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Firefox is now the last major browser that still supports uBlock Origin

www.pcworld.com

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

News

Aug 13, 2026

Firefox re­cently an­nounced via Bluesky post: Our sup­port for uBlock Origin is­n’t go­ing any­where.” The mo­ment comes in re­sponse to news that Microsoft Edge is soon go­ing to lock out uBlock Origin and other ad-block­ing ex­ten­sions that run on Manifest V2 ar­chi­tec­ture.

Once Microsoft Edge moves to Manifest V3, ad-block­ing ex­ten­sions won’t have ac­cess to the func­tions needed to prop­erly iden­tify and block ads that oc­cur while brows­ing web­sites and watch­ing videos.

Microsoft’s move is­n’t sur­pris­ing, as Edge is based on Chromium, the open-source browser en­gine that pow­ers most web browsers to­day, in­clud­ing Opera, Brave, Vivaldi, and Samsung Browser. Google ini­ti­ated the mi­gra­tion from Manifest V2 to V3 in Chrome/Chromium, and Microsoft Edge is now fol­low­ing Google’s lead.

But Firefox is one of the few web browsers re­main­ing that is­n’t based on Chromium, and it’s now the only ma­jor browser to still sup­port uBlock Origin. Neither Safari nor DuckDuckGo—the two other ma­jor non-Chromium browsers out there—sup­port uBlock Origin.

For die-hard uBlock Origin fans, Firefox ap­pears to be the only browser left with­out com­pro­mises. With any other browser, you’ll need to set­tle for uBlock Origin Lite (with fewer fea­tures and less ad-block­ing suc­cess) or what­ever built-in ad-block­ing fea­ture comes with the browser.

This ar­ti­cle orig­i­nally ap­peared on our sis­ter pub­li­ca­tion PC för Alla and was trans­lated and lo­cal­ized from Swedish.

Qwen/Qwen3.8-27B-FP8 · Hugging Face

huggingface.co

This repos­i­tory con­tains FP8-quantized model weights and con­fig­u­ra­tion files for the post-trained model in the Hugging Face Transformers for­mat. These ar­ti­facts are com­pat­i­ble with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc. The quan­ti­za­tion method is fine-grained fp8 quan­ti­za­tion with block size of 128, and its per­for­mance met­rics are nearly iden­ti­cal to those of the orig­i­nal model.

This repos­i­tory con­tains FP8-quantized model weights and con­fig­u­ra­tion files for the post-trained model in the Hugging Face Transformers for­mat.

These ar­ti­facts are com­pat­i­ble with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc.

The quan­ti­za­tion method is fine-grained fp8 quan­ti­za­tion with block size of 128, and its per­for­mance met­rics are nearly iden­ti­cal to those of the orig­i­nal model.

For users seek­ing man­aged, scal­able in­fer­ence with­out in­fra­struc­ture main­te­nance, the of­fi­cial Qwen API ser­vice is pro­vided by Qwen Cloud. In par­tic­u­lar, Qwen3.8 – 27B will be avail­able as a hosted ver­sion with more pro­duc­tion fea­tures, e.g., 1M con­text length by de­fault, of­fi­cial built-in tools. For more in­for­ma­tion, please re­fer to the Qwen3.8 – 27B Overview. The ser­vice is com­ing soon. Stay tuned for up­dates.

For users seek­ing man­aged, scal­able in­fer­ence with­out in­fra­struc­ture main­te­nance, the of­fi­cial Qwen API ser­vice is pro­vided by Qwen Cloud.

In par­tic­u­lar, Qwen3.8 – 27B will be avail­able as a hosted ver­sion with more pro­duc­tion fea­tures, e.g., 1M con­text length by de­fault, of­fi­cial built-in tools. For more in­for­ma­tion, please re­fer to the Qwen3.8 – 27B Overview. The ser­vice is com­ing soon. Stay tuned for up­dates.

Following the wide­spread com­mu­nity adop­tion of the Qwen3.5 and Qwen3.6 se­ries, we are pleased to in­tro­duce Qwen3.8, the most ca­pa­ble gen­er­a­tion in the Qwen open-model fam­ily to date.

Built on the ar­chi­tec­tural foun­da­tion of Qwen3.5, Qwen3.8 de­liv­ers sub­stan­tial gains across cod­ing, pro­fes­sional work, re­search, and long-hori­zon agen­tic tasks. Qwen3.8 – 27B brings these ad­vances to a com­pact, de­ploy­ment-friendly dense model: a na­tive vi­sion-lan­guage model that un­der­stands im­ages and videos, with flex­i­ble think­ing con­trol, de­signed to carry com­plex, multi-step tasks through to com­ple­tion with greater re­li­a­bil­ity.

Qwen3.8 Highlights

Qwen3.8 – 27B fea­tures the fol­low­ing en­hance­ments:

Core Capabilities: Comprehensive im­prove­ments across cod­ing, pro­fes­sional work, re­search, and long-hori­zon agen­tic tasks.

Agent Execution: Stronger au­tonomous plan­ning and bet­ter han­dling of en­vi­ron­ment feed­back, lead­ing to more re­li­able end-to-end task com­ple­tion.

Downstream Compatibility: Broader sup­port for pop­u­lar har­nesses and de­vel­op­ment tools, mak­ing it eas­ier to in­te­grate into your ex­ist­ing stack.

Flexible Thinking Control: Thinking mode is on by de­fault and can be dis­abled per re­quest; rea­son­ing depth can be tuned with rea­son­ing_­ef­fort, and rea­son­ing con­text from his­tor­i­cal mes­sages is re­tained via pre­serve_­think­ing.

Vision-Language Understanding: Native sup­port for im­age and video un­der­stand­ing, from STEM di­a­grams and doc­u­ments to hour-scale videos.

Model Overview

Type: Causal Language Model with Vision Encoder

Training Stage: Pre-training & Post-training

Language Model Number of Parameters: 27B Hidden Dimension: 5120 Token Embedding: 248,320 (Padded) Number of Layers: 64 Hidden Layout: 16 × (3 × (Gated DeltaNet → FFN) → 1 × (Gated Attention → FFN)) Gated DeltaNet: Number of Linear Attention Heads: 48 for V and 16 for QK Head Dimension: 128

Gated Attention: Number of Attention Heads: 24 for Q and 4 for KV Head Dimension: 256 Rotary Position Embedding Dimension: 64

Feed Forward Network: Intermediate Dimension: 17,408

LM Output: 248,320 (Padded) MTP (Multi-Token Prediction): trained with mul­ti­ple steps

Number of Parameters: 27B

Hidden Dimension: 5120

Token Embedding: 248,320 (Padded)

Number of Layers: 64

Hidden Layout: 16 × (3 × (Gated DeltaNet → FFN) → 1 × (Gated Attention → FFN))

Gated DeltaNet: Number of Linear Attention Heads: 48 for V and 16 for QK Head Dimension: 128

Number of Linear Attention Heads: 48 for V and 16 for QK

Head Dimension: 128

Gated Attention: Number of Attention Heads: 24 for Q and 4 for KV Head Dimension: 256 Rotary Position Embedding Dimension: 64

Number of Attention Heads: 24 for Q and 4 for KV

Head Dimension: 256

Rotary Position Embedding Dimension: 64

Feed Forward Network: Intermediate Dimension: 17,408

Intermediate Dimension: 17,408

LM Output: 248,320 (Padded)

MTP (Multi-Token Prediction): trained with mul­ti­ple steps

Context Length: 262,144 na­tively and ex­ten­si­ble up to 1,000,000 to­kens.

