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OpenAI, Anthropic AI agents targeted real people and systems in cyber tests

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Artificial Intelligence

OpenAI and Anthropic have confirmed that their AI models were involved in separate, newly disclosed third-party cybersecurity testing incidents that resulted in a real website being breached and social engineering attacks against people outside the intended testing boundaries.

These incidents are unrelated to the previously disclosed Hugging Face breach, in which OpenAI models hacked the AI platform and used exposed credentials to breach accounts at four other third-party services during another cybersecurity evaluation.

OpenAI disclosed the two new incidents on Tuesday, saying they occurred during evaluations conducted by the UK AI Security Institute and cybersecurity testing company Irregular.

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Spear-phishing attacks on GitHub project maintainers

The UK AI Security Institute, commonly known as AISI, is a government research organization that evaluates the capabilities and risks of advanced AI models.

During a recent cyber-range evaluation, AISI says agents powered by Anthropic’s Claude Mythos 5 and OpenAI’s GPT-5.6 Sol took unsanctioned actions on the public internet while trying to complete simulated hacking challenges.

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Across 122 evaluation attempts, AISI identified 19 unsanctioned actions on the live internet in 10 runs. Seventeen involved Mythos 5 and two involved GPT-5.6 Sol.

AISI says the attempts were unsuccessful and that it found no resulting real-world harm.

“These attempts were unsuccessful, and our investigations have not evidenced any resulting real-world harm,” AISI said in a separate advisory.

“But this is the first time we have seen risks around autonomy and deception manifest this clearly, without specific prompting, in the real-world.  “

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AISI intentionally enabled open internet access and disabled the model providers’ cyber classifiers to measure the models’ underlying capabilities. However, the agents were only authorized to attack the simulated cyber range and were not explicitly told how they could use their internet access or instructed to avoid interacting with real people and systems.

Anthropic confirmed to BleepingComputer that AISI was testing a version of Claude Mythos 5 but said it is still investigating and cannot yet confirm all of the technical details described in AISI’s report.

The company said it was notified on Monday and is working with AISI to obtain the evaluation transcripts needed to conduct its own review.

“We’re grateful to the UK AISI for their leadership on this incident, which underscores the need for a broader conversation about how to safely evaluate increasingly capable AI agents,” an Anthropic spokesperson told BleepingComputer.

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“As we shared after disclosing our own incident last week, the field needs stronger, shared standards for how evaluation environments are built and secured. We look forward to partnering with the UK AISI to learn more about this incident as we conduct our own investigation.”

Anthropic noted that AISI tested Mythos 5 without its standard cyber safeguards enabled and that this is not the same configuration available to customers. AISI says its evaluation design and configurations may have contributed to the behavior, but did not anticipate how the agent would show “signs of novel, potentially deceptive behaviours”.

AISI says a Mythos 5 agent searched the internet for terms related to the cyber challenge and mistakenly concluded that an unrelated public GitHub repository was connected to the test.

The agent then attempted a supply-chain attack by submitting malicious code to the real open-source project, believing that compromising the software could provide a path into a machine within the simulated range.

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Most concerning, the agent researched the project’s maintainers, created multiple fake GitHub identities, and used those accounts in social engineering attacks to push the maintainer into approving a malicious pull request.

When a human reviewer warned that the pull request contained malware, the agent denied the accusation and used other fake accounts it controlled to pressure the maintainer and create the appearance that independent users had reviewed and approved the changes.

Overview of one AI agent’s social engineering attack against a project maintainer
Overview of one AI agent’s social engineering attack against a project maintainer
Source: AISI

The agent continued its social engineering attacks by hiding its identity using Tor and proxy services and creating disposable GitHub accounts.

It sent five targeted emails to the developers, with some containing malware and others attempting to persuade them to approve the code change.

The agent also posted bug reports containing malicious code and hidden prompt-injection instructions designed to trick AI coding assistants into taking unintended actions.

