On January 14, 2006, John Resig in­tro­duced a JavaScript li­brary called jQuery at BarCamp in New York City. Now, 20 years later, the jQuery team is happy to an­nounce the fi­nal re­lease of jQuery 4.0.0. After a long de­vel­op­ment cy­cle and sev­eral pre-re­leases, jQuery 4.0.0 brings many im­prove­ments and mod­ern­iza­tions. It is the first ma­jor ver­sion re­lease in al­most 10 years and in­cludes some break­ing changes, so be sure to read through the de­tails be­low be­fore up­grad­ing. Still, we ex­pect that most users will be able to up­grade with min­i­mal changes to their code.

Many of the break­ing changes are ones the team has wanted to make for years, but could­n’t in a patch or mi­nor re­lease. We’ve trimmed legacy code, re­moved some pre­vi­ously-dep­re­cated APIs, re­moved some in­ter­nal-only pa­ra­me­ters to pub­lic func­tions that were never doc­u­mented, and dropped sup­port for some “magic” be­hav­iors that were overly com­pli­cated.

We have an up­grade guide and jQuery Migrate plu­gin re­lease ready to as­sist with the tran­si­tion. Please up­grade and let us know if you en­counter any is­sues.

As usual, the re­lease is avail­able on our CDN and the npm pack­age man­ager. Other third party CDNs will prob­a­bly have it avail­able soon as well, but re­mem­ber that we don’t con­trol their re­lease sched­ules and they will need some time. Here are the high­lights for jQuery 4.0.0.

jQuery 4.0 drops sup­port for IE 10 and older. Some may be ask­ing why we did­n’t re­move sup­port for IE 11. We plan to re­move sup­port in stages, and the next step will be re­leased in jQuery 5.0. For now, we’ll start by re­mov­ing code specif­i­cally sup­port­ing IE ver­sions older than 11.

We also dropped sup­port for other very old browsers, in­clud­ing Edge Legacy, iOS ver­sions ear­lier than the last 3, Firefox ver­sions ear­lier than the last 2 (aside from Firefox ESR), and Android Browser. No changes should be re­quired on your end. If you need to sup­port any of these browsers, stick with jQuery 3.x.

jQuery 4.0 adds sup­port for Trusted Types, en­sur­ing that HTML wrapped in TrustedHTML can be used as in­put to jQuery ma­nip­u­la­tion meth­ods in a way that does­n’t vi­o­late the re­quire-trusted-types-for Content Security Policy di­rec­tive.

Along with this, while some AJAX re­quests were al­ready us­ing tags to main­tain at­trib­utes such as cross­do­main, we have since switched most asyn­chro­nous script re­quests to use <script> tags to avoid any CSP er­rors caused by us­ing in­line scripts. There are still a few cases where XHR is used for asyn­chro­nous script re­quests, such as when the”head­ers” op­tion is passed (use scrip­tAt­trs in­stead!), but we now use a tag when­ever pos­si­ble.

It was a spe­cial day when the jQuery source on the main branch was mi­grated from AMD to ES mod­ules. The jQuery source has al­ways been pub­lished with jQuery re­leases on npm and GitHub, but could not be im­ported di­rectly as mod­ules with­out RequireJS, which was jQuery’s build tool of choice. We have since switched to Rollup for pack­ag­ing jQuery and we do run all tests on the ES mod­ules sep­a­rately. This makes jQuery com­pat­i­ble with mod­ern build tools, de­vel­op­ment work­flows, and browsers through the use of .

• The 2025 US tar­iffs are an own goal: American im­porters and con­sumers bear nearly the en­tire cost. Foreign ex­porters ab­sorb only about 4% of the tar­iff bur­den—the re­main­ing 96% is passed through to US buy­ers.

• Using ship­ment-level data cov­er­ing over 25 mil­lion trans­ac­tions val­ued at nearly $4 tril­lion, we find near-com­plete pass-through of tar­iffs to US im­port prices.

• US cus­toms rev­enue surged by ap­prox­i­mately $200 bil­lion in 2025—a tax paid al­most en­tirely by Americans.

• Event stud­ies around dis­crete tar­iff shocks on Brazil (50%) and India (25–50%) con­firm: ex­port prices did not de­cline. Trade vol­umes col­lapsed in­stead.

