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Deepfakes develop into an enterprise danger for CIOs and CISOs

Dr. Mike
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Deepfakes develop into an enterprise danger for CIOs and CISOs


Rumors, deceptions and outright lies have at all times plagued the enterprise world. Immediately, nevertheless, the fallout from deepfakes and different AI-generated content material is immediate and measurable. A viral second can crater gross sales, injury a model and rattle buyers. A spoofed voice or video can persuade an worker to switch hundreds of thousands of {dollars} to a nonexistent “buyer.”

“It has develop into extremely low cost and simple to create a deepfake and inflict severe injury on an organization or enterprise chief,” mentioned Alfredo Ramirez IV, a senior director in Gartner’s rising applied sciences and tendencies safety division. “The arrival of consumer-grade AI era instruments has created a really low barrier to entry.”

Assaults are extra frequent and extra refined. In accordance with Gartner, 62% of organizations have skilled a deepfake assault involving social engineering prior to now 12 months. “The enterprise is rising as a large goal,” mentioned Hany Farid, a professor {of electrical} engineering and laptop sciences on the College of California, Berkeley Faculty of Data.

Associated:The place CISOs want to rent and develop cybersecurity expertise

For CIOs and CISOs, the challenges — and dangers — are rising, Farid mentioned. It’s vital to evolve to extra superior technical controls together with different instruments and processes that dial down dangers. This trust-based infrastructure – an evolution towards zero belief 2.0 — verifies identification, provenance and intent on the exact second it issues.

“Realizing who and what’s actual and what’s AI-generated is crucial. Reacting shortly to assaults or doubtlessly damaging viral content material is important,” Farid mentioned.

How deepfakes undermine enterprise belief 

Solely a few years in the past, deepfakes have been notoriously straightforward to identify. The additional fingers and malformed objects of early deepfakes have given method to eerily correct artificial content material. Due to low cost and extensively out there software program, even educated specialists with refined forensics instruments have hassle verifying the authenticity  of media. 

“Enterprise leaders should take into consideration defending their corporations,” mentioned Andy Parsons, international head of content material at Adobe.

Among the many threats:  

The issue is larger than many CIOs and CISOs acknowledge. Monetary losses to companies on account of deepfakes and AI fraud within the U.S. might attain $40 billion by 2027, up from $12.3 billion in 2023, based on Deloitte.

Associated:IT errors that escalate into severe cyber-risk

Already, a number of high-profile incidents have rocked corporations. In 2024, a finance worker at Arup, a U.Okay.-based engineering agency, transferred $25 million throughout a video assembly through which each senior chief on display screen was an AI-generated deepfakes. At Qantas Airways, outdoors specialists mentioned that it’s “extremely believable” that voice-cloning was used in 2025 to persuade call-center groups to share credentials for six million clients.

“The post-Covid world has largely shifted to distant interactions. Video calls have develop into the norm,” mentioned Matthew Moynahan, CEO of GetReal Safety, a agency that authenticates and verifies digital media. “There’s a rising quantity of streaming video and different artificial media coming from sources and factors of origin that can’t be verified.”

Why cybersecurity instruments fail towards deepfakes

Combating deepfakes and different generative AI assaults begins with a safety reset. “The very first thing to appreciate is that if the dangerous content material is actual, you will have an issue and if it is faux you will have a distinct drawback,” Farid factors out. “All the things revolves round realizing what you are coping with.”

Trendy cybersecurity instruments fall quick. Whereas they excel at monitoring community site visitors and detecting malware, they can not confirm whether or not an individual on a video name — or pixels in a picture — are actual or faux. “These instruments have no idea what I appear like, what I sound like, or how I am shifting round. Deepfakes fully bypass conventional controls,” Moynahan defined.

Associated:Hackers are utilizing AI bots to scale ransomware negotiations

AI detection strategies alone will not resolve the issue, Farid mentioned. He estimated that many detection instruments are solely about 80% efficient and provide no perception into why the system detected a deepfake within the first place. False-positives and false-negatives are solely a part of the issue. “There is not any explainability. You possibly can’t go right into a courtroom of legislation or clarify to the press or public why a picture or video is actual or faux,” he mentioned.

Much more daunting is the truth that a detection software should function in actual time and connect with videoconferencing platforms like Microsoft Groups and Zoom. It is not sufficient to view a easy confidence rating, mentioned Farid, who can be co-founder and chief science officer at GetReal Safety. “You want immediate verifications throughout workflows, not a three-day forensic evaluation.”

GetReal Safety is considered one of a rising array of companies devoted to combating artificial content material. Others embody Actuality Defender, Deep Media and Sensity AI. Nonetheless one other group of safety companies, together with Hive and Pindrop, tackle AI-generated content material moderation, voice-channel deepfakes, and fraud protection.

Efficient instruments are those who analyze and validate indicators inside media, together with analyzing visible and acoustic cues equivalent to lighting consistency, shadow angles and 3D geometry, together with behavioral biometrics like voice patterns, facial actions and recognized human traits. Sign manipulation and environmental cues, equivalent to an individual’s recognized location and IP tackle, additionally must be analyzed.

How enterprises can defend towards deepfakes

Detection alone will not make the issue go away. Organizations require a broader protection ecosystem that spans intelligence, evaluation, practices and inside safeguards. Narrative intelligence, for instance, displays exterior platforms for disinformation campaigns. This makes it attainable to catch an assault early. Purple-team workout routines expose vulnerabilities, together with the place a spoofed voice, picture or video is prone to slip by means of. And multi-factor verification, utilizing recognized call-back numbers and safety questions that solely an actual CFO or CEO might reply, reduces the chance of a human judgment error.

If an assault does pierce a corporation’s defenses, it is also necessary to reply shortly and decisively. This contains sharing essential details internally and guaranteeing that authorized, communications and advertising groups have the data they should work together with clients, companions, the media and others. A shared playbook is important, Ramirez mentioned.

Digital provenance has additionally emerged as a beneficial useful resource. It traces a video, audio file or picture to its origin and exhibits whether or not it was altered someplace alongside the best way. For instance, the Coalition for Content material Provenance and Authenticity (C2PA) embeds cryptographically signed metadata into content material. Parsons, a member of the C2PA steering committee, likened this to a “diet label.”

