Today, we’re in­tro­duc­ing Muse Glimmer, the next model from Meta Superintelligence Labs, and open sourc­ing the model weights un­der a per­mis­sive Apache 2.0 li­cense.

Muse Glimmer is a 30-billion-parameter model op­ti­mized for al­ways-on lo­cal agent work­flows. It’s small enough to run on a Mac or PC with a sin­gle con­sumer GPU, en­abling use cases that range from lo­cal agents and func­tion call­ing, to lo­cal cod­ing, and LLM-as-a-judge eval­u­a­tion. Muse Glimmer de­liv­ers strong per­for­mance on key agen­tic use cases and bench­marks com­pared with lead­ing mod­els in its size cat­e­gory.

Foundation mod­els have achieved re­mark­able ca­pa­bil­i­ties across rea­son­ing, code gen­er­a­tion, and tool use — yet most de­ploy­ments still de­pend on cloud in­fra­struc­ture and net­work ac­cess. Running mod­els lo­cally en­ables you to use AI any­where, any­time, with or with­out an in­ter­net con­nec­tion. This is in­creas­ingly vi­able: the open source com­mu­nity has shown that smaller mod­els, when trained ef­fec­tively, can ap­proach fron­tier-level per­for­mance on tar­geted tasks. Muse Glimmer is op­ti­mized for these lo­cal use cases.

Keeping with our long tra­di­tion of shar­ing fun­da­men­tal AI re­search, we’re re­leas­ing Muse Glimmer open weights to­day on Hugging Face, along with de­vel­oper doc­u­men­ta­tion to help you start build­ing and run­ning your own agents. Muse Glimmer is built to work with the tools de­vel­op­ers al­ready use. Optimized in­te­gra­tions on llama.cpp, MLX, and ExecuTorch will land in the com­ing days, so you can go from down­load to work­ing agent in min­utes.

How We Trained Muse Glimmer

An agent that man­ages your sched­ule, drafts your mes­sages, or­ga­nizes your files, and learns how you work needs deep ac­cess to per­sonal con­text. It also needs sev­eral ca­pa­bil­i­ties work­ing in con­cert: long-hori­zon ex­e­cu­tion, pre­cise tool call­ing, mul­ti­modal un­der­stand­ing, long-con­text mem­ory, and in­struc­tion fol­low­ing.

We de­signed Muse Glimmer to bal­ance ca­pa­bil­ity against the mem­ory and com­pute con­straints of lo­cal hard­ware. This re­quired a com­pact ar­chi­tec­ture, a novel dis­til­la­tion recipe that trans­fers agen­tic rea­son­ing from a much larger teacher model, and in­fer­ence op­ti­miza­tions — in­clud­ing quan­ti­za­tion — to meet la­tency ex­pec­ta­tions. We achieved this in the fol­low­ing phases:

Pre-Training. We trained Muse Glimmer on Muse Spark’s out­puts us­ing logit dis­til­la­tion, lever­ag­ing a sim­i­lar data mix as the teacher.

Mid-Training. We trained the model on longer-con­text, more agent-heavy data with richer rea­son­ing traces, along­side or­ganic data.

Post-Training. We com­bined su­per­vised fine-tun­ing with a mix of on-pol­icy dis­til­la­tion and re­in­force­ment learn­ing across gen­eral, rea­son­ing, cod­ing, and agen­tic do­mains.

Muse Glimmer was eval­u­ated un­der the stan­dards set out in Meta’s Advanced AI Scaling Framework and as­sessed for open-weight re­lease across all rel­e­vant cat­e­gories.

Built for Agents: What Muse Glimmer Can Do

Building ef­fec­tive agents re­quires key ca­pa­bil­i­ties work­ing to­gether to achieve the user’s goals. Muse Glimmer is trained and eval­u­ated across each of the fol­low­ing:

End-to-end Agentic Task Completion. Muse Glimmer achieves strong suc­cess rates on full-task bench­marks in­clud­ing DeepSearch QA, MCP-Atlas, 𝛕-Bench and SWE-Bench, which mea­sure its abil­ity to work within scaf­folds, write and de­bug code, and re­solve multi-turn re­quests from start to fin­ish.

Reliable Tool Use. The model han­dles a wide range of func­tion calls, in­vok­ing tools with pre­cise schemas through­out ex­tended work­flows.

Multi-Step Reasoning. Muse Glimmer chains rea­son­ing over long hori­zons, sus­tain­ing co­her­ent plans across com­plex, ex­tended work­flows.

Failure Recovery. When a tool call fails or re­turns an un­ex­pected re­sult, the model is trained to di­ag­nose the er­ror and retry rather than halt.

Multimodal Input and Reasoning. Through a ded­i­cated per­cep­tion en­coder, the model ac­cepts in­ter­leaved text and im­ages. This en­ables agents to in­ter­pret screen­shots, charts, and doc­u­ments along­side con­ver­sa­tion.

Scaffold Compatibility. Muse Glimmer works across OpenClaw and other agen­tic or­ches­tra­tion pat­terns.

Controllable Effort. Muse Glimmer sup­ports dif­fer­ent rea­son­ing strengths to se­lect the right bal­ance be­tween qual­ity and speed.

Multilingual. Muse Glimmer is trained on data from more than 100 lan­guages.

Performance

We eval­u­ated Muse Glimmer across a broad range of bench­marks to as­sess the di­verse ca­pa­bil­i­ties re­quired for ef­fec­tive au­tonomous agent be­hav­ior. Compared with Gemma4 – 31B and Qwen3.6 – 27B, Muse Glimmer per­forms strongly for its size class on sev­eral widely used LLM bench­marks.

For more de­tail about our eval­u­a­tions, see our re­port.

Optimized for Local Deployments

A lo­cal agent is truly use­ful if it’s fast enough to feel re­spon­sive. An agent that takes min­utes to re­ply or plan its next step breaks the flow of real work. We ap­plied two op­ti­miza­tions to make Muse Glimmer run at prac­ti­cal speeds on con­sumer hard­ware with­out sac­ri­fic­ing qual­ity.

Fitting the Model on Your Device.

At full pre­ci­sion, a 30-billion pa­ra­me­ter model would re­quire over 55 GB of mem­ory — far more than any con­sumer GPU of­fers. We use quan­ti­za­tion tech­niques to com­press the mod­el’s weights to ap­prox­i­mately 4-bit pre­ci­sion, shrink­ing the lan­guage model to un­der 20 GB. This leaves enough head­room for the mod­el’s work­ing mem­ory (its “KV cache”), the per­cep­tion en­coder for im­age un­der­stand­ing, and the spec­u­la­tive de­cod­ing drafter to run si­mul­ta­ne­ously within a 24 GB or 32 GB en­ve­lope. We val­i­dated that this com­pres­sion in­tro­duces min­i­mal to no degra­da­tion on agen­tic tasks.

Faster Generation Through Speculative Decoding.

Language mod­els nor­mally gen­er­ate text one to­ken at a time, which can feel slow dur­ing long rea­son­ing chains or multi-step tool calls. Muse Glimmer ships with a light­weight “drafter” model based on DFlash — a small com­pan­ion net­work that pro­poses en­tire blocks of to­kens at once. The main model then ver­i­fies these pro­pos­als in par­al­lel, ac­cept­ing cor­rect to­kens and cor­rect­ing wrong ones. This tech­nique lets Muse Glimmer gen­er­ate text sig­nif­i­cantly faster than stan­dard to­ken-by-to­ken gen­er­a­tion while pro­duc­ing iden­ti­cal out­put qual­ity. We pro­vide quan­tized drafter ver­sions to in­cur a smaller mem­ory over­head in the re­lease.

The Result:

We mea­sure the speed of our K-Quant-17GB model along­side the quan­tized DFlash drafter on MacBook M4-Max, M5-Max and on a RTX-5090. The model is fast enough for fluid con­ver­sa­tion and real-time agent in­ter­ac­tion, all run­ning en­tirely on your de­vice.

Get Started With Muse Glimmer Today

Muse Glimmer is avail­able now, and you can down­load the weights on Hugging Face. In the com­ing days, run it lo­cally through part­ners like Ollama, LM Studio, and Unsloth, de­ploy it with edge frame­works in­clud­ing llama.cpp, ExecuTorch, and MLX, serve it at scale with vLLM and SGLang, or get started quickly through part­ners like Together AI, Fireworks AI, and OpenRouter. You can even cus­tomize it for your use case by lever­ag­ing PyTorch’s TorchTitan train­ing fea­ture to tune the model fur­ther.

We’re also work­ing with our part­ners in­clud­ing AMD, Arm, Dell, Intel, and NVIDIA to op­ti­mize per­for­mance across de­vices. In ad­di­tion, we’re re­leas­ing doc­u­men­ta­tion so de­vel­op­ers have the re­sources they need to get started and build re­spon­si­bly with Muse Glimmer. This in­cludes guid­ance on set­ting up cus­tom scaf­folds, so it’s even eas­ier to start build­ing and de­ploy­ing per­sonal agents on day one. You can learn more and find re­sources to build on Meta’s AI Developer Center.

This work builds on Meta’s long track record of open AI re­search, ex­tend­ing it into agen­tic AI and giv­ing de­vel­op­ers ac­cess to lo­cal agen­tic ca­pa­bil­i­ties. As al­ways, we wel­come feed­back from the com­mu­nity and can’t wait to see what de­vel­op­ers build with this open weights model.

Download the Model on Hugging Face Developer Documentation

I re­ported this on January 28th, 2026. It is now July 2026. Six months later. The Firestore data­base is still wide open. The CTO never re­sponded. I guess my emails were too long and they did­n’t view them.

What is tl;dv?

tl;dv (Too Long; Didn’t View) is an AI meet­ing record­ing plat­form. It drops a bot into your Google Meet, Zoom, or Teams call, records every­thing, tran­scribes it, and gen­er­ates sum­maries with AI. Over 2 mil­lion users. Backed by in­vestors. Endorsed by half of LinkedIn’s sales in­flu­encer com­mu­nity.

They store your sales calls, job in­ter­views, per­for­mance re­views, in­ter­nal strat­egy ses­sions. The kind of con­tent where some­one says “this call is be­ing recorded” and every­one ner­vously laughs and then shares trade se­crets for 45 min­utes.

The Vulnerability

When you sign up for tl;dv, the plat­form au­then­ti­cates you with a JWT and ex­changes it for a Firebase to­ken via gw.tldv.io/​v1/​users/​fire­base/​to­ken. That to­ken lets you query their Firestore data­base at pro­jects/​lmi-store/​data­bases/(​de­fault).

