Stuff that’s in the code but not shipped yet. Feature-flagged, env-gated, or just com­mented out.

A vir­tual pet that lives in your ter­mi­nal. Species and rar­ity are de­rived from your ac­count ID. Persistent mode with mem­ory con­sol­i­da­tion be­tween ses­sions and au­tonomous back­ground ac­tions.Long plan­ning ses­sions on Opus-class mod­els, up to 30-minute ex­e­cu­tion win­dows.Con­trol Claude Code from your phone or a browser. Full re­mote ses­sion with per­mis­sion ap­provals.Run ses­sions in the back­ground with –bgtmuxSessions talk to each other over Unix do­main sock­ets.Be­tween ses­sions, the AI re­views what hap­pened and or­ga­nizes what it learned.

It was not a phone call. It was not a meet­ing. For thou­sands of Oracle em­ploy­ees across the globe, Tuesday morn­ing be­gan with a sin­gle email land­ing in their in­boxes just af­ter 6 a.m. EST — and by the time they fin­ished read­ing it, their ca­reers at one of the world’s largest tech­nol­ogy com­pa­nies were over.

Oracle has launched what an­a­lysts be­lieve could be the most ex­ten­sive lay­off in the com­pa­ny’s his­tory, with es­ti­mates sug­gest­ing the cuts will af­fect be­tween 20,000 and 30,000 em­ploy­ees — roughly 18% of its global work­force of ap­prox­i­mately 162,000 peo­ple. Workers in the United States, India, and other re­gions all re­ported re­ceiv­ing the same ter­mi­na­tion no­tice at nearly the same hour, sent un­der the name “Oracle Leadership.”

There was no heads-up from hu­man re­sources, no con­ver­sa­tion with a di­rect man­ager, and no ad­vance no­tice of any kind. Just an email.

The email that cir­cu­lated widely af­ter screen­shots were posted by af­fected work­ers on Reddit’s r/​em­ploy­eesO­fOr­a­cle com­mu­nity and the pro­fes­sional fo­rum Blind was brief and for­mu­laic. It told em­ploy­ees that fol­low­ing a re­view of the com­pa­ny’s cur­rent busi­ness needs, a de­ci­sion had been made to elim­i­nate their roles as part of a broader or­ga­ni­za­tional change, that the day of the email was their fi­nal work­ing day, and that a sev­er­ance pack­age would be made avail­able af­ter sign­ing ter­mi­na­tion pa­per­work through DocuSign.

Employees were also in­structed to up­date their per­sonal email ad­dresses to re­ceive sub­se­quent com­mu­ni­ca­tions, in­clud­ing sep­a­ra­tion de­tails and an­swers to fre­quently asked ques­tions. For many, ac­cess to in­ter­nal pro­duc­tion sys­tems was re­voked al­most im­me­di­ately af­ter the mes­sage ar­rived.

Based on ac­counts shared across both Reddit and Blind, the cuts were wide­spread and, in some units, se­vere. Among the teams re­ported to be most af­fected:

RHS (Revenue and Health Sciences) — em­ploy­ees de­scribed a re­duc­tion in force of at least 30%, with 16 or more en­gi­neers from in­di­vid­ual busi­ness units cut in a sin­gle ac­tion.

SVOS (SaaS and Virtual Operations Services) — sim­i­larly re­ported a 30% or greater re­duc­tion, with man­ager-level roles in­cluded in the sweep.

At least one man­ager was con­firmed among those let go, and af­fected em­ploy­ees in India said the sev­er­ance struc­ture is ex­pected to fol­low a stan­dard for­mula based on years of ser­vice, paid out in months. Any un­vested re­stricted stock units, how­ever, were for­feited im­me­di­ately.

Workers who had vested stock were told they would re­tain ac­cess to those shares through Fidelity. Some em­ploy­ees noted April 3 as their for­mal last work­ing day, with a one-month gar­den leave pe­riod to fol­low. Separately, posts on Blind al­leged that Oracle had re­cently in­stalled mon­i­tor­ing soft­ware on com­pany-is­sued Mac lap­tops ca­pa­ble of log­ging all de­vice ac­tiv­ity, with warn­ings cir­cu­lat­ing among af­fected em­ploy­ees not to copy any files or code be­fore re­turn­ing their ma­chines.

The lay­offs are di­rectly tied to Oracle’s ag­gres­sive and debt-heavy ex­pan­sion into ar­ti­fi­cial in­tel­li­gence in­fra­struc­ture. According to analy­sis from TD Cowen, the job cuts are ex­pected to free up be­tween $8 bil­lion and $10 bil­lion in cash flow — money the com­pany ur­gently needs to fund a mas­sive build­out of AI data cen­ters.

The fi­nan­cial pic­ture sur­round­ing that ex­pan­sion is strik­ing. Oracle has taken on $58 bil­lion in new debt within just two months. Its stock has lost more than half its value since reach­ing a peak in September 2025. Multiple U. S. banks have re­port­edly stepped back from fi­nanc­ing some of its data cen­ter pro­jects. All of this is hap­pen­ing even as the com­pany posted a 95% jump in net in­come — reach­ing $6.13 bil­lion — last quar­ter.

The con­trast un­der­scores the scale of the bet Oracle is mak­ing: record prof­its on one side, a mount­ing debt load and tens of thou­sands of elim­i­nated jobs on the other. For the work­ers who woke up Tuesday morn­ing to that 6 a.m. email, the com­pa­ny’s am­bi­tions of­fered lit­tle com­fort.