C2PA’s content material credentials at the moment are shifting by means of the ISO requirements course of. Together with digital watermarking instruments like Google’s SynthID and tamper-evident logs that create append-only, cryptographically verifiable information, it’s attainable to supply verifiable and defendable media property. “This does not show fact, but it surely does put authenticity inside attain,” Parsons says. “C2PA and cryptographic strategies are an necessary basis for reaching a better degree of trustworthiness.” 

Though it is attainable to strip metadata from these provenance programs — and these frameworks do nothing to cease the unfold of deepfakes and different artificial content material — they set up a baseline for authenticity. As well as, as extra organizations undertake digital provenance instruments, malicious content material turns into simpler to identify.

Concluded Farid: “Oftentimes, you will have just a few seconds to find out whether or not incoming video and different content material is actual or faux, and there are extreme penalties if you happen to make the mistaken determination.”



Tim Cook dinner sums up Steve Jobs in simply 4 phrases

Dr. Mike
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Tim Cook dinner sums up Steve Jobs in simply 4 phrases

Abstract created by Good Solutions AI

In abstract:

  • Macworld stories on Tim Cook dinner’s 2024 letter revealing his transformative first assembly with Steve Jobs when becoming a member of struggling Apple in 1998.
  • Regardless of warnings about Apple’s unsure future, Cook dinner was captivated by Jobs’ inspiring imaginative and prescient and keenness for expertise throughout their encounter.
  • Cook dinner’s choice to hitch Apple led to his eventual succession as the corporate’s seventh CEO 13 years later, following Jobs’ footsteps.

Apple boss Tim Cook dinner joined the corporate in 1998, and has achieved a rare quantity within the years since: he has pushed Apple’s income into the stratosphere, and change into a billionaire within the course of. Nevertheless it seems that the choice to take the job wasn’t as apparent on the time because it now appears looking back.

In a 2024 letter which the Steve Jobs Archive has this week revealed for the primary time, Cook dinner describes the combined emotions with which he weighed up the prospects of working at Cupertino. In these days the corporate wasn’t the reliable company behemoth of 2026.

“On the time,” he writes, “Apple had been struggling and Steve was working to proper a ship that had drifted in his absence. Many individuals doubted the corporate might survive, and I used to be warned that accepting a job there would include dangers.”

That “Steve,” in fact, refers back to the Apple founder who solely the yr earlier than had returned from exile to be Apple’s sixth CEO. Cook dinner describes his first assembly with Steve Jobs as a fateful day when “my want to be a part of one thing actually inspiring would lastly meet its second.” What follows is an enchanting glimpse of the primary encounter between Apple’s two nice leaders.

“When Steve spoke,” Cook dinner remembers, “any trepidation I harbored immediately dissolved. I had by no means met somebody with a lot ardour and imaginative and prescient.

“He spoke with charisma and readability—a couple of future the place expertise might unlock a wellspring of human creativity and potential, connecting us and uplifting us in methods even he had but to think about. In Steve, I discovered an unbelievable mentor who impressed me to develop and problem myself in new and vital methods.”

And the remainder is historical past. Jobs invited Cook dinner to hitch his group of “deeply curious people prepared to work onerous for one thing better than themselves” (these are the latter’s phrases, not the previous’s), and he accepted. Some 13 years later, Cook dinner adopted in Jobs’ footsteps and have become Apple’s seventh CEO.

Cook dinner’s letter, together with others by numerous leaders and creators with a connection to Apple, was initially shared solely with fellows of the Steve Jobs Archive. They’re launched this week as a part of a celebration of what would have been Jobs’ 71st birthday.

Local weather change might threaten monarch mass migration

Dr. Mike
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Local weather change might threaten monarch mass migration


Local weather change could threaten North America’s iconic mass monarch butterfly migration. 

Each fall, thousands and thousands of monarchs (Danaus plexippus) journey 1000’s of kilometers over North America as they go away their breeding grounds in Canada and the US for wintering grounds in a mountainous a part of central Mexico. The butterflies make the trek again north over a number of generations when temperatures heat within the spring and summer time months, following the expansion of milkweed (Asclepias), their most popular meals supply.

However Mexico’s appropriate monarch overwintering habitat might shift south because the local weather adjustments in many years to come back, researchers report February 25 in PLOS Local weather. That might lengthen an already arduous journey and enhance the vitality required to make the journey.  

That additional distance may push some people to remain in Mexico as an alternative of continuous north, says Carolina Ureta, a biologist on the Nationwide Autonomous College of Mexico in Mexico Metropolis. “On this case, the species will not be in peril due to local weather change, however the migration could be.”  

Monarchs are on the decline in North America. Habitat loss, excessive climate, pesticides and parasites are among the many causes fewer bugs attain their winter residence. Populations in central Mexico, as soon as practically 700 million people robust, have declined by greater than 80 p.c because the Nineties. 

Citizen scientists have observed that some monarchs appear to stay in northeastern or central Mexico, says Víctor Sánchez Cordero, a conservation biologist additionally on the Nationwide Autonomous College of Mexico. “That is smart as a result of not all monarch populations worldwide migrate.” Butterflies in Chile, New Zealand and throughout Europe, as an illustration, don’t journey lengthy distances. However whether or not local weather change may alter North American monarchs’ epic transcontinental journey was unknown.

Ureta, Sánchez Cordero and colleagues leveraged laptop simulations to foretell the place in Mexico monarchs may discover milkweed, the one plant on which monarchs lay eggs and that caterpillars feed on. Appropriate monarch habitat might decline by 2070, the group discovered. Some simulations taking local weather, biology and atmosphere into consideration recommend a drop from 19,500 sq. kilometers of supreme habitat to roughly 8,000 sq. kilometers. Local weather change might additionally push that habitat south of the bugs’ current overwintering websites, fracturing and lengthening their migratory route.   

Making that return flight north might take extra vitality than it’s price, Ureta says, and a few people could keep as an alternative. Wing dimension might be a useful indicator to assist researchers determine if butterflies are staying or going: Resident populations in different components of the world are likely to have a smaller wingspan than migrants. 


