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Pull re­quest overview

This PR changes the Git ex­ten­sion’s git.ad­dAICoAu­thor set­ting so that AI co-au­thor trail­ers are en­abled by de­fault, mak­ing the de­fault be­hav­ior au­to­mat­i­cally add a Co-authored-by trailer when AI-generated code con­tri­bu­tions are de­tected.

Changes:

Updates git.ad­dAICoAu­thor con­fig­u­ra­tion de­fault from “off” to “all”.

Copilot’s find­ings

Files re­viewed: 1/1 changed files

Comments gen­er­ated: 1

Screenshot Changes

Base: 3c1b53dd Current: eec3f9cf

Changed (3)

blocks-ci screen­shots changed

Replace the con­tents of test/​com­po­nent­Fix­tures/​blocks-ci-screen­shots.md with:

<!– auto-gen­er­ated by CI — do not edit man­u­ally –>

#### ed­i­tor/​codeEd­i­tor/​CodeEd­i­tor/​Dark 

#### ed­i­tor/​codeEd­i­tor/​CodeEd­i­tor/​Light 

NoiceBroice

ref­er­enced this pull re­quest in ThomasSnowden37/Harmoniq-Charts

Co-authored-by: Copilot <copi­lot@github.com>

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srid

men­tioned this pull re­quest

Merged

Open

mi­crosoft

locked as spam and lim­ited con­ver­sa­tion to col­lab­o­ra­tors

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Two weeks ago I wrote about Anthropic silently reg­is­ter­ing a Native Messaging bridge in seven Chromium-based browsers on every ma­chine where Claude Desktop was in­stalled [1]. The pat­tern was: in­stall on user launch of prod­uct A, write con­fig­u­ra­tion into the user’s in­stalls of prod­ucts B, C, D, E, F, G, H with­out ask­ing. Reach across ven­dor trust bound­aries. No con­sent di­a­log. No opt-out UI. Re-installs it­self if the user re­moves it man­u­ally, every time Claude Desktop is launched.

This week I dis­cov­ered the same pat­tern, ex­e­cuted by Google. Google Chrome is reach­ing into users’ ma­chines and writ­ing a 4 GB on-de­vice AI model file to disk with­out ask­ing. The file is named weights.bin. It lives in OptGuideOnDeviceModel. It is the weights for Gemini Nano, Google’s on-de­vice LLM. Chrome did not ask. Chrome does not sur­face it. If the user deletes it, Chrome re-down­loads it.

The le­gal analy­sis is the same one I gave for the Anthropic case. The en­vi­ron­men­tal analy­sis is new. At Chrome’s scale, the cli­mate bill for one model push, paid in at­mos­pheric CO2 by the en­tire planet, is be­tween six thou­sand and sixty thou­sand tonnes of CO2-equivalent emis­sions, de­pend­ing on how many de­vices re­ceive the push. That is the en­vi­ron­men­tal cost of one com­pany uni­lat­er­ally de­cid­ing that two bil­lion peo­ples’ de­fault browser will mass-dis­trib­ute a 4 GB bi­nary they did not re­quest.

This is, in my pro­fes­sional opin­ion, a di­rect breach of Article 5(3) of Directive 2002/58/EC (the ePri­vacy Directive) [2], a breach of the Article 5(1) GDPR prin­ci­ples of law­ful­ness, fair­ness, and trans­parency [3], a breach of Article 25 GDPR’s data-pro­tec­tion-by-de­sign oblig­a­tion [3], and an en­vi­ron­men­tal harm of a mag­ni­tude that would be a no­ti­fi­able event un­der the Corporate Sustainability Reporting Directive (CSRD) for any in-scope un­der­tak­ing [4].

What is on the disk and how it got there

On any ma­chine that has Chrome in­stalled, in the user pro­file, sits a di­rec­tory whose name is OptGuideOnDeviceModel. Inside it is a file called weights.bin. The file is ap­prox­i­mately 4 GB. It is the weights file for Gemini Nano. Chrome uses it to power fea­tures Google has mar­keted un­der names like “Help me write”, on-de­vice scam de­tec­tion, and other AI-assisted browser func­tions.

The file ap­peared with no con­sent prompt. There is no check­box in Chrome Settings la­belled “download a 4 GB AI model”. The down­load trig­gers when Chrome’s AI fea­tures are ac­tive, and those fea­tures are ac­tive by de­fault in re­cent Chrome ver­sions. On any ma­chine that meets the hard­ware re­quire­ments, Chrome treats the user’s hard­ware as a de­liv­ery tar­get and writes the model.

The cy­cle of dele­tion and re-down­load has been doc­u­mented across mul­ti­ple in­de­pen­dent re­ports on Windows in­stal­la­tions [5][6][7][8] - the user deletes, Chrome re-down­loads, the user deletes again, Chrome re-down­loads again. The only ways to make the dele­tion stick are to dis­able Chrome’s AI fea­tures through chrome://​flags or en­ter­prise pol­icy tool­ing that home users do not gen­er­ally have, or to unin­stall Chrome en­tirely [5]. On ma­cOS the file lands as mode 600 owned by the user (so it is deletable in prin­ci­ple) but Chrome holds the in­stall state in Local State af­ter the bytes are writ­ten, and as soon as the vari­a­tions server next tells Chrome the pro­file is el­i­gi­ble, the down­load fires again - the ar­chi­tec­ture is the same, only the file per­mis­sions dif­fer.

How I ver­i­fied this on a freshly cre­ated Apple Silicon pro­file

Most of the ex­ist­ing re­port­ing on this be­hav­iour is from Windows users who no­ticed their disk fill­ing up - use­ful, but Google could (and prob­a­bly will) try to char­ac­terise those re­ports as anec­dotes from non-rep­re­sen­ta­tive con­fig­u­ra­tions. So I went look­ing for a clean wit­ness on a dif­fer­ent plat­form.

The wit­ness I found is ma­cOS it­self. The ker­nel keeps a filesys­tem event log called .fseventsd - it records every file cre­ate, mod­ify and delete at the OS level, in­de­pen­dent of any ap­pli­ca­tion log­ging. Chrome can­not edit it, Google can­not re­motely reach it, and the page files that record the events sur­vive the dele­tion of the files they ref­er­ence.

I cre­ated a Chrome user-data di­rec­tory on 23 April 2026 to run an au­to­mated au­dit (one of the WebSentinel 100-site pri­vacy sweeps). The au­dit dri­ver is fully Chrome DevTools Protocol - it loads a page, dwells for five min­utes with no in­put, cap­tures events, closes Chrome be­tween sites - and the pro­file had re­ceived zero key­board or mouse in­put from a hu­man at any point in its ex­is­tence. Every “AI mode” sur­face in Chrome was un­touched - in fact every UI sur­face in Chrome was un­touched, the au­dit dri­ver only in­ter­acts with the doc­u­ment via CDP and the om­ni­box is never reached. By 29 April the pro­file con­tained 4 GB of OptGuideOnDeviceModel weights - and I knew it be­cause a rou­tine du -sh of the au­dit-pro­file di­rec­tory caught it dur­ing a cleanup pass.

I went back to .fseventsd to ask ex­actly when those 4 GB landed. ma­cOS gave me the an­swer, byte-pre­cise, in three se­quen­tial page files:

24 April 2026, 16:38:54 CEST (14:38:54 UTC) - Chrome cre­ates the OptGuideOnDeviceModel di­rec­tory in the au­dit pro­file (page file 0000000003f7f339).

24 April 2026, 16:47:22 CEST (14:47:22 UTC) - three con­cur­rent un­packer sub­processes spawn tem­po­rary di­rec­to­ries in /private/var/folders/…/com.google.Chrome.chrome_chrome_Unpacker_BeginUnzipping.*/. One of them (5xzqPo) writes weights.bin, man­i­fest.json, _metadata/verified_contents.json and on_de­vice_­mod­el_ex­e­cu­tion_­con­fig.pb. The sec­ond writes a Certificate Revocation List up­date. The third writes a browser pre­load-data up­date. Chrome batched a se­cu­rity up­date, a pre­load re­fresh and a 4 GB AI model into the same idle win­dow, as if they were equiv­a­lent (page file 00000000040c8855).

24 April 2026, 16:53:22 CEST (14:53:22 UTC) - the un­packed weights.bin is moved to its fi­nal lo­ca­tion at OptGuideOnDeviceModel/2025.8.8.1141/weights.bin along with adapter_­cache.bin, en­coder_­cache.bin, _metadata/verified_contents.json and the ex­e­cu­tion con­fig. Concurrently four ad­di­tional model tar­gets (numbered 40, 49, 51 and 59 in Chrome’s op­ti­miza­tion-guide enum) reg­is­ter fresh en­tries in op­ti­miza­tion_guide_­mod­el_­s­tore - these are the smaller text-safety and prompt-rout­ing mod­els that pair with the LLM. None of these tar­gets ex­isted in the pro­file be­fore this mo­ment (page file 00000000040d0f9c).