• Indian ex­port cus­toms data val­i­dates our find­ings: when fac­ing US tar­iffs, Indian ex­porters main­tained their prices and re­duced ship­ments. They did not “eat” the tar­iff.

The other day I was brows­ing my one-and-only so­cial net­work — which is not a so­cial net­work, but I’m tired of ar­gu­ing with peo­ple on­line about it — HackerNews. It’s like this dark cor­ner of the in­ter­net, where anony­mous tech-en­thu­si­asts, sci­en­tists, en­tre­pre­neurs, and in­ter­net-trolls, like to lurk. I like HackerNews. It helps me stay up-to-date about re­cent tech news (like Cloudflare ac­quir­ing Astro which makes me happy for the Astro team, but also sad and wor­ried since I re­ally like Astro, and big-tech has a ten­dency to ruin things); it mostly avoids pol­i­tics; and it’s not a so­cial net­work.

And, in the fash­ion of HackerNews, I stum­bled upon some­one shar­ing their open-source pro­ject. It’s great to see peo­ple work on their pro­jects and de­cide to show them to the world. I think peo­ple un­der­es­ti­mate the fear of ac­tu­ally ship­ping stuff, which in­volves shar­ing it with the world.

Upon glanc­ing at the com­ment sec­tion, I started to see other anony­mous par­tic­i­pants ques­tion­ing the va­lid­ity of said open-source pro­ject in terms of how much of it was AI-generated. I grabbed my pop­corn, and started to fol­low this thread. More ac­cu­sa­tions started to ap­pear: the com­mit time­line does not make sense; the code has AI-generated com­ments; etc. And at the same time, the au­thor tried to re­ply to every com­ment claim­ing that they wrote this 100% with­out us­ing AI.

I don’t mind peo­ple us­ing AI to write code, even though I tried to re­sist it my­self, un­til even­tu­ally suc­cumb­ing to it. But I think it’s fair to dis­close the use of AI, es­pe­cially in open-source soft­ware. People on the in­ter­net are, mostly, anony­mous, and it’s not al­ways pos­si­ble to ver­ify the claims or ex­per­tise of par­tic­u­lar in­di­vid­u­als. But as the amount of code is grow­ing, con­sid­er­ing that every­one is us­ing AI to gen­er­ate what­ever-app they want, it’s im­pos­si­ble to ver­ify every piece of code we are go­ing to use. So it’s fair to know, I think, if some pro­ject is AI gen­er­ated and to what ex­tent. In the end, LLMs are just prob­a­bilis­tic next-to­ken gen­er­a­tors. And while they are get­ting ex­tremely good at most sim­ple tasks, they have the po­ten­tial to wreak havoc with harder prob­lems or edge-cases (especially if there are no ex­pe­ri­enced en­gi­neers, with do­main knowl­edge, to re­view the gen­er­ated code).

As I was fol­low­ing this thread, I started to see a pat­tern: the com­ments of the au­thor looked AI gen­er­ated too:

The use of em-dashes, which on most key­board re­quire a spe­cial key-com­bi­na­tion that most peo­ple don’t know, and while in mark­down two dashes will ren­der as em-dash, this is not true of HackerNews (hence, you of­ten see — in HackerNews com­ments, where the au­thor is prob­a­bly used to Markdown ren­derer turn­ing it into em-dash)

The no­to­ri­ous “you are ab­solutely right”, which no liv­ing hu­man ever used be­fore, at least not that I know of

The other no­to­ri­ous “let me know if you want to [do that thing] or [explore this other thing]” at the end of the sen­tence

I was sit­ting there, re­fresh­ing the page, see­ing the au­thor be­ing con­fronted with use of AI in both their code and their com­ments, while the au­thor claim­ing to have not used AI at all. Honestly, I was think­ing I was go­ing in­sane. Am I wrong to sus­pect them? What if peo­ple DO USE em-dashes in real life? What if English is not their na­tive lan­guage and in their na­tive lan­guage it’s fine to use phrases like “you are ab­solutely right”? Is this even a real per­son? Are the peo­ple who are com­ment­ing real?

