I ha­rass the sea with my tiny boat and am called a pi­rate, you do it with a great fleet and are called a king.

I ha­rass the sea with my tiny boat and am called a pi­rate, you do it with a great fleet and are called a king.

Anthropic is ac­tively cam­paign­ing to end soft­ware en­gi­neer­ing. They need you to be­lieve they can do that. Well, maybe it’s not you that they need to con­vince. Maybe it’s your C-Suite, var­i­ous world lead­ers, or the man­ager of your re­tire­ment fund. They’ve raised $132 bil­lion in in­vest­ment, and are ap­proach­ing an IPO val­ued over $1 tril­lion. Since they can­not show prof­itabil­ity, this de­pends on sell­ing their hy­po­thet­i­cal fu­ture im­pact.

In lit­er­ary terms, Anthropic is an un­re­li­able nar­ra­tor.

One of their key nar­ra­tives is: Coding is go­ing away, then the rest of soft­ware en­gi­neer­ing, and even­tu­ally most other hu­man la­bor. This kind of money be­hind this kind of story has an im­pact, re­gard­less of how true we think the story is.

People will make ar­chi­tec­ture, prod­uct, and staffing de­ci­sions based on these events. Many of those de­ci­sions will be based on fear - fear of lay­offs, rap­ture-esk warn­ings of be­ing “Left Behind”, Doom Trolling, etc…

To make good de­ci­sions we need to think clearly, which is hard right now. Put on your skep­ti­cal hat.

Views are my own. I have no his­tory with Zig. I’ve never spo­ken to Andrew Kelley, but found his re­cent JetBrains in­ter­view a great watch.

My in­ter­est here is in pub­lic lit­er­acy about AI in soft­ware. That’s been my ca­reer fo­cus now for 3 years, along with im­prov­ing the tech­nol­ogy it­self. During half of that time I was Chief Architect of a cod­ing agent startup - both a cus­tomer of Anthropic’s mod­els and com­peti­tor to their agent Claude Code. My cur­rent pro­ject is The Coding Agency.

So where were we?

This week, Anthropic / Bun put out their ex­pla­na­tion of the de­ci­sion to port Bun from Zig to Rust. This ex­pla­na­tion came two months af­ter merg­ing the mi­gra­tion to the main­line. Explaining the di­rec­tion be­fore­hand would have been more tra­di­tional in an in­fra­struc­ture pro­ject like this, but mean­while the de­lay con­ve­niently al­lowed the story to be car­ried by sexy head­lines like The Register’s Anthropic’s Bun Rust rewrite merged at speed of AI. Much in­vest. Very wow.

Zig’s cre­ator Andrew Kelley has now put out a re­sponse with his own thoughts. It’s blunt, to an un­usual de­gree. That has ques­tion­able op­tics. As a gen­eral rule, you would not want to worry that when you switch pro­gram­ming lan­guages you will wake up the next morn­ing to the old lan­guage’s leader un­load­ing on your per­sonal flaws. As Dax hi­lar­i­ously put it:

guys we have a pretty sub­stan­tial open­source zig code­base and i’m ter­ri­fied he’s gonna look at it

guys we have a pretty sub­stan­tial open­source zig code­base and i’m ter­ri­fied he’s gonna look at it

Still, as I read Andrew’s piece I found my­self cheer­ing out loud. I may have briefly jumped around the room. Some called his take a “meltdown”, all I can say is he’s gained a new fan to­day.

Sometimes things need to be called out.

What is model be­hav­ior?

On my best days I’d as­pire to some­thing like Buddhist right speech, a high stan­dard that every­thing we say should meet all five of these cri­te­ria.

Is it true?

Is it help­ful?

Is it timely?

Is it kind?

Is it from kind­ness?

We’re break­ing deco­rum a lit­tle, stray­ing into “true, but un­kind” ter­ri­tory. I’m de­fend­ing some­one’s choice to do that. I don’t do that lightly, and I hope it’s help­ful.

Background

Just to catch you up…

Bun is a TypeScript run­time, like a faster NodeJS.

Zig is a sys­tems pro­gram­ming lan­guage, like a mod­ern C.

Bun was writ­ten in Zig un­til re­cently - one of the largest Zig code­bases.

Bun claims near 100% AI con­tri­bu­tions.

Zig al­lows 0% AI con­tri­bu­tions.

Bun was ac­quired by Anthropic, a lead­ing AI model lab.

Bun’s founder ex­per­i­mented with a mas­sive agen­tic rewrite from Zig to un­safe Rust.

That ex­per­i­ment was merged days later and is now the of­fi­cial ver­sion.

This is sit­u­a­tion is con­tro­ver­sial on a few fronts, though ap­par­ently no one in­volved ac­tu­ally wants Bun to stay in Zig. The drama lives purely in the meta-dis­cus­sion. The mi­gra­tion process it­self is pretty in­ter­est­ing, I would con­sider do­ing some­thing sim­i­lar in the right sit­u­a­tion.

Who to be­lieve

When peo­ple choose be­tween Zig and Rust for their pro­jects, they will nat­u­rally see the Bun sit­u­a­tion as a data-point. That fact that one of the biggest Zig users wound up re­vers­ing the de­ci­sion feels rel­e­vant, re­gard­less of the rea­sons. People will try to un­der­stand what hap­pened, and de­cide which is more true:

Anthropic/Bun story: Bun tried every­thing rea­son­able, and was still over­whelmed by mem­ory bugs be­cause Zig was­n’t up to the task.

Anthropic/Bun story: Bun tried every­thing rea­son­able, and was still over­whelmed by mem­ory bugs be­cause Zig was­n’t up to the task.

Andrew’s story: The Bun code is a mess be­cause of their en­gi­neer­ing de­ci­sions, in­clud­ing overus­ing AI agents to write and re­view every­thing.

Andrew’s story: The Bun code is a mess be­cause of their en­gi­neer­ing de­ci­sions, in­clud­ing overus­ing AI agents to write and re­view every­thing.

I’d lean more to­ward the lat­ter, but I sus­pect the dom­i­nant fac­tor is more bor­ing:

Ray’s story: Faced with a le­git­i­mate chal­lenge of mem­ory bugs, there were sev­eral vi­able op­tions. Management ea­gerly ap­proved the Rust rewrite op­tion be­cause it was a great mar­ket­ing op­por­tu­nity to show­case their new Fable model, Anthropic al­ready uses Rust, and Zig is openly against us­ing Anthropic’s prod­ucts.

Ray’s story: Faced with a le­git­i­mate chal­lenge of mem­ory bugs, there were sev­eral vi­able op­tions. Management ea­gerly ap­proved the Rust rewrite op­tion be­cause it was a great mar­ket­ing op­por­tu­nity to show­case their new Fable model, Anthropic al­ready uses Rust, and Zig is openly against us­ing Anthropic’s prod­ucts.