Benchmark Results

Text Performance

Agentic ter­mi­nal cod­ing

Terminal Bench 2.1 (Terminus)

Agentic cod­ing

SWE-bench Pro

Repo-level code gen­er­a­tion

NL2Repo-Bench

Agentic cod­ing

DeepSWE 1.1

Software en­gi­neer­ing

QwenSWEBench

Long-horizon of­fice work

CoWorkBench

Professional job tasks

JobBench

Frontier agen­tic tasks

Agents’ Last Exam

Pass@1

20.4

Score

42.9

Pass@1

10.6

Score

27.3

Pass@1

13.2

Score

33.6

Instruction fol­low­ing

IFBench

Scientific rea­son­ing

GPQA Diamond

Multidisciplinary rea­son­ing

HLE

Competitive cod­ing

LiveCodeBench v6

SWE-bench Pro: Except for Opus4.6 Max, which uses the of­fi­cially re­ported score, all mod­els are eval­u­ated with the Claude Code har­ness at temp=1.0, top_p=0.95, and a 256K con­text win­dow. Problematic tasks were cor­rected, and all base­line mod­els were re-eval­u­ated on the re­fined bench­mark.

NL2Repo-Bench: Evaluated with the Claude Code har­ness. To pre­vent re­ward hack­ing, we dis­able Bash com­mands that at­tempt to ac­cess the spe­cific repos­i­tory, such as pip down­load, pip in­stall, and git clone.

DeepSWE 1.1: Evaluated with the Claude Code har­ness at temp=1.0, top_p=0.95, and a 256K con­text win­dow.

QwenSWEBench: In-house cod­ing bench­mark for eval­u­at­ing mod­els’ soft­ware en­gi­neer­ing ca­pa­bil­i­ties. Evaluated with the Claude Code har­ness. Reporting avg@3 with an 8-hour time­out, max_­to­kens=32,768, tem­per­a­ture=1.0, and a 256K con­text win­dow.

CoWorkBench: In-house cowork bench­mark for eval­u­at­ing long-hori­zon tasks across com­puter sci­ence, fi­nance, law, med­ical, and other pro­duc­tiv­ity do­mains.

HLE: Judged by GPT-4o.

The best re­sult in each row is shown in bold.

Empty cells (–) in­di­cate that re­sults are not yet avail­able or not ap­plic­a­ble.

VL Performance

Computer use

OSWorld-Verified

Browser use

WebArena-Verified

Mobile use

AndroidWorld

Application recre­ation

RecreationBench

Multimodal tool use

ClawEval-MM

Pass@3

57.4

Average

Every Fucking Website

lxe.github.io

In case you’re not aware, there’s COVID-19 hap­pen­ing! Here’s some stuff we wrote that you won’t read.

You ob­vi­ously know what cook­ies are. If we don’t put this here, de­lighted lawyers from EU and CA will sue us. Not only this is very ex­pen­sive, there are no browser set­tings to re­move this, since every site does this dif­fer­ently. You voted for this! Also you have to click I agree”

Count Binface receives over a quarter of votes in Clacton by-election

www.bbc.com

1 day ago

Jennifer McKiernanPolitical re­porter

Getty Images

Count Binface, the self-styled in­ter­galac­tic space war­rior, has re­ceived nearly 10,000 votes in the Clacton by-elec­tion, his best per­for­mance yet.

Farage has re-won his seat, re­ceiv­ing more than 22,000 votes in Clacton, on the Essex coast.

Binface re­ceived 26.9% of the vote while Farage won 63.3%. Binface had his high­est share yet with 9,455 votes, hav­ing lost to no fewer than three prime min­is­ters, and one who later be­came prime min­is­ter, in pre­vi­ous at­tempts.

But how many votes has he pre­vi­ously re­ceived? And where does he fit into the British tra­di­tion of spoof­ing politi­cians?

2017: May the force be with you

Getty Images

The man in­side the bin is the co­me­dian Jon Harvey, an Oxford grad­u­ate who has spe­cialised in satire, writ­ing scripts for BBC com­edy shows The Thick of It and Have I Got News For You.

He first donned a bin on his head to stand for elec­tion in 2017, when he chal­lenged the then Prime Minister Theresa May in her Maidenhead con­stituency, al­though back then he was known as Lord Buckethead, a char­ac­ter in­spired by a Star Wars par­ody film.

He won 249 votes and vi­ral fame, lead­ing to an ap­pear­ance on John Oliver’s HBO show Last Week Tonight - as well as a le­gal dis­pute with an­other Lord Buckethead he de­scribed at the time as an un­pleas­ant bat­tle on the planet Copyright”.

2019: The bin takes on Boris Johnson

Getty Images

Harvey found him­self a dif­fer­ent bin to cover his head and switched char­ac­ters to Count Binface to take on the next Conservative leader, Boris Johnson, an­nounc­ing him­self as the leader of the Recyclons from planet Sigma IX.

He only won 69 votes, but was again able to take his place on stage as the elec­tion re­sult was de­clared along­side a sit­ting prime min­is­ter, who was also flanked by a can­di­date dressed as the Sesame Street char­ac­ter Elmo, at his Uxbridge elec­tion count.

2024: Sunak takes out the trash

Getty Images

A third Conservative leader, Rishi Sunak, was in Count Binface’s sights in the 2024 gen­eral elec­tion cam­paign.

He got 308 votes, which at the time was his best re­sult.

The Monster Raving Loony Party’s can­di­date, Sir Archibald Stanton, re­ceived 99 votes - 0.2% of the vote share.

2026: Burnham courts the Count

Getty Images

In June this year, it was Andy Burnham’s turn to face Binface in the by-elec­tion that paved the way for the then Greater Manchester Mayor to be­come prime min­is­ter.

Rather than stu­diously ig­nor­ing the in­ter­galac­tic war­lord, as some may have been tempted to do, Burnham shook him warmly by the hand as he was elected Labour MP for Makerfield.

Binface bagged just 95 votes to Burnham’s 24,927.

2026: The Bin’s best re­sult yet

While Nigel Farage won the Clacton by-elec­tion on Friday morn­ing, Count Binface came sec­ond.

The Reform UK leader got 22,239 while Count Binface re­ceived 9,455. The in­ter­galac­tic space war­rior cel­e­brated the num­ber with his usual two peace sign fin­gers.

Speaking to BBC Breakfast af­ter, Binface said: I promised to be a lo­cal cham­pion for Clacton and I thought to hear the ver­dict of the Clactonites was the least I could do.”

A great British tra­di­tion?

The UK has a rich his­tory of nov­elty can­di­dates stand­ing in elec­tions, with Monster Raving Loony Party founder Screaming Lord Sutch - a rock mu­si­cian who fought more than 40 elec­tions in his trade­mark top hat and gold lame suit - first stand­ing in a by-elec­tion in the 1960s. A dif­fer­ent Lord Buckethead stood in 1987 and 1992, while co­me­dian Al Murray’s pub land­lord stood against Farage in 2015.