The meet­ings col­lec­tion has no ten­ant iso­la­tion. Any au­then­ti­cated tl;dv user can query every meet­ing across every ac­count on the plat­form. Each meet­ing record hands you the cre­ator’s email ad­dress, the con­fer­ence ID (which is a join­able Google Meet or Teams room), the provider, the record­ing sta­tus, and time­stamps.

For meet­ings in record­ing sta­tus, that con­fer­ence ID is a live, ac­tive call. You can watch the col­lec­tion in real time, see a meet­ing start record­ing, grab the ID, and walk into some­one’s call un­in­vited. At any given time there are roughly 1,000 meet­ings with sta­tus: record­ing sit­ting in the col­lec­tion. A thou­sand live calls with ex­posed con­fer­ence IDs. An at­tacker with a bot could join all of them si­mul­ta­ne­ously.

I Joined 2 Meetings

I did it.

Grabbed a con­fer­ence ID from Firestore and joined a live Google Meet be­long­ing to the Malaysian Ministry of Education. A lady was pre­sent­ing to over 157 par­tic­i­pants. The tl;dv bot was al­ready in the par­tic­i­pant list. I was in the same call. Nobody in­vited me. The Firestore data­base did.

I also joined a call where stu­dents from a ma­jor US uni­ver­sity were build­ing a startup app. 21 peo­ple in the call. They were screen-shar­ing their en­tire pro­ject, dis­cussing pro­to­types, and, I kid you not, talk­ing about how they needed to add client-side val­i­da­tion for .edu email ad­dresses. They were also set­ting up Supabase live on screen, and all I could think was “please set up RLS poli­cies” be­cause most peo­ple don’t, and then you end up like tl;dv.

I wanted to say some­thing so badly. “Hey, you might want server-side val­i­da­tion too.” But this was a proof of con­cept, not a con­sul­ta­tion.

The Scale

I queried the Firestore meet­ings col­lec­tion and saw there were 181,874 meet­ing records be­long­ing to 84,312 unique users across 35,003 email do­mains.

Government meet­ings from 23 coun­tries: Brazil, Colombia, Peru, Ukraine, El Salvador, the Philippines, Chile, Indonesia, Mexico, the United States, Qatar, Malaysia, Uzbekistan, Sri Lanka, Haiti, South Africa, Jamaica, Honduras, Argentina, Thailand, Japan, Israel, and Belize. All .gov do­mains. Government em­ploy­ees record­ing calls on a plat­form that lets any free-tier user enu­mer­ate the whole thing.

University meet­ings from Berkeley, the University of Tokyo, De La Salle, Universidad Nacional de Colombia. Dozens of .edu and .ac do­mains.

Corporate meet­ings from all 35,000 re­main­ing do­mains. Mitsui-Soko (484 meet­ings across four re­gional of­fices), Mitsui Fudosan, HubSpot, Confluent, Mekari, AnyMind Group. Every com­pany that ever used tl;dv had their meet­ing meta­data in the same un­pro­tected col­lec­tion.

Peak month was July 2025 with 43,209 meet­ings. Busiest time slot: Wednesday at 2pm UTC, 7,804 meet­ings. Hump-day standup hour.

But Wait, There’s More

I wanted to know how much ac­tual con­tent was ac­ces­si­ble too, by de­fault meet­ings are pri­vate (Meaning you cant watch the video or see the tran­script), so I scraped 27,334 meet­ing IDs and checked which ones were pub­lic. Over 1,000 were. 715 in­vi­tee emails ex­posed across 228 do­mains.

Highlights: a Brazilian gov­ern­ment con­ser­va­tion meet­ing (PACTO Mata Atlântica) with par­tic­i­pants from WWF, The Nature Conservancy, Conservation International, WRI, and the São Paulo state gov­ern­ment. Meetings from Ukraine’s Ministry of Digital Transformation. A HubSpot sales call. Sessions in­volv­ing Universidad Nacional de Colombia and Chile’s Cámara Verde.

The Pasta Infrastructure

tl;dv names their mi­croser­vices af­ter pasta. A sub­do­main scan re­veals cap­pellini, car­bonara, fusilli, pasta, penne, put­tanesca-v0, and ravi­oli, all un­der tldv.io. An en­tire Italian restau­rant worth of Express servers.

Too Long; Didn’t Score

While ex­plor­ing their sub­do­mains I found https://​world­cup.tldv.io. A FIFA World Cup 2026 vibecoded pre­dic­tion game built on Base44 for tl;dv em­ploy­ees. It’s called “World Cup Pick’em” and their in­ter­nal squad is named “Too Long; Didn’t Score.” Cute.

The Player en­tity API has zero au­then­ti­ca­tion. GET /api/entities/Player re­turns every player record with­out a ses­sion cookie. 43 play­ers. 19 @tldv.io em­ploy­ees with full names and cor­po­rate emails.

Raphael Allstadt, my dis­clo­sure con­tact who gave vague re­as­sur­ances and then went quiet, came in 2nd place with 298 points. His per­sonal Gmail was also in the API re­sponse. Player #5 on the global leader­board is “Super Duper CEO.” I’ll let you guess who that is.

The Prediction and Fixture en­ti­ties are also wide open. A com­pany that records mil­lions of peo­ple’s meet­ings vibecoded an in­ter­nal fun app that leaks their own em­ployee di­rec­tory. The irony is al dente.

Disclosure

On January 28th I mes­saged Raphael Allstadt on LinkedIn and told him I’d found a huge vul­ner­a­bil­ity that leaks user data. He re­sponded within min­utes: “thank you! can you re­port it to our CTO and we will look at it im­me­di­ately?” I sent the email. He said “thank you!” I asked about a re­ward. “My CTO will come back to you,” he said.

The CTO never came back to me.

January 29th: “your cto hasnt reached out yet btw and its not fixed.” January 30th, Raphael: “I am sure the team is re­view­ing it very very soon ❤️” February 14th: “havent got an email and the vul­ner­a­bil­ity stilll works.” Raphael: “He’ll come back ☺️” I told him to maybe fix the vul­ner­a­bil­ity and not leave cus­tomers ex­posed. February 19th: “We’re on it. It needs some time, but rest as­sured we’re fol­low­ing through. For fur­ther com­mu­ni­ca­tion, i’ll rec­om­mend reach­ing out to our CTO.”

The CTO who never re­sponded. That CTO.

March 6th: “still not fixed.” Seen by Raphael at 5:42 PM. No re­ply.

July 22nd: “still not fixed…” No re­ply.

Their se­cu­rity page is a tro­phy case. SOC2 com­pli­ant. GDPR com­pli­ant. EU AI Act com­pli­ant. Hosted in the EU. AES-256 en­cryp­tion. A founder com­mit­ment video. Six com­pli­ance badges lined up in a row. Buried at the bot­tom, a sin­gle line: “If you have dis­cov­ered a pri­vacy or se­cu­rity is­sue that we should ad­dress, please al­ways let us know at [email protected]. Our se­cu­rity team will re­spond within 24 hours.” I emailed the CTO di­rectly. Six months. No re­sponse. Their Firestore data­base has bet­ter up­time than their in­box.

To tl;dv

Your plat­form records peo­ple’s most sen­si­tive con­ver­sa­tions. Job in­ter­views. Sales ne­go­ti­a­tions. Government brief­ings. Your users trusted you with con­tent they ex­plic­itly con­sented to record.

Fix the Firestore ten­ant iso­la­tion. Firestore se­cu­rity rules ex­ist for this. You al­ready do it cor­rectly for every other col­lec­tion (users, chats, tran­scripts, clips, record­ings, videos, notes, teams, or­ga­ni­za­tions all re­turn 403). You just for­got meet­ings.

Put auth on the World Cup app or take it down. Your em­ployee di­rec­tory is one GET re­quest away.

Respond to se­cu­rity re­searchers. Especially when they’re telling you that every meet­ing on your plat­form is queryable by any­one with a free ac­count.

So long and thanks for all the pasta :3

For help please visit help.ft.com. We apol­o­gise for any in­con­ve­nience.

The fol­low­ing in­for­ma­tion can help our sup­port team to re­solve this is­sue.

An Effort in­ves­ti­ga­tion has iden­ti­fied a co­or­di­nated op­er­a­tion to in­flu­ence American law­mak­ers by five for­eign non-gov­ern­ment or­ga­ni­za­tions and their US af­fil­i­ates. These NGOs have con­verged upon a uni­fied strat­egy: use the rhetoric of ‘child safe­ty’ to ad­vo­cate for dig­i­tal ID laws that would pre­vent adults from us­ing the in­ter­net anony­mously.

In Britain, they suc­ceeded in pass­ing those laws. They now form part of a sys­tem which sur­veils, ar­rests, and jails po­lit­i­cal dis­si­dents. Digital ID laws are a key com­po­nent used to strip Brits of in­ter­net anonymity, an oth­er­wise ef­fec­tive tech­no­log­i­cal coun­ter­mea­sure against au­thor­i­tar­i­an­ism.

British NGOs are now repli­cat­ing their play­book in the United States of America, at­tempt­ing to pass a patch­work of dig­i­tal ID laws in 21 states and the US Congress.

One British NGO, 5Rights, reg­is­tered un­der the Foreign Agents Registration Act, but has failed to file crit­i­cal in­for­ma­tion re­lated to its for­eign lead­er­ship. All five for­eign NGOs have in­flu­enced American pol­icy, ei­ther di­rectly or us­ing American prox­ies with sig­nif­i­cant for­eign man­age­ment.

The Center for Countering Digital Hate (CCDH) was founded by British Labour con­sul­tants Imran Ahmed and Morgan McSweeney2.

CCDH has al­ready been in­volved in cen­sor­ship scan­dals in the US and UK. They led a boy­cott cam­paign against X im­me­di­ately af­ter Elon Musk’s ac­qui­si­tion, spon­sored ma­jor cen­sor­ship leg­is­la­tion in the UK, and fre­quently hosted events in which US and UK gov­ern­ment of­fi­cials ad­vo­cated for cen­sor­ship.3

America First Legal, a law firm con­nected with the Trump ad­min­is­tra­tion, ac­cused CCDH of vi­o­lat­ing the Foreign Agents Registration Act (FARA) in 2024. The US Department of Justice has not pub­licly an­nounced any in­ves­ti­ga­tion into CCDH, and did not re­spond to our re­quest for com­ment.

Effort in­de­pen­dently cor­rob­o­rated the core claims made in this let­ter about the na­tion­al­i­ties and res­i­dences of CCDH lead­er­ship — that Imran Ahmed is CEO of both or­ga­ni­za­tions and is a British na­tional, that Clark and Brookes are shared di­rec­tors of both US and UK en­ti­ties, and that McNeill was a board mem­ber un­til July 11, 2024.

