For every cloud ser­vice I use, I want to have a lo­cal copy of my data for backup pur­poses and in­de­pen­dence. Unfortunately, the gpho­tos-sync tool stopped

work­ing in March

2025 when Google re­stricted the OAuth scopes, so I needed an al­ter­na­tive for my ex­ist­ing Google Photos setup. In this post, I de­scribe how I have set up

Immich, a self-hostable photo man­ager.

Here is the end re­sult: a few (live) pho­tos from NixCon

2025:

I am run­ning Immich on my Ryzen 7 Mini PC (ASRock DeskMini

X600), which con­sumes less than 10 W of power in idle and has plenty of re­sources for VMs (64 GB RAM, 1 TB disk). You can read more about it in my blog post from July 2024:

I in­stalled Proxmox, an Open Source vir­tu­al­iza­tion plat­form, to di­vide this mini server into VMs, but you could of course also in­stall Immich di­rectly on any server.

I cre­ated a VM (named “photos”) with 500 GB of disk space, 4 CPU cores and 4 GB of RAM.

For the ini­tial im­port, you could as­sign more CPU and RAM, but for nor­mal us­age, that’s enough.

I (declaratively) in­stalled

NixOS on that VM as de­scribed in this blog post:

Afterwards, I en­abled Immich, with this ex­act con­fig­u­ra­tion:

At this point, Immich is avail­able on lo­cal­host, but not over the net­work, be­cause NixOS en­ables a fire­wall by de­fault. I could en­able the

ser­vices.im­mich.open­Fire­wall op­tion, but I ac­tu­ally want Immich to only be avail­able via my Tailscale VPN, for which I don’t need to open fire­wall ac­cess — in­stead, I use tailscale serve to for­ward traf­fic to lo­cal­host:2283:

pho­tos# tailscale serve –bg http://​lo­cal­host:2283

Because I have Tailscale’s MagicDNS

and TLS cer­tifi­cate pro­vi­sion­ing

en­abled, that means I can now open https://​pho­tos.ex­am­ple.ts.net in my browser on my PC, lap­top or phone.

At first, I tried im­port­ing my pho­tos us­ing the of­fi­cial Immich CLI:

% nix run nix­p­kgs#im­mich-cli — lo­gin https://​pho­tos.ex­am­ple.ts.net se­cret

% nix run nix­p­kgs#im­mich-cli — up­load –recursive /home/michael/lib/photo/gphotos-takeout

Unfortunately, the up­load was not run­ning re­li­ably and had to be restarted man­u­ally a few times af­ter run­ning into a time­out. Later I re­al­ized that this was be­cause the Immich server runs back­ground jobs like thumb­nail cre­ation, meta­data ex­trac­tion or face de­tec­tion, and these back­ground jobs slow down the up­load to the ex­tent that the up­load can fail with a time­out.

The other is­sue was that even af­ter the up­load was done, I re­al­ized that Google Takeout archives for Google Photos con­tain meta­data in sep­a­rate JSON files next to the orig­i­nal im­age files:

Unfortunately, these files are not con­sid­ered by im­mich-cli.

Luckily, there is a great third-party tool called

im­mich-go, which solves both of these is­sues! It pauses back­ground tasks be­fore up­load­ing and restarts them af­ter­wards, which works much bet­ter, and it does its best to un­der­stand Google Takeout archives.

I ran im­mich-go as fol­lows and it worked beau­ti­fully:

% im­mich-go \

up­load \

from-google-pho­tos \

–server=https://​pho­tos.ex­am­ple.ts.net \

–api-key=secret \

~/Downloads/takeout-*.zip

My main source of new pho­tos is my phone, so I in­stalled the Immich app on my iPhone, logged into my Immich server via its Tailscale URL and en­abled au­to­matic backup of new pho­tos via the icon at the top right.

I am not 100% sure whether these set­tings are cor­rect, but it seems like cam­era pho­tos gen­er­ally go into Live Photos, and Recent should cover other files…?!

If any­one knows, please send an ex­pla­na­tion (or a link!) and I will up­date the ar­ti­cle.

I also strongly rec­om­mend to dis­able no­ti­fi­ca­tions for Immich, be­cause oth­er­wise you get no­ti­fi­ca­tions when­ever it up­loads im­ages in the back­ground. These no­ti­fi­ca­tions are not re­quired for back­ground up­load to work, as an Immich

de­vel­oper con­firmed on

Reddit. Open

Settings → Apps → Immich → Notifications and un-tick the per­mis­sion check­box:

Immich’s doc­u­men­ta­tion on

back­ups con­tains some good rec­om­men­da­tions. The Immich de­vel­op­ers rec­om­mend back­ing up the en­tire con­tents of UPLOAD_LOCATION, which is /var/lib/immich on NixOS. The

back­ups sub­di­rec­tory con­tains SQL dumps, whereas the 3 di­rec­to­ries up­load,

li­brary and pro­file con­tain all user-up­loaded data.

Hence, I have set up a sys­temd timer that runs rsync to copy /var/lib/immich

onto my PC, which is en­rolled in a 3-2-1 backup

scheme.

Immich (currently?) does not con­tain photo edit­ing fea­tures, so to ro­tate or crop an im­age, I down­load the im­age and use GIMP.

To share im­ages, I still up­load them to Google Photos (depending on who I share them with).

The two most promis­ing op­tions in the space of self-hosted im­age man­age­ment tools seem to be Immich and Ente.

I got the im­pres­sion that Immich is more pop­u­lar in my bub­ble, and Ente made the im­pres­sion on me that its scope is far larger than what I am look­ing for:

Ente is a ser­vice that pro­vides a fully open source, end-to-end en­crypted plat­form for you to store your data in the cloud with­out need­ing to trust the ser­vice provider. On top of this plat­form, we have built two apps so far: Ente Photos (an al­ter­na­tive to Apple and Google Photos) and Ente Auth (a 2FA al­ter­na­tive to the dep­re­cated Authy).

I don’t need an end-to-end en­crypted plat­form. I al­ready have en­cryp­tion on the tran­sit layer (Tailscale) and disk layer (LUKS), no need for more com­plex­ity.

Immich is a de­light­ful app! It’s very fast and gen­er­ally seems to work well.

The ini­tial im­port is smooth, but only if you use the right tool. Ideally, the of­fi­cial im­mich-cli could be im­proved. Or maybe im­mich-go could be made the of­fi­cial one.

I think the auto backup is too hard to con­fig­ure on an iPhone, so that could also be im­proved.

But aside from these ini­tial stum­bling blocks, I have no com­plaints.

Table Of Contents

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The con­tro­versy high­lights a wider trend in which more of what peo­ple see on­line is pre-processed by AI be­fore reach­ing them. Smartphone mak­ers like Samsung and Google have long used AI to “enhance” im­ages. Samsung pre­vi­ously ad­mit­ted to us­ing AI to sharpen moon pho­tos, while Google’s Pixel “Best Take” fea­ture stitches to­gether fa­cial ex­pres­sions from mul­ti­ple shots to cre­ate a sin­gle “perfect” group pic­ture.