That makes fine busi­ness sense, it just is­n’t a mar­ket­ing story. The mar­ket­ing needed to fo­cus on how their AI was pow­er­ful enough to do this rewrite (even though it was not pow­er­ful enough to catch a use-af­ter-free).

For bet­ter or worse, this bag­gage is now top-of-mind in the Rust vs Zig ques­tion. The sit­u­a­tion tends to pit Jarred’s judge­ment against Andrew’s in the eye’s of the com­mu­nity. Any face-sav­ing ex­ag­ger­a­tion spo­ken through Anthropic’s mega­phone could un­in­ten­tion­ally af­fect Zig’s rep­u­ta­tion.

I can un­der­stand why rather than leave well enough alone, Andrew would de­cide to… add some con­text.

Is this a smear?

From my per­spec­tive, Anthropic is the party we need to hold ac­count­able here. That’s what this is all about. Bun founder Jarred Sumner is get­ting caught in the cross­fire in a sense. So is Zig.

It would be nice if this could be dis­cussed strictly on the tech­ni­cal points, and we’ll get to them. However, I don’t think Anthropic is mak­ing a tech­ni­cal ar­gu­ment, they are deal­ing in spec­ta­cle.

Anthropic is us­ing Jarred’s cred­i­bil­ity to help sell their nar­ra­tive. In re­spond­ing to that, we’re com­ment­ing on his cred­i­bil­ity. That’s messy. I don’t love it.

Still, if re­port­ing the things that some­one says and does comes off as a smear, then maybe that be­hav­ior was part of the prob­lem too.

The meat grinder

My first im­pres­sion of the Bun pro­ject was the 2022 an­nounce­ment, in­clud­ing this warn­ing to re­cruits.

Oven is go­ing to be a grind, es­pe­cially the first nine months or so. If work-life bal­ance means a lot of time spent not work­ing, it’s prob­a­bly not a good fit.

Oven is go­ing to be a grind, es­pe­cially the first nine months or so. If work-life bal­ance means a lot of time spent not work­ing, it’s prob­a­bly not a good fit.

When I see a state­ment like that from a prospec­tive man­ager, it says a num­ber of things, not the least of which is “this per­son has no idea what they are do­ing”. A lot of rea­son­ably good coders have never seen an ex­am­ple of a good man­ager, and have all kinds of weird ideas about what man­age­ment is.

Running at “crunch time” all the time is bad for health and bad for pro­duc­tiv­ity. That is a ro­bustly es­tab­lished fact about knowl­edge work. For some ref­er­ences, see the Human Factors sec­tion of Hillel’s Empirical Software Engineering.

My ad­vice? Don’t work for peo­ple that brag about 90 hour weeks. Work for peo­ple who will de­fend your abil­ity to sleep at night.

In Andrew’s piece, he sum­ma­rizes what he’s heard from the grapevine of the Bun team’s ex­pe­ri­ence:

Poor com­mu­ni­ca­tion, un­re­al­is­tic ex­pec­ta­tions, low em­pa­thy, no ex­pe­ri­ence. Just a to­tal shit show

Poor com­mu­ni­ca­tion, un­re­al­is­tic ex­pec­ta­tions, low em­pa­thy, no ex­pe­ri­ence. Just a to­tal shit show

I mean… of course it was. The hearsay is es­sen­tially re­peat­ing what was an­nounced pub­licly. Their job list­ing might as well have said, “now seek­ing ap­pli­cants for to­tal shit show”. It’s bad form for us to say this out loud. We’re sup­posed to let the Tech Bros go on about how cut­ting cor­ners is some ge­nius pro­duc­tiv­ity hack. Then the peo­ple that lis­ten to them can even­tu­ally call us in to fix the re­sults. It would be a great arrange­ment if I cared less about out­comes. It’s quite lu­cra­tive.

FWIW, I’ve used Bun a few times and liked it well enough. Cool tech is of­ten pro­duced in spite of bad work en­vi­ron­ments. I’m not the one say­ing that their en­vi­ron­ment re­sulted in a buggy un­main­tain­able mess, Bun is the one say­ing that.

Say some­thing nice

The piece about the mi­gra­tion process is very cool, with de­tails that are reusable. No com­plaints, I think that’s the real con­tri­bu­tion here. I par­tic­u­larly like the hon­esty in ex­plain­ing that this was a port to un­safe Rust, al­low­ing a lit­eral file-by-file mi­gra­tion to min­i­mize risk, paving the way for re­design in fu­ture steps. That’s a sen­si­ble move ex­plained well.

There’s some truth to the idea that lan­guage choice is be­com­ing more re­versible. This method will take it’s place among other types of rewrite au­toma­tion with pros and cons. These tech­niques can be com­bined and fur­ther hard­ened with Formal Methods. Darpa’s TRACTOR (Translating All C to Rust) re­search pro­gram pub­lished a re­port this year which should cover the state of the art.

My fa­vorite book on soft­ware mod­ern­iza­tion pro­jects is Kill It With Fire by Marianne Bellotti. As agents al­low us more moves we can make with old code, we still need good judge­ment and com­mu­ni­ca­tion in de­cid­ing where to go. Let’s talk about that next.

The rewrite ra­tio­nale is fluff

These are the ba­sic in­gre­di­ents of ex­plain­ing a tech­ni­cal de­ci­sion:

What is the mo­ti­va­tion?

What op­tions did you con­sider?

What are the pros and cons?

Here’s a great ex­am­ple by Richard Feldman on his de­ci­sion to move the Roc com­piler from Rust to Zig. I was ini­tially shocked by that move (I’m some­what fa­nat­i­cal about lan­guage safety), but ul­ti­mately his points made sense and this started my cu­rios­ity about Zig.

When the Bun rewrite was merged, I’d hoped to see a sim­i­lar treat­ment. This is what we got in­stead, two months late.

✅ What is the mo­ti­va­tion?

⚠️ What op­tions did you con­sider?

🚫 What are the pros and cons?

For the as­pir­ing tech leads out there: When you skimp on these in­gre­di­ents, es­pe­cially the “pros and cons”, you risk giv­ing the im­pres­sion that you ap­proached the prob­lem with one an­swer al­ready in mind and are giv­ing it a post-hoc jus­ti­fi­ca­tion. Maybe you have rea­sons that you aren’t say­ing.

It feels dis­hon­est.

All pros no cons

Rather than a real trade­off com­par­i­son, we get a “Bun is bet­ter in Rust” sec­tion cov­er­ing only up­sides. A change like this al­ways has trade-offs, an ob­vi­ous one would be build time.