CCDH sup­ported bills with the ex­plicit in­tent of im­port­ing British laws. A joint state­ment by Buffy Wicks, the lead au­thor of AB 2273, Jordan Cunningham, an­other AB 2273 au­thor, and 5Rights Foundation states, “The Bill is prac­ti­ca­ble and re­al­is­tic, draw­ing as it does on the UK’s Age Appropriate Design Code (AADC).”

AB 2273 was co-de­signed by 5Rights Foundation, a for­eign prin­ci­pal that paid to lobby for AB 2273, ac­cord­ing to their own Foreign Agents Registration Act fil­ing.

5Rights is the lead­ing NGO pro­mot­ing the British Age Appropriate Design Code / AB 2273 model across American states. 5Rights en­gaged on 42 bills across 18 states, 11 of which have be­come law.

5Rights paid Capitol Connection $50,000 to lobby in the California Legislature from May to September 2022. They did not dis­close this lob­by­ing on be­half of a for­eign agent un­til 2024, over a year af­ter the bill they lob­bied for passed.

In their dis­clo­sure, Capitol Connection de­nied that 5Rights was su­per­vised, owned, di­rected, con­trolled, fi­nanced, or sub­si­dized by a for­eign gov­ern­ment, for­eign po­lit­i­cal party, or other for­eign prin­ci­pal. They did not sub­mit any in­for­ma­tion for ques­tion 12, which could have clar­i­fied what level of con­trol Kidron, their founder and then-di­rec­tor, had over 5Rights.

5Rights is a British non­profit founded by Baroness Beeban Tania Kidron, who sits in the British House of Lords, the up­per cham­ber of the British Parliament.

Despite the British gov­ern­ment us­ing these laws to tar­get po­lit­i­cal dis­si­dents, Baroness Kidron and 5Rights now ad­vo­cate for VPN bans, a change that would add the UK to a small num­ber of au­thor­i­tar­ian regimes — Russia, China, and North Korea — that ban VPNs.4

A cen­tral node in that British cen­sor­ship ecosys­tem is the Institute for Strategic Dialogue. They have con­tracted with the US State Department, European Union, and sev­eral UK min­istries for a to­tal of over $17M US dol­lars.5

Government fund­ing records by ju­ris­dic­tion

United States

$11.21m

European Union

$5.54m

United Kingdom

$0.72m

ISD’s con­tracts ex­plic­itly de­scribe a mis­sion to con­trol in­ter­net speech. In the re­ports and pol­icy rec­om­men­da­tions pro­duced for these con­tracts,6 ISD con­flates po­lit­i­cal dis­sent with “misinformation”, “extremism”, “hate speech”, or even “violent ex­trem­ism”, both jus­ti­fy­ing and en­abling cen­sor­ship by gov­ern­ments for­eign and do­mes­tic.

ISD has lob­bied fed­er­ally in the United States.7 Their re­port states that “a ma­jor­ity of Board mem­bers sit on both boards so that de­ci­sions can be taken col­lec­tively.”

Reset Tech is yet an­other global con­sor­tium with over­lap­ping lead­er­ship. Reset de­scribes its own gov­er­nance as fol­lows: “We are gov­erned by a Board of Directors that over­sees our global op­er­a­tions.”8

Reset Tech Action, Reset Tech’s US 501(c)4 af­fil­i­ate, spent $1,352,800 lob­by­ing Congress and state leg­is­la­tures from 2024 through Q2 2026. Effort found sig­nif­i­cant over­lap be­tween Reset Tech and 5Rights: 4 of 6 bills it lob­bied for are bills 5Rights en­gaged with, in­clud­ing AB 2273, the bill 5Rights also lob­bied for.9

Reset Tech is also tied to ISD through their EU af­fil­i­ate, Reset Tech GmbH, which re­ceived €4.9M from the EU gov­ern­ment as part of the con­sor­tium led by ISD.

In the­ory, there may be age ver­i­fi­ca­tion laws which do not con­tribute to au­thor­i­tar­ian con­trol of speech. However, when for­eign prin­ci­pals are lob­by­ing for age ver­i­fi­ca­tion law, dur­ing a time when those laws are be­ing used to sup­press po­lit­i­cal speech in their home coun­tries, it can­not be a sur­prise if those laws are used for the same pur­poses in America.

Footnotes

Effort mapped en­gage­ments based on pub­lic state­ments, records, and news cov­er­age. The map is a lower bound of en­gage­ments the Effort team was able to ver­ify, but the list of en­gage­ments might be in­com­plete.

Effort mapped en­gage­ments based on pub­lic state­ments, records, and news cov­er­age. The map is a lower bound of en­gage­ments the Effort team was able to ver­ify, but the list of en­gage­ments might be in­com­plete.

Morgan McSweeney is iden­ti­fied as a founder by The Times and the New Statesman in cov­er­age of the launch. CCDH’s web­site con­tin­ues to iden­tify Imran Ahmed as its founder and CEO.

Morgan McSweeney is iden­ti­fied as a founder by The Times and the New Statesman in cov­er­age of the launch. CCDH’s web­site con­tin­ues to iden­tify Imran Ahmed as its founder and CEO.

CCDH-supported UK cen­sor­ship leg­is­la­tion:

Draft Online Safety Bill Online Safety Bill Online Safety Act 2023

X boy­cott cam­paign and cen­sor­ship speeches

CCDH-supported UK cen­sor­ship leg­is­la­tion:

Draft Online Safety Bill

Online Safety Bill

Online Safety Act 2023

X boy­cott cam­paign and cen­sor­ship speeches

In an ar­ti­cle ti­tled “The VPN loop­hole in the fight to pro­tect chil­dren,” Kidron called so­cial me­dia bans with­out VPN bans “for show and head­lines, not for chil­dren.” This rhetoric is de­ployed for a VPN-ban pol­icy which would pre­dom­i­nantly af­fect adults.

In an ar­ti­cle ti­tled “The VPN loop­hole in the fight to pro­tect chil­dren,” Kidron called so­cial me­dia bans with­out VPN bans “for show and head­lines, not for chil­dren.” This rhetoric is de­ployed for a VPN-ban pol­icy which would pre­dom­i­nantly af­fect adults.

We use con­ver­sion rates for July 27, 2026: €1 = $1.1389 and €1 = £0.85524. It ex­cludes the £635,204 ag­gre­gate for three un­named gov­ern­ment con­tracts and the £2,322,079 un­al­lo­cated gov­ern­ment-and-mul­ti­lat­eral re­main­der.

PeriodGovernment coun­ter­par­tyRe­cip­i­ent ISD en­ti­ty­Con­tract / award / spend recor­dReported amoun­tRecord

2024Government coun­ter­par­ties not namedIn­sti­tute for Strategic Dialogue (UK)Three gov­ern­ment con­tracts re­ported in the an­nual-re­turn sum­mary£635,204Char­ity Commission record 2024Multiple gov­ern­ments and mul­ti­lat­er­alsIn­sti­tute for Strategic Dialogue (UK)Accounts-listed fun­ders: US State Department; European Union; UK FCDO, DCMS and Home Office; Australian DFAT; Danish MFA; New Zealand Department of Internal Affairs; Public Safety Canada; Canadian Privy Council; UNESCO; German Government; and Ministerium der Finanzen des LandesNot sep­a­rately dis­closedISD 2024 ac­counts 2024Government and mul­ti­lat­eral in­sti­tu­tion­sIn­sti­tute for Strategic Dialogue (UK)Undisclosed re­main­der af­ter the three-con­tract ag­gre­gate£2,322,079­Cal­cu­lated from £2,957,283 less £635,204; see 2024 ac­counts. 2019 – 2021London MOPACInstitute for Strategic Dialogue (UK)Comprehensive scop­ing, en­gage­ment and con­sul­ta­tion process£50,000­MOPAC con­tract reg­is­ter 2022OfcomInstitute for Strategic Dialogue (UK)Analysis of on­line hate in the UK£79,250Contracts Finder 2022 – 2024London MOPACInstitute for Strategic Dialogue (UK)Shared Endeavour Fund in­de­pen­dent fund eval­u­a­tion£49,961.75­MOPAC reg­is­ter 2023 – 2024London MOPACInstitute for Strategic Dialogue (UK)Shared Endeavour Fund in­de­pen­dent fund eval­u­a­tion ex­ten­sion£61,746­MOPAC reg­is­ter 2023UK Department for Digital, Culture, Media & SportInstitute for Strategic Dialogue (UK)Research into cli­mate-re­lated mis/​dis­in­for­ma­tion af­fect­ing the UK£37,677Open-contract record 2024UK Foreign, Commonwealth & Development OfficeInstitute for Strategic Dialogue (UK)PPM con­sul­tancy spend recorded in January£102,437.90FCDO spend file 2024UK Foreign, Commonwealth & Development OfficeInstitute for Strategic Dialogue (UK)PPM con­sul­tancy spend recorded in March£158,752.07FCDO spend file 2024UK Ministry of Housing, Communities & Local GovernmentInstitute for Strategic Dialogue (UK)Evidence re­view of the 2022 Leicester un­restUndis­closedISD 2024 ac­counts 2024 – 2027European Commission, DG CNECTInstitute for Strategic Dialogue gGmbH (Germany), con­sor­tium lead; Institute for Strategic Dialogue (UK), con­sor­tium mem­berDig­i­tal Services Act com­pli­ance mon­i­tor­ing, five-mem­ber con­sor­tium€4,861,089 con­sor­tium to­tal; ISD share undis­closedTED award no­tice 2019 – 2022US Department of StateInstitute for Strategic Dialogue (UK)Community-based in­ter­ven­tions pro­gram in Kenya · SLMAQM19GR2273$2,250,000USAspending 2024 – 2027US Department of JusticeInstitute for Strategic Dialogue–USStrong Cities Network com­mu­nity-based hate-pre­ven­tion pro­ject · 15PBJA24GG02835ADVA$2,000,000USAspending 2022 – 2023US Department of StateInstitute for Strategic Dialogue (UK)Strong Cities Network re­gional hubs and gov­er­nance · SLMAQM22CA0079$1,333,333USAspending 2024 – 2026US Department of Homeland SecurityInstitute for Strategic Dialogue–USDomestic vi­o­lent-ex­trem­ism trends analy­sis · 23STFRG00021$1,249,621DHS no­tice of award Period not re­port­e­dUS Department of Homeland SecurityInstitute for Strategic Dialogue–USCountering vi­o­lent ex­trem­ism fi­nan­cial as­sis­tance · EMW-2023-GR-00123$817,129USAspending 2017 – 2019US Department of StateInstitute for Strategic Dialogue (UK)Novation from Trialogue Educational Trust · SLMAQM17CA2016$567,953.63USAspending 2024 – 2025US Department of StateInstitute for Strategic Dialogue (UK)Strong Cities Network ca­pac­ity-build­ing · SAQMIP24CA5173$444,005USAspending 2021 – 2023US Department of StateInstitute for Strategic Dialogue–USYoung peo­ple’s on­line and of­fline ini­tia­tives · SJO10021CA3010$422,408.08USAspending 2024 – 2025US Department of Homeland SecurityInstitute for Strategic Dialogue–USTargeted Violence and Terrorism Prevention grant · EMW-2024-GR-05344$315,009.94USAspending 2021 – 2023US Department of StateInstitute for Strategic Dialogue (UK)Young Cities pro­gram in Belgium · SBE20021GR3012$269,541.97USAspending 2023 – 2024US Department of StateInstitute for Strategic Dialogue (UK)Community re­silience against hate and po­lar­iza­tion · SGE21023GR0096$249,783.96USAspending 2023 – 2024US Department of StateInstitute for Strategic Dialogue (UK)Social co­he­sion and anti-Ukraine nar­ra­tives · SAQMIP24GR0009$246,669USAspending 2017US Department of StateInstitute for Strategic Dialogue–USStrong Cities Network CVE ex­per­tise · SLMAQM17CA1034$238,235USAspending 2018US Department of StateInstitute for Strategic Dialogue (UK)Digital plat­forms for im­mi­gra­tion in­te­gra­tion and CVE · SBE20017GR029$199,727USAspending 2021 – 2023US Department of StateInstitute for Strategic Dialogue (UK)City Pair Program work­shop · SFI30021GR3015$140,000USAspending 2017 – 2018US Department of StateInstitute for Strategic Dialogue (UK)Strong Cities Network ex­changes and work­shops · SIN65017CA0020$80,000USAspending 2020 – 2021US Department of StateInstitute for Strategic Dialogue (UK)Monitoring on­line in­for­ma­tion op­er­a­tions dur­ing COVID-19 · SFR63020CA0049$66,293.46USAspending 2024 – 2025US Department of StateInstitute for Strategic Dialogue (UK)Strong Cities Network peer learn­ing and ca­pac­ity build­ing · SUK56024GR0031$63,760USAspending 2017 – 2018US Department of StateInstitute for Strategic Dialogue (UK)Travel for Strong Cities Network work­shop · SUK56017CA034$50,000USAspending 2008 – 2009US Department of StateInstitute for Strategic Dialogue (UK)Counter-radicalization re­search and net­work de­vel­op­ment · SUK56008GR724$50,000USAspending 2017US Department of StateInstitute for Strategic Dialogue–USIndonesia CVE mes­sag­ing · SLMAQM17CA1041$33,848.99USAspending 2024US Department of StateInstitute for Strategic Dialogue–USLocal-leader con­fer­ence on hate pre­ven­tion and so­cial co­he­sion · SCA52524GR0019$32,963.16USAspending 2024 – 2025US Department of StateInstitute for Strategic Dialogue (UK)Strong Cities Network global sum­mit lo­gis­tics · SSF75024GR0015$24,992USAspending 2024US Department of StateInstitute for Strategic Dialogue–USCity-led strate­gies against hate ini­tia­tive · SSW80024GR0003$24,578.09USAspending 2018US Department of StateInstitute for Strategic Dialogue (UK)Australian–American city ties · SAS20018GR034$17,383USAspending 2024US Department of StateInstitute for Strategic Dialogue–USFrench cities coun­ter­ing hate-mo­ti­vated vi­o­lence · SFR63024CA0018$14,000USAspending 2023US Department of StateInstitute for Strategic Dialogue (UK)Strong Cities transat­lantic event travel · SNO60023GR0011$10,000USAspending 2024 – 2025US Department of StateInstitute for Strategic Dialogue (UK)Smart Cities Network peer learn­ing and ca­pac­ity build­ing · SMO55024GR0075$1,560.21USAspending