And then it hit me. We have reached the Dead Internet. The Dead Internet Theory claims that since around 2016 (a whoop­ing 10 years al­ready), the in­ter­net is mainly dead, i.e. most in­ter­ac­tions are be­tween bots, and most con­tent is ma­chine gen­er­ated to ei­ther sell you stuff, or game the SEO game (in or­der to sell you stuff).

I’m proud to say that I spent a good por­tion of my teenage years on the in­ter­net, chat­ting and learn­ing from real peo­ple who knew more than me. Back in the early 2000s, there were barely bots on the in­ter­net. The av­er­age non-tech hu­man did­n’t know any­thing about ph­pBB fo­rums, and the weird peo­ple with pseu­do­nyms who hanged-out in there. I spent count­less hours in­side IRC chan­nels, and on ph­pBB fo­rums, learn­ing things like net­work pro­gram­ming, OS-development, game-de­vel­op­ment, and of course web-de­vel­op­ment (which be­came my pro­fes­sion for al­most two decades now). I’m ba­si­cally a grad­u­ate of the Internet University. Back then, no­body had doubts that they were talk­ing to a hu­man-be­ing. Sure, you could think that you spoke to a hot girl, who in re­al­ity was a fat guy, but hey, at least they were real!

But to­day, I no longer know what is real. I saw a pic­ture on LinkedIn, from a real tech com­pany, post­ing about their “office vibes” and their happy em­ploy­ees. And then I went to the com­ment sec­tion, and sure enough this pic­ture is AI gen­er­ated (mangled text that does not make sense, weird hand ar­ti­facts). It was posted by an em­ployee of the com­pany, it showed other em­ploy­ees of said com­pany, and it was al­tered with AI to show­case a dif­fer­ent re­al­ity. Hell, maybe the peo­ple on the pic­ture do not even ex­ist!

And these are mild ex­am­ples. I don’t use so­cial net­works (and no, HackerNews is not a so­cial net­work), but I hear hor­ror sto­ries about AI gen­er­ated con­tent on Facebook, Xitter, TikTok, rang­ing from pho­tos of gi­ants that built the pyra­mids in Egypt, all the way to short videos of pretty girls say­ing that the EU is bad for Poland.

I hon­estly got sad that day. Hopeless, if I could say. AI is eas­ily avail­able to the masses, which al­low them to gen­er­ate shit­load of AI-slop. People no longer need to write com­ments or code, they can just feed this to AI agents who will gen­er­ate the next “you are ab­solutely right” mas­ter­piece.

I like tech­nol­ogy. I like soft­ware en­gi­neer­ing, and the con­cept of the in­ter­net where peo­ple could share knowl­edge and cre­ate com­mu­ni­ties. Were there ma­li­cious ac­tors back then on the in­ter­net? For sure. But what I am see­ing to­day, makes me ques­tion whether the fu­ture we are headed to is a fu­ture where tech­nol­ogy is use­ful any­more. Or, rather, it’s a fu­ture where bots talk with bots, and hu­man knowl­edge just gets re­cy­cled and repack­aged into “10 step to fix your [daily prob­lem] you are hav­ing” for the sake of sell­ing you more stuff.

Unless oth­er­wise noted, all con­tent is gen­er­ated by a hu­man.

bitchat is a de­cen­tral­ized peer-to-peer mes­sag­ing ap­pli­ca­tion that op­er­ates over blue­tooth mesh net­works. no in­ter­net re­quired, no servers, no phone num­bers.

tra­di­tional mes­sag­ing apps de­pend on cen­tral­ized in­fra­struc­ture that can be mon­i­tored, cen­sored, or dis­abled. bitchat cre­ates ad-hoc com­mu­ni­ca­tion net­works us­ing only the de­vices pre­sent in phys­i­cal prox­im­ity. each de­vice acts as both client and server, au­to­mat­i­cally dis­cov­er­ing peers and re­lay­ing mes­sages across mul­ti­ple hops to ex­tend the net­work’s reach.

this ap­proach pro­vides cen­sor­ship re­sis­tance, sur­veil­lance re­sis­tance, and in­fra­struc­ture in­de­pen­dence. the net­work re­mains func­tional dur­ing in­ter­net out­ages, nat­ural dis­as­ters, protests, or in re­gions with lim­ited con­nec­tiv­ity.

ios/​ma­cos ver­sion:

app­store: bitchat mesh

source code: https://​github.com/​per­mis­sion­lesstech/​bitchat

sup­ports ios 16.0+ and ma­cos 13.0+. build us­ing xcode with xcode­gen or swift pack­age man­ager.

the soft­ware is re­leased into the pub­lic do­main.