Objections to such frivolous” can­di­dates date back even fur­ther - to 1918, when a £150 de­posit was in­tro­duced for can­di­dates. That was later upped to £500, in 1985, in large part due to the pop­u­lar­ity of the Monster Raving Loony Party.

BBC/ Willie Smith

But the bar for en­try re­mains fairly low: any­one over the age of 18 who can scrape to­gether a £500 de­posit and get sup­port from 10 peo­ple in the form of sig­na­tures is al­lowed to stand as a can­di­date in UK elec­tions.

That’s why Count Binface has been able to stand in so many high-pro­file elec­tions. He has, how­ever, lost his £500 every time, af­ter fail­ing to meet the min­i­mum 5% of votes cast in or­der for his de­posit to be re­turned.

Yet Binface has had his mo­ment in the spot­light each time.

That is be­cause an­other British tra­di­tion means all elec­tion can­di­dates must stand side-by-side on a stage at the elec­tion count to hear how many votes they have each re­ceived - it’s a lit­eral lev­eller, where every­one from prime min­sters to a bloke dressed as a bin has the right to be seen and heard as an of­fi­cial can­di­date.

But all of these no-hope nov­elty can­di­dates share a few se­ri­ous aims: to poke fun at power, prick the pom­pos­ity of po­lit­i­cal elites, and al­low peo­ple a protest vote.

How Google is Making Private AI Practical with Homomorphic Encryption

blog.google

Today we’re ex­cited to show­case HEIR, the lat­est pow­er­ful tool added to our Private Computing Toolkit. HEIR is an open source com­piler that un­locks cryp­to­graph­i­cally-se­cure pri­vate AI in­fer­ence.

Homomorphic en­cryp­tion

As new ben­e­fits emerge with the growth of AI, bal­anc­ing pri­vacy and se­cu­rity is top of mind. Standard pro­tec­tions like end-to-end en­cryp­tion pre­sent a trade-off: user-data can be pro­tected from data breaches, but then the ser­vice provider can­not pro­vide fea­tures that de­pend on the data, such as spam or virus de­tec­tion. Critical sec­tors like health­care and fi­nance are even more averse to these risks, and strict reg­u­la­tions limit data shar­ing across in­sti­tu­tions. Alternative mech­a­nisms to pro­vide the same fea­tures, like lo­cal pro­cess­ing, are lim­ited by the ca­pa­bil­i­ties of the lo­cal de­vice and the sen­si­tiv­ity of the ser­vice provider’s IP. Shipping pro­pri­etary AI to a de­vice risks leak­ing the model.

A so­lu­tion to these is­sues is ho­mo­mor­phic en­cryp­tion, a rapidly ma­tur­ing tech­nol­ogy that fun­da­men­tally al­ters this trade-off by al­low­ing com­pu­ta­tions to be per­formed di­rectly on en­crypted data. Servers can process ci­pher­texts and re­turn en­crypted re­sults with­out ex­pos­ing any un­der­ly­ing in­for­ma­tion. For ex­am­ple, a cloud ser­vice can pro­vide con­tent rec­om­men­da­tions with­out be­ing able to see the user’s fea­tures. This is no ex­ag­ger­a­tion: one of the demos fea­tured in this post does ex­actly this. But while ho­mo­mor­phic en­cryp­tion has a non­triv­ial cost over­head, it shifts the ca­pa­bil­ity/​pri­vacy trade-off to a ques­tion of cost. And the cost of ho­mo­mor­phic en­cryp­tion is rapidly de­creas­ing.

Google’s his­tory of in­no­va­tions in pri­vacy tech­nol­ogy—from dif­fer­en­tial pri­vacy and pri­vate set mem­ber­ship to pri­vate in­for­ma­tion re­trieval and se­cure en­claves on Google Cloud—has al­ways fo­cused on se­cur­ing user data. Homomorphic en­cryp­tion is an­other pow­er­ful tool we’re adding to our pri­vate com­put­ing toolkit. Like pri­vate in­for­ma­tion re­trieval, and in con­trast to hard­ware-based so­lu­tions, ho­mo­mor­phic en­cryp­tion’s strong se­cu­rity and pri­vacy guar­an­tees are purely cryp­to­graphic. However, man­u­ally con­vert­ing an ex­ist­ing pro­gram to use ho­mo­mor­phic en­cryp­tion ef­fi­ciently re­quires a team of cryp­tog­ra­phers.

About HEIR

To over­come the us­abil­ity chal­lenges and ad­vance the op­por­tu­nity ho­mo­mor­phic en­cryp­tion pro­vides, re­searchers and en­gi­neers at Google built the HEIR com­piler pro­ject. HEIR (Homomorphic Encryption Intermediate Representation) is an open-source com­piler tool­chain and de­vel­op­ment plat­form for ho­mo­mor­phic en­cryp­tion. In par­tic­u­lar, HEIR can con­vert pre-trained AI mod­els that op­er­ate on un­en­crypted data to op­er­ate on en­crypted in­puts. Our vi­sion is to make HEIR a one-click so­lu­tion to en­able non-ex­perts to in­cor­po­rate en­crypted in­fer­ence into pro­duc­tion ap­pli­ca­tions.

Since an­nounc­ing our in­ten­tions in 2023, we’ve seen the ho­mo­mor­phic en­cryp­tion com­mu­nity em­brace HEIR. We have part­nered with com­pa­nies de­vel­op­ing hard­ware ac­cel­er­a­tors for ho­mo­mor­phic en­cryp­tion, in­clud­ing Belfort, Niobium, Cornami, and Optalysys. The fruits of those ef­forts are shown in our demos be­low, and we plan to demon­strate the la­tency ben­e­fits of these ac­cel­er­a­tors in the near fu­ture. HEIR has also be­come a pro­duc­tive re­search plat­form. By build­ing on HEIR, cryp­tog­ra­phers can fo­cus on their spe­cific op­ti­miza­tion and use the ex­ist­ing in­fra­struc­ture for test­ing, bench­mark­ing, and com­par­isons. This has re­sulted in col­lab­o­ra­tions with Georgia Tech, Carnegie Mellon, UC Santa Barbara, Illinois Institute of Technology, Purdue, the University of Edinburgh, Tsinghua University, and oth­ers. To date, four peer-re­viewed pub­li­ca­tions were built on HEIR, with more in prepa­ra­tion, and HEIR has ac­cu­mu­lated nu­mer­ous ci­ta­tions.

Applications of HEIR

To demon­strate how far ho­mo­mor­phic en­cryp­tion has come, we’re shar­ing four pri­vate in­fer­ence ap­pli­ca­tions. Each ap­pli­ca­tion was com­piled with HEIR, and la­tency num­bers are pre­sented for a sin­gle-threaded CPU. The source code for all ex­am­ples is avail­able in our GitHub repos­i­tory.

A Deep Learning Recommendation Model un­locks serv­ing pri­vate con­tent rec­om­men­da­tions, joint work with Belfort Labs, LG, and New York University.

Credit card fraud de­tec­tion: Together with Niobium and hard­shell.ai, we com­piled a credit card fraud de­tec­tor.

Threat in­tru­sion: Together with Niobium we com­piled the Kitsune sys­tem for anom­aly de­tec­tion of en­crypted net­work traf­fic. This al­lows a ser­vice provider to de­tect anom­alies with­out re­veal­ing the con­tents of net­work pack­ets to the ser­vice provider.