Typically when you use Rust for a large code­base, you are buy­ing safety and pay­ing in slower com­pi­la­tion. There’s no shame in that, it can be a win­ning bar­gain. In that past, this fac­tor was im­por­tant enough to Bun that they forked the Zig com­piler to try and im­prove it. If we’re right that the Rust port in­creased build time for con­trib­u­tors, why not dis­close that? It comes off as more cred­i­ble to own the im­pact and the pri­or­i­ties that make it right move over­all.

They also seem to be padding the list by mix­ing in other im­prove­ments they’ve made af­ter the rewrite that aren’t re­ally re­lated to it.

They did­n’t try a style guide?

Recall that the mo­ti­va­tion was mem­ory bugs. Definitely not Bun’s only source of bugs but a fre­quent one, caus­ing four fix com­mits per week by my count. Painful.

Theoretically, every mem­ory bug rep­re­sents a vi­o­la­tion of some con­ven­tion - an ex­pec­ta­tion of how this kind of ob­ject should be dealt with. Therefore it be­hooves us to es­tab­lish a clear idea of what’s ex­pected in what cir­cum­stance. We should try to use any lan­guage ef­fec­tively for that mat­ter, Rust style guides are a thing too, but man­ual mem­ory man­age­ment adds scope to the ex­pec­ta­tions we need.

How have other peo­ple solved this prob­lem? Another flag­ship Zig code­base is TigerBeetle, a fi­nan­cial trans­ac­tion data­base. It is not plagued by mem­ory bugs, in fact it ap­pears to be one of the most re­li­able data­bases in ex­is­tence. They will gladly tell you that this is due to their TigerStyle ap­proach and some in­no­v­a­tive test­ing strate­gies. Worth a look! The word “style” might un­der­sell it, it’s a whole en­gi­neer­ing phi­los­o­phy with Zig cod­ing guide­lines as one el­e­ment.

Here’s a taste of TigerStyle. Not every ap­pli­ca­tion can copy-and-paste this ex­act strat­egy, but it il­lus­trates the re­la­tion­ship be­tween mem­ory al­lo­ca­tion and other de­sign de­ci­sions.

All mem­ory must be sta­t­i­cally al­lo­cated at startup. No mem­ory may be dy­nam­i­cally al­lo­cated (or freed and re­al­lo­cated) af­ter ini­tial­iza­tion. This avoids un­pre­dictable be­hav­ior that can sig­nif­i­cantly af­fect per­for­mance, and avoids use-af­ter-free. As a sec­ond-or­der ef­fect, it is our ex­pe­ri­ence that this also makes for more ef­fi­cient, sim­pler de­signs that are more per­for­mant and eas­ier to main­tain and rea­son about, com­pared to de­signs that do not con­sider all pos­si­ble mem­ory us­age pat­terns up­front as part of the de­sign.

All mem­ory must be sta­t­i­cally al­lo­cated at startup. No mem­ory may be dy­nam­i­cally al­lo­cated (or freed and re­al­lo­cated) af­ter ini­tial­iza­tion. This avoids un­pre­dictable be­hav­ior that can sig­nif­i­cantly af­fect per­for­mance, and avoids use-af­ter-free. As a sec­ond-or­der ef­fect, it is our ex­pe­ri­ence that this also makes for more ef­fi­cient, sim­pler de­signs that are more per­for­mant and eas­ier to main­tain and rea­son about, com­pared to de­signs that do not con­sider all pos­si­ble mem­ory us­age pat­terns up­front as part of the de­sign.

Clearly, if we’re weigh­ing a rewrite in Rust, we’d first con­sider if we should use the cur­rent lan­guage dif­fer­ently. Hear’s how Bun’s write-up pre­sents that op­tion.

Many pro­jects opt to an­swer these kinds of ques­tions through a style guide. TigerBeetle’s TigerStyle is an ex­am­ple in Zig and Google’s 31,000 word C++ style guide is an­other. The chal­lenge with style guides is en­force­ment. How do you make sure the style guide is fol­lowed? Historically, code re­view was the an­swer with best-ef­fort en­force­ment via lin­ters & sta­tic an­a­lyz­ers.

Many pro­jects opt to an­swer these kinds of ques­tions through a style guide. TigerBeetle’s TigerStyle is an ex­am­ple in Zig and Google’s 31,000 word C++ style guide is an­other. The chal­lenge with style guides is en­force­ment. How do you make sure the style guide is fol­lowed? Historically, code re­view was the an­swer with best-ef­fort en­force­ment via lin­ters & sta­tic an­a­lyz­ers.

I ex­pected the next sen­tence to dis­cuss Bun’s style guide, why it was­n’t work­ing, per­haps how it evolved over time… nope. They seem to just pay lip-ser­vice the pri­mary way the com­mu­nity ad­dresses their prob­lem, shrug their shoul­ders and move on. Did I miss some­thing? Over four years on a pro­ject of this size, it’s sur­pris­ing they did­n’t se­ri­ously at­tempt this if they ex­pe­ri­enced these prob­lems. It’s al­most like the pro­ject was run by some­one who tries to hold all the con­text in their head and never have meet­ings.

What’s more be­wil­der­ing is that they dis­miss style guides with hes­i­ta­tions that are re­futed within their own ar­ti­cle. Consider that clas­sic ob­jec­tion that guides are hard to en­force. Fair, though maybe an odd bar­rier for a team ad­vanced enough to fork the com­piler they use. Here’s the thing, they al­ready claim to have solved the en­force­ment prob­lem be­cause they use agen­tic re­view. PORTING.md is it­self a style guide, scoped to the mi­gra­tion process. They have just con­ducted an agen­tic re­view of their en­tire rewrit­ten code­base against strin­gent guide­lines and de­clared it a suc­cess.

This does­n’t make sense. Let’s as­sume agen­tic re­view works, I think it can un­der the right cir­cum­stances. That would re­quire de­sign and well-thought guide­lines. I think they were sim­ply more ex­cited about putting that men­tal en­ergy into a rewrite than a re-ar­chi­tec­ture, for any num­ber of un­stated rea­sons. It may have been the right choice.

We’re still wor­ried about syn­tax?

There’s one more bit I want to nit­pick, a com­mon cog­ni­tive dis­so­nance in dis­cus­sions about agent-first cod­ing. Bun’s piece briefly dives into to the weeds of what a “style guide op­tion” might look like.