Do you re­quire a (replacement) smart­phone for your work at Radboud University? If so, there is a strong pos­si­bil­ity that you will re­ceive a Fairphone from 1 February 2026 on­wards. Radboud University has de­cided to choose Fairphone as its stan­dard com­pany smart­phone model for rea­sons of sus­tain­abil­ity, cost ef­fi­ciency and man­age­ment sup­port.

Do you re­quire a (replacement) smart­phone for your work at Radboud University? If so, there is a strong pos­si­bil­ity that you will re­ceive a Fairphone from 1 February 2026 on­wards. Radboud University has de­cided to choose Fairphone as its stan­dard com­pany smart­phone model for rea­sons of sus­tain­abil­ity, cost ef­fi­ciency and man­age­ment sup­port.

The Fairphone is a sus­tain­able smart­phone with eas­ily re­place­able parts such as the bat­tery and screen. This makes the de­vice last longer. Fair and re­cy­cled ma­te­ri­als, such as plas­tic and alu­minium, are used as much as pos­si­ble in the pro­duc­tion of this smart­phone. Fairphone also pays at­ten­tion to good and safe work­ing con­di­tions in its fac­to­ries.

Fairphones are is­sued to em­ploy­ees by the Information & Library Services (ILS) di­vi­sion. In ad­di­tion to new Fairphones, the uni­ver­sity can also reis­sue used Samsung de­vices where pos­si­ble. These are Samsung de­vices that have al­ready been re­turned and still meet the tech­ni­cal and age re­quire­ments. As long as these de­vices are still avail­able, not every em­ployee will re­ceive a Fairphone im­me­di­ately. Employees who have an iPhone from Radboud University can con­tinue to use it as long as the de­vice is still func­tion­ing. However, re­turned iPhones will no longer be reis­sued.

Employees who pre­fer to use their pri­vate phone for work can re­quest an RU SIM card for this pur­pose. The costs for us­ing your own de­vice will not be re­im­bursed. Naturally, smart­phone mod­els that have al­ready been is­sued will con­tinue to be sup­ported by ILS col­leagues, as will pri­vately pur­chased smart­phone mod­els used for work.

Due to its longer lifes­pan, the to­tal cost of a Fairphone is lower than that of com­pa­ra­ble de­vices. In ad­di­tion, Radboud University only needs to pur­chase, man­age and sup­port one stan­dard model. This re­sults in smaller stock, eas­ier man­age­ment and faster sup­port. Manuals and in­struc­tions also only need to be main­tained for one de­vice.

Furthermore, less in­vest­ment is re­quired in knowl­edge of dif­fer­ent mod­els/​brands. This also helps to speed up in­ci­dent han­dling and, where nec­es­sary, smart­phone re­place­ment.

Fairphone of­fers a five-year war­ranty and long-term soft­ware sup­port for up to eight years. This means that de­vices need to be re­placed less quickly. This fits in with Radboud University’s cir­cu­lar­ity strat­egy, which fo­cuses on the longest pos­si­ble use and reuse of ICT hard­ware.

Mastering the Schengen Shuffle: How to Use Precise Date Counting for 90/180-Day Visa Compliance

Navigate the com­plex 90/180-day visa rule with pre­ci­sion. Learn how to use a days be­tween dates cal­cu­la­tor to avoid en­try bans, fines, and bor­der is­sues.

The Time-Debt Audit: Is Your Loan Stealing Your Future Autonomy?

Stop view­ing loans as monthly pay­ments and start see­ing them as ‘life hours.’ Use our Time-Debt Audit to cal­cu­late your Freedom Ratio be­fore you sign.

Beyond the ‘Bad Request’: A Guide to URL Encoding for No-Code Automation

Stop ‘Bad Request’ er­rors in Zapier, Make, and Airtable. Master URL en­cod­ing to pro­tect your au­toma­tion work­flows from data cor­rup­tion and bro­ken API calls.

