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.

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.

About Space Weather

Products and DataForecasts

Report and Forecast of Solar and Geophysical Activity

Weak or mi­nor degra­da­tion of HF ra­dio com­mu­ni­ca­tion on sun­lit side, oc­ca­sional loss of ra­dio con­tact.

Low-frequency nav­i­ga­tion sig­nals de­graded for brief in­ter­vals.

More about the NOAA Space Weather Scales

G4 Levels were first reached at 2:38pm EST (1938 UTC) on 19 January, 2026 upon CME shock ar­rival. CME pas­sage is ex­pected to con­tinue through the evening with G4 lev­els re­main­ing pos­si­ble.

Apple is test­ing a new de­sign for App Store search ads on iPhone. Some users on iOS 26.3 are notic­ing that the blue back­ground around spon­sored re­sults is no longer shown, blur­ring the line be­tween what paid ad re­sults look like and the real search re­sults that fol­low.

This means the only dif­fer­en­tia­tor be­tween or­ganic re­sults and the pro­moted ad is the pres­ence of the small ‘Ad’ ban­ner next to the app icon. Right now, it ap­pears to be in some kind of A/B test phase.

We have asked Apple for clar­ity on the change, and whether this will roll out more widely in the fu­ture.

It may be re­lated to the com­pa­ny’s an­nounce­ment from December that App Store search re­sults will soon start in­clud­ing more than one spon­sored re­sult for a given search query. The re­moval of the blue back­ground will mean all of the ads will ap­pear in the list in a more in­te­grated fash­ion.

Of course, this also has the ef­fect of mak­ing it harder for users to quickly dis­tin­guish at a glance what is an ad and what is­n’t, po­ten­tially mis­lead­ing some users into not re­al­is­ing that the first re­sult is a paid ad place­ment. While not great for user ex­pe­ri­ence, it prob­a­bly helps in­crease click-through rates which ul­ti­mately boosts Apple’s rev­enue in its ads busi­ness.

👋 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

* Install the sup­ported ver­sions of SGLang and Transformers (using uv is rec­om­mended):

uv pip in­stall sglang==0.3.2.de­v9039+pr-17247.g90c446848 –extra-index-url https://​sgl-pro­ject.github.io/​whl/​pr/

uv pip in­stall git+https://​github.com/​hug­ging­face/​trans­form­ers.git@76732b4e7120808f­f989edb­d16401f61­fa6a0afa

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},

With a bal­anced sales struc­ture across in­di­vid­ual mar­kets, Dr. Ing. h.c. F. Porsche AG, Stuttgart, de­liv­ered a to­tal of 279,449 cars to cus­tomers around the world in 2025. The fig­ure was 310,718 for the pre­vi­ous year, rep­re­sent­ing a de­cline of 10 per cent. Porsche’s top pri­or­ity re­mains a value-ori­ented de­riv­a­tive mix.

With a bal­anced sales struc­ture across in­di­vid­ual mar­kets, Dr. Ing. h.c. F. Porsche AG, Stuttgart, de­liv­ered a to­tal of 279,449 cars to cus­tomers around the world in 2025. The fig­ure was 310,718 for the pre­vi­ous year, rep­re­sent­ing a de­cline of 10 per cent. Porsche’s top pri­or­ity re­mains a value-ori­ented de­riv­a­tive mix.

“After sev­eral record years, our de­liv­er­ies in 2025 were be­low the pre­vi­ous year’s level. This de­vel­op­ment is in line with our ex­pec­ta­tions and is due to sup­ply gaps for the 718 and Macan com­bus­tion-en­gined mod­els, the con­tin­u­ing weaker de­mand for ex­clu­sive prod­ucts in China, and our value-ori­ented sup­ply man­age­ment,” says Matthias Becker, Member of the Executive Board for Sales and Marketing at Porsche AG. “In 2025, we de­lighted our cus­tomers with out­stand­ing cars — such as the 911 Turbo S with its T-Hybrid drive sys­tem.” The re­sponse to the launch of the Cayenne Electric at the end of 2025 also shows, Becker adds, that Porsche is meet­ing cus­tomer ex­pec­ta­tions with its in­no­v­a­tive and high-per­for­mance prod­ucts.