Hotword Detector: Together with Belfort Labs we com­piled a hot­word de­tec­tion model, which could al­low an au­dio-trig­gered AI agent to rec­og­nize hot­words while pro­tect­ing the pri­vacy of the au­dio record­ings.

As the soft­ware in­dus­try adapts to se­cu­rity and pri­vacy changes amid AI, our re­search team is work­ing to make ho­mo­mor­phic en­cryp­tion, easy to de­velop, fast to run, and ubiq­ui­tous across in­dus­try.

Everything is about to “go dark”

blog.cryptographyengineering.com

I’m com­ing down from spend­ing a few days at Usenix Security, right here in my home­town of Baltimore. This means that my days have been taken up with two kinds of con­ver­sa­tion: first, ex­plain­ing to col­leagues why Baltimore is­n’t ac­tu­ally like The Wire. And sec­ond, try­ing not to talk about AI.

Here I’m go­ing to break that sec­ond rule.

I have many wor­ries about what AI means for our field, for var­i­ous de­f­i­n­i­tions of field”. But in this post I want to fo­cus on just one thing I’ve started wor­ry­ing about, and it’s a per­verse thing: specif­i­cally, I’m con­cerned that AI is go­ing to make soft­ware much too se­cure.

While that does­n’t sound so bad on the sur­face, there’s a con­se­quence to this. I mean some­thing very spe­cific: I’m con­cerned that U.S. in­tel­li­gence and law en­force­ment agen­cies are about to go dark, mean­ing: that they’re go­ing to sud­denly lose a huge por­tion of their ca­pa­bil­ity. And that this is­n’t go­ing to be sim­ply a prob­lem for those agen­cies, but also for those of us who value com­puter se­cu­rity and pri­vacy in gen­eral.

Going Dark, and the era of law en­force­ment hack­ing

To ex­plain how we got here, we need to talk about re­cent his­tory. This ac­tu­ally gives me a real ex­cuse to ref­er­ence The Wire, just be­cause it’s a per­fect snap­shot of what elec­tronic sur­veil­lance looked like way back in 2002. If you’ve seen the first sea­son, you’ll re­call that it’s about cops wire­tap­ping drug deal­ers who use pay­phones and burn­ers. The mo­bile phones in the show are rel­a­tively new tech­nol­ogy for the time, but from a tech­no­log­i­cal per­spec­tive noth­ing in this sce­nario would have shocked a cop who jumped for­ward from, say, 1989.

In less than a decade from the pre­mier, every­thing in those episodes be­came to­tally quaint.

The change be­gan in the late 2000s, thanks to the rise of smart­phones and tex­ting. Because smart­phones can ac­tu­ally store data as well as con­vey­ing it, the con­tents of those phones quickly be­came a use­ful new source of law-en­force­ment ca­pa­bil­ity. Or they were un­til 2010, when Apple be­gan en­crypt­ing iPhone stor­age us­ing a key de­rived from the user’s pass­code (Android phones fol­lowed shortly there­after.) The next year, Apple de­ployed end-to-end en­cryp­tion in iPhone text mes­sages. By 2014, a tiny tex­ting startup named WhatsApp had gath­ered 600 mil­lion users world­wide. By 2016 those users, now nearly a bil­lion strong, were all us­ing de­fault end-to-end en­crypted mes­sag­ing and calls. These two trends — the move from calls to texts, and texts to en­crypted data — hap­pened very rapidly. The chart be­low gives one view of the tran­si­tion:

The FBI and law en­force­ment agen­cies were not in­sen­si­tive to what was hap­pen­ing. In 2014, Director Comey an­nounced an ini­tia­tive called Going Dark, which would launch a national con­ver­sa­tion” about what providers could do — or be com­pelled to do — to make these new com­mu­ni­ca­tions me­dia leg­i­ble to law en­force­ment and coun­ter­in­tel­li­gence.

In 2016, the agency quit talk­ing and took their the­ory to court. When a ter­ror­ist at­tack left the FBI hold­ing a shooter’s locked iPhone, the agency or­dered Apple to give them ac­cess. The com­pany re­fused. What broke the stale­mate — and, to some ex­tent, ended Going Dark” it­self — was some­thing that nei­ther the FBI nor Apple ex­pected. An out­side com­pany an­nounced that there was no need for Apple’s as­sis­tance: they could sim­ply hack the phone.

The Apple v. FBI case turned out to be mi­cro­cosm of the whole Going Dark de­bate. For the next decade, law en­force­ment and in­tel­li­gence agen­cies con­tin­ued to ask for exceptional ac­cess” back­doors. But the ur­gency was gone: both agen­cies and man­u­fac­tur­ers knew that law en­force­ment could pur­chase tar­geted hack­ing tools like GrayKey (for phone un­lock­ing), or even re­mote ex­ploita­tion tools like NSO Group’s Pegasus, as­sum­ing they needed them badly enough. Vendors like Apple and Google played a vig­or­ous de­fense, clos­ing vul­ner­a­bil­i­ties as soon as they learned about them. But of­fen­sive vul­ner­a­bil­ity hunters con­sis­tently man­aged to keep the edge.

And now there’s a very good chance that all this is about to be his­tory.

The era of AI bug hunt­ing is here

This April (just four months ago!) Anthropic an­nounced a new model called Mythos that hap­pened to be un­usu­ally skilled at soft­ware vul­ner­a­bil­ity find­ing. The U.S. gov­ern­ment tem­porar­ily blocked its ex­port, re­strict­ing ac­cess to U.S. agen­cies and trusted ven­dors. While the ban was dra­matic and made for good PR, it turned out to be mostly point­less. OpenAI, along with Chinese open-weight model labs like Z.ai and Moonshot, have since demon­strated that vul­ner­a­bil­ity find­ing is­n’t some­thing that a sin­gle lab is likely to hold a mo­nop­oly on. The list of se­ri­ous vul­ner­a­bil­i­ties that these mod­els have found is get­ting scarier (or more im­pres­sive) by the day.

At first glance, this might seems like good news for the of­fen­sive team, and for hack­ers in gen­eral. But I doubt that’s how this will play out in the long term. Defenders are now in the process of patch­ing every bug they can find — of­ten decades worth of bugs — and the back­log feels huge. But they’re mak­ing progress. Entire CI tool­chains are be­ing re­built to in­cor­po­rate AI-based vul­ner­a­bil­ity scan­ning be­fore soft­ware ever reaches the point where a hu­man will touch it. While I doubt this means that every bug will be found (even cal­cu­lat­ing the num­ber of bugs in a piece of code is prob­a­bly un­com­putable), in the real world, it does feel likely that we’re go­ing to hit some sort of a ceil­ing on the num­ber of use­ful bugs, and prob­a­bly we’ll hit it soon.

Thus: over the next two years, ma­jor pieces of soft­ware are likely to run out of re­motely-ex­ploitable bugs.

Obviously I think this is great. But for law en­force­ment and of­fen­sive in­tel­li­gence agen­cies, it’s go­ing to be a night­mare. For the first time since 2010, law en­force­ment might ex­pe­ri­ence what it looks like to re­ally go dark”, across a huge cat­e­gory of ad­vanced (well-maintained) de­vices and pieces of soft­ware.

So how is this a prob­lem?