OpenAI on Tuesday an­nounced that it closed a record-break­ing fund­ing round at a post-money val­u­a­tion of $852 bil­lion.

The round to­taled $122 bil­lion of com­mit­ted cap­i­tal, up from the $110 bil­lion fig­ure that the com­pany an­nounced in February. SoftBank co-led the round along­side other in­vestors, in­clud­ing Andreessen Horowitz and D. E. Shaw Ventures, OpenAI said.

OpenAI kick­started the ar­ti­fi­cial in­tel­li­gence boom with the launch of its ChatGPT chat­bot in 2022, and the com­pany has since bal­looned into one of the fastest-grow­ing com­mer­cial en­ti­ties on the planet. As of March, ChatGPT sup­ports more than 900 mil­lion weekly ac­tive users, in­clud­ing more than 50 mil­lion sub­scribers.

“AI is dri­ving pro­duc­tiv­ity gains, ac­cel­er­at­ing sci­en­tific dis­cov­ery, and ex­pand­ing what peo­ple and or­ga­ni­za­tions can build,” OpenAI said in a re­lease. “This fund­ing gives us the re­sources to con­tinue to lead at the scale this mo­ment de­mands.”

With the close of its lat­est fund­ing round, OpenAI CEO Sam Altman will be un­der pres­sure to jus­tify his com­pa­ny’s mas­sive val­u­a­tion, es­pe­cially as it gears up for a po­ten­tial IPO. The startup has been re­treat­ing from some hefty spend­ing plans and shut­ter­ing cer­tain fea­tures and prod­ucts in re­cent months, in­clud­ing its short-form video app Sora, as it looks to rein in costs.

Walk into my lab and the first thing you’ll no­tice is the dots. The walls are lined with clear boxes, each one la­beled, dated, and cov­ered in dot stick­ers. Some boxes are buried in dots of every color. Others have a few. Others are bare. You don’t know what they mean yet, but you can see the pat­tern. That’s the sys­tem. It costs three dol­lars, has no soft­ware, and I’ve been us­ing it for four years.

I’ve been col­lect­ing elec­tronic com­po­nents since uni­ver­sity in 2011. Resistors, ca­pac­i­tors, mi­cro­con­trollers, mo­tors, dri­vers, DC-DC con­vert­ers, dis­plays, am­pli­fiers, ser­vos, LEDs, con­nec­tors. The usual tra­jec­tory of some­one who keeps find­ing new pro­jects. At first, my col­lec­tion was small. A few tool­boxes held every­thing. Then I grad­u­ated, kicked it into high gear, and by 2017 the col­lec­tion had out­grown every con­tainer I owned.

I was stuck in an awk­ward mid­dle ground. Too many parts for no sys­tem at all, but I was still one per­son. I did­n’t have the prob­lems that DigiKey or Mouser have, where they need bar­codes on every­thing and a vast com­put­er­ized in­ven­tory. I was look­ing for some­thing sim­ple that made sense for the scale I was work­ing at.

The first thing I did was get rid of every opaque con­tainer I owned. Every tool­box, every parts or­ga­nizer with lit­tle pock­ets, any­thing I could­n’t see through. I re­placed every­thing with stan­dard­ized 4L clear boxes from Superstore.

I learned this les­son early and it stuck: if I can’t see what’s in a box, I for­get it ex­ists. Clear boxes fixed that. I started sort­ing parts into cat­e­gories that emerged nat­u­rally over time. A box for ca­pac­i­tors, a box for re­sis­tors, a box for mo­tors, a box for LEDs.

The parts or­ga­niz­ers with in­di­vid­ual pock­ets were the first to go. They seem like a good idea when your col­lec­tion is small, but as you keep adding parts, the fixed com­part­ments be­come a prob­lem. Components out­grow the pock­ets, and even­tu­ally you run out of pock­ets. The whole or­ga­nizer be­comes a con­straint in­stead of solv­ing the prob­lem. Clear boxes don’t have this prob­lem and the sys­tem can scale by sim­ply buy­ing more boxes.

As I worked on pro­jects over months and years, I started to build an in­tu­ition about which boxes I was reach­ing for and which ones were col­lect­ing dust. My box of bat­ter­ies was al­ways on my desk. My box of fuses had­n’t been opened in my en­tire mem­ory. But it was just a feel­ing. I could­n’t quan­tify it. I could­n’t tell you whether I opened my LED box twenty times last year or five. My mem­ory is not good enough to track us­age pat­terns across years of dif­fer­ent pro­jects.

And mean­while, I had a con­stant in­flux of new parts. I’d work on an LED pro­ject, then move on to some­thing that needed pneu­matic com­po­nents, so I’d or­der pumps and fit­tings. Then I’d get in­ter­ested in piezo­electrics and or­der a bunch of piezos. Parts kept be­ing added to my col­lec­tion but my avail­able space did not in­crease.

As Kirchhoff’s cur­rent law states, the cur­rent into a node must equal the cur­rent out. If I kept ac­quir­ing parts at this pace with­out get­ting rid of any­thing, I would even­tu­ally drown. I needed a way to fig­ure out what was worth keep­ing and what should go, so the sys­tem can reach a steady state.