Total in­stall time, from di­rec­tory cre­ation to fi­nal move: 14 min­utes and 28 sec­onds. Total hu­man ac­tion against the pro­file dur­ing that win­dow: none. The au­dit dri­ver was ei­ther dwelling on a third-party home page or tran­si­tion­ing be­tween sites - the un­packer fired in the back­ground while a tab waited for a five-minute timer to ex­pire.

The nam­ing in­side that fsev­entsd record is, if any­thing, the most damn­ing de­tail. The temp di­rec­tory is com.google.Chrome.chrome_chrome_Un­pack­er_Be­gi­n­Un­zip­ping.5xzqPo - that pre­fix com.google.Chrome.chrome_chrome_* is the bun­dle ID and sub­process nam­ing con­ven­tion Google Chrome it­self uses. It is not com.google.Google­Up­dater.* and it is not com.google.Google­Soft­ware­Up­date.*. The writer is Chrome - the browser process the user has in­stalled and trusts to load web pages - reach­ing into the user’s filesys­tem on its own ini­tia­tive and lay­ing down a 4 GB ML bi­nary while the fore­ground tab does some­thing com­pletely un­re­lated.

Three fur­ther pieces of cor­rob­o­rat­ing ev­i­dence sit else­where on the same ma­chine:

Chrome’s own Local State JSON for the au­dit pro­file con­tains an op­ti­miza­tion_guide.on_de­vice block with mod­el_­val­i­da­tion_re­sult: { at­temp­t_­count: 1, re­sult: 2, com­po­nen­t_ver­sion: “2025.8.8.1141” }. Chrome ran the model. The com­po­nen­t_ver­sion matches the ver­sion string the fsev­entsd events recorded as the path com­po­nent. Two in­de­pen­dent wit­nesses, same arte­fact. The same block re­ports per­for­mance_­class: 6, vram_mb: “36864″ - Chrome char­ac­terised my hard­ware (read the GPU, read the uni­fied mem­ory to­tal) to de­cide whether I was el­i­gi­ble for the model push, be­fore any user-fac­ing AI fea­ture sur­faced.

Chrome’s own Local State JSON for the au­dit pro­file con­tains an op­ti­miza­tion_guide.on_de­vice block with mod­el_­val­i­da­tion_re­sult: { at­temp­t_­count: 1, re­sult: 2, com­po­nen­t_ver­sion: “2025.8.8.1141” }. Chrome ran the model. The com­po­nen­t_ver­sion matches the ver­sion string the fsev­entsd events recorded as the path com­po­nent. Two in­de­pen­dent wit­nesses, same arte­fact. The same block re­ports per­for­mance_­class: 6, vram_mb: “36864″ - Chrome char­ac­terised my hard­ware (read the GPU, read the uni­fied mem­ory to­tal) to de­cide whether I was el­i­gi­ble for the model push, be­fore any user-fac­ing AI fea­ture sur­faced.

Chrome’s ChromeFeatureState for the au­dit pro­file lists OnDeviceModelBackgroundDownload<OnDeviceModelBackgroundDownload and ShowOnDeviceAiSettings<OnDeviceModelBackgroundDownload in the en­able-fea­tures block. The first flag is what trig­gers the silent down­load. The sec­ond flag is what re­veals the on-de­vice AI sec­tion in chrome://​set­tings. Both are gated by the same roll­out flag - which means that by Chrome’s own ar­chi­tec­ture, the in­stall be­gins be­fore the user has any set­tings UI in which to refuse it. The set­tings page that would let you dis­cover the fea­ture ex­ists is en­abled in lock­step with the in­stall - it is de­sign, not over­sight.

Chrome’s ChromeFeatureState for the au­dit pro­file lists OnDeviceModelBackgroundDownload<OnDeviceModelBackgroundDownload and ShowOnDeviceAiSettings<OnDeviceModelBackgroundDownload in the en­able-fea­tures block. The first flag is what trig­gers the silent down­load. The sec­ond flag is what re­veals the on-de­vice AI sec­tion in chrome://​set­tings. Both are gated by the same roll­out flag - which means that by Chrome’s own ar­chi­tec­ture, the in­stall be­gins be­fore the user has any set­tings UI in which to refuse it. The set­tings page that would let you dis­cover the fea­ture ex­ists is en­abled in lock­step with the in­stall - it is de­sign, not over­sight.

The GoogleUpdater logs record the on-de­vice-model con­trol com­po­nent (appid {44fc7fe2 – 65ce-487c-93f4-edee46eeaaab}) be­ing down­loaded from http://​edgedl.me.gvt1.com/​edgedl/​dif­f­gen-puf­fin/%​7B44fc7fe2 – 65ce-487c-93f4-edee46eeaaab%7D/… - a 7 MB com­pressed con­trol file that ar­rived on 20 April 2026, three days be­fore the au­dit pro­file in ques­tion was cre­ated. That is the up­stream con­trol plane: it is pro­file-in­de­pen­dent, it is launched au­to­mat­i­cally by a LaunchAgent that fires every hour, and the URL is plain HTTP (the in­tegrity is ver­i­fied by the CRX-3 sig­na­ture in­side the pack­age, not by trans­port se­cu­rity). The con­trol com­po­nent gives Chrome the man­i­fest point­ing at the ac­tual weights, and Chrome’s in-process OnDeviceModelComponentInstaller - a sep­a­rate code path from GoogleUpdater - then fetches the multi-GB weights di­rect from Google’s CDN.

The GoogleUpdater logs record the on-de­vice-model con­trol com­po­nent (appid {44fc7fe2 – 65ce-487c-93f4-edee46eeaaab}) be­ing down­loaded from http://​edgedl.me.gvt1.com/​edgedl/​dif­f­gen-puf­fin/%​7B44fc7fe2 – 65ce-487c-93f4-edee46eeaaab%7D/… - a 7 MB com­pressed con­trol file that ar­rived on 20 April 2026, three days be­fore the au­dit pro­file in ques­tion was cre­ated. That is the up­stream con­trol plane: it is pro­file-in­de­pen­dent, it is launched au­to­mat­i­cally by a LaunchAgent that fires every hour, and the URL is plain HTTP (the in­tegrity is ver­i­fied by the CRX-3 sig­na­ture in­side the pack­age, not by trans­port se­cu­rity). The con­trol com­po­nent gives Chrome the man­i­fest point­ing at the ac­tual weights, and Chrome’s in-process OnDeviceModelComponentInstaller - a sep­a­rate code path from GoogleUpdater - then fetches the multi-GB weights di­rect from Google’s CDN.

So we now have a four-way ev­i­dence chain - ma­cOS ker­nel filesys­tem events, Chrome’s own per-pro­file state, Chrome’s run­time fea­ture flags, and Google’s com­po­nent-up­dater logs - all four agree­ing on the same con­duct, and the con­duct is: a 4 GB AI model ar­rived on this user’s disk with­out con­sent, with­out no­tice, on a pro­file that re­ceived zero hu­man in­put, in a win­dow of 14 min­utes and 28 sec­onds, on a Tuesday af­ter­noon.

Reports of the OptGuideOnDeviceModel di­rec­tory and the weights.bin file have been cir­cu­lat­ing in com­mu­nity fo­rums for over a year - what is new in 2026 is the scale and the ver­i­fi­a­bil­ity. Chrome’s mar­ket share has held above 64% glob­ally [9][10], Chrome’s user base is be­tween 3.45 bil­lion and 3.83 bil­lion in­di­vid­u­als world­wide de­pend­ing on which 2026 es­ti­mate you trust [9][11], and Google has been rolling Gemini fea­tures into Chrome with in­creas­ing ag­gres­sion. The be­hav­iour is no longer af­fect­ing a mi­nor­ity of power users on a mi­nor­ity of plat­forms - it is af­fect­ing hun­dreds of mil­lions of de­vices, on every desk­top OS Chrome ships against.

The Anthropic com­par­i­son, point for point

The same dark-pat­tern play­book. I am re­peat­ing my cat­e­gori­sa­tion from the Claude Desktop ar­ti­cle [1] be­cause the pat­terns are iden­ti­cal and that is the point.

1. Forced bundling across trust bound­aries. Anthropic in­stalled Claude Desktop, then wrote into Brave, Edge, Arc, Vivaldi, Opera, and Chromium. Google in­stalls Chrome, then writes a 4 GB AI model un­der the user’s pro­file di­rec­tory with­out au­tho­ri­sa­tion. The bi­nary is not Chrome. It is a sep­a­rately-trained ma­chine-learn­ing model, with a sep­a­rate pur­pose, a sep­a­rate data-pro­tec­tion pro­file, and a sep­a­rate con­sent foot­print.

2. Invisible de­fault, no opt-in. No di­a­logue at first launch. No check­box in Settings. The model is down­loaded; the user finds out about it months later when their disk fills up [5][6][7].