A Full Information to Bookmarklets

Dr. Mike
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A Full Information to Bookmarklets


You’re certainly no stranger to bookmarks. The flexibility to favourite, save, or “bookmark” internet pages has been a staple browser characteristic for many years. Browsers don’t simply allow you to bookmark internet pages, although. You can even bookmark JavaScript, permitting you to take action rather more than merely save pages.

A JavaScript script saved as a bookmark is named a “bookmarklet,” though some folks additionally use the time period “favelet” or “favlet.” Bookmarklets have been round for the reason that late 90s. The location that coined them, bookmarklets.com, even stays round in the present day. They’re easy and versatile, a reality evidenced by many of the bookmarklets listed on the aforementioned website are nonetheless working in the present day regardless of being untouched for over 20 years.

Whereas bookmarklets have fallen a bit to the wayside in more moderen years as browsers have grown extra succesful and dev instruments have matured, they’re nonetheless a precious instrument in any internet developer’s arsenal. They’re easy however succesful, and no extra software program is required to create or use them. In case you watch any good machinist or engineer at work, they’re continuously constructing instruments and utilities, even one-off contraptions, to handle issues or come to a extra swish answer as they work. As builders, we must always endeavor to do the identical, and bookmarklets are an ideal option to facilitate such a factor.

Making a Bookmarklet

Bookmarklets are extraordinarily simple to make. You write a script in precisely the identical method you’d if writing it for the browser console. You then put it aside as a bookmark, prefixing it with javascript: which designates it to be used within the browser URL bar.

Let’s work via making a brilliant primary bookmarklet, one which sends a easy alert. We’ll take the beneath code, which triggers a message utilizing the alert() technique, and bookmarklet-ify it.

alert("Hey, World!");

Subsequent, we’ll flip it into an Instantly Invoked Perform Expression (IIFE), which has a number of advantages. Firstly, it creates a brand new scope to keep away from polluting the worldwide namespace and prevents our bookmarklet from interfering with JavaScript already on the web page, or vice versa. Secondly, it’ll trigger the bookmarklet to set off upon click on.

We’ll obtain this by enclosing it inside an nameless operate (lambda) (e.g., (() => {})) and suffixing it with ();, which can execute our operate.

(() => {
  alert("Hey, World!");
})();

For reliability throughout browsers, it’s to our profit to URL-encode our bookmarklet to flee particular characters. With out doing so, browsers can go awry and misread our code. Even when it isn’t totally obligatory with a easy bookmarklet like this, it will probably forestall a whole lot of bother that will come up with extra complexity. You possibly can encode your bookmarklet your self utilizing JavaScript’s encodeURIComponent() operate, or you should utilize one among a variety of present instruments. We’ll additionally cut back it to a single line.

(()%3Dpercent3Epercent7Balert(%22Hellopercent2Cpercent20World!%22)%3Bpercent7D)()%3B

We should prefix javascript: in order that our browser is aware of this isn’t a typical URL to a webpage however as a substitute a JavaScript bookmarklet.

javascript:(()%3Dpercent3Epercent7Balert(%22Hellopercent2Cpercent20World!%22)%3Bpercent7D)()%3B

Putting in a Bookmarklet

Lastly, we should add it to our browser as a bookmarklet. As you may count on, that is extraordinarily depending on the browser you’re utilizing.

In Safari on macOS, the simplest manner is to bookmark a webpage after which edit that bookmark right into a bookmarklet:

In Firefox on desktop, the simplest manner is to secondary click on on the bookmark toolbar after which “Add Bookmark…”:

Firefox window showing the Add Bookmark option.

In Chrome on desktop, the simplest manner is to secondary click on on the bookmark toolbar after which “Add web page…”:

Chrome window showing the Add page option.

Many cellular browsers additionally permit the creation and utilization of bookmarks. This may be particularly precious, as browser dev instruments are sometimes unavailable on cellular.

CSS Bookmarklets

You’ve little question been trying on the phrase “JavaScript” above with a glance of disdain. That is CSS-Methods in any case. Worry not, as a result of we will make bookmarklets that apply CSS to our web page in a plethora of how.

My private favourite technique from an authoring perspective is to create a component with my chosen content material:

javascript: (() => {
  var fashion = doc.createElement("fashion");
  fashion.innerHTML = "physique{background:#000;colour:rebeccapurple}";
  doc.head.appendChild(fashion);
})();

The rather more swish strategy is to make use of the CSSStyleSheet interface. This strategy permits for incremental updates and allows you to instantly entry the CSS Object Mannequin (CSSOM) to learn selectors, modify present properties, take away or reorder guidelines, and examine computed construction. The browser additionally validates values enter this fashion, which helps forestall you from inputting damaged CSS. It’s extra complicated but additionally provides you higher management.

javascript: (() => {
  const sheet = new CSSStyleSheet();
  doc.adoptedStyleSheets = [...document.adoptedStyleSheets, sheet];
  sheet.insertRule("physique { border: 5px strong rebeccapurple !vital; }", 0);
  sheet.insertRule("img { filter: distinction(10); }", 1);
})();

As we’re writing CSS for normal utilization throughout no matter web page we want to use our bookmarklet on, you will need to stay conscious that we might run into points with specificity or conflicts with the web page’s present stylesheets. Utilizing !vital is often thought of a foul code odor, however within the context of overriding unknown present kinds, it’s a cheap option to handle our wants.

Limitations

Sadly, there are a number of roadblocks that may hinder our utilization of bookmarklets. Essentially the most pervasive are Content material Safety Insurance policies (CSP). A CSP is a safety characteristic that makes an attempt to stop malicious actions, similar to cross-site scripting assaults, by permitting web sites to manage what will be loaded. You wouldn’t need to permit scripts to run in your financial institution’s web site, as an example. A bookmarklet that depends on cross-origin requests (requests from exterior the present web site) may be very often blocked. For that reason, a bookmarklet ought to ideally be self-contained, moderately than reliant on something exterior. In case you’re suspicious a bookmarklet is being blocked by an internet site’s safety insurance policies, you possibly can verify the console in your browser’s developer instruments for an error.

Firefox blocking a bookmarklet from running due to inline scripts being disallowed.