US rows are the com­plete set of re­cip­i­ent-name matches for “INSTITUTE FOR STRATEGIC DIALOGUE” in USAspending’s pro­ject-grant and co­op­er­a­tive-agree­ment search through August 3, 2026; award val­ues are shown in US dol­lars.

We use con­ver­sion rates for July 27, 2026: €1 = $1.1389 and €1 = £0.85524. It ex­cludes the £635,204 ag­gre­gate for three un­named gov­ern­ment con­tracts and the £2,322,079 un­al­lo­cated gov­ern­ment-and-mul­ti­lat­eral re­main­der.

US rows are the com­plete set of re­cip­i­ent-name matches for “INSTITUTE FOR STRATEGIC DIALOGUE” in USAspending’s pro­ject-grant and co­op­er­a­tive-agree­ment search through August 3, 2026; award val­ues are shown in US dol­lars.

Archived ISD re­port ex­am­ple.

Archived ISD re­port ex­am­ple.

US Senate LDA data­base.

Federal fil­ing pe­ri­o­dReg­is­trantRe­ported amountSource

2026 Q1ISD-USLess than $5,000LDA re­port 2026 Q2ISD-USLess than $5,000LDA re­port

US Senate LDA data­base.

Reset Tech home­page global col­lec­tive ref­er­ences: “Reset Tech”: 1, “we”: 6, and “our”: 5 (only in the con­text of Reset Tech).

Reset Tech home­page global col­lec­tive ref­er­ences: “Reset Tech”: 1, “we”: 6, and “our”: 5 (only in the con­text of Reset Tech).

The table to­tals $1,352,800 in re­ported lob­by­ing pay­ments and ex­pen­di­tures from 2024 through Q2 2026: $1,222,500 in fed­eral lob­by­ing pay­ments, $100,000 in Maryland em­ployer ex­pen­di­tures, and $30,300 in Nebraska lob­by­ist com­pen­sa­tion and re­im­burse­ment.

Filing pe­ri­o­dReg­is­trantRe­ported amount

2024 Q1–Q4Corbin Strategies$320,000 2024 Q1–Q4Center Road Solutions$170,000 2025 Q1–Q4; 2026 Q1–Q2EFB Advocacy LLC$502,500 2024 Q1–Q4; 2025 Q1–Q4Epplin Strategic Planning$230,000 2024Reset Tech Action$100,000 2024 – 2025Reset Tech Action$30,300

The table to­tals $1,352,800 in re­ported lob­by­ing pay­ments and ex­pen­di­tures from 2024 through Q2 2026: $1,222,500 in fed­eral lob­by­ing pay­ments, $100,000 in Maryland em­ployer ex­pen­di­tures, and $30,300 in Nebraska lob­by­ist com­pen­sa­tion and re­im­burse­ment.

We iden­ti­fied AVPA as a sig­nif­i­cant for­eign in­flu­ence over age ver­i­fi­ca­tion laws in the UK and US and added them to the map ac­cord­ingly, but they are out­side of the di­rect scope of this in­ves­ti­ga­tion, as we did not iden­tify legally clas­si­fied lob­by­ing from AVPA.

AVPA is a British trade or­ga­ni­za­tion of age ver­i­fi­ca­tion sup­pli­ers — mem­bers with a fi­nan­cial stake in age ver­i­fi­ca­tion man­dates.

AVPA’s page lists Alastair Graham as chair and Ian Moody, Tony Allen, Andy Lulham, Julie Dawson, and Ryan Bessemer as the ex­ec­u­tive com­mit­tee. Their na­tion­al­i­ties are as fol­lows.

NameRoleSource con­firm­ing cit­i­zen­ship

Alastair GrahamChairBritish — Companies House of­fi­cer record Ian MoodyExecutive CommitteeBritish — Companies House of­fi­cer record Tony AllenExecutive CommitteeBritish — Companies House of­fi­cer record Andy LulhamExecutive CommitteeBritish — LinkedIn pro­file Julie DawsonExecutive CommitteeBritish — Companies House Yoti di­rec­tor record Ryan BessemerExecutive CommitteeAustralian — LinkedIn pro­file

We iden­ti­fied AVPA as a sig­nif­i­cant for­eign in­flu­ence over age ver­i­fi­ca­tion laws in the UK and US and added them to the map ac­cord­ingly, but they are out­side of the di­rect scope of this in­ves­ti­ga­tion, as we did not iden­tify legally clas­si­fied lob­by­ing from AVPA.

AVPA is a British trade or­ga­ni­za­tion of age ver­i­fi­ca­tion sup­pli­ers — mem­bers with a fi­nan­cial stake in age ver­i­fi­ca­tion man­dates.

AVPA’s page lists Alastair Graham as chair and Ian Moody, Tony Allen, Andy Lulham, Julie Dawson, and Ryan Bessemer as the ex­ec­u­tive com­mit­tee. Their na­tion­al­i­ties are as fol­lows.

Mars Bar from 1991 found - and it’s 20g big­ger than to­day’s

20 hours ago

Eleanor MaslinEast Yorkshire and Lincolnshire

Victoria Gordon

A 35-year-old Mars Bar has been found dur­ing a house clear­ance — and the dis­cov­ery has gone vi­ral amid claims it high­lights the ef­fect of “shrinkflation”.

The choco­late bar with a best-be­fore date of 1991 was found dur­ing a clear-out of a house in Scunthorpe.

Victoria Gordon, who runs the clean­ing ser­vice, posted a photo on so­cial me­dia of the 62.5g bar along­side one of to­day’s Mars Bars, which is 40g.

“It was nearly as big as my hand, which was kind of why I no­ticed it,” she said.

Victoria Gordon

Speaking on BBC Radio Lincolnshire, Gordon said: “We were clear­ing out a hoard­er’s house and every­thing we were root­ing through was decades old.

“This Mars Bar stood out to me be­cause as I picked it up it was nearly the whole length of my hand.

“I was like, ‘Wow, look at the size of that!’”

A Mars spokesper­son said: “Over the last 35 years, we have made a num­ber of up­dates to our bar sizes and pack for­mats to re­flect con­sumer de­mand, along­side con­sid­er­ing wider ex­ter­nal fac­tors such as man­u­fac­tur­ing costs and the price of co­coa.”

Supplied

Gordon, who runs Pocket Rockets, is not sure what she will do with the bar, but she said she might be sit­ting on a “gold mine”.

“I do post some hoard­ing videos but I’ve never had any­thing go this vi­ral,” she said.

“It’s so fas­ci­nat­ing what peo­ple find so in­ter­est­ing. I al­most put it in the skip [but] I might do a UK tour with it.”

Related sto­ries

HB5511 is of­fi­cially about TikTok and Instagram. Read past the press re­lease and it’s also about your op­er­at­ing sys­tem.