3. More dif­fi­cult to re­move than in­stall. Adding the file took zero clicks. Removing it re­quires (a) dis­cov­er­ing the file ex­ists, (b) un­der­stand­ing what it is, (c) nav­i­gat­ing into a hid­den user pro­file path, (d) delet­ing it (and on Windows, also clear­ing the read-only at­tribute first), and (e) ac­cept­ing that Chrome will silently re-down­load it on next el­i­gi­ble win­dow un­less the user also nav­i­gates chrome://​flags, en­ter­prise pol­icy, or plat­form-spe­cific con­fig­u­ra­tion tool­ing to dis­able the un­der­ly­ing Chrome AI fea­ture [5]. None of those steps is doc­u­mented in the place a nor­mal user looks - none of them is even hinted at in de­fault Chrome.

4. Pre-staging of ca­pa­bil­ity the user has not re­quested. The Nano model ex­ists on the user’s disk so that Chrome fea­tures that use it can run in­stantly when the user in­vokes them. The user has not in­voked any of those fea­tures. The model still sits there, tak­ing 4 GB.

5. Scope in­fla­tion through generic nam­ing. OptGuideOnDeviceModel is in­ter­nal Chrome jar­gon for “OptimizationGuide on-de­vice model stor­age”. A user look­ing at their disk us­age, even one who knows roughly what they are look­ing at, would not match OptGuideOnDeviceModel/weights.bin to “Gemini Nano LLM weights”. Accurate nam­ing would be GeminiNanoLLM/weights.bin. Google chose to ob­fus­cate the name.

6. Registration into re­sources the user has not con­fig­ured. A user who has not opened Chrome’s AI fea­tures still gets the model. A user who has opened them once and de­cided they were not in­ter­ested still gets the model. The file’s pres­ence is de­cou­pled from the user’s ac­tual use of any fea­ture it pow­ers.

7. Documentation gap. Google’s user-fac­ing doc­u­men­ta­tion about Chrome’s AI fea­tures does not, with the promi­nence pro­por­tion­ate to a 4 GB silent down­load, tell the user that the cost of the fea­ture be­ing avail­able is a 4 GB file ap­pear­ing on their de­vice. The be­hav­iour is doc­u­mented in places a cu­ri­ous ad­min will find. It is not doc­u­mented in the place a reg­u­lar user looks be­fore in­stalling Chrome or be­fore Chrome de­cides to be­gin push­ing the model.

8. Automatic re-in­stall on every run. Same as Claude Desktop. Delete the file, Chrome re-cre­ates it. The user’s dele­tion is treated as a tran­sient state to be cor­rected, not as a di­rec­tive to be re­spected.

9. Retroactive sur­vival of any fu­ture user con­sent. If Google in fu­ture starts ask­ing users “would you like Chrome to down­load a 4 GB AI model”, that prompt does not retro-ac­tively le­git­imise the silent in­stalls that have al­ready hap­pened on hun­dreds of mil­lions of de­vices. The dam­age to the trust re­la­tion­ship is done. The bytes have moved. The at­mos­phere has been writ­ten to.

10. Code-signed, shipped through the nor­mal re­lease chan­nel. This is not test build be­hav­iour. It is Chrome sta­ble.

The “AI Mode” pill is the cherry on top

Here is the part that should make every pri­vacy lawyer in the au­di­ence put their cof­fee down. When Chrome 147 launches against an el­i­gi­ble pro­file, the om­ni­box - the ad­dress bar at the top of the win­dow, the most vis­i­ble piece of real es­tate in the en­tire browser - ren­ders an “AI Mode” pill to the right of the URL field. A rea­son­able user, see­ing “AI Mode” sit­ting in their browser’s most promi­nent UI el­e­ment in 2026, with the well-pub­li­cised ex­is­tence of on-de­vice LLMs in Chrome and a 4 GB Gemini Nano bi­nary al­ready silently in­stalled on their disk, is go­ing to draw what feels like an ob­vi­ous in­fer­ence - that the vis­i­ble AI Mode is us­ing the on-de­vice model, that their queries stay on the de­vice, that the lo­cal model is what pow­ers the lo­cal-look­ing sur­face.

Every part of that in­fer­ence is wrong. The AI Mode pill in the Chrome 147 om­ni­box is a cloud-backed Search Generative Experience sur­face - every query the user types into it is sent over the net­work to Google’s servers for pro­cess­ing by Google’s hosted mod­els. The on-de­vice Nano model is not in­voked by the AI Mode UI flow at all. They are en­tirely sep­a­rate code paths - the most vis­i­ble AI af­for­dance in the browser does not use the lo­cal model the user has been silently given, and the fea­tures that do use the lo­cal model (Help-Me-Write in <textarea>, tab-group AI sug­ges­tions, smart paste, page sum­mary) are buried in textarea-con­text menus and tab-group right-click menus that the av­er­age user will dis­cover, on av­er­age, never.

Think about what that arrange­ment ac­tu­ally is. The user pays the stor­age cost of the silent in­stall (4 GB on disk, plus the band­width of the silent down­load). The user’s most vis­i­ble AI ex­pe­ri­ence - the pill they ac­tu­ally see and click - de­liv­ers no on-de­vice ben­e­fit at all be­cause it routes to Google’s servers re­gard­less. The on-de­vice model is there­fore a sunk cost im­posed on the user, with no off­set­ting trans­parency ben­e­fit at the sur­face where trans­parency would mat­ter most. To put it an­other way - if the on-de­vice in­stall had given the user a clear “your AI Mode queries stay on your de­vice” prop­erty, the in­stall would have a de­fen­si­ble pri­vacy fram­ing (worse stor­age, bet­ter data flow). It does not - the in­stall gives Google a fu­ture-op­tions re­source (the model can be in­voked by other Chrome sub­sys­tems with­out fur­ther server round-trips) at the user’s disk-and-band­width ex­pense, while the head­line AI sur­face con­tin­ues to send the user’s queries to Google as be­fore. The lo­cal model is a Google-side as­set po­si­tioned on the user’s de­vice - it is not a user-side as­set and one could ar­gue it is noth­ing but sleight-of-hand to hide that ac­tu­ally, the vis­i­ble AI mode is NOT us­ing the lo­cal model.

That arrange­ment, on its own, en­gages at least three of the de­cep­tive de­sign pat­tern fam­i­lies cat­a­logued in EDPB Guidelines 03/2022 [20]. It is mis­lead­ing in­for­ma­tion be­cause the vis­i­ble la­bel “AI Mode” cre­ates a false im­pres­sion about where pro­cess­ing oc­curs - the la­bel does not say “cloud-backed” or “queries sent to Google”, and a rea­son­able user with knowl­edge of on-de­vice AI will in­fer lo­cal­ity from the prox­im­ity of an on-de­vice 4 GB model on their disk. It is skip­ping be­cause the user is not given a mo­ment to choose be­tween lo­cal-only and cloud-backed AI sur­faces - both are switched on by the same up­stream roll­out, with no per-fea­ture con­sent. And it is hin­der­ing be­cause turn­ing AI Mode off does not also re­move the on-de­vice in­stall, and re­mov­ing the on-de­vice in­stall does not turn AI Mode off - the two are sep­a­rately con­trolled, and dis­cov­er­ing both con­trols re­quires know­ing about both chrome://​flags and chrome://​set­tings/​ai, nei­ther of which is ob­vi­ous in de­fault Chrome.

So: not just a non-con­sented in­stall, but a non-con­sented in­stall that dou­bles as cover for a par­al­lel cloud-backed sur­face that mis­rep­re­sents to the user where their typ­ing is be­ing processed. Both lay­ers com­pound the con­sent prob­lem.

Why this is un­law­ful in the EEA and the UK

Article 5(3) of Directive 2002/58/EC (the ePri­vacy Directive) pro­hibits the stor­ing of in­for­ma­tion, or the gain­ing of ac­cess to in­for­ma­tion al­ready stored, in the ter­mi­nal equip­ment of a sub­scriber or user, with­out the user’s prior, freely-given, spe­cific, in­formed, and un­am­bigu­ous con­sent, ex­cept where strictly nec­es­sary for the pro­vi­sion of an in­for­ma­tion-so­ci­ety ser­vice ex­plic­itly re­quested by the user [2]. The 4 GB Gemini Nano weights file is in­for­ma­tion stored in the user’s ter­mi­nal equip­ment. The user did not con­sent. The user has not re­quested any ser­vice that strictly re­quires a 4 GB on-de­vice LLM. Chrome is func­tional with­out the file. The Article 5(3) breach is di­rect.

Article 5(1) GDPR re­quires pro­cess­ing of per­sonal data to be law­ful, fair, and trans­par­ent to the data sub­ject [3]. Where the user’s hard­ware is pro­filed to de­ter­mine el­i­gi­bil­ity for the model push, where the in­stall events are logged on Google’s servers, and where the on-de­vice fea­tures the model pow­ers process user prompts (whether or not those prompts leave the de­vice), the law­ful­ness, fair­ness, and trans­parency of all of that pro­cess­ing de­pend on the user be­ing told, in plain lan­guage, what is hap­pen­ing. They are not.