With 84,328 de­liv­er­ies, the Macan was the best-sell­ing model line. North America re­mains the largest sales re­gion with 86,229 de­liv­er­ies — a fig­ure that is in line with the pre­vi­ous year.

Porsche repo­si­tioned it­self in 2025 and made for­ward-look­ing strate­gic prod­uct de­ci­sions. The de­liv­ery mix in 2025 un­der­scores that the sports car man­u­fac­turer is con­sis­tently re­spond­ing to global cus­tomer pref­er­ences by ex­pand­ing its dri­ve­train strat­egy to of­fer com­bus­tion-en­gined, plug-in hy­brid, and fully elec­tric cars. In 2025, 34.4 per cent of Porsche cars de­liv­ered world­wide were elec­tri­fied (+7.4 per­cent­age points), with 22.2 per cent be­ing fully elec­tric and 12.1 per cent be­ing plug-in hy­brids. This puts the global share of fully elec­tric ve­hi­cles at the up­per end of the tar­get range of 20 to 22 per cent for 2025. In Europe, for the first time, more elec­tri­fied cars were de­liv­ered than pure com­bus­tion-en­gined mod­els (57.9 per cent elec­tri­fi­ca­tion share), with every third car be­ing fully elec­tric. Among the Panamera and Cayenne mod­els, plug-in hy­brid de­riv­a­tives dom­i­nate the European de­liv­ery fig­ures. At the same time, the com­bus­tion-en­gined and T-Hybrid 911 set a new bench­mark with 51,583 de­liv­er­ies world­wide.

With 86,229 de­liv­er­ies, North America re­mains the largest sales re­gion, as it was the year prior. After record de­liv­er­ies in 2024, the Overseas and Emerging Markets also largely main­tained its pre­vi­ous-year lev­els, with 54,974 cars de­liv­ered (-1 per cent). In Europe (excluding Germany), Porsche de­liv­ered 66,340 cars by the end of the year, down 13 per cent year-on-year. In the German home mar­ket, 29,968 cus­tomers took de­liv­ery of new cars — a de­cline of 16 per cent. Reasons for the de­crease in both re­gions in­clude sup­ply gaps for the com­bus­tion-en­gined 718 and Macan mod­els due to EU cy­ber­se­cu­rity reg­u­la­tions.

In China, 41,938 cars were de­liv­ered to cus­tomers (-26 per cent). Key rea­sons for the de­cline re­main chal­leng­ing mar­ket con­di­tions, es­pe­cially in the lux­ury seg­ment, as well as in­tense com­pe­ti­tion in the Chinese mar­ket, par­tic­u­larly for fully elec­tric mod­els. Porsche con­tin­ues to fo­cus on value-ori­ented sales.

Deliveries of the Macan to­taled 84,328 units (+2 per cent), with fully elec­tric ver­sions ac­count­ing for over half at 45,367 ve­hi­cles. In most mar­kets out­side the EU, the com­bus­tion-en­gined Macan con­tin­ues to be of­fered, with 38,961 of these be­ing de­liv­ered. Some 27,701 Panamera mod­els were de­liv­ered by the end of December (-6 per cent).

The 911 sports car icon recorded 51,583 de­liv­er­ies by year-end (+1 per cent), set­ting an­other de­liv­ery record. The 718 Boxster and 718 Cayman to­taled 18,612 de­liv­er­ies, down 21 per cent from the pre­vi­ous year due to the model line’s phase-out. Production ended in October 2025.

The Taycan ac­counted for 16,339 de­liv­er­ies (-22 per cent), mainly due to the slow­down in the adop­tion of elec­tro­mo­bil­ity. The keys to 80,886 Cayenne mod­els were handed to cus­tomers in 2025, a de­cline of 21 per cent, partly due to catch-up ef­fects the pre­vi­ous year. The new fully elec­tric Cayenne cel­e­brated its world pre­miere in November, with the first mar­kets to of­fer the model be­gin­ning to de­liver to cus­tomers from this spring. It will be of­fered along­side com­bus­tion-en­gined and plug-in hy­brid ver­sions of the Cayenne.