I con­sid­ered RFID tags, bar­code scan­ners, a spread­sheet. All of them felt like too much. Then I found the sim­plest pos­si­ble so­lu­tion on AliExpress for a few dol­lars.

I or­dered sheets of col­ored dot stick­ers. Six mil­lime­ters in di­am­e­ter. Hundreds of them for al­most noth­ing.

Every box al­ready had a la­bel on the front with its cat­e­gory and the date I cre­ated the box. The new rule was sim­ple: every time I open a box, I place one col­ored dot sticker near the la­bel. That’s it. Use the box, add a dot.

I quickly re­al­ized that on days when I’m deep in a pro­ject, I might open the same box five or ten times. Tracking every sin­gle open­ing would be noise. So I re­fined the rule: one dot per box per day. If I open my LED box ten times on a Tuesday, it still gets one dot. What I ac­tu­ally care about is how many days per year I use a box.

Then, be­cause I had all of these dif­fer­ent col­ors, I de­cided to as­sign one color per year. I have over ten col­ors, so the sys­tem works for at least a decade. A piece of pa­per in my tech­ni­cal ref­er­ence binder maps each color to its year so I never for­get.

That’s the en­tire sys­tem. Sticker sheets cost a few dol­lars, and there is no data­base, no server, and no app. The sys­tem that works is the one sim­ple enough to do every day for four years.

I won­dered at first whether I’d ac­tu­ally keep up with it. Would I for­get? Would it be an­noy­ing to find a sticker sheet every time I opened a box?

Both prob­lems solved them­selves. I keep sheets of stick­ers in mul­ti­ple lo­ca­tions around the lab, so I’m al­ways within ar­m’s reach of one. Applying a dot is mus­cle mem­ory at this point. And for­get­ting turns out to be hard, be­cause the dots are their own re­minder. Even if the box I just opened has no dots, the neigh­bor­ing boxes are cov­ered in them. The vi­sual prompt is every­where.

Visitors al­ways ask about the dots as they’re im­pos­si­ble to miss. When I ex­plain the sys­tem and show how I add a dot when­ever I use a box, there’s usu­ally a pause, and then it clicks. A sin­gle dot­ted box does­n’t mean much on its own. It’s see­ing a whole shelf of them, some cov­ered and some bare, that makes it ob­vi­ous this is a sys­tem.

After four years, the data is hard to ar­gue with. Walk into my lab and you can read the shelves like a dash­board. Some boxes are cov­ered in dots of every color, used year af­ter year, pro­ject af­ter pro­ject. Others have a clus­ter of one color from a sin­gle pro­ject and noth­ing since. Others are com­pletely bare.

The biggest sur­prise was which parts turned out to be es­sen­tial. It was­n’t sen­sors, even though I had many dif­fer­ent kinds, it was­n’t spe­cial­ized com­po­nents or “cool” things. The most-dot­ted boxes are:

Glue. Tape. Stickers. General-purpose con­nec­tors. Batteries. Magnets. LEDs. DC-DC power con­vert­ers. USB-C to bar­rel jack ca­bles. Capacitors. Resistors. Mechanical tools like files, drill bits, and cut­ters. Calipers. SD cards and USB dri­ves. Rubber feet. Fasteners.

In ret­ro­spect, it makes a lot of sense. All of these things are cross-cut­ting con­cerns. Power com­po­nents like bat­ter­ies, DC-DC con­vert­ers, and USB-C ca­bles ap­pear in nearly every pro­ject. Connection com­po­nents like glue, tape, mag­nets, fas­ten­ers, and gen­eral-pur­pose con­nec­tors bridge dif­fer­ent sys­tems to­gether. Rubber feet show up when­ever any­thing needs to sit on a desk. These aren’t the ex­cit­ing parts. They’re the com­mon com­po­nents that nearly every pro­ject shares.

Even within a cat­e­gory, the dots re­veal pat­terns. My met­ric fas­tener boxes tell a clear story: M3 is by far the most used, with two boxes ded­i­cated to it. M6 is next be­cause I use it for op­ti­cal bread­boards. M2.5 barely gets dot­ted be­cause it’s spe­cial­ized for things like Raspberry Pi mount­ing holes.

Meanwhile, sen­sors barely got dot­ted. Fuses, piezo­elec­tric mod­ules, spe­cial­ized con­nec­tors: too ap­pli­ca­tion-spe­cific to be core. Discrete LCD mod­ules went un­used af­ter I started buy­ing mi­cro­con­trollers with in­te­grated dis­plays and but­tons. I use ca­pac­i­tors and re­sis­tors con­stantly, but in­duc­tors got used maybe twice in four years.

And then there were the tools I thought were es­sen­tial. My os­cil­lo­scope, func­tion gen­er­a­tor, and logic an­a­lyzer are com­monly rec­om­mended as must-have tools for any elec­tron­ics lab. Five dots on the os­cil­lo­scope in four years. I was gen­uinely sur­prised. I know for some peo­ple, in fields like RF, these tools are in­dis­pens­able. But in my work, they’re not. I would­n’t have had the con­fi­dence to say that with­out the data.

As I con­sol­i­dated boxes and in­tro­duced larger sizes, find­ing spe­cific parts in­side a box be­came frus­trat­ing. I went through three gen­er­a­tions of bags: zi­plock bags from the gro­cery store, then clear logo-free bags from AliExpress (which wrin­kled), then thick-walled clear bags that were more ex­pen­sive but worth it. If you’re start­ing from scratch, skip the first two and go straight to thick clear bags.