Having a rigid style guide with clear own­er­ship ex­pec­ta­tions ex­plic­itly spelled out in the type sys­tem was a real op­tion for Bun. Since Zig has no op­er­a­tor over­load­ing, we would likely end up with a lot of code look­ing some­thing like this:

Every so of­ten the Earth pro­duces a sig­nal that is im­pos­si­ble to ig­nore. This graph is one of them. It shows sea-sur­face tem­per­a­tures in the Niño 3.4 re­gion of the equa­to­r­ial Pacific, one of the most im­por­tant parts of the Earth’s cli­mate sys­tem. Each blue line rep­re­sents a dif­fer­ent year since 1982. The red line is this year. It does­n’t just set a new record. It has de­parted en­tirely from the range of pre­vi­ous ob­ser­va­tions.

If this graph rep­re­sented stock mar­ket prices, a new Olympic record or a med­ical test re­sult, it would dom­i­nate the head­lines. Instead, it is be­ing met largely with si­lence. That si­lence should con­cern us just as much as the graph it­self.

The first thing to un­der­stand is that this is not a com­puter model. It’s not a fore­cast. It’s not a sim­u­la­tion of what might hap­pen decades from now. These are di­rect ob­ser­va­tions from satel­lites, ships and ocean buoys mea­sur­ing the tem­per­a­ture of the trop­i­cal Pacific Ocean. This is re­al­ity un­fold­ing now be­fore our eyes.

The Niño 3.4 re­gion is of­ten de­scribed as the beat­ing heart of the Earth’s cli­mate sys­tem. Changes here in­flu­ence at­mos­pheric cir­cu­la­tion across much of the globe through a phe­nom­e­non known as the El Niño–Southern Oscillation. During El Niño events, warm wa­ter spreads across the cen­tral and east­ern Pacific, al­ter­ing wind pat­terns and re­dis­trib­ut­ing rain­fall around the planet. Australia ex­pe­ri­ences hot­ter, drier con­di­tions with an in­creased risk of drought and bush­fire. South America of­ten re­ceives heav­ier rain­fall and flood­ing, while parts of Asia ex­pe­ri­ence se­vere drought. The con­se­quences are felt in agri­cul­ture, wa­ter sup­plies, ecosys­tems and economies on every con­ti­nent.

El Niño it­self is noth­ing new. It’s been part of Earth’s nat­ural cli­mate vari­abil­ity for thou­sands of years. What’s new is the back­ground cli­mate in which it now op­er­ates. Human ac­tiv­i­ties have in­creased at­mos­pheric car­bon diox­ide con­cen­tra­tions by more than fifty per cent since the Industrial Revolution. Around ninety per cent of the ex­cess heat trapped by these green­house gases has been ab­sorbed by the oceans. The trop­i­cal Pacific is thus no longer os­cil­lat­ing around a cli­mate that ex­isted a cen­tury ago. It’s os­cil­lat­ing around a much warmer base­line. Every El Niño now be­gins with sub­stan­tially more heat al­ready stored in the ocean than was once the case.

That dis­tinc­tion mat­ters be­cause the cli­mate sys­tem is dri­ven by en­ergy. Warmer oceans evap­o­rate more wa­ter. A warmer at­mos­phere can hold more mois­ture. This gives storms more fuel, pro­duc­ing heav­ier rain­fall and more de­struc­tive flood­ing. At the same time, re­gions that miss out on rain­fall ex­pe­ri­ence greater evap­o­ra­tion, in­ten­si­fy­ing droughts and heat­waves. Climate change does­n’t elim­i­nate nat­ural vari­abil­ity; it am­pli­fies it.

Australia’s al­ready ex­pe­ri­enced this am­pli­fi­ca­tion. The Black Summer bush­fires, re­peated coral bleach­ing events on the Great Barrier Reef, ma­rine heat­waves off Western Australia and record-break­ing tem­per­a­tures across the con­ti­nent have all oc­curred in a cli­mate that is sig­nif­i­cantly warmer than that of pre­vi­ous gen­er­a­tions. As the oceans con­tinue to warm, the like­li­hood and sever­ity of these ex­tremes con­tinue to in­crease.

And the con­se­quences ex­tend well be­yond weather. The oceans un­der­pin vir­tu­ally every ma­jor com­po­nent of the Earth’s cli­mate sys­tem. They reg­u­late at­mos­pheric cir­cu­la­tion, trans­port heat around the globe and drive rain­fall pat­terns that sus­tain forests, grass­lands and agri­cul­ture. They also sup­port ma­rine ecosys­tems upon which bil­lions of peo­ple de­pend for food and liveli­hoods.

When ocean tem­per­a­tures move out­side the his­tor­i­cal range, ecosys­tems un­ravel. Coral reefs bleach be­cause mi­cro­scopic al­gae that pro­vide most of their en­ergy can no longer sur­vive pro­longed heat stress. Fish species mi­grate to­wards cooler wa­ters, dis­rupt­ing fish­eries that have ex­isted for cen­turies. Kelp forests col­lapse. Oxygen lev­els de­cline. Marine heat­waves, once con­sid­ered rare, are be­com­ing in­creas­ingly com­mon and in­creas­ingly se­vere. These eco­log­i­cal im­pacts don’t oc­cur in iso­la­tion. They feed back into the cli­mate sys­tem it­self.

Scientists de­scribe the Earth as a net­work of in­ter­con­nected tip­ping el­e­ments. Rather than op­er­at­ing in­de­pen­dently, ma­jor com­po­nents of the cli­mate sys­tem in­flu­ence one an­other. Changes in one part of the sys­tem trig­ger changes else­where, some­times in un­ex­pected ways. The Atlantic Meridional Overturning Circulation, Greenland’s ice sheet, West Antarctica’s glac­i­ers, Arctic sea ice and the Amazon rain­for­est are all ex­pe­ri­enc­ing rapid desta­bil­i­sa­tion.

Each of these sys­tems is un­der stress. Each in­flu­ences oth­ers. The more they change, the greater the risk that the cli­mate sys­tem be­gins to pro­duce cas­cad­ing ef­fects that be­come in­creas­ingly dif­fi­cult - or im­pos­si­ble - to re­verse on hu­man timescales.

Ultimately, though, cli­mate change is not re­ally about ocean tem­per­a­tures, at­mos­pheric cir­cu­la­tion or sta­tis­ti­cal anom­alies. It’s also about peo­ple. Hotter oceans con­tribute to higher food prices, more de­struc­tive storms, de­clin­ing fish­eries, in­creased in­sur­ance costs, re­duced wa­ter se­cu­rity, dam­aged in­fra­struc­ture, wors­en­ing pub­lic health and dis­place­ment of com­mu­ni­ties. They ex­ac­er­bate in­equal­ity be­cause it’s in­vari­ably the poor­est and most vul­ner­a­ble who have the fewest re­sources to adapt. They also in­crease geopo­lit­i­cal in­sta­bil­ity as na­tions com­pete over dwin­dling re­sources and re­spond to grow­ing hu­man­i­tar­ian crises.