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When a real person questioned one of the posts, the agent edited it to conceal the malicious content. In another attempt, it signed off in Danish to appear more convincing to a Danish-speaking maintainer.

AISI researchers found that agents coordinated with each other across different evaluation runs, using a shared GitHub repository as a message board to leave instructions for one another.

“This is the first time AISI has seen deception of this severity that was targeted at a real person, unprompted, in the real world,” the institute said.

AISI says it remains unclear when, or whether, the model understood that it was interacting with real people rather than simulated targets.

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OpenAI model hacked real website during simulated CTF

The second newly disclosed incident occurred during Capture-the-Flag evaluations conducted by Irregular that were supposed to be isolated from the internet.

In one test, the fictional target’s name happened to match a real domain, causing the model to exploit a real website that it believed was part of the simulated challenge.

While Irregular’s testing environment was supposed to be isolated from the internet, a misconfiguration allowed OpenAI models to access the public internet and target the real website.

“Based on Irregular’s investigation, the model also found and used credentials to operate that same site,” OpenAI said.

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OpenAI says the model exploited a basic vulnerability rather than using a zero-day or escaping its testing environment.

OpenAI says Irregular has not discovered any impact beyond the affected site’s own data, but its investigation remains ongoing. OpenAI says the company is preparing a white paper on containment and securely conducting cyber evaluations.


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Revolut’s Nik Storonsky closes a $500m fund for his algorithm-run venture firm QuantumLight

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Nik Storonsky, the man behind Revolut, has closed a $500m second fund for QuantumLight, the algorithmic venture-capital firm he co-founded to let software, rather than partners, decide where the money goes.

The fund is double the size of QuantumLight’s $250m debut vehicle from last year, a swift escalation for an outfit still trying to prove that data can out-pick the humans.

Nik Storonsky, whose personal fortune has climbed with Revolut and who is reportedly in line for a vast share award, is the firm’s most conspicuous backer.

QuantumLight’s pitch is a direct challenge to the clubby traditions of venture capital. Instead of a bench of star partners trading on instinct and network, the firm runs a systematic, data-driven model that screens companies at scale and generates investment decisions quantitatively, something closer to a quant hedge fund than a Sand Hill Road partnership.

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The approach is of a piece with Nik Storonsky’s reputation as fintech’s most relentless optimiser. He built Revolut into Europe’s most valuable private tech company on a culture of aggressive targets and data over sentiment, and last year QuantumLight published a hiring playbook distilling the management methods behind that rise, a set of blunt tips that read like an operating manual for high-growth companies.

QuantumLight applies the same conviction, that most decisions are better made by system than by instinct, to the business of picking winners.

Doubling the fund in barely a year is a statement of confidence, though whose confidence is the interesting question.

QuantumLight has not detailed its outside backers, and Storonsky’s own wealth gives him ample means to seed his own experiments.

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An oversubscribed close suggests limited partners are buying the thesis too, wagering that algorithmic sourcing can surface growth-stage companies that traditional funds overlook, and that the model deserves twice the firepower after a single year.

QuantumLight’s first fund is only a year old, far too young to have produced the exits that would show whether the machine actually beats the market, and venture returns take the better part of a decade to judge.

Plenty of firms have promised to “quant-ify” venture capital before, and the discipline’s best returns still tend to come from a handful of outlier bets that are notoriously hard to model, precisely because they look unreasonable at the moment they are made.

Still, the timing is apt. As AI reshapes every knowledge industry, the people who allocate capital are hardly exempt, and a wave of funds now claim to use machine learning to source deals, score founders and time markets.

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QuantumLight is among the most committed to the idea, and the most credibly funded, which makes its record a useful test case for whether software can genuinely industrialise a trade that has always prized taste and relationships over spreadsheets.

There is also the matter of a chief executive’s attention. Storonsky is steering Revolut through a pivotal stretch, having lately won a French banking licence and pushed into business banking, with an IPO reportedly a couple of years away and likely to list in the US, all while running a second act in venture capital.