I started see­ing the whole sys­tem like a file sys­tem on a com­puter. Boxes are top-level di­rec­to­ries. Bags are sub­di­rec­to­ries. Parts are files. Bags can con­tain other bags. The Johnny Decimal sys­tem rec­om­mends no more than ten items per cat­e­gory. I don’t fol­low that rigidly, but I agree with the spirit: in­side a box, aim for roughly ten bags. Inside a bag, aim for roughly ten sub-bags max. When things get too crowded, sub­di­vide.

Every bag gets a hand­writ­ten la­bel with its con­tents and the cur­rent date. I put dates on every­thing. Time turns out to be a great uni­ver­sal or­ga­nizer, just like how a photo col­lec­tion is won­der­fully or­ga­nized by date more than by any other sin­gle di­men­sion.

Eventually my lab over­flowed and I had to make real de­ci­sions about what stays and what goes. The dots helped me make those de­ci­sions.

I set up three tiers. My most-dot­ted boxes stay within fif­teen feet of my desk. Less fre­quent boxes go in a closet in the lab. Boxes with no dots for a long time go to a sep­a­rate stor­age shed out­side of my lab, which I think of as “cold stor­age”.

Cold stor­age ex­am­ples: a box of liq­uid pumps (ink pumps, peri­staltic pumps, air pumps). A box of piezo ac­tu­a­tors and piezo mo­tors. I find piezos fas­ci­nat­ing, but I’ve re­luc­tantly come to ad­mit over time that they’re just not that use­ful to me. A set of Parker lin­ear mo­tors I bought as lab sur­plus on eBay. Cool hard­ware, but the soft­ware for the ViX servo dri­ves only works on Windows XP, and I did­n’t have much need for lin­ear mo­tors. Zero dots for two years and moved it to the shed.

Sometimes things come back. When I started build­ing a pick-and-place ma­chine, my pneu­matic com­po­nents came right out of cold stor­age. That’s not a fail­ure, I ex­pect that some things will come back, just not very many things. Cold stor­age is like a stag­ing area, not a grave­yard. If a box sits there long enough un­touched, the next step is do­nat­ing or sell­ing.

This closes a loop. When you con­stantly ac­quire new parts but have lim­ited space, you need a sys­tem that tells you what should go out the door as new things come in. The dots pro­vide that sig­nal. A lot of peo­ple hoard things they don’t need. Seeing clear ev­i­dence that a box has zero dots is what helps me over­come the hes­i­ta­tion to fi­nally let go of it.

Principles I’ve learned over four years of the dot sys­tem.

Clear boxes, same size and shape. Having a com­mon form fac­tor is like hav­ing a com­mon soft­ware in­ter­face. Lids be­come in­ter­change­able. If a box breaks you can re­place it. You’ll prob­a­bly need a few dif­fer­ent sizes. Pick sizes where each jump is roughly dou­ble the last. I use four sizes to­tal.

Labels on the front, not the lid. You will re­gret lid la­bels the mo­ment you stack boxes.

Date every­thing. Every la­bel, every bag. It feels un­nec­es­sary at first but it pays off over time. It’s also a kind of time cap­sule for your­self.

Thick clear bags. Take the time to la­bel them. A per­ma­nent marker works fine. I use name tag sized white la­bels.

Keep sticker sheets near your boxes. If ap­ply­ing a dot takes more than two sec­onds, you’ll stop do­ing it. I put sticker sheets in half a dozen places around the lab near my boxes.

Everything needs a home. If only some things are in the sys­tem, the value is di­min­ished. Everything you want to track needs to be­long some­where.

Don’t dot the ob­vi­ous. I put dots on my sol­der­ing iron, calipers, and iso­propyl al­co­hol bot­tle but it was point­less. I al­ready knew these tools were cor­ner­stones of my lab. The dots are most valu­able for things where us­age is gen­uinely am­bigu­ous.

Curate cat­e­gories. A box of ran­dom mis­cel­la­neous parts teaches you noth­ing. Boxes of parts that are used to­gether yield high-qual­ity sig­nal.

And then give it time. A year in, you’ll start see­ing pat­terns. Two years in, you’ll trust them enough to know how to refac­tor your col­lec­tion.

The dot sys­tem does­n’t have to be fig­ured out all at once. Mine evolved through three gen­er­a­tions of bags and two ma­jor re­or­ga­ni­za­tions. My in­ter­ests changed, my do­main of ex­per­tise grew, my col­lec­tion ex­panded. The sys­tem evolved along with me. I like that it is a liv­ing, fluid sys­tem.

Walk into my lab and the dots will tell you every­thing you need to know. They told me too. It just took four years and a $3 pack of stick­ers. I’m still adding dots.

OkCupid and Match set­tle with Trump FTC, don’t have to pay any fi­nan­cial penalty.

OkCupid and its owner Match Group reached a set­tle­ment with the Trump ad­min­is­tra­tion for not telling dat­ing-app cus­tomers that nearly 3 mil­lion user pho­tos were shared with a com­pany mak­ing a fa­cial recog­ni­tion sys­tem. OkCupid also gave the fa­cial recog­ni­tion firm ac­cess to user lo­ca­tion in­for­ma­tion and other de­tails with­out cus­tomers’ con­sent, the Federal Trade Commission said.