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NanoKVM is a hard­ware KVM switch de­vel­oped by the Chinese com­pany Sipeed. Released last year, it en­ables re­mote con­trol of a com­puter or server us­ing a vir­tual key­board, mouse, and mon­i­tor. Thanks to its com­pact size and low price, it quickly gained at­ten­tion on­line, es­pe­cially when the com­pany promised to re­lease its code as open-source. However, as we’ll see, the de­vice has some se­ri­ous se­cu­rity is­sues. But first, let’s start with the ba­sics.

As men­tioned, NanoKVM is a KVM switch de­signed for re­motely con­trol­ling and man­ag­ing com­put­ers or servers. It fea­tures an HDMI port, three USB-C ports, an Ethernet port for net­work con­nec­tiv­ity, and a spe­cial se­r­ial in­ter­face. The pack­age also in­cludes a small ac­ces­sory for man­ag­ing the power of an ex­ter­nal com­puter.

Using it is quite sim­ple. First, you con­nect the de­vice to the in­ter­net via an Ethernet ca­ble. Once on­line, you can ac­cess it through a stan­dard web browser (though JavaScript JIT must be en­abled). The de­vice sup­ports Tailscale VPN, but with some ef­fort (read: hack­ing), it can also be con­fig­ured to work with your own VPN, such as WireGuard or OpenVPN server. Once set up, you can con­trol it from any­where in the world via your browser.

The de­vice could be con­nected to the tar­get com­puter us­ing an HDMI ca­ble, cap­tur­ing the video out­put that would nor­mally be dis­played on a mon­i­tor. This al­lows you to view the com­put­er’s screen di­rectly in your browser, es­sen­tially act­ing as a vir­tual mon­i­tor.

Through the USB con­nec­tion, NanoKVM can also em­u­late a key­board, mouse, CD-ROM, USB drive, and even a USB net­work adapter. This means you can re­motely con­trol the com­puter as if you were phys­i­cally sit­ting in front of it - but all through a web in­ter­face.

While it func­tions sim­i­larly to re­mote man­age­ment tools like RDP or VNC, it has one key dif­fer­ence: there’s no need to in­stall any soft­ware on the tar­get com­puter. Simply plug in the de­vice, and you’re ready to man­age it re­motely. NanoKVM even al­lows you to en­ter the BIOS, and with the ad­di­tional ac­ces­sory for power man­age­ment, you can re­motely turn the com­puter on, off, or re­set it.

This makes it in­cred­i­bly use­ful - you can power on a ma­chine, ac­cess the BIOS, change set­tings, mount a vir­tual bootable CD, and in­stall an op­er­at­ing sys­tem from scratch, just as if you were phys­i­cally there. Even if the com­puter is on the other side of the world.

NanoKVM is also quite af­ford­able. The fully-fea­tured ver­sion, which in­cludes all ports, a built-in mini screen, and a case, costs just over €60, while the stripped-down ver­sion is around €30. By com­par­i­son, a sim­i­lar RaspberryPi-based de­vice, PiKVM, costs around €400. However, PiKVM is sig­nif­i­cantly more pow­er­ful and re­li­able and, with a KVM split­ter, can man­age mul­ti­ple de­vices si­mul­ta­ne­ously.

As men­tioned ear­lier, the an­nounce­ment of the de­vice caused quite a stir on­line - not just be­cause of its low price, but also due to its com­pact size and min­i­mal power con­sump­tion. In fact, it can be pow­ered di­rectly from the tar­get com­puter via a USB ca­ble, which it also uses to sim­u­late a key­board, mouse, and other USB de­vices. So you have only one USB ca­ble - in one di­rec­tion it pow­ers NanoKVM, on the other it helps it to sim­u­late key­board mouse and other de­vices on a com­puter you want to man­age.

The de­vice is built on the open-source RISC-V proces­sor ar­chi­tec­ture, and the man­u­fac­turer even­tu­ally did re­lease the de­vice’s soft­ware un­der an open-source li­cense at the end of last year. (To be fair, one part of the code re­mains closed, but the com­mu­nity has al­ready found a suit­able open-source re­place­ment, and the man­u­fac­turer has promised to open this por­tion soon.)

However, the real is­sue is se­cu­rity.

Understandably, the com­pany was ea­ger to re­lease the de­vice as soon as pos­si­ble. In fact, an early ver­sion had a mi­nor hard­ware de­sign flaw - due to an in­cor­rect cir­cuit ca­ble, the de­vice some­times failed to de­tect in­com­ing HDMI sig­nals. As a re­sult, the com­pany re­called and re­placed all af­fected units free of charge. Software de­vel­op­ment also pro­gressed rapidly, but in such cases, the pri­mary fo­cus is typ­i­cally on get­ting ba­sic func­tion­al­ity work­ing, with se­cu­rity tak­ing a back­seat.

So, it’s not sur­pris­ing that the de­vel­op­ers made some se­ri­ous mis­steps - rushed de­vel­op­ment of­ten leads to stu­pid mis­takes. But some of the se­cu­rity flaws I dis­cov­ered in my quick (and by no means ex­haus­tive) re­view are gen­uinely con­cern­ing.

One of the first se­cu­rity analy­sis re­vealed nu­mer­ous vul­ner­a­bil­i­ties - and some rather bizarre dis­cov­er­ies. For in­stance, a se­cu­rity re­searcher even found an im­age of a cat em­bed­ded in the firmware. While the Sipeed de­vel­op­ers ac­knowl­edged these is­sues and rel­a­tively quickly fixed at least some of them, many re­main un­re­solved.

After pur­chas­ing the de­vice my­self, I ran a quick se­cu­rity au­dit and found sev­eral alarm­ing flaws. The de­vice ini­tially came with a de­fault pass­word, and SSH ac­cess was en­abled us­ing this pre­set pass­word. I re­ported this to the man­u­fac­turer, and to their credit, they fixed it rel­a­tively quickly. However, many other is­sues per­sist.

The user in­ter­face is rid­dled with se­cu­rity flaws - there’s no CSRF pro­tec­tion, no way to in­val­i­date ses­sions, and more. Worse yet, the en­cryp­tion key used for pass­word pro­tec­tion (when log­ging in via a browser) is hard­coded and iden­ti­cal across all de­vices. This is a ma­jor se­cu­rity over­sight, as it al­lows an at­tacker to eas­ily de­crypt pass­words. More prob­lem­atic, this needed to be ex­plained to the de­vel­op­ers. Multiple times.