Founders are rarely one-company people, but the split focus is the kind of thing Revolut’s eventual public-market investors may come to weigh.

For now, $500m is a serious sum with which to test a serious idea: that the qualities venture capitalists have always sold, judgment, instinct, a good eye, can be replaced, or at least bettered, by code.

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If Nik Storonsky is right, QuantumLight will look prescient. If he is wrong, it will be an expensive reminder that some bets resist being reduced to a model. Either way, the experiment has just doubled in size.

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Apple will begin assembling Mac Minis at Foxconn’s Houston plant later this year

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In context: A new Mac Mini assembly line at Foxconn’s Houston facility is expected to begin production later this year, expanding Apple’s US manufacturing footprint for AI-related hardware. The project is part of Apple’s effort to increase domestic production while continuing to rely on contract manufacturers and an international supply chain.

The line will operate in a new 170,000-square-foot space at the plant, which already makes AI servers for Apple. Foxconn is funding the assembly-line buildout, while Apple has committed to purchasing the products made there.

The Mac Mini has seen stronger demand over the past year, particularly among customers using the compact desktop to run AI models at home. Its planned Houston production also comes after Apple discontinued the Mac Pro, which was assembled in the US at a Flextronics plant that President Trump visited with Apple CEO Tim Cook in 2019.

Cook and Commerce Secretary Howard Lutnick toured the Houston site last week. The visit included a new manufacturing school that Apple is opening to provide hands-on training for small and midsize US companies. Apple previously launched a classroom-based manufacturing program in Detroit.

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“Advanced manufacturing is where the puck is going,” Lutnick told workers taking an Apple manufacturing course. “The problem is we need to train Americans.”

Cook said Apple’s US investment plans reflect its broader commitment to domestic production. “We believe in the promise of this nation and we’re proud to put our money where our mouth is,” he said in a speech.

Apple’s investment strategy relies heavily on its purchasing power rather than on building and owning factories. The company’s capital spending remains far below that of Amazon, Microsoft, and Google, which have made major investments in AI infrastructure and semiconductor capacity. Apple’s total capital expenditures since 2023 are less than what each of those companies spent in its most recent quarter.

That model is evident in Houston. Foxconn is paying to build the production lines, while Apple is supporting the project through product orders. The arrangement preserves Apple’s long-standing reliance on manufacturing partners while allowing it to use its supply-chain scale to influence where production and component sourcing take place.

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Apple has made similar commitments in semiconductors. The company is among the businesses that have agreed to buy chip wafers from TSMC’s Arizona plant, a project expected to cost more than $200 billion. Apple has also reached a preliminary agreement for Intel to manufacture some of its device chips and said it plans to spend $30 billion on US-made chips from Broadcom.

The company has pledged to invest $600 billion in the US over four years. The total includes spending already planned for its American business, including employee pay, retail and corporate operations, and purchases from domestic suppliers.

The administration has encouraged Apple to expand its US manufacturing operations. President Trump has pressed the company to make iPhones domestically, but Apple has not announced such plans. Instead, it is expanding iPhone assembly in India.

The Houston event was among Cook’s final public appearances as Apple’s chief executive. He is expected to become chairman next month, with John Ternus, Apple’s longtime hardware engineering chief, expected to succeed him as CEO.

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Image credit: The Wall Street Journal

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Microsoft confirms outage affecting search in Microsoft 365 apps

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Microsoft 365

Microsoft says some users are experiencing issues searching in Microsoft 365 apps, including Outlook on the web, Outlook desktop, SharePoint Online, and OneDrive.

According to an incident report seen by BleepingComputer and tracked under MO1456424 in the Microsoft 365 Admin Center, the root cause is what Microsoft describes as a recent deployment that causes resource utilization problems.

“Impact is specific to some users served through the affected infrastructure who are attempting to search for content in SharePoint Online, OneDrive, Outlook on the web, or Outlook desktop,” Microsoft said.

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“Our investigation identified that a recent deployment introduced a resource utilization inefficiency issue, leading to impact.”