Article 25 GDPR re­quires the con­troller to im­ple­ment ap­pro­pri­ate tech­ni­cal and or­gan­i­sa­tional mea­sures to en­sure that, by de­fault, only per­sonal data that are nec­es­sary for each spe­cific pur­pose are processed [3]. Pre-staging a 4 GB AI model on a user’s disk, against a con­tin­gency that the user might in fu­ture in­voke an AI fea­ture, is the ar­chi­tec­tural op­po­site of by-de­fault min­imi­sa­tion and the pro­fil­ing of the de­vice to de­ter­mine whether or not to push the model is not dif­fer­ent to the pro­fil­ing used to track you on­line and as such that pro­file con­tains per­sonal data and if the AI model is used, will process per­sonal data, so the GDPR ar­gu­ments are in scope and valid.

Under the UK GDPR and the Privacy and Electronic Communications Regulations 2003, the analy­sis is the same. Under the California Consumer Privacy Act, the ab­sence of a no­tice-at-col­lec­tion cov­er­ing this spe­cific cat­e­gory of pre-staged soft­ware puts Google’s CCPA no­tice pos­ture in ques­tion [12].

Then there are the crim­i­nal-law vi­o­la­tions un­der var­i­ous na­tional com­puter-mis­use statutes - which again can­not be over­stated.

ESG: the cli­mate cost of the silent push

The Anthropic case I wrote about was a desk­top ap­pli­ca­tion in­stalling a 350-byte JSON man­i­fest in seven di­rec­to­ries. The band­width and en­ergy cost of that, summed across all Claude Desktop users, was neg­li­gi­ble. The Chrome case is dif­fer­ent. Chrome is push­ing a 4 GB bi­nary across hun­dreds of mil­lions of de­vices. That has a mea­sur­able, quan­tifi­able, and frankly alarm­ing en­vi­ron­men­tal foot­print.

I am cal­cu­lat­ing this us­ing the same method­ol­ogy our WebSentinel au­dit plat­form ap­plies to web­site en­vi­ron­men­tal analy­sis [13]:

Energy in­ten­sity of net­work data trans­fer: 0.06 kWh per GB, the mid-band of Pärssinen et al. (2018) “Environmental im­pact as­sess­ment of on­line ad­ver­tis­ing”, Science of The Total Environment [14]. The pa­per re­ports a 0.04 – 0.10 kWh/​GB range de­pend­ing on the share of fixed-line vs mo­bile trans­fer and in­clu­sion of end-user de­vice en­ergy. 0.06 is a de­fen­si­ble mid-point.

Grid emis­sions fac­tor: 0.25 kg CO2e per kWh, the EEA / IEA com­pos­ite EU-27 elec­tric­ity-sup­ply fac­tor for 2024 re­port­ing [15]. Globally the fig­ure varies from ~0.10 kg/​kWh on mostly-re­new­able grids to over 0.70 kg/​kWh on coal-heavy grids; 0.25 is mid-band for a global push and is the fig­ure WebSentinel uses by de­fault.

Per-device cost of one Nano push

Bandwidth: 4 GB

Energy: 4 × 0.06 = 0.24 kWh per de­vice per push

CO2: 0.24 × 0.25 = 0.06 kg CO2e per de­vice per push

That is per de­vice, per push. A sin­gle down­load of the model. It does not in­clude re-down­loads trig­gered by the user try­ing and fail­ing to delete the file. It does not in­clude sub­se­quent up­dates to the model. It does not in­clude the on-de­vice in­fer­ence en­ergy when the model is ac­tu­ally used. It is just the one-time de­liv­ery cost to one de­vice.

Aggregated cost across the de­ploy­ment

Google does not pub­lish how many de­vices re­ceive the Nano push. The el­i­gi­bil­ity cri­te­ria gat­ing the push (a hard­ware “performance class” that Chrome com­putes from CPU class, GPU class, sys­tem RAM and avail­able VRAM - typ­i­cally ~16 GB uni­fied mem­ory or bet­ter on Apple Silicon, ~16 GB RAM and a dis­crete or in­te­grated GPU with suf­fi­cient VRAM on Windows and Linux) carve out the very low end of the con­sumer in­stall base, but the qual­i­fy­ing pop­u­la­tion is still enor­mous. I will use three il­lus­tra­tive de­ploy­ment bands so the reader can pick whichever they con­sider clos­est to re­al­ity. None of these bands is im­plau­si­bly large for a fea­ture that ships in de­fault-on Chrome.

To com­pare those num­bers to what an ESG re­port could com­pare to:

24 GWh (low band) is roughly the an­nual elec­tric­ity con­sump­tion of about 7,000 av­er­age UK house­holds [16].

24 GWh (low band) is roughly the an­nual elec­tric­ity con­sump­tion of about 7,000 av­er­age UK house­holds [16].

120 GWh (mid band) is roughly the an­nual elec­tric­ity con­sump­tion of about 36,000 av­er­age UK house­holds, or the an­nual out­put of a 14 MW wind tur­bine run­ning at typ­i­cal UK ca­pac­ity fac­tor.

120 GWh (mid band) is roughly the an­nual elec­tric­ity con­sump­tion of about 36,000 av­er­age UK house­holds, or the an­nual out­put of a 14 MW wind tur­bine run­ning at typ­i­cal UK ca­pac­ity fac­tor.

240 GWh (high band) is roughly the an­nual elec­tric­ity con­sump­tion of about 72,000 av­er­age UK house­holds, or the an­nual out­put of about 28 MW of in­stalled wind ca­pac­ity.

240 GWh (high band) is roughly the an­nual elec­tric­ity con­sump­tion of about 72,000 av­er­age UK house­holds, or the an­nual out­put of about 28 MW of in­stalled wind ca­pac­ity.

6,000 tonnes CO2e (low band) is roughly the an­nual emis­sions of 1,300 av­er­age pas­sen­ger cars in the EU [17].

6,000 tonnes CO2e (low band) is roughly the an­nual emis­sions of 1,300 av­er­age pas­sen­ger cars in the EU [17].

30,000 tonnes CO2e (mid band) is roughly the an­nual emis­sions of 6,500 cars, or one re­turn flight from London to Sydney for about 8,000 pas­sen­gers in econ­omy.

30,000 tonnes CO2e (mid band) is roughly the an­nual emis­sions of 6,500 cars, or one re­turn flight from London to Sydney for about 8,000 pas­sen­gers in econ­omy.

60,000 tonnes CO2e (high band) is roughly the an­nual emis­sions of 13,000 cars.

60,000 tonnes CO2e (high band) is roughly the an­nual emis­sions of 13,000 cars.

These are the de­liv­ery-only num­bers. They count the bytes tra­vers­ing the net­work ex­actly once. They do not count:

The roughly 4 GB × N de­vices of disk-stor­age cost, sus­tained, on user hard­ware. SSDs have a per-GB em­bod­ied car­bon cost of ap­prox­i­mately 0.16 kg CO2e per GB of NAND man­u­fac­tured [18]; for 1 bil­lion de­vices × 4 GB that is around 640,000 tonnes CO2e of em­bod­ied SSD al­lo­cated to a use case the user did not con­sent to. This is a one-off man­u­fac­tur­ing-car­bon im­pact, but the stor­age bur­den is borne in per­pe­tu­ity by user de­vices that could oth­er­wise have used the space for user data.

The on-de­vice in­fer­ence en­ergy when Nano is in­voked. Per in­fer­ence this is small. At 2 bil­lion daily Chrome users it is no longer small.

The re-down­load cy­cle for users who try to delete the file. Each suc­cess­ful re-trig­ger of the down­load is an­other 4 GB × 0.06 kWh × 0.25 kg = 0.06 kg CO2e per de­vice per re-down­load.

The fu­ture model up­dates. Gemini Nano is not a one-shot arte­fact; it is an evolv­ing model with pe­ri­odic weight re­freshes. Each re­fresh re­peats the cal­cu­la­tion.

In ESG-reporting lan­guage, the one-time push of the cur­rent model is a Scope 3 Category 11 (“use of sold prod­ucts”) emis­sion against Google, at­trib­ut­able to the user-side de­liv­ery of a bi­nary the user did not re­quest, in the op­er­a­tion of a free prod­uct Google dis­trib­utes [4].

Why the band­width side mat­ters in its own right

In ad­di­tion to the car­bon cost, the net­work-band­width cost is paid by ISPs, by mo­bile net­work op­er­a­tors, by users on me­tered con­nec­tions, and by every piece of net­work in­fra­struc­ture that has to carry an un­wanted 4 GB pay­load to a des­ti­na­tion that did not ask for it. Per the Pärssinen ref­er­ence, around 50% of that de­liv­ery en­ergy is in the ac­cess net­work and CDN edge, around 30% is in user-side equip­ment (router, mo­dem, NIC), and the re­main­der is in the core. None of that in­fra­struc­ture ex­ists for free. Every byte Chrome pushes is a byte that com­petes with bytes the user ac­tu­ally wanted.

For users on capped mo­bile data plans, par­tic­u­larly in re­gions where smart­phone-as-only-in­ter­net is dom­i­nant (much of Africa, much of South and Southeast Asia, most of Latin America), 4 GB of un­re­quested down­load is on the or­der of a mon­th’s data al­lowance, vapourised by Chrome on the user’s be­half. Google has not, to my knowl­edge, pub­lished any analy­sis of the wel­fare im­pact of this on the pop­u­la­tions whose in­ter­net ac­cess is me­tered.