Another con­cern is the de­vice’s re­liance on Chinese DNS servers. And con­fig­ur­ing your own (custom) DNS set­tings is quite com­pli­cated. Additionally, the de­vice com­mu­ni­cates with Sipeed’s servers in China - down­load­ing not only up­dates but also the closed-source com­po­nent men­tioned ear­lier. For this closed source com­po­nent it needs to ver­ify an iden­ti­fi­ca­tion key, which is stored on the de­vice in plain text. Alarmingly, the de­vice does not ver­ify the in­tegrity of soft­ware up­dates, in­cludes a strange ver­sion of the WireGuard VPN ap­pli­ca­tion (which does not work on some net­works), and runs a heav­ily stripped-down ver­sion of Linux that lacks sys­temd and apt. And these are just a few of the is­sues.

Were these prob­lems sim­ply over­sights? Possibly. But what ad­di­tion­ally raised red flags was the pres­ence of tcp­dump and air­crack - tools com­monly used for net­work packet analy­sis and wire­less se­cu­rity test­ing. While these are use­ful for de­bug­ging and de­vel­op­ment, they are also hack­ing tools that can be dan­ger­ously ex­ploited. I can un­der­stand why de­vel­op­ers might use them dur­ing test­ing, but they have ab­solutely no place on a pro­duc­tion ver­sion of the de­vice.

And then I dis­cov­ered some­thing even more alarm­ing - a tiny built-in mi­cro­phone that is­n’t clearly men­tioned in the of­fi­cial doc­u­men­ta­tion. It’s a minia­ture SMD com­po­nent, mea­sur­ing just 2 x 1 mm, yet ca­pa­ble of record­ing sur­pris­ingly high-qual­ity au­dio.

What’s even more con­cern­ing is that all the nec­es­sary record­ing tools are al­ready in­stalled on the de­vice! By sim­ply con­nect­ing via SSH (remember, the de­vice ini­tially used de­fault pass­words!), I was able to start record­ing au­dio us­ing the amixer and arecord tools. Once recorded, the au­dio file could be eas­ily copied to an­other com­puter. With a lit­tle ex­tra ef­fort, it would even be pos­si­ble to stream the au­dio over a net­work, al­low­ing an at­tacker to eaves­drop in real time.

Physically re­mov­ing the mi­cro­phone is pos­si­ble, but it’s not ex­actly straight­for­ward. As seen in the im­age, dis­as­sem­bling the de­vice is tricky, and due to the mi­cro­phone’s tiny size, you’d need a mi­cro­scope or mag­ni­fy­ing glass to prop­erly des­ol­der it.

To sum­ma­rize: the de­vice is rid­dled with se­cu­rity flaws, orig­i­nally shipped with de­fault pass­words, com­mu­ni­cates with servers in China, comes pre­in­stalled with hack­ing tools, and even in­cludes a built-in mi­cro­phone - fully equipped for record­ing au­dio - with­out clear men­tion of it in the doc­u­men­ta­tion. Could it get any worse?

I am pretty sure these is­sues stem from ex­treme neg­li­gence and rushed de­vel­op­ment rather than ma­li­cious in­tent. However, that does­n’t make them any less con­cern­ing.

That said, these find­ings don’t mean the de­vice is en­tirely un­us­able.

Since the de­vice is open-source, it’s en­tirely pos­si­ble to in­stall cus­tom soft­ware on it. In fact, one user has al­ready be­gun port­ing his own Linux dis­tri­b­u­tion - start­ing with Debian and later switch­ing to Ubuntu. With a bit of luck, this work could soon lead to of­fi­cial Ubuntu Linux sup­port for the de­vice.

This cus­tom Linux ver­sion al­ready runs the man­u­fac­tur­er’s mod­i­fied KVM code, and within a few months, we’ll likely have a fully in­de­pen­dent and sig­nif­i­cantly more se­cure soft­ware al­ter­na­tive. The only mi­nor in­con­ve­nience is that in­stalling it re­quires phys­i­cally open­ing the de­vice, re­mov­ing the built-in SD card, and flash­ing the new soft­ware onto it. However, in re­al­ity, this process is­n’t too com­pli­cated.

And while you’re at it, you might also want to re­move the mi­cro­phone… or, if you pre­fer, con­nect a speaker. In my test, I used an 8-ohm, 0.5W speaker, which pro­duced sur­pris­ingly good sound - es­sen­tially turn­ing the NanoKVM into a tiny mu­sic player. Actually, the idea is not so bad, be­cause PiKVM also in­cluded 2-way au­dio sup­port for their de­vices end of last year.

All this of course raises an in­ter­est­ing ques­tion: How many sim­i­lar de­vices with hid­den func­tion­al­i­ties might be lurk­ing in your home, just wait­ing to be dis­cov­ered? And not just those of Chinese ori­gin. Are you ab­solutely sure none of them have built-in minia­ture mi­cro­phones or cam­eras?

You can start with your iPhone - last year Apple has agreed to pay $95 mil­lion to set­tle a law­suit al­leg­ing that its voice as­sis­tant Siri recorded pri­vate con­ver­sa­tions. They shared the data with third par­ties and used them for tar­geted ads. “Unintentionally”, of course! Yes, that Apple, that cares about your pri­vacy so much.

And Google is do­ing the same. They are fac­ing a sim­i­lar law­suit over their voice as­sis­tant, but the lit­i­ga­tion likely won’t be set­tled un­til this fall. So no, small Chinese startup com­pa­nies are not the only prob­lem. And if you are wor­ried about Chinese com­pa­nies oblig­a­tions to­wards Chinese gov­ern­ment, let’s not for­get that U. S. com­pa­nies also have oblig­a­tions to co­op­er­ate with U.S. gov­ern­ment. While Apple is pub­licly claim­ing they do not co­op­er­ate with FBI and other U. S. agen­cies (because thy care about your pri­vacy so much), some me­dia re­vealed that Apple was hold­ing a se­ries se­cre­tive Global Police Summit at its Cupertino head­quar­ters where they taught po­lice how to use their prod­ucts for sur­veil­lance and polic­ing work. And as one of the po­lice of­fi­cers pointed out - he has “never been part of an en­gage­ment that was so col­lab­o­ra­tive.”. Yep.

If you want to test the built-in mi­cro­phone your­self, sim­ply con­nect to the de­vice via SSH and run the fol­low­ing two com­mands:

* arecord -Dhw:0,0 -d 3 -r 48000 -f S16_LE -t wav test.wav & > /dev/null & (this will cap­ture the sound to a file named test.wav)

Now, speak or sing (perhaps the Chinese na­tional an­them?) near the de­vice, then press Ctrl + C, copy the test.wav file to your com­puter, and lis­ten to the record­ing.

The Core Project is a highly mod­u­lar based sys­tem with com­mu­nity build ex­ten­sions.