Governor JB Pritzker’s press re­lease on HB5511 is thick with quotes from leg­is­la­tors and ad­vo­cacy groups, and it names Instagram, TikTok, Snapchat, X, Facebook, and Roblox specif­i­cally. Device setup gets one men­tion, framed as some­thing a par­ent con­fig­ures dur­ing setup. Nowhere does it ex­plain that the law also cre­ates a sep­a­rate le­gal cat­e­gory called an op­er­at­ing sys­tem provider, with its own 2028 dead­line and its own civil penal­ties, that has noth­ing to do with what any par­ent chooses to click.

TL;DR

HB5511, the Children’s Social Media Safety Act, is now Illinois Public Act 104 – 0664. Pritzker signed it July 31.

The head­line pro­vi­sions tar­get so­cial plat­forms: no al­go­rith­mic feeds for mi­nors by de­fault, no no­ti­fi­ca­tions be­tween 10pm and 7am, no con­tact from adult strangers.

A sep­a­rate part of the bill de­fines op­er­at­ing sys­tem provider and cov­ered man­u­fac­turer broadly enough to in­clude any­one who builds an in­ter­net-con­nected OS, com­mer­cial or non­profit.

By January 1, 2028, those providers have to build an age-de­c­la­ra­tion step and hand an age-bracket sig­nal to any app that re­quests one.

Unlike Colorado, and un­like where California is head­ing, Illinois added no ex­emp­tion for open source soft­ware.

Enforcement runs through the Illinois Attorney General only. The bil­l’s own text caps penal­ties at $7,500 per af­fected child. The gov­er­nor’s press re­lease ad­ver­tises penal­ties of up to $50,000 per vi­o­la­tion. Those num­bers don’t ob­vi­ously square with each other.

The Version Illinois Wants You to Read

Set the op­er­at­ing sys­tem ques­tion aside for a sec­ond, be­cause the so­cial me­dia half of this bill is fairly stan­dard for 2026. Platforms built around al­go­rith­mic feeds, plus plat­forms where kids can be con­tacted by strangers (Roblox is the named ex­am­ple), now have to de­fault mi­nors into chrono­log­i­cal, fol­low-only feeds in­stead of an en­gage­ment-op­ti­mized one. Notifications get cut off overnight. Adult strangers can’t see a mi­nor’s pro­file, mes­sage them, or see their lo­ca­tion. News sites, email providers, broad­band com­pa­nies, and school soft­ware are all carved out by name.

It passed the General Assembly on June 1 with­out a sin­gle no vote, 57 – 0 in the Senate and 113 – 0 in the House con­cur­rence. Pritzker signed it July 31, flanked by quotes from Attorney General Kwame Raoul and groups like Common Sense Media and Mothers Against Media Addiction. Nothing about that roll­out men­tions your desk­top.

The Part the Press Release Skipped

Here’s what ac­tu­ally set off the Reddit thread: a post claim­ing Illinois now re­quires op­er­at­ing sys­tem providers, open source pro­jects in­cluded, to build age ver­i­fi­ca­tion by 2028. It was­n’t uni­ver­sally be­lieved. On at least one mir­ror of the dis­cus­sion, a com­menter ar­gued the fram­ing was mis­lead­ing and that the post should be cor­rected. So in­stead of trust­ing a screen­shot ei­ther way, we went and read the bill on the Illinois General Assembly’s own tracker.

It holds up. Separate from the so­cial me­dia rules, HB5511 cre­ates du­ties for an op­er­at­ing sys­tem provider and folds de­vice mak­ers, OS ven­dors, and app stores to­gether un­der the term cov­ered man­u­fac­turer. Legislative track­ers that fol­low this ex­act cat­e­gory of bill across states file this piece un­der its own name: Digital Age Assurance, the same bucket Colorado’s and California’s ver­sions land in.

What Every Covered Manufacturer Has to Build by 2028

An ac­ces­si­ble setup screen that asks an ac­count holder to in­di­cate a birth date, an age, or both.

A way for any app or plat­form that asks (the bill calls them “operators” and “covered de­vel­op­ers”) to re­ceive a sig­nal for that age, de­liv­ered through a con­sis­tent, en­crypted API.

A hard limit on what gets shared: only the min­i­mum in­for­ma­tion needed to an­swer the ques­tion, and no hand­ing it to a third party be­yond what the law re­quires.

The sig­nal it­self is­n’t a birth­day, it’s a bracket: un­der 13, 13 to 15, 16 to 17, or 18 and up. Operating sys­tems have un­til January 1, 2028 to have this built. Platforms then have un­til July 1, 2028 to start ac­tu­ally re­quest­ing that sig­nal for their users. Once an app gets a “minor” bracket back, the law treats it as hav­ing ac­tual knowl­edge the user is un­der­age, which is what flips on every de­fault pro­tec­tion in the so­cial me­dia half of the bill.

Nothing in the bill re­quires a pass­port scan or a face scan at setup. It’s self-de­clared, the same way most apps ask your birth­day to­day, just cen­tral­ized once at the OS level in­stead of re­peated app by app. That’s ex­actly why a good chunk of the r/​linux replies were jokes about set­ting their in­stal­l’s date of birth to some­time in the Nixon ad­min­is­tra­tion.

Nobody Carved Out an Exception This Time

This struc­ture, OS hands out an age bracket, apps pull it through an API, al­ready showed up in Colorado and California, and both ran into the same ob­jec­tion: the de­f­i­n­i­tions were broad enough to catch com­mu­nity-run, non­com­mer­cial, open source pro­jects with no re­al­is­tic way to run an age-gated setup wiz­ard, let alone a com­pli­ance de­part­ment.

Colorado fixed it. Governor Jared Polis signed SB26 – 051 on June 3, and largely be­cause System76 founder Carl Richell worked di­rectly with the bil­l’s co-au­thor, State Senator Matt Ball, the fi­nal ver­sion ex­empts op­er­at­ing sys­tems, apps, code repos­i­to­ries like GitHub and GitLab, and con­tainer plat­forms like Docker and Podman, as long as they’re dis­trib­uted un­der an open li­cense. It also blocks a ven­dor from lock­ing down a mod­i­fied ver­sion of the soft­ware just to dodge the ex­emp­tion.

California is try­ing to get to the same place. Its orig­i­nal law, AB-1043, had the iden­ti­cal gap. Assemblymember Buffy Wicks, who wrote that bill, in­tro­duced a fol­low-up, AB-1856, specif­i­cally to re­de­fine op­er­at­ing sys­tem provider so it ex­cludes any­one ship­ping soft­ware un­der those same open terms. As of this writ­ing, that fix is still mov­ing through Sacramento, not fin­ished.

Illinois skipped that step en­tirely. HB5511’s de­f­i­n­i­tions for cov­ered man­u­fac­turer and ap­pli­ca­tion store are ex­actly as broad as Colorado’s and California’s were be­fore any­one patched them. The struc­ture is­n’t unique to Illinois, ei­ther: California did it first, Colorado fol­lowed the same blue­print, and HB5511 reads like a close cousin of both, same age brack­ets, same API-based sig­nal, same per-child penalty fig­ures.

Even Big Tech’s Own Lobby Hated This One

Before Pritzker signed any­thing, the Electronic Frontier Foundation sent him a let­ter ask­ing for a veto, call­ing the bill “a mas­sive pri­vacy and free speech night­mare” and nam­ing the open source ecosys­tem specif­i­cally as one of the things it put at risk. EFF grouped Illinois with a wider run of state bills lean­ing on child safety lan­guage to jus­tify sweep­ing age-ver­i­fi­ca­tion man­dates.

Separately, and for very dif­fer­ent rea­sons, NetChoice, the trade group that counts com­pa­nies like Google and Meta among its mem­bers, filed tes­ti­mony op­pos­ing the same bill. Its ob­jec­tion was First Amendment law and the risk of ex­pos­ing sen­si­tive user data, not open source specif­i­cally. It’s an odd pair­ing: a dig­i­tal rights non­profit and the lob­by­ing arm for the plat­forms the bill is sup­posed to be reg­u­lat­ing, ar­gu­ing against the same bill for op­po­site rea­sons. Illinois law­mak­ers passed it unan­i­mously any­way.

Could Anyone Actually Enforce This?

Only the Illinois Attorney General can bring a case. There’s no pri­vate right of ac­tion, so an in­di­vid­ual can’t sue over this per­son­ally. The civil penalty writ­ten into the bill it­self is up to $2,500 per af­fected child for a neg­li­gent vi­o­la­tion and up to $7,500 per af­fected child for an in­ten­tional one. That’s not a co­in­ci­dence: it’s the ex­act same fig­ure Colorado’s law uses, be­cause these bills are largely work­ing from the same tem­plate as they spread state to state.

Set that against the gov­er­nor’s own press re­lease, which ad­ver­tises penal­ties of up to $50,000 per vi­o­la­tion. It’s pos­si­ble both num­bers are tech­ni­cally ac­cu­rate and just re­fer to dif­fer­ent sec­tions of a fairly long piece of leg­is­la­tion, but noth­ing in the state’s own ma­te­ri­als rec­on­ciles them for the reader, and the big­ger num­ber is the one that made it into the an­nounce­ment.

As for ac­tu­ally reach­ing a hob­by­ist dis­tro main­tainer: noth­ing in the bill has teeth against some­one with no busi­ness pres­ence in Illinois, which is ex­actly the loop­hole half of r/​linux jumped to im­me­di­ately. Expect a wave of joke warn­ing la­bels on dis­tro down­load pages long be­fore any­one pays a fine. The providers who can’t shrug this off are the ones al­ready do­ing real busi­ness in the state, mean­ing Google, Microsoft, Apple, and any Linux ven­dor with ac­tual Illinois rev­enue on the books.

What Happens Between Now and 2028

The com­pli­ance dead­line is still more than a year out, which leaves room for a few things to hap­pen be­fore it mat­ters. NetChoice has al­ready chal­lenged com­pa­ra­ble so­cial me­dia and age-ver­i­fi­ca­tion laws in Mississippi, Colorado, California, Louisiana, Georgia, and Ohio, with mixed re­sults, some pro­vi­sions blocked, oth­ers up­held. Given that track record, a chal­lenge to HB5511 specif­i­cally would­n’t be a shock, though noth­ing had been filed as of this writ­ing. There’s also room for an amend­ment adding the same open source carve-out Colorado and California landed on. Or there’s room for noth­ing to change, in which case Illinois be­comes the ver­sion other states copy in­stead of the ex­cep­tion.

Which of those hap­pens prob­a­bly de­pends on whether the open source com­mu­nity shows up in Springfield the way Carl Richell showed up in Denver. Nobody did this time. There’s still time to change that be­fore January 1, 2028 turns into a dead­line that ac­tu­ally bites.