Keep in mind that mo­bile data plans (4G and 5G) are used by many house­holds who do not have ac­cess to fiber, ca­ble or adsl and are used for desk­top de­vices as well as mo­bile - so the ar­gu­ment that Google won’t push this to mo­bile de­vices (although I have not found any­thing of­fi­cial to sup­port that ar­gu­ment any­way) will not fly.

What Google should have done

This is not a hard list. It is the same list I gave Anthropic in the Claude Desktop ar­ti­cle, ap­plied to Google.

Ask. First time Chrome is about to down­load the Nano model, pop a di­a­logue. “Chrome would like to down­load a 4 GB AI model file to your de­vice to power the fol­low­ing fea­tures. Allow, or skip and de­cide later.” Two but­tons. Done.

Ask. First time Chrome is about to down­load the Nano model, pop a di­a­logue. “Chrome would like to down­load a 4 GB AI model file to your de­vice to power the fol­low­ing fea­tures. Allow, or skip and de­cide later.” Two but­tons. Done.

Pull, not push. Trigger the down­load as a down­stream con­se­quence of the user in­vok­ing an AI fea­ture for the first time. Let the fea­ture it­self be the con­sent event. Do not pre-stage on a con­tin­gency.

Pull, not push. Trigger the down­load as a down­stream con­se­quence of the user in­vok­ing an AI fea­ture for the first time. Let the fea­ture it­self be the con­sent event. Do not pre-stage on a con­tin­gency.

Surface it. In chrome://​set­tings/, list the AI model files Chrome has down­loaded, their size, the fea­tures they power, and a “Remove and stop down­load­ing” but­ton per model. Make re­moval per­sis­tent, not a tran­sient state Chrome cor­rects on next launch.

Surface it. In chrome://​set­tings/, list the AI model files Chrome has down­loaded, their size, the fea­tures they power, and a “Remove and stop down­load­ing” but­ton per model. Make re­moval per­sis­tent, not a tran­sient state Chrome cor­rects on next launch.

Document it. Tell the user, plainly, in the Chrome de­scrip­tion on the Microsoft Store, in the Chrome in­staller, on the Google Chrome down­load page, that Chrome will down­load ad­di­tional model files of sub­stan­tial size on sup­ported hard­ware. Currently, this is es­sen­tially un­doc­u­mented to a nor­mal user.

Document it. Tell the user, plainly, in the Chrome de­scrip­tion on the Microsoft Store, in the Chrome in­staller, on the Google Chrome down­load page, that Chrome will down­load ad­di­tional model files of sub­stan­tial size on sup­ported hard­ware. Currently, this is es­sen­tially un­doc­u­mented to a nor­mal user.

Respect dele­tion. If the user deletes weights.bin, do not re-cre­ate it. If the user has a strong pref­er­ence about what is on their disk, the ap­pli­ca­tion is not in a po­si­tion to over­ride that pref­er­ence be­cause the ap­pli­ca­tion thinks it knows bet­ter.

Respect dele­tion. If the user deletes weights.bin, do not re-cre­ate it. If the user has a strong pref­er­ence about what is on their disk, the ap­pli­ca­tion is not in a po­si­tion to over­ride that pref­er­ence be­cause the ap­pli­ca­tion thinks it knows bet­ter.

Disclose at scale. Publish, in Google’s an­nual ESG re­port, the ag­gre­gate band­width and car­bon foot­print of all AI-feature model pushes to user de­vices, bro­ken down by re­gion. Treat it as the Scope 3 Category 11 emis­sion it is. Account for it.

Disclose at scale. Publish, in Google’s an­nual ESG re­port, the ag­gre­gate band­width and car­bon foot­print of all AI-feature model pushes to user de­vices, bro­ken down by re­gion. Treat it as the Scope 3 Category 11 emis­sion it is. Account for it.

Talking to 35 Strangers at the Gym

Published: May 1, 2026 Updated: May 5, 2026

Background

A cou­ple months ago, I was the Wizard of Loneliness. I had grad­u­ated from col­lege al­most two years prior and, while I had luck­ily found a job, I was un­suc­cess­ful in find­ing friends.

Each night, I would look up “how to make friends af­ter col­lege” and find the same ad­vice given every time: “do your hobby with other peo­ple, fre­quently”.

On pa­per, the gym seemed like the per­fect op­por­tu­nity to meet peo­ple since I would go there nearly every day; how­ever, ac­cord­ing to Reddit, there’s a num­ber of peo­ple who want to be left alone and can be ir­ri­tated if you in­ter­rupted their work­out to talk.

I am deeply afraid of ir­ri­tat­ing some­one or be­ing in awk­ward sit­u­a­tions. Here’s a list of things that I did as a re­sult of that fear:

Hesitated for a cou­ple min­utes be­fore wak­ing up my room­mate when the fire alarm went off

Hesitated for a cou­ple min­utes be­fore wak­ing up my room­mate when the fire alarm went off

Pretended I did­n’t know a child­hood friend when they said hi be­cause I did­n’t know how to act around peo­ple I used to know

Pretended I did­n’t know a child­hood friend when they said hi be­cause I did­n’t know how to act around peo­ple I used to know

Ignored peo­ple I knew from class in­stead of say­ing hi be­cause I did­n’t know for sure if they re­mem­bered me even though the class had only 10 peo­ple in it

Ignored peo­ple I knew from class in­stead of say­ing hi be­cause I did­n’t know for sure if they re­mem­bered me even though the class had only 10 peo­ple in it

So you can un­der­stand when I say that walk­ing up to some­one and start­ing a con­ver­sa­tion with them at the gym of all places is kinda ter­ri­fy­ing for me.

Unfortunately, there was no other good op­tion. My other hobby is pro­gram­ming, but the Syracuse Development group only meets up once a month, and ac­tiv­i­ties sug­gested by r/​Syra­cuse like vol­ley­ball and trivia night re­quire you to al­ready have friends. I did­n’t have a choice. If I wanted friends, I would have to put in the work at the gym.

Problem Statement

I am lonely and have no friends.

Procedure

I de­cided to run a lit­tle ex­per­i­ment to find some friends.

Each day, for one month, I picked out one per­son to ap­proach. Usually it would be some­one I saw fre­quently at the gym.

If they were in the mid­dle of an ex­er­cise, I waited for them to fin­ish their set.

Then, I would ap­proach them, stand near them and wave to get their at­ten­tion, and then give them my open­ing line.

Initially, my open­ing line for every­one was “Hey I see you here all the time. You’re pretty strong. What’s your split?” After a week or so, I be­gan cus­tomiz­ing the open­ing line per per­son based on what I found in­ter­est­ing about them.

For in­stance, some­one was wear­ing a Boston hat and I was cu­ri­ous whether they went to school in Boston like I did, so I asked them about it. After the open­ing line, I tried to talk to them for 5 – 10 min­utes un­til they let me go. I tried not to be the one to end it be­cause I have a habit of end­ing con­ver­sa­tions early, but I did leave them alone if they ob­vi­ously did not want to talk.

Results

Here’s the raw data. I split it up by week and put it into these col­lapsi­ble things be­cause it takes up a lot of space. Click on each week to see the data for that week.

Description is a short de­scrip­tion of the per­son.

Length is how long the con­ver­sa­tion was. A short con­ver­sa­tion is 0 – 2 min­utes, a medium con­ver­sa­tion is 5 – 7 min­utes, and a long con­ver­sa­tion is 10+ min­utes.

Notes are just any­thing in­ter­est­ing about the con­ver­sa­tion or the per­son I was talk­ing to.

Aftermath is what hap­pened af­ter that con­ver­sa­tion.

Reflection

The first cou­ple days were ex­tremely dif­fi­cult. I had been con­di­tioned to be­lieve that ini­ti­at­ing a con­ver­sa­tion with a stranger was weird and it was tough to break free from that. As a re­sult, for the first few peo­ple, I would al­ways make a de­tour at the last sec­ond, i.e. make a trip to the wa­ter foun­tain. I chick­ened out! The so­lu­tion was to ap­proach the per­son as quickly as pos­si­ble so that I did­n’t have time to think about run­ning away.

Luckily, most peo­ple were re­cep­tive. I got a rush of dopamine when­ever some­one re­sponded pos­i­tively to my con­ver­sa­tion, so talk­ing to new peo­ple be­came strangely ad­dic­tive. I kept talk­ing to more and more new peo­ple each day un­til I talked to a whop­ping seven (SIX SEVENNN) new peo­ple in one day (this is why Week 3 has a lot of en­tries). It was crazy.

Something in­ter­est­ing I learned early on was that even if some­one had head­phones on, there was a good chance they were open to con­ver­sa­tion. I mean, I had my ear­buds in and I was will­ing to talk to any­body. Most peo­ple were just lis­ten­ing to mu­sic and took the head­phones off to talk.

