“There are also sex scenes filmed with the smart glasses — some­one is wear­ing them hav­ing sex. That is why this is so ex­tremely sen­si­tive. There are cam­eras every­where in our of­fice, and you are not al­lowed to bring your own phones or any de­vice that can record”, an em­ployee says. In or­der to an­swer ques­tions and in­ter­pret what the cam­era sees, the glasses re­quire that data be processed via Meta’s in­fra­struc­ture — it is not pos­si­ble to in­ter­act with the AI solely lo­cally on the phone. We con­tact Synsam and Synoptik for an in­ter­view about what train­ing the sales staff re­ceive and how it can be that the an­swers they give are so dif­fer­ent. Synsam re­sponded in writ­ing that its role is to in­form cus­tomers about the ap­plic­a­ble terms and to pro­vide in­ter­nal train­ing, but that re­spon­si­bil­ity for com­ply­ing with Swedish law and Meta’s terms ul­ti­mately rests with the wearer. Synoptik re­sponded in sim­i­lar terms, say­ing its staff are trained in ethics and em­p­hazise the user’s re­spon­si­bil­ity.But for the AI as­sis­tant to func­tion, voice, text, im­age and some­times video must be processed and may be shared on­wards. This data pro­cess­ing is done au­to­mat­i­cally and can­not be turned off.It is not spec­i­fied how much data may be analysed or for how long it may be stored. Nor is it spec­i­fied who is given ac­cess to the data.Where do the im­ages come from? Can pri­vate videos from Sweden end up on screens in Kenya? Those who ap­pear in the im­ages, have they con­sented to ap­pear­ing in this way?“Many be­lieve that data must be stored within the EU to be pro­tected. But un­der GDPR it does not mat­ter where the server is lo­cated — as long as the coun­try meets the EU’s re­quire­ments. If it does not, data may not be sent there”.“Tech­ni­cally, we have data cen­tres in Sweden, Denmark and Ireland, but the phys­i­cal lo­ca­tion is ac­tu­ally less rel­e­vant. The le­gal re­spon­si­bil­ity lies with Meta Ireland, which is the European en­tity. Where the data is ac­tu­ally processed — in Europe or in the US — does not change the reg­u­la­tory frame­work”.“For it to be per­mit­ted to use a ser­vice provider in a third coun­try (outside the EU), it is re­quired that ro­bust agree­ments with in­struc­tions are in place. It must also be en­sured that there is le­gal sup­port for the trans­fers, so that the data that is trans­ferred re­ceives con­tin­ued strong and equiv­a­lent pro­tec­tion when it is processed in a third coun­try. The pro­tec­tion must there­fore not be­come weaker when it is processed by sub­con­trac­tors”, says Petra Wierup.

Hur san­no­likt är det att du skulle rek­om­mendera SvD till en vän eller kol­lega?

Most British Columbians will change their clocks for the last time this Sunday.

B. C. is per­ma­nently adopt­ing day­light time, mak­ing its “spring for­ward” on March 8 the last time change, Premier David Eby an­nounced Monday.

“We are done wait­ing. British Columbia is go­ing to change our clocks just one more time — and then never again,” Eby said.

He said chang­ing the clocks causes “all types of prob­lems,” from chil­dren and their par­ents los­ing sleep, to dogs get­ting up at the wrong time, to more car ac­ci­dents.

Residents will have eight months to pre­pare for Nov. 1, 2026, when the clocks would have been turned back one hour, but will now re­main the same.

B. C.’s new time zone will be called “Pacific time,” ac­cord­ing to the province.

Residents in cer­tain com­mu­ni­ties in east­ern B. C. that rec­og­nize some form of moun­tain time will not be af­fected by the change.

B. C. passed leg­is­la­tion to make this change pos­si­ble in 2019, but with­out a firm time­line. Previously, Eby said he would wait for B.C.’s American neigh­bours — in­clud­ing Washington state, Oregon and California — to do the same.

While U. S. President Donald Trump ex­pressed in­ter­est in elim­i­nat­ing day­light time shortly af­ter his 2024 elec­tion, Congress has not passed the nec­es­sary leg­is­la­tion.

Eby noted the Yukon has al­ready made the change to per­ma­nent day­light time and added he hopes American neigh­bours will fol­low suit.

CBC News reached out to Washington State Governor Bob Ferguson, but did not hear back im­me­di­ately.

University of B. C. busi­ness pro­fes­sor Werner Antweiler said that while he was sur­prised by B.C.’s de­ci­sion to make this change with­out wait­ing for nearby states, he sees ben­e­fits in elim­i­nat­ing time changes.

Time changes, par­tic­u­larly switch­ing clocks an hour for­ward in the spring, has been found to be harm­ful, as it im­poses “jet lag on the en­tire pop­u­la­tion,” he said.

“Somebody had to move first — it might as well be B. C. — and then see how it plays out,” Antweiler said.

“The ques­tion is now, who will fol­low?”

A pub­lic en­gage­ment re­port in 2019 for the B. C. gov­ern­ment found that 93 per cent of re­spon­dents pre­ferred year-round day­light time.

However, 54 per cent of those who re­sponded said it was im­por­tant for B. C. to have align­ing poli­cies on day­light time with other ju­ris­dic­tions.

Of those who wanted year-round day­light time, three-quar­ters said it was due to health and well­ness con­cerns.

Switching to per­ma­nent stan­dard time was not a vot­ing op­tion.

Bridgitte Anderson, President and CEO of the Greater Vancouver Board of Trade, ex­pressed con­cern about B. C.’s de­ci­sion to move for­ward alone in this de­ci­sion.

“The uni­lat­eral change in time is an un­wel­come dis­trac­tion that will make it more dif­fi­cult to at­tract and re­tain busi­nesses in British Columbia,” she said in a state­ment.

“The choice to change the time un­lit­er­ally will cre­ate an ad­di­tional headache for busi­nesses op­er­at­ing on both sides of the bor­der.”

The Vancouver Airport Authority was among groups in 2019 that pushed for B. C. to align with other ju­ris­dic­tions on the Pacific coast, to avoid un­nec­es­sary con­fu­sion for trav­ellers.

A spokesper­son for the Vancouver Airport Authority said in re­sponse to the an­nounced change that align­ment is “fundamental” for air­line op­er­a­tions and ef­fi­cient sched­ul­ing.

“We will work with in­dus­try to bet­ter un­der­stand the po­ten­tial sched­ule and pas­sen­ger im­pli­ca­tions of mov­ing to per­ma­nent day­light sav­ing time with­out neigh­bour­ing ju­ris­dic­tions also fol­low­ing suit,” the state­ment said.

Ryan Mitton, the B. C. di­rec­tor of leg­isla­tive af­fairs for the Canadian Federation of Independent Business, said that while some may be re­lieved not to re­set the clocks each year, it may also cause “confusion and dis­rup­tion.”

“This ap­pears mo­ti­vated by an at­tempt to dis­tract from the province’s $13-billion deficit, not gen­uine con­cern for the im­pacts of the time change,” he said in a state­ment.

Identity ver­i­fi­ca­tion and age ver­i­fi­ca­tion is an in­creasinly com­mon pol­icy con­ver­sa­tion at the mo­ment, in nu­mer­ous coun­tries.

Often, this is in com­bi­na­tion with pro­pos­als to ban chil­dren from vary­ing con­cepts of “social me­dia”, which gen­er­ally means that every­one would have to prove that they were not a child.

I have yet to see a well-con­sid­ered pro­posal.

Worse, the ques­tion that they are try­ing an­swer is rarely stated clearly and con­cisely.

And it is un­usual to see any con­sid­er­a­tion of broader so­ci­o­log­i­cal is­sues, let alone an em­pha­sis on this, with a fo­cus in­stead on per­ceived “quick win” tech­noso­lu­tion­ism.

I was pon­der­ing last night for which ser­vices I, per­son­ally, would ac­tu­ally be will­ing to ver­ify my age or iden­tity.

At least, none that I can think of at the mo­ment.

I ap­pre­ci­ate that I com­pute in an un­usual way (when com­pared with most com­puter users), and that much of what I do on­line is about ac­cess­ing my own ser­vices.

Some of those - my fedi server, my RSS server, my mes­sag­ing ser­vices - are build around en­joy­ing stuff from other peo­ple’s ser­vices.

Would I be will­ing to ver­ify my iden­tity or age to read some­one’s RSS feed? No. While I en­joy the myr­iad blogs that I fol­low, none are cru­cial to me.

I oc­ca­sion­ally watch videos (which started on YouTube, but which I down­load into my Jellyfin in­stance), and per­haps YouTube will be forced to do age ver­i­fi­ca­tion. It would be a shame, but again, I’ll just not watch YouTube videos. Not a big loss. Mostly, I buy sec­ond­hand DVDs, rip them, and watch them from my Jellyfin in­stance. I haven’t been asked to ver­ify my age for a DVD pur­chase (online or of­fline) in a very long time.

Friends have had to at­tempt to block ac­cess to their sites from the UK. While I can still ac­cess their sites via Tor, that’s what I tend to do. I feel sorry for them for the likely sig­nif­i­cant drop in vis­i­tors, likely af­fect­ing their en­joy­ment and in some cases their rev­enue, and, prob­a­bly their in­cen­tive to con­tinue to write / post / record stuff.

I don’t use any in­di­vid­ual fo­rums any more (their demise is a shame; I’d pre­fer this over cen­tralised dis­cus­sion sites), nor do I use Reddit. I oc­ca­sion­ally look at the com­ments on HN if one of my posts is sur­faced there, but if HN forced iden­tify or age ver­i­fi­ca­tion, I’d just stop do­ing it. No big deal for me.

Websites with com­ments sec­tions? I don’t want to see the com­ments any­way, so I block those, which makes for a very pleas­ant brows­ing ex­pe­ri­ence. I don’t com­ment my­self.

Code forges / places to con­tribute to FOSS? Most of my FOSS con­tri­bu­tions are non-code, but even so, I use some or­gan­i­sa­tion’s GitLab re­pos, and oc­ca­sion­ally I con­tribute to pro­jects on other forges. I doubt that my con­tri­bu­tions are mean­ing­ful in them­selves, and it may not be an op­tion to switch in­fra­struc­ture in any case (that might ont make the re­quire­ment go away), but since I am not a mas­sive, or par­tic­u­larly valu­able con­trib­u­tor, I’d feel less bad about sim­ply step­ping away.