Looking ahead, Matthias Becker says: “In 2026, we have a clear fo­cus; we want to man­age de­mand and sup­ply ac­cord­ing to our ‘value over vol­ume’ strat­egy. At the same time, we are plan­ning our vol­umes for 2026 re­al­is­ti­cally, con­sid­er­ing the pro­duc­tion phase-out of the com­bus­tion-en­gined 718 and Macan mod­els.” In par­al­lel, Porsche is con­sis­tently in­vest­ing in its three-pronged pow­er­train strat­egy and will con­tinue to in­spire cus­tomers with unique sports cars in 2026. An im­por­tant com­po­nent is the ex­pan­sion of the brand’s cus­tomiza­tion of­fer­ing — via both the Exclusive Manufaktur and Sonderwunsch pro­gram. In do­ing so, the com­pany is re­spond­ing to cus­tomers’ ever-in­creas­ing de­sire for in­di­vid­u­al­iza­tion.

All amounts are in­di­vid­u­ally rounded to the near­est cent; this may re­sult in mi­nor dis­crep­an­cies when summed.

This press re­lease con­tains for­ward-look­ing state­ments and in­for­ma­tion on the cur­rently ex­pected busi­ness de­vel­op­ment of Porsche AG. These state­ments are sub­ject to risks and un­cer­tain­ties. They are based on as­sump­tions about the de­vel­op­ment of eco­nomic, po­lit­i­cal and le­gal con­di­tions in in­di­vid­ual coun­tries, eco­nomic re­gions and mar­kets, in par­tic­u­lar for the au­to­mo­tive in­dus­try, which we have made based on the in­for­ma­tion avail­able to us and which we con­sider to be re­al­is­tic at the time of pub­li­ca­tion. If any of these or other risks ma­te­ri­alise, or if the as­sump­tions un­der­ly­ing these state­ments prove in­cor­rect, the ac­tual re­sults could be sig­nif­i­cantly dif­fer­ent from those ex­pressed or im­plied by such state­ments. Forward-looking state­ments in this pre­sen­ta­tion are based solely on the in­for­ma­tion per­tain­ing on the day of pub­li­ca­tion.

These for­ward-look­ing state­ments will not be up­dated later. Such state­ments are valid on the day of pub­li­ca­tion and may be over­taken by later events.

This in­for­ma­tion does not con­sti­tute an of­fer to ex­change or sell or of­fer to ex­change or pur­chase se­cu­ri­ties.

At the end of November 2025, Ursula von der Leyen gave Trump and his tech oli­garchs an early Christmas pre­sent: an un­prece­dented at­tack on dig­i­tal rights. In its so-called Digital Omnibus, the European Commission pro­posed weak­en­ing im­por­tant rules de­signed to pro­tect us from Big Tech’s abuses of power.

These are the pro­tec­tions that keep every­one’s data safe, gov­ern­ments and com­pa­nies ac­count­able, pro­tect peo­ple from hav­ing ar­ti­fi­cial in­tel­li­gence (AI) sys­tems de­cide their life op­por­tu­ni­ties, and ul­ti­mately keep our so­ci­eties free from unchecked sur­veil­lance.

At the same time, the Digital Omnibus is part of the European Commission’s deregulation agenda, which threat­ens key so­cial and en­vi­ron­men­tal stan­dards in Europe. Ironically this dereg­u­la­tion agenda is be­ing pro­moted by the Commission as a way to make the EU ‘competitive’ — de­spite in re­al­ity ac­tively em­pow­er­ing US Big Tech com­pa­nies that dom­i­nate the field.

The Digital Omnibus was im­me­di­ately heav­ily crit­i­cised by nu­mer­ous civil so­ci­ety or­gan­i­sa­tions. Politico even called it the end of the ‘Brussels ef­fect’ — that is, that European tech reg­u­la­tions are adopted in other coun­tries — and wrote that “Washington is [now] set­ting the pace on dereg­u­la­tion in Europe.”

To show the ex­tent of Big Tech’s in­flu­ence on the Digital Omnibus, we com­pared the Commission’s pro­pos­als with the lob­by­ing po­si­tions from Big Tech and its as­so­ci­a­tions.