As bookmarklets are simply URLs, there isn’t any strict restrict to the size specified. In utilization, browsers do impose limits, although they’re increased than you’ll encounter most often. In my very own testing (which can differ by model and platform), listed here are the higher limits I discovered: The most important bookmarklet I might create in each Firefox and Safari was 65536 bytes. Firefox wouldn’t let me create a bookmarklet of any higher size, and Safari would let me create a bookmarklet, however it could do nothing when triggered. The most important bookmarklet I might create in Chrome was 9999999 characters lengthy, and I began having points interacting with the textbox after that time. In case you want one thing longer, you may contemplate loading a script from an exterior location, retaining in thoughts the aforementioned CSP limitations:

javascript:(() => {
  var script=doc.createElement('script');
  script.src="https://instance.com/bookmarklet-script.js";
  doc.physique.appendChild(script);
})();

In any other case, you may contemplate a userscript instrument like TamperMonkey, or, for one thing extra superior, creating your personal browser extension. An alternative choice is making a snippet in your browser developer instruments. Bookmarklets are greatest for small snippets.

Cool Bookmarklets

Now that you simply’ve acquired a gauge on what bookmarklets are and, to an extent, what they’re able to, we will check out some helpful ones. Nonetheless, earlier than we do, I want to stress that you have to be cautious operating bookmarklets you discover on-line. Bookmarklets you discover on-line are code written by another person. As at all times, you have to be cautious, cautious, and discerning. Folks can and have written malicious bookmarklets that steal account credentials or worse.

For that reason, when you paste code beginning with javascript: into the handle bar, browsers mechanically strip the javascript: prefix to stop folks from unwittingly triggering bookmarklets. You’ll have to reintroduce the prefix. To get across the javascript: stripping, bookmarklets are sometimes distributed as hyperlinks on a web page, which you’re anticipated to tug and drop into your bookmarks.

Particular bookmarklets have been talked about on CSS-Methods earlier than. Given the evolution of browsers and the online platform, a lot has been obsoleted now, however some extra modern articles embrace:

You should definitely take a look at the feedback of these posts, for they’re full of numerous nice bookmarklets from the group. Talking of bookmarklets from the group:

In case you’ve acquired any golden bookmarklets that you simply discover precious, you should definitely share them within the feedback.

AI to assist researchers see the larger image in cell biology | MIT Information

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AI to assist researchers see the larger image in cell biology | MIT Information

Learning gene expression in a most cancers affected person’s cells may also help medical biologists perceive the most cancers’s origin and predict the success of various therapies. However cells are complicated and comprise many layers, so how the biologist conducts measurements impacts which knowledge they’ll acquire. As an illustration, measuring proteins in a cell might yield totally different details about the results of most cancers than measuring gene expression or cell morphology.

The place within the cell the knowledge comes from issues. However to seize full details about the state of the cell, scientists typically should conduct many measurements utilizing totally different strategies and analyze them separately. Machine-learning strategies can pace up the method, however present strategies lump all the knowledge from every measurement modality collectively, making it tough to determine which knowledge got here from which a part of the cell.

To beat this drawback, researchers on the Broad Institute of MIT and Harvard and ETH Zurich/Paul Scherrer Institute (PSI) developed a man-made intelligence-driven framework that learns which details about a cell’s state is shared throughout totally different measurement modalities and which info is exclusive to a specific measurement sort.

By pinpointing which info got here from which cell elements, the method supplies a extra holistic view of the cell’s state, making it simpler for a biologist to see the whole image of mobile interactions. This might assist scientists perceive illness mechanisms and monitor the development of most cancers, neurodegenerative issues corresponding to Alzheimer’s, and metabolic ailments like diabetes.

“After we examine cells, one measurement is commonly not adequate, so scientists develop new applied sciences to measure totally different facets of cells. Whereas we have now some ways of taking a look at a cell, on the finish of the day we solely have one underlying cell state. By placing the knowledge from all these measurement modalities collectively in a better approach, we might have a fuller image of the state of the cell,” says lead creator Xinyi Zhang SM ’22, PhD ’25, a former graduate pupil within the MIT Division of Electrical Engineering and Laptop Science (EECS) and an affiliate of the Eric and Wendy Schmidt Heart on the Broad Institute of MIT and Harvard, who’s now a bunch chief at AITHYRA in Vienna, Austria.

Zhang is joined on a paper concerning the work by G.V. Shivashankar, a professor within the Division of Well being Sciences and Know-how at ETH Zurich and head of the Laboratory of Multiscale Bioimaging at PSI; and senior creator Caroline Uhler, a professor in EECS and the Institute for Information, Techniques, and Society (IDSS) at MIT, member of MIT’s Laboratory for Data and Resolution Techniques (LIDS), and director of the Eric and Wendy Schmidt Heart on the Broad Institute. The analysis seems right now in Nature Computational Science.

Manipulating a number of measurements

There are lots of instruments scientists can use to seize details about a cell’s state. As an illustration, they’ll measure RNA to see if the cell is rising, or they’ll measure chromatin morphology to see if the cell is coping with exterior bodily or chemical alerts.

“When scientists carry out multimodal evaluation, they collect info utilizing a number of measurement modalities and combine it to raised perceive the underlying state of the cell. Some info is captured by one modality solely, whereas different info is shared throughout modalities. To completely perceive what is occurring contained in the cell, you will need to know the place the knowledge got here from,” says Shivashankar.

Usually, for scientists, the one solution to kind this out is to conduct a number of particular person experiments and examine the outcomes. This gradual and cumbersome course of limits the quantity of knowledge they’ll collect.

Within the new work, the researchers constructed a machine-learning framework that particularly understands which info overlaps between totally different modalities, and which info is exclusive to a specific modality however not captured by others.

“As a consumer, you’ll be able to merely enter your cell knowledge and it mechanically tells you which of them knowledge are shared and which knowledge are modality-specific,” Zhang says.

To construct this framework, the researchers rethought the standard approach machine-learning fashions are designed to seize and interpret multimodal mobile measurements.

Normally these strategies, often known as autoencoders, have one mannequin for every measurement modality, and every mannequin encodes a separate illustration for the information captured by that modality. The illustration is a compressed model of the enter knowledge that discards any irrelevant particulars.

The MIT methodology has a shared illustration area the place knowledge that overlap between a number of modalities are encoded, in addition to separate areas the place distinctive knowledge from every modality are encoded.

In essence, one can consider it like a Venn diagram of mobile knowledge.