For Wikipedia, I’d prob­a­bly re­build my Kiwix in­stance and use that in­stead. Yes, ar­ti­cles would not be quite so up to date, but I rarely ac­cess Wikipedia for rapidly-chang­ing in­for­ma­tion. In any case, there are trade­offs, and per­son­ally I would pre­fer my pri­vacy, the se­cu­rity of my per­sonal data, and, well, just not be­ing part of this kind of cen­sor­ship.

Signal? That would be a pain. I don’t have a workaround for that. I’m hap­pily us­ing XMPP, but as a com­ple­ment to Signal, not an al­ter­na­tive.

Teams/Zoom? I don’t have ac­counts on those ser­vices, but I do join, via my browser, when a client sends me a link. If I was faced with a choice of hav­ing to ver­ify my iden­tity/​age for these ser­vices, then I’d have to con­sider the po­si­tion care­fully. Realistically, I am not in a po­si­tion to say “no, I will not use Teams”, as some long-term clients are not go­ing to change their cor­po­rate ap­proach just be­cause Neil does­n’t like some­thing, and I’d rather not lose them as clients. So that could be a pain, if those ser­vices were within scope.

I’ll still ob­ject to these mea­sures - “I’m okay, Jack” would be a self­ish stance - but, in prac­tice, yes, I’d be sur­prised if they im­pacted me.

Self-imposed (or, at least, self-con­trolled) dig­i­tal iso­la­tion­ism, per­haps.

Or per­haps, in the fu­ture, some ser­vice will pop up that I will re­ally, re­ally want to use, de­spite it re­quir­ing iden­tity / age ver­i­fi­ca­tion.

The Condé Nast-owned Ars Technica has ter­mi­nated se­nior AI re­porter Benj Edwards fol­low­ing a con­tro­versy over his role in the pub­li­ca­tion and re­trac­tion of an ar­ti­cle that in­cluded AI-fabricated quotes, Futurism has con­firmed.

Earlier this month, Ars re­tracted the story af­ter it was found to in­clude fake quotes at­trib­uted to a real per­son. The ar­ti­cle — a write-up of a vi­ral in­ci­dent in which an AI agent seem­ingly pub­lished a hit piece about a hu­man en­gi­neer named Scott Shambaugh — was ini­tially pub­lished on February 13. After Shambaugh pointed out that he’d never said the quotes at­trib­uted to him, Ars‘ ed­i­tor-in-chief Ken Fisher apol­o­gized in an ed­i­tor’s note, in which he con­firmed that the piece in­cluded “fabricated quo­ta­tions gen­er­ated by an AI tool and at­trib­uted to a source who did not say them” and char­ac­ter­ized the er­ror as a “serious fail­ure of our stan­dards.” He added that, upon fur­ther re­view, the er­ror ap­peared to be an “isolated in­ci­dent.” (404 Media first re­ported on the re­trac­tion.)

Shortly af­ter Fisher’s ed­i­tor’s note was pub­lished, Edwards, one of the re­port’s two by­lined au­thors, took to Bluesky to take “full re­spon­si­bil­ity” for the in­clu­sion of the fab­ri­cated quotes.

In the post, Edwards said that he was sick at the time, and “while work­ing from bed with a fever and very lit­tle sleep,” he “unintentionally made a se­ri­ous jour­nal­is­tic er­ror” as he at­tempted to use an “experimental Claude Code-based AI tool” to help him “extract rel­e­vant ver­ba­tim source ma­te­r­ial.” He said the tool was­n’t be­ing used to gen­er­ate the ar­ti­cle, but was in­stead de­signed to “help list struc­tured ref­er­ences” to put in an out­line. When the tool failed to work, said Edwards, he de­cided to try and use ChatGPT to help him un­der­stand why.

“I should have taken a sick day be­cause in the course of that in­ter­ac­tion, I in­ad­ver­tently ended up with a para­phrased ver­sion of Shambaugh’s words rather than his ac­tual words,” Edwards con­tin­ued. He em­pha­sized that the “text of the ar­ti­cle was hu­man-writ­ten by us, and this in­ci­dent was iso­lated and is not rep­re­sen­ta­tive of Ars‘ ed­i­to­r­ial stan­dards. None of our ar­ti­cles are AI-generated, it is against com­pany pol­icy and we have al­ways re­spected that.”

Edwards also stressed that his col­league Kyle Orland, the site’s se­nior gam­ing ed­i­tor who co-by­lined the re­tracted story, had “no role in this er­ror.”

The con­tro­versy was met with a wave of push­back and spec­u­la­tion from Ars read­ers, many of whom ex­pressed deep frus­tra­tion and dis­ap­point­ment in a lengthy com­ment thread on the web­site. On February 27, Ars cre­ative di­rec­tor Aurich Lawson, while clos­ing the com­ment thread, said that “Ars has com­pleted its re­view of this mat­ter” and that “the ap­pro­pri­ate in­ter­nal steps have been taken.”

“In the com­ing weeks, we’ll pub­lish a reader-fac­ing guide ex­plain­ing how we use and do not use AI in our work,” Lawson wrote. “We do not com­ment on per­son­nel de­ci­sions.”

As of February 28, Edwards’ bio on Ars was changed to past tense, ac­cord­ing to an archived ver­sion of the web­page. It now reads that Edwards “was a re­porter at Ars, where he cov­ered ar­ti­fi­cial in­tel­li­gence and tech­nol­ogy his­tory.”

Futurism reached out to Ars, Condé Nast, and Edwards to in­quire about the re­porter’s em­ploy­ment sta­tus. Neither the pub­li­ca­tion nor its owner replied. Edwards said he was un­able to com­ment at this time.

Ars‘ re­trac­tion is­n’t the first AI con­tro­versy to rock a news­room, nor to anger a pub­li­ca­tion’s read­ers. It also comes at a mo­ment in which many me­dia bosses are push­ing staff to find uses for AI — as are ex­ec­u­tives across most in­dus­tries — even while clear guide­lines around use of the tech­nol­ogy that up­hold ed­i­to­r­ial ethics re­main elu­sive.

These edicts to in­te­grate AI, mean­while, are back­dropped by a com­pli­cated, ever-shift­ing land­scape: con­tentious copy­right bat­tles be­tween news gi­ants and AI com­pa­nies; si­mul­ta­ne­ous deal-strik­ing by news gi­ants and AI com­pa­nies; an in­ter­net in­creas­ingly full of AI-generated slop news and mis­in­for­ma­tion; and a traf­fic cliff tied to Google’s “AI Overviews,” which now para­phrase news in­stead of point­ing read­ers to a list of blue links.

It’s a com­bus­tive, dis­ori­ent­ing mo­ment in the his­tory of me­dia and tech­nol­ogy, when lines in the sand are be­ing drawn by both jour­nal­ists and their au­di­ences. And the Ars fall­out un­der­lines a phe­nom­e­non we’ve seen again and again, as even peo­ple who are deeply fa­mil­iar with AI and its short­com­ings can end up re­ly­ing on it at a crit­i­cal mo­ment — and in the process, fall vic­tim to some­thing much older than gen­er­a­tive AI: hu­man er­ror.

“The irony of an AI re­porter be­ing tripped up by AI hal­lu­ci­na­tion is not lost on me,” Edwards said in his February 15 Bluesky post. “I take ac­cu­racy in my work very se­ri­ously and this is a painful fail­ure on my part.”

More on AI and me­dia: Google’s AI Is Actively Destroying the News Media

I’ve spent the last six months work­ing on a startup, build­ing agent pro­to­types for one of the largest con­sumer pack­aged goods com­pa­nies in the world. As part of that work, our team re­lied on off-the-shelf voice agent plat­forms to help the com­pany op­er­ate more ef­fec­tively. Though I can’t go into the busi­ness de­tails, the tech­ni­cal take­away was clear: voice agents are pow­er­ful, and there are bril­liant off-the-shelf ab­strac­tions like Vapi and ElevenLabs that make spin­ning up voice agents a breeze. But: these ab­strac­tions also hide a sur­pris­ing amount of com­plex­ity.

Just a few days be­fore I started writ­ing this, ElevenLabs raised one of the largest fund­ing rounds in the space, and new fron­tier mod­els like GPT-5.3 and Claude 4.6 dropped. This made me won­der: could I ac­tu­ally build the or­ches­tra­tion layer of a voice agent my­self? Not just a toy ex­per­i­ment, but some­thing that could have close to the same per­for­mance as an all-in-one plat­form like Vapi?

To my sur­prise, I could. It took ~a day and roughly $100 in API cred­its - and the re­sult out­per­formed Vapi’s equiv­a­lent setup by 2× on la­tency, achiev­ing ~400ms end-to-end re­sponse times.

This es­say walks through the full build: why voice agents are de­cep­tively hard, how the turn-tak­ing loop works, how I wired to­gether STT, LLM, and TTS into a stream­ing pipeline, and how ge­og­ra­phy and model se­lec­tion made the biggest dif­fer­ence. Along the way, you can lis­ten to au­dio demos and play with in­ter­ac­tive di­a­grams of the ar­chi­tec­ture.

Voice agents are a big step-change in com­plex­ity com­pared to agen­tic chat.

Text agents are rel­a­tively sim­ple, be­cause the end-user’s ac­tions co­or­di­nate every­thing. The model pro­duces text, the user reads it, types a re­ply, and hits “send.” That ac­tion de­fines the turn bound­ary. Nothing needs to hap­pen un­til the user ex­plic­itly ad­vances the flow.

Voice does­n’t work that way. The or­ches­tra­tion is con­tin­u­ous, real-time, and must care­fully man­age mul­ti­ple mod­els at once. At any mo­ment, the sys­tem must de­cide: is the user speak­ing, or are they lis­ten­ing? And the tran­si­tions be­tween those two states are where all the dif­fi­culty lives.