Digital Quarantine: How to Use Subnetting to Secure Your Home Office and IoT Devices

Learn how to use a sub­net cal­cu­la­tor to build a ‘Digital Quarantine’ for your home. Isolate vul­ner­a­ble IoT de­vices from your work data and per­sonal files.

The ROI of Your Ride: Using a Car Loan Calculator to Turn Your Vehicle into a Business Asset

Don’t let car pay­ments kill your gig econ­omy prof­its. Learn to use a car loan cal­cu­la­tor to de­ter­mine the ROI of your ve­hi­cle for Uber, DoorDash, and more.

Beyond the Nest Egg: Finding Your Financial ‘Crossover Point’ with Compound Interest

Discover the Crossover Point: the mile­stone where in­ter­est earn­ings ex­ceed your con­tri­bu­tions. A guide to com­pound in­ter­est for late-start in­vestors.

The ‘Wait Tax’: Quantifying the Exact Cost of Delaying Your Investments

Stop wait­ing for the ‘perfect time’ to in­vest. Learn how to cal­cu­late your ‘Wait Tax’—the mas­sive fi­nan­cial penalty of de­lay­ing your port­fo­lio by just 12–24 months.

The Minimum Viable Rest Strategy: A Survival Guide to Sleep Cycles for High-Stakes Performance

Master the Minimum Viable Rest (MVR) strat­egy us­ing the 90-minute sleep cy­cle rule. Learn how to cal­cu­late sur­vival win­dows to main­tain clar­ity dur­ing crunch pe­ri­ods.

Beat the Monday Blues: The ‘Social Jetlag’ Recovery Plan Using the 90-Minute Rule

Stop the Sunday night panic. Use the 90-minute sleep cy­cle rule and our Sleep Calculator to re­cover from so­cial jet­lag and wake up re­freshed on Monday morn­ing.

Calculate how your in­vest­ments grow over time with com­pound in­ter­est.

Stop wait­ing for the ‘perfect time’ to in­vest. Learn how to cal­cu­late your ‘Wait Tax’—the mas­sive fi­nan­cial penalty of de­lay­ing your port­fo­lio by just 12–24 months.

Discover the Crossover Point: the mile­stone where in­ter­est earn­ings ex­ceed your con­tri­bu­tions. A guide to com­pound in­ter­est for late-start in­vestors.

Calculate how your in­vest­ments grow over time with com­pound in­ter­est.

Stop wait­ing for the ‘perfect time’ to in­vest. Learn how to cal­cu­late your ‘Wait Tax’—the mas­sive fi­nan­cial penalty of de­lay­ing your port­fo­lio by just 12–24 months.

Discover the Crossover Point: the mile­stone where in­ter­est earn­ings ex­ceed your con­tri­bu­tions. A guide to com­pound in­ter­est for late-start in­vestors.

Compound in­ter­est is in­ter­est cal­cu­lated on both the ini­tial prin­ci­pal and the ac­cu­mu­lated in­ter­est from pre­vi­ous pe­ri­ods. Unlike sim­ple in­ter­est, which only earns in­ter­est on the orig­i­nal amount, com­pound in­ter­est al­lows your money to grow ex­po­nen­tially over time.

Albert Einstein re­port­edly called com­pound in­ter­est “the eighth won­der of the world,” say­ing: “He who un­der­stands it, earns it; he who does­n’t, pays it.”

The ba­sic for­mula for com­pound in­ter­est is:

For con­tin­u­ous com­pound­ing, the for­mula be­comes:

A quick men­tal math trick to es­ti­mate how long it takes to dou­ble your money:

The more fre­quently in­ter­est com­pounds, the more you earn. Think of it as: how of­ten the bank cal­cu­lates and adds in­ter­est to your bal­ance.

At a 10% an­nual rate on $10,000 over 10 years:

When plan­ning long-term in­vest­ments, it’s cru­cial to un­der­stand the dif­fer­ence be­tween nom­i­nal re­turns (the num­ber you see) and real re­turns (actual pur­chas­ing power).

Nominal Return: The raw per­cent­age your in­vest­ment grows — what your ac­count state­ment shows.

Real Return: Your re­turn af­ter ac­count­ing for in­fla­tion — what your money can ac­tu­ally buy.

Example: You in­vest $10,000 at 10% an­nual re­turn for 20 years.