OkCupid and Match do not have to pay a fi­nan­cial penalty in a deal made with the FTC over an in­ci­dent from 2014. OkCupid and Match did not ad­mit or deny the al­le­ga­tions but agreed to a per­ma­nent pro­hi­bi­tion bar­ring them from mis­rep­re­sent­ing how they use and share per­sonal data, the FTC said yes­ter­day.

The FTC has been run en­tirely by Republicans since President Trump fired both Democratic com­mis­sion­ers. The pro­posed set­tle­ment re­quires ap­proval from a judge and was sub­mit­ted in US District Court for the Northern District of Texas.

The dat­ing-site com­pany said it’s pleased to set­tle the mat­ter with­out pay­ing any fine. “While we do not ad­mit any wrong­do­ing, we have set­tled this mat­ter with the FTC with no mon­e­tary penalty to re­solve an is­sue from 2014 and move for­ward,” an OkCupid spokesper­son said in a state­ment pro­vided to Ars to­day. “The al­leged con­duct at is­sue does not re­flect how OkCupid op­er­ates to­day. Over the years, we have fur­ther strength­ened our pri­vacy prac­tices and data gov­er­nance to en­sure we meet the ex­pec­ta­tions of our users.”

Although a re­cent court rul­ing im­poses lim­its on the FTC’s en­force­ment pow­ers, that rul­ing ap­plied only to the FTC’s in-house ad­min­is­tra­tive process. The FTC can still pur­sue de­cep­tive ad­ver­tis­ing claims in courts and seek fi­nan­cial penal­ties through court or­ders or set­tle­ments.

FTC: OkCupid im­posed no re­stric­tions on data use

The FTC crit­i­cized Match and OkCupid for shar­ing OkCupid data with Clarifai, an AI com­pany that of­fers fa­cial recog­ni­tion tech­nol­ogy. Clarifai’s web­site says it of­fers AI ser­vices to “military, civil­ian, in­tel­li­gence, and gov­ern­ment” cus­tomers and to pri­vate-sec­tor com­pa­nies in var­i­ous in­dus­tries.

The FTC said that “OkCupid pro­vided the third party with ac­cess to nearly three mil­lion OkCupid user pho­tos as well as lo­ca­tion and other in­for­ma­tion with­out plac­ing any for­mal or con­trac­tual re­stric­tions on how the in­for­ma­tion could be used.” OkCupid “did not in­form con­sumers or give them the chance to opt out of such shar­ing,” the FTC said.

The FTC said the data-shar­ing vi­o­lated the OkCupid pri­vacy pol­icy, which told con­sumers that it does­n’t share “your per­sonal in­for­ma­tion with oth­ers ex­cept as in­di­cated in this Privacy Policy or when we in­form you and give you an op­por­tu­nity to opt out of hav­ing your per­sonal in­for­ma­tion shared.”

The FTC al­leged that “since September 2014, Match and OkCupid took ex­ten­sive steps to con­ceal—in­clud­ing through try­ing to ob­struct the FTC’s in­ves­ti­ga­tion—and deny that OkCupid shared users’ per­sonal in­for­ma­tion with the data re­cip­i­ent. For ex­am­ple, when a news story re­vealed that the third party had ob­tained large OkCupid datasets, OkCupid claimed to the me­dia and OkCupid users that it was not in­volved with the third party.”

The data-shar­ing arrange­ment was de­scribed in a 2019 ar­ti­cle by The New York Times.

Clarifai founder and CEO Matt Zeiler “said his com­pany had built a face data­base with im­ages from OkCupid,” and “used the im­ages from OkCupid to build a ser­vice that could iden­tify the age, sex and race of de­tected faces,” ac­cord­ing to the Times’ 2019 ar­ti­cle.

“An OkCupid spokes­woman said Clarifai con­tacted the com­pany in 2014 ‘about col­lab­o­rat­ing to de­ter­mine if they could build un­bi­ased AI and fa­cial recog­ni­tion tech­nol­o­gy’ and that the dat­ing site ‘did not en­ter into any com­mer­cial agree­ment then and ha[s] no re­la­tion­ship with them now.’ She did not ad­dress whether Clarifai had gained ac­cess to OkCupid’s pho­tos with­out its con­sent,” the Times wrote.

But even if they had no “commercial agree­ment,” Zeiler told the Times that his com­pany gained ac­cess to user pho­tos be­cause some of OkCupid’s founders in­vested in Clarifai, the 2019 ar­ti­cle said. “Clarifai used the im­ages from OkCupid to build a ser­vice that could iden­tify the age, sex and race of de­tected faces, Mr. Zeiler said,” ac­cord­ing to the ar­ti­cle, which added that “Mr. Zeiler said Clarifai would sell its fa­cial recog­ni­tion tech­nol­ogy to for­eign gov­ern­ments, mil­i­tary op­er­a­tions and po­lice de­part­ments pro­vided the cir­cum­stances were right.”

The FTC said in a com­plaint yes­ter­day that OkCupid, which was pur­chased by Match.com in 2011, made “false and mis­lead­ing claims” about how it used cus­tomer data. The com­plaint makes ref­er­ences to Humor Rainbow, the name of the com­pany that cre­ated OkCupid.