The researchers additionally used a particular, two-step coaching process that helps their mannequin deal with the complexity concerned in deciding which knowledge are shared throughout a number of knowledge modalities. After coaching, the mannequin can establish which knowledge are shared and that are distinctive when fed cell knowledge it has by no means seen earlier than.

Distinguishing knowledge

In assessments on artificial datasets, the framework accurately captured recognized shared and modality-specific info. After they utilized their methodology to real-world single-cell datasets, it comprehensively and mechanically distinguished between gene exercise captured collectively by two measurement modalities, corresponding to transcriptomics and chromatin accessibility, whereas additionally accurately figuring out which info got here from solely a kind of modalities.

As well as, the researchers used their methodology to establish which measurement modality captured a sure protein marker that signifies DNA harm in most cancers sufferers. Understanding the place this info got here from would assist a medical scientist decide which approach they need to use to measure that marker.

“There are too many modalities in a cell and we will’t presumably measure all of them, so we want a prediction software. However then the query is: Which modalities ought to we measure and which modalities ought to we predict? Our methodology can reply that query,” Uhler says.

Sooner or later, the researchers need to allow the mannequin to offer extra interpretable details about the state of the cell. In addition they need to conduct further experiments to make sure it accurately disentangles mobile info and apply the mannequin to a wider vary of medical questions.

“It’s not adequate to only combine the knowledge from all these modalities,” Uhler says. “We will study so much concerning the state of a cell if we fastidiously examine the totally different modalities to grasp how totally different parts of cells regulate one another.”

This analysis is funded, partly, by the Eric and Wendy Schmidt Heart on the Broad Institute, the Swiss Nationwide Science Basis, the U.S. Nationwide Institutes of Well being, the U.S. Workplace of Naval Analysis, AstraZeneca, the MIT-IBM Watson AI Lab, the MIT J-Clinic for Machine Studying and Well being, and a Simons Investigator Award.

The Obtain: Introducing the Crime concern

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The Obtain: Introducing the Crime concern


Know-how has lengthy made crime and its prosecution a sport of cat and mouse. However those self same new applied sciences which have allowed crime to outpace legislation have additionally reenergized legislation enforcement and authorities—providing new methods to root out crime, to collect proof, to surveil folks.

That stress is the important thing to our new March/April concern. Due to applied sciences like cryptocurrency and off-the-shelf autonomous autopilots, there’s by no means been a greater time to do crime. And due to pervasive surveillance and digital infrastructure, there’s by no means been a greater time to struggle it—typically on the expense of what we used to consider as basic civil rights.

Right here’s a sneak peek at what you’ll be able to count on:

+ The fascinating story of what occurred when cyber safety researcher Allison Nixon determined to trace down the mysterious on-line figures threatening to kill her. Learn the total story.

+ AI is already making on-line crimes simpler, however these stories of AI-powered superhacks are significantly overblown. Right here’s why.

+ Welcome to the darkish aspect of crypto’s permissionless dream.

+ Chicago is residence to an enormous monitoring system to trace its residents, together with tens of 1000’s of surveillance cameras. However whereas legislation enforcement claims it’s obligatory to guard public security, privateness activists have likened it to a surveillance panopticon. Learn the total story.

+ Fashionable thieves are stealing luxurious automobiles proper from beneath their producers’ and house owners’ noses. However how are they doing it?

+ How uncrewed narco submarines are poised to shake up how drug smugglers try to evade legislation enforcement.  

+ How revolutionary conservationists are utilizing tech to struggle again towards wildlife traffickers—together with by turning rhinos radioactive. 

Which Samsung Galaxy S26 Extremely shade must you purchase?

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Which Samsung Galaxy S26 Extremely shade must you purchase?


The massive and in cost Samsung Galaxy S26 Extremely is available in 4 colours which can be extensively accessible, and two extra on-line unique shades. With all these upgrades over the last-gen S25 Extremely, it is not arduous to resolve to improve to the S26 Extremely. What’s going to bother you, nonetheless, is selecting which Samsung Galaxy S26 Extremely shade to purchase. Let me ease your process by showcasing all of the accessible colours of their full glory, adopted by some sensible recommendation.

The mighty Galaxy S26 Extremely is available in half a dozen colours

Why you’ll be able to belief Android Central


Our professional reviewers spend hours testing and evaluating services so you’ll be able to select the most effective for you. Discover out extra about how we check.

leaks predicted, Samsung forewent daring shade choices with the S26 Extremely. Gone are the brilliant oranges and reds of yesteryear, changed with a really monotonous blue-toned shade story. Of the six shades of the Galaxy S26 Extremely, just one is a heat hue.

Nobel Prize–successful mind scientist steps down over Epstein ties

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Nobel Prize–successful mind scientist steps down over Epstein ties


February 25, 2026

2 min learn

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Nobel Prize–successful mind scientist steps down over Epstein ties

Richard Axel resigned from his submit co-leading Columbia College’s Mortimer B. Zuckerman Thoughts Mind Conduct Institute over his lengthy ties to Jeffrey Epstein

By Dan Vergano edited by Claire Cameron

Close-up of Richard Axel and Cornelia standing in front of a Breakthrough Prize backdrop

Richard Axel and his spouse, Cornelia Bargmann, in 2019.

On Tuesday Nobel Prize winner Richard Axel resigned as co-director Columbia College’s Mortimer B. Zuckerman Thoughts Mind Conduct Institute over his decade-long affiliation with convicted intercourse offender Jeffrey Epstein. A molecular biologist, Axel shared the 2004 Nobel Prize in Physiology or Drugs for his work revealing how the mind identifies odors.

“My previous affiliation with Jeffrey Epstein was a critical error in judgment, which I deeply remorse,” Axel mentioned in an announcement. He additionally introduced he would not be an investigator with the Howard Hughes Medical Institute. “I apologize for compromising the belief of my associates, college students, and colleagues,” Axel mentioned in the identical assertion.

Axel’s resignation got here after the Columbia College scholar newspaper, the Columbia Spectator, reported earlier this month that Axel and his spouse have been invited to Epstein’s island in 2011—three years after the financier’s conviction for soliciting prostitution from a minor—however that the scientist didn’t go.