People did­n’t al­ways re­spond pos­i­tively though. In Week 1 and Week 2, I came across a num­ber of peo­ple who were re­ally short with their re­sponses and did­n’t try to con­tinue the con­ver­sa­tion. They gave off the vibe that they did­n’t want to talk to me. It was re­ally awk­ward and al­most made me end the ex­per­i­ment.

But over time, I came to ac­cept that it’s ok if they did­n’t want to talk to me. That’s just one of the things you have to ex­pect when you do some­thing like this.

And be­ing in an awk­ward sit­u­a­tion is ac­tu­ally not that bad. It sucks in the mo­ment, but then you just take a few min­utes to calm down and then you move on with your life. You’re ok.

However, I did end up pulling back in Week 4 and Week 5. I felt like con­stantly talk­ing to more new peo­ple was pro­duc­ing di­min­ish­ing re­turns. I had al­ready es­tab­lished a con­nec­tion with many peo­ple at the gym, so it was a bet­ter use of my lim­ited time (remember I still have to work out!) to nur­ture those ex­ist­ing con­nec­tions into mean­ing­ful ones.

I ended up pri­or­i­tiz­ing the 5 – 6 peo­ple who seemed the most in­ter­ested in me.

One of these peo­ple is some­one I will re­fer to as “the other Asian guy”. I got a lot closer to him than ex­pected. We re­al­ized we had the same work­out rou­tine so we be­came gym bud­dies and started work­ing out to­gether. A few weeks later, he in­vited me to his apart­ment, where he cooked me a smash burger. His girl­friend showed me graphic pic­tures of what she was learn­ing in PA school too. Then, we watched a movie with their cat. I’m re­ally grate­ful that they were kind enough to have me over as a guest.

Also, some­thing new hap­pened: in­stead of scar­ing peo­ple away, I had a pos­i­tive im­pact on some­one.

These texts were from one of the peo­ple I pri­or­i­tized, the male SU stu­dent. He had re­cently moved to Syracuse and was strug­gling to make new friends. He re­lated to a cou­ple of my videos where I talked about the same strug­gles and was su­per ap­pre­cia­tive that I talked to him that day. The fol­low­ing week, we tried out Kofta Burger af­ter a rec­om­men­da­tion from my friend who lives down­town.

The burger was de­li­cious and we had a great time.

Despite my suc­cesses, my work is­n’t done. I re­al­ized near the end of the month that what I truly wanted was to con­sis­tently hang out with peo­ple on the week­ends. Unfortunately, most of the friends I’ve made are busy on the week­end. They’re tak­ing trips to visit loved ones, go­ing to the bar (I’m not that into drink­ing), or run­ning er­rands, so it’s hard to plan any­thing.

But I guess that’s a bet­ter prob­lem to have than eter­nal lone­li­ness.

A few months ago, I was googling “how to make friends af­ter col­lege” every night. Now I have peo­ple to text, peo­ple to wave to at the gym, and peo­ple who no­tice when I don’t show up for a few days. AND I be­came a more re­silient per­son who is un­afraid to do hard and scary things.

No more Wizard of Loneliness for me!

Heh this blew up on HackerNews. I want to give some more con­text for peo­ple who are un­sure if the gym was the right place to do this. And this is all in hind­sight; I did not re­al­ize this un­til now.

The gym I go to, Crunch Fitness, has a so­cial as­pect to it. While many peo­ple keep to them­selves, it’s com­mon to see peo­ple chat­ting. Sometimes they’re chat­ting in be­tween sets. Other times, they’re chat­ting on the tread­mill. The staff go out of their way to in­ter­act with us, and of­ten the peo­ple who did­n’t want to talk to me talk to other peo­ple! I guess they are more open with their friends.

The peo­ple at the gym are also re­ally sup­port­ive. I for­got to men­tion this but once, when I was do­ing hip thrusts, I messed up and did­n’t rerack the ma­chine cor­rectly. I fell on my butt and the ma­chine made a huge CLANK sound when it fell. Everybody turned to look at me. I was re­ally em­barassed. But then, one guy came and helped me re­turn the ma­chine to the start­ing po­si­tion while an­other guy swung by to make sure I was ok. He as­sured me that it hap­pened to every­one and to not let it get to me. I did­n’t know ei­ther of these peo­ple! They just wanted to help.

I don’t dis­agree that the gym is pri­mar­ily a place to work­out, but I think that it’s also a place where you can find com­mu­nity. Maybe my gym is spe­cial in how so­cial it is but maybe peo­ple are friend­lier than they ap­pear to be. I’m bet­ting on the lat­ter.

Modders, start your en­gines.

by William Judd

Yesterday, 10:29am

With the rather ex­cel­lent Steam Controller now on its way to the lucky few that man­aged to or­der one, Valve has re­leased a full set of CAD files for their new hard­ware. The idea is to let en­ter­pris­ing mod­ders cre­ate their own Steam Controller add-ons, like skins, charg­ing stands, grip ex­ten­ders or smart­phone mounts.

The Valve re­lease in­cludes files for the ex­ter­nal shell (“surface topol­ogy”) of the Controller and Puck, with a .STP, .STL and en­gi­neer­ing di­a­gram of each de­vice, with the lat­ter show­ing ar­eas that must re­main un­cov­ered to let the de­vice main­tain its sig­nal strength and oth­er­wise func­tion as de­signed.

Valve has pre­vi­ously re­leased CAD files for its Steam Deck hand­held, Valve Index VR suite and even the orig­i­nal Steam Controller a decade ago, so this re­lease is wel­comed but not un­ex­pected.

The re­lease is un­der a fairly re­stric­tive Creative Commons li­cense which al­lows for non-com­mer­cial use and re­quires at­tri­bu­tion and shar­ing of de­signs back to the com­mu­nity. However, the li­cense also sug­gests that com­mer­cial en­ti­ties in­ter­ested in mak­ing ac­ces­sories for the Steam Controller or its Puck can con­tact Valve di­rectly to dis­cuss terms.

What is your ul­ti­mate Steam Controller or Steam Controller Puck ac­ces­sory? Let us know in the com­ments be­low. For me, it would def­i­nitely be a smart­phone clip - play­ing through some­thing rel­a­tively low-stakes like Forza Horizon 6 via Moonlight game stream­ing on a phone would be slick.

[source steam­com­mu­nity.com]

Will is web­site ed­i­tor for Digital Foundry, spe­cial­is­ing in PC hard­ware, sim rac­ing and dis­play tech­nol­ogy.

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Bluesky

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Parkinson’s Law states that work ex­pands to fill the time avail­able. In the era of AI, work­ers now have a tool that ex­pands to fill what­ever a large lan­guage model can be per­suaded to gen­er­ate, which is to say, with­out limit.

Parkinson’s Law states that work ex­pands to fill the time avail­able. In the era of AI, work­ers now have a tool that ex­pands to fill what­ever a large lan­guage model can be per­suaded to gen­er­ate, which is to say, with­out limit.

What I have watched hap­pen in my pro­fes­sion in the last two years, I am still strug­gling to de­scribe. The first time I knew some­thing was wrong, roughly a year and a quar­ter ago, I no­ticed a col­league re­ply­ing to me us­ing AI. His re­sponse was ob­vi­ously gen­er­ated by Claude. The punc­tu­a­tion gave it away — em dashes where no one types em dashes, the rhyth­mic struc­ture, the con­fi­dent grasp of tech­nolo­gies I knew for a fact he did not un­der­stand. I sat with it for a while, weigh­ing whether to de­bate some­one who was vis­i­bly copy-past­ing ver­ba­tim from a model. The chan­nel was pub­lic, and I spent more time than I should have cor­rect­ing fun­da­men­tals. Eventually I stopped. He was not, in any mean­ing­ful sense, on the other side of the con­ver­sa­tion.

Generative AI can pro­duce work that looks ex­pert with­out be­ing ex­pert, and the fail­ure ar­rives in two shapes. The first is when novices in a field are able to pro­duce work that re­sem­bles what their se­niors pro­duce, faster or more ad­vanced than their judg­ment. The sec­ond is when peo­ple gen­er­ate ar­ti­facts in dis­ci­plines they were never trained in. The two fail­ures look sim­i­lar from a dis­tance and are not the same. Research has mostly mea­sured the first. The sec­ond is what it is miss­ing, and in my ex­pe­ri­ence it is the riskier of the two.

Cross do­main gen­er­a­tion

People who can­not write code are build­ing soft­ware. People who have never de­signed a data sys­tem are de­sign­ing data sys­tems. Most of it is not shipped; it is built, of­ten for many hours, pos­si­bly shown in­ter­nally with great vigor, used qui­etly, and oc­ca­sion­ally sur­faced to a client with­out much fan­fare. Workers can ob­sess over an idea, work­ing many hours over­time. There are a few prac­ti­tion­ers who use the cur­rent agen­tic tools to do com­plex things prop­erly, but they are scarce and as I find, typ­i­cally in code gen­er­a­tion. AI, for all its ca­pa­bil­i­ties at the level of the in­di­vid­ual, has not scaled prop­erly in my work­place.