It starts with a re­cent Linux ker­nel, vm­linuz, and our root filesys­tem and start-up scripts pack­aged with a ba­sic set of ker­nel mod­ules in core.gz. Core (11MB) is sim­ply the ker­nel + core.gz - this is the foun­da­tion for user cre­ated desk­tops, servers, or ap­pli­ances. TinyCore is Core + Xvesa.tcz + Xprogs.tcz + aterm.tcz + fltk-1.3.tcz + flwm.tcz + wbar.tcz

TinyCore be­comes sim­ply an ex­am­ple of what the Core Project can pro­duce, an 16MB FLTK/FLWM desk­top.

CorePlus ofers a sim­ple way to get started us­ing the Core phi­los­o­phy with its in­cluded com­mu­nity pack­aged ex­ten­sions en­abling easy em­bed­ded fru­gal or pen­drive in­stal­la­tion of the user’s choice of sup­ported desk­top, while main­tain­ing the Core prin­ci­pal of mounted ex­ten­sions with full pack­age man­age­ment.

It is not a com­plete desk­top nor is all hard­ware com­pletely sup­ported. It rep­re­sents only the core needed to boot into a very min­i­mal X desk­top typ­i­cally with wired in­ter­net ac­cess.

The user has com­plete con­trol over which ap­pli­ca­tions and/​or ad­di­tional hard­ware to have sup­ported, be it for a desk­top, a net­book, an ap­pli­ance, or server, se­lec­table by the user by in­stalling ad­di­tional ap­pli­ca­tions from on­line repos­i­to­ries, or eas­ily com­pil­ing most any­thing you de­sire us­ing tools pro­vided.

Our goal is the cre­ation of a no­madic ul­tra small graph­i­cal desk­top op­er­at­ing sys­tem ca­pa­ble of boot­ing from cdrom, pen­drive, or fru­gally from a hard drive. The desk­top boots ex­tremely fast and is able to sup­port ad­di­tional ap­pli­ca­tions and hard­ware of the users choice. While Tiny Core al­ways re­sides in ram, ad­di­tional ap­pli­ca­tions ex­ten­sions can ei­ther re­side in ram, mounted from a per­sis­tent stor­age de­vice, or in­stalled into a per­sis­tent stor­age de­vice.

We in­vite in­ter­ested users and de­vel­op­ers to ex­plore Tiny Core. Within our fo­rums we have an open de­vel­ope­ment model. We en­cour­age shared knowl­edge. We pro­mote com­mu­nity in­volve­ment and com­mu­nity built ap­pli­ca­tion ex­ten­sions. Anyone can con­tribute to our pro­ject by pack­ag­ing their fa­vorite ap­pli­ca­tion or hard­ware sup­port to run in Tiny Core. The Tiny Core Linux Team cur­rently con­sists of eight mem­bers who pe­ruse the fo­rums to as­sist from an­swer­ing ques­tions to help­ing pack­age new ex­ten­sions.

Join us here and on IRC Freenode #tinycorelinux.