The de­bate over exceptional ac­cess” mech­a­nisms never re­ally went away. In some places, like the UK, it even metas­ta­sized into some­thing worse. Here in the US it mostly went into hi­ber­na­tion. Some of the slow­down can le­git­i­mately be at­trib­uted to ex­pert push­back — aca­d­e­mics and in­dus­try en­gi­neers point­ing out the risk that back­doors might be abused by the very ad­ver­saries that Agencies are sup­posed to be pro­tect­ing us against. But I fear that this was less of a prin­ci­pled pause, and more of a mar­ket that was just pric­ing sup­ply.

The de­struc­tion of the low-hang­ing vul­ner­a­bil­ity fruit will make law en­force­ment (and in­tel­li­gence) agen­cies’ need much more acute. The de­mand for con­structed, in­ten­tional back­doors will re-start in earnest. The re­sult will be enor­mous pres­sure on in­dus­try to re-ar­chi­tect their sys­tems to make their sys­tems amenable to ex­cep­tional ac­cess. In some cases, gov­ern­ments will ask for these ca­pa­bil­i­ties in the ex­pec­ta­tion that they’ll be use­ful for spy­ing on other gov­ern­ments — a strat­egy that might have been un­de­tectable in the pre-AI era, but that prob­a­bly will be less pro­duc­tive now. The re­sults are un­pre­dictable. One re­sult might be that non-US gov­ern­ments en­tirely re­move their de­pen­dence on US soft­ware.

The worst part about this dy­namic is that these po­ten­tial new back­doors will prob­a­bly only af­fect the coun­tries that de­mand them, mean­ing that they will be pri­mar­ily use­ful for al­low­ing the US to weaken its own sys­tems. This will in turn al­low for­eign ad­ver­saries to find new ways to at­tack our com­mu­ni­ca­tions. This de­lib­er­ate self-sab­o­tage will hap­pen just at a mo­ment when we’re fi­nally get­ting a han­dle on se­cur­ing our own in­fra­struc­ture.

So what do we do about it?

I hon­estly have no idea. This is not a call to ac­tion for ex­perts to rally be­hind a so­phis­ti­cated plan. Like so many things about the AI rev­o­lu­tion, it’s just oc­cur­ring to me that we’re on a long greasy slide to a place that will look dif­fer­ent than where we are to­day. Just re­al­iz­ing this does­n’t mean that I have a clever plan to avoid it. In this case, we’re just go­ing to have to hope that this time we make the right choices, for no other rea­son than that they’re right.

Seven books I keep close because I love them

blog.plover.com

Seven books I keep close be­cause I love them

The book­shelf by my el­bow, the one that I can reach with­out get­ting up, has seven books on it, not nec­es­sar­ily the ones I look in the most, but the ones whose em­a­na­tions I most hope will in­fuse me as I write.

Roget’s Thesaurus (4th edi­tion)

The one I ac­tu­ally re­fer to most of­ten is the Harper and Row Roget’s Thesaurus. I thought I had ac­quired this in my teens, but the note on the fly­leaf says 1989.

This is the fourth edi­tion. I was very ex­cited to get the eighth edi­tion, which I thought I might like bet­ter, and for some time I kept them next to each other so that I could look up the same things in both, and com­pare. My con­clu­sion was that while the eighth edi­tion had more stuff in it, it was­n’t stuff I needed. And it is re­ally fat. So I have re­tired it to a far­ther shelf and will even­tu­ally get rid of it.

The the­saurus is a book that is widely mis­un­der­stood. It is not, as many peo­ple mock­ingly imag­ine, just a com­pendium of syn­onyms, and its cor­rect and in­tended use is not to re­place com­mon words with more im­pres­sive-sound­ing ones. just as the cor­rect use of a screw­driver is not to scrape the ve­neer off of an ex­pen­sive cab­i­net.

Thesaurus” means storehouse” or treasure room”. Roget’s idea, sim­i­lar to that of John Wilkins be­fore him, was to clas­sify every­thing in the world into a hi­er­ar­chy, in this case a hi­er­ar­chy with a thou­sand di­vi­sions. At the top level the di­vi­sions are grouped into Abstract con­cepts”, Space”, Physics”, Matter”, Sensation” and so on. Then un­der abstract con­cepts” there are sub­classes, of which sub­class VI is Time”, sub­di­vided into five smaller sec­tions:

A. Absolute time B. Relative time C. Time with ref­er­ence to age D. Time with ref­er­ence to sea­son E. Recurrent time

At the next level down, sec­tion (1)(VI)(B) is di­vided into:

§116. Priority §117. Posteriority §118. Simultaneity §119. The Past §120. The Present §121. The Future

Roget’s idea is that if you are think­ing or writ­ing about time, and specif­i­cally about how it goes by, you will leaf through those sec­tions for in­spi­ra­tion, not to find a more pompous way of ex­press­ing some­thing you have al­ready writ­ten, but to re­fine your own idea of what it is you wanted to ex­press.

Perhaps you are try­ing to say that one event fol­lowed im­me­di­ately af­ter an­other. You might look at §117 pos­te­ri­or­ity (later time)” which men­tions ensue”, consequence”, aftermath”, and subsequent” — not syn­onyms, but re­lated as­pects of sim­i­lar con­cepts, worth more or less con­sid­er­a­tion de­pend­ing on what you are try­ing to em­pha­size. §117 will also sug­gest com­mon phrases like step into the shoes of” — not a syn­onym by any means, but a re­lated idea. This is prob­a­bly not what you wanted in this case, but it in an­other it might be just the thing, and in any case it might give you a bright idea.

If noth­ing in sec­tion 117 seems suit­able, it is right next to §116 pri­or­ity”, and you might dis­cover that in­stead of say­ing that the sec­ond event fol­lowed im­me­di­ately af­ter the first, you would rather say that the first im­me­di­ately pre­ceded the sec­ond. Or per­haps you re­al­ize, look­ing at §118 Simultaneity”, that what you re­ally want to say is that the two events were not quite si­mul­ta­ne­ous. Or per­haps, find­ing your way to §131 Earliness” and §132 Lateness” you re­al­ize that your mean­ing would be more clearly ex­pressed if you said that the sec­ond event was a lit­tle tardy, or that the first event was pre­ma­ture.

Looking through the in­dex for immediately” you will see that the in­dex dis­tin­guishes sev­eral senses of immediate”: are you try­ing to sug­gest in­stan­ta­ne­ity, or con­ti­nu­ity, or haste, or prompt­ness, or punc­tu­al­ity? And in this way the book helps you re­fine your un­der­stand­ing of what you were try­ing to say.

One can use the the­saurus for more con­crete tasks. Perhaps I am try­ing to re­mem­ber a word, but I can’t quite put my fin­ger on it. I know it it is not coexisting”, but is some­thing like it. I can look up coexisting” in the in­dex, and it will take me to §118 Simultaneity” where I find contemporaneous”… aha, that’s what I was look­ing for! The re­ally im­por­tant thing about the the­saurus is this large-scale or­ga­niz­ing prin­ci­ple, which puts re­lated ideas near one an­other.

Note that none of this works for some­one who does­n’t know what the words ac­tu­ally mean. All that per­son can do with the the­saurus is to re­place one wrong word with an­other one, more or less at ran­dom. Effective tool use re­quires skill and train­ing, and care­ful thought.