This is why graphs like this mat­ter. Not be­cause they prove that cat­a­stro­phe is in­evitable, and not be­cause they pre­dict the pre­cise se­quence of events over com­ing years. Science rarely deals in ab­solutes. What they show is that Earth is mov­ing be­yond the range within which mod­ern hu­man civil­i­sa­tion de­vel­oped. We’re en­ter­ing cli­matic con­di­tions that our in­fra­struc­ture, ecosys­tems, economies and in­sti­tu­tions were never de­signed to ac­com­mo­date.

The ques­tion is whether we’re will­ing to pay at­ten­tion and act be­fore the changes be­come too large, too rapid and too in­ter­con­nected for us to man­age.

Sam Neill, the ver­sa­tile New Zealand ac­tor whose ca­reer spanned Oscar win­ners and block­busters such as The Piano and Jurassic Park, has died aged 78.

The ac­tor’s death was an­nounced on Monday in a state­ment shared on his Instagram ac­count. No cause of death was given, but Neill had only re­cently re­vealed he was can­cer-free af­ter be­ing di­ag­nosed with stage three an­gioim­munoblas­tic T-cell lym­phoma, a type of blood can­cer, in 2022.

“It is with im­mense sad­ness that the whā­nau of Sam Neill share the news of his pass­ing on Monday 13th July, in Sydney Australia. Sam was sur­rounded by fam­ily and passed with the dig­nity that has char­ac­terised his whole life.

“The loss was sud­den and un­ex­pected but blessed by the fact that Sam re­mained can­cer free. They would like to ex­press their deep­est grat­i­tude to the staff at St Vincent’s Private hos­pi­tal for their in­cred­i­ble care.

“More de­tails will be shared later, but for now, on be­half of the fam­ily, we ask that you re­spect their pri­vacy as they nav­i­gate this im­mea­sur­able loss.”

Neill’s peers, friends and ad­mir­ers paid trib­ute to him on Monday as news of his death spread.

Neill was born Nigel John Dermot Neill in 1947 in Omagh, Northern Ireland to an English mother, and a New Zealander fa­ther who was serv­ing in the British army. The Neills moved to New Zealand in 1954. He took the name Sam when he was 12 be­cause there were sev­eral Nigels at his school, and: “I found I moved more eas­ily in the world as a Sam. Nigel is an awk­ward fit in most cir­cum­stances. Imagine be­ing a movie ac­tor called Nigel Neill.”

Neill at­tended school and uni­ver­sity in Christchurch, but did­n’t set­tle on act­ing un­til af­ter he failed a “catastrophic” year of study­ing law. He be­gan ap­pear­ing in Canterbury University pro­duc­tions, and moved to Wellington to join the Downstage Theatre as a pro­fes­sional ac­tor, where he was paid $35 a week and any left­over food from the kitchen from meals served to the au­di­ence be­fore the show.

After some small roles on lo­cal tele­vi­sion, his break­out role was in the 1977 film Sleeping Dogs, the first New Zealand film to open in the US. Soon af­ter that he landed a lead­ing role in My Brilliant Career (1979); played the son of the devil in Omen III (1981); ap­peared in Andrzej Żuławski‘s cult film Possession (1981); in the 1988 biopic Evil Angels (also known as A Cry in the Dark), as Lindy Chamberlain’s hus­band, Michael, op­po­site Meryl Streep; and in The Hunt for Red October (1990). His role in Ivanhoe (1982) made Neill a big name in Sweden, where the film has aired on TV every New Year’s Day for 40 years.

Neill came to wide­spread in­ter­na­tional at­ten­tion in 1993 with two per­for­mances: as New Zealand set­tler Alisdair Stewart in Jane Campion’s Oscar-winner The Piano; and as Dr Alan Grant in Steven Spielberg’s Jurassic Park, a role orig­i­nally of­fered to Harrison Ford. Neill played Alan Grant again in se­quels Jurassic Park III and Jurassic World Dominion.

Neill shaped a ca­reer play­ing mem­o­rable ro­man­tic leads and charis­matic vil­lains. He had more than 150 cred­its over five decades, in­clud­ing Dead Calm, The Jungle Book, In the Mouth of Madness, Event Horizon, Bicentennial Man, The Dish and Peter Rabbit. He was one of the lead­ing can­di­dates to suc­ceed Roger Moore as James Bond and did a screen-test in 1986, but lost out to Timothy Dalton.

In 2016 he starred in Taika Waititi’s break­out hit Hunt for the Wilderpeople, which led to small cameos in Waititi’s Thor: Ragnarok and Thor: Love and Thunder.

Neill also worked in tele­vi­sion, play­ing the cor­rupt Maj Chester Campbell in Peaky Blinders, The Twelve, The Tudors, and episodes of The Simpsons and Rick and Morty. He was nom­i­nated for a Golden Globe for his por­trayal of spy Sidney Reilly in the 1983 minis­eries Reilly, Ace of Spies.

Neill lived on a farm and win­ery called Two Paddocks, in the Central Otago wine re­gion. He de­scribed it as “a ridicu­lously time- and money-con­sum­ing busi­ness. I would not do it if it was not so sat­is­fy­ing and fun, and it gets me pissed once in a while.” He named his farm an­i­mals af­ter his col­leagues, in­clud­ing Laura Dern (chicken), Kylie Minogue (duck) and Helena Bonham Carter (cow).

In 2023, Neill re­vealed in his mem­oir, Did I Ever Tell You This? that he had been un­der­go­ing chemother­apy for a year af­ter be­ing di­ag­nosed with stage three an­gioim­munoblas­tic T-cell lym­phoma, a type of blood can­cer. By the time his book was pub­lished his can­cer was in re­mis­sion, but he un­der­went monthly chemother­apy for the rest of his life, hav­ing signed a con­tract with the drug com­pany that if he was still alive af­ter four months, the treat­ment would be free.

“I’m not afraid to die,” he told the Guardian in 2023, “but it would an­noy me. Because I’d re­ally like an­other decade or two, you know? We’ve built all these lovely ter­races, we’ve got these olive trees and cy­presses, and I want to be around to see it all ma­ture. And I’ve got my lovely lit­tle grand­chil­dren. I want to see them get big. But as for the dy­ing? I could­n’t care less.”

He said he “dreaded” any prospect of re­tire­ment. “Some of it is to do with com­ing from a lit­tle place, the most ob­scure place in the world, as far from any­thing as you could get, and be­ing asked to do some­thing with an in­ter­na­tional di­men­sion. How im­mensely se­duc­tive is that?”