Use tab to nav­i­gate through the menu items. Or: How the AI Bubble, Panic, and Unpreparedness Stole ChristmasWritten by Tom of Moore’s Law Is DeadAt the be­gin­ning of November, I or­dered a 32GB DDR5 kit for pair­ing with a Minisforum BD790i X3D moth­er­board, and three weeks later those very same sticks of DDR5 are now listed for a stag­ger­ing $330– a 156% in­crease in price from less than a month ago! At this rate, it seems likely that by Christmas, that DDR5 kit alone could be worth more than the en­tire Zen 4 X3D plat­form I planned to pair it with! How could this hap­pen, and more specif­i­cally — how could this hap­pen THIS quickly? Well, buckle up! I am about to tell you the story of Sam Altman’s Dirty DRAM Deal, or: How the AI bub­ble, panic, and un­pre­pared­ness stole Christmas…But be­fore I dive in, let me make it clear that my RAM kit’s 156% jump in price is­n’t a fluke or some ex­treme ex­am­ple of what’s go­ing on right now. Nope, and in fact, I’d like to pro­vide two more ex­am­ples of how how im­pos­si­ble it is be­com­ing to get ahold of RAM - these were pro­vided by a cou­ple of our sources within the in­dus­try:One source that works at a US Retailer, stated that a RAM Manufacturer called them in or­der to in­quire if they might buy RAM from  to stock up for their other cus­tomers. This would be like Corsair ask­ing a Best Buy if they had any RAM around.An­other source that works at a Prebuilt PC com­pany, was re­cently given an es­ti­mate for when they would re­ceive RAM or­ders if they placed them now…and they were told December…of 2026So what hap­pened?  Well, it all comes down to three per­fectly syn­er­gis­tic events:two un­prece­dented RAM deals that took every­one by sur­prise.The se­crecy and size of the deals trig­gered full-scale panic buy­ing from every­one else.The mar­ket had al­most zero safety stock left due to tar­iffs, worry about RAM prices over the sum­mer, and stalled equip­ment trans­fers.Be­low, we’re go­ing to walk through each of these fac­tors — and then I’m go­ing to warn you about which hard­ware cat­e­gories will be hit the hard­est, which prod­ucts are al­ready be­ing can­celled, and what you should buy  before the shelves turn into a re­peat of 2021–2022…because this is doomed to turn into much more than just RAM scarcity…deals with Samsung and SK Hynix for 40% of the worlds DRAM sup­ply.  Now, did OpenAI’s com­pe­ti­tion sus­pect some big RAM deals could be signed in late 2025? Yes. Ok, but did they think it would be deals this huge and with mul­ti­ple com­pa­nies? NO!  In fact, if you go back and read re­port­ing on Sam Altman’s now in­fa­mous trip to South Korea on October 1st, even just mere hours be­fore the mas­sive deals with Samsung and SK Hynix were  — most re­port­ing sim­ply men­tioned vague re­ports about Sam talk­ing to Samsung, SK Hynix, TSMC, and Foxconn. But the re­port­ing at the time was soft, al­most dis­mis­sive — “exploring ties,” “seeking co­op­er­a­tion,” “probing for part­ner­ships.” Nobody hinted that OpenAI was about to swal­low up to 40% of global DRAM out­put — even on morn­ing be­fore it hap­pened! Nobody saw this com­ing - this is clear in the lack of re­port­ing about the deals be­fore they were an­nounced, and every MLID Source who works in DRAM man­u­fac­tur­ing and dis­tri­b­u­tion in­sist this took every­one in the in­dus­try by sur­prise.To be clear - the shock was­n’t that OpenAI made a big deal, no, it was that they made two mas­sive deals this big, at the same time, with Samsung and SK Hynix si­mul­ta­ne­ously! In fact, ac­cord­ing to our sources - both com­pa­nies had no idea how big each oth­er’s deal was, nor how close to si­mul­ta­ne­ous they were. And this se­crecy mat­tered. It mat­tered a lot.Had Samsung known SK Hynix was about to com­mit a sim­i­lar chunk of sup­ply — or vice-versa — the pric­ing and terms would have likely been dif­fer­ent. It’s en­tirely con­ceiv­able they would­n’t have both agreed to sup­ply such a sub­stan­tial part of global sup­ply if they had known more…but at the end of the day - OpenAI did suc­ceed in keep­ing the cir­cles tight, lock­ing down the NDAs, and lever­ag­ing the fact that these com­pa­nies as­sumed the other was­n’t giv­ing up this much wafer vol­ume si­mul­ta­ne­ously…in or­der to make a sur­gi­cal strike on the global RAM sup­ply chain…and it’s worked so far…Part II — Instant Panic: How did we miss this?Imag­ine you’re run­ning a hy­per scaler, or maybe you’re a ma­jor OEM, or per­haps pre­tend that you are sim­ply one of OpenAI’s chief com­peti­tors: On October 1st of 2025, you would have woken up to the news that OpenAI had just cor­nered the mem­ory mar­ket more ag­gres­sively than any com­pany in the last decade, and you had­n’t heard even a mur­mur that this was com­ing be­fore­hand! Well, you would prob­a­bly make some fol­low-up calls to col­leagues in the in­dus­try, and then also quickly hear ru­mors that it was­n’t just you - also the two largest sup­pli­ers did­n’t even see each oth­er’s si­mul­ta­ne­ous co­op­er­a­tion with OpenAI com­ing ! You would­n’t go: “Well, that’s an in­ter­est­ing co­in­ci­dence”, no, you would say: “WHAT ELSE IS GOING ON THAT WE DON’T KNOW ABOUT?”Again — it’s not the size of the deals that’s solely the is­sue here, no, it’s also the of them. On October 1st sil­i­con val­ley ex­ec­u­tives and pro­cure­ment man­agers pan­icked over con­cerns like these:What other deals don’t we know about? Is this just the first of many?None of our DRAM sup­pli­ers warned us ahead of time! We have to as­sume they also won’t in the fu­ture, and that it’s pos­si­ble  of global DRAM could be bought up with­out us get­ting a sin­gle warn­ing!We know OpenAI’s com­peti­tors are al­ready panic-buy­ing!  If we don’t move we might be locked out of the mar­ket un­til 2028!OpenAI’s com­peti­tors, OEMs, and cloud providers scram­bled to se­cure what­ever in­ven­tory re­mained out of self-de­fense, and self-de­fense in a world that was en­tirely  due to the ac­cel­er­ant I’ll now ex­plain in Part III…Normally, the DRAM mar­ket has buffers: ware­houses of emer­gency stock, ex­cess wafer starts, older DRAM man­u­fac­tur­ing ma­chin­ery be­ing sold off to bud­get brands while the big brands up­grade their pro­duc­tion lines…but not in 2025, in 2025 those would-be buffers were de­pleted for three sep­a­rate rea­sons:Tar­iff Chaos. Companies had de­lib­er­ately re­duced how much DRAM they or­dered for their safety stock over the sum­mer of 2025 be­cause tar­iffs were chang­ing al­most weekly. Every RAM pur­chase risked be­ing made at the wrong mo­ment — and so fewer pur­chases were made.Prices had been falling all sum­mer. Because of the hes­i­tancy to pur­chase as much safety stock as usual, RAM prices were also gen­uinely falling over time.  And, ob­vi­ously when mem­ory is get­ting cheaper month over month, the thing you’d feel is pres­sured to buy a com­mod­ity that could be cheaper the next month…so every­one waited.Sec­ondary RAM Manufacturing Had Stalled. Budget brands nor­mally buy older DRAM fab­ri­ca­tion equip­ment from mega-pro­duc­ers like Samsung when Samsung up­grades their DRAM lines to the lat­est and great­est equip­ment.  This al­lows the DRAM mar­ket to more than it would oth­er­wise be­cause it makes any up­grad­ing of the fan­ci­est pro­duc­tion lines to still be change to the mar­ket. However, Korean mem­ory firms have been ter­ri­fied that re­selling old equip­ment to China-adjacent OEMs might trig­ger U.S. re­tal­i­a­tion…and so those ma­chines have been sit­ting idle in ware­houses since early spring.Yep, there was no cush­ion. OpenAI hit the mar­ket at the ex­act mo­ment it was least pre­pared. And now time for the biggest twist of all, a twist that’s ac­tu­ally , and there­fore should be get­ting dis­cussed by far more peo­ple in this writer’s opin­ion: OpenAI is­n’t even both­er­ing to buy fin­ished mem­ory mod­ules! No, their deals are un­prece­dent­edly only for raw wafers — un­cut, un­fin­ished, and not even al­lo­cated to a spe­cific DRAM stan­dard yet. It’s not even clear if they have de­cided yet on how or when they will fin­ish them into RAM sticks or HBM!  Right now it seems like these wafers will just be stock­piled in ware­houses — like a kid who hides the toy­box be­cause they’re afraid no­body wants to play with them, and thus self­ishly feels no­body but them should get the toys!And let’s just say it: Here is the un­com­fort­able truth Sam Altman is al­ways loath to ad­mit in in­ter­views: OpenAI is wor­ried about los­ing its lead. The last 18 months have seen com­peti­tors catch­ing up fast — Anthropic, Meta, xAI, and specif­i­cally Google’s Gemini 3 has got­ten a ton of praise just in the past week. Everyone’s chas­ing train­ing ca­pac­ity. Everyone needs mem­ory. DRAM is the lifeblood of scal­ing in­fer­ence and train­ing through­put. Cutting sup­ply to your ri­vals is not a con­spir­acy the­ory. It’s a busi­ness tac­tic as old as busi­ness it­self.  And so, when you con­sider how se­cre­tive OpenAI was about their deals with Samsung and SK Hynix, but ad­di­tion­ally how un­ready they were to im­me­di­ately uti­lize their ware­houses of DRAM wafers — it sure seems like a pri­mary goal of these deals was to , and not just an at­tempt to pro­tect OpenAI’s own sup­ply…Part V — What will be can­celled? What should you buy now?Al­right, now that we are done ex­plain­ing the , let’s get to the “ – be­cause even if the RAM short­age mirac­u­lously im­proves im­me­di­ately be­hind the scenes — even if the AI Bubble in­stantly popped or 10 com­pa­nies started tool­ing up for more DRAM ca­pac­ity this sec­ond (and many are, to be fair), at a min­i­mum the next six to nine months are al­ready screwed  See above: DRAM man­u­fac­tures are quot­ing 13-Month lead times for DDR5!  This is not a tem­po­rary blip. This could be a once-in-a-gen­er­a­tion shock. So what gets hit first? What gets hit hard­est? Well, be­low is an E through S-Tier rank­ing of which prod­ucts are “the most screwed”:S-Tier (Already Screwed — Too Late to Buy) -RAM it­self, ob­vi­ously. RAM prices have “exploded”. The det­o­na­tion is in the past.SSDs. These tends to fol­low DRAM pric­ing with a lag.RADEON GPUs. AMD does­n’t bun­dle RAM in their BOM kits to AIBs the way Nvidia does. In fact, the RX 9070 GRE 16GB this chan­nel leaked months ago is al­most cer­tainly can­celled ac­cord­ing to our sourcesXBOX. Microsoft did­n’t plan. Prices may rise and/​or sup­ply may dwin­dle in 2026.Nvidia GPUs. Nvidia main­tains large mem­ory in­ven­to­ries for its board part­ners, giv­ing them a buffer. But high-ca­pac­ity GPUs (like a hy­po­thet­i­cal 24GB 5080 SUPER) are on ice for now be­cause  stores were never suf­fi­ciently built up. In fact, Nvidia is qui­etly telling part­ners that their SUPER re­fresh “might” launch Q3 2026 — al­though most part­ners think it’s just a place­holder for when Nvidia ex­pects new ca­pac­ity to come on­line, and thus SUPER may never launch.C-Tier (Think about buy­ing soon)Lap­tops and phones. These com­pa­nies ne­go­ti­ate im­mense long-term con­tracts, so they’re not hit im­me­di­ately. But once their stock­piles run dry, watch out!D-Tier (Consider buy­ing soon, but there’s no rush)PlaySta­tion. Sony planned bet­ter than al­most any­one else. They bought ag­gres­sively dur­ing the sum­mer price trough, which is why they can af­ford a Black Friday dis­count while every­one else is rais­ing prices.Any­thing with­out RAM. Specifically CPUs that do not come with cool­ers could see price  over time since there could be a  in de­mand for CPUs if no­body has the RAM to feed them in sys­tems.???-Tier —Steam Machine. Valve keeps things quiet, but the big un­known is whether they pre-bought RAM months ago be­fore an­nounc­ing their much-hyped Steam Machine. If they did al­ready stock­pile an am­ple sup­ply of DDR5 - then Steam Machine should launch fine, but sup­ply could dry up tem­porar­ily at some point while they wait for prices to drop. However, if they did­n’t plan ahead - ex­pect a high launch price and very lit­tle re­sup­ply…it might even need to be can­celled or there might need to be a vari­ant of­fered with­out RAM in­cluded (BYO RAM Edition!).And that’s it! This last bit was the most im­por­tant part of the ar­ti­cle in this writer’s opin­ion — an at­tempt at help­ing you avoid get­ting burned. Well, ac­tu­ally, there is one other im­por­tant rea­son for this ar­ti­cle’s ex­is­tence I’ll tack onto the end — a hope that other peo­ple start dig­ging into what’s go­ing on at OpenAI.  I mean se­ri­ously — do we even have a sin­gle re­li­able au­dit of their fi­nan­cials to back up them out­ra­geously spend­ing this much money…  Heck, I’ve even heard from nu­mer­ous sources that OpenAI is “buying up the man­u­fac­tur­ing equip­ment as well” — and with­out moun­tains of con­crete proof, and/​or more in­put from ad­di­tional sources on what that re­ally means…I don’t feel I can touch that hot potato with­out get­ting burned…but I hope some­one else will…