When the user starts speak­ing, the agent must im­me­di­ately stop talk­ing - can­cel gen­er­a­tion, can­cel speech syn­the­sis, flush any buffered au­dio. When the user stops speak­ing, the sys­tem must con­fi­dently de­cide that they’re done, and start re­spond­ing with min­i­mal de­lay. Get ei­ther wrong and the con­ver­sa­tion feels bro­ken.

This is­n’t as sim­ple as mea­sur­ing loud­ness. Human speech in­cludes pauses, hes­i­ta­tions, filler sounds, back­ground noise, and non-ver­bal ac­knowl­edge­ments that should­n’t in­ter­rupt the agent. Downstream from this are the things every­one no­tices: end-to-end la­tency, awk­ward si­lences, agents cut­ting you off, or talk­ing over you.

We judge the qual­ity of voice com­mu­ni­ca­tion sub­con­sciously, as it is so deeply in­grained in who we are. Small tim­ing er­rors that would be ac­cept­able in text - a pause here, a de­lay there - im­me­di­ately feel wrong in speech.

In prac­tice, a good voice agent is not about any sin­gle model. It’s an or­ches­tra­tion prob­lem. You string to­gether mul­ti­ple com­po­nents, and the qual­ity of the ex­pe­ri­ence de­pends al­most en­tirely on how those pieces are co­or­di­nated in time.

The is­sue with all-in-one SDKs is that you get a long list of pa­ra­me­ters to tune, with­out re­ally un­der­stand­ing which ones mat­ter or why. When some­thing feels off, it’s hard to know where the prob­lem lives. That’s what pushed me to go one layer deeper and build the core loop my­self.

Before writ­ing any code, I spent time it­er­at­ing on the ar­chi­tec­ture with ChatGPT out­side of my ed­i­tor. I’ve found this use­ful when work­ing in un­fa­mil­iar do­mains: build a men­tal model first, then im­ple­ment.

My goal with agen­tic cod­ing is al­ways the same. I want to un­der­stand the struc­ture of what I’m build­ing well enough that I can open any file and im­me­di­ately see why it ex­ists and how it fits into the sys­tem.

After a few it­er­a­tions, I re­duced the en­tire prob­lem to a sin­gle loop and a tiny state ma­chine. At the core, a voice agent only needs to an­swer one ques­tion: is the user speak­ing, or lis­ten­ing?

There are two states:

And two tran­si­tions where every­thing hap­pens:

* When the user starts speak­ing, we must stop all agent au­dio and gen­er­a­tion im­me­di­ately.

* When the user stops speak­ing, we must start gen­er­at­ing and stream­ing the agent re­sponse with as lit­tle la­tency as pos­si­ble.

This turn-de­tec­tion logic is the core of every voice sys­tem, so I de­cided to start there.

For the first im­ple­men­ta­tion, I de­lib­er­ately avoided tran­scrip­tion, lan­guage mod­els, and text-to-speech. I wanted the sim­plest check­point that still felt di­rec­tion­ally like a voice agent.

The setup was min­i­mal. A small FastAPI server han­dles an in­com­ing WebSocket con­nec­tion from Twilio, which streams base64-en­coded μ-law au­dio pack­ets at 8kHz in ~20ms frames. Each packet was de­coded and fed into a Voice Activity Detection model - in my case, Silero VAD.

Silero is a tiny, open-source model (around 2MB) that can quickly de­ter­mine whether a short chunk of au­dio con­tains speech. Turn-taking is a much harder prob­lem than speech de­tec­tion, but VAD is still a use­ful prim­i­tive, es­pe­cially for de­cid­ing whether au­dio should be for­warded to more ex­pen­sive down­stream sys­tems.

On top of this, I built a triv­ial state ma­chine: a boolean flag rep­re­sent­ing whether the user was cur­rently speak­ing or lis­ten­ing. When the sys­tem de­tected the end of speech, it played a pre-recorded WAV file back to the caller. When speech re­sumed, it sent a clear sig­nal over the Twilio WebSocket to flush any buffered au­dio and stop play­back im­me­di­ately.

I started this way to iso­late the hard­est part of the prob­lem - turn de­tec­tion - with­out wiring up the rest of the sys­tem.

The re­sult, while ba­sic, was al­ready im­pres­sive:

VAD-only test - the agent plays a pre-recorded clip when­ever I stop talk­ing, and cuts off in­stantly when I in­ter­rupt.

The agent re­sponds im­me­di­ately when I stop speak­ing, and shuts up the in­stant I in­ter­rupted it. Even with­out tran­scrip­tion or gen­er­a­tion, the loop feels some­what con­ver­sa­tional.

This also gave me a use­ful base­line for la­tency. With ea­ger turn-end­ing and a pre-recorded re­sponse, the sys­tem rep­re­sented a lower bound on how fast a voice agent could pos­si­bly feel.

This first pass was valu­able, but its lim­i­ta­tions were ob­vi­ous.

Detecting the pres­ence of speech is not the same as know­ing when a user has fin­ished their thought. A slow speaker might pause for sev­eral sec­onds mid-sen­tence. A pure VAD would ea­gerly de­cide the turn had ended and start talk­ing too early.

In prac­tice, real turn-tak­ing re­quires com­bin­ing low-level au­dio sig­nals with higher-level se­man­tic cues from the tran­script it­self. That meant the VAD-only ap­proach could­n’t scale to a real sys­tem.

What it did give me was a clean con­trol-flow model and a solid la­tency base­line to com­pare against. With that in place, it was time to wire in the full pipeline.

The next step was re­plac­ing my hand-rolled turn de­tec­tion with some­thing de­signed for pro­duc­tion: Deepgram’s Flux.

Flux is a stream­ing API that com­bines tran­scrip­tion and turn de­tec­tion in a sin­gle model. You feed it a con­tin­u­ous au­dio stream, and it emits events - most im­por­tantly, “start of turn” and “end of turn,” with the fi­nal tran­script in­cluded at the end.

This re­placed the core of my ar­chi­tec­ture. Flux be­came the source of truth for when the agent should speak and when it should im­me­di­ately stop and lis­ten.

On top of that, I built a ded­i­cated agent-turn pipeline. When Flux sig­nals the end of a user turn, this pipeline kicks off a real-time se­quence:

* The tran­script and con­ver­sa­tion his­tory are sent to an LLM to be­gin gen­er­a­tion.

* As soon as the first to­ken ar­rives, it is streamed into a text-to-speech ser­vice over WebSocket.

* Every au­dio packet pro­duced by TTS is for­warded di­rectly to the out­bound Twilio socket.

The core idea is to pipeline every stream as to max­i­mally re­duce la­tency.

One im­por­tant de­tail here was keep­ing text-to-speech con­nec­tions warm. Establishing a fresh WebSocket to ElevenLabs adds a few hun­dred mil­lisec­onds of la­tency, so I kept a small pool of pre-con­nected sock­ets alive. That alone shaved roughly 300ms off the re­sponse time.

Barge-ins were han­dled sym­met­ri­cally. When Flux de­tects that the user starts speak­ing, the agent pipeline is im­me­di­ately can­celled: in-flight LLM gen­er­a­tion is stopped, TTS is torn down, and a clear mes­sage is sent to Twilio to flush any queued au­dio. The agent falls silent in­stantly, and Flux re­sumes lis­ten­ing for the next end-of-turn.

The full ar­chi­tec­ture - Twilio streams au­dio to Deepgram Flux for turn de­tec­tion, which trig­gers ei­ther a barge-in (cancel every­thing) or an agent turn (LLM → TTS → au­dio back to the caller).

My first test was to run the or­ches­tra­tion en­tirely lo­cally, mainly to un­der­stand how ge­o­graphic place­ment af­fects la­tency. I built most of this pro­ject from a re­mote wooden cabin in south­ern Turkey, while trav­el­ing and hik­ing, so this setup was far from ideal.

Latency trace run­ning lo­cally from south­ern Turkey. TTFT av­er­ages ~1.3s, with first au­dio ar­riv­ing ~1.6s af­ter the turn ends.

End-to-end la­tency av­er­aged around 1.6 sec­onds, mea­sured from my server. According to Twilio, their me­dia edge adds roughly ~100ms on top of that, bring­ing to­tal per­ceived la­tency to about 1.7s.

That’s still quite far from Vapi’s ~840ms la­tency for a com­pa­ra­ble con­fig­u­ra­tion - more than twice as slow. At that point, the de­lay be­comes no­tice­able. Conversations start to feel hes­i­tant. Pauses stretch just long enough to feel awk­ward.

This was a use­ful re­minder: even with a cor­rect ar­chi­tec­ture, ge­og­ra­phy mat­ters.

In our ar­chi­tec­ture, every packet of au­dio hops to and from three ex­ter­nal ser­vices. If you want to min­i­mize la­tency, the or­ches­tra­tion layer needs to live phys­i­cally close to them.

To fur­ther im­prove la­tency, I de­ployed the sys­tem on Railway in the EU re­gion and con­fig­ured Twilio, Deepgram, and ElevenLabs to use their EU de­ploy­ments as well (Note: ElevenLabs au­to­mat­i­cally chooses the near­est re­gion by de­fault)

The dif­fer­ence was im­me­di­ate:

Latency trace af­ter de­ploy­ing to Railway EU. TTFT drops to ~300-500ms, with first au­dio at ~550-750ms.

The av­er­age la­tency mea­sured at the server dropped to ~690ms, which trans­lates to a to­tal end-to-end la­tency of roughly ~790ms once Twilio’s edge is in­cluded - more than 2x im­prove­ment!

For com­par­i­son, the equiv­a­lent con­fig­u­ra­tion in Vapi - us­ing the same STT, LLM, and TTS mod­els - es­ti­mates around ~840ms. In this setup, the cus­tom or­ches­tra­tion ac­tu­ally beats Vapi’s own es­ti­mates by about 50ms.

More im­por­tantly, the sub­jec­tive dif­fer­ence is ob­vi­ous. The con­ver­sa­tion feels re­spon­sive. Interruptions work cleanly. The agent no longer feels like it’s hes­i­tat­ing be­fore every re­ply.

Hosted pipeline - the con­ver­sa­tion feels nat­ural, with clean in­ter­rup­tions and fast re­sponses.