The pro­pos­als in the Digital Omnibus con­cern both data pro­tec­tion and rules for AI. While the EU mis­tak­enly speaks of ben­e­fits for European cor­po­ra­tions, it is clear that weak dig­i­tal rules strengthen the power of Google, Microsoft, Meta etc, thereby jeop­ar­dis­ing the goal of be­com­ing more in­de­pen­dent from Big Tech and the US.

In the past, Big Tech has re­peat­edly spread the one-sided lob­by­ing mes­sage that data pro­tec­tion hin­ders eco­nomic growth and in­no­va­tion, es­pe­cially with re­gard to AI. This in­cludes ex­cep­tions for SMEs and a fun­da­men­tal fo­cus on mak­ing more use of data in­stead of pro­tect­ing it.

Tech com­pa­nies are spread­ing these mes­sages with a record-break­ing lob­by­ing bud­get, a huge lob­by­ing net­work, and sup­port from the Trump ad­min­is­tra­tion. The dig­i­tal in­dus­try’s an­nual lobby spend­ing has grown from €113 mil­lion in 2023 to €151 mil­lion to­day — an in­crease of 33.6 per­cent in just two years.

Now, the European Commission ap­pears to be bow­ing to this lob­by­ing pres­sure and adopt­ing key lob­by­ing mes­sages from Google, Microsoft, Meta and their many lobby or­gan­i­sa­tions in its Digital Omnibus.

Here we break down these in­dus­try lob­by­ing mes­sages, how they have been adopted by the Commission as pro­posed text changes, and what the real world im­pacts could be.

NVIDIA ex­ec­u­tives al­legedly au­tho­rized the use of mil­lions of pi­rated books from Anna’s Archive to fuel its AI train­ing. In an ex­panded class-ac­tion law­suit that cites in­ter­nal NVIDIA doc­u­ments, sev­eral book au­thors claim that the tril­lion-dol­lar com­pany di­rectly reached out to Anna’s Archive, seek­ing high-speed ac­cess to the shadow li­brary data.

NVIDIA ex­ec­u­tives al­legedly au­tho­rized the use of mil­lions of pi­rated books from Anna’s Archive to fuel its AI train­ing. In an ex­panded class-ac­tion law­suit that cites in­ter­nal NVIDIA doc­u­ments, sev­eral book au­thors claim that the tril­lion-dol­lar com­pany di­rectly reached out to Anna’s Archive, seek­ing high-speed ac­cess to the shadow li­brary data.

Chip gi­ant NVIDIA has been one of the main fi­nan­cial ben­e­fi­cia­ries in the ar­ti­fi­cial in­tel­li­gence boom.

Revenue surged due to high de­mand for its AI-learning chips and data cen­ter ser­vices, and the end does­n’t ap­pear to be in sight.

Besides sell­ing the most sought-af­ter hard­ware, NVIDIA is also de­vel­op­ing its own mod­els, in­clud­ing NeMo, Retro-48B, InstructRetro, and Megatron. These are trained us­ing their own hard­ware and with help from large text li­braries, much like other tech gi­ants do.

Like other tech com­pa­nies, NVIDIA has also seen sig­nif­i­cant le­gal push­back from copy­right hold­ers in re­sponse to its train­ing meth­ods. This in­cludes au­thors, who, in var­i­ous law­suits, ac­cused tech com­pa­nies of train­ing their mod­els on pi­rated books.

In early 2024, for ex­am­ple, sev­eral au­thors sued NVIDIA over al­leged copy­right in­fringe­ment.

Through the class ac­tion law­suit, they claimed that the com­pa­ny’s AI mod­els were trained on the Books3 dataset that in­cluded copy­righted works taken from the ‘pirate’ site Bibliotik. Since this hap­pened with­out per­mis­sion, the au­thors de­manded com­pen­sa­tion.

In re­sponse, NVIDIA de­fended its ac­tions as fair use, not­ing that books are noth­ing more than sta­tis­ti­cal cor­re­la­tions to its AI mod­els. However, the al­le­ga­tions did­n’t go away. On the con­trary, the plain­tiffs found more ev­i­dence dur­ing dis­cov­ery.

Last Friday, the au­thors filed an amended com­plaint that sig­nif­i­cantly ex­pands the scope of the law­suit. In ad­di­tion to adding more books, au­thors, and AI mod­els, it also in­cludes broader “shadow li­brary” claims and al­le­ga­tions.