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Axel and Epstein, who died in 2019 whereas awaiting trial on federal intercourse trafficking prices, had an extended, public friendship, with the scientist praising Epstein in a 2007 New York Journal article. The title “richard axel” seems 933 instances within the Division of Justice’s just lately launched Epstein information. (Quite a few individuals are talked about within the information, and their look alone doesn’t point out any wrongdoing.)

Axel is amongst a number of high-profile scientists to have been linked to Epstein, who was identified for cultivating shut connections with teachers and science media, together with Scientific American. Axel has up to now written three articles for Scientific American; the latest was revealed in 2006.

In an announcement launched on Tuesday, Columbia College mentioned that “the College has seen no proof that Dr. Axel violated any College coverage or the legislation.” Axel will proceed his analysis on the college, in keeping with the assertion. Axel didn’t instantly reply to a request for remark from Scientific American.

Editor’s Word (2/25/26): It is a creating story and could also be up to date.

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A number of Brokers Auditing Your Diff-in-Diff Code (Half 1)

Dr. Mike
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0
A number of Brokers Auditing Your Diff-in-Diff Code (Half 1)


That is a part of an extended sequence I’m doing on Claude Code for quantitative social sciences. I’m going to try (fingers crossed) to put in writing a shorter submit at present. Earlier than I do, I wished to thank everybody for his or her assist of the substack. It’s a labor of affection. The substack offers me a possibility to put in writing and specific myself creatively whereas additionally sharing what I’ve discovered about this or that, be it causal inference, AI or some random kick I’m on.

I filmed a video walkthrough of me doing this train. You’ll see that video right here. Be aware that throughout the strategy of the code audit, I spotted that there have been two extra packages that I wished to guage. As such we’ll illustrate the code audit thought utilizing 5 diff-in-diff packages: two Stata packages, two python packages, and one R package deal. We will likely be focusing primarily on the Callaway and Sant’Anna estimator, however that is actually agnostic in regards to the estimator as we can even be specializing in the preprocessing phases, too. The opening of this substack explains the thought behind it — impartial errors — and the remainder explains the implementation. The video walks you thru precisely what I did. I hope you discover this beneficial. This’ll be the primary of many diff-in-diff workout routines, so buckle up!

If you’re a standard reader, perhaps think about turning into a paying subscriber. I’ve set the worth on the lowest worth level ($5/mo) that substack permits. Take pleasure in!

Immediately’s substack would be the first of many wherein I illustrate utilizing Claude Code in a challenge the place the duties embrace a pipeline of processing knowledge and estimating common therapy results utilizing the Callaway and Sant’Anna technique. However this one’s fairly slender in focus, which I feel will make it extra normal to all individuals, no matter whether or not they’re utilizing diff-in-diff. Immediately’s substack is about code audits utilizing a number of brokers to duplicate code in a number of languages. Right here is the thought:

  • I feel we should always reap the benefits of Claude Code’s brokers to “audit our code” and achieve this aggressively. Virtually prefer it’s a well being inspector whose objective is to close us down.

  • I feel we are able to use Claude Code’s skill to talk in a number of languages to do that.

And to speak about this, I’ll illustrate it with some easy examples, together with a video stroll via of me utilizing it for some easy duties.

Hallucination as Measurement Error

We should within the social sciences embrace utilizing Claude Code in our workflow to eradicate all errors that it may be used to cease. There are a number of kinds of errors, and their causes are because of many issues — issues which can be completely unrelated to 1 one other. A few of them are reasoning errors, and maybe Claude Code can catch these (I’ve discovered it catches a good quantity), however the ones I need to discuss are coding errors.

As we shift in the direction of AI brokers writing an increasing number of, if not all, of our code, we should always think about the likelihood that AI brokers primarily based on giant language fashions just like the pre-trained generative transformer (GPT) will at all times have issues hallucinating. However what if hallucination may be conceived of as measurement error. That’s, hallucination within the context of writing code is random as a result of LLM simply probabilistically writing down the incorrect executed code.

I’m not saying to you that I know that is the case a lot as I’m saying that it could possibly be a handy fiction for us as quantitative social sciences to speak that approach. For one, it’s a approach of speaking we’re way more conversant in than we’re with the probabilistic nature of the LLMs within the first place. I doubt many people have learn the unique “Consideration is All You Want” by Vaswani, et al. (which has now 232,500 cites since its first look in 2017). However I feel all of us have a minimum of in some level in our life learn in any econometrics textbook the concept there exists a variable that has been recorded incorrectly and as such the variable is classically incorrect. Classically incorrect within the sense that the variable’s values will likely be completely different from the “true worth” by that worth plus some random noise, often centered at zero and often standardized to have some fastened variance, like a standard distribution. In such circumstances, regressions utilizing it is going to have coefficients on that variable that are attenuated in the direction of zero.

I would really like so that you can be open to that language, however utilized to the code Claude Code generates for our evaluation. It could possibly be someplace hidden within the pipeline. It could possibly be someplace within the regression instructions. It could possibly be someplace within the lifting of the regression output into automated tables and figures. Perhaps it’s one thing seemingly small like permitting for the pattern composition to vary as fastened results are added in, not realizing that not all the pattern had these fastened results, inflicting 50% of the pattern to drop. Or perhaps it’s a merge syntax error. It could possibly be even that basic Stata error:

substitute olddog = 10 if olddog>10

which these of us who’re outdated canine will know not solely prime codes all values of olddog at 10 when olddog is bigger than 10. It additionally replaces olddog to be 10 for all lacking values too.

That’s an outdated error, well-known to Stata customers, lots of whom needed to be taught it both the arduous approach or on the Stata listserv from the prolific, terribly useful and Stata legend Nick Cox. However word that that command is itself distinctive to Stata syntax.

So, let’s do that. Let’s simply assume that 9 instances out of 10 Claude Code doesn’t make that mistake. Claude Code is aware of, as a result of it has been educated on each conceivable writing about Stata, together with the manuals, and together with Nick’s personal phrases, that one of many right methods to do it’s this:

substitute olddog = 10 if olddog>10 & olddog~=.