An on­line ver­sion would be more con­ve­nient, but again, it would­n’t have the same stuff and I am very at­tached to the one I have.

My ban­ish­ment of the 8th edi­tion left a lot of space on the shelf, some of which I have filled with an an­thol­ogy of the prose of Sir Thomas Browne. I think this will be health­ful and in­spir­ing for me, es­pe­cially if I re­mem­ber to take it up and thumb through it from time to time.

The Prose of Sir Thomas Browne

One re­cur­ring theme on this blog since the very ear­li­est days has been the writ­ers of the English Baroque pe­riod. In 2008 I wrote:

[Browne] is witty, and learned, and wise, and hu­mane, and to read his books is to feel that you are in the com­pany of this witty, learned, wise, hu­mane man, one of the best men that the English Renaissance has to of­fer, and that you are prof­it­ing thereby.

[Browne] is witty, and learned, and wise, and hu­mane, and to read his books is to feel that you are in the com­pany of this witty, learned, wise, hu­mane man, one of the best men that the English Renaissance has to of­fer, and that you are prof­it­ing thereby.

His work was also a fa­vorite of Jorge Luis Borges’, in case you con­sider that a rec­om­men­da­tion.

Browne has shown up here a num­ber of times, al­though not so much as he should have, be­cause I started the blog the year af­ter I was on my big Thomas Browne kick. One rea­son I have put this book next to my el­bow is that I hope it will spark a new Browne kick. (I wrote in 2006 I’m sure I will re­turn some­day”, and it is long past time for that re­turn.)

My fa­vorite book by Browne is his Pseudodoxia Epidemica, which is a com­pi­la­tion of stuff that peo­ple in 1646 be­lieved that Browne thought was prob­a­bly wrong. I wrote about that in some de­tail in 2008 al­though I did­n’t get around to pub­lish­ing it un­til 2020. And some­how the other three ar­ti­cles I was writ­ing about this have never seen the light of day. One is about his dis­cus­sion of whether John the Baptist ac­tu­ally ate lo­custs or whether they were lo­cust beans or some­thing else. Browne is firmly on the side of it be­ing ac­tual lo­custs, as am I. My un­pub­lished ar­ti­cle says:

Chester Brown’s ver­sion of the gospels makes it clear that John was a crazy old bug-gob­bler.

Chester Brown’s ver­sion of the gospels makes it clear that John was a crazy old bug-gob­bler.

Panels from Yummy Fur #17, page 15, by Chester Brown.

Also Sir Thomas comes up in con­nec­tion with whether snails have eyes in their horns — a rare ex­am­ple where he was wrong, and for a dumb rea­son:

If we con­cede they have two eyes, we must alse grant, they have no lesse than four… And there­fore if they have two eyes, they have also four, which will be mon­strous, and be­yond the af­fir­ma­tion of any.

If we con­cede they have two eyes, we must alse grant, they have no lesse than four… And there­fore if they have two eyes, they have also four, which will be mon­strous, and be­yond the af­fir­ma­tion of any.

Browne seems to be nop­ing out of the very idea of four-eyed snails, and there­fore that they must have none at all. In a later edi­tion of the book, he changed his mind, which is to his credit.

He had a thought­ful and well-in­formed opin­ion about whether Pythagoras for­bade his fol­low­ers from eat­ing beans, sup­pos­edly be­cause he thought they con­tained the souls of the dead. (Browne says the for­mer is true, but not the lat­ter.)

I have trou­ble con­nect­ing with the thinkers of the Middle Ages. Their think­ing seems to me to be fright­ened, so over­cau­tious, so cramped and cir­cum­scribed, I can’t read it with­out sad­ness for the way that me­dieval Christianity stran­gled the hu­man spirit for so long. But in the early Renaissance there is a flow­er­ing of a joy­fully brave will­ing­ness to try to un­der­stand the world, and to fol­low any in­quiry, no mat­ter how ex­trav­a­gant or ridicu­lous. The whole idea of God has trans­formed, changed from some­thing con­strict­ing to some­thing em­pow­er­ing. The world be­fore be­longed to God, and hu­mans were in it only grudg­ingly and on promise of good be­hav­ior. But when the Renaissance started, the world be­came a beau­ti­ful gift, in which hu­mans had been placed to honor God by ad­mir­ing and mar­veling at his cre­ation.

This ad­mi­ra­tion and mar­vel, the will­ing­ness to fol­low any path to un­der­stand­ing, is how I want to be about knowl­edge and how I hope I am. Reading Browne, I al­ways feel like he and I would have got­ten along well, and that that is one of the best parts of my­self.

Boccaccio’s Decameron

The story of the Decameron is this: It is 1348, and Florence is dev­as­tated by Black Plague. Nothing can be done, de­spair is every­where, and there are not enough left liv­ing to bury the dead. So ten young peo­ple, still healthy, de­cide to turn their backs on suf­fer­ing and quit town. They take pro­vi­sions and ser­vants, re­tire to the coun­try, and try to for­get the hor­rors they have seen. There they spend the time feast­ing, walk­ing in the gar­dens, play­ing chess, and, once a day, for ten days, they meet, choose a theme, and then each of them tells a story on the theme.

I ex­plained this once to a friend who said That sounds cool, when was it writ­ten?” I said In 1348!” It is one of the two great works of clas­si­cal Italian lit­er­a­ture, the other of course be­ing Dante. Dante is solidly me­dieval, hi­er­ar­chi­cal, doc­tri­naire, and ob­sessed with a God who is sup­pos­edly lov­ing but does­n’t seem to know how to show it. That was in 1308 or so, and then, only a few decades later, we have the Decameron which could not be more dif­fer­ent. It is about peo­ple, do­ing peo­ple things in the real world, eat­ing, drink­ing, singing, ar­gu­ing, and mak­ing love. God is pre­sent, but not op­pres­sive. He has sent a ter­ri­ble plague for who knows what rea­son, but rather than sub­mit to it the char­ac­ters of the Decameron try to take prac­ti­cal steps to make the best of it.

There is a story in the Decameron for every mood, usu­ally more than one. Some are sad, some ro­man­tic, some funny and sala­cious. Dioneo is ex­empt from fol­low­ing the daily theme and usu­ally has a story that is more or less dirty.

My fa­vorite story is prob­a­bly the one about the cross-dress­ing English princess, or per­haps the one about how young Caterina wanted to sleep on the bal­cony so that she could hear the nightin­gale, which I find very sweet. But the fun­ni­est one is about the abbess who is called out of her cell one night to be­rate a nun for hav­ing her lover stay over, and who does­n’t re­al­ize that in her hurry she has put her own lover’s trousers on her head in­stead of her wim­ple.

I have sev­eral dif­fer­ent Decamerons, but this copy is the Cormac Ó Cuilleanáin trans­la­tion, which has made sev­eral pre­vi­ous ap­pear­ances here:

On the word squillions”. Following up a chance en­counter in the Oxford English Dictionary is what led me to dis­cover the Decameron in the first place

The phrase two-bit huck­ster”

soup-guzzling pie-muncher”

soup-guzzling pie-muncher” again

There’s also an un­pub­lished blog ar­ti­cle invit­ing me to look into this pas­sage:

Messer Lotto Gualandi gave him a daugh­ter of his, Bartolomea by name, one of the fairest and hand­somest young ladies of Pisa — al­though most of the fe­males from that be­nighted town look like taran­tu­las.