* Nominal value: $67,275 (what your ac­count shows)

Historical in­fla­tion rates vary by coun­try, but a com­mon as­sump­tion for de­vel­oped economies is 2-3% an­nu­ally. During high-in­fla­tion pe­ri­ods, this can ex­ceed 5-10%.

Start early — Time is your great­est ally. Even small amounts grow sig­nif­i­cantly over decades.

Be con­sis­tent — Regular con­tri­bu­tions am­plify the ef­fect of com­pound­ing.

Seek higher rates — Even a 1% dif­fer­ence com­pounds to sig­nif­i­cant amounts over time.

Beat in­fla­tion — Ensure your real re­turn is pos­i­tive; oth­er­wise, you’re los­ing pur­chas­ing power.

👋 Join our Discord com­mu­nity.

📖 Check out the GLM-4.7 tech­ni­cal blog, tech­ni­cal re­port(GLM-4.5).

📍 Use GLM-4.7-Flash API ser­vices on Z.ai API Platform.

👉 One click to GLM-4.7.

GLM-4.7-Flash is a 30B-A3B MoE model. As the strongest model in the 30B class, GLM-4.7-Flash of­fers a new op­tion for light­weight de­ploy­ment that bal­ances per­for­mance and ef­fi­ciency.

For lo­cal de­ploy­ment, GLM-4.7-Flash sup­ports in­fer­ence frame­works in­clud­ing vLLM and SGLang. Comprehensive de­ploy­ment in­struc­tions are avail­able in the of­fi­cial Github repos­i­tory.

vLLM and SGLang only sup­port GLM-4.7-Flash on their main branches.

* us­ing pip (must use pypi.org as the in­dex url):

pip in­stall -U vllm –pre –index-url https://​pypi.org/​sim­ple –extra-index-url https://​wheels.vllm.ai/​nightly

pip in­stall git+https://​github.com/​hug­ging­face/​trans­form­ers.git

* us­ing pip in­stall sglang from source, then up­date trans­form­ers to the lat­est main branch.

us­ing with trans­form­ers as

pip in­stall git+https://​github.com/​hug­ging­face/​trans­form­ers.git

im­port torch

from trans­form­ers im­port AutoModelForCausalLM, AutoTokenizer

MODEL_PATH = “zai-org/GLM-4.7-Flash”

mes­sages = [{“role”: “user”, “content”: “hello”}]

to­k­enizer = AutoTokenizer.from_pretrained(MODEL_PATH)

in­puts = to­k­enizer.ap­ply_chat_tem­plate(

mes­sages,

to­k­enize=True,

ad­d_­gen­er­a­tion_prompt=True,

re­turn_­dict=True,

re­turn_ten­sors=“pt”,

model = AutoModelForCausalLM.from_pretrained(

pre­trained_­mod­el_­name_or_­path=MOD­EL_­PATH,

torch_d­type=torch.bfloat16,

de­vice_map=“auto”,

in­puts = in­puts.to(model.de­vice)

gen­er­at­ed_ids = model.gen­er­ate(**in­puts, max_new_­to­kens=128, do_sam­ple=False)

out­put_­text = to­k­enizer.de­code(gen­er­at­ed_ids[0][in­puts.in­put_ids.shape[1]:])

print(out­put_­text)

vllm serve zai-org/​GLM-4.7-Flash \

–tensor-parallel-size 4 \

–speculative-config.method mtp \

–speculative-config.num_speculative_tokens 1 \

–tool-call-parser glm47 \

–reasoning-parser glm45 \

–enable-auto-tool-choice \

–served-model-name glm-4.7-flash

python3 -m sglang.launch_server \

–model-path zai-org/​GLM-4.7-Flash \

–tp-size 4 \

–tool-call-parser glm47 \

–reasoning-parser glm45 \

–speculative-algorithm EAGLE \

–speculative-num-steps 3 \

–speculative-eagle-topk 1 \

–speculative-num-draft-tokens 4 \

–mem-fraction-static 0.8 \

–served-model-name glm-4.7-flash \

–host 0.0.0.0 \

–port 8000

If you find our work use­ful in your re­search, please con­sider cit­ing the fol­low­ing pa­per:

@misc{5team2025glm45agenticreasoningcoding,

ti­tle={GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models},

au­thor={GLM Team and Aohan Zeng and Xin Lv and Qinkai Zheng and Zhenyu Hou and Bin Chen and Chengxing Xie and Cunxiang Wang and Da Yin and Hao Zeng and Jiajie Zhang and Kedong Wang and Lucen Zhong and Mingdao Liu and Rui Lu and Shulin Cao and Xiaohan Zhang and Xuancheng Huang and Yao Wei and Yean Cheng and Yifan An and Yilin Niu and Yuanhao Wen and Yushi Bai and Zhengxiao Du and Zihan Wang and Zilin Zhu and Bohan Zhang and Bosi Wen and Bowen Wu and Bowen Xu and Can Huang and Casey Zhao and Changpeng Cai and Chao Yu and Chen Li and Chendi Ge and Chenghua Huang and Chenhui Zhang and Chenxi Xu and Chenzheng Zhu and Chuang Li and Congfeng Yin and Daoyan Lin and Dayong Yang and Dazhi Jiang and Ding Ai and Erle Zhu and Fei Wang and Gengzheng Pan and Guo Wang and Hailong Sun and Haitao Li and Haiyang Li and Haiyi Hu and Hanyu Zhang and Hao Peng and Hao Tai and Haoke Zhang and Haoran Wang and Haoyu Yang and He Liu and He Zhao and Hongwei Liu and Hongxi Yan and Huan Liu and Huilong Chen and Ji Li and Jiajing Zhao and Jiamin Ren and Jian Jiao and Jiani Zhao and Jianyang Yan and Jiaqi Wang and Jiayi Gui and Jiayue Zhao and Jie Liu and Jijie Li and Jing Li and Jing Lu and Jingsen Wang and Jingwei Yuan and Jingxuan Li and Jingzhao Du and Jinhua Du and Jinxin Liu and Junkai Zhi and Junli Gao and Ke Wang and Lekang Yang and Liang Xu and Lin Fan and Lindong Wu and Lintao Ding and Lu Wang and Man Zhang and Minghao Li and Minghuan Xu and Mingming Zhao and Mingshu Zhai and Pengfan Du and Qian Dong and Shangde Lei and Shangqing Tu and Shangtong Yang and Shaoyou Lu and Shijie Li and Shuang Li and Shuang-Li and Shuxun Yang and Sibo Yi and Tianshu Yu and Wei Tian and Weihan Wang and Wenbo Yu and Weng Lam Tam and Wenjie Liang and Wentao Liu and Xiao Wang and Xiaohan Jia and Xiaotao Gu and Xiaoying Ling and Xin Wang and Xing Fan and Xingru Pan and Xinyuan Zhang and Xinze Zhang and Xiuqing Fu and Xunkai Zhang and Yabo Xu and Yandong Wu and Yida Lu and Yidong Wang and Yilin Zhou and Yiming Pan and Ying Zhang and Yingli Wang and Yingru Li and Yinpei Su and Yipeng Geng and Yitong Zhu and Yongkun Yang and Yuhang Li and Yuhao Wu and Yujiang Li and Yunan Liu and Yunqing Wang and Yuntao Li and Yuxuan Zhang and Zezhen Liu and Zhen Yang and Zhengda Zhou and Zhongpei Qiao and Zhuoer Feng and Zhuorui Liu and Zichen Zhang and Zihan Wang and Zijun Yao and Zikang Wang and Ziqiang Liu and Ziwei Chai and Zixuan Li and Zuodong Zhao and Wenguang Chen and Jidong Zhai and Bin Xu and Minlie Huang and Hongning Wang and Juanzi Li and Yuxiao Dong and Jie Tang},

year={2025},

eprint={2508.06471},

archivePre­fix={arXiv},

pri­ma­ryClass={cs.CL},

url={https://​arxiv.org/​abs/​2508.06471},

At least 39 peo­ple have died in a train col­li­sion in south­ern Spain and dozens more have been in­jured in the coun­try’s worst rail crash in more than a decade, Spain’s Civil Guard has said. Carriages on a Madrid-bound train de­railed and crossed over to the op­po­site tracks, col­lid­ing with an on­com­ing train in Adamuz on Sunday evening.Four hun­dred pas­sen­gers and staff were on­board both trains, the rail net­works said. Emergency ser­vices treated 122 peo­ple, with 43, in­clud­ing four chil­dren, still in hos­pi­tal. Of those, 12 adults and one child are in in­ten­sive care.Span­ish Transport Minister Óscar Puente said the death toll “is not yet fi­nal”, as of­fi­cials launched an in­ves­ti­ga­tion.