However on today, Claude Code randomly left that final half out. And since on that day, Claude Code randomly left that final half out, your olddog variable has been prime coded at 10 each for these rows that had values larger than 10 (e.g., olddog = 15), in addition to these rows whose olddog variable was lacking (i.e., olddog = .). Why did it make the error then in your code at present? It made that mistake randomly. However you solely ran the pipeline as soon as; you solely generated the pipeline as soon as. And as such, you pulled a foul draw unknowingly, and because it did run, and it didn’t run into an error, the syntax error cascaded down via your pipeline into your evaluation with systematic measurement error inflicting your outcomes to be primarily based on mismeasured variables that could possibly be extreme relying on what number of lacking values there are within the knowledge.

Hallucination Errors are Unbiased Throughout Languages

So here’s what I suggest. I suggest that you simply assume a second factor. I suggest that you simply think about that Claude Code will randomly hallucinate its code. And that since you’re offloading a number of the cognitive work to it, and that your expertise are depreciating on account of that, then you will need to discover a solution to insert verification steps wherever potential utilizing Claude Code in a focused method. And I suggest that you simply think about this:

  • R will hallucinate with some probabilistic error, ε_R

  • Python will hallucinate with some probabilistic error, ε_P

  • Stata will hallucinate with some probabilistic error, ε_S

If the errors are impartial, the chance all three hallucinate the identical incorrect result’s ε_R × ε_P × ε_S — a really small quantity. And I feel it’s affordable to say that they gained’t as a result of if the errors actually are syntax errors, then we shouldn’t anticipate it to point out up on the similar time in the identical place. If all three errors are pairwise impartial, then we are able to write down these three covariance equations and set them to equal to zero:

  1. Cov(ε_R, ε_P) = 0

  2. Cov(ε_R, ε_S) = 0

  3. Cov(ε_P, ε_S) = 0

Recall that these are zero due to the definition of covariance and the way in which wherein the imply of the product of two random variables which can be impartial breaks out into the product of the imply of every one, inflicting your entire covariance equation to be zero.

(textual content{Cov}(varepsilon_i, varepsilon_j)
= E[varepsilon_i varepsilon_j] – E[varepsilon_i]E[varepsilon_j]
= E[varepsilon_i]E[varepsilon_j] – E[varepsilon_i]E[varepsilon_j]
= 0
)

That is the precept I would like you to remember: that if Claude Code or any AI Agent is making errors because of language-specific syntax, and whether it is random, then it’s affordable to imagine that the errors are stochastic and due to this fact impartial of each other. Which lets you justify incorporating not simply code audits into your course of, however replication of your complete challenge in different languages.

Requesting Code Audits To Replicate In A number of Languages

Which leads me to my subsequent level: get Claude Code to audit your code systematically like a well being inspector, in addition to replicate your code in two different languages. These are two separate duties, and whereas many individuals are already integrating into their AI Agent workflow “code audits” by hyper-antagonistic subagents, that won’t essentially imply that they’re getting hyper-antagonistic subagents to duplicate their code within the different languages already put in in your machine first.

What I feel you need due to this fact is a workflow with a pipeline of code that from begin to end is totally replicated in two different languages such that at every stage, your code creates tables and figures which have the very same values for all variables, and check statistics the identical, right down to a number of trailing digits.

This solely works with the code that’s non-random although. It gained’t work with bootstrapping, for example, which is itself primarily based on seeds which can be most likely distinctive to that language. So you might not have the ability to do that to verify bootstrapped normal errors for the reason that resampling is random. Different examples the place the sort of code audit gained’t work is:

  • Simulation-based estimators — simulated MLE, technique of simulated moments (these draw random simulations as a part of the chance approximation)

  • Bayesian MCMC — Gibbs sampling, Hamiltonian Monte Carlo (Stan, brms)

  • EM algorithms with random beginning factors — combination fashions typically randomize preliminary cluster assignments

  • Machine studying — SGD, random forests, neural internet initialization

However it is going to work for a lot of different issues, together with fundamental processing duties (e.g., cleansing variables, merges) in addition to many quite common statistical modeling strategies (e.g., OLS, difference-in-differences, instrumental variables, F assessments, analytical normal errors, R-squared).

So, what you need to do is have Claude Code not solely audit the code utilizing its personal reasoning. You need to even have Claude Code replicate the code, from begin to end (i.e., together with the pre-analysis processing phases in your pipeline), in two different languages, after which have an agent verify that the output produced in tables for all three are equivalent.

Distinction-in-Variations As Case Research

So, right here’s to the video stroll via. We now have 5 language-specific packaged code for implementing each normal difference-in-differences, in addition to extra advanced difference-in-differences utilizing differential timing and the inclusion of covariates. Subsequently, it’s potential to do the form of code audit I’m describing for difference-in-differences. Those we’ll use are csdid (Stata), csdid2 (Stata), did (R), variations (python) and diff-diff (python). And I will likely be specializing in auditing the components of the pipeline and evaluation that’s deterministic.

Our instance will come from this Brazilian examine that I additionally analyze in my forthcoming guide, Causal Inference: The Remix, which will likely be revealed this summer time by Yale College Press. Right here’s the paper in query.

What I do on this video stroll via is straightforward. I merely have Claude Code generate the code to estimate occasion examine plots of the impact of the CAPS deinstitutionalization (i.e., closing psychological well being establishments) in Brazil on homicides, which is without doubt one of the a number of outcomes that the authors, Mateus Dias and Luiz Felipe Fontes, use of their fascinating and vital examine about psychological well being reform and hospitalization.

To do that, I’ll use a program referred to as Brazil.do this I wrote. It’s a prolonged set of code, however we could have Claude Code take solely a portion of it that cleans and estimates the impact utilizing csdid and csdid2 in Stata. I’m utilizing, in different phrases, the Callaway and Sant’Anna technique because it is without doubt one of the extra widespread strategies used when estimating combination results below differential timing. However, csdid can be a person created package deal. The unique command was in R referred to as did. And there are additionally two packages in python. There may be one written by Isaac Gerber in python as effectively. You will discover that one right here.

However there may be really a second python package deal for diff-in-diff referred to as variations. It’s written by Bernardo Dionisi. So we can even replicate the evaluation in his diff-in-diff package deal in python, alongside Isaac’s.