Microsoft says it has already developed a fix and deployed it to reduce resource pressure and restore service for all affected Microsoft 365 users.

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While the company has yet to share which regions were impacted by this outage, it tagged it as an incident, which usually describes a critical service issue with noticeable user impact.

Last year, Microsoft mitigated similar incidents that broke file search for OneDrive, Outlook on the web, and SharePoint Online users.

In July, it also addressed a massive outage that took down Azure and Microsoft 365 services for users in North America after a bug in its automated network maintenance request system removed IP routes from more devices than intended.

On Monday, Microsoft resolved another incident that brought down GitHub, its website, the API, and many other services for more than eight hours, with users reporting server errors when trying to access GitHub, while others encountered problems loading commits, repositories, and Pull Request pages.

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Samsung’s Galaxy Z Fold 9 could get an even wider screen

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Samsung could be planning an even wider Galaxy Z Fold for 2027. A new report suggests the company is working on a foldable specifically designed to make video viewing more comfortable.

According to ETNews, Samsung has expanded its planned 2027 foldable lineup to five devices. Alongside the expected Galaxy Z Fold 9, Galaxy Z Fold 9 Ultra, Galaxy Z Flip 9 and a new Galaxy Z TriFold, the company is reportedly developing a second wide-format foldable.

Details are still thin, but the key difference could be its display. The report says Samsung is working on a screen aspect ratio specifically optimised for watching video instead of sticking with the 4:3 ratio used by the Galaxy Z Fold 8.

That could mean a noticeably wider display when the phone is unfolded. Samsung hasn’t revealed the exact ratio, so 16:9 or 16:10 are only possibilities at this stage, rather than confirmed specifications.

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The idea makes some sense for a foldable. The Galaxy Z Fold 8’s large internal screen is useful for everything from multitasking to watching films. However, its squarer 4:3 shape isn’t an especially natural fit for most widescreen video. A wider panel could reduce the amount of unused space around 16:9 content.

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It’s worth stressing that this isn’t necessarily the Galaxy Z Fold 9 itself. ETNews describes the device as a second wide-format model in Samsung’s 2027 range. Meanwhile, specifications and even the final positioning remain unclear. The report does, however, suggest Samsung is looking beyond simply repeating the current Fold formula.

The wider foldable is expected to launch in the second half of 2027 alongside the rest of Samsung’s next-generation foldable lineup.

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For now, the Galaxy Z Fold 8 is the device to watch. However, Samsung’s reported plans suggest its foldable strategy could get considerably more interesting next year.

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The next phase of AI adoption could change the future of supply chains

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As global supply chains remain exposed to geopolitical and climate uncertainty, retail and consumer packaged goods (CPG) businesses face challenges of fluctuating prices and demand. In the United Kingdom, supply chain volatility is adding to uncertainty in raw material and packaging costs to impact CPG companies’ production economics.

Research has found that a huge majority of British retailers were not confident of scaling up their supply chain operations to meet the expected increase in consumer demand. In fact, 43% of retail leaders ranked supply chain issues among their top three business challenges in 2025, highlighting widespread concern over operational capacity in the face of rising demand and cost uncertainty.

Ambeshwar Nath

EVP & Industry Head (EMEA) for Consumer Goods, Retail & Logistics at Infosys.

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A botched Mastercard update left Australian shoppers unable to pay

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Facepalm: Over the weekend, many Australian shoppers found their Mastercard payments declined mid-purchase. The US-based company confirmed the issue Saturday and says its network is now back to normal. While the disruption technically hit Mastercard’s global network, it was felt most acutely by shoppers in Australia.

An undisclosed number of Australian customers were unable to pay with their cards during Saturday’s shopping trips. As reported by ABC, Mastercard quickly identified the cause of the new outage: a scheduled system update that went wrong, triggering declined transactions for a period of several hours.

The situation was resolved by the end of the day, Mastercard said, though the company hasn’t shared specifics about what the update was actually meant to do.