Neill was ap­pointed an Officer of the Order of the British em­pire in 1991 for his ser­vices to act­ing and a Distinguished Companion of the New Zealand Order of Merit (DCNZM) in 2007. Years later, af­ter a change to New Zealand’s ho­n­ours sys­tem al­lowed re­cip­i­ents to con­vert the DCNZM into a knight­hood, Neill ac­cepted a knight­hood and gained the ti­tle sir in 2022.

Neill jok­ingly de­scribed his fam­ily life as “somewhat hap­haz­ard” due to his ca­reer. He is sur­vived by his four chil­dren and eight grand­chil­dren. His chil­dren are Andrew, who was placed for adop­tion when Neill was in his early 20s but re­united with his fa­ther in 1994; Tim, his son with ac­tor Lisa Harrow; Elena, his daugh­ter with makeup artist Noriko Watanabe; and Maiko, Watanabe’s daugh­ter from her first mar­riage, who Neill adopted.

The Los Angeles Police Department (LAPD) is re­port­edly end­ing its deal with Flock Safety, a sur­veil­lance com­pany that helps law en­force­ment track ve­hi­cles us­ing thou­sands of its li­cense plate cam­eras placed across the United States.

A se­nior LAPD of­fi­cial told news out­lets, first re­ported by ABC7 and the Los Angeles Times, that the po­lice de­part­ment would al­low its three-year con­tract with Flock to ex­pire when it ends on Saturday. The de­part­ment cited “serious con­cerns” around civil lib­er­ties and pri­vacy. Flock’s cam­eras are op­er­ated by the Atlanta, Georgia-based com­pany and not the LAPD.

“This con­tract is not be­ing re­newed be­cause of se­ri­ous con­cerns around civil lib­er­ties and civil rights is­sues, par­tic­u­larly around pri­vacy and the data that is be­ing col­lected from these cam­eras,” LAPD’s chief in­for­ma­tion of­fi­cer Dean Gialamas was quoted as say­ing. “The LAPD had to make a dif­fi­cult de­ci­sion, in this case dis­con­tin­u­ing us­ing Flock ser­vices un­til we can get those data, pri­vacy, se­cu­rity and shar­ing con­cerns ironed out through a con­trac­tual re­la­tion­ship.”

A spokesper­son for the LAPD did not re­spond to a re­quest for com­ment from TechCrunch over the week­end, and it’s un­clear if Flock’s cam­eras will con­tinue record­ing in ab­sence of an ac­tive con­tract. According to ABC7, the po­lice de­part­ment is seek­ing new lan­guage in its con­tract ad­dress­ing pri­vacy and data stor­age con­cerns.

As the third-largest po­lice de­part­ment in the U.S., the LAPD is one of Flock’s largest gov­ern­ment cus­tomers to date. Several ma­jor U.S. cities have also stopped work­ing with Flock, in­clud­ing Mountain View, California and South Portland, Maine, cit­ing pri­vacy wor­ries and con­cerns that fed­eral im­mi­gra­tion of­fi­cials used the cam­eras to track peo­ple in vi­o­la­tion of their lo­cal laws gov­ern­ing their sanc­tu­ary city poli­cies.

The con­tract ex­piry caught the sur­veil­lance com­pany by “surprise,” said Flock spokesper­son Holly Beilin in an email to TechCrunch. Flock said it was con­fi­dent that the com­pany could “clear up the cur­rent mis­con­cep­tions” that led to the con­trac­t’s end. Flock would not say which spe­cific mis­con­cep­tions it was re­fer­ring to.

Flock has a net­work of at least 80,000 cam­eras around the U.S. that scan li­cense plates and al­low po­lice and fed­eral agen­cies to track ve­hi­cles.

The com­pany has faced heavy back­lash from lo­cal com­mu­ni­ties that have ap­proved and then re­neged on their deals with Flock over con­cerns with pri­vacy and sur­veil­lance. Some lo­cals have taken mat­ters into their own hands by dis­man­tling Flock cam­eras and cov­er­ing them with trash bags, even as some com­mu­ni­ties found that Flock re­in­stalled cam­eras with­out per­mis­sion from lo­cal au­thor­i­ties.

Researchers have iden­ti­fied an uptick in doc­u­mented cases of mo­torists be­ing pulled over, de­tained, and held at gun­point by po­lice, or jailed, due to false pos­i­tives and er­rors with li­cense plate read­ers. Last week, a jour­nal­ist with car re­views and news web­site The Drive de­tailed how he was tracked for days and later boxed-in by po­lice af­ter a Flock cam­era mis­tak­enly flagged the li­cense plate of the on-loan re­view unit he was dri­ving as stolen.

Flock has also faced scrutiny fol­low­ing sev­eral se­cu­rity lapses that have ex­posed cam­eras and data, which in one case al­lowed in­de­pen­dent news out­let 404 Media to watch them­selves live on pub­licly ex­posed Flock cam­eras. Lawmakers have also urged fed­eral con­sumer au­thor­i­ties to in­ves­ti­gate Flock for fail­ing to im­ple­ment mea­sures that would pre­vent hack­ers and spies from gain­ing ac­cess to its se­cu­rity cam­eras, warn­ing that many of the po­lice user lo­gins are not pro­tected with multi-fac­tor au­then­ti­ca­tion.

404 Media also re­ported that the U.S. Drug Enforcement Administration used a lo­cal po­lice of­fi­cer’s pass­word with­out their knowl­edge to search for a sus­pect ac­cused of an im­mi­gra­tion vi­o­la­tion.

Do you know about se­cu­rity or pri­vacy is­sues with Flock Safety, or is­sues with Flock cam­eras in your com­mu­nity? We would love to hear from you. From a non-work de­vice, you can se­curely con­tact Zack Whittaker on the Signal mes­sag­ing app with the user­name za­ck­whit­taker.1337.

When you pur­chase through links in our ar­ti­cles, we may earn a small com­mis­sion. This does­n’t af­fect our ed­i­to­r­ial in­de­pen­dence.

Zack Whittaker is the se­cu­rity ed­i­tor at TechCrunch. He also au­thors the weekly cy­ber­se­cu­rity newslet­ter, this week in se­cu­rity.

He can be reached via en­crypted mes­sage at za­ck­whit­taker.1337 on Signal. You can also con­tact him by email, or to ver­ify out­reach, at zack.whit­taker@techcrunch.com.

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The re­sult, up front

Apple’s new SpeechAnalyzer is the most ac­cu­rate on-de­vice speech en­gine we tested. It beat every Whisper model we ship, in­clud­ing Whisper Small, on both the clean and the noisy half of LibriSpeech, while run­ning roughly three times faster than Small. And the API it re­places, SFSpeechRecognizer, came last on clean speech: be­hind even Whisper Tiny, a 40MB model.