Conclusion

That is going to be the primary of many posts utilizing Claude Code to estimate diff-in-diff, however at present’s was simply in regards to the “code audit” utilizing a really particular model of my referee2 persona. And I need to cease right here as a result of this can be a prolonged submit already as it’s. However within the subsequent submit, I’ll evaluation the outcomes with you and we’ll attempt to get to the underside as as to whether or not there are issues which can be as a result of audit, the packages, each or neither. However the level at present is simply as an instance a selected workflow I’ve been engaged on to implement verification aggressively into evaluation utilizing Claude Code, however doing so with a really slender but extraordinarily frequent and excessive worth job — the estimating of therapy results utilizing diff-in-diff which for the time being may be carried out doing a minimum of 5 completely different packages (2 in Stata, 1 in R, 2 in python). So we’ll see within the subsequent assembly the way it went!

Mac Mini vs. Cloud VPS

Dr. Mike
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0
Mac Mini vs. Cloud VPS


As of current, the AI group has shifted its obsession from chatbots to brokers. On the middle of this storm is OpenClaw (previously Moltbot), an open-source framework that permits AI to reside in your {hardware} and act in your behalf.

Nonetheless, an enormous rift has fashioned within the developer group: The {Hardware} Struggle. On one aspect, influencers are shopping for the brand new Mac Mini M4 as the last word “Agent Command Middle.” On the opposite, senior DevOps engineers argue that operating domestically is a “safety suicide mission,” advocating for remoted Cloud VPS deployments.

This text offers a comparability of efficiency, safety, and value of Mac mini vs Cloud VPS that will help you determine the place your agent ought to reside.

Mac Mini M4: The “Gold Commonplace” for Private Use

For a lot of, the Mac Mini is the one logical alternative for OpenClaw. For the reason that undertaking’s rebranding (from Clawdbot → Moltbot → OpenClaw) in January 2026, the “M-series” structure has turn into the reference {hardware} for a number of key causes.

  • iMessage Gravity: In order for you your OpenClaw agent to answer to your blue-bubble texts, you should have a macOS atmosphere. A VPS can not do that natively.
  • Native Inference Effectivity: Utilizing Apple’s MLX framework, a Mac Mini can run a 7B or 14B mannequin domestically at 40+ tokens per second. In the event you did this on a VPS, you’d want a devoted GPU occasion costing over $100/month.
  • Bodily Sovereignty: Your information by no means leaves your home. For customers accustomed to conventional computing, this “air-gapped” really feel is a serious promoting level.

The M4’s Unified Reminiscence permits the CPU and GPU to share the identical RAM pool. Quicker processing pace and no delays. The most affordable M4 Mac mini you should purchase begins at ₹60,000 (~$600).

Cloud VPS: The “Sandboxed” Agent

VPS or Digital Personal Server has gained reputation because the {hardware} value for operating LLMs turned infeasible. Whereas the Mac Mini is glossy, the privileges required for it perform correctly in an working methods is alarming.

  • Safety: A current vulnerability (CVE-2026-25253) allowed 1-click Distant Code Execution utilizing OpenClaw. On a Mac Mini, an attacker positive aspects a foothold in your house community. On a VPS, they get a “bare” Linux field with nothing to steal.
  • Uptime is King: An agent meant to observe your shares or server logs 24/7 can’t be topic to your own home’s “pressured macOS updates” or a cat tripping over the facility twine.
  • Scalability: In case your agent grows from a easy chatbot to a multi-agent crew (utilizing the favored Moltworker structure), you’ll be able to improve a VPS from 2GB to 32GB of RAM with a single click on. You may’t add extra RAM right into a Mac Mini (because it’s soldered).

Not like Mac mini, which is exclusive and particular of itself, Cloud VPS suppliers are totally different and serve totally different audiences. The names go from Hostinger which gives quite a lot of VPS plans to select from, all the way in which to Contabo which gives AI assisted internet hosting at as little as $4 monthly.

Technical Comparability

Metric Mac Mini M4 (16GB/256GB) Entry-Degree VPS (e.g., Hostinger/DO)
Preliminary Value $599 (One-time) $0 (Upfront)
Month-to-month Value ~$2 (Electrical energy) $5 – $15 (Subscription)
Reliability Susceptible to house Wi-Fi/Energy Outage 99.9% Uptime (Knowledge Middle)
Scope iMessage, Native Information, HomeKit Webhooks, Slack, Telegram
Safety Threat Excessive (Entry to Native Community) Low (Remoted Sandbox)
Inference Excessive (Steel GPU / 45+ tok/s) CPU-bound (Gradual for native LLMs)

The winners throughout the 6 features are break up evenly between the 2 infrastructures. This implies there isn’t a transparent winner, and the utilization is closely state of affairs particular. Except, you need each!

The “Hybrid” Setup!

Probably the most subtle customers aren’t selecting one. As an alternative, they’re utilizing a Hybrid Structure.

  1. The Gateway (VPS): Runs the OpenClaw management panel and public-facing Telegram/WhatsApp bots.
  2. The Employee (Mac Mini): An area node that connects to the VPS through a safe Tailscale tunnel.

This lets you hold your iMessage integration and native file entry whereas maintaining the “uncovered” a part of the agent on a hardened cloud server. Albeit costly, this hybrid setup makes up for the limitation of both infrastructure.

The Selection

In case your aim is a private assistant that manages your texts and native life, the Mac Mini M4 is an unbeatable piece of {hardware}, supplied you wrap OpenClaw in a non-root Docker container (for safety).

Nonetheless, in case you are constructing autonomous workflows for work or analysis, a Cloud VPS is the one method to make sure the safety and uptime required in 2026.

Don’t let the “aesthetic” of a Mac Mini in your desk distract you from the architectural actuality of agentic safety. Additionally, the massive upfront value of over $500 isn’t bearable by many. Contemplating the tech evolves with time, counting on devoted VPS suppliers will probably be prudent for many customers. 

Ceaselessly Requested Questions

Q1. What’s a VPS in OpenClaw deployment?

A. A VPS is a distant cloud server that runs your agent securely and stays on-line 24/7.

Q2. Why would somebody select a Mac Mini for OpenClaw?

A. It allows native iMessage integration and sooner native LLM efficiency utilizing Apple’s unified reminiscence.

Q3. What’s the good thing about a hybrid OpenClaw setup?

A. It combines VPS safety and uptime with Mac Mini entry to native recordsdata and macOS-only options.

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