Today we re­lease Needle 2: an open 45M-parameter model for tool call­ing, de­vice use and struc­tured ex­trac­tion. The whole model is a sin­gle 14MB bi­nary that runs a full ses­sion in 28MB of RAM. It is built on our Simple Attention Network find­ings, com­pressed to CQ2-bit with Cactus Quants, and baked into its own en­gine.

On the tool call and mo­bile de­vice use bench­marks, Needle 2 trades wins with other small mod­els like FunctionGemma 270M, LFM2.5 230M and Apple FM, at 5× to 70× smaller, and 2 bits against their f16. Needle hits 500 to­kens/​sec de­code speed on a Raspberry Pi 5, be­tween 400 – 1,500 to­kens/​sec on VR de­vices like Meta Quest 3S and Apple Vision Pro, and ranges 300 – 700 on sub-$200 phones such as the Samsung A-Series. With a peak ses­sion RAM around 28MB, Needle runs on newer mi­cro­con­trollers like ESP32-S3.

The Playground lets you test Needle for wear­ables, ro­bots, smart homes, phones, and au­to­mo­tive. Needle is li­censed un­der Apache 2.0, with weights on Hugging Face; the repo gets you run­ning.

Our Bet

Bringing On-Device AI to <$200 Devices: Edge AI has lately meant Macs and PCs, but the edge is mostly cheap hard­ware: over 21 bil­lion con­nected IoT de­vices against roughly 1.5 bil­lion PCs, and in emerg­ing mar­kets most phones ship un­der $200. Count bud­get phones, Raspberry Pis, mi­cro­con­trollers, wear­ables, small ro­bots like Reachy Mini, and con­nected home de­vices, and roughly four in five edge de­vices cost un­der $200. That is the hard­ware Needle tar­gets: no GPU, no NPU, a few hun­dred MB of RAM.

Function Call & Device Use: Turning on a light does not need a fron­tier model. A watch, a home, a ro­bot: each al­ready ex­poses its abil­i­ties as func­tions with typed pa­ra­me­ters, so the only hard part is map­ping a messy sen­tence onto them: which func­tion, with which val­ues. Framed that way, the prob­lem needs no world knowl­edge and no open-ended prose, which is why 45M pa­ra­me­ters suf­fice where chat needs bil­lions. That smaller for­mu­la­tion is the bet every­thing else fol­lows from.

Extraction & Structured Outputs: The schema is the in­ter­face, and the same for­mu­la­tion cov­ers doc­u­ments: a schema plus a para­graph re­turns typed fields, an enum field is a clas­si­fier, an ar­ray field col­lects a list in one call. We en­force this with a con­tract, not a con­ven­tion: every turn is an­swered with a call en­ve­lope, the empty call is the re­fusal, and a byte-level gram­mar com­piled from the de­clared schemas con­strains every to­ken. The gram­mar car­ries the syn­tax, so all 45M pa­ra­me­ters go to choos­ing func­tions and ground­ing ar­gu­ments in the user’s words.

Edge-Cloud Collaboration: No small model cov­ers every­thing, so Needle says so in­stead of guess­ing: every re­sponse car­ries a learned con­fi­dence score, and off-topic re­quests re­turn the empty call. Above your thresh­old, act; be­low it, re-ask or es­ca­late to the cloud. Most de­vice re­quests are rou­tine con­trol, so es­ca­la­tion stays rare and the de­fault path stays pri­vate, in­stant, and free.

Lossless 2bit Quantization: Small mod­els break un­der post-hoc quan­ti­za­tion, so we never quan­tize post-hoc: Needle 2 trains against Cactus Quants from pre­train through post-train, weights, ac­ti­va­tions, and KV cache alike. The 2bit model you de­ploy is the model that was trained. That is what fits 45M pa­ra­me­ters into 14MB with noth­ing lost on our bat­tery.

Co-designed Model & Inference: Every ar­chi­tec­tural choice was bench­marked on the tar­get hard­ware be­fore it earned its pa­ra­me­ters, and the de­liv­er­able is the pair, not the weights: a sin­gle de­pen­dency-free C++ bi­nary that probes the CPU at startup and picks its ker­nels, with the model, to­k­enizer, and gram­mar com­piler sealed in­side. One ar­ti­fact runs from Cortex-M to x86 to WebAssembly. There is noth­ing to in­stall and noth­ing to down­load.

Fine-tune on your Mac/PC: Every prod­uct has its own tool vo­cab­u­lary, and a 45M model is small enough to re­train where it runs: the repo and python pack­age tune and test on your own com­puter in min­utes to a few hours. Ship a Needle that speaks your de­vice’s tools, not a generic as­sis­tant.

Production

Needle is pro­duc­tion-ready for prod­ucts that re­quire a min­i­mal RAM foot­print, low la­tency, pri­vacy, and of­fline re­li­a­bil­ity. Pebble - the pi­o­neer of the mod­ern wear­able in­dus­try - runs it lo­cally in the Index 01 app to turn spo­ken re­quests into ac­tions with­out de­pend­ing on a net­work con­nec­tion.

The Pebble Index Ring has no screen. So when you speak to it, the ac­tion just has to hap­pen, every time, with or with­out in­ter­net con­nec­tion. We run Cactus Needle lo­cally in the app, in­stead of re­ly­ing on the cloud. The mod­el’s foot­print is tiny and the per­for­mance never lets us down.

The Pebble Index Ring has no screen. So when you speak to it, the ac­tion just has to hap­pen, every time, with or with­out in­ter­net con­nec­tion. We run Cactus Needle lo­cally in the app, in­stead of re­ly­ing on the cloud. The mod­el’s foot­print is tiny and the per­for­mance never lets us down.

Architecture

Needle 2 is pre­trained on a pro­pri­etary 115B-token cor­pus and post-trained on 38B to­kens with com­pact rea­son­ing traces and care­ful dataset dis­tri­b­u­tion de­sign. For scale: LFM2.5 – 230M was pre­trained on 19 tril­lion to­kens, roughly 120× Needle’s to­tal, and the eval­u­a­tion be­low shows the two trad­ing wins. Each com­po­nent ex­ists to buy ca­pa­bil­ity with­out buy­ing band­width. The Hadamard MLP re­places the usual dense up-and-down pro­jec­tions with a fixed Walsh trans­form and learned di­ag­o­nals, so the chan­nel mix­ing that dom­i­nates a small mod­el’s weight reads costs al­most no pa­ra­me­ters at all. The en­gram moves world knowl­edge out of the stack into hashed n-gram ta­bles that are read a few rows per to­ken: ca­pac­ity that is nearly free at de­code time, which mat­ters on de­vices where every megabyte read from flash is la­tency and bat­tery. The multi-lane resid­ual streams give a 27-layer, 512-wide net­work the rout­ing flex­i­bil­ity of a much wider one, at the cost of a few dot prod­ucts per layer rather than more at­ten­tion or MLP vol­ume.

The mem­ory sys­tem is de­signed back­wards from fixed-RAM de­vices. Attention uses a 256-token slid­ing win­dow so the KV cache is bounded no mat­ter how long a ses­sion runs, and the sys­tem prompt and tool de­c­la­ra­tions are pinned as per­ma­nent sinks so the one thing a tool-call­ing model must never for­get—its tools—is struc­turally un­able to be evicted. The cache it­self is trained with QAT, and weights are stored in Cactus Quants at a mixed bits per weight av­er­ag­ing 2bit. The re­sult is that qual­ity de­ci­sions and de­ploy­ment de­ci­sions stay de­cou­pled: one trained model, spe­cial­ized to what­ever pre­ci­sion and win­dow a tar­get de­vice can af­ford.

The en­gine earns its speed from what it re­fuses to com­pute. Weights never de­com­press into RAM: the 2-bit codes are ex­panded in­side vec­tor reg­is­ters, fused into in­te­ger dot prod­ucts, so res­i­dent mem­ory stays at blob size and the arith­metic path is int8 end to end—ac­ti­va­tions, KV cache, and the lane rout­ing ta­bles alike. The gram­mar is an op­ti­miza­tion, not just a guar­an­tee: be­cause the matcher knows which to­kens are le­gal be­fore the log­its ex­ist, the en­gine com­putes out­put scores only for can­di­date rows, skip­ping up to 98% of the vo­cab­u­lary pro­jec­tion on struc­tural to­kens, and skips it en­tirely on steps whose out­put is al­ready forced. One uni­ver­sal bi­nary probes the CPU at startup and self-se­lects its ker­nel tier—SDOT, NEON, AVX2, RISC-V vec­tors, wasm SIMD, or scalar—and the thread pool spins through the short se­r­ial sec­tions of a to­ken in­stead of sleep­ing, which alone nearly dou­bled de­code. None of this changes a sin­gle out­put: every trick is ei­ther ex­act or val­i­dated to­ken-for-to­ken against the ref­er­ence path.

All of it is ul­ti­mately an en­ergy ar­gu­ment. On de­vice sil­i­con, mov­ing a byte out of flash or DRAM costs or­ders of mag­ni­tude more than a mul­ti­ply-ac­cu­mu­late, so the bud­get that mat­ters is FLOPs per to­ken and bytes per to­ken to­gether. The ar­chi­tec­ture cuts the first: a con­ven­tional trans­former of Needle’s width and depth spends 164 MFLOPs per to­ken, and even one squeezed down to Needle’s pa­ra­me­ter count spends 87, be­cause every pa­ra­me­ter it owns must be ex­er­cised through a mat­mul. Needle spends 70, and keeps a fifth of its pa­ra­me­ters as gath­ered mem­ory that costs no arith­metic at all. The bi­nary cuts the sec­ond, as the en­gine sec­tion showed: noth­ing re­ma­te­ri­al­izes, the arith­metic stays int8 end to end, and the gram­mar prunes com­pute out­right, so de­cod­ing a to­ken reads at most the 14MB blob once, and on struc­tural to­kens mean­ing­fully less. This is what bat­tery life is made of. Even on a high-end phone, an al­ways-on as­sis­tant lives in­side a power bud­get; every MFLOP is mil­li­watt-hours, and Needle spends 7× to 85× fewer of them per to­ken than the mod­els it is bench­marked against.

Compute per to­ken

Bounded ses­sion mem­ory is what puts mi­cro­con­trollers in reach. Because the slid­ing win­dow caps state, Needle 2′s RAM is a de­ter­min­is­tic 28MB ceil­ing, not a curve that grows with con­ver­sa­tion length. That fits MCU-class parts with ex­ter­nal RAM, such as ESP32-P4 with 32MB of PSRAM, or STM32H7 and NXP i.MX RT boards with SDRAM. The en­gine com­piles sin­gle-threaded for bare metal and ships as a sta­tic li­brary for Cortex-M4, M7, and M55.