The au­thors, in­clud­ing Abdi Nazemian, now cite var­i­ous in­ter­nal Nvidia emails and doc­u­ments, sug­gest­ing that the com­pany will­ingly down­loaded mil­lions of copy­righted books.

The new com­plaint al­leges that “competitive pres­sures drove NVIDIA to piracy”, which al­legedly in­cluded col­lab­o­rat­ing with the con­tro­ver­sial Anna’s Archive li­brary.

According to the amended com­plaint, a mem­ber of Nvidia’s data strat­egy team reached out to Anna’s Archive to find out what the pi­rate li­brary could of­fer the tril­lion-dol­lar com­pany

“Desperate for books, NVIDIA con­tacted Anna’s Archive—the largest and most brazen of the re­main­ing shadow li­braries—about ac­quir­ing its mil­lions of pi­rated ma­te­ri­als and ‘including Anna’s Archive in pre-train­ing data for our LLMs’,” the com­plaint notes.

“Because Anna’s Archive charged tens of thou­sands of dol­lars for ‘high-speed ac­cess’ to its pi­rated col­lec­tions […] NVIDIA sought to find out what “high-speed ac­cess” to the data would look like.”

According to the com­plaint, Anna’s Archive then warned Nvidia that its li­brary was il­le­gally ac­quired and main­tained. Because the site pre­vi­ously wasted time on other AI com­pa­nies, the pi­rate li­brary asked NVIDIA ex­ec­u­tives if they had in­ter­nal per­mis­sion to move for­ward.

This per­mis­sion was al­legedly granted within a week, af­ter which Anna’s Archive pro­vided the chip gi­ant with ac­cess to its pi­rated books.

“Within a week of con­tact­ing Anna’s Archive, and days af­ter be­ing warned by Anna’s Archive of the il­le­gal na­ture of their col­lec­tions, NVIDIA man­age­ment gave ‘the green light’ to pro­ceed with the piracy. Anna’s Archive of­fered NVIDIA mil­lions of pi­rated copy­righted books.”

The com­plaint states that Anna’s Archive promised to pro­vide NVIDIA with ac­cess to roughly 500 ter­abytes of data. This in­cluded mil­lions of books that are usu­ally only ac­ces­si­ble through Internet Archive’s dig­i­tal lend­ing sys­tem, which it­self has been tar­geted in court.

The com­plaint does not ex­plic­itly men­tion whether NVIDIA ended up pay­ing Anna’s Archive for ac­cess to the data.

Additionally, it’s worth men­tion­ing that NVIDIA also stands ac­cused of us­ing other pi­rated sources. In ad­di­tion to the pre­vi­ously in­cluded Books3 data­base, the new com­plaint also al­leges that the com­pany down­loaded books from LibGen, Sci-Hub, and Z-Library.

In ad­di­tion to down­load­ing and us­ing pi­rated books for its own AI train­ing, the au­thors al­lege NVIDIA dis­trib­uted scripts and tools that al­lowed its cor­po­rate cus­tomers to au­to­mat­i­cally down­load “The Pile“, which con­tains the Books3 pi­rated dataset.

These al­le­ga­tions lead to new claims of vic­ar­i­ous and con­trib­u­tory in­fringe­ment, al­leg­ing that NVIDIA gen­er­ated rev­enue from cus­tomers by fa­cil­i­tat­ing ac­cess to these pi­rated datasets.

Based on these and other claims, the au­thors re­quest to be com­pen­sated for the dam­ages they suf­fered. This ap­plies to the named au­thors, but also to po­ten­tially hun­dreds of oth­ers who may later join the class ac­tion law­suit.

As far as we know, this is the first time that cor­re­spon­dence be­tween a ma­jor U. S. tech com­pany and Anna’s Archive was re­vealed in pub­lic. This will only raise the pro­file of the pi­rate li­brary, which just lost sev­eral do­main names, even fur­ther.

A copy of the first con­sol­i­dated and amended com­plaint, filed at the U. S. District Court for the Northern District of California, is avail­able here (pdf). The named au­thors in­clude Abdi Nazemian, Brian Keene, Stewart O’Nan, Andre Dubus III, and Susan Orlean.