“When OkCupid users in­quired about OkCupid and the Data Recipient, Humor Rainbow re­it­er­ated its lack of in­volve­ment with the Data Recipient. Humor Rainbow stated that ‘any im­pli­ca­tion that OkCupid re­leased users’ in­for­ma­tion to [the Data Recipient] is false,’” the FTC com­plaint said.

The FTC com­plaint de­scribed how the data-shar­ing arrange­ment was made:

In September 2014, the CEO of Clarifai, Inc. e-mailed one of OkCupid’s founders re­quest­ing that Humor Rainbow give Clarifai, Inc. (i.e., the Data Recipient) ac­cess to large datasets of OkCupid pho­tos. Despite not hav­ing any busi­ness re­la­tion­ship with Humor Rainbow, the Data Recipient sought Humor Rainbow’s as­sis­tance be­cause each of OkCupid’s founders, in­clud­ing Humor Rainbow’s President and Match Group, LLC’s CEO, were fi­nan­cially in­vested in the Data Recipient.

In re­sponse to this re­quest, Humor Rainbow gave the Data Recipient ac­cess to nearly three mil­lion OkCupid user pho­tos. Humor Rainbow’s President and Chief Technology Officer were di­rectly in­volved in fa­cil­i­tat­ing the data trans­fer. In ad­di­tion to user pho­tos, Humor Rainbow shared other per­sonal data with the Data Recipient, in­clud­ing each user’s de­mo­graphic and lo­ca­tion in­for­ma­tion.

Humor Rainbow never ex­e­cuted a for­mal agree­ment or set forth re­stric­tions gov­ern­ing the Data Recipient’s ac­cess to, or use of, the OkCupid user data. The Data Recipient did not pay for the data and never pro­vided any ser­vices to Humor Rainbow or on be­half of OkCupid.

The FTC said that un­der the pro­posed set­tle­ment:

OkCupid and Match are per­ma­nently pro­hib­ited from mis­rep­re­sent­ing or as­sist­ing oth­ers in mis­rep­re­sent­ing: The ex­tent to which the com­pa­nies col­lect, main­tain, use, dis­close, delete or pro­tect any per­sonal in­for­ma­tion such as pho­tos and de­mo­graphic and ge­olo­ca­tion data; The pur­pose for which they col­lect, main­tain, use or dis­close such per­sonal data; and the func­tion of pri­vacy con­trols they pro­vide con­sumers through user in­ter­faces, any con­sumer choices af­forded to con­sumers un­der ap­plic­a­ble state pri­vacy laws, or any other mech­a­nisms the com­pa­nies of­fer con­sumers to limit or man­age the pro­cess­ing of per­sonal data.

The FTC said its in­ves­ti­ga­tion in­volved the “successful en­force­ment in fed­eral court” of a civil in­ves­tiga­tive de­mand that “required OkCupid to turn over in­for­ma­tion re­quested by the agency.” Although the FTC merely re­quired OkCupid and Match to be hon­est with users about data prac­tices and did not ex­tract a fi­nan­cial penalty, the agency talked tough about the en­force­ment ac­tion in its press re­lease.

“The FTC en­forces the pri­vacy promises that com­pa­nies make,” said Christopher Mufarrige, di­rec­tor of the FTC’s Bureau of Consumer Protection. “We will in­ves­ti­gate, and where ap­pro­pri­ate, take ac­tion against com­pa­nies that promise to safe­guard your data but fail to fol­low through—even if that means we have to en­force our Civil Investigative Demands in court.”

Jon is a Senior IT Reporter for Ars Technica. He cov­ers the tele­com in­dus­try, Federal Communications Commission rule­mak­ings, broad­band con­sumer af­fairs, court cases, and gov­ern­ment reg­u­la­tion of the tech in­dus­try.

Starlink satel­lite breaks apart into “tens of ob­jects”; SpaceX con­firms “anomaly”

You can fi­nally change the goofy Gmail ad­dress you chose years ago

After 16 years and $8 bil­lion, the mil­i­tary’s new GPS soft­ware still does­n’t work

RFK Jr. wants Americans to use pep­tides that were banned over safety risks

Large mod­els can’t fit on smart­phones. Datacenters can’t sus­tain them. PrismML is build­ing ul­tra dense in­tel­li­gence to solve both. The first com­mer­cially vi­able model with 1-bit weights. Requiring only 1.15GB of mem­ory, 1-bit Bonsai 8B was en­gi­neered for ro­bot­ics, real-time agents, and edge com­put­ing. It has a 14× smaller foot­print than a full-pre­ci­sion 8B model, runs 8× faster, and is 5× more en­ergy ef­fi­cient, while match­ing lead­ing 8B mod­els on bench­marks. This re­sults in over 10× the in­tel­li­gence den­sity of full-pre­ci­sion 8B mod­els¹. Requiring just 0.57GB of mem­ory, 1-bit Bonsai 4B de­liv­ers ex­cep­tional speed, reach­ing 132 to­kens per sec­ond on an M4 Pro. It pairs strong ac­cu­racy with out­stand­ing en­ergy ef­fi­ciency, mak­ing it ideal for work­loads that de­mand both per­for­mance and speed¹.With a foot­print of only 0.24GB of mem­ory, 1-bit Bonsai 1.7B pushes the lim­its of on-de­vice speed, reach­ing 130 to­kens per sec­ond on an iPhone 17 Pro Max. Combining in­dus­try-lead­ing en­ergy ef­fi­ciency with solid ac­cu­racy, it’s a light­weight model built for heavy­weight tasks¹.