Evaluation

We eval­u­ate on five pub­lic func­tion-call­ing bench­marks: Google’s Mobile Actions, DroidCall, the Seal-Tools in-do­main and out-of-do­main tests, and BFCL v4 sin­gle-turn. Scoring is or­dered strict ex­act match: a row passes only if the func­tion names, the call or­der, and every ar­gu­ment value match. All Needle 2 num­bers are mea­sured end-to-end through the shipped C++ en­gine in its pro­duc­tion con­fig­u­ra­tion: CQ2-bit weights, tool re­trieval on, and the 256-token slid­ing KV win­dow. Nothing is re­laxed for bench­mark­ing; the num­bers re­flect the ex­act en­gine a de­vice runs, win­dow evic­tion in­cluded. Baselines run the re­leased check­points un­der vLLM at full con­text, and Apple FM runs on-de­vice.

Two asym­me­tries make this com­par­i­son hard, and we state both up­front. Precision: the base­lines stay at f16 de­lib­er­ately, be­cause con­ven­tional post-train­ing quan­ti­za­tion to 2 bits col­lapses mod­els that were never trained for ag­gres­sive com­pres­sion, while Cactus Quants is baked into Needle’s train­ing from the ground up. That skew fa­vors the base­lines. Scope: Needle is trained specif­i­cally for agen­tic tool call­ing and noth­ing else, while every base­line is a gen­eral lan­guage model car­ry­ing chat, prose, and world knowl­edge along­side its tool call­ing. That skew fa­vors Needle. There is no clean way to level both at once, so we do not try. The ta­bles an­swer one nar­row ques­tion: which model ex­e­cutes tool calls cor­rectly within an on-de­vice bud­get. We ac­cept the skew; it still paints the pic­ture we in­tend.

Mobile Actions (961 rows)

DroidCall test split (200 rows)

Seal-Tools in-do­main (700 rows)

Seal-Tools out-of-do­main (654 rows)

Needle was not trained for gen­eral func­tion call­ing: its cor­pus is con­sumer de­vice ac­tions—smart home, mo­bile, wear­ables, TV, car—plus struc­tured ex­trac­tion, and BFCL’s gen­eral-pur­pose and en­ter­prise API sur­faces, in­clud­ing the Java and JavaScript SDK cat­e­gories, sit en­tirely out­side that dis­tri­b­u­tion. It ex­trap­o­lates nonethe­less: on Python sim­ple calls it lands within a point of FunctionGemma, a model six times larger trained for ex­actly this task, and it keeps a 93.4 well-formed rate across all 3,641 rows. The gap con­cen­trates where its train­ing data has never been: Java, JavaScript, and the par­al­lel multi-call cat­e­gories.

BFCL v4 sin­gle-turn (3,641 rows)

These re­lease notes are op­ti­mized for view­ing in­side Squeak, as they con­tain a lot of in­ter­ac­tive ex­am­ples. On this page, in­ter­ac­tive links open in SqueakJS, which is a browser-based Smalltalk VM with some lim­i­ta­tions. For the best ex­pe­ri­ence, down­load Squeak and read the re­lease notes there.

*** Squeak 6.1 “Vanessa” Release Notes ***

As Squeak ap­proaches its 30th an­niver­sary, we are proud to an­nounce the next ver­sion of the sys­tem, Squeak 6.1. Some high­lights of this re­lease are:

A new tree browser, which en­ables nav­i­ga­tion through classes and cat­e­gories us­ing re­fur­bished hi­er­ar­chi­cal morphs,

The re­turn of Objectland (also known as the “Worlds of Squeak”),

Several changes and fixes for the ker­nel in­fra­struc­ture for sim­u­lat­ing, un­wind­ing, and sched­ul­ing processes and re­shap­ing classes,

Miscellaneous im­prove­ments and ad­di­tions to the toolset and user in­ter­face for in­spect­ing, de­bug­ging, pro­fil­ing, and ver­sion­ing code.

Please find be­low a de­tailed list­ing of all the changes, which in­cludes notes on Major Deprecations, Known Issues, and Compatibility Notes at the bot­tom.

About these re­lease notes. Phew, what a re­lease! Since the last re­lease 4 years ago, we have merged 1700+ patches with 9000+ method changes. Beyond doc­u­ment­ing tech­ni­cal changes in de­tail, these notes high­light the big­ger pic­ture and the over­all im­pact of ma­jor de­vel­op­ments. Along the way, you will find plenty of links to code point­ers and in­ter­ac­tive ex­am­ples. Thus, these re­lease notes serve not only as a changelog but also as a hands-on guide to ex­plor­ing new fea­tures and mech­a­nisms in Squeak. Click here to view an out­line of this doc­u­ment.

In mem­ory of Vanessa Freudenberg (1972 – 2025).