Lower is bet­ter: WER is word er­ror rate, the per­cent­age of words an en­gine sub­sti­tutes, drops, or in­vents. LibriSpeech test-clean is 2,620 ut­ter­ances of clean read speech; test-other is 2,939 harder, nois­ier ut­ter­ances. Every en­gine ran fully on-de­vice on an Apple M2 Pro (32GB, ma­cOS 26.5.1).

Apple SpeechAnalyzer2.12%

Whisper Small3.74%

Whisper Base5.42%

Whisper Tiny7.88%

SFSpeechRecognizer (legacy)9.02%

Why we ran this

With iOS 26 and ma­cOS 26, Apple re­placed SFSpeechRecognizer with a new API, SpeechAnalyzer and SpeechTranscriber. It pub­lished no ac­cu­racy fig­ures for ei­ther one. So every de­vel­oper de­cid­ing whether to mi­grate, and every­one com­par­ing Apple’s built-in recog­ni­tion against Whisper, has been guess­ing.

We ship both Apple en­gines and three Whisper mod­els side by side in Inscribe, a pri­vate on-de­vice AI work­space, which puts us in an un­usual po­si­tion: we can run all five through iden­ti­cal pro­duc­tion code paths on the same ma­chine and the same au­dio. So we did.

Should you mi­grate off SFSpeechRecognizer?

Yes. This is the clear­est re­sult in the data. The new API cuts word er­ror rate by 3.5 to 4x on the same au­dio: from 9.02% to 2.12% on clean speech, and from 16.25% to 4.56% on noisy speech. There is no ac­cu­racy trade-off to weigh; the new API wins every­where we mea­sured, and it pro­duces punc­tu­ated, cased text where the legacy en­gine’s out­put is rougher.

Put dif­fer­ently: an hour-long meet­ing tran­scribed with the legacy API con­tains roughly four times as many wrong words as the same meet­ing through SpeechAnalyzer. If your app still uses SFSpeechRecognizer for any­thing longer than a voice com­mand, the mi­gra­tion is worth it on ac­cu­racy alone.

SpeechAnalyzer vs Whisper

The more sur­pris­ing re­sult: Apple’s new en­gine also beat Whisper Small, the largest model we ship, by a com­fort­able mar­gin on both splits, at roughly a third of Whisper Small’s com­pute time per sec­ond of au­dio. For English, on Apple hard­ware, the built-in en­gine is now the strongest on-de­vice op­tion we can mea­sure.

Whisper keeps two real ad­van­tages. It cov­ers far more lan­guages (SpeechTranscriber sup­ports around 30 lo­cales), and it runs any­where, not just on Apple plat­forms with OS 26. But for English tran­scrip­tion on a cur­rent iPhone or Mac, the days of Whisper be­ing the au­to­matic ac­cu­racy pick are over.

We changed our own prod­uct on this re­sult: Inscribe’s Auto en­gine now prefers SpeechAnalyzer for the lan­guages it sup­ports, and Whisper for every­thing else. Shipping a bench­mark and ig­nor­ing it in your own de­faults would be a strange kind of hon­esty.

Speed

All five en­gines ran com­fort­ably faster than real time: be­tween roughly 12x and 40x on the M2 Pro, mean­ing an hour of au­dio tran­scribes in about 1.5 to 5 min­utes on-de­vice. SpeechAnalyzer was about 3x faster than Whisper Small per sec­ond of au­dio while beat­ing it on ac­cu­racy. We are de­lib­er­ately not print­ing a pre­cise per-en­gine tim­ing table yet: the ac­cu­racy runs shared the ma­chine with a de­vel­op­ment work­load, which does not af­fect WER but does add noise to tim­ing. We will up­date this page with tim­ings from a ded­i­cated idle run.

Methodology, and why you can check it

A bench­mark from a com­pany that sells one of the en­gines should be treated with sus­pi­cion. Ours has two prop­er­ties de­signed for that sus­pi­cion.

The Whisper col­umn is re­pro­ducible against OpenAI’s own num­bers

We used LibriSpeech pre­cisely be­cause OpenAI pub­lished Whisper’s WER on it. If our har­ness mea­sured Whisper cor­rectly, our num­bers should land on theirs. They do, on all six mea­sure­ments:

The small, con­sis­tent pos­i­tive off­set (a slightly stricter text nor­mal­izer plus CoreML quan­ti­za­tion) is what hon­est re­pro­duc­tion looks like; ran­dom er­ror would scat­ter in both di­rec­tions. Since the same cor­pus, nor­mal­izer, and scorer pro­duced the Apple columns, the num­bers no­body else can check in­herit the val­i­da­tion from the num­bers any­one can.

The raw tran­scripts are pub­lic

Every per-ut­ter­ance hy­poth­e­sis for both Apple en­gines is down­load­able be­low, next to the ref­er­ence text and per-ut­ter­ance WER. Disagree with our nor­mal­iza­tion? Rescore it your­self.

sum­mary.json - all ten mea­sure­ments, ma­chine-read­able (3KB)

raw-tran­scripts-ap­ple.json.gz - SpeechAnalyzer, all 5,559 ut­ter­ances (620KB)

raw-tran­scripts-legacy.json.gz - SFSpeechRecognizer, all 5,559 ut­ter­ances (620KB)

Details that de­cide whether a WER num­ber means any­thing

Same pro­duc­tion code paths. Each en­gine ran through the ex­act code Inscribe users get, not a lab har­ness with dif­fer­ent buffer­ing or set­tings.

Text nor­mal­iza­tion. LibriSpeech ref­er­ences are up­per­case, un­punc­tu­ated, with num­bers spelled out; mod­ern en­gines emit punc­tu­a­tion and dig­its. Both sides pass through the same nor­mal­izer (casing, punc­tu­a­tion, dig­its-to-words, con­trac­tions), mir­ror­ing OpenAI’s English nor­mal­izer. Score raw text and you pun­ish en­gines for for­mat­ting nicely rather than for mis­hear­ing.

Corpus WER, not av­er­aged WER. Total er­rors di­vided by to­tal ref­er­ence words, so short ut­ter­ances are not over-weighted.

Fully on-de­vice, ver­i­fied. SFSpeechRecognizer sends au­dio to Apple’s servers by de­fault. We forced on-de­vice recog­ni­tion and made the har­ness refuse to run rather than silently fall back to the cloud, both be­cause a cloud re­sult would in­val­i­date the com­par­i­son and be­cause we were not go­ing to up­load 5,559 ut­ter­ances from a pri­vacy prod­uct.

Failures counted, not hid­den. An en­gine re­turn­ing noth­ing scores 100% WER for that ut­ter­ance. It hap­pened once in 27,795 tran­scrip­tions (legacy, test-other).

