of my tests, was the only way I could connect to a machine in a remote corner of the house where 5GHz has very little reach–but it managed 60fps just fine.
The Linkr is quite flexible in terms of video capture. I’ve needed to hack in support for custom EDIDs in my old PiKVMs, so it’s nice to see that is baked in, and the built-in HDMI bridge goes from 1280x720@30/60Hz to 2560x1440@30Hz, with standard 1080p in the middle.
I also found it a nice touch that the Linkr includes a virtual sound card that it exposes via USB to the target system, although I have had zero use for audio in any of my tests…
The Linkr, like all devices, does warm up while in use, and its metal underside can be surprisingly warm to the touch–and yet, my IR thermometer didn’t see it get past 45°C even after hours of continuous use (disconnecting, of course, lets it idle cooler).
As you’ve probably divined from the Quick Start shot above, this is a pretty trivial web-based setup: go to linkr.now (with Chrome or Edge, because Apple still hasn’t figured out most of the modern device-related browser APIs), and you get an HTML app that will find the Linkr and help you connect to it – via USB or, later, via Wi-Fi.
The entire thing is very slick, and the user interface is both responsive and easy to navigate–here’s a little slideshow of the original firmware version:
A tour of the web interface captured with firmware 1.4.2.
Firmware updates and release notes are available on GitHub, and since I got mine (v1.4.2), Radxa has added quite a few new features, as well as a bunch of fixes, in what is today v1.5.2:
A Plugin Center, which is a sensible way to keep adding more features without changing the core firmware–I haven’t yet had time to investigate how I could build my own, since I only noticed it as I finished this draft.
ZeroTier and EasyTier support (I use Tailscale myself, but it’s nice to see options).
Screenshot OCR to recognise text in screenshots and edit or copy the results (see below); recognition runs locally, and an optional plugin supplies the OCR resources without Internet access.
Experimental IPv6 support (which works, at least on my LAN).
FN-button hotspot toggle (double-press it to turn the Wi-Fi hotspot on or off).
One fix in particular was very useful already (they fixed resolution switching with the Radxa Dragon Q8B as video input, and I’m still testing that this weekend), and the pace at which they are currently shipping updates is reassuring, even though I couldn’t find published source code for the firmware in the public repository.
Other than that, you get all the typical remote KVM features (as well as Tailscale support, which I use extensively):
Video resolution settings (and custom EDID, as pointed out above).
Wake-on-LAN (for any MAC address, although you can pin the ones you need).
Keyboard and mouse control (as well as the virtual USB audio capture, all exposed via USB ID 1d6b:0104 - Multifunction Composite Gadget).
Mouse control can be set to both absolute and relative, as well as reversing the scroll wheel (which I thought was a very nice touch).
However, Mac and iOS users can’t really use some of the more advanced web UI features like screenshots, recordings or screen OCR, because they’re not available in Safari. Some of this is Apple’s problem, but I’ve hacked Safari-compatible screenshot support into other KVMs, so Radxa can probably improve that.
I did find the screenshot OCR feature interesting, but it requires pretty crisp text, and some SBCs just aren’t willing to play ball on their boot consoles–however, it can be immediately useful in a pinch:
Screenshot OCR on a boot console; the recognition results can be edited and copied.
A nice touch about this is that recognition happens fully in-browser:
It uses tesseract.js to recognise English and Simplified Chinese.
By default, it downloads OCR resources over the Internet, including the worker script from cdn.jsdelivr.net.
The screenshot is processed locally by the browser worker, which returns the recognised text and bounding boxes to the UI.
The offline plugin just caches a local copy of the worker, engine and language data inside the Linkr itself, removing the external-download requirement.
But the real reason I am very much enjoying using the Linkr is that, unlike most KVMs, it actually exposes an API that you can either script against or just point your AI agent to.
I have been using that for over a month now to great effect (including doing a couple of Fedora and Windows installs, which is a veritable quagmire of edge cases) and built a piclaw add-on you can use as a reference.
The release notes also describe new API controls for resolution and video quality, which my add-on doesn’t cover yet. But the basic screenshot and input controls work amazingly well if you pair them with a vision-enabled model, and are really simple:
The documented public API uses an access token in the Authorization: token <token> header, and boils down to two endpoints:
GET /api/public/snapshot returns the current screen as a JPEG.
POST /api/public/control accepts an ordered events array containing keyboard, mouse, text and delay operations.
The control primitives are small enough to wrap directly in agent tools:
keyboard presses or releases keys using browser KeyboardEvent.code names, so combinations are sequences of key-down and key-up events.
mouse_abs positions the pointer using normalised coordinates between 0 and 1 (this can be a little tricky for some models, but they get it eventually).
mouse_rel moves it by pixel offsets (both support mouse buttons and scrolling).
text types up to 1024 characters, limited to printable ASCII, tabs and newlines.
delay pauses between events for a specified number of milliseconds (useful when the target needs time to react).
That gives an agent the usual screenshot/action loop without installing anything on the target machine.