Negative log of the mod­el’s er­ror rate di­vided by the model size

Tokens per sec­ond across hard­ware plat­forms (higher is bet­ter)

Milliwatt-hours per to­ken across hard­ware (lower is bet­ter)

Successful ar­ti­fi­cial in­tel­li­gence is­n’t just about mak­ing mod­els larger, but also smarter. Utilizing break­through re­search at Caltech, PrismML is push­ing the fron­tier of in­tel­li­gence den­sity by re­shap­ing how mod­els are de­signed, pri­or­i­tiz­ing in­tel­li­gence per bit over sheer pa­ra­me­ter count.

We are look­ing for en­gi­neers look­ing to push the fron­tier of in­tel­li­gence den­sity.

Thanks, your ap­pli­ca­tion has been re­ceived!Oops! Something went wrong while sub­mit­ting the form.

… is what I’m read­ing far too of­ten! Some of you are los­ing faith!

A grow­ing sen­ti­ment amongst my peers — those who haven’t al­ready re­signed to an NPC ca­reer path† — is that blog­ging is over. Coding is cooked. What’s the point of shar­ing in­sights and ex­per­tise when the Cognitive Dark Forest will feed on our hu­man­ity?

Before I’m dis­missed as an ill-in­formed hater please note: I’ve done my re­search.

† To be fair it’s a valid choice in this econ­omy. Clock in, slop around, clock out. Why not?

Star Trek’s cap­tain Kirk lean­ing into a com­puter cast in shadow look­ing con­tem­pla­tive.

It’s never been more im­por­tant to blog. There has never been a bet­ter time to blog. I will tell you why. We’re be­ing starved for hu­man con­ver­sa­tion and au­then­tic voices. What’s more: every­one is try­ing to take your voice away. Do not opt-out of us­ing it your­self.

First let’s ac­cept the re­al­i­ties. The gi­ant pla­gia­rism ma­chines have al­ready stolen every­thing. Copyright is dead. Licenses are washed away in clean rooms. Mass sur­veil­lance and track­ing are a fea­ture, pri­vacy is a bug. Everything is an “algorithm” op­ti­mised to ex­ploit.

How can we pos­si­bly com­bat that?

From a purely self­ish per­spec­tive it’s never been eas­ier to stand out and as­sert your­self as an au­thor­ity. When every­one is de­fer­ring to the big bull­shit­ter in the cloud your orig­i­nal thoughts are in­valu­able. Your brain is your biggest as­set. Share it with oth­ers for mu­tual ben­e­fit.

I find writ­ing stuff down im­proves my mem­ory and hard­ens my re­solve. I bet that’s true for you too. It’s part rote learn­ing part rub­ber­duck­ing†. Writing pub­licly in blog form forces me to ques­tion as­sump­tions. Even when re­search fails me Cunningham’s Law saves me.

† Some will claim writ­ing into a pre­dic­tive chat box helps too, and sure, they’re ab­solutely right!

Blogging makes you a bet­ter pro­fes­sional. No mat­ter how small your au­di­ence, some­one will even­tu­ally stum­ble upon your blog and it will un­block their path.

Don’t ac­cept a fate be­ing forced upon you.

The AI in­dus­try is 99% hype; a bil­lion dol­lar in­dus­trial com­plex to put a price tag on cre­ation. At this point if you be­lieve AI is ‘just a tool’ you’re wil­fully ig­nor­ing the harm. (Regardless, why do I keep be­ing told it’s an ‘extreme’ stance if I de­cide not to buy some­thing?)

The 1% util­ity AI has is over­shad­owed by the over­whelm­ing medioc­racy it re­gur­gi­tates.

We’re say­ing good­bye to Sora. To every­one who cre­ated with Sora, shared it, and built com­mu­nity around it: thank you. What you made with Sora mat­tered, and we know this news is dis­ap­point­ing.

Is there any­thing, in the en­tire recorded his­tory of hu­man cre­ation, that could have pos­si­bly mat­tered less than the flat­u­lence Sora pro­duced? NFTs had more value.

I’m not pro­tec­tive over the word “art”. Generative AI is art. It’s ir­re­deemably shit art; end of con­ver­sa­tion. A child’s crayon doo­dle is also lack­ing re­fined artistry but we hang it on our fridge be­cause a hu­man made it and that mat­ters. We care and car­ing has a pos­i­tive ef­fect on our lives. When you pass hu­man cre­ativ­ity through the slop wringer, or just prompt an in­can­ta­tion, the re­sult is con­tin­voucly morged; a va­pid mock­ery of the in­put. The garbage out no longer mat­ters, no­body cares, no­body ben­e­fits.

I for­got where I was go­ing with this… oh right: don’t re­sign your­self to the deskilling of our craft. You should keep blog­ging! Take pride in your abil­ity and unique voice. But please don’t des­e­crate your­self with slop.

A di­sheveled Oliver Twist looks up plead­ingly hold­ing out an empty bowl.

The only win­ning move is not to play.

We’ve got­ten too com­fort­able with the con­ve­nience of Big Tech. We do not have to con­tinue play­ing their game. Don’t buy the nar­ra­tives they’re sell­ing.