So far in this pro­ject, I’d been us­ing gpt-4o-mini, which seemed to be the low­est-la­tency model avail­able from OpenAI. However, af­ter dig­ging a bit deeper, I dis­cov­ered that the in­fer­ence la­tency of Groq’s llama-3.3-70b could be up to 3× faster.

I wanted to ver­ify this for my­self, so I set up a small test har­ness on my pro­duc­tion server. It ran 360 chat com­ple­tions across a range of mod­els, can­celling each re­quest im­me­di­ately af­ter the first to­ken was re­ceived. Below are the re­sult­ing first-to­ken la­tency mea­sure­ments:

First-token la­tency across providers - Groq’s mod­els are in a league of their own.

As you can see, Groq’s mod­els leave every­thing from OpenAI in the dust. As far as I can tell, this is the low­est achiev­able la­tency with­out run­ning your own in­fer­ence in­fra­struc­ture. It’s gen­uinely im­pres­sive - ~80ms is faster than a hu­man blink, which is usu­ally quoted at around 100ms.

I swapped out gpt-4o-mini for Groq’s llama-3.3-70b, and the re­sults hon­estly sur­prised me:

Aside from the very first turn, the con­ver­sa­tion felt smooth and snappy. With av­er­age end-to-end la­tency hov­er­ing around ~400ms, I was strug­gling to keep up - lis­ten­ing back to the record­ing, it sounds like I was tak­ing longer to re­ply than the agent.

Latency trace with Groq - end-to-end la­tency av­er­ag­ing ~400ms, with first au­dio of­ten ar­riv­ing in un­der 500ms.

At this la­tency, in­ter­rup­tion han­dling also feels dra­mat­i­cally bet­ter. The agen­t’s voice cuts out al­most im­me­di­ately af­ter I start speak­ing, mak­ing the in­ter­ac­tion feel far closer to a real con­ver­sa­tion than any­thing I’d ex­pe­ri­enced be­fore.

I was re­ally sur­prised that I could beat off-the-shelf providers by a full mul­ti­ple. From ex­ten­sive ex­pe­ri­ence work­ing with both Vapi and Elevenlabs agent SDKs on a real pro­duc­tion use case, I found that my ini­tial pro­to­type is able to re­li­ably achieve a 2x la­tency im­prove­ment, which is a huge deal when it comes to serv­ing nat­ural-sound­ing and pleas­ant voice agent in­ter­ac­tions.

Building a voice agent from scratch taught me what ac­tu­ally mat­ters in get­ting AI voice con­ver­sa­tions to feel snappy:

Latency

What users ex­pe­ri­ence as “responsiveness” is the time from when they stop speak­ing to when they hear the first syl­la­ble of the agen­t’s re­sponse. That path runs through turn de­tec­tion, tran­scrip­tion, LLM time-to-first-to­ken, text-to-speech syn­the­sis, out­bound au­dio buffer­ing, and net­work hops be­tween all of them. You op­ti­mize this by iden­ti­fy­ing which stages sit on the crit­i­cal path and mak­ing sure noth­ing blocks un­nec­es­sar­ily.

Model choice and TTFT

In voice sys­tems, re­ceiv­ing the first LLM to­ken is the mo­ment the en­tire pipeline can be­gin mov­ing. The TTFT ac­counts for more than half of the to­tal la­tency, so choos­ing a la­tency-op­ti­mised in­fer­ence setup like Groq made the biggest dif­fer­ence. Model size also seems to mat­ter: larger mod­els may be re­quired for some com­plex use cases, but they also im­pose a la­tency cost that’s very no­tice­able in con­ver­sa­tional set­tings. The right model de­pends on the job, but TTFT is the met­ric that ac­tu­ally mat­ters.

Pipelining the agent turn.

A pro­duc­tion voice agent can­not be built as STT → LLM → TTS as three se­quen­tial steps. The agent turn must be a stream­ing pipeline: LLM to­kens flow into TTS as soon as they ar­rive, and au­dio frames flow to the phone im­me­di­ately. The goal is to never un­nec­es­sar­ily block gen­er­a­tion. Anything that waits for a full re­sponse be­fore mov­ing on is wast­ing time.

Cancelling in-flight calls.

Interruption han­dling must prop­a­gate to all parts of the agent turn, im­me­di­ately. When a user starts speak­ing, the sys­tem must can­cel LLM gen­er­a­tion, tear down TTS, and flush any buffered out­bound au­dio si­mul­ta­ne­ously. Missing any one of those makes barge-ins feel bro­ken.

Geography is a first-class de­sign pa­ra­me­ter.

Once you or­ches­trate mul­ti­ple ex­ter­nal ser­vices - tele­phony, STT, TTS, LLM - place­ment dom­i­nates every­thing. If those ser­vices aren’t co-lo­cated, la­tency com­pounds quickly. Moving the or­ches­tra­tion layer and us­ing the cor­rect re­gional end­points cut e2e la­tency in half. Service place­ment makes a huge dif­fer­ence.

Taken to­gether, these lessons ex­plain why voice feels de­cep­tively hard. Real-time sys­tems are un­for­giv­ing, and hu­mans are ex­tremely sen­si­tive to tim­ing er­rors.

Off-the-shelf vs. be­spoke

This is­n’t an ar­gu­ment against plat­forms like Vapi or ElevenLabs. Those sys­tems of­fer far more than or­ches­tra­tion: APIs, ob­serv­abil­ity, re­li­a­bil­ity, and deep con­fig op­tions that would take real ef­fort to re­pro­duce. For most teams, re­build­ing all of that would be a mis­take - be­ing able to test and val­i­date a voice agent app with­out get­ting to this level of tech­ni­cal depth is truly amaz­ing, and that’s how I first got ex­cited about the tech­nol­ogy.

But build­ing your voice agent your­self - even a stripped-down one - is still a worth­while ex­er­cise. It forces you to un­der­stand what the pa­ra­me­ters ac­tu­ally con­trol, why cer­tain de­faults ex­ist, and where the real bot­tle­necks live. That un­der­stand­ing makes you bet­ter at con­fig­ur­ing the off-the-shelf plat­forms, and in some cases lets you build some­thing more be­spoke when your use case de­mands it.

Voice is an or­ches­tra­tion prob­lem. Once you see the loop clearly, it be­comes a solv­able en­gi­neer­ing prob­lem.

The full source code is avail­able on GitHub: github.com/​Nick­Tikhonov/​shuo

Follow me on X for more.

Apple in­tro­duces MacBook Pro with all‑new M5 Pro and M5 Max, de­liv­er­ing break­through pro per­for­mance and next-level on-de­vice AI

The world’s best pro lap­top raises the bar again with blaz­ing-fast CPU and GPU per­for­mance, plus up to 2x faster SSD speeds and 1TB of start­ing stor­age

Apple to­day an­nounced the lat­est 14- and 16-inch MacBook Pro with the all-new M5 Pro and M5 Max, bring­ing game-chang­ing per­for­mance and AI ca­pa­bil­i­ties to the world’s best pro lap­top. With M5 Pro and M5 Max, MacBook Pro fea­tures a new CPU with the world’s fastest CPU core,1 a next-gen­er­a­tion GPU with a Neural Accelerator in each core, and higher uni­fied mem­ory band­width, al­to­gether de­liv­er­ing up to 4x AI per­for­mance com­pared to the pre­vi­ous gen­er­a­tion, and up to 8x AI per­for­mance com­pared to M1 mod­els.2 This al­lows de­vel­op­ers, re­searchers, busi­ness pro­fes­sion­als, and cre­atives to un­lock new AI-enabled work­flows right on MacBook Pro. It now comes with up to 2x faster SSD per­for­mance2 and starts at 1TB of stor­age for M5 Pro and 2TB for M5 Max. The new MacBook Pro in­cludes N1, an Apple-designed wire­less net­work­ing chip that en­ables Wi-Fi 7 and Bluetooth 6, bring­ing im­proved per­for­mance and re­li­a­bil­ity to wire­less con­nec­tions. It also of­fers up to 24 hours of bat­tery life; a gor­geous Liquid Retina XDR dis­play with a nano-tex­ture op­tion; a wide ar­ray of con­nec­tiv­ity, in­clud­ing Thunderbolt 5; a 12MP Center Stage cam­era; stu­dio-qual­ity mics; an im­mer­sive six-speaker sound sys­tem; Apple Intelligence fea­tures; and the power of ma­cOS Tahoe. The new MacBook Pro comes in space black and sil­ver, and is avail­able to pre-or­der start­ing to­mor­row, March 4, with avail­abil­ity be­gin­ning Wednesday, March 11.

“MacBook Pro with M5 Pro and M5 Max re­de­fines what’s pos­si­ble on a pro lap­top, now up to 4x faster than the pre­vi­ous gen­er­a­tion,” said John Ternus, Apple’s se­nior vice pres­i­dent of Hardware Engineering. “With Neural Accelerators in the GPU, the new MacBook Pro en­ables pro­fes­sion­als to run ad­vanced LLMs on de­vice and un­lock ca­pa­bil­i­ties that no other lap­top can do — all while main­tain­ing ex­cep­tional bat­tery life. Combined with even faster uni­fied mem­ory and stor­age, it em­pow­ers users to take their work even fur­ther, un­leash­ing new pos­si­bil­i­ties and push­ing the bound­aries of what they can do.”

On the new MacBook Pro, LLMs will run even faster in pop­u­lar apps like LM Studio.

On the new MacBook Pro, im­age analy­sis will run even faster in pop­u­lar apps like QuPath.