I have a col­league, a care­ful and in­tel­li­gent per­son in a role that is not en­gi­neer­ing, who spent two months ear­lier this year build­ing a sys­tem that should have been de­signed by some­one with for­mal train­ing in data ar­chi­tec­ture. He used the tools well, by the stan­dards by which use of the tools is cur­rently mea­sured. He pro­duced a great deal of code, a great deal of doc­u­men­ta­tion, a great deal of what looked, to any­one who did not know what to look for, like progress. He could not, when asked, ex­plain how any of it ac­tu­ally worked. The work was wrong from the first day. The schemas, and more im­por­tantly the ob­jec­tives, were wrong in a way that would have been ob­vi­ous to any­one with two years in the field. Several of us did know. When opin­ions were voiced even as high as a V.P., he fought back. The room had been arranged in such a way that say­ing so was not a con­tri­bu­tion; his man­agers were too in­vested in the ap­pear­ance of mo­men­tum to want the ap­pear­ance dis­turbed. The work will con­tinue, in all prob­a­bil­ity, un­til it is shown to a stake­holder, and they de­cide not to in­vest.

This is the part of the phe­nom­e­non I find hard­est to write about. The tool did not make him a worse col­league. It made him able to im­per­son­ate, for months, a dis­ci­pline he had never trained in, and the im­per­son­ation was good enough that the in­sti­tu­tional in­cen­tives all bent to­ward let­ting him con­tinue. Perhaps it’s a fail­ure of man­age­ment, but I have been find­ing man­age­ment to be so ea­ger to em­brace AI that they’re will­ing to ac­cept the risk.

It would be tol­er­a­ble, per­haps, if the tool of­fered an hon­est as­sess­ment of what it had pro­duced. The Cheng et al. Stanford study pub­lished in Science this spring [1] con­firmed what every reg­u­lar user al­ready knew: lead­ing mod­els are roughly fifty per­cent more agree­able than hu­man re­spon­dents, af­firm­ing the user even where the af­fir­ma­tion is un­war­ranted. Berkeley CMR meta-analy­ses [4] found AI-literate users of­ten over­es­ti­mate their per­for­mance. Particularly in­ter­est­ing when work­ers stray out­side of their train­ing. An NBER study of sup­port agents [2] found gen­er­a­tive AI boosted novice pro­duc­tiv­ity by about a third while barely help­ing ex­perts. Harvard Business School re­searchers found the same pat­tern in con­sult­ing work [3]. So you have over­con­fi­dent, novices able to im­prove their in­di­vid­ual pro­duc­tiv­ity in an area of ex­per­tise they are un­able to re­view for cor­rect­ness. What could go wrong?

The con­duit prob­lem

A grow­ing body of work calls this out­put-com­pe­tence de­cou­pling [5]. In any pre­vi­ous era, the qual­ity of a piece of work was a more or less re­li­able sig­nal of the com­pe­tence of the per­son who pro­duced it. A novice es­say read like a novice es­say; novice code crashed in novice ways. AI has sev­ered that re­la­tion­ship. A novice now pro­duces work that does not be­tray the novice, be­cause the com­pe­tence the work re­flects is not the novice’s com­pe­tence at all. It is the sys­tem’s. The per­son, in the trans­ac­tion, be­comes a kind of con­duit, ca­pa­ble of rout­ing the out­put to a re­cip­i­ent and in­ca­pable of eval­u­at­ing it on the way through.

The skills of pro­duc­ing work and judg­ing it were de­lib­er­ately dis­tinct, but ac­com­plish­ing the work it­self used to teach the judg­ment. The first skill now be­longs, in large part, to the ma­chines. The sec­ond still be­longs to us, though fewer are both­er­ing to ac­quire or uti­lize it.

The ar­chi­tec­tural cri­tique that used to come from some­one who was taught, or who had built and bro­ken three of these be­fore now comes from a model with no em­bod­ied mem­ory of build­ing or break­ing any­thing. The slow­ness was not a tax on the real work; the slow­ness was the real work. It was how the work got good, and how the peo­ple pro­duc­ing the work got good, and how the firm whose name was on the work could promise the client that what they were buy­ing was a par­tic­u­lar kind of thing rather than a generic one.

The cur­rent gen­er­a­tion of agen­tic sys­tems is built around the premise that the hu­man is the bot­tle­neck — that the loop runs faster and cleaner with­out the awk­ward de­lay of some­one read­ing what is about to hap­pen and de­cid­ing whether it should. This is, in a great many cases, ex­actly back­wards. The hu­man in the loop is not a ves­tige of an ear­lier era; the hu­man is the only part of the loop with skin in the game. Removing the H from HITL is not an ef­fi­ciency. It is the aban­don­ment of the only mech­a­nism the sys­tem has for catch­ing it­self.

Slop on the in­side

Requirements doc­u­ments that were once a page are now twelve. Status up­dates that were once three sen­tences are now bul­leted sum­maries of bul­leted sum­maries. Retrospective notes, post-in­ci­dent re­ports, de­sign memos, kick­off decks: every ar­ti­fact that can be elon­gated is, by peo­ple who do not read what they pro­duce, for read­ers who do not read what they re­ceive. The cost of pro­duc­ing a doc­u­ment has fallen to nearly zero; the cost of read­ing one has not, and is in fact ris­ing, be­cause the reader must now sift the syn­thetic con­text for what­ever the doc­u­ment was orig­i­nally about. Each in­di­vid­ual de­ci­sion to elon­gate seems ra­tio­nal, and each is in­de­pen­dently re­warded — read­ers are more con­fi­dent in longer AI-generated ex­pla­na­tions whether or not the ex­pla­na­tions are cor­rect [5]. The col­lec­tive ef­fect is that the sig­nal in any given work­place is harder to find than it was be­fore any of this be­gan. The check­points have been hid­den, drowned in their own pa­per­work, even when the peo­ple drown­ing them were gen­uinely try­ing to “be brief”.

This is a new form of slop, and it is more ex­pen­sive than the pub­lic kind, be­cause the peo­ple pro­duc­ing it are be­ing paid a salary to do so. The pipeline of fu­ture ex­perts is thin­ning from both ends. The work that used to teach judg­ment is now done by the tool, and the en­try-level roles where the teach­ing hap­pened are be­ing cut on the the­ory that the tool can do the work. What this is caus­ing, in many of­fices in­clud­ing mine, is a great deal of mo­tion and very lit­tle of what mo­tion used to cre­ate.

The down­stream costs are ac­cu­mu­lat­ing quickly. Most of the pub­lic dis­cus­sion of AI slop has fo­cused on the flood into pub­lic mar­kets — a University of Florida mar­ket­ing study [6] be­ing among the more di­rect treat­ments. What is less re­marked upon is the same dy­namic play­ing out in­side or­ga­ni­za­tions: time wasted us­ing AI on tasks that did not need it, on ar­ti­facts no one will read, on processes that ex­ist only be­cause the tool made it cheap to con­struct them. On decks that spell out things that pre­vi­ously did­n’t even need to be said or were as­sumed.

What to do about it

What dis­ci­pline looks like, in this en­vi­ron­ment, is al­most em­bar­rass­ingly old-fash­ioned and may seem ob­vi­ous to most of you un­til you try to avoid it. Use the tool where you can ver­ify pre­cisely what it pro­duces. Never ask a model for con­fir­ma­tion; the tool agrees with every­one, and an agree­ment that costs the agreer noth­ing is worth noth­ing.

Generative AI does well on tasks where feed­back is fast, where be­ing ap­prox­i­mately right is good enough, where the hu­man re­mains the fi­nal ar­biter. Drafting a memo, gen­er­at­ing ex­am­ples, sum­ma­riz­ing ma­te­r­ial the reader could ver­ify if they cared to. The University of Illinois Generative AI guid­ance [7] and the PLOS Computational Biology “Ten Simple Rules” pa­per on AI in re­search [8], among the more care­ful doc­u­ments now cir­cu­lat­ing, list much of this ex­plic­itly: brain­storm­ing, copy­edit­ing, re­for­mu­lat­ing one’s own ideas, pat­tern de­tec­tion in data one al­ready un­der­stands.

In every rec­om­mended use, the hu­man sup­plies the judg­ment and the tool sup­plies the through­put. This is a stronger po­si­tion than hu­man-in-the-loop. The tool sits out­side the work, con­tribut­ing where in­vited and silent oth­er­wise, which is the op­po­site of what most agen­tic sys­tems are now be­ing built to do.

For firms, the com­pet­i­tive ad­van­tage of a firm whose work can be trusted has not dis­ap­peared; it has, if any­thing, ap­pre­ci­ated, be­cause so many of the fir­m’s com­peti­tors are qui­etly con­vert­ing them­selves into con­tent-gen­er­a­tion pipelines and count­ing on the client not to no­tice.