What build­ing this taught us about our own app

The bench­mark found a ship­ping bug in Inscribe. Our Apple-engine file im­port fed au­dio to SpeechAnalyzer and closed the in­put stream, but never called fi­nal­ize­AndFin­ishThrough­End­OfIn­put(). Without that call the an­a­lyzer never de­liv­ers its fi­nal re­sults, and the im­port hangs for­ever. It had gone un­no­ticed be­cause our Auto set­ting pre­ferred Whisper. The fix shipped the same day, and it is part of why we pub­lish the har­ness de­tails: mea­sur­ing your own prod­uct care­fully has a way of find­ing the things you were not look­ing for.

Limitations

English only. LibriSpeech is English read speech. These num­bers say noth­ing about the 100+ lan­guages Whisper sup­ports that SpeechTranscriber does not.

Read au­dio­book speech, not meet­ings. LibriSpeech is the stan­dard, com­pa­ra­ble cor­pus, which is why we started with it. Accented, far-field, and multi-speaker meet­ing au­dio is the ob­vi­ous fol­low-up.

One ma­chine. M2 Pro, ma­cOS 26.5.1. Accuracy should trans­fer across Apple Silicon; speed will vary by chip.

Whisper via WhisperKit CoreML. Quantized on-de­vice con­ver­sions, the same builds Inscribe ships. Reference GPU im­ple­men­ta­tions may dif­fer slightly, which the val­i­da­tion table quan­ti­fies.

What this means if you just want good tran­scrip­tion

If you are on a cur­rent iPhone or Mac, the best on-de­vice tran­scrip­tion en­gine for English is al­ready in the op­er­at­ing sys­tem, and the pri­vate op­tion is no longer the com­pro­mise op­tion. Inscribe uses ex­actly the en­gines mea­sured here: SpeechAnalyzer where it sup­ports your lan­guage, Whisper where it does not, all fully on-de­vice, noth­ing up­loaded. The bench­mark is not sep­a­rate from the prod­uct; it is how we de­cide what the prod­uct does.

Related read­ing

Apple Intelligence tran­scrip­tion

Best of­fline tran­scrip­tion apps

Private tran­scrip­tion apps

ABOUT ME

I’m an in­ter­galac­tic space war­rior and leader of the Recyclons from planet Sigma IX. I came to Earth in 2017 and stood against Prime Minister Theresa May (as ‘Lord Buckethead’), go­ing went vi­ral (in a non-Covid way). Then in 2018, af­ter an un­for­tu­nate bat­tle on the planet Copyright, I rews­pawned in my true form as Count Binface to take on Boris Johnson in the 2019 elec­tion, where I scored a sur­pris­ing 69. In 2021, I re­ceived 92,896 votes (including 24,775 first choice votes) from the hu­mans of London, who made me their 9th choice to be Mayor of the Earth cap­i­tal, out of 20 can­di­dates. This is a new record for an alien stand­ing for pub­lic of­fice on planet Earth. (I also de­feated Piers Corbyn and UKIP in the process.) In 2023, I came 8th in the Uxbridge (and South Ruislip) by-elec­tion, win­ning 190 votes with a 275% in­crease from 2019. I de­feated Piers Corbyn and UKIP again in the process. I cam­paign for jus­tice, lasers, Lovejoy, af­ford­able crois­sants and the re­turn of Ceefax. In 2024 I fought to be London Mayor again, win­ning 24,260 votes and de­feat­ing Britain First, and then took on Prime Minister Rishi Sunak at the General Election in Richmond & Northallerton, achiev­ing a (moral) vic­tory with 308 votes.

These are fac­tual re­sults. My best fic­tional re­sult is in the hit TV show Industry (Season Four, Episode Two), where I take on Kit Harington in Wakefield (not a sports hall in Cardiff) and win 309 votes!

My hob­bies in­clude in­vad­ing star sys­tems, dom­i­nat­ing in­fe­rior species, and the Lovejoy box set.

Ride the Yamanote line through a voxel Tokyo synced to Japan’s real clock, weather, and sea­sons. A lofi bed plays while N5 sen­tences are read aloud and drift by as sub­ti­tles — an am­bi­ent Japanese study room you just press play into.

“After los­ing their jobs at NOAA, Rebecca Lindsey, her sis­ter and an­other col­league teamed up to re­build a piv­otal re­source the Trump ad­min­is­tra­tion took of­fline.”

Link: Trump dis­man­tled a fed­eral cli­mate web­site. These women re­built it., by Jenae Barnes at The 19th

This should­n’t have been nec­es­sary, but is still won­der­ful to see. Climate.gov had been the go-to re­source for cli­mate data, but it went of­fline when the Trump Administration rad­i­cally cut NOAA’s fund­ing. At that point:

“[Rebecca] Lindsey joined forces with for­mer NOAA em­ploy­ees Anna Eshelman, and Mary Lindsey, her older sis­ter, to be­come the core team be­hind the de­ac­ti­vated site’s suc­ces­sor, Climate.us, pre­serv­ing over 15 years of key cli­mate data and re­sources. The trove fea­tures key maps, ed­u­ca­tional ma­te­ri­als and cli­mate in­di­ca­tor re­ports, in­clud­ing the now-deleted Fifth National Climate Assessment, the gov­ern­men­t’s most com­pre­hen­sive analy­sis of cli­mate change that was at risk of be­ing lost to the pub­lic.”

This is pos­si­ble be­cause US gov­ern­ment data is pub­lic do­main by law. Had it not been avail­able un­der a per­mis­sive li­cense, the ad­min­is­tra­tion’s act of van­dal­ism would have meant the data was gone for good. But be­cause it was, the datasets can find a new home.

It’s a joy to use. Check out the cli­mate dash­board, which tracks num­bers like the to­tal area of the Arctic Ocean that was at least 15% ice-cov­ered each September. It also hosts a set of re­sources for teach­ing cli­mate and en­ergy. The dataset gallery in­cludes cru­cial in­for­ma­tion like the NOAA’s archive of oral his­to­ries from peo­ple whose lives were af­fected by cli­mate change.

But it’s also pre­car­i­ous. The whole thing re­lies on do­na­tions to keep it afloat, which is re­ally what tax dol­lars are for. Still, for the mo­ment it’s won­der­ful to see peo­ple pick up the slack when gov­ern­ment is no longer do­ing its job. In the ab­sence of gov­ern­ment sup­port, archives like this are works of jour­nal­ism in them­selves: ways to help us make stronger de­ci­sions. They de­serve stronger sup­port, and ul­ti­mately, we all de­serve the restora­tion of such im­por­tant gov­ern­ment in­fra­struc­ture.