Scaling up per­for­mance from M5 and of­fer­ing the same break­through GPU ar­chi­tec­ture with a Neural Accelerator in each core, M5 Pro and M5 Max de­liver up to 4x faster LLM prompt pro­cess­ing than M4 Pro and M4 Max, and up to 8x AI im­age gen­er­a­tion than M1 Pro and M1 Max.2 This en­ables AI re­searchers and de­vel­op­ers to train cus­tom mod­els lo­cally, and cre­ative pro­fes­sion­als to lever­age AI-powered tools for video edit­ing, mu­sic pro­duc­tion, and de­sign work. Both chips also bring up to a 50 per­cent in­crease in graph­ics per­for­mance com­pared to M4 Pro and M4 Max,3,4 en­abling mo­tion de­sign­ers to work with com­plex 3D scenes in real time and VFX artists to pre­view ef­fects in­stantly. And with a faster and more power-ef­fi­cient Neural Engine and higher uni­fied mem­ory band­width, the new MacBook Pro de­liv­ers in­cred­i­ble on-de­vice AI ca­pa­bil­i­ties. The in­crease in uni­fied mem­ory band­width en­ables com­plex work­flows like in­ten­sive AI model train­ing and mas­sive video pro­jects. M5 Pro sup­ports up to 64GB of uni­fied mem­ory with up to 307GB/s of mem­ory band­width, while M5 Max sup­ports up to 128GB of uni­fied mem­ory with up to 614GB/s of mem­ory band­width.

With the power of M5 Pro and M5 Max on MacBook Pro, AI re­searchers and de­vel­op­ers can train cus­tom mod­els lo­cally, and cre­ative pro­fes­sion­als are able to lever­age AI-powered tools for video edit­ing, mu­sic pro­duc­tion, and de­sign work.

With the power of M5 Pro and M5 Max on MacBook Pro, AI re­searchers and de­vel­op­ers can train cus­tom mod­els lo­cally, and cre­ative pro­fes­sion­als are able to lever­age AI-powered tools for video edit­ing, mu­sic pro­duc­tion, and de­sign work.

With the power of M5 Pro and M5 Max on MacBook Pro, AI re­searchers and de­vel­op­ers can train cus­tom mod­els lo­cally, and cre­ative pro­fes­sion­als are able to lever­age AI-powered tools for video edit­ing, mu­sic pro­duc­tion, and de­sign work.

Up to 7.8x faster AI im­age gen­er­a­tion per­for­mance when com­pared to MacBook Pro with M1 Pro, and up to 3.7x faster than MacBook Pro with M4 Pro.

Up to 6.9x faster LLM prompt pro­cess­ing when com­pared to MacBook Pro with M1 Pro, and up to 3.9x faster than MacBook Pro with M4 Pro.

Up to 5.2x faster 3D ren­der­ing in Maxon Redshift when com­pared to MacBook Pro with M1 Pro, and up to 1.4x faster than MacBook Pro with M4 Pro.

Up to 1.6x faster gam­ing per­for­mance with ray trac­ing in games like Cyberpunk 2077: Ultimate Edition when com­pared to MacBook Pro with M4 Pro.

Up to 8x faster AI im­age gen­er­a­tion per­for­mance when com­pared to MacBook Pro with M1 Max, and up to 3.8x faster than MacBook Pro with M4 Max.

Up to 6.7x faster LLM prompt pro­cess­ing when com­pared to MacBook Pro with M1 Max, and up to 4x faster than MacBook Pro with M4 Max.

Up to 5.4x faster video ef­fects ren­der­ing per­for­mance in Blackmagic DaVinci Resolve Studio when com­pared to MacBook Pro with M1 Max, and up to 3x faster than MacBook Pro with M4 Max.

Up to 3.5x faster AI video-en­hanc­ing per­for­mance in Topaz Video when com­pared to MacBook Pro with M4 Max.

With up to 2x faster read/​write per­for­mance, reach­ing speeds of up to 14.5GB/s, the new MacBook Pro ac­cel­er­ates work­flows for pro­fes­sion­als work­ing across 4K and 8K video pro­jects.

A MacBook Pro user sits out­side with a tele­scope un­der a starry night’s sky.

A MacBook Pro user works at their desk with two ex­ter­nal dis­plays.

The new MacBook Pro de­liv­ers up to a phe­nom­e­nal 24 hours of bat­tery life, so up­graders can take their pro work­flows any­where.

The gor­geous Liquid Retina XDR dis­play de­liv­ers 1600 nits peak HDR bright­ness and up to 1000 nits for SDR con­tent for stun­ning vi­su­als.

The new MacBook Pro can drive up to two high-res­o­lu­tion ex­ter­nal dis­plays with M5 Pro, and up to four high-res­o­lu­tion dis­plays with M5 Max, pro­vid­ing the flex­i­bil­ity to cre­ate ex­pan­sive work­spaces.

Customers can pre-or­der the new 14- and 16-inch MacBook Pro mod­els with M5 Pro and M5 Max start­ing to­mor­row, March 4, on ap­ple.com/​store and in the Apple Store app in 33 coun­tries and re­gions, in­clud­ing the U. S. All mod­els will be­gin ar­riv­ing to cus­tomers, and will be in Apple Store lo­ca­tions and Apple Authorized Resellers, start­ing Wednesday, March 11.

The 14‑inch MacBook Pro with M5 Pro starts at $2,199 (U.S.) and $2,049 (U.S.) for ed­u­ca­tion; and the 16‑inch MacBook Pro with M5 Pro starts at $2,699 (U.S.) and $2,499 (U.S.) for ed­u­ca­tion.

The 14‑inch MacBook Pro with M5 Max starts at $3,599 (U.S.) and $3,299 (U.S.) for ed­u­ca­tion; and the 16‑inch MacBook Pro with M5 Max starts at $3,899 (U.S.) and $3,599 (U.S.) for ed­u­ca­tion. All mod­els are avail­able in space black and sil­ver.

Additional tech­ni­cal spec­i­fi­ca­tions, con­fig­ure-to-or­der op­tions, and ac­ces­sories are avail­able at ap­ple.com/​mac.

The 14-inch MacBook Pro with M5 now comes stan­dard with 1TB of stor­age, and is avail­able in space black and sil­ver, start­ing at $1,699 (U.S.) and $1,599 (U.S.) for ed­u­ca­tion.

With Apple Trade In, cus­tomers can trade in their cur­rent com­puter and get credit to­ward a new Mac. Customers can visit ap­ple.com/​shop/​trade-in to see what their de­vice is worth.

AppleCare de­liv­ers ex­cep­tional ser­vice and sup­port, with flex­i­ble op­tions for Apple users. Customers can choose AppleCare+ to cover their new Mac, or in the U.S., AppleCare One to pro­tect mul­ti­ple prod­ucts in one sim­ple plan. Both plans in­clude cov­er­age for ac­ci­dents like drops and spills, theft and loss pro­tec­tion on el­i­gi­ble prod­ucts, bat­tery re­place­ment ser­vice, and 24/7 sup­port from Apple Experts. For more in­for­ma­tion, visit ap­ple.com/​ap­ple­care.

Every cus­tomer who buys di­rectly from Apple Retail gets ac­cess to Personal Setup. In these guided on­line ses­sions, a Specialist can walk them through setup or fo­cus on fea­tures that will help them make the most of their new de­vice. Customers can also learn more about get­ting started and go­ing fur­ther with their new de­vice with a Today at Apple ses­sion at their near­est Apple Store.

Customers in the U.S. who shop at Apple us­ing Apple Card can pay monthly at 0 per­cent APR when they choose to check out with Apple Card Monthly Installments, and they’ll get 3 per­cent Daily Cash back — all up front. More in­for­ma­tion — in­clud­ing de­tails on el­i­gi­bil­ity, ex­clu­sions, and Apple Card terms — is avail­able at ap­ple.com/​ap­ple-card/​monthly-in­stall­ments.

Apple in­tro­duces MacBook Pro with all‑new M5 Pro and M5 Max, de­liv­er­ing break­through pro per­for­mance and next-level on-de­vice AI

The world’s best pro lap­top raises the bar again with blaz­ing-fast CPU and GPU per­for­mance, plus up to 2x faster SSD speeds and 1TB of start­ing stor­age

CUPERTINO, CALIFORNIA Apple to­day an­nounced the lat­est 14- and 16-inch MacBook Pro with the all-new M5 Pro and M5 Max, bring­ing game-chang­ing per­for­mance and AI ca­pa­bil­i­ties to the world’s best pro lap­top. With M5 Pro and M5 Max, MacBook Pro fea­tures a new CPU with the world’s fastest CPU core,1 a next-gen­er­a­tion GPU with a Neural Accelerator in each core, and higher uni­fied mem­ory band­width, al­to­gether de­liv­er­ing up to 4x AI per­for­mance com­pared to the pre­vi­ous gen­er­a­tion, and up to 8x AI per­for­mance com­pared to M1 mod­els.2 This al­lows de­vel­op­ers, re­searchers, busi­ness pro­fes­sion­als, and cre­atives to un­lock new AI-enabled work­flows right on MacBook Pro. It now comes with up to 2x faster SSD per­for­mance2 and starts at 1TB of stor­age for M5 Pro and 2TB for M5 Max. The new MacBook Pro in­cludes N1, an Apple-designed wire­less net­work­ing chip that en­ables Wi-Fi 7 and Bluetooth 6, bring­ing im­proved per­for­mance and re­li­a­bil­ity to wire­less con­nec­tions. It also of­fers up to 24 hours of bat­tery life; a gor­geous Liquid Retina XDR dis­play with a nano-tex­ture op­tion; a wide ar­ray of con­nec­tiv­ity, in­clud­ing Thunderbolt 5; a 12MP Center Stage cam­era; stu­dio-qual­ity mics; an im­mer­sive six-speaker sound sys­tem; Apple Intelligence fea­tures; and the power of ma­cOS Tahoe. The new MacBook Pro comes in space black and sil­ver, and is avail­able to pre-or­der start­ing to­mor­row, March 4, with avail­abil­ity be­gin­ning Wednesday, March 11.

“MacBook Pro with M5 Pro and M5 Max re­de­fines what’s pos­si­ble on a pro lap­top, now up to 4x faster than the pre­vi­ous gen­er­a­tion,” said John Ternus, Apple’s se­nior vice pres­i­dent of Hardware Engineering. “With Neural Accelerators in the GPU, the new MacBook Pro en­ables pro­fes­sion­als to run ad­vanced LLMs on de­vice and un­lock ca­pa­bil­i­ties that no other lap­top can do — all while main­tain­ing ex­cep­tional bat­tery life. Combined with even faster uni­fied mem­ory and stor­age, it em­pow­ers users to take their work even fur­ther, un­leash­ing new pos­si­bil­i­ties and push­ing the bound­aries of what they can do.”