I had to burn through quite a few tokens in initial testing (and the skills my add-on bundles are the result of that), but you should be able to use a relatively cheap model to automate typical system administration tasks, as long as it supports vision.
Can it do fully unattended installations? Well… It’s tricky. Can you figure out when to enter the BIOS on a random machine and what key to press? That is so variable across machines (and sometimes even on the same machine) that the only way I got it to work was to get into the BIOS (after a few tries), pick the boot volume myself and then hand over to piclaw.
The results and reliability are highly dependent on the AI model you use. I’ve had good experiences with astra, opus or sol on a variety of desktop automation tasks, and they were all able to use the Linkr to go through a standard OS installer. I also got them to check Windows updates (clicking through all the steps and choosing when to reboot) and even do console rpm-ostree and flatpak updates (and reboots) without any issues except the high token count that comes with handling screenshots (and model-side OCR).
This is what currently makes the Linkr worth looking at if you want to automate hardware setup, with the caveat that it can, indeed, do away with the odd bit of drudgery, but you need to be smart about how to do it (only retrieving screenshots at intervals/decision points to save tokens, for instance) and, preferably, script things so that the model is only really phoning it in.
For me it was almost a straight conversion of some of the stuff I’ve actually been doing in Proxmox for a while, so it’s nice to have a way to set up a blank box.
Hardware-wise, I should note that you can’t hit a reset button with the Linkr, so if your hardware doesn’t honour Ctrl+Alt+Del, you’re stuck. Other KVMs have dedicated interfaces to do that (and you can always use a smart plug, like I do with my test SBCs), but it’s something to keep in mind.
Additionally, I’ve had a couple of instances where the Linkr had a little trouble fitting directly into PCs or SBCs (including Radxa’s own) because of lack of clearance around the HDMI port or having the USB-C port on the side (which in a few cases meant it would point straight into the desk).
Nothing that you can’t fix with an HDMI extension cable (I used a Chromecast male-to-female extension, which is around 10cm), but worth mentioning since it doesn’t come in the box.
Another minor hassle is that if you power the Linkr directly from your target device, many devices (even standard PCs) won’t power up USB until they’ve gone past display initialisation, so the Linkr may skip UEFI/BIOS screens while it boots.
When testing SBCs, I had to use that power/data splitter cable to keep the Linkr powered up independently–otherwise it would boot up after the servers had tried (and failed) to initialise HDMI, so I’d get no video out (and, depending on device, they wouldn’t reactivate HDMI after USB input or Wake-on-LAN, either).
I’m obviously biased towards anything that lets me put a machine on Wi-Fi and get at it through a browser without installing yet another proprietary app, so the Linkr already had quite a bit going for it.
But having an API that I can script against, or hand over to an agent once I’ve persuaded the machine to boot from the right device, makes it considerably more useful for the sort of testing I do, and I am quite likely to replace some of my other KVMs with Linkrs solely to free up Ethernet ports.
I’ll still need the odd HDMI extension and a separate power supply for a few machines (especially ARM ones), but at least the wiring will be much easier, and who knows, I might even start testing more than one SBC at once…
Had a fairly slow start to the week, then a progressively intense ramp-up that I tempered by way of a couple of strategically timed outings and a little time on my own projects.
Tab grouping and auto-tiling aren’t new by any means, but zooming to a subset of windows is very, very neat.
It isn’t worth paying a subscription fee for (and if it proves to be really productive it might get Sherlocked within a couple of years, depending on whether Apple manages to shrug off the mess that is Stage Manager), and is likely to have three open-source clones tomorrow, so I’ll let the hype settle and give the concept a try once I find an implementation I can hack.
Oct 13th 2026 · 1 min read
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#ai #apple #hardware #homekit #siri
This feels like Pixar’s Luxo or the classic half-dome iMac crossed over into the WALL-E universe, and looks like it is going to be cloned to oblivion. The $299 price is… interesting considering the tech inside it (parts of what it can do are highly non-trivial, and very much the kind of AI Apple likes doing).
I feel somewhat vindicated that Apple seems to have built a Siri for Families of sorts, but at the same time I have to wonder what flavour of it (and when) will be available in Europe, and exactly how much more bang for the buck it affords than, say, hacking a cheap Android picture frame–which is what I’ve been doing for a while now with the Lenovo ThinkSmart View.
I do think I want one, but there are a few things to settle besides price and value. For starters, having more screens in the house doesn’t seem like a winning proposition (the HomePods we’ve got work OK for alarms, reminders, etc.), and the American fascination with the kitchen island (which, by the way, needs power sockets in the middle…) doesn’t translate to European flats.
I find the Apple Home Collection a lot more interesting, but I’m going to reserve judgement until I understand whether it’s worth considering switching any of my home automation hardware… and all the LG gear is extremely expensive as such things go these days.
Oct 12th 2026 · 2 min read
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#apple #audio #automation #privacy #shortcuts #siri #watch
I have been pondering the Audio Intelligence Live Rewind feature that Apple announced in the last keynote, and even though I know I am very late to this entire discussion, I still want to go on the record about it.