Reddit user Dycus built a cam­era us­ing the sen­sor from an op­ti­cal mouse. After about 65 hours of work, Dycus had a low-res­o­lu­tion black-and-white cam­era with mul­ti­ple shoot­ing modes, housed in a nifty 3D-printed body.

PetaPixel has pre­vi­ously re­ported on sim­i­lar pro­jects that turn old op­ti­cal com­puter mice into func­tional cam­eras, but Dycus’ pro­ject is unique in that he de­signed a full-blown cam­era.

Optical com­puter mice work by de­tect­ing move­ment with a pho­to­elec­tric cell (or sen­sor) and a light. The light is emit­ted down­ward, strik­ing a desk or mousepad, and then re­flect­ing to the sen­sor. The sen­sor has a lens to help di­rect the re­flected light, en­abling the mouse to con­vert pre­cise phys­i­cal move­ment into an in­put for the com­put­er’s on-screen cur­sor. The way the re­flected changes in re­sponse to move­ment is trans­lated into cur­sor move­ment val­ues.

It’s a clever so­lu­tion for a fun­da­men­tal com­puter prob­lem: how to con­trol the cur­sor. For most com­puter users, that’s fine, and they can hap­pily use their mouse and go about their day. But when Dycus came across a PCB from an old op­ti­cal mouse, which they had saved be­cause they knew it was pos­si­ble to read im­ages from an op­ti­cal mouse sen­sor, the itch to build a mouse-based cam­era was too much to ig­nore.

The new op­ti­cal mouse cam­era has a lot of neat fea­tures, in­clud­ing mul­ti­ple shoot­ing modes, nu­mer­ous color palettes (the cam­era it­self has 64 shades of gray), con­trol­lable ex­po­sure, and 32kB of on-cam­era stor­age to save up to 48 pic­tures. In ad­di­tion to a stan­dard sin­gle-shot mode, the cam­era also cap­tures quad shots and “smear” shots, which are panora­mas.

Posts from the elec­tron­ics

com­mu­nity on Reddit

“The panorama ‘smear shot’ is def­i­nitely my fa­vorite mode, it scans out one col­umn at a time across the screen as you sweep the cam­era,” Dycus writes on Reddit. “It’s scaled 2x ver­ti­cally but 1x hor­i­zon­tally, so you get ex­tra ‘temporal res­o­lu­tion’ hor­i­zon­tally if you do the sweep well.”

The op­ti­cal mouse cam­era can also record move­ments, like it would if it were in­te­grated into an ac­tual mouse, and con­vert mo­tion into draw­ings on the cam­er­a’s screen.

Given that the cam­era is­n’t even sniff­ing one megapixel ter­ri­tory — its stan­dard pho­tos are just 900 pix­els ver­sus the 1,000,000 re­quired to hit 1MP — the im­age qual­ity is not par­tic­u­larly im­pres­sive, but as Dycus notes and Game Boy Camera en­thu­si­asts can at­test, it’s not about the res­o­lu­tion, it’s about the fun fac­tor.

“Despite the low res­o­lu­tion, it’s eas­ily pos­si­ble to take rec­og­niz­able pic­tures of stuff,” Dycus says. “The ‘high’ color depth def­i­nitely helps. I’d like it to the Game Boy Camera (which I also en­joy), which is much higher res­o­lu­tion but only has four col­ors.”

Let’s say you’ve done a com­pu­ta­tion in Wolfram Language. And now you want to scale it up. Maybe 1000x or more. Well, to­day we’ve re­leased an ex­tremely stream­lined way to do that. Just wrap the scaled up com­pu­ta­tion in and off it’ll go to our new Wolfram Compute Services sys­tem. Then—in a minute, an hour, a day, or what­ever—it’ll let you know it’s fin­ished, and you can get its re­sults.