This is al­ready com­ing to a head. Deloitte has al­ready re­funded part of a $440,000 fee over an AI-hallucinated gov­ern­ment re­port. It could be a pro­duc­tion sys­tem built on a hal­lu­ci­nated spec­i­fi­ca­tion, or a se­nior en­gi­neer who re­al­izes they have spent the last year nom­i­nally re­view­ing work they could no longer com­pe­tently re­view. The reck­on­ing will not be sub­tle. The firms still do­ing the work prop­erly will be in a po­si­tion to charge for it. The firms that have hol­lowed them­selves out will dis­cover that what they hol­lowed out was the thing the client was pay­ing for.

Misunderstanding and mis­use of AI in the work­place is ram­pant. In many of the rooms I now find my­self in, ex­per­tise has been asked to look the other way: to de­liver faster, pro­duce more, in­te­grate the tools more deeply, get out of the way of the col­leagues who are “getting things done”. The ar­ti­facts are ac­cu­mu­lat­ing; the work is not. And some­where on the other side of all this out­put, a client is open­ing a de­liv­er­able, read­ing a sum­ma­rized list, and they may just choose to re­view it man­u­ally.

Disclaimer: I am not an ex­pert, or a writer. This is not an aca­d­e­mic ar­ti­cle. Whether I like it or not, I am at the precipice of AI. These are my ex­pe­ri­ences, in my work­place, with ref­er­ences to things that I think are relevent. If you take one thing away, take away that peo­ple are im­pres­sion­able crea­tures. Also, those that claimed this ar­ti­cle is iron­i­cally a ca­su­alty of it’s own com­plaint are 100% right, Kudos.

References

1. Sycophantic AI de­creases proso­cial in­ten­tions and pro­motes de­pen­dence (Cheng, Lee, Khadpe, Yu, Han, & Jurafsky, 2026). Science.

2. Generative AI at Work (Brynjolfsson, Li, & Raymond, 2025). The Quarterly Journal of Economics, 140(2), 889 – 942. Also: NBER Working Paper No. 31161, April 2023.

3. Navigating the Jagged Technological Frontier (Dell’Acqua, McFowland, Mollick, et al., 2026). Organization Science. Originally HBS Working Paper No. 24 – 013, 2023.

4. Seven Myths About AI and Productivity: What the Evidence Really Says (Berkeley CMR, 2025). Meta-analysis con­firm­ing asym­met­ric AI pro­duc­tiv­ity gains and user over­con­fi­dence.

5. Beyond the Steeper Curve: AI-Mediated Metacognitive Decoupling (Koch, 2025). Longer AI ex­pla­na­tions make users more con­fi­dent re­gard­less of cor­rect­ness.

6. Generative AI and the mar­ket for cre­ative con­tent (Zou, Shi, & Wu, 2026). Forthcoming, Journal of Marketing Research.

7. Generative AI Guidance (University of Illinois). Recommended uses and lim­i­ta­tions of gen­er­a­tive AI in aca­d­e­mic and pro­fes­sional work.

8. Ten sim­ple rules for op­ti­mal and care­ful use of gen­er­a­tive AI in sci­ence (Helmy, Jin, et al., 2025). PLOS Computational Biology, 21(10), e1013588.

30.04.2026, 11:37 Uhr

Belgium will stop de­com­mis­sion­ing its nu­clear power plants, Prime Minister Bart De Wever an­nounced on Thursday.

The gov­ern­ment is go­ing to ne­go­ti­ate with op­er­a­tor ENGIE over the na­tion­al­iza­tion of the plants, De Wever said.

“This gov­ern­ment chooses safe, af­ford­able, and sus­tain­able en­ergy. With less de­pen­dence on fos­sil im­ports and more con­trol over our own sup­ply,” he wrote on X.

ENGIE said it signed a let­ter of in­tent with the Belgian gov­ern­ment on ex­clu­sive ne­go­ti­a­tions.

The agree­ment cov­ers the po­ten­tial ac­qui­si­tion of “the com­plete nu­clear fleet of seven re­ac­tors, the as­so­ci­ated per­son­nel, all nu­clear sub­sidiaries, as well as all as­so­ci­ated as­sets and li­a­bil­i­ties, in­clud­ing de­com­mis­sion­ing and dis­man­tling oblig­a­tions,” a press re­lease said.

A ba­sic agree­ment is ex­pected to be reached by October, it said.

Belgium orig­i­nally de­cided in 2003 to phase-out nu­clear power pro­duc­tion by 2025, but po­lit­i­cal de­bate and en­ergy se­cu­rity con­cerns have led to de­lays.

Last year the Belgian par­lia­ment voted by a large ma­jor­ity to end the nu­clear phase-out. De Wever’s gov­ern­ment also aims to build new nu­clear power plants.

Belgium has seven nu­clear re­ac­tors at two dif­fer­ent sites, al­though three re­ac­tors have al­ready been taken off the grid.

The fate of the age­ing in­stal­la­tions has been de­bated for decades. The coun­try is cur­rently heav­ily de­pen­dent on gas im­ports to cover its elec­tric­ity needs as it has been strug­gling to ex­pand re­new­able power gen­er­a­tion sig­nif­i­cantly.

Bart De Wever on X

ENGIE press re­lease

(c) 2026 dpa Deutsche Presse Agentur GmbH

news

Another brand back­flips and ad­mits that touch-sen­si­tive but­tons for fre­quently used con­trols were a mis­take, but only af­ter the nudge from cus­tomers.

Electric Cars

Mercedes-Benz joins the grow­ing list of man­u­fac­tur­ers lis­ten­ing to cus­tomers and ad­mit­ting that touch-sen­si­tive con­trols and bury­ing con­trols in menus were mis­takes.

The German brand re­mains com­mit­ted to of­fer­ing large screens in its mod­els, but has lis­tened to its cus­tomers and will of­fer phys­i­cal but­tons for key func­tions in fu­ture.

This is partly un­like Audi and Volkswagen, which have cho­sen to re­duce the size of their in­fo­tain­ment screens to make room for the re­turn­ing phys­i­cal con­trols.

The up­com­ing GLC and C-Class will be of­fered with the 39.1-inch MBUX ‘Hyperscreen’ that cov­ers al­most the en­tire width of the dash­board, but with phys­i­cal but­tons in front of the dual wire­less charg­ers, along with phys­i­cal but­tons and switches re­turn­ing to the steer­ing wheel.

Mercedes-Benz Sales boss Mathias Geisen, when speak­ing to Autocar, said the brand has changed its course: “Customers told us two years ago, ‘guys, nice idea, but it just does­n’t work for us’, so we changed that and made it more ana­logue.”

Physical but­tons, switches, and di­als will con­tinue to be in­cor­po­rated into up­com­ing mod­els, as the brand plans to blend its screen with the re­quired phys­i­cal con­trols.

He also ex­plained that “I’m a big be­liever in screens, be­cause I re­ally be­lieve if you want to con­nect, you have to make the magic work be­hind the screen.”

“But in our fu­ture prod­ucts, you will see more hard keys for spe­cific func­tions that cus­tomers want to have di­rect ac­cess for with hard keys.

“When we do car re­search clin­ics, cus­tomers are very clear: ‘We love the big screens, but we want to have [hard con­trols for] spe­cific func­tion­al­i­ties.’”

The brand will also of­fer a cus­tomis­able wall­pa­per el­e­ment for the near me­tre-wide seam­less touch­screen, a choice that its sales boss ad­mits was brought be­cause phones are such a huge part of peo­ple’s lives and they are used to that level of tech­nol­ogy.

“If you want to con­nect to the cus­tomer, you’ve got to find a way to trans­late this dig­i­tal ex­pe­ri­ence from your phone to the cus­tomer.”

The new-gen­er­a­tion GLC SUV will show­case the brand’s new MB.EA elec­tric ve­hi­cle plat­form when it ar­rives in the fourth quar­ter of 2026 (October to December), shared with the up­com­ing C-Class when it’s due early next year.

9 Images

Electric Cars Guide

Components

DNS

Services

DNS Nameservice

May 6, 2026 01:34 CESTMay 5, 2026 23:34 UTC

RESOLVED

All Services are up and run­ning.

May 5, 2026 23:28 CESTMay 5, 2026 21:28 UTC

INVESTIGATING

Frankfurt am Main, 5 May 2026 — DENIC eG is cur­rently ex­pe­ri­enc­ing a dis­rup­tion in its DNS ser­vice for .de do­mains. As a re­sult, all DNSSEC-signed .de do­mains are cur­rently af­fected in their reach­a­bil­ity. The root cause of the dis­rup­tion has not yet been fully iden­ti­fied. DENIC’s tech­ni­cal teams are work­ing in­ten­sively on analy­sis and on restor­ing sta­ble op­er­a­tions as quickly as pos­si­ble. Based on cur­rent in­for­ma­tion, users and op­er­a­tors of .de do­mains may ex­pe­ri­ence im­pair­ments in do­main res­o­lu­tion. Further up­dates will be pro­vided as soon as re­li­able find­ings on the cause and re­cov­ery are avail­able. DENIC asks all af­fected par­ties for their un­der­stand­ing. For fur­ther en­quiries, DENIC can be con­tacted via the usual chan­nels.

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