Messer Lotto Gualandi gave him a daugh­ter of his, Bartolomea by name, one of the fairest and hand­somest young ladies of Pisa — al­though most of the fe­males from that be­nighted town look like taran­tu­las.

The J.M. Rigg trans­la­tion says spotted lizards”. This is closer to the orig­i­nal Italian, which is lucer­tole ver­minare, lit­er­ally small wormy lizards.

I have my doubts about the de­sir­abil­ity of liv­ing to be a thou­sand years old, but if I do de­cide to do it, one rea­son will cer­tainly be that I will need the time to learn Medieval Italian and trans­late the Decameron.

From Frege to Gödel, edited by van Heijenoort

This is a col­lec­tion of the most im­por­tant pa­pers in math­e­mat­i­cal logic from the time of Frege (who, I have writ­ten be­fore, was re­spon­si­ble for kick­ing the field of logic out of its me­dieval pe­riod into the mod­ern world) to Gödel (who spoiled every­thing).

In be­tween these van Hei­jenoort hits all the most im­por­tant ideas, start­ing with Frege’s ex­pla­na­tion of Begriffsschrift, which is wacky and weird and which did­n’t catch on ex­cept it kind of did and it still un­der­lies half of math­e­mat­i­cal logic and which is the pro­to­type for many of the sym­bols we still use. After this there is Russell’s tragic cor­re­spon­dence with Frege in which he pointed out, too late, that Frege’s foun­da­tional the­ory did­n’t work.

The book reprints Peano’s orig­i­nal de­scrip­tion of the Peano num­bers, per­haps the most suc­cess­ful sin­gle math­e­mat­i­cal the­ory of all time.

The book in­cludes Zermelo’s proof of Zermelo’s the­o­rem that every set can be well-or­dered, and Ackermann’s dis­cov­ery of Ackermann’s func­tion, which demon­strated the not every com­putable func­tion is prim­i­tive re­cur­sive.

The book has Russell on type the­ory and early work by Kolmogorov and Brouwer on the ori­gin of in­tu­ition­ism. (Heyting is miss­ing.)

Van Heijenoort has come up here when I wanted to quote from Schönfinkel’s pa­per about the SKI-calculus, Wiener’s pa­per in­vent­ing the or­dered pair, and im­plic­itly in prob­a­bly a dozen other math and logic ar­ti­cles here over the years.

The book is on my shelf be­cause I re­fer to it pretty of­ten, but also be­cause I can usu­ally find some­thing in­ter­est­ing just by thumb­ing through it. For ex­am­ple, these re­marks by Thoralf Skolem about the fu­til­ity of de­riv­ing in­duc­tion from set-the­o­retic foun­da­tions.

Bonus trivia: Van Heijenoort was the per­sonal sec­re­tary of Leon Trotsky, and while he was ac­com­pa­ny­ing Trotsky dur­ing the lat­ter’s ex­ile in Mexico, he was one of Frida Kahlo’s lovers.

Orbis Sensualium Pictis (English edi­tion), Johannes Comenius

I adore this book. My heart swells with love when I think of it.

I don’t have a blog ar­ti­cle about it and there is a story be­hind that. In 2018 I went to a con­fer­ence in Cleveland and my ho­tel was in a build­ing that had for­merly been the Cleveland Department of Education. It con­tains two big mu­rals, one de­pict­ing The Progress of Education”:

I planned to write a blog ar­ti­cle about these peo­ple. It’s clear who some of them are. For ex­am­ple, Moses is easy to rec­og­nize at lower right, be­cause of the glow­ing horns, and Confucius is next to him. Some peo­ple I was fa­mil­iar with once they were iden­ti­fied for me: the red-haired guy sec­ond from right in the back row is Friedrich Fröbel, who I knew; his gifts” are a fore­run­ner of the Montessori ma­te­ri­als.

But in do­ing the re­search I got to the bearded hat-wear­ing dude top­most on the right side and com­pletely fell off the bus, be­cause that is Johann Comenius who is fa­mous be­cause he wrote one of the most mar­velous and en­chant­ing books I’ve ever read, the Orbis Pictus.

I have to re­sist the temp­ta­tion to say too much, be­cause Orbis Pictus de­railed the ar­ti­cle about The Progress of Education”, it then de­railed its own ar­ti­cle which has been in progress for eight years, and if I let it it will de­rail this ar­ti­cle too, be­cause every time I pick up Orbis Pictus I for­get what­ever I was do­ing and I am lost in the pages with a happy and in­no­cent smile on my face.

I’m go­ing to pre­com­mit to writ­ing only one para­graph about this in­cred­i­ble book. It was the first il­lus­trated chil­dren’s book pub­lished in Europe, in 1658, and it was an im­me­di­ate hit, be­ing trans­lated from German into English the fol­low­ing year, then into French, Italian, and many other lan­guages. It swept the con­ti­nent be­cause every­one loved it.

Most of the book fol­lows this pat­tern: there will be an en­graved il­lus­tra­tion, de­pict­ing some as­pect of or­di­nary hu­man ac­tiv­ity, such as (I open it up to a ran­dom page) Tame Foul” (that is, fowl”):

Items of in­ter­est in the en­grav­ing are an­no­tated with num­bers, and the fac­ing page ex­plains the il­lus­tra­tion, one item at a time:

The Cock 1 (which croweth in a morn­ing), hath a comb, 2.

The Cock 1 (which croweth in a morn­ing), hath a comb, 2.

In a sec­ond col­umn to the right of this is the same text, but in Latin, so that while the reader is learn­ing about tame fowl, they are also learn­ing Latin:

Gallus 1. (qui manè can­tat) ha­bet Cristam, 2.

Gallus 1. (qui manè can­tat) ha­bet Cristam, 2.

The prose is limpid, gen­tle, pithy, and di­rect. It hits the im­por­tant points of in­ter­est, in­vites ques­tions, and ends be­fore any­one can get bored. There are pages on anatomy, butch­ery, feast­ing, wine­mak­ing, var­i­ous prin­ci­pal virtues, fam­ily trees, cities, buri­als, ships, wells, horol­ogy, am­phib­ians.

Now I will re­luc­tantly put it down, rather than leav­ing this ar­ti­cle un­fin­ished as I have so many be­fore.

The Bible (New International Version, large print)

This of course is the cor­ner­stone of Western cul­ture and no well-ed­u­cated per­son can be with­out a knowl­edge of what is in it. It is full of great wis­dom and great sto­ries, and also cru­elty, evil lies, and re­minders that the world now is in many ways bet­ter than it was be­cause peo­ple are bet­ter.

I would like to un­der­stand the world I live in, and there is no way to un­der­stand 21st-century America with­out un­der­stand­ing the Bible.

The NIV is not the most po­et­i­cal trans­la­tion, but it is clear, mod­ern, and ac­cu­rate. (I got it on the rec­om­men­da­tion of Sterling Hanenkampf. Thanks, Sterling!) In for­mer times I had a col­lec­tion of Bibles but this is the only one that re­mains. I even got rid of the old King James that be­longed to my mother, since of­fice space is pre­cious and I have had a dig­i­tal copy on my com­puter since the early 1990s.