Puente de­scribed the in­ci­dent as “extremely strange”. All the rail­way ex­perts con­sulted by the gov­ern­ment “are ex­tremely baf­fled by the ac­ci­dent”, he told re­porters in Madrid. Rail net­work op­er­a­tor Adif said the col­li­sion hap­pened at 19:45 lo­cal time (18:45 GMT), about an hour af­ter the train left Málaga head­ing north to Madrid, when it de­railed on a straight stretch of track near the city of Córdoba.The force of the crash pushed the car­riages of the sec­ond train into an em­bank­ment, Puente said. He added that most of those killed and in­jured were in the front car­riages of the sec­ond train, which was trav­el­ling south from Madrid to Huelva.The type of train in­volved in the crash was a Freccia 1000, which can reach top speeds of 400 km/​h (250 mph), a spokesper­son for the Italian rail com­pany Ferrovie dello Stato told Reuters news agency.Res­cue teams said the twisted wreck­age of the trains made it dif­fi­cult to re­cover peo­ple trapped in­side the car­riages.Cór­doba fire chief Francisco Carmona told Spanish pub­lic broad­caster RTVE: “We have even had to re­move a dead per­son to be able to reach some­one alive. It is hard, tricky work.”

Salvador Jimenez, a jour­nal­ist with RTVE who was on one of the trains, said the im­pact felt like an “earthquake”. “I was in the first car­riage. There was a mo­ment when it felt like an earth­quake and the train had in­deed de­railed,” Jimenez said. Footage from the scene ap­pears to show some train car­riages had tipped over on their sides. Rescue work­ers can be seen scal­ing the train to pull peo­ple out of the lop­sided train doors and win­dows.A Madrid-bound pas­sen­ger, José, told pub­lic broad­caster Canal Sur: “There were peo­ple and scream­ing, call­ing for doc­tors.”

All rail ser­vices be­tween Madrid and Andalusia were sus­pended fol­low­ing the ac­ci­dent and are ex­pected to re­main closed all day on Monday. Iryo, a pri­vate rail com­pany that op­er­ated the jour­ney from Málaga, said around 300 pas­sen­gers were on board the train that first de­railed, while the other train — op­er­ated by the state-funded firm Renfe — had around 100 pas­sen­gers.The of­fi­cial cause is not yet known. An in­ves­ti­ga­tion is not ex­pected to de­ter­mine what hap­pened for at least a month, ac­cord­ing to the trans­port min­is­ter. Spain’s Prime Minister, Pedro Sánchez, said the coun­try will en­dure a “night of deep pain”. The mayor of Adamuz, Rafael Moreno, was one of the first peo­ple on the scene of the ac­ci­dent, de­scrib­ing it as “a night­mare”.King Felipe VI and Queen Letizia said they were fol­low­ing news of the dis­as­ter “with great con­cern”.“We ex­tend our most heart­felt con­do­lences to the rel­a­tives and loved ones of the dead, as well as our love and wishes for a swift re­cov­ery to the in­jured,” the royal palace said on X.The emer­gency agency in the re­gion of Andalusia urged any crash sur­vivors to con­tact their fam­i­lies or post on so­cial me­dia that they are alive.

Advanced med­ical posts were set up for im­pacted pas­sen­gers to be treated for in­juries and trans­ferred to hos­pi­tal. Adif said it set up spaces for rel­a­tives of the vic­tims at Atocha, Seville, Córdoba, Málaga and Huelva sta­tions. The Spanish Red Cross has de­ployed emer­gency sup­port ser­vices to the scene, while also of­fer­ing coun­selling to fam­i­lies nearby. Miguel Ángel Rodríguez from the Red Cross told RNE ra­dio: “The fam­i­lies are go­ing through a sit­u­a­tion of great anx­i­ety due to the lack of in­for­ma­tion. These are very dis­tress­ing mo­ments.”