M5 Pro and M5 Max are built us­ing the new Apple-designed Fusion Architecture and en­gi­neered from the ground up for AI. This in­no­v­a­tive de­sign com­bines two dies into a sin­gle sys­tem on a chip, pro­vid­ing tremen­dous per­for­mance boosts. M5 Pro and M5 Max fea­ture a new up-to-18-core CPU with 6 su­per cores, the world’s fastest CPU core,1 and 12 all-new per­for­mance cores, op­ti­mized for power-ef­fi­cient, mul­ti­threaded pro work­loads — al­to­gether de­liv­er­ing up to 30 per­cent faster per­for­mance.3 M5 Pro is de­signed for users run­ning com­plex work­flows, like coders op­ti­miz­ing al­go­rithms and pho­tog­ra­phers pro­cess­ing mas­sive im­age li­braries, while M5 Max is for those push­ing the ab­solute lim­its, such as en­gi­neers run­ning rig­or­ous sim­u­la­tions.

Scaling up per­for­mance from M5 and of­fer­ing the same break­through GPU ar­chi­tec­ture with a Neural Accelerator in each core, M5 Pro and M5 Max de­liver up to 4x faster LLM prompt pro­cess­ing than M4 Pro and M4 Max, and up to 8x AI im­age gen­er­a­tion than M1 Pro and M1 Max.2 This en­ables AI re­searchers and de­vel­op­ers to train cus­tom mod­els lo­cally, and cre­ative pro­fes­sion­als to lever­age AI-powered tools for video edit­ing, mu­sic pro­duc­tion, and de­sign work. Both chips also bring up to a 50 per­cent in­crease in graph­ics per­for­mance com­pared to M4 Pro and M4 Max,3,4 en­abling mo­tion de­sign­ers to work with com­plex 3D scenes in real time and VFX artists to pre­view ef­fects in­stantly. And with a faster and more power-ef­fi­cient Neural Engine and higher uni­fied mem­ory band­width, the new MacBook Pro de­liv­ers in­cred­i­ble on-de­vice AI ca­pa­bil­i­ties. The in­crease in uni­fied mem­ory band­width en­ables com­plex work­flows like in­ten­sive AI model train­ing and mas­sive video pro­jects. M5 Pro sup­ports up to 64GB of uni­fied mem­ory with up to 307GB/s of mem­ory band­width, while M5 Max sup­ports up to 128GB of uni­fied mem­ory with up to 614GB/s of mem­ory band­width.

Up to 7.8x faster AI im­age gen­er­a­tion per­for­mance when com­pared to MacBook Pro with M1 Pro, and up to 3.7x faster than MacBook Pro with M4 Pro.

Up to 6.9x faster LLM prompt pro­cess­ing when com­pared to MacBook Pro with M1 Pro, and up to 3.9x faster than MacBook Pro with M4 Pro.

Up to 5.2x faster 3D ren­der­ing in Maxon Redshift when com­pared to MacBook Pro with M1 Pro, and up to 1.4x faster than MacBook Pro with M4 Pro.

Up to 1.6x faster gam­ing per­for­mance with ray trac­ing in games like Cyberpunk 2077: Ultimate Edition when com­pared to MacBook Pro with M4 Pro.

Up to 8x faster AI im­age gen­er­a­tion per­for­mance when com­pared to MacBook Pro with M1 Max, and up to 3.8x faster than MacBook Pro with M4 Max.

Up to 6.7x faster LLM prompt pro­cess­ing when com­pared to MacBook Pro with M1 Max, and up to 4x faster than MacBook Pro with M4 Max.

Up to 5.4x faster video ef­fects ren­der­ing per­for­mance in Blackmagic DaVinci Resolve Studio when com­pared to MacBook Pro with M1 Max, and up to 3x faster than MacBook Pro with M4 Max.

Up to 3.5x faster AI video-en­hanc­ing per­for­mance in Topaz Video when com­pared to MacBook Pro with M4 Max.

The new MacBook Pro de­liv­ers up to 2x faster read/​write per­for­mance com­pared to the pre­vi­ous gen­er­a­tion,4 reach­ing speeds of up to 14.5GB/s5 and ac­cel­er­at­ing work­flows for pro­fes­sion­als work­ing across 4K and 8K video pro­jects, LLMs, and com­plex datasets. MacBook Pro with M5 Pro now comes stan­dard with 1TB of stor­age, while MacBook Pro with M5 Max now comes stan­dard with 2TB. And the 14-inch MacBook Pro with M5 now comes stan­dard with 1TB of stor­age.

Even More Value for Upgraders

The new 14- and 16-inch MacBook Pro with M5 Pro and M5 Max mark a ma­jor leap for pro users. There’s never been a bet­ter time for cus­tomers to up­grade from a pre­vi­ous gen­er­a­tion of MacBook Pro with Apple sil­i­con or an Intel-based Mac.

Enhanced AI per­for­mance with Neural Accelerators in the GPU: Users up­grad­ing from M1 mod­els will ex­pe­ri­ence up to 8x faster AI per­for­mance.2

Exceptional bat­tery life: The new MacBook Pro gets up to 24 hours of bat­tery life, giv­ing Intel-based up­graders up to 13 ad­di­tional hours, and users com­ing from M1 mod­els will get up to three more hours, so they can get more done on a sin­gle charge.2 And un­like many PC lap­tops, MacBook Pro de­liv­ers the same in­cred­i­ble per­for­mance whether plugged in or on bat­tery. Users will be able to fast-charge up to 50 per­cent in just 30 min­utes us­ing a 96W or higher USB-C power adapter.2

Best dis­play in a pro lap­top: Upgraders will en­joy the Liquid Retina XDR dis­play, which fea­tures 1600 nits peak HDR bright­ness and up to 1000 nits for SDR con­tent, and of­fers a nano-tex­ture op­tion.

Comprehensive con­nec­tiv­ity: The new MacBook Pro has a wide ar­ray of con­nec­tiv­ity op­tions, in­clud­ing three Thunderbolt 5 ports for high-speed data trans­fer, HDMI that sup­ports up to 8K res­o­lu­tion, an SDXC card slot for quick me­dia im­port, and MagSafe 3 with fast-charge ca­pa­bil­ity. Upgraders can also drive up to two high-res­o­lu­tion ex­ter­nal dis­plays with M5 Pro, and up to four high-res­o­lu­tion dis­plays with M5 Max, pro­vid­ing the flex­i­bil­ity to cre­ate ex­pan­sive work­spaces.

Wi-Fi 7 and Bluetooth 6: With the Apple N1 chip, Wi-Fi 7 and Bluetooth 6 bring im­proved per­for­mance and re­li­a­bil­ity to wire­less con­nec­tions.

Advanced cam­era, mics, and speak­ers: Featuring a 12MP Center Stage cam­era with Desk View sup­port and stu­dio-qual­ity mics, the new MacBook Pro will al­low users to look and sound their best while tak­ing calls. They will also ex­pe­ri­ence an im­mer­sive six-speaker sound sys­tem with sup­port for Spatial Audio.

ma­cOS Tahoe trans­forms the MacBook Pro ex­pe­ri­ence with pow­er­ful ca­pa­bil­i­ties that tur­bocharge pro­duc­tiv­ity.6 Major up­dates to Spotlight make it eas­ier to find rel­e­vant apps and files and im­me­di­ately take ac­tion right from the search bar. Apple Intelligence is even more ca­pa­ble while pro­tect­ing users’ pri­vacy at every step.7 Shortcuts get even more pow­er­ful with in­tel­li­gent ac­tions and the abil­ity to tap di­rectly in to Apple Intelligence mod­els. Integrated into Messages, FaceTime, and the Phone app, Live Translation helps users eas­ily com­mu­ni­cate across lan­guages, trans­lat­ing text and au­dio.7 Additionally, de­vel­op­ers can bring Apple Intelligence ca­pa­bil­i­ties into their ap­pli­ca­tions or tap in to the Foundation Models frame­work for spe­cial­ized on-de­vice in­tel­li­gence tasks. Continuity fea­tures in­clude the Phone app on Mac, which lets users re­lay cel­lu­lar calls from their nearby iPhone, and with Live Activities from iPhone, they can stay on top of things hap­pen­ing in real time.6 ma­cOS Tahoe also fea­tures a beau­ti­ful new de­sign with Liquid Glass, and users can per­son­al­ize their Mac in even more ways with an up­dated Control Center, in ad­di­tion to new color op­tions for fold­ers, app icons, and wid­gets.

MacBook Pro was built with the en­vi­ron­ment in mind, and brings Apple even closer to reach­ing its am­bi­tious plan to be car­bon neu­tral across its en­tire foot­print by 2030. It is made with 45 per­cent re­cy­cled con­tent,8 in­clud­ing 100 per­cent re­cy­cled alu­minum in the en­clo­sure and 100 per­cent re­cy­cled cobalt in the bat­tery. It is man­u­fac­tured with 50 per­cent re­new­able elec­tric­ity, such as wind and so­lar, across the sup­ply chain. The new MacBook Pro is de­signed to be durable and re­pairable, and also of­fers in­dus­try-lead­ing soft­ware sup­port, while meet­ing Apple’s high stan­dards for en­ergy ef­fi­ciency and safer chem­istry. The pa­per pack­ag­ing is 100 per­cent fiber-based and can be eas­ily re­cy­cled.9

Customers can pre-or­der the new 14- and 16-inch MacBook Pro mod­els with M5 Pro and M5 Max start­ing to­mor­row, March 4, on ap­ple.com/​store and in the Apple Store app in 33 coun­tries and re­gions, in­clud­ing the U.S. All mod­els will be­gin ar­riv­ing to cus­tomers, and will be in Apple Store lo­ca­tions and Apple Authorized Resellers, start­ing Wednesday, March 11.

The 14‑inch MacBook Pro with M5 Pro starts at $2,199 (U.S.) and $2,049 (U.S.) for ed­u­ca­tion; and the 16‑inch MacBook Pro with M5 Pro starts at $2,699 (U.S.) and $2,499 (U.S.) for ed­u­ca­tion.