For decades I’ve of­ten needed to do big, crunchy cal­cu­la­tions (usually for sci­ence). With large vol­umes of data, mil­lions of cases, ram­pant com­pu­ta­tional ir­re­ducibil­ity, etc. I prob­a­bly have more com­pute ly­ing around my house than most peo­ple—these days about 200 cores worth. But many nights I’ll leave all of that com­pute run­ning, all night—and I still want much more. Well, as of to­day, there’s an easy so­lu­tion—for every­one: just seam­lessly send your com­pu­ta­tion off to Wolfram Compute Services to be done, at ba­si­cally any scale.

For nearly 20 years we’ve had built-in func­tions like and in Wolfram Language that make it im­me­di­ate to par­al­lelize sub­com­pu­ta­tions. But for this to re­ally let you scale up, you have to have the com­pute. Which now—thanks to our new Wolfram Compute Services—everyone can im­me­di­ately get.

The un­der­ly­ing tools that make Wolfram Compute Services pos­si­ble have ex­isted in the Wolfram Language for sev­eral years. But what Wolfram Compute Services now does is to pull every­thing to­gether to pro­vide an ex­tremely stream­lined all-in-one ex­pe­ri­ence. For ex­am­ple, let’s say you’re work­ing in a note­book and build­ing up a com­pu­ta­tion. And fi­nally you give the in­put that you want to scale up. Typically that in­put will have lots of de­pen­den­cies on ear­lier parts of your com­pu­ta­tion. But you don’t have to worry about any of that. Just take the in­put you want to scale up, and feed it to . Wolfram Compute Services will au­to­mat­i­cally take care of all the de­pen­den­cies, etc.

And an­other thing: , like every func­tion in Wolfram Language, is deal­ing with sym­bolic ex­pres­sions, which can rep­re­sent any­thing—from nu­mer­i­cal ta­bles to im­ages to graphs to user in­ter­faces to videos, etc. So that means that the re­sults you get can im­me­di­ately be used, say in your Wolfram Notebook, with­out any im­port­ing, etc.

OK, so what kinds of ma­chines can you run on? Well, Wolfram Compute Services gives you a bunch of op­tions, suit­able for dif­fer­ent com­pu­ta­tions, and dif­fer­ent bud­gets. There’s the most ba­sic 1 core, 8 GB op­tion—which you can use to just “get a com­pu­ta­tion off your own ma­chine”. You can pick a ma­chine with larger mem­ory—cur­rently up to about 1500 GB. Or you can pick a ma­chine with more cores—cur­rently up to 192. But if you’re look­ing for even larger scale par­al­lelism Wolfram Compute Services can deal with that too. Because can map a func­tion across any num­ber of el­e­ments, run­ning on any num­ber of cores, across mul­ti­ple ma­chines.

OK, so here’s a very sim­ple ex­am­ple—that hap­pens to come from some sci­ence I did a lit­tle while ago. Define a func­tion that ran­domly adds nonover­lap­ping pen­tagons to a clus­ter:

For 20 pen­tagons I can run this quickly on my ma­chine:

But what about for 500 pen­tagons? Well, the com­pu­ta­tional geom­e­try gets dif­fi­cult and it would take long enough that I would­n’t want to tie up my own ma­chine do­ing it. But now there’s an­other op­tion: use Wolfram Compute Services!

And all I have to do is feed my com­pu­ta­tion to :

Immediately, a job is cre­ated (with all nec­es­sary de­pen­den­cies au­to­mat­i­cally han­dled). And the job is queued for ex­e­cu­tion. And then, a cou­ple of min­utes later, I get an email:

Not know­ing how long it’s go­ing to take, I go off and do some­thing else. But a while later, I’m cu­ri­ous to check how my job is do­ing. So I click the link in the email and it takes me to a dash­board—and I can see that my job is suc­cess­fully run­ning:

I go off and do other things. Then, sud­denly, I get an email:

It fin­ished! And in the mail is a pre­view of the re­sult. To get the re­sult as an ex­pres­sion in a Wolfram Language ses­sion I just eval­u­ate a line from the email:

And this is now a com­putable ob­ject that I can work with, say com­put­ing ar­eas

One of the great strengths of Wolfram Compute Services is that it makes it easy to use large-scale par­al­lelism. You want to run your com­pu­ta­tion in par­al­lel on hun­dreds of cores? Well, just use Wolfram Compute Services!

Here’s an ex­am­ple that came up in some re­cent work of mine. I’m search­ing for a cel­lu­lar au­toma­ton rule that gen­er­ates a pat­tern with a “lifetime” of ex­actly 100 steps. Here I’m test­ing 10,000 ran­dom rules—which takes a cou­ple of sec­onds, and does­n’t find any­thing:

To test 100,000 rules I can use and run in par­al­lel, say across the 16 cores in my lap­top:

Still noth­ing. OK, so what about test­ing 100 mil­lion rules? Well, then it’s time for Wolfram Compute Services. The sim­plest thing to do is just to sub­mit a job re­quest­ing a ma­chine with lots of cores (here 192, the max­i­mum cur­rently of­fered):

A few min­utes later I get mail telling me the job is start­ing. After a while I check on my job and it’s still run­ning:

I go off and do other things. Then, af­ter a cou­ple of hours I get mail telling me my job is fin­ished. And there’s a pre­view in the email that shows, yes, it found some things:

And here they are—rules plucked from the hun­dred mil­lion tests we did in the com­pu­ta­tional uni­verse:

But what if we wanted to get this re­sult in less than a cou­ple of hours? Well, then we’d need even more par­al­lelism. And, ac­tu­ally, Wolfram Compute Services lets us get that too—us­ing . You can think of as a souped up ana­log of —mapping a func­tion across a list of any length, split­ting up the nec­es­sary com­pu­ta­tions across cores that can be on dif­fer­ent ma­chines, and han­dling the data and com­mu­ni­ca­tions in­volved in a scal­able way.

Because is a “pure ” we have to re­arrange our com­pu­ta­tion a lit­tle—mak­ing it run 100,000 cases of se­lect­ing from 1000 ran­dom in­stances:

The sys­tem de­cided to dis­trib­ute my 100,000 cases across 316 sep­a­rate “child jobs”, here each run­ning on its own core. How is the job do­ing? I can get a dy­namic vi­su­al­iza­tion of what’s hap­pen­ing:

And it does­n’t take many min­utes be­fore I’m get­ting mail that the job is fin­ished:

And, yes, even though I only had to wait for 3 min­utes to get this re­sult, the to­tal amount of com­puter time used—across all the cores—is about 8 hours.

Now I can re­trieve all the re­sults, us­ing to com­bine all the sep­a­rate pieces I gen­er­ated:

And, yes, if I wanted to spend a lit­tle more, I could run a big­ger search, in­creas­ing the 100,000 to a larger num­ber; and Wolfram Compute Services would seam­lessly scale up.