Regular readers will know I’ve had a long fascination for the Yamaha DX7–after all, besides getting a Reface DX quite some time ago, I also built a MiniDexed box and accumulated more software instruments than I have time to use, as well as an embarrassing amount of other physical gear that brands me as a victim of Gear Acquisition Syndrome.
Sometimes I feel like I am only really alive on weekends. Sadly, that only seems to happen part-way through Sunday afternoons, which speaks to my utter lack of timing of late.
I’m feeling the edges of burnout creep in, and having gone through that before, I’m pulling the brakes on anything that is neither immediately useful nor satisfactory.
This was not on my bingo card for… well, this decade, given the relative success of their more recent gear like the KO II.
Sure, there are some really strange things in the line-up, like the medieval flavour, and their UX can stray well beyond quirky into cuckoo land. But they’ve always been a source of whimsy and musical creativity–my OP-1 being a case in point.
Then again, things like the M-VAVE FM-1 are vastly cheaper these days (and arguably have better hardware features). They’re hackable, too, with an active ecosystem–which I suspect will dictate the success of future music hardware.
Oct 6th 2026 · 1 min read
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#ai #europe #llm #mistral #open-weight
At last, Mistral has shipped a model that, judging by the model card, seems to compete with Chinese open-weight models–on paper, at least. It’s available via their API now, with the weights promised for the end of the month.
Now they need to demonstrate that the EU can do this consistently. There are scattered labs in Prague and Germany (which never seem to make it to Hacker News, for some reason), but the perception of AI work in Europe is still pretty poor–something I’ve ranted about before, including Mistral’s sovereignty pitch, which is at least backed up by their own European datacentres (the 3,800 Grace Blackwell GPUs used to train this model are relatively modest compared with hyperscaler clusters, but they did build out the infrastructure, and that deserves recognition).
Oct 6th 2026 · 1 min read
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#android #arm #google #googlebooks #intel
Google acknowledging that some Android apps don’t run well on Intel Googlebooks is about what I’d expected. One of Android’s hidden catches is that Google has been neglecting it on Intel for a long time, and there isn’t a polished ARM-to-x86 translation layer to make up for it.
The main reason the Lenovo Chromebook I tested had such a seamless Android app experience was its MediaTek processor, and I really think the best Googlebooks are going to be the ARM ones.
Update: There is a fly in the ointment here that has me worried a bit, though. Googlebooks seem to absolutely require a Google login for activation (like Chromebooks), which makes it a little harder for me to consider them–you can use an Apple device (and a regular Android device) without an account, but if Google enforces this for Googlebooks and then they decide to arbitrarily nuke your account (as they’ve been known to do on occasion to people doing off-label things, even normal development), you’re completely hosed.
Oct 4th 2026 · 17 min read
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#android #arm #chromebook #chromeos #lenovo #review
A few months ago, around the time Googlebooks were announced, I became really interested in Chromebooks again, partly because I’d completely lost touch and partly because I heard good things about the new ARM chipsets, namely the MediaTek Kompanio Ultra. But Chromebooks are not a common thing in my neck of the woods.
This week was a bit different. For starters, it rained. And I visited the local office. And I consciously set aside hours to catch up on my writing instead of herding AI or doomscrolling, and again, failed at a bunch of that because–well, I lied.
Redlamp was developed by one of the most talented Mac developers I’ve worked with in the past, and I’m very happy to see it–especially considering the way Apple completely neglected Aperture, and the shambles Photos still is if you have an inkling about real photography workflows.
It’s a native RAW editor for Apple Silicon, written in Swift and Metal, that opens folders directly and keeps edits in sidecar files. RAW development, masks and local adjustments, reusable Recipes and film looks are already there–although it’s still pre-alpha, with crop, healing and lens corrections on the roadmap.
Library management is further down the road too, so it isn’t a full Aperture replacement yet. I’ve added an app page with a screenshot and a few notes, and I look forward to using it from now on.
Oct 2nd 2026 · 1 min read
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#apple #exchange #macos #mail #microsoft #outlook
The writing has been on the wall for EWS in Exchange Online for ages, and Apple’s promised Graph support still hasn’t shipped; M365 can temporarily keep EWS enabled until April 2027, but right now some tenants may effectively kick out Apple Mail/Calendar, which is just stupid because it is definitely not Microsoft’s fault that EWS is being phased out in favor of a better, much more flexible approach.
I have zero idea about why it’s taking Apple this long to get their act together, since EWS has been feature-frozen since 2018 and Graph has been meat and potatoes stuff for ages. Even though I do run Outlook locally for my (very rare now) consulting/advisory work, I am not looking forward to being locked out of my accounts just because Apple effectively stopped maintaining its cloud account integrations and has been phoning it in for the last 3 or 4 macOS releases–not to mention that, as I’ve found over the past couple of years while trying to automate stuff, it is effectively impossible to have a unified local API for contacts, calendars and to-dos that actually works, let alone e-mail…
So I guess it’s a moderately good thing I’ve been using Graph wrappers for years now to get around Apple’s inability to maintain things, no?
Rui Carmo