Detailed Improvements in Language, Tools, and the Environment

~~~ GUI Frameworks ~~~

Morphic (up to Morphic-ct.2218/MorphicTests-ct.97)

Major over­haul of tree morphs: Improves col­ors and mouse and key­board short­cuts for nav­i­gat­ing trees. Revises type-to-fil­ter sim­i­lar to lists, high­lights search terms, and en­ables search­ing sin­gle columns via [TAB]. Adds a con­fig­urable fil­ter mode to search within the cur­rent se­lec­tion, all vis­i­ble nodes, or the en­tire tree. Introduces a re­cur­sive “find”/“find again” fea­ture avail­able via [CMD] + [F]/[CMD] + [G]. Adds a flag for au­to­matic ex­pan­sion of trees. Improves sup­port for drag’n’­drop by au­to­mat­i­cally ex­pand­ing nodes dur­ing drag­ging af­ter one sec­ond of hov­er­ing. Miscellaneous sta­bil­ity and per­for­mance im­prove­ments for lay­out­ing, ren­der­ing, and event han­dling in trees.

Improves col­ors and mouse and key­board short­cuts for nav­i­gat­ing trees.

Revises type-to-fil­ter sim­i­lar to lists, high­lights search terms, and en­ables search­ing sin­gle columns via [TAB]. Adds a con­fig­urable fil­ter mode to search within the cur­rent se­lec­tion, all vis­i­ble nodes, or the en­tire tree.

Introduces a re­cur­sive “find”/“find again” fea­ture avail­able via [CMD] + [F]/[CMD] + [G].

Adds a flag for au­to­matic ex­pan­sion of trees.

Improves sup­port for drag’n’­drop by au­to­mat­i­cally ex­pand­ing nodes dur­ing drag­ging af­ter one sec­ond of hov­er­ing.

Miscellaneous sta­bil­ity and per­for­mance im­prove­ments for lay­out­ing, ren­der­ing, and event han­dling in trees.

In the world, sup­ports drop­ping of class ref­er­ences, sys­tem and method cat­e­gories, and in­spec­tor and ex­plorer fields to dis­play them in a new win­dow/​wid­get.

For mouse in­ter­ac­tions, adds new pref­er­ences to cus­tomize the dou­ble-click time and drag thresh­olds.

In the dock­ing bar win­dow menu, adds an item to col­lapse win­dows. Makes “find work­space” eas­ier to use by ex­pand­ing the se­lected win­dow if col­lapsed. Reorders and dec­o­rates items in the help menu.

Text ed­i­tors: Underlines links (like this one!) dur­ing hov­er­ing and makes click­ing and text se­lec­tion through them more con­ve­nient. When en­clos­ing/​un­en­clos­ing a se­lec­tion in sin­gle/​dou­ble quotes, nested quotes are now au­to­mat­i­cally es­caped/​un­escaped.

Underlines links (like this one!) dur­ing hov­er­ing and makes click­ing and text se­lec­tion through them more con­ve­nient.

When en­clos­ing/​un­en­clos­ing a se­lec­tion in sin­gle/​dou­ble quotes, nested quotes are now au­to­mat­i­cally es­caped/​un­escaped.

Morphic API: Allows morphs to opt out of in­di­vid­ual halo events and to spec­ify a bal­loon text via a block in­stead of a se­lec­tor.

Menu con­struc­tion: Adds new util­i­ties for adding item groups and tem­porar­ily switch­ing ac­tion tar­gets dur­ing con­struc­tion. #addList: now in­ter­prets back­slashes in help tu­ples as line breaks. Automatically trims trail­ing lines be­tween menu items.

Adds new util­i­ties for adding item groups and tem­porar­ily switch­ing ac­tion tar­gets dur­ing con­struc­tion.

#addList: now in­ter­prets back­slashes in help tu­ples as line breaks.

Automatically trims trail­ing lines be­tween menu items.

Revises the de­bug menus of sev­eral morphs by adding a time-pro­filer short­cut for but­tons, pro­vid­ing ac­cess to the list and tree con­tents, and mak­ing ex­ist­ing “browse ac­tion” and “debug ac­tion” com­mands faster and more re­li­able.

Honors the pref­er­ence “Open Tools Attached to Mouse Cursor” in Morph>>openAsTool.

Lots of UI tweaks and sta­bil­ity im­prove­ments: Improves theme sup­port for progress bars, text morph menus, and di­a­log win­dows. Improves high-DPI sup­port for but­tons, scroll panes, slid­ers, menus, multi-se­lec­tion lists, trees, drop-shad­ows, the scratch pad, the key­board ex­er­ciser, and oth­ers. Improves mul­ti­lin­gual sup­port in dif­fer­ent places. Fixes slips re­gard­ing the world dis­play depth menu, clock con­fig­u­ra­tion changes, search-bar print-its, pro­ject view morph styling, and tran­script count­ing. Fixes an is­sue when pro­fil­ing code where user events were swal­lowed. Several lay­out­ing fixes re­gard­ing pro­por­tional lay­outs, text morphs, scroll panes, and trans­for­ma­tion morphs. Fixes ren­der­ing is­sues with trans­form morphs, poly­gons, multi-se­lec­tion lists, and trees. Fixes scrolling in nested scroll panes. In text morphs, im­proves sta­bil­ity of text se­lec­tion and tweaks in­den­ta­tion re­gard­ing empty and blank lines. Fixes “browse senders” of true, false, and nil, adds miss­ing ac­cess to work­space bind­ings dur­ing ac­cept-its, and im­proves ro­bust­ness of ed­i­tor his­tory. Fixes bugs in con­struc­tion of text con­tain­ers and con­ver­sion of para­graphs to texts. In lists, fixes au­to­matic se­lec­tion be­fore drag­ging an item. Fixes in­cor­rect yel­low-but­ton menu in­vo­ca­tion on but­tons and lists. Fixes a bug dur­ing menu con­struc­tion, which de­pended on unini­tial­ized state. Fixes scal­ing of color forms. Fixes in­tro­spec­tion of event han­dlers in morph meta-menus. Improves com­pat­i­bil­ity be­tween old and new bal­loon morphs. Fixes a re­mark­able slip that (1) pre­vented col­lapsed win­dows from ap­ply­ing a new UI theme and (2) in­tro­duced a pos­si­bly sig­nif­i­cant mem­ory leak of win­dows. Fixes an is­sue on ma­cOS where call­ing the VM with ad­di­tional com­mand line ar­gu­ments or plug­ging in ex­ter­nal de­vices led to an in­cor­rect “The VM is con­fig­ured as a sin­gle­ton ap­pli­ca­tion” warn­ing. Improves sta­bil­ity and back­ward com­pat­i­bil­ity when load­ing morphs from files. Fixes cross-com­pat­i­bil­ity and con­cur­rency is­sues with MVC. Improves re­li­a­bil­ity of ha­los.

Improves theme sup­port for progress bars, text morph menus, and di­a­log win­dows.

Improves high-DPI sup­port for but­tons, scroll panes, slid­ers, menus, multi-se­lec­tion lists, trees, drop-shad­ows, the scratch pad, the key­board ex­er­ciser, and oth­ers.

Improves mul­ti­lin­gual sup­port in dif­fer­ent places.

Fixes slips re­gard­ing the world dis­play depth menu, clock con­fig­u­ra­tion changes, search-bar print-its, pro­ject view morph styling, and tran­script count­ing.

Fixes an is­sue when pro­fil­ing code where user events were swal­lowed.

Several lay­out­ing fixes re­gard­ing pro­por­tional lay­outs, text morphs, scroll panes, and trans­for­ma­tion morphs.

Fixes ren­der­ing is­sues with trans­form morphs, poly­gons, multi-se­lec­tion lists, and trees.

Fixes scrolling in nested scroll panes.

In text morphs, im­proves sta­bil­ity of text se­lec­tion and tweaks in­den­ta­tion re­gard­ing empty and blank lines.

Fixes “browse senders” of true, false, and nil, adds miss­ing ac­cess to work­space bind­ings dur­ing ac­cept-its, and im­proves ro­bust­ness of ed­i­tor his­tory.

Fixes bugs in con­struc­tion of text con­tain­ers and con­ver­sion of para­graphs to texts.

In lists, fixes au­to­matic se­lec­tion be­fore drag­ging an item.

Fixes in­cor­rect yel­low-but­ton menu in­vo­ca­tion on but­tons and lists.

Fixes a bug dur­ing menu con­struc­tion, which de­pended on unini­tial­ized state.

Fixes scal­ing of color forms.

Fixes in­tro­spec­tion of event han­dlers in morph meta-menus.

Improves com­pat­i­bil­ity be­tween old and new bal­loon morphs.

Fixes a re­mark­able slip that (1) pre­vented col­lapsed win­dows from ap­ply­ing a new UI theme and (2) in­tro­duced a pos­si­bly sig­nif­i­cant mem­ory leak of win­dows.

Fixes an is­sue on ma­cOS where call­ing the VM with ad­di­tional com­mand line ar­gu­ments or plug­ging in ex­ter­nal de­vices led to an in­cor­rect “The VM is con­fig­ured as a sin­gle­ton ap­pli­ca­tion” warn­ing.

Improves sta­bil­ity and back­ward com­pat­i­bil­ity when load­ing morphs from files.

Fixes cross-com­pat­i­bil­ity and con­cur­rency is­sues with MVC.

Improves re­li­a­bil­ity of ha­los.

Improves per­for­mance of large tree wid­gets, trans­for­ma­tion morphs, and an­i­mated GIFs.

Miscellaneous clean-ups and doc­u­men­ta­tion im­prove­ments for in­put events, ed­i­tor at­trib­utes, and oth­ers.

MorphicExtras (up to MorphicExtras-ct.360)

Introduces Objectland, which is a re­con­struc­tion of the fa­mous “Worlds of Squeak” from 2003 and of­fers a col­or­ful col­lec­tion of ex­am­ples that demon­strate the mul­ti­far­i­ous ca­pa­bil­i­ties of Squeak. Re-adds the clas­sic Etoys race car ex­am­ple and adds sev­eral new ex­am­ples.

After 18 years of spot­less, clean Squeak, rein­tro­duces and up­dates the fa­mous BlobMorph.

For we­b­cams, adds a mir­ror op­tion and ex­tends in­ter­face for dou­ble-buffer­ing. Improves UI and sta­bil­ity of we­b­cam morph.

Improves in­stru­ment menu of score play­ers.

Fixes the “preserve trash” pref­er­ence and im­proves the ro­bust­ness of the pi­ano key­board.

Improves high-DPI sup­port for the ob­jects tool, sev­eral of its tools such as event recorders, score play­ers, record­ing con­trols, and pi­ano key­boards, and sev­eral EToys-related morphs.

Etoys (up to EToys-ct.532)

Restores and re­vises a tu­to­r­ial on paint­ing and cre­at­ing scripts in Etoys.

Adds an undo but­ton to FreeCell.

Improves state in­di­ca­tion in Tetris.

Improves in­stru­ment menu of the midi in­put morph.

Improves ro­bust­ness of the play­ers gallery, the spec­trum an­a­lyzer, and the midi in­put morph. Fixes chang­ing the head­ing of a player.

Clean-ups and fixes for cards and stacks.

Improves high-DPI sup­port for Etoys icons, tile morphs and script ed­i­tors, all games, the ob­jects tool, the spec­trum an­a­lyzer, file lists, watches, and cal­en­dars.

Minor speedups for Kedama and play­ers.

Several clean-ups and refac­tor­ings that im­prove over­all mod­u­lar­ity and avoid un­in­tended de­pen­den­cies of other pack­ages on Etoys.

ST80 (up to ST80-mt.311)

Adds a close item to the world menu.

Improves high-DPI sup­port for sys­tem views.

Adds View>>imageForm for tak­ing a screen­shot of a view and dis­plays it in in­spec­tors.

Adds ed­i­tor short­cut [CMD] + [SHIFT] + [D] for “debug it” (already ex­ists in Morphic).

Miscellaneous fixes and sta­bil­ity im­prove­ments: Ensures con­fir­ma­tion di­a­log be­fore clos­ing the cur­rent MVC pro­ject. Prevents un­ex­pected au­thor-ini­tials di­a­log when open­ing the ST80 world menu for the first time. Avoids an is­sue with stale de­ferred ac­tions in an empty MVC world, which caused emer­gency de­bug­gers to ap­pear only af­ter press­ing a mouse but­ton. In text ed­i­tors, fixes pretty-print­ing and spawn­ing if no com­pat­i­ble model is avail­able. Gently han­dles nil se­lec­tion pro­vided by the model. Fixes an is­sue with re­cently in­tro­duced key­board short­cuts. Repairs folder choosers.

Ensures con­fir­ma­tion di­a­log be­fore clos­ing the cur­rent MVC pro­ject.

Prevents un­ex­pected au­thor-ini­tials di­a­log when open­ing the ST80 world menu for the first time.

Avoids an is­sue with stale de­ferred ac­tions in an empty MVC world, which caused emer­gency de­bug­gers to ap­pear only af­ter press­ing a mouse but­ton.

In text ed­i­tors, fixes pretty-print­ing and spawn­ing if no com­pat­i­ble model is avail­able. Gently han­dles nil se­lec­tion pro­vided by the model. Fixes an is­sue with re­cently in­tro­duced key­board short­cuts.

Repairs folder choosers.

CommandLine (up to CommandLine-eem.27)

Repairs the pref­er­ence “Save snap­shot of im­age on fail­ure”.

Improves UIManager sup­port for var­i­ous file di­alogs, font di­alogs, con­fir­ma­tions, and re­quests.

For in­ter­ac­tive di­a­log re­quests, im­proves the er­ror mes­sage be­fore quit­ting.

~~~ Programming & Tools ~~~

Tools (up to Tools-mt.1366/ToolsTests-ct.137)

Introduces a new tree browser, which dis­plays sys­tem cat­e­gories, classes, and mes­sage cat­e­gories in hi­er­ar­chi­cal panes and in­te­grates Monticello pack­ages. There are also five new pref­er­ences for con­fig­ur­ing its ap­pear­ance. Reworks drag’n’­drop for tree browsers and tra­di­tional browsers to sup­port all mean­ing­ful com­bi­na­tions of panes for copy­ing or mov­ing classes, meth­ods, and cat­e­gories. Adds dou­ble-click sup­port for hi­er­ar­chy tree browsers to switch the cen­tral class. This is es­pe­cially fun for multi-in­her­i­tance hi­er­ar­chies with traits. In the class pane menu, adds new items for gen­er­at­ing a new class or trait. In the mes­sage cat­e­gory menu, adds items to browse all [related] mes­sage cat­e­gories in the sys­tem. In the an­no­ta­tion pane of class de­f­i­n­i­tions, adds a short­cut for read­ing the full class com­ment. Simplifies ex­ten­sion point for cus­tom browsers to reg­is­ter as hi­er­ar­chy browsers. Improves multi-en­vi­ron­ment sup­port for all kinds of browsers and mes­sage sets.

Reworks drag’n’­drop for tree browsers and tra­di­tional browsers to sup­port all mean­ing­ful com­bi­na­tions of panes for copy­ing or mov­ing classes, meth­ods, and cat­e­gories.

Adds dou­ble-click sup­port for hi­er­ar­chy tree browsers to switch the cen­tral class. This is es­pe­cially fun for multi-in­her­i­tance hi­er­ar­chies with traits.

In the class pane menu, adds new items for gen­er­at­ing a new class or trait.

In the mes­sage cat­e­gory menu, adds items to browse all [related] mes­sage cat­e­gories in the sys­tem.

In the an­no­ta­tion pane of class de­f­i­n­i­tions, adds a short­cut for read­ing the full class com­ment.

Simplifies ex­ten­sion point for cus­tom browsers to reg­is­ter as hi­er­ar­chy browsers.

Improves multi-en­vi­ron­ment sup­port for all kinds of browsers and mes­sage sets.

Pick any air­craft or satel­lite pass­ing over your house right now, and go sit in its win­dow seat.

The sky here is the real one out­side — your lo­ca­tion, your weather, this min­ute’s light — with the air­craft and satel­lites that are gen­uinely over­head. Click one and the cam­era fol­lows it; stow away and it takes a seat on board, over real ter­rain.

All of that is drawn in real time, which needs JavaScript and WebGL 2. Switching JavaScript on for this site should do it.