The 14‑inch MacBook Pro with M5 Max starts at $3,599 (U.S.) and $3,299 (U.S.) for ed­u­ca­tion; and the 16‑inch MacBook Pro with M5 Max starts at $3,899 (U.S.) and $3,599 (U.S.) for ed­u­ca­tion. All mod­els are avail­able in space black and sil­ver.

Additional tech­ni­cal spec­i­fi­ca­tions, con­fig­ure-to-or­der op­tions, and ac­ces­sories are avail­able at ap­ple.com/​mac.

The 14-inch MacBook Pro with M5 now comes stan­dard with 1TB of stor­age, and is avail­able in space black and sil­ver, start­ing at $1,699 (U.S.) and $1,599 (U.S.) for ed­u­ca­tion.

With Apple Trade In, cus­tomers can trade in their cur­rent com­puter and get credit to­ward a new Mac. Customers can visit ap­ple.com/​shop/​trade-in to see what their de­vice is worth.

AppleCare de­liv­ers ex­cep­tional ser­vice and sup­port, with flex­i­ble op­tions for Apple users. Customers can choose AppleCare+ to cover their new Mac, or in the U.S., AppleCare One to pro­tect mul­ti­ple prod­ucts in one sim­ple plan. Both plans in­clude cov­er­age for ac­ci­dents like drops and spills, theft and loss pro­tec­tion on el­i­gi­ble prod­ucts, bat­tery re­place­ment ser­vice, and 24/7 sup­port from Apple Experts. For more in­for­ma­tion, visit ap­ple.com/​ap­ple­care.

Every cus­tomer who buys di­rectly from Apple Retail gets ac­cess to Personal Setup. In these guided on­line ses­sions, a Specialist can walk them through setup or fo­cus on fea­tures that will help them make the most of their new de­vice. Customers can also learn more about get­ting started and go­ing fur­ther with their new de­vice with a Today at Apple ses­sion at their near­est Apple Store.

Customers in the U.S. who shop at Apple us­ing Apple Card can pay monthly at 0 per­cent APR when they choose to check out with Apple Card Monthly Installments, and they’ll get 3 per­cent Daily Cash back — all up front. More in­for­ma­tion — in­clud­ing de­tails on el­i­gi­bil­ity, ex­clu­sions, and Apple Card terms — is avail­able at ap­ple.com/​ap­ple-card/​monthly-in­stall­ments.

About Apple

Apple rev­o­lu­tion­ized per­sonal tech­nol­ogy with the in­tro­duc­tion of the Macintosh in 1984. Today, Apple leads the world in in­no­va­tion with iPhone, iPad, Mac, AirPods, Apple Watch, and Apple Vision Pro. Apple’s six soft­ware plat­forms — iOS, iPa­dOS, ma­cOS, watchOS, vi­sionOS, and tvOS — pro­vide seam­less ex­pe­ri­ences across all Apple de­vices and em­power peo­ple with break­through ser­vices in­clud­ing the App Store, Apple Music, Apple Pay, iCloud, and Apple TV. Apple’s more than 150,000 em­ploy­ees are ded­i­cated to mak­ing the best prod­ucts on earth and to leav­ing the world bet­ter than we found it.

Testing was con­ducted by Apple in February 2026 us­ing ship­ping com­pet­i­tive sys­tems and se­lect in­dus­try-stan­dard bench­marks.

Testing was con­ducted by Apple in January and February 2026. See ap­ple.com/​mac­book-pro for more in­for­ma­tion.

Results are com­pared to pre­vi­ous-gen­er­a­tion 16-inch MacBook Pro with Apple M4 Pro, 14-core CPU, 20-core GPU, 48GB of uni­fied mem­ory, and a 4TB SSD.

Results are com­pared to pre­vi­ous-gen­er­a­tion 16-inch MacBook Pro with Apple M4 Max, 16-core CPU, 40-core GPU, 128GB of uni­fied mem­ory, and an 8TB SSD.

Testing was con­ducted by Apple in January and February 2026 us­ing pre­pro­duc­tion 16-inch MacBook Pro sys­tems with Apple M5 Max, 18-core CPU, 40-core GPU, 128GB of uni­fied mem­ory, and an 8TB SSD. Tested with FIO 3.41, 1024KB re­quest size, 10GB test file and IO depth=8. Performance tests are con­ducted us­ing spe­cific com­puter sys­tems and re­flect the ap­prox­i­mate per­for­mance of MacBook Pro.

ma­cOS Tahoe is avail­able as a free soft­ware up­date. Some fea­tures may not be avail­able in all re­gions or in all lan­guages. See re­quire­ments at ap­ple.com/​os/​ma­cos.

Apple Intelligence is avail­able in beta with sup­port for these lan­guages: English, Danish, Dutch, French, German, Italian, Norwegian, Portuguese, Spanish, Swedish, Turkish, Vietnamese, Chinese (simplified), Chinese (traditional), Japanese, and Korean. Some fea­tures may not be avail­able in all re­gions or lan­guages. For fea­ture and lan­guage avail­abil­ity and sys­tem re­quire­ments, see sup­port.ap­ple.com/​en-us/​121115.

Product re­cy­cled or re­new­able con­tent is the mass of cer­ti­fied re­cy­cled ma­te­r­ial rel­a­tive to the over­all mass of the de­vice, not in­clud­ing pack­ag­ing or in-box ac­ces­sories.

Breakdown of U.S. re­tail pack­ag­ing by weight. Adhesives, inks, and coat­ings are ex­cluded from cal­cu­la­tions.

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* Up to 7.8x faster AI im­age gen­er­a­tion per­for­mance when com­pared to MacBook Pro with M1 Pro, and up to 3.7x faster than MacBook Pro with M4 Pro.

* Up to 6.9x faster LLM prompt pro­cess­ing when com­pared to MacBook Pro with M1 Pro, and up to 3.9x faster than MacBook Pro with M4 Pro.

* Up to 5.2x faster 3D ren­der­ing in Maxon Redshift when com­pared to MacBook Pro with M1 Pro, and up to 1.4x faster than MacBook Pro with M4 Pro.

* Up to 1.6x faster gam­ing per­for­mance with ray trac­ing in games like Cyberpunk 2077: Ultimate Edition when com­pared to MacBook Pro with M4 Pro.

* Up to 8x faster AI im­age gen­er­a­tion per­for­mance when com­pared to MacBook Pro with M1 Max, and up to 3.8x faster than MacBook Pro with M4 Max.

* Up to 6.7x faster LLM prompt pro­cess­ing when com­pared to MacBook Pro with M1 Max, and up to 4x faster than MacBook Pro with M4 Max.

* Up to 5.4x faster video ef­fects ren­der­ing per­for­mance in Blackmagic DaVinci Resolve Studio when com­pared to MacBook Pro with M1 Max, and up to 3x faster than MacBook Pro with M4 Max.

* Up to 3.5x faster AI video-en­hanc­ing per­for­mance in Topaz Video when com­pared to MacBook Pro with M4 Max.

* Enhanced AI per­for­mance with Neural Accelerators in the GPU: Users up­grad­ing from M1 mod­els will ex­pe­ri­ence up to 8x faster AI per­for­mance.2

* Exceptional bat­tery life: The new MacBook Pro gets up to 24 hours of bat­tery life, giv­ing Intel-based up­graders up to 13 ad­di­tional hours, and users com­ing from M1 mod­els will get up to three more hours, so they can get more done on a sin­gle charge.2 And un­like many PC lap­tops, MacBook Pro de­liv­ers the same in­cred­i­ble per­for­mance whether plugged in or on bat­tery. Users will be able to fast-charge up to 50 per­cent in just 30 min­utes us­ing a 96W or higher USB-C power adapter.2

* Best dis­play in a pro lap­top: Upgraders will en­joy the Liquid Retina XDR dis­play, which fea­tures 1600 nits peak HDR bright­ness and up to 1000 nits for SDR con­tent, and of­fers a nano-tex­ture op­tion.

* Comprehensive con­nec­tiv­ity: The new MacBook Pro has a wide ar­ray of con­nec­tiv­ity op­tions, in­clud­ing three Thunderbolt 5 ports for high-speed data trans­fer, HDMI that sup­ports up to 8K res­o­lu­tion, an SDXC card slot for quick me­dia im­port, and MagSafe 3 with fast-charge ca­pa­bil­ity. Upgraders can also drive up to two high-res­o­lu­tion ex­ter­nal dis­plays with M5 Pro, and up to four high-res­o­lu­tion dis­plays with M5 Max, pro­vid­ing the flex­i­bil­ity to cre­ate ex­pan­sive work­spaces.

* Wi-Fi 7 and Bluetooth 6: With the Apple N1 chip, Wi-Fi 7 and Bluetooth 6 bring im­proved per­for­mance and re­li­a­bil­ity to wire­less con­nec­tions.

* Advanced cam­era, mics, and speak­ers: Featuring a 12MP Center Stage cam­era with Desk View sup­port and stu­dio-qual­ity mics, the new MacBook Pro will al­low users to look and sound their best while tak­ing calls. They will also ex­pe­ri­ence an im­mer­sive six-speaker sound sys­tem with sup­port for Spatial Audio.

* Customers can pre-or­der the new 14- and 16-inch MacBook Pro mod­els with M5 Pro and M5 Max start­ing to­mor­row, March 4, on ap­ple.com/​store and in the Apple Store app in 33 coun­tries and re­gions, in­clud­ing the U.S. All mod­els will be­gin ar­riv­ing to cus­tomers, and will be in Apple Store lo­ca­tions and Apple Authorized Resellers, start­ing Wednesday, March 11.

* The 14‑inch MacBook Pro with M5 Pro starts at $2,199 (U.S.) and $2,049 (U.S.) for ed­u­ca­tion; and the 16‑inch MacBook Pro with M5 Pro starts at $2,699 (U.S.) and $2,499 (U.S.) for ed­u­ca­tion.

* The 14‑inch MacBook Pro with M5 Max starts at $3,599 (U.S.) and $3,299 (U.S.) for ed­u­ca­tion; and the 16‑inch MacBook Pro with M5 Max starts at $3,899 (U.S.) and $3,599 (U.S.) for ed­u­ca­tion. All mod­els are avail­able in space black and sil­ver.