The AI in­dus­try is built on the preda­tory busi­ness model of casi­nos. Except they’ve for­get the house is sup­posed to win. One up­side of this loom­ing eco­nomic and in­tel­lec­tual de­pres­sion is that the me­dia is be­gin­ning to recog­nise gate keep­ers are no longer the hand that feeds them. Big Tech is not the web. You don’t have to use it nor sup­port it. Blog for the old web, the open web, the in­die web — the web you want to see.

And if you think I’m be­ing dra­matic and I’ve up­set your new toys, you’re wel­come to be left be­hind in the mi­as­matic dystopia these tech­no­facists are rac­ing to build.

The race is on to test new ve­hi­cles in the un­der­ground Large Hadron Collider tun­nel, ahead of ma­jor works start­ing this sum­mer

The race is on to test new ve­hi­cles in the un­der­ground Large Hadron Collider tun­nel, ahead of ma­jor works start­ing this sum­mer

Following on from the ro­botic mice, CERN en­gi­neers have now de­vel­oped a su­per-charged kart to en­able work­ers to race through the Large Hadron Collider (LHC) un­der­ground tun­nel dur­ing the up­com­ing ma­jor works, start­ing this sum­mer.

The karts promise a power boost to ac­tiv­i­ties dur­ing this pe­riod, known as Long Shutdown 3 (LS3), which will see the LHC trans­formed into the High-Luminosity LHC. These ve­hi­cles will re­place the bi­cy­cles that were used un­til now to travel through the 27-km un­der­ground tun­nel, en­abling en­gi­neers and tech­ni­cians to speed to ar­eas where im­prove­ments to the ac­cel­er­a­tor are re­quired.

“Each kart is turbo-boosted by 64 su­per­con­duct­ing en­gines,” ex­plains pro­ject leader Mario Idraulico. “When the en­gines are cooled to be­low their crit­i­cal tem­per­a­tures, the Meissner ef­fect lev­i­tates the karts, al­low­ing them to zip through the tun­nels at high speeds and, mamma mia, they’re su­per!”

Early tests have been promis­ing, and the next steps in­volve test­ing dif­fer­ent kart de­signs in an un­der­ground race. Safety co­or­di­na­tor Luigi Fratello has en­sured that each dri­ver will be is­sued with Safety and Health Equipment for Long and Limited Stays (SHELLS), al­though his re­sponse to dri­vers want­ing ba­nanas in the tun­nel was “Oh no!”

These karts, al­though de­vel­oped to sup­port CERN’s fun­da­men­tal re­search pro­gramme, show clear ap­pli­ca­tions for so­ci­ety. CERN’s Knowledge Transfer Group has be­gun dis­cus­sions with European startup com­pany Quantum Mushroom to ex­plore aero­space ap­pli­ca­tions and pow­er­ing for next-gen­er­a­tion anti-grav­ity ve­hi­cles.

Surprisingly, the kart pro­ject be­gan from a col­lab­o­ra­tion be­tween CERN en­gi­neers and on­site nurs­ery school chil­dren — one ex­am­ple of CERN’s com­mit­ment to in­spir­ing fu­ture gen­er­a­tions. “We’re thrilled that the chil­dren’s kart de­signs were the in­spi­ra­tion for the en­gi­neered karts,” ex­claimed school­teacher Yoshi Kyouryuu, mid-way through paint­ing spots on eggs for an Easter egg hunt.

“As ed­u­ca­tors, we pro­mote cu­rios­ity from a young age, which is why we paint ques­tion marks all over our yel­low school walls,” ex­plained school di­rec­tor, Rosalina Pfirsich, look­ing up from her sto­ry­book. “With all the con­tri­bu­tions the chil­dren have made to the up­com­ing High-Luminosity LHC pro­ject, we’ve taken to call­ing them Luma!”

Find out more about the High-Luminosity LHC pro­ject.

Core AWS ser­vices plus real in­fra­struc­ture — RDS runs ac­tual data­bases, ElastiCache runs real Redis, ECS starts real Docker con­tain­ers, Athena ex­e­cutes real SQL via DuckDB (when in­stalled).

Same de­vel­oper ex­pe­ri­ence. Fraction of the cost and foot­print.

Core AWS ser­vices plus real in­fra­struc­ture — RDS runs ac­tual data­bases, ElastiCache runs real Redis, ECS starts real Docker con­tain­ers, Athena ex­e­cutes real SQL via DuckDB (when in­stalled).

Same de­vel­oper ex­pe­ri­ence. Fraction of the cost and foot­print.

Where it mat­ters most — RDS, ElastiCache, and ECS run real Docker con­tain­ers. No fake end­points, no stubbed re­sponses.

CreateDBInstance spins up an ac­tual Postgres or MySQL Docker con­tainer. Connect with psy­copg2 —

it’s a real data­base.

CreateCacheCluster starts an ac­tual Redis con­tainer. Use re­dis-py, run SUBSCRIBE, use it as your

ses­sion store.

RunTask pulls and starts real Docker con­tain­ers via the Docker socket. Test your ECS task

de­f­i­n­i­tions lo­cally.

Queries ex­e­cute via DuckDB when in­stalled. Query S3 data with ac­tual SQL, get ac­tual re­sult sets

back. Falls back to mock re­sults with­out it.

Works with boto3, AWS CLI, Terraform, CDK, Pulumi — any tool that speaks the AWS API.

No BSL, no fea­ture gates, no “community” vs “pro”. Every ser­vice is free. Fork it, em­bed it. MIT

is MIT.