Like every­thing around Wolfram Language, Wolfram Compute Services is fully pro­gram­ma­ble. When you sub­mit a job, there are lots of op­tions you can set. We al­ready saw the op­tion which lets you choose the type of ma­chine to use. Currently the choices range from Basic1x8 (1 core, 8 GB) through Basic4x16 (4 cores, 16 GB) to “parallel com­pute” Compute192x384 (192 cores, 384 GB) and “large mem­ory” Memory192x1536 (192 cores, 1536 GB).

Different classes of ma­chine cost dif­fer­ent num­bers of cred­its to run. And to make sure things don’t go out of con­trol, you can set the op­tions (maximum time in sec­onds) and (maximum num­ber of cred­its to use).

Then there’s no­ti­fi­ca­tion. The de­fault is to send one email when the job is start­ing, and one when it’s fin­ished. There’s an op­tion that lets you give a name to each job, so you can more eas­ily tell which job a par­tic­u­lar piece of email is about, or where the job is on the web dash­board. (If you don’t give a name to a job, it’ll be re­ferred to by the UUID it’s been as­signed.)

The op­tion lets you say what no­ti­fi­ca­tions you want, and how you want to re­ceive them. There can be no­ti­fi­ca­tions when­ever the sta­tus of a job changes, or at spe­cific time in­ter­vals, or when spe­cific num­bers of cred­its have been used. You can get no­ti­fi­ca­tions ei­ther by email, or by text mes­sage. And, yes, if you get no­ti­fied that your job is go­ing to run out of cred­its, you can al­ways go to the Wolfram Account por­tal to top up your cred­its.

There are many prop­er­ties of jobs that you can query. A cen­tral one is . But, for ex­am­ple, gives you a whole as­so­ci­a­tion of re­lated in­for­ma­tion:

If your job suc­ceeds, it’s pretty likely will be all you need. But if some­thing goes wrong, you can eas­ily drill down to study the de­tails of what hap­pened with the job, for ex­am­ple by look­ing at .

If you want to know all the jobs you’ve ini­ti­ated, you can al­ways look at the web dash­board, but you can also get sym­bolic rep­re­sen­ta­tions of the jobs from:

For any of these job ob­jects, you can ask for prop­er­ties, and you can for ex­am­ple also ap­ply to abort them.

Once a job has com­pleted, its re­sult will be stored in Wolfram Compute Services—but only for a lim­ited time (currently two weeks). Of course, once you’ve got the re­sult, it’s very easy to store it per­ma­nently, for ex­am­ple, by putting it into the Wolfram Cloud us­ing [expr]. (If you know you’re go­ing to want to store the re­sult per­ma­nently, you can also do the right in­side your .)

Talking about pro­gram­matic uses of Wolfram Compute Services, here’s an­other ex­am­ple: let’s say you want to gen­er­ate a com­pute-in­ten­sive re­port once a week. Well, then you can put to­gether sev­eral very high-level Wolfram Language func­tions to de­ploy a sched­uled task that will run in the Wolfram Cloud to ini­ti­ate jobs for Wolfram Compute Services:

And, yes, you can ini­ti­ate a Wolfram Compute Services job from any Wolfram Language sys­tem, whether on the desk­top or in the cloud.

Wolfram Compute Services is go­ing to be very use­ful to many peo­ple. But ac­tu­ally it’s just part of a much larger con­stel­la­tion of ca­pa­bil­i­ties aimed at broad­en­ing the ways Wolfram Language can be used.

Mathematica and the Wolfram Language started—back in 1988—as desk­top sys­tems. But even at the very be­gin­ning, there was a ca­pa­bil­ity to run the note­book front end on one ma­chine, and then have a “remote ker­nel” on an­other ma­chine. (In those days we sup­ported, among other things, com­mu­ni­ca­tion via phone line!) In 2008 we in­tro­duced built-in par­al­lel com­pu­ta­tion ca­pa­bil­i­ties like and . Then in 2014 we in­tro­duced the Wolfram Cloud—both repli­cat­ing the core func­tion­al­ity of Wolfram Notebooks on the web, and pro­vid­ing ser­vices such as in­stant APIs and sched­uled tasks. Soon there­after, we in­tro­duced the Enterprise Private Cloud—a pri­vate ver­sion of Wolfram Cloud. In 2021 we in­tro­duced Wolfram Application Server to de­liver high-per­for­mance APIs (and it’s what we now use, for ex­am­ple, for Wolfram|Alpha). Along the way, in 2019, we in­tro­duced Wolfram Engine as a stream­lined server and com­mand-line de­ploy­ment of Wolfram Language. Around Wolfram Engine we built WSTPServer to serve Wolfram Engine ca­pa­bil­i­ties on lo­cal net­works, and we in­tro­duced WolframScript to pro­vide a de­ploy­ment-ag­nos­tic way to run com­mand-line-style Wolfram Language code. In 2020 we then in­tro­duced the first ver­sion of , to be used with cloud ser­vices such as AWS and Azure. But un­like with Wolfram Compute Services, this re­quired “do it your­self” pro­vi­sion­ing and li­cens­ing with the cloud ser­vices. And, fi­nally, now, that’s what we’ve au­to­mated in Wolfram Compute Services.

OK, so what’s next? An im­por­tant di­rec­tion is the forth­com­ing Wolfram HPCKit—for or­ga­ni­za­tions with their own large-scale com­pute fa­cil­i­ties to set up their own back ends to , etc. is built in a very gen­eral way, that al­lows dif­fer­ent “batch com­pu­ta­tion providers” to be plugged in. Wolfram Compute Services is ini­tially set up to sup­port just one stan­dard batch com­pu­ta­tion provider: . HPCKit will al­low or­ga­ni­za­tions to con­fig­ure their own com­pute fa­cil­i­ties (often with our help) to serve as batch com­pu­ta­tion providers, ex­tend­ing the stream­lined ex­pe­ri­ence of Wolfram Compute Services to on-premise or or­ga­ni­za­tional com­pute fa­cil­i­ties, and au­tomat­ing what is of­ten a rather fid­dly job process of sub­mis­sion (which, I must say, per­son­ally re­minds me a lot of the main­frame job con­trol sys­tems I used in the 1970s).

Wolfram Compute Services is cur­rently set up purely as a batch com­pu­ta­tion en­vi­ron­ment. But within the Wolfram System, we have the ca­pa­bil­ity to sup­port syn­chro­nous re­mote com­pu­ta­tion, and we’re plan­ning to ex­tend Wolfram Compute Services to of­fer this—al­low­ing one, for ex­am­ple, to seam­lessly run a re­mote ker­nel on a large or ex­otic re­mote ma­chine.

But this is for the fu­ture. Today we’re launch­ing the first ver­sion of Wolfram Compute Services. Which makes “supercomputer power” im­me­di­ately avail­able for any Wolfram Language com­pu­ta­tion. I think it’s go­ing to be very use­ful to a broad range of users of Wolfram Language. I know I’m go­ing to be us­ing it a lot.