During the outage, many shoppers found themselves unable to complete purchases with a Mastercard-issued credit card. ABC reports that some shoppers tried backup cards without luck, and were ultimately forced to leave their carts behind and head home for cash. By the time they returned, the outage had already cleared and payments were working normally again.

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According to Downdetector data, the outage left a clear mark on Saturday’s shopping activity. Reports of card issues climbed past 1,700 by 3 pm, then fell back to 173 a couple of hours later. Most complaints centered on fund transfers and mobile banking, though cash withdrawals and Apple Pay were affected, too.

Anyone living inside a digital, networked economy knows all too well how disruptive a systemic outage can be. Payment processors like Mastercard and Visa sit at the center of that infrastructure, and they’re routinely criticized for becoming unreliable at the exact moment people need them most.

In light of the infamous CrowdStrike incident a couple of years ago, banking organizations warned that total dependence on “digital money” and payment processors is a disaster waiting to happen. Another massive CrowdStrike-scale event could bring a cashless society to a standstill, they argued, which is why physical cash should still play a meaningful role in today’s economy.

This weekend’s Mastercard incident lends some weight to those warnings. In a worst-case scenario, the next global outage could carry far heavier consequences. And honestly, I’d almost forgotten what cash is even like.

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Microsoft MVP creates site to remind you of all the brands Redmond replaced

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If you’re still talking about ‘DirSync’ or ‘Active Directory’ instead of ‘Entra’, and need to explain why, this is the site for you

If you’re struggling to stay up to date with Redmond’s regular product re-branding exercises, here’s the site for you: The Microsoft Rebrand Registry.

Microsoft Most Valuable Professional (MVP) Loryan Strant created the site because he thinks it’s a valuable resource, and also in the hope it makes visitors “chuckle.”

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Readers may remember that Strant has also created the site Let Me Correct That For You, which lists the exact names of Microsoft products – an effort he told The Register he thinks is useful because Microsoft in its wisdom uses Camel Case for names like PowerPoint but went with conventional capitalization for Copilot.

Another of his sites immortalizes Microsoft cloud product logos. He’s also created HumbledandHonored.com, a site that generates social media posts MVPs can use to announce they have earned or retained Microsoft’s awards.

Strant told The Register that the Rebrand Registry came about after some banter between himself and other MVPs, during which the topic of Microsoft’s many product name changes came up. He decided to do something about it.

The site lists 72 Microsoft products and 158 names they’ve had over the years.

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It also includes some analysis of Microsoft’s branding, which sees a product’s name survive for an average of two years and eleven months.

The site lists eight products that have gone through three name changes:

·       Azure AI Search

·       Azure App Service

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·       Azure DevOps

·       Azure SQL Database

·       Foundry Tools

·       Microsoft 365 Copilot app

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·       Microsoft Configuration Manager

·       Microsoft Defender for Endpoint

Strant has even had a go at predicting which Microsoft products are likely to get a new name soon, by considering the amount of time the current name has applied, prior names, and the frequency with which Microsoft changes names of products in the same family.

That methodology led him to suggest an “elevated” likelihood of name changes for the Azure App Service, Azure SQL Database, Azure DevOps, and Microsoft Dynamics 365 Field Service.

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The site considers surviving products only, and Strant admits his analysis is therefore biased towards product Microsoft still publishes. He also pointed out that he’s not decided how to handle successor products, for example when Microsoft discontinued Skype for Business and put similar functions into Teams.

Strant said he created Let Me Correct That For You using WordPress, while his Microsoft logo library grew out of a OneDrive folder and relies on a GitHub repo.

For the Rebrand Registry, he used vibe coding tools.

“I have my own harness that lets me custom-build things,” he explained, adding that he rigorously validates data rather than relying on AI tools to get facts right.

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Strant said most of the feedback he gets about his sites is positive, either on LinkedIn or during face-to-face meetings at events. He’s heard that Microsoft people appreciate his efforts because Redmond hasn’t preserved the same data his sites record.