I find that most of my ar­ti­cles men­tion­ing the Bible are un­pub­lished for some rea­son. It comes up a bit in con­nec­tion with Ploni Almoni, and in pass­ing in many other places.

One of the un­fin­ished ar­ti­cles is a se­ries of notes on the theme of Jesus’s ad­mo­ni­tion Do not put the Lord your God to the test” (Matthew 4:7) and its re­la­tion­ship to a lot of other things like light­ning rods, Christian Science (not Christian sci­ence), how Larry Wall be­came a com­puter pro­gram­mer, Pikuach ne­fesh, and the story of the old lady who re­fused to evac­u­ate from her house dur­ing a flood. It’ll be epic if I ever fin­ish it, but I prob­a­bly won’t.

Another in­com­plete one is about the in­cred­i­ble story of Samson and Delilah:

She asks him flat out:

[Judges 16:6] Tell me the se­cret of your great strength, and how you can be tied up and sub­dued.

Instead of just telling her to fuck off, Samson lies:

[16:7] If any­one ties me with seven fresh bow­strings that have not been dried, I’ll be­come as weak as any other man.

The Philistines bring her bow­strings and she tries it that night, but Samson snaps the bow­strings as eas­ily as a piece of string snaps when it comes close to a flame. …

Then it goes as be­fore! He tells her a dif­fer­ent lie, know­ing full well that she will be­tray him, and she does be­tray him, and he makes a fool of her again! (16:11 – 12)

Okay, that was fun. Let’s do it again! (16:13 – 14)

She asks him flat out:

[Judges 16:6] Tell me the se­cret of your great strength, and how you can be tied up and sub­dued.

[Judges 16:6] Tell me the se­cret of your great strength, and how you can be tied up and sub­dued.

Instead of just telling her to fuck off, Samson lies:

[16:7] If any­one ties me with seven fresh bow­strings that have not been dried, I’ll be­come as weak as any other man.

[16:7] If any­one ties me with seven fresh bow­strings that have not been dried, I’ll be­come as weak as any other man.

The Philistines bring her bow­strings and she tries it that night, but Samson snaps the bow­strings as eas­ily as a piece of string snaps when it comes close to a flame. …

Then it goes as be­fore! He tells her a dif­fer­ent lie, know­ing full well that she will be­tray him, and she does be­tray him, and he makes a fool of her again! (16:11 – 12)

Okay, that was fun. Let’s do it again! (16:13 – 14)

After sev­eral rep­e­ti­tions of this, Samson de­cides that be­ing shaved, blinded and crushed will be less ex­as­per­at­ing than lis­ten­ing to any more of Delilah’s nag­ging.

I read once that the whole point of the book of Judges is that the peo­ple in it are all ter­ri­ble, they are all far from the path of right­eous­ness, and so you def­i­nitely should­n’t act like them. I don’t know if that in­ter­pre­ta­tion is cor­rect, but it is cer­tainly true that the peo­ple in it are all ter­ri­ble.

In Australia, a Home Battery Boom Has Helped Cut Wholesale Power Prices in Half

e360.yale.edu

NSW Climate and Energy Action

A lit­tle more than one year ago, Australia rolled out a pro­gram to heav­ily sub­si­dize home bat­ter­ies, part of a larger ef­fort to make use of the huge vol­umes of so­lar en­ergy that were go­ing to waste. On Friday, of­fi­cials an­nounced that more than 500,000 bat­ter­ies had been in­stalled un­der the plan, help­ing to slash whole­sale power prices roughly in half.

Energy Minister Chris Bowen said that Australia now has more home bat­ter­ies than the United States, which has a pop­u­la­tion 12 times larger. This is a story of global sig­nif­i­cance that Australian house­holds have achieved,” Bowen said in a press con­fer­ence.

Australia is the world leader in rooftop so­lar, with pan­els in­stalled on more than one in three house­holds, the high­est rate of adop­tion glob­ally. But abun­dant so­lar power has cre­ated a new dilemma as the grid faces a surge of elec­tric­ity from con­nected rooftop ar­rays. Power prices plunge. Centralized power plants are forced of­fline, threat­en­ing grid sta­bil­ity. And much of that so­lar power goes to waste.

The gov­ern­ment has moved to make use of this sur­plus so­lar en­ergy, in­clud­ing by of­fer­ing free power in the early af­ter­noon to home­own­ers in Queensland, New South Wales, and South Australia, re­gard­less of whether they have so­lar pan­els on their roof or not. The goal is to spur more con­sumers to run ap­pli­ances or charge elec­tric ve­hi­cles dur­ing this win­dow.

With its home bat­tery sub­sidy pro­gram, launched in July 2025, the gov­ern­ment is aim­ing to help house­holds use more so­lar en­ergy by pro­vid­ing a 30 per­cent dis­count on res­i­den­tial bat­tery sys­tems con­nected to so­lar ar­rays.

The sub­sidy pro­gram has spurred a boom in in­stal­la­tions. Australia is on track to more than dou­ble its home bat­tery ca­pac­ity this year, Bloomberg re­ports. The pro­gram has also been a boon to the grid. By re­ly­ing on bat­ter­ies in the early evening, when de­mand peaks, home­own­ers are re­duc­ing the need for util­i­ties to fire up ad­di­tional power plants dur­ing those hours, which is help­ing to lower costs for other ratepay­ers, of­fi­cials say.

The sub­sidy pro­gram has been the ma­jor fac­tor in the whole­sale price of en­ergy falling in Australia by 47 per­cent in the last 12 months,” Bowen said. Australia is one of the very, very few coun­tries in the world which is re­duc­ing whole­sale prices in the midst of a global en­ergy cri­sis.”

ALSO ON YALE E360

A Home Battery Revolution Is Reshaping the Power Grid

AI by Hand ✍️ | Prof. Tom Yeh | Substack

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Math, Algorithms, Architectures, by hand

By Prof. Tom Yeh

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Unattended Remote Access on Wayland with RustDesk

rustdesk.com

Wayland sup­port has been one of the harder parts of Linux re­mote desk­top.

RustDesk can now pro­vide true un­at­tended ac­cess on Wayland, with­out re­quir­ing some­one at the re­mote ma­chine to ap­prove every ses­sion. Multi-monitor se­tups are sup­ported as well.

After the ini­tial setup, you can con­nect even when no one is at the re­mote ma­chine — in­clud­ing from the lo­gin screen af­ter a re­boot.

For now, we are re­leas­ing this as a sep­a­rate pre­view build for x86_64 Debian/Ubuntu-based sys­tems:

Download the Wayland un­at­tended ac­cess build

Wayland sup­port is still lim­ited in sev­eral ma­jor re­mote desk­top prod­ucts. AnyDesk cur­rently re­quires Xorg for in­com­ing Linux ses­sions, while TeamViewer still de­scribes Wayland sup­port as ex­per­i­men­tal for com­mon desk­top en­vi­ron­ments.

We would like to get more real-world test­ing be­fore mak­ing this the de­fault.

Once the im­ple­men­ta­tion is sta­ble, we plan to bring un­at­tended Wayland ac­cess to more Linux dis­tri­b­u­tions, in­clud­ing Fedora and Arch Linux, and even­tu­ally in­clude it in the stan­dard RustDesk re­leases.

If you use Wayland, es­pe­cially with mul­ti­ple mon­i­tors, please give the pre­view build a try and let us know what works—and what does­n’t.

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