* Additional tech­ni­cal spec­i­fi­ca­tions, con­fig­ure-to-or­der op­tions, and ac­ces­sories are avail­able at ap­ple.com/​mac.

* The 14-inch MacBook Pro with M5 now comes stan­dard with 1TB of stor­age, and is avail­able in space black and sil­ver, start­ing at $1,699 (U.S.) and $1,599 (U.S.) for ed­u­ca­tion.

* With Apple Trade In, cus­tomers can trade in their cur­rent com­puter and get credit to­ward a new Mac. Customers can visit ap­ple.com/​shop/​trade-in to see what their de­vice is worth.

* AppleCare de­liv­ers ex­cep­tional ser­vice and sup­port, with flex­i­ble op­tions for Apple users. Customers can choose AppleCare+ to cover their new Mac, or in the U.S., AppleCare One to pro­tect mul­ti­ple prod­ucts in one sim­ple plan. Both plans in­clude cov­er­age for ac­ci­dents like drops and spills, theft and loss pro­tec­tion on el­i­gi­ble prod­ucts, bat­tery re­place­ment ser­vice, and 24/7 sup­port from Apple Experts. For more in­for­ma­tion, visit ap­ple.com/​ap­ple­care.

For at least 10 years, every Time Machine set up I have been in charge of, or tasked with main­tain­ing for some­one else, has even­tu­ally run into an is­sue where it stops back­ing up suc­cess­fully. The only so­lu­tion has been to start over, to not in­herit backup state and to man­u­ally delete the old backup. My ex­pe­ri­ence while look­ing up this so­lu­tion re­peat­edly has been that this is not un­com­mon, and def­i­nitely is not just me hold­ing it wrong; in­deed the steps are marked as rec­om­mended so­lu­tions on Apple’s own fo­rums.

For sev­eral years, Spotlight’s tag in­dex has been un­re­li­able. Querying for a file type and a tag of­ten re­turns only a sub­set of the most re­cent files with the tags. Rebuilding the en­tire Spotlight in­dex does noth­ing to al­le­vi­ate this. The only cure is to re­launch the Finder, which some­times fixes it. (There’s also, 13 years af­ter its in­tro­duc­tion, no good, sup­ported and doc­u­mented com­mand line in­ter­face or API to enu­mer­ate, add or re­move tags (aside from those as­sum­ing that they are just the seven col­ors of la­bels). Just say­ing.)

For a few months, Finder has been hav­ing trou­ble with some Spotlight queries some­times. When it hap­pens, ei­ther they seem­ingly kick off and just hang for­ever, or they show re­sults and then as you try to do some­thing, Finder hangs (maybe as a re­sult of a race con­di­tion dur­ing an up­date of the re­sult). The only cure is to re­launch the Finder. Rebuilding the en­tire Spotlight in­dex does noth­ing to al­le­vi­ate this.

For sev­eral years, Finder has been hav­ing trou­ble keep­ing win­dows up to date with folder changes. Most com­monly seen when a pro­gram I’m cod­ing in my day-to-day work writes files to a folder, those files of­ten don’t show up at all. Sometimes you can force it to re­load by back­ing out of the folder, us­ing Go To Folder, en­ter­ing the full path, leav­ing it for a few sec­onds and let­ting the go to panel “autocomplete” the name - for some rea­son, that seems to clear out the cob­webs mo­men­tar­ily and sync with the cur­rent state of the file sys­tem. Sometimes, even that workaround does­n’t work, and the only cure is to re­launch the Finder. Leaving the en­tire com­puter to be for hours on end, then clos­ing all win­dows, then open­ing a new win­dow show­ing the same folder still does not re­fresh the state of the folder. Creating a new folder in the Finder in the af­fected folder, that new folder does ap­pear, but things that did not orig­i­nate from within the Finder - no.

For a year or so, lis­ten­ing to some­thing with AirPods Pro and then open­ing Quick Look in the Finder to see a video with an au­dio track of­ten glitches out the au­dio af­ter a sec­ond or two. The mixed au­dio is fine be­fore and af­ter, but there is a very un­pleas­ant glitch. No firmware or OS up­grade has re­solved the is­sue.

For sev­eral years, switch­ing to a win­dow in a full screen space of­ten does not nec­es­sar­ily fo­cus the win­dow. If you cmd+tab to a win­dow that has its own full screen space, you can see that the win­dow does not ac­tive, and that hit­ting a key­board short­cut that is in­tended to be valid just gives you a beep. You have to man­u­ally click in the win­dow to ac­ti­vate it. This es­pe­cially af­fects Safari in full screen win­dows with video, where hit­ting space to pause or left/​right to scan is no longer ef­fec­tive.

With the pos­si­ble ex­cep­tion of in­di­vid­ual dodgy Time Machine pro­to­col im­ple­men­ta­tions from third par­ties, all of the is­sues are di­rectly trace­able to com­po­nents fully in Apple’s con­trol. None of these is­sues are im­pos­si­ble for Apple to fix. All of them are in­cum­bent on them to do so. Nearly all of them have per­sisted for at least two ma­jor OS re­leases and mul­ti­ple Macs.

In the mid­dle of all this, what Apple chooses to fo­cus on is to im­ple­ment a re­design that no one asked for, that butch­ers both the most con­ceiv­ably fun­da­men­tal us­abil­ity and the vi­sual pleas­ant­ness its user base has self-se­lected its plat­forms for; which only sav­ing grace is that it is half-assed enough to not ac­tu­ally re­ally change some things too badly, com­pared to what it could have been like. Although, had I up­graded to ma­cOS Tahoe, chances are on top of the vi­sual change, I would have been treated to ba­sic Apple Event in­fra­struc­ture falling apart and stop­ping work­ing caus­ing hangs, in­sta­bil­ity and un­pre­dictabil­ity.

I have a MacBook Pro M1 Max from 2021, and be­cause it is an ex­cel­lent piece of hard­ware that still per­forms its func­tion ad­mirably, I have been hold­ing on. The cur­rent state of ma­cOS Tahoe is abysmal - I know be­cause I lis­ten to peo­ple who are long-time Mac users, who say so. If it was more sta­ble, maybe I would do what I did with the last few up­grades, all of which made non-pro­duc­tive tweaks to the user in­ter­face in the in­ter­est of unity across plat­forms, and just up­grade. As it stands now, there’s no chance.

The hard­ware is great and no doubt M5 and M6 vari­ants will run cir­cles around M1, but if I have to sink down fur­ther into this bog, that price is too high to pay - a com­mon enough sen­ti­ment that it is a mat­ter of pub­lic in­ter­est to doc­u­ment downgrad­abil­ity or at­tempt­ing to block dark pat­tern up­grades. (And lest you think this is just Mac-related, the dis­ease has spread at least to the wrist, but I am scop­ing it down some­what for clar­ity.)

At some point, enough has to be enough. Apparently, the up­com­ing ver­sions are go­ing to be bug fix/​im­prove­ment fo­cused re­leases in the vein of the leg­endary Snow Leopard re­lease (which it­self was not un­con­tro­ver­sial at the time of its re­lease for the num­ber of things it re­moved). But with things hav­ing got­ten this bad over so many years, my ques­tion is: does Apple even have the or­ga­ni­za­tional acu­ity to un­der­stand, value and fo­cus on these prob­lems?

Clearly, if not break­ing de­vel­op­ers and users was a pri­or­ity, we would not have been where we are to­day, or would we? Even ig­nor­ing bugs and de­sign changes, in which way does it serve users to phase out Rosetta 2, which in a con­tainer-heavy world is more or less re­quired for de­vel­op­ers due to the ecosys­tem of ARM64 Linux con­tain­ers be­ing nowhere near as wide­spread as for AMD x86-64 ones, and which keeps many ap­pli­ca­tions runnable that oth­er­wise would­n’t be?

My hope is that there are Mac lovers within Apple who bite their tongue at every silly icon re­design, ti­tle bar-shrink­ing de­sign re­or­ga­ni­za­tion, misty shower win­dow—re-skin—love let­ter that they are forced to en­act in­stead of tak­ing what was once (and par­tially still is) that rarest of jew­els, a long-term, con­tin­u­ously up­dated, well-de­signed user in­ter­face and mass mar­ket op­er­at­ing sys­tem and it­er­at­ing on it to make it bet­ter. That there are peo­ple who, in so many words, bleed six col­ors; who have found not just a ster­ile tool, but a cul­ture and a com­mu­nity. And who, like so many oth­ers in so many other sit­u­a­tions, re­cently had to see what they love, what they value, what shaped them, torn apart by shift­ing, switch­ing or re­cently starkly ex­posed pri­or­i­ties of peo­ple above them who ei­ther don’t know what they have, or are happy to use it as a ve­hi­cle and ride it to places they care more about.

My hope is that Macintosh is not just one of these em­pires that was at the height of its power and then dis­in­te­grated be­cause of war­ring fac­tions, sa­ti­ated and un­cu­ri­ous rulers, and droughts for which no one was pre­pared, ru­in­ing crops no one re­al­ized were es­sen­tial for sur­vival.

My hope is that there re­mains a pri­mor­dial spark, a glimpse of ge­nius, to re­dis­cover, to re­con­nect to - to serve not an­nual trends or con­stant phoni­fi­ca­tion, but the needs of the user to use the com­puter as a tool to get some­thing done.

My hope is that, just as Apple crawled out of a hard­ware night­mare pock­marked by ther­mal throt­tling, key­boards in­ca­pac­i­tated by strands of hu­man hair and lack of re­spect for its users needs, it can choose to re­fo­cus its soft­ware and its hu­mil­ity too, and stop do­ing this to the bi­cy­cle for the mind.

The high court had also sought a re­port from the ju­nior judge who had used the AI-generated rul­ings. She told the court that this was her first time us­ing an AI tool and she had be­lieved the ci­ta­tions to be “genuine”. She had no in­ten­tion to mis­quote or mis­rep­re­sent the rul­ings and that “the mis­take oc­curred solely due to the re­liance on an au­to­matic source”, the high court wrote.