“I hope that people find them useful, and get a chuckle,” he said. ®

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Fostering trust in the age of misinformation, disinformation, and malinformation

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The reality for many organizations is that their employees are already being deceived. So, probably are their customers, their investors, and their board.

For years, the warnings have focused on the impact of deepfakes, such as fake CEOs on video calls, cloned voices authorizing payments, and fraudulent emails.

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This May Look Like Plastic Rods and a Hand Lever, But It’s Acutally a Digi-Comp 1 Mechanical Computer from 1963

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Digi-Comp 1 Mechanical Computer 1963
In 1963 a kit of red and white polystyrene plates, stiff metal rods, rubber bands, and short plastic tubes sold for $4.99 ($54.45 today) and assembled into a working digital computer. Three small windows on the front face displayed binary digits as either 0 or 1. A white lever marked “Clock” stuck out from the right side. Pushing that lever fully inward and then drawing it back out advanced every calculation by one step. No batteries or power cord were required. All motion came from the user’s hand and the tension stored in the rubber bands.



E.S.R. Inc., a small company founded by three engineers who originally intended to produce electronic computing equipment, release the kit as a side project to create quick cash. Instead of being a one-hit wonder, the Digi-Comp 1 sold out faster than anyone could keep up. Over 100,000 units were sold, with some estimating it could have been as many as 250,000. For a period, the number of Digi-Comp 1s was actually greater than the number of true electronic computers in use. At least in the middle of the 1960s. Eventually, the business chose to move its focus to more… traditional toys, and Digi-Comp 1 would remain in production for a little longer. It remained in production until the early 1970s.


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You assemble the device by slapping the base plate down and joining the upright supports in one seamless action, with no tools required. Then you add three horizontal bars that can move in any way because they can lock into either of two spots that you’d intuitively associate with binary 0 or binary 1, and those three bars may represent any number between 000 and 111, or, in more common terms, 0 to 7. Six thin rods now run along the front of the machine, with another six going along the back. Along the front, there are little tubes that you put onto tabs, and on the back, there are tubes that you fit onto the appropriate tabs. The arrangement of the back tubes dictates which rods can move and which cannot during a single clock cycle.

Digi-Comp 1 Mechanical Computer 1963
Now, the front rods serve as logic sensors, and depending on the condition of those three sliding bars, they will either drop or remain held up. The back rods are your actuators. So, if a rear rod swings free, it can push the bar from 0 to 1 or 1 to 0, as long as the right tube is in place. The rear rods with odd numbers reset to zero, while those with even numbers reset to one. Rubber bands keep the rods taut, allowing them to snap back into position as soon as an obstructing tube is relocated or a passage opens.

Digi-Comp 1 Mechanical Computer 1963
When you draw the lever all the way in and secure the logic rods, you complete a full clock cycle. Any rod that is not blocked by a front tube then connects to the corresponding rod on the back. Then, on the way back out, those free rear rods spring into action, shifting the sliding bars to whatever position is required by where you’ve placed the tubes. By the time the bars have set, the overall pattern of what is blocked and what is not has changed, making it ready for the next cycle. That’s all there is to it, because the machine’s current state totally controls its next state. In other words, it is a three-bit finite-state machine.

Digi-Comp 1 Mechanical Computer 1963
Users rummaged through the large instruction booklet to find tube arrangements that really worked. One fairly conventional configuration transformed the machine into a binary counter that counted up from 000 in a smooth, step-by-step manner, 000 to 001, then 010, 011, and so on all the way up to 111 until eventually counting down to 000 again. Other layouts became more fascinating, as you could combine two numbers, subtract one from another, move bits left or right, or just flip the entire value on its head. You could also use it for simple multiplication and comparisons. The kit featured a clever little plastic bit that allowed you to create “or” situations and solve some interesting challenges. People were able to encode games like Nim so that the machine would enforce the rules and vary the outcome depending on the starting position.

Digi-Comp 1 Mechanical Computer 1963
The results appeared immediately in the three front windows when the bars were clicked into place. The documentation that came with the tube layouts included not only the charts for how to set up the tubes, but also the fundamentals of binary counting and Boolean logic, all explained in a way that a 12-year-old could grasp. Many people who received a Digi-Comp 1 as a present later claimed that it was the first gadget to make abstract rules feel real and concrete. The tangible “click” of the bars moving and the rods shifting in front of you was extremely effective in demonstrating cause and consequence in a manner that a simple diagram cannot.

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New Lucid Gravity GT-S Hits 60 MPH in 3.1 Seconds, Seats 7

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American luxury EV builder Lucid Motors announced and unveiled the Lucid Gravity GT-S this weekend during Monterey Car Week in California. The new performance variant of the brand’s three-row electric SUV inherits the upgraded three-motor powertrain from the 1,070-horsepower Lucid Air Sapphire, seats up to seven and features a 3.1-second 0-60 sprint.

Lucid calls the new GT-S trim level “America’s most powerful three-row SUV,” backing up the claim with that stated 1,070 hp from the EV’s three-motor (one front, two rear) setup. That sort of oomph is enough to propel the SUV to 60 mph in just 3.1 seconds — a tick behind its sibling, the lighter Air Sapphire sedan’s 1.89-second blitz, but still an impressive feat for a luxury SUV with three rows for passengers and a large cargo capacity.

Lucid Gravity GT-S, rear view, parked near the waterfront
Lucid’s top-of-the-line Gravity shaves about a half-second off the Grand Touring model’s 0-60 time.

Amazingly, while the Gravity GT-S may be the most powerful vehicle in its class, it’s not the quickest. Rivian’s range-topping R1S Quad-Motor keeps pace with 1,025 hp and an estimated 2.6 seconds to 60 mph, though Edmunds’ instrumented testing clocked it closer to 3 seconds flat. Tesla’s Model X Plaid packs 1,020 hp and a Tesla-claimed 2.5-second run — the Falcon-doored three-row EV was recently discontinued, but new and low-mileage examples are still relatively easy to find. Drivers with a half-second more patience can also consider the Cadillac Vistiq, which gets the job done in its 3.7-second Velocity Max mode with only 615 ponies. The level of speed on offer for luxury EV buyers these days is, frankly, absurd.

In addition to straight-line acceleration, Lucid has also boosted the GT-S handling. The spec comes standard with the automaker’s Dynamic Handling Package, which includes an adaptive air suspension that automatically lowers the SUV for efficiency at speed and hunkers down during dynamic driving. Independent rear-wheel steering is also standard, boosting low-speed agility and high-speed stability.

Lucid estimates the focus shift to performance will cost the GT-S trim a bit of efficiency. Range is projected to drop to around 373 miles, versus the 450 miles of the Gravity Grand Touring trim level, though that estimate has not yet been confirmed by the EPA.

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Lucid Gravity interior detail showcasing black leather and blue contrast stitching
Like the Sapphire, the GT-S distinguishes itself with blue trim inside and out.Lucid Motors

Sapphire styling, inside and out

Along with the performance chops, the Gravity GT-S gets a Sapphire-inspired makeover inside and out. Exterior touches include blue accents and blue brake calipers, plus GT-S badging complete with a blue S that looks identical to the Sapphire’s branding.

Inside, the GT-S is upholstered in Lucid’s Mojave PurLuxe interior — a synthetic, animal-free leather alternative — finished with blue stitching and piping. Buyers who prefer real leather can opt for the Tahoe leather interior, which adds $1,300 to the bottom line. Either way, the blue theme carries through to the steering wheel and armrest stitching, plus blue seatbelts, a blue steering wheel badge, and blue embossing on the Lucid Bear headrest logos.

Close up of GT-S sport wheel with blue Lucid Bear logo and brake caliper.

This level of performance and luxury doesn’t come cheap. The Lucid Gravity GT-S will be available exclusively in the US, priced starting at an eye-watering $125,900, excluding tax, options and the $1